Procedure Composite Process List
Get a list of ProcedureComputation objects. ProcedureComputations have a 1:1 mapping with Observations where used.
These may have a number of 2 or more components made up of combinations of Computation and Acquisition records.
The details of the underlying records have been serialised.
### Available end points:
- `/ProcedureComputations/` - Will list all ProcedureComputations in the database
- `/ProcedureComputations.json` - Will return all ProcedureComputations in json format
- `/ProcedureComputations/<object_id>/` - Returns ProcedureComputations object with that id
### Available Methods:
- `GET`
- `HEAD`
### Available filters:
None
### How to use filters:
None
GET /api/v2/composites/?format=api&offset=300
{ "count": 662, "next": "https://api.catalogue.ceda.ac.uk/api/v2/composites/?format=api&limit=100&offset=400", "previous": "https://api.catalogue.ceda.ac.uk/api/v2/composites/?format=api&limit=100&offset=200", "results": [ { "ob_id": 14529, "computationComponent": [ { "ob_id": 14521, "uuid": "70aa606ca0584f4594588fc6d7842595", "title": "NAME dispersion model footprints", "abstract": "Atmospheric dispersion model footprints computed at the University of Leicester for various projects using the the Met Office's Numerical Atmospheric-dispersion Modelling Environment (NAME)", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 14528, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 5509, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/14527/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/99/?format=api", "relatedTo": { "ob_id": 14528, "uuid": "96ffb69542634508b8969ba111a733c6", "short_code": "acq" } }, { "ob_id": 5510, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/14527/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/83/?format=api", "relatedTo": { "ob_id": 14528, "uuid": "96ffb69542634508b8969ba111a733c6", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [] }, { "ob_id": 14538, "computationComponent": [ { "ob_id": 14521, "uuid": "70aa606ca0584f4594588fc6d7842595", "title": "NAME dispersion model footprints", "abstract": "Atmospheric dispersion model footprints computed at the University of Leicester for various projects using the the Met Office's Numerical Atmospheric-dispersion Modelling Environment (NAME)", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 14534, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 5520, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/14527/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/12831/?format=api", "relatedTo": { "ob_id": 14534, "uuid": "84c1506ac5c34092a7cbfaac748b390d", "short_code": "acq" } }, { "ob_id": 5521, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/14527/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/3165/?format=api", "relatedTo": { "ob_id": 14534, "uuid": "84c1506ac5c34092a7cbfaac748b390d", "short_code": "acq" } }, { "ob_id": 5522, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/14527/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/11230/?format=api", "relatedTo": { "ob_id": 14534, "uuid": "84c1506ac5c34092a7cbfaac748b390d", "short_code": "acq" } }, { "ob_id": 5523, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/14527/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/11731/?format=api", "relatedTo": { "ob_id": 14534, "uuid": "84c1506ac5c34092a7cbfaac748b390d", "short_code": "acq" } }, { "ob_id": 5524, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/14527/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/196/?format=api", "relatedTo": { "ob_id": 14534, "uuid": "84c1506ac5c34092a7cbfaac748b390d", "short_code": "acq" } }, { "ob_id": 5525, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/14527/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/811/?format=api", "relatedTo": { "ob_id": 14534, "uuid": "84c1506ac5c34092a7cbfaac748b390d", "short_code": "acq" } }, { "ob_id": 5526, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/14527/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/807/?format=api", "relatedTo": { "ob_id": 14534, "uuid": "84c1506ac5c34092a7cbfaac748b390d", "short_code": "acq" } }, { "ob_id": 5527, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/14527/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/11723/?format=api", "relatedTo": { "ob_id": 14534, "uuid": "84c1506ac5c34092a7cbfaac748b390d", "short_code": "acq" } }, { "ob_id": 5528, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/14527/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/13069/?format=api", "relatedTo": { "ob_id": 14534, "uuid": "84c1506ac5c34092a7cbfaac748b390d", "short_code": "acq" } }, { "ob_id": 5529, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/14527/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/14537/?format=api", "relatedTo": { "ob_id": 14534, "uuid": "84c1506ac5c34092a7cbfaac748b390d", "short_code": "acq" } }, { "ob_id": 5511, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/14527/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/14532/?format=api", "relatedTo": { "ob_id": 14534, "uuid": "84c1506ac5c34092a7cbfaac748b390d", "short_code": "acq" } }, { "ob_id": 5512, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/14527/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/14533/?format=api", "relatedTo": { "ob_id": 14534, "uuid": "84c1506ac5c34092a7cbfaac748b390d", "short_code": "acq" } }, { "ob_id": 5513, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/14527/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/315/?format=api", "relatedTo": { "ob_id": 14534, "uuid": "84c1506ac5c34092a7cbfaac748b390d", "short_code": "acq" } }, { "ob_id": 5514, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/14527/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/311/?format=api", "relatedTo": { "ob_id": 14534, "uuid": "84c1506ac5c34092a7cbfaac748b390d", "short_code": "acq" } }, { "ob_id": 5515, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/14527/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/3126/?format=api", "relatedTo": { "ob_id": 14534, "uuid": "84c1506ac5c34092a7cbfaac748b390d", "short_code": "acq" } }, { "ob_id": 5516, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/14527/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/3110/?format=api", "relatedTo": { "ob_id": 14534, "uuid": "84c1506ac5c34092a7cbfaac748b390d", "short_code": "acq" } }, { "ob_id": 5517, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/14527/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/11751/?format=api", "relatedTo": { "ob_id": 14534, "uuid": "84c1506ac5c34092a7cbfaac748b390d", "short_code": "acq" } }, { "ob_id": 5518, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/14527/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/14535/?format=api", "relatedTo": { "ob_id": 14534, "uuid": "84c1506ac5c34092a7cbfaac748b390d", "short_code": "acq" } }, { "ob_id": 5519, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/14527/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/14536/?format=api", "relatedTo": { "ob_id": 14534, "uuid": "84c1506ac5c34092a7cbfaac748b390d", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [] }, { "ob_id": 14545, "computationComponent": [ { "ob_id": 14521, "uuid": "70aa606ca0584f4594588fc6d7842595", "title": "NAME dispersion model footprints", "abstract": "Atmospheric dispersion model footprints computed at the University of Leicester for various projects using the the Met Office's Numerical Atmospheric-dispersion Modelling Environment (NAME)", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 14540, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 5539, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/14527/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/12831/?format=api", "relatedTo": { "ob_id": 14540, "uuid": "508a5328da23404e9d242ed18f62dc47", "short_code": "acq" } }, { "ob_id": 5531, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/14527/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/13069/?format=api", "relatedTo": { "ob_id": 14540, "uuid": "508a5328da23404e9d242ed18f62dc47", "short_code": "acq" } }, { "ob_id": 5536, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/14527/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/11731/?format=api", "relatedTo": { "ob_id": 14540, "uuid": "508a5328da23404e9d242ed18f62dc47", "short_code": "acq" } }, { "ob_id": 5532, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/14527/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/11723/?format=api", "relatedTo": { "ob_id": 14540, "uuid": "508a5328da23404e9d242ed18f62dc47", "short_code": "acq" } }, { "ob_id": 5530, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/14527/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/14537/?format=api", "relatedTo": { "ob_id": 14540, "uuid": "508a5328da23404e9d242ed18f62dc47", "short_code": "acq" } }, { "ob_id": 5533, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/14527/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/807/?format=api", "relatedTo": { "ob_id": 14540, "uuid": "508a5328da23404e9d242ed18f62dc47", "short_code": "acq" } }, { "ob_id": 5534, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/14527/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/811/?format=api", "relatedTo": { "ob_id": 14540, "uuid": "508a5328da23404e9d242ed18f62dc47", "short_code": "acq" } }, { "ob_id": 5537, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/14527/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/11230/?format=api", "relatedTo": { "ob_id": 14540, "uuid": "508a5328da23404e9d242ed18f62dc47", "short_code": "acq" } }, { "ob_id": 5535, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/14527/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/196/?format=api", "relatedTo": { "ob_id": 14540, "uuid": "508a5328da23404e9d242ed18f62dc47", "short_code": "acq" } }, { "ob_id": 5543, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/14527/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/3110/?format=api", "relatedTo": { "ob_id": 14540, "uuid": "508a5328da23404e9d242ed18f62dc47", "short_code": "acq" } }, { "ob_id": 5538, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/14527/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/3165/?format=api", "relatedTo": { "ob_id": 14540, "uuid": "508a5328da23404e9d242ed18f62dc47", "short_code": "acq" } }, { "ob_id": 5542, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/14527/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/11751/?format=api", "relatedTo": { "ob_id": 14540, "uuid": "508a5328da23404e9d242ed18f62dc47", "short_code": "acq" } }, { "ob_id": 5540, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/14527/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/14536/?format=api", "relatedTo": { "ob_id": 14540, "uuid": "508a5328da23404e9d242ed18f62dc47", "short_code": "acq" } }, { "ob_id": 5541, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/14527/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/14535/?format=api", "relatedTo": { "ob_id": 14540, "uuid": "508a5328da23404e9d242ed18f62dc47", "short_code": "acq" } }, { "ob_id": 5544, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/14527/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/3126/?format=api", "relatedTo": { "ob_id": 14540, "uuid": "508a5328da23404e9d242ed18f62dc47", "short_code": "acq" } }, { "ob_id": 5545, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/14527/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/311/?format=api", "relatedTo": { "ob_id": 14540, "uuid": "508a5328da23404e9d242ed18f62dc47", "short_code": "acq" } }, { "ob_id": 5546, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/14527/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/315/?format=api", "relatedTo": { "ob_id": 14540, "uuid": "508a5328da23404e9d242ed18f62dc47", "short_code": "acq" } }, { "ob_id": 5547, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/14527/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/14533/?format=api", "relatedTo": { "ob_id": 14540, "uuid": "508a5328da23404e9d242ed18f62dc47", "short_code": "acq" } }, { "ob_id": 5548, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/14527/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/14532/?format=api", "relatedTo": { "ob_id": 14540, "uuid": "508a5328da23404e9d242ed18f62dc47", "short_code": "acq" } }, { "ob_id": 5549, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/14542/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/11751/?format=api", "relatedTo": { "ob_id": 14540, "uuid": "508a5328da23404e9d242ed18f62dc47", "short_code": "acq" } }, { "ob_id": 5550, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/14543/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/11731/?format=api", "relatedTo": { "ob_id": 14540, "uuid": "508a5328da23404e9d242ed18f62dc47", "short_code": "acq" } }, { "ob_id": 5551, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/14542/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/11731/?format=api", "relatedTo": { "ob_id": 14540, "uuid": "508a5328da23404e9d242ed18f62dc47", "short_code": "acq" } }, { "ob_id": 5552, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/14527/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/111/?format=api", "relatedTo": { "ob_id": 14540, "uuid": "508a5328da23404e9d242ed18f62dc47", "short_code": "acq" } }, { "ob_id": 5553, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/14542/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/14544/?format=api", "relatedTo": { "ob_id": 14540, "uuid": "508a5328da23404e9d242ed18f62dc47", "short_code": "acq" } }, { "ob_id": 5554, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/14542/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/11726/?format=api", "relatedTo": { "ob_id": 14540, "uuid": "508a5328da23404e9d242ed18f62dc47", "short_code": "acq" } }, { "ob_id": 12652, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/14527/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/14270/?format=api", "relatedTo": { "ob_id": 14540, "uuid": "508a5328da23404e9d242ed18f62dc47", "short_code": "acq" } }, { "ob_id": 12653, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/14542/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/33332/?format=api", "relatedTo": { "ob_id": 14540, "uuid": "508a5328da23404e9d242ed18f62dc47", "short_code": "acq" } }, { "ob_id": 12654, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/14542/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/33335/?format=api", "relatedTo": { "ob_id": 14540, "uuid": "508a5328da23404e9d242ed18f62dc47", "short_code": "acq" } }, { "ob_id": 12655, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/33337/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/14532/?format=api", "relatedTo": { "ob_id": 14540, "uuid": "508a5328da23404e9d242ed18f62dc47", "short_code": "acq" } }, { "ob_id": 12656, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/33338/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/14532/?format=api", "relatedTo": { "ob_id": 14540, "uuid": "508a5328da23404e9d242ed18f62dc47", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/148881/?format=api" ] }, { "ob_id": 14588, "computationComponent": [ { "ob_id": 14615, "uuid": "1c75f914814545e68231638b42dd60f0", "title": "Volcanic Ash Product Meteosat Second Generation 2 (MSG-2) or METEOSAT-9", "abstract": "Volcanic Ash Product derived from Meteosat Second Generation 2 (MSG-2) or METEOSAT-9.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 14587, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 5570, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/2658/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/3847/?format=api", "relatedTo": { "ob_id": 14587, "uuid": "9d75bba2f78f4c65bafab61d08e7ec14", "short_code": "acq" } }, { "ob_id": 5571, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/2658/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/2659/?format=api", "relatedTo": { "ob_id": 14587, "uuid": "9d75bba2f78f4c65bafab61d08e7ec14", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/56568/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/56567/?format=api" ] }, { "ob_id": 14617, "computationComponent": [ { "ob_id": 14616, "uuid": "53e81259174b4cd981826a14a8bd923e", "title": "Snow Detection Products Meteosat Second Generation 2 (MSG-2) or METEOSAT-9", "abstract": "Snow Detection Products derived from Meteosat Second Generation 2 (MSG-2) or METEOSAT-9.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 14587, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 5570, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/2658/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/3847/?format=api", "relatedTo": { "ob_id": 14587, "uuid": "9d75bba2f78f4c65bafab61d08e7ec14", "short_code": "acq" } }, { "ob_id": 5571, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/2658/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/2659/?format=api", "relatedTo": { "ob_id": 14587, "uuid": "9d75bba2f78f4c65bafab61d08e7ec14", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/56677/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/56678/?format=api" ] }, { "ob_id": 14621, "computationComponent": [ { "ob_id": 14620, "uuid": "4271cba420254cfd8c366c1239afa826", "title": "Latest Fog Products Meteosat Second Generation 2 (MSG-2) or METEOSAT-9", "abstract": "Latest Fog Products derived from Meteosat Second Generation 2 (MSG-2) or METEOSAT-9.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 14587, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 5570, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/2658/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/3847/?format=api", "relatedTo": { "ob_id": 14587, "uuid": "9d75bba2f78f4c65bafab61d08e7ec14", "short_code": "acq" } }, { "ob_id": 5571, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/2658/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/2659/?format=api", "relatedTo": { "ob_id": 14587, "uuid": "9d75bba2f78f4c65bafab61d08e7ec14", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/56690/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/56691/?format=api" ] }, { "ob_id": 14627, "computationComponent": [ { "ob_id": 14626, "uuid": "f476449646a444fd8568d00705c1da9d", "title": "Cloud top height and temperature Products Meteosat Second Generation 2 (MSG-2) or METEOSAT-9", "abstract": "Cloud top height and temperature derived from Meteosat Second Generation 2 (MSG-2) or METEOSAT-9.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 14587, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 5570, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/2658/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/3847/?format=api", "relatedTo": { "ob_id": 14587, "uuid": "9d75bba2f78f4c65bafab61d08e7ec14", "short_code": "acq" } }, { "ob_id": 5571, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/2658/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/2659/?format=api", "relatedTo": { "ob_id": 14587, "uuid": "9d75bba2f78f4c65bafab61d08e7ec14", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/56710/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/56711/?format=api" ] }, { "ob_id": 14637, "computationComponent": [ { "ob_id": 14636, "uuid": "e81e8a74308a478598a8e8229a59e803", "title": "Infra red Products Meteosat Second Generation 2 (MSG-2) or METEOSAT-9", "abstract": "Infra red images derived from Meteosat Second Generation 2 (MSG-2) or METEOSAT-9.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 14587, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 5570, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/2658/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/3847/?format=api", "relatedTo": { "ob_id": 14587, "uuid": "9d75bba2f78f4c65bafab61d08e7ec14", "short_code": "acq" } }, { "ob_id": 5571, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/2658/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/2659/?format=api", "relatedTo": { "ob_id": 14587, "uuid": "9d75bba2f78f4c65bafab61d08e7ec14", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/56746/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/56747/?format=api" ] }, { "ob_id": 14690, "computationComponent": [ { "ob_id": 14689, "uuid": "ce5c511a1f204e0eab83e7c4b5669cd0", "title": "Visible imagery Products Meteosat Second Generation 2 (MSG-2) or METEOSAT-9", "abstract": "Visible imagery images derived from Meteosat Second Generation 2 (MSG-2) or METEOSAT-9.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 14587, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 5570, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/2658/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/3847/?format=api", "relatedTo": { "ob_id": 14587, "uuid": "9d75bba2f78f4c65bafab61d08e7ec14", "short_code": "acq" } }, { "ob_id": 5571, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/2658/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/2659/?format=api", "relatedTo": { "ob_id": 14587, "uuid": "9d75bba2f78f4c65bafab61d08e7ec14", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/56959/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/56958/?format=api" ] }, { "ob_id": 14733, "computationComponent": [ { "ob_id": 14732, "uuid": "ba4c9c7b40f94264a15dae6a9cbca977", "title": "Water Vapour imagery Products Meteosat Second Generation 2 (MSG-2) or METEOSAT-9", "abstract": "Water Vapour images derived from Meteosat Second Generation 2 (MSG-2) or METEOSAT-9.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 14587, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 5570, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/2658/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/3847/?format=api", "relatedTo": { "ob_id": 14587, "uuid": "9d75bba2f78f4c65bafab61d08e7ec14", "short_code": "acq" } }, { "ob_id": 5571, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/2658/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/2659/?format=api", "relatedTo": { "ob_id": 14587, "uuid": "9d75bba2f78f4c65bafab61d08e7ec14", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/57122/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/57123/?format=api" ] }, { "ob_id": 14768, "computationComponent": [ { "ob_id": 14636, "uuid": "e81e8a74308a478598a8e8229a59e803", "title": "Infra red Products Meteosat Second Generation 2 (MSG-2) or METEOSAT-9", "abstract": "Infra red images derived from Meteosat Second Generation 2 (MSG-2) or METEOSAT-9.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 14689, "uuid": "ce5c511a1f204e0eab83e7c4b5669cd0", "title": "Visible imagery Products Meteosat Second Generation 2 (MSG-2) or METEOSAT-9", "abstract": "Visible imagery images derived from Meteosat Second Generation 2 (MSG-2) or METEOSAT-9.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 14732, "uuid": "ba4c9c7b40f94264a15dae6a9cbca977", "title": "Water Vapour imagery Products Meteosat Second Generation 2 (MSG-2) or METEOSAT-9", "abstract": "Water Vapour images derived from Meteosat Second Generation 2 (MSG-2) or METEOSAT-9.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 14587, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 5570, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/2658/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/3847/?format=api", "relatedTo": { "ob_id": 14587, "uuid": "9d75bba2f78f4c65bafab61d08e7ec14", "short_code": "acq" } }, { "ob_id": 5571, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/2658/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/2659/?format=api", "relatedTo": { "ob_id": 14587, "uuid": "9d75bba2f78f4c65bafab61d08e7ec14", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/57342/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/57343/?format=api" ] }, { "ob_id": 19012, "computationComponent": [], "acquisitionComponent": [ { "ob_id": 14895, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 5598, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/51/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/61/?format=api", "relatedTo": { "ob_id": 14895, "uuid": "8bab98c5f0284ea186729867012f05e4", "short_code": "acq" } }, { "ob_id": 5599, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/51/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/99/?format=api", "relatedTo": { "ob_id": 14895, "uuid": "8bab98c5f0284ea186729867012f05e4", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/71540/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/71541/?format=api" ] }, { "ob_id": 19018, "computationComponent": [ { "ob_id": 19014, "uuid": "861c003fc43442dabb62ad72ee604c88", "title": "Computation Component: Level 1B processing algorithm applied to Sentinel 3 SRAL raw data.", "abstract": "This computation involves the Level 1 processing algorithm applied to raw Synthetic Aperture Radar Altimeter (SRAL) data. \r\n\r\nThe main algorithms of the Level-1 SAR_Ku chain are:\r\n\r\nDetermine surface type -\r\n\r\nThis algorithm computes the surface type (\"open ocean or semi-enclosed seas\", \"enclosed seas or lakes\", \"continental ice\" or \"land\") determining the position of a \"land-sea mask\" Auxiliary Data File nearest to the geolocated measurement. The latitude and longitude resolution of this land-sea mask is 2 minutes.\r\n\r\nCompute tracker ranges corrected for USO frequency drift -\r\n\r\nThis algorithm computes the USO correction from an Auxiliary Data File called \"USO file\" and this correction is applied to the tracker range. The \"USO file\" provides the real USO frequency drift measured on-board wrt the USO frequency nominal value. This algorithm also computes the tracker range rate converted into distance versus time.\r\n\r\nCompute tracker ranges corrected for internal path correction -\r\n\r\nThis algorithm computes the internal path correction from an Auxiliary Data File called \"CAL1 LTM file\" and this correction is applied to the tracker range. The \"CAL1 LTM file\" provides the internal path delay measured on-board thanks to the CAL1 calibration mode, which measures the difference of travel between the transmission and the reference lines within the altimeter. This algorithm also computes and applies the instrumental delay correction measured on-ground, due to the distance between the duplexer and the antenna reference point.\r\n\r\nCorrect the AGC for instrumental errors -\r\n\r\nThis algorithm computes the Automatic Gain Control (AGC) instrumental correction and applies this correction to the AGC. The AGC instrumental correction is computed taking into account the real gain value applied on-board and stored as a matrix table on an Auxiliary Data File called \"characterisation file\".\r\n\r\nCorrect and apply power & phase corrections -\r\n\r\nThis algorithm computes and applies to each burst the phase and power variations within all the echoes of every burst. These phase and power corrections are measured on-board through a sequence of calibration echoes in CAL1 calibration mode.\r\n\r\nCorrect the waveforms -\r\n\r\nOn-board, there is a calibration mode called CAL2 that is able to compute the Gain Profile Range Window (GPRW) that provides the information of the attenuation of the samples of the Level . The GPRW accounts for several instrumental effects (e.g. intermediate frequency filters gain response) that have an impact on the Level 0 waveforms power. This algorithm corrects these Level-0 waveforms by the GPRW instrumental effects.\r\n\r\nCompute surface locations -\r\n\r\nIn the SAR_Ku processing chain, the output measurements are referenced to surface locations along the satellite track. These surface locations correspond with the intersection of the Doppler beams with an estimation of the surface elevations. These surface locations are used along all L1 SAR_Ku processing.\r\n\r\nDetermine Doppler beams direction -\r\n\r\nThis algorithm determines the angular spacing between the instantaneous zero Doppler plane and the lines defined by the burst centre and the reference surface locations \"observed\" within the burst sequence.\r\n\r\nDoppler beams generation -\r\n\r\nThis algorithm generates the Doppler beams in the frequency domain. Each burst of pulse-limited time-domain echoes are transformed into the frequency domain using an FFT (Fast Fourier Transform) in the along-track direction.\r\n\r\nCompute and apply Doppler correction -\r\n\r\nThis algorithm computes and applied the Doppler correction to the tracker ranges. This correction is needed to remove the echoes frequency shifts due to sensor-target velocity. The Doppler correction is computed and applied in the frequency domain to each Doppler beam. This correction is a function of the emitted frequency, the pulse emitted duration, the satellite velocity of the beams, the emitted bandwidth, and the sign of the slope of the transmitted chirp.\r\n\r\nCompute and apply slant range corrections - \r\n\r\nThis algorithm computes the slant corrections (both fine and coarse) that correct the range migration due to the motion of the sensor along the orbit.\r\n\r\nRange compression - \r\n\r\nThis algorithm performs a range compression of the waveform that is the conversion of each Doppler processed burst of pulse-width time-domain echoes to the frequency domain.\r\n\r\nTracker alignment correction - \r\n\r\nThis algorithm corrects the azimuth processed echo stack for on-board tracker variation. It means that for each surface location, the waveforms are aligned before multi-looking.\r\n\r\nDoppler beams stack & multi-looking - \r\n\r\nThis algorithm computes the stacked Doppler beams (I2+Q2 power waveforms) through the non-coherent summation of all the beams corresponding to each surface location.\r\n\r\nCompute sigma0 scaling factor - \r\n\r\nThis algorithm computes the sigma0 scaling factor that is used at Level2 to determine the backscatter coefficients from the retracked amplitudes. The sigma0 scaling factor accounts for all power attenuations and gains which have an impact on the signal received on-board.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 19015, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 10047, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/19017/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/19016/?format=api", "relatedTo": { "ob_id": 19015, "uuid": "1c1605795ae247c28a64d003c686bdb2", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/71551/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/71550/?format=api" ] }, { "ob_id": 19026, "computationComponent": [ { "ob_id": 19029, "uuid": "68e7fd451fd848ecb0b6e53dfd68ae4a", "title": "Level 1 processing algorithm applied to Sentinel 3 Ocean and Land Colour Instrument (OLCI) raw data", "abstract": "This computation involves the Level 1 processing algorithm applied to raw Ocean and Land Colour Instrument (OLCI) data. This product consists of the physical measurements from the instrument. These are Top Of Atmosphere (TOA) radiances, calibrated to geophysical units (W.m-2. sr-1 µm-1), georeferenced onto the Earth's surface, spatially resampled onto an evenly spaced grid, and annotated with illumination and observation geometry, environment data (meteorological data) and quality and classification flags.\r\nThe product is available at two spatial resolutions: full resolution and reduced resolution.\r\n\r\nThe processing involves the following steps:\r\n\r\n1. Data extraction and quality checks.\r\n2. Radiometric scaling.\r\n3. Stray light correction.\r\n4. Georeferencing.\r\n5. Pixel classification functions.\r\n6. Spatial re-sampling.\r\n7. Product formatting (into the two spatial resolutions)\r\n\r\nFor more information please see the OLCI user guide in the docs tab.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 19028, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 10049, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/19017/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/19027/?format=api", "relatedTo": { "ob_id": 19028, "uuid": "4b9669233ac644fa853788607d6ca1b2", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/71610/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/182463/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/71611/?format=api" ] }, { "ob_id": 19035, "computationComponent": [ { "ob_id": 19034, "uuid": "255d30cc4ffd418fa31919f1c08db266", "title": "Level 2 processing algorithm applied to Sentinel 3 Sea and Land Surface Temperature Radiometer (SLSTR) raw data", "abstract": "This computation involves the Level 2 processing algorithm applied to raw Sea and Land Surface Temperature Radiometer (SLSTR) data. MORE INFORMATION TO FOLLOW", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 19031, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 10051, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/19017/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/19032/?format=api", "relatedTo": { "ob_id": 19031, "uuid": "af8ab2c193c64a119d4be3f2fb9a3c36", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/71639/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/71640/?format=api" ] }, { "ob_id": 19038, "computationComponent": [ { "ob_id": 19040, "uuid": "826fb42295b4469c95b0fd6573aec1c8", "title": "Level 1 processing algorithm applied to Sentinel 3 Sea and Land Surface Temperature Radiometer (SLSTR) raw data", "abstract": "This computation involves the Level 1 processing algorithm applied to raw Sea and Land Surface Temperature Radiometer (SLSTR) data. Level 1 processing uses Level-0 products to compute radiometric measurements for each SLSTR channel in both views. This includes radiometric calibration for thermal and solar channels, several tests concerning surface and cloud flagging, and the determination of pixels' properties such as day/night, position in the instrument grid or geographical position.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 19031, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 10051, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/19017/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/19032/?format=api", "relatedTo": { "ob_id": 19031, "uuid": "af8ab2c193c64a119d4be3f2fb9a3c36", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/71652/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/71653/?format=api" ] }, { "ob_id": 19058, "computationComponent": [ { "ob_id": 5549, "uuid": "399f7c2982f748f1a2568d6f4b2f53eb", "title": "CCSR/NIES Global Circulation Model deployed on Centre for Climate System Research / National Institude for Environmental Studies (Japan) computer", "abstract": "This computation involved: CCSR/NIES Global Circulation Model deployed on Centre for Climate System Research / National Institude for Environmental Studies (Japan) computer.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/3641/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/3642/?format=api" ] }, { "ob_id": 7452, "uuid": "10c5108e23554417a30bf69733c6e4d1", "title": "Hadley Centre Coupled Model 3 (HadCM3) deployed on unknown computer", "abstract": "This computation involved: Hadley Centre Coupled Model 3 (HadCM3).", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 11069, "uuid": "a54087147ce34dfa859f9a35f4e1fd7a", "title": "GFDL-CM2.1 Global Coupled Climate Model deployed on Geophysical Fluid Dynamics Laboratory (USA) computing facility", "abstract": "This computation involved: GFDL-CM2.1 Global Coupled Climate Model deployed on Geophysical Fluid Dynamics Laboratory (USA) computing facility.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7396/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7397/?format=api" ] }, { "ob_id": 11078, "uuid": "d89de4fe539f43ac96b5c9a50f213898", "title": "ECHAM5 general circulation atmospheric model deployed on Max Planck Institute für Meteorologie computing facility", "abstract": "This computation involved: ECHAM5 general circulation atmospheric model deployed on Max Planck Institute für Meteorologie computing facility. It is a computer-Fortan95 stand-alone general circulation atmospheric model (GCAM). The model can also run as part of a coupled atmosphere ocean GCM, or in assimilation mode by linear relaxation (nudging). This model is developed by the Max Planck Institute for Meteorology, one of the research organisations of the Max Planck Society. The model was given its name as a combination of its origin (the 'EC' being short for 'ECMWF') and the place of development of its parametrisation package, Hamburg. Model MPI-ECHAM4 (1996) is the fourth in a series of models developed at MPI that originally derive from cycle 17 of the European Centre for Medium-Range Weather Forecasts (ECMWF) model. The ECHAM4 model's immediate predecessor is AMIP baseline model MPI ECHAM3 (1992). ECHAM5 is currently the most recent version of the ECHAM model. Compared to its predecessor, ECHAM4, it is more portable and because of both major and minor changes to the different parts of code that it uses, it produces a significantly different simulated climate.\r\nECHAM5 hosts sub-models going beyond the usual meteorological processes of a GCM as, Interception of snow by the canopy, heat budget of the soil, lake mode, .orbital variations, Sedimentation and cloud microphysics, etc.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7405/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7406/?format=api" ] }, { "ob_id": 11237, "uuid": "f4f7db7abe4b46bc97d890d2cd596dce", "title": "MRI-CGCM2.3.2 Meteorological Research Institute Coupled Global Circulation Model deployed on Meteorological Research Institute (Japan) computer", "abstract": "This computation involved: MRI-CGCM2.3.2 Meteorological Research Institute Coupled Global Circulation Model deployed on Meteorological Research Institute (Japan) computer.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7486/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7487/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7488/?format=api" ] }, { "ob_id": 11296, "uuid": "c2bd8550d8244c5194bae57694a604ae", "title": "BCCR-BCM2.0 Bergen Climate Model Version 2 deployed on Bjerknes Centre for Climate Research (Norway) Computer", "abstract": "This computation involved: BCCR-BCM2.0 Bergen Climate Model Version 2 deployed on Bjerknes Centre for Climate Research (Norway) Computer.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7517/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7518/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7519/?format=api" ] }, { "ob_id": 11332, "uuid": "2157135ec9df4585b5149e09477eba69", "title": "GISS-AOM Atmosphere Ocean Model deployed on NASA Goddard Institute for Space Studies (GISS) (USA) computer", "abstract": "This computation involved: GISS-AOM Atmosphere Ocean Model deployed on NASA Goddard Institute for Space Studies (GISS) (USA) computer.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7533/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7534/?format=api" ] }, { "ob_id": 11354, "uuid": "3672b23aa71b465ea49afbc2d9fac6e7", "title": "GFDL-CM2.0 Global Coupled Climate Model deployed on Geophysical Fluid Dynamics Laboratory (USA) computing facility", "abstract": "This computation involved: GFDL-CM2.0 Global Coupled Climate Model deployed on Geophysical Fluid Dynamics Laboratory (USA) computing facility.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7548/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7549/?format=api" ] }, { "ob_id": 11360, "uuid": "242f8485857e43db87352eee07bda1e3", "title": "CGCM3.1 Canadian Global Coupled Model Version 3.1 deployed on Canadian Centre for Climate Modelling and Analysis computing facility", "abstract": "This computation involved: CGCM3.1 Canadian Global Coupled Model Version 3.1 deployed on Canadian Centre for Climate Modelling and Analysis computing facility.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7552/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7553/?format=api" ] }, { "ob_id": 11420, "uuid": "873cc8a375d245d28dad362a4cf8abda", "title": "GISS-ModelE/HYCOM Coupled Atmosphere Ocean Model deployed on NASA Goddard Institute for Space Studies (GISS) (USA) computer", "abstract": "This computation involved: GISS-ModelE/HYCOM Coupled Atmosphere Ocean Model deployed on NASA Goddard Institute for Space Studies (GISS) (USA) computer.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7586/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7587/?format=api" ] }, { "ob_id": 11426, "uuid": "0b1dbbb59d8a4d01b10aeeaac96dd81a", "title": "GISS-ModelE/Russell Coupled Atmosphere Ocean Model deployed on NASA Goddard Institute for Space Studies (GISS) (USA) computer", "abstract": "This computation involved: GISS-ModelE/Russell Coupled Atmosphere Ocean Model deployed on NASA Goddard Institute for Space Studies (GISS) (USA) computer.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7591/?format=api" ] }, { "ob_id": 11490, "uuid": "7f66241fddd04a57b4c0e286dfeae21f", "title": "CNRM-CM3 Centre National de Recherches Météorologiques Coupled Model Version 3 deployed on Météo-France/Centre National de Recherches Météorologiques (France) computer", "abstract": "This computation involved: CNRM-CM3 Centre National de Recherches Météorologiques Coupled Model Version 3 deployed on Météo-France/Centre National de Recherches Météorologiques (France) computer.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7616/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7617/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7618/?format=api" ] }, { "ob_id": 11493, "uuid": "0852f5355de045d38dbd550104ed34cf", "title": "INM-CM3.0 Institute for Numerical Mathematics Coupled Model Version 3.0 deployed on Institute for Numerical Mathematics (Russia) computer", "abstract": "This computation involved: INM-CM3.0 Institute for Numerical Mathematics Coupled Model Version 3.0 deployed on Institute for Numerical Mathematics (Russia) computer.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7620/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7621/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7622/?format=api" ] }, { "ob_id": 11523, "uuid": "e84beffe4fa640249df4a4412590070d", "title": "NCAR-PCM Parallel Climate Model deployed on National Centre for Atmospheric Research (USA) computing facility", "abstract": "This computation involved: NCAR-PCM Parallel Climate Model deployed on National Centre for Atmospheric Research (USA) computing facility.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7642/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7643/?format=api" ] }, { "ob_id": 11728, "uuid": "15ceee46510a0a5b8aea10d03a93e6cf", "title": "CSIRO-mk30 deployed on unknown computer", "abstract": "This computation involved: CSIRO-mk30. \n\nEmpty content", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7699/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7700/?format=api" ] }, { "ob_id": 11739, "uuid": "5e85fd62a49c1a728593d8f4a6036de8", "title": "ncare-ccsm30 deployed on unknown computer", "abstract": "This computation involved: ncare-ccsm30. \n\nEmpty content", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7720/?format=api" ] }, { "ob_id": 11876, "uuid": "4dcabe9b70db4ed8b9e3460767d7068b", "title": "Hadley Centre Global Environmental Model version 1a (HadGEM1a) deployed on unknown computer", "abstract": "This computation involved: Hadley Centre Global Environmental Model version 1a (HadGEM1a). The HadGEM1a model builds on the IPCC AR4 version of HadGEM1 and includes various small improvements to the science and fixing of known problems.\n\nThe main advances from HadGEM1 are 1) Improved tropical biases and ENSO 2) Reduced continental warm dry bias 3) Improved aerosols", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7954/?format=api" ] }, { "ob_id": 13391, "uuid": "49e6741a6645410080dad9c859cc85f5", "title": "CSIRO-Mk3.5 Global Circulation Model deployed on Commonwealth Scientific and Industrial Research Organisation computing facility", "abstract": "This computation involved: CSIRO-Mk3.5 Global Circulation Model deployed on Commonwealth Scientific and Industrial Research Organisation computing facility.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 19052, "uuid": "c86f9d26bbcd4849a52a71d46afe354f", "title": "Institut Pierre‐Simon Laplace IPSL‐CM4 model", "abstract": "Institut Pierre‐Simon Laplace IPSL‐CM4 model", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 19053, "uuid": "975e8911ec4f45d781d20116285781d4", "title": "Commonwealth Scientific and Industrial Research Organisation in collaboration with the Queensland Climate Change Centre of Excellence CSIRO‐Mk3‐6‐0 model", "abstract": "Commonwealth Scientific and Industrial Research Organisation in collaboration with the Queensland Climate Change Centre of Excellence CSIRO‐Mk3‐6‐0 model ", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [], "identifier_set": [], "responsiblepartyinfo_set": [] }, { "ob_id": 19061, "computationComponent": [ { "ob_id": 5539, "uuid": "4f4c586a22dc49f98a38359660c8d711", "title": "ECHAM4 ocean coupled general circulation model deployed on Max Planck Institute für Meteorologie computing facility", "abstract": "This computation involved: ECHAM4 ocean coupled general circulation model deployed on Max Planck Institute für Meteorologie computing facility.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/3631/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/3632/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/3633/?format=api" ] }, { "ob_id": 5544, "uuid": "d1b14400d2714f1a90acd1cdfd1bbfda", "title": "CSIRO-Mk2 Global Circulation Model deployed on Commonwealth Scientific and Industrial Research Organisation computing facility", "abstract": "This computation involved: CSIRO-Mk2 Global Circulation Model deployed on Commonwealth Scientific and Industrial Research Organisation computing facility.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/3636/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/3637/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/3638/?format=api" ] }, { "ob_id": 5552, "uuid": "98b7d6d6d60e489d95122b900111aad3", "title": "CGCM2 Canadian Global Coupled Model Version 2 deployed on Canadian Centre for Climate Modelling and Analysis computing facility", "abstract": "This computation involved: CGCM2 Canadian Global Coupled Model Version 2 deployed on Canadian Centre for Climate Modelling and Analysis computing facility.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/3644/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/3645/?format=api" ] }, { "ob_id": 7452, "uuid": "10c5108e23554417a30bf69733c6e4d1", "title": "Hadley Centre Coupled Model 3 (HadCM3) deployed on unknown computer", "abstract": "This computation involved: Hadley Centre Coupled Model 3 (HadCM3).", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 11523, "uuid": "e84beffe4fa640249df4a4412590070d", "title": "NCAR-PCM Parallel Climate Model deployed on National Centre for Atmospheric Research (USA) computing facility", "abstract": "This computation involved: NCAR-PCM Parallel Climate Model deployed on National Centre for Atmospheric Research (USA) computing facility.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7642/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7643/?format=api" ] } ], "acquisitionComponent": [], "identifier_set": [], "responsiblepartyinfo_set": [] }, { "ob_id": 19208, "computationComponent": [ { "ob_id": 1296, "uuid": "bee49269363e4ceaa43e0a00ba3296f3", "title": "Reading University Ocean Reanalysis Software deployed on Reading University computer", "abstract": "This computation involved: Reading University Ocean Reanalysis Software deployed on Reading University computer.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 19207, "uuid": "abaf95a2ba174025a34d8b6ef5289b2b", "title": "University of Reading NEMO coupled ice-ocean model v2.3", "abstract": "Model: NEMO coupled ice-ocean model v2.3\r\nConfiguration: ORCA025_LIM2 (1/4o by 46 vertical levels)\r\nData assimilated: UR025.3 assimilates in situ temperature and salinity observations that were obtained from the UK Met Office quality controlled ENACT/ENSEMBLES (EN3_v2a) dataset available from (http://www.metoffice.gov.uk/hadobs/en3/) A detailed description of the data set including the quality control processing is presented in Ingleby and Huddleston (2007). Assimilation method: Temperature profiles (T) are assimilated along with a salinity balancing increment following the method of Troccoli and Haines, 1999). Salinity profiles (S) are then assimilated along isotherms (i.e., S(T)) up to latitudes of around 50oN/S, using the methodology described by Haines et al. (2006). At higher latitudes salinity is assimilated in a univariate way on z levels. Model – data differences (innovations) are evaluated at the closest model time step, and assimilation increments are calculated every 5 days. Increments are then introduced into the model evenly over the following day (Incremental Analysis Updating, Bloom et al., 1996). Smith and Haines (2009) give more details of the assimilation methodology. Surface Forcing: Surface atmospheric forcing for UR025.3 is obtained from ECMWF ERA-Interim atmospheric reanalysis (Simmons et. al., 2007; Dee and Uppala, 2009; Dee et al., 2011). The ERA-Interim reanalysis provides 10-m wind, 2-m air humidity and 2-m air temperature to compute 6-hourly turbulent air/sea and air/sea-ice fluxes during model integration, using the bulk formula proposed by Large and Yeager (2004, 2009). Downwelling short and long wave radiative fluxes and precipitation are also provided by ERA-Interim. The river runoff is Dai and Trenberth (2002). To prevent drift in the density distributions, a sea surface salinity relaxation to the WOA05 climatology, Boyer et al (2006), is applied with a timescale of 180 days for the top 10 m at the ice-free surface, decreasing to 36 days under ice.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/72304/?format=api" ] }, { "ob_id": 19211, "computationComponent": [ { "ob_id": 19210, "uuid": "579d206516e24a75a67682ae318b38c4", "title": "UCL MODIS land cover algorithm", "abstract": "UCL MODIS land cover algorithm ", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 6754, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 2234, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/10897/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/10898/?format=api", "relatedTo": { "ob_id": 6754, "uuid": "8c6d1e0f28e9458bbfbe1872db4f9637", "short_code": "acq" } }, { "ob_id": 10057, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/10906/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/10898/?format=api", "relatedTo": { "ob_id": 6754, "uuid": "8c6d1e0f28e9458bbfbe1872db4f9637", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [] }, { "ob_id": 19221, "computationComponent": [ { "ob_id": 19222, "uuid": "30a97a092f094765877e783f97aec34c", "title": "Meteosat Geostationary Satellites First Generation visible imagery", "abstract": "Visible imagery images derived from Meteosat Geostationary Satellites First Generation visible imagery or METEOSAT-7.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 19223, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 10062, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/1860/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/2659/?format=api", "relatedTo": { "ob_id": 19223, "uuid": "ed311e8c950045f7833b2f5bc547b5fc", "short_code": "acq" } }, { "ob_id": 10063, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/1860/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/3847/?format=api", "relatedTo": { "ob_id": 19223, "uuid": "ed311e8c950045f7833b2f5bc547b5fc", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/72605/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/72606/?format=api" ] }, { "ob_id": 19230, "computationComponent": [ { "ob_id": 19231, "uuid": "3a513a1aa2c548c6ac8bb35eaa404276", "title": "Meteosat Geostationary Satellites First Generation water vapour imagery", "abstract": "Visible imagery images derived from Meteosat Geostationary Satellites First Generation water vapour or METEOSAT-7.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 19223, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 10062, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/1860/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/2659/?format=api", "relatedTo": { "ob_id": 19223, "uuid": "ed311e8c950045f7833b2f5bc547b5fc", "short_code": "acq" } }, { "ob_id": 10063, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/1860/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/3847/?format=api", "relatedTo": { "ob_id": 19223, "uuid": "ed311e8c950045f7833b2f5bc547b5fc", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/72635/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/72636/?format=api" ] }, { "ob_id": 19235, "computationComponent": [ { "ob_id": 19236, "uuid": "e239141e7c6247afbd2810701557c031", "title": "Meteosat Geostationary Satellites First Generation infra red imagery", "abstract": "Visible imagery images derived from Meteosat Geostationary Satellites First Generation infra red or METEOSAT-7.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 19223, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 10062, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/1860/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/2659/?format=api", "relatedTo": { "ob_id": 19223, "uuid": "ed311e8c950045f7833b2f5bc547b5fc", "short_code": "acq" } }, { "ob_id": 10063, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/1860/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/3847/?format=api", "relatedTo": { "ob_id": 19223, "uuid": "ed311e8c950045f7833b2f5bc547b5fc", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/72649/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/72650/?format=api" ] }, { "ob_id": 19634, "computationComponent": [ { "ob_id": 4351, "uuid": "2382e4b219fd4cd7993e95dd37c3a574", "title": "Met Office Extended Operational NWP model deployed on Met Office supercomputer (Exeter)", "abstract": "This computation involved: Met Office Extended Operational NWP model deployed on Met Office supercomputer (Exeter). The version of the Unified Model (UM) model currently being used for stratospheric data assimilation is the 50-level troposphere-stratosphere configuration. This model includes a scheme to represent forcing from a full spectrum of gravity wave phase speeds, and a simple representation of methane oxidation has been included to improve the simulation of water vapour.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/2923/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/2924/?format=api" ] } ], "acquisitionComponent": [ { "ob_id": 19633, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 10815, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/1635/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/1656/?format=api", "relatedTo": { "ob_id": 19633, "uuid": "2a4884bda5c4468ea08406032f61967d", "short_code": "acq" } }, { "ob_id": 10816, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/1635/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/1636/?format=api", "relatedTo": { "ob_id": 19633, "uuid": "2a4884bda5c4468ea08406032f61967d", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/74436/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/169550/?format=api" ] }, { "ob_id": 19720, "computationComponent": [ { "ob_id": 19721, "uuid": "da144f66dd31441da4ddd9e0901a2330", "title": "Stratospheric Aerosol and Gas Experiment II (SAGE II): species profiles, version 6.20", "abstract": "This computation involved: deployed on Earth Radiation Budget Satellite (ERBS). Version 1 contained SAGE II monthly mean global colour image maps and the relevant gridded data for aerosol extinction at 1020 nm, 525 nm, 453 nm and 385 nm wavelength, ozone mixing ratio, water vapour mixing ratio and relative humidity, nitrogen dioxide mixing ratio at up 14 pressure levels, for the period January 1985 to December 1993. As the original SAGE II measurements were made at geometrical heights, meteorological data from the National Meteorological Center (NMC) were used to determine the actual pressure heights for the SAGE II profile data and also have been used to calculate the relative humidity. For easy reference, the NMC atmospheric temperature, geometrical altitude and tropopause data used in the determination of SAGE II data are also included. Users of the image/data version 1.0 products need to be aware that these meteorological data are not measured by the SAGE II instrument itself.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 7221, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 2335, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/1178/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/1179/?format=api", "relatedTo": { "ob_id": 7221, "uuid": "7d3bb7c90a2d48aa8ef263319130f6f5", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [] }, { "ob_id": 19723, "computationComponent": [ { "ob_id": 560, "uuid": "caa1da8e55124f9c8567b5c8df5e2656", "title": "deployed on Meteor -3M satellite", "abstract": "This computation involved: deployed on Meteor -3M satellite. Meteor-3M is a joint Russian-US environment/atmosphere monitoring meteorological satellite launched on December 10th, 2001.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 19722, "uuid": "8610de4f26894321bb18a7c17944e9cb", "title": "SAGE III: Level 1B transmission profiles", "abstract": "The Level 1B Transmission product contains\r\nthe SAGE III atmospheric slant path transmission\r\nprofiles at 87 spectral channels, as listed in\r\nAppendix B. The profiles are skewed vertically\r\nand extend from sea level to an altitude of 100 km\r\nin 0.5 km intervals. The standard deviation of the\r\nbinned transmission data is also provided for each reported altitude and\r\nchannel. These data have been geolocated and\r\nnormalized against exoatmospheric solar\r\nmeasurements to produce slant path transmission\r\nprofiles. Algorithm retrievals outlined in the\r\nAlgorithm Theoretical Basis Document (ATBD)\r\nare used to reduce and invert these data into the\r\nLevel 2 products listed in Appendices C and D.\r\nThe Level 1B product is only available for solar\r\nmeasurements.\r\nIn the construction of the transmission profiles,\r\natmospheric density information is used to correct\r\nfor refraction effects. This information is derived\r\nfrom temperature profiles interpolated to the\r\nlocation and time of each SAGE III event from\r\nglobal gridded meteorological analyses provided\r\nby the National Oceanic and Atmospheric\r\nAdministration’s (NOAA’s) National Center for\r\nEnvironmental Prediction (NCEP). These data\r\nextend from the surface to a pressure-altitude of\r\n0.4 hPa (~55 km). Above this altitude,\r\nclimatological temperature data are used from the\r\nGlobal Reference Atmospheric Model - 1995\r\n(GRAM95, NASA Technical Memorandum\r\n4715). The composite temperature profile\r\ninformation is included in the Level 1B data\r\nproduct.\r\nNote that the NCEP temperature product is also\r\nused to correct for molecular scattering in the\r\nLevel 2 retrieval algorithm. The retrieval of\r\ntemperature directly from the SAGE III solar\r\nmeasurements occurs later, downstream in the data \r\nLaRC 475-03-060\r\nVersion 1.4 SAGE III Data Products User’s Guide\r\n03/04\r\n6\r\nprocessing flow, and is reported in the Level 2\r\nproducts. ", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 564, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 246, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/561/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/562/?format=api", "relatedTo": { "ob_id": 564, "uuid": "0da3fb6b632b406aae6c8a065d2cf417", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [] }, { "ob_id": 19724, "computationComponent": [ { "ob_id": 560, "uuid": "caa1da8e55124f9c8567b5c8df5e2656", "title": "deployed on Meteor -3M satellite", "abstract": "This computation involved: deployed on Meteor -3M satellite. Meteor-3M is a joint Russian-US environment/atmosphere monitoring meteorological satellite launched on December 10th, 2001.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 19725, "uuid": "7f0e01aab1bf43cbbcbd8166c3563a19", "title": "SAGE III: Level 2 Solar species profiles", "abstract": "The Level 2 Solar Species products are produced from the Level 1B Transmission profiles by using algorithms.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 564, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 246, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/561/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/562/?format=api", "relatedTo": { "ob_id": 564, "uuid": "0da3fb6b632b406aae6c8a065d2cf417", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [] }, { "ob_id": 19914, "computationComponent": [ { "ob_id": 19915, "uuid": "bf8dd6f6a6c84d9fb00f780ae677d312", "title": "Level 1B reprocessed retrieved data", "abstract": "Level 1B reprocessed retrieved data", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 8344, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 2588, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/846/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/8342/?format=api", "relatedTo": { "ob_id": 8344, "uuid": "c1311786388a421fa0675d8b69258757", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [] }, { "ob_id": 19916, "computationComponent": [ { "ob_id": 19917, "uuid": "8a33ec1c442f4a52a73b195f1deb7f14", "title": "Level 1B reprocessed radiance product, Version 3", "abstract": "Level 1B reprocessed retrieved data Version 3", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 8344, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 2588, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/846/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/8342/?format=api", "relatedTo": { "ob_id": 8344, "uuid": "c1311786388a421fa0675d8b69258757", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [] }, { "ob_id": 20019, "computationComponent": [ { "ob_id": 32778, "uuid": "e71c879b049f4ccca07542044df25f09", "title": "Level 1 processing algorithm applied to Sentinel 1 raw data, Instrument Processing Facility (IPF) v2", "abstract": "This computation involves the Level 1 processing algorithm applied to raw Synthetic Aperture Radar (SAR) data. This consists of Level 1 preprocessing, special handling for TOPSAR mode, Doppler centroid estimation, Level 1 Single Look Complex (SLC) processing algorithms and Level 1 post-processing to generate the output Single Look Complex (SLC) and Ground Range Detected (GRD) products as well as quicklook images. \r\n\r\nLevel-1 Single Look Complex (SLC) products consist of focused SAR data, geo-referenced using orbit and attitude data from the satellite, and provided in slant-range geometry. Slant range is the natural radar range observation coordinate, defined as the line-of-sight from the radar to each reflecting object. The products are in zero-Doppler orientation where each row of pixels represents points along a line perpendicular to the sub-satellite track.\r\n\r\nThe products include a single look in each dimension using the full available signal bandwidth and complex samples (real and imaginary) preserving the phase information. The products have been geo-referenced using the orbit and attitude data from the satellite and have been corrected for azimuth bi-static delay, elevation antenna pattern and range spreading loss.\r\n\r\nFor more information on the changes for this processing version please see the Sentinel 1 document libary under the docs tab.", "keywords": "Synthetic Aperture Radar, Sentinel 1, Level 1, algorithm, SAR", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 20018, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 10863, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/20017/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/12313/?format=api", "relatedTo": { "ob_id": 20018, "uuid": "c28a3a6627354dd19363ac971116b0d8", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/76096/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/146482/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/76097/?format=api" ] }, { "ob_id": 20119, "computationComponent": [ { "ob_id": 14521, "uuid": "70aa606ca0584f4594588fc6d7842595", "title": "NAME dispersion model footprints", "abstract": "Atmospheric dispersion model footprints computed at the University of Leicester for various projects using the the Met Office's Numerical Atmospheric-dispersion Modelling Environment (NAME)", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 20121, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 10871, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/14527/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/11735/?format=api", "relatedTo": { "ob_id": 20121, "uuid": "bf1dc55708fc486390f0197e89abef2a", "short_code": "acq" } }, { "ob_id": 10872, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/817/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/11735/?format=api", "relatedTo": { "ob_id": 20121, "uuid": "bf1dc55708fc486390f0197e89abef2a", "short_code": "acq" } }, { "ob_id": 10873, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/11918/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/11735/?format=api", "relatedTo": { "ob_id": 20121, "uuid": "bf1dc55708fc486390f0197e89abef2a", "short_code": "acq" } }, { "ob_id": 10874, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/11918/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/20120/?format=api", "relatedTo": { "ob_id": 20121, "uuid": "bf1dc55708fc486390f0197e89abef2a", "short_code": "acq" } }, { "ob_id": 10875, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/11918/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/14516/?format=api", "relatedTo": { "ob_id": 20121, "uuid": "bf1dc55708fc486390f0197e89abef2a", "short_code": "acq" } }, { "ob_id": 10878, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/14527/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/20147/?format=api", "relatedTo": { "ob_id": 20121, "uuid": "bf1dc55708fc486390f0197e89abef2a", "short_code": "acq" } } ] }, { "ob_id": 20148, "independentInstrument": [], "instrumentplatformpair_set": [] } ], "identifier_set": [], "responsiblepartyinfo_set": [] }, { "ob_id": 24922, "computationComponent": [ { "ob_id": 24928, "uuid": "e768f449cbf84c3caba05ddc63c44989", "title": "MIPclouds Algorithm", "abstract": "The purpose of the Algorithm Theoretical Basis Document (ATBD) is to present the algorithm and technical\r\ndetails necessary to realise a processor for the retrieval of cloud properties form the Level 1b (L1B) data of\r\nESA instrument MIPAS on-board the ENVISAT satellite. The infrared spectra measured by MIPAS (main information\r\nof L1B) include sufficient information to retrieve various cloud parameter. Recent publications have\r\nalready shown the large potential of the dataset ([11], [12], [5], [6]). But so far no validated and consolidated\r\nMIPAS cloud product is available for the scientific community. Consequently the development of a cloud parameter\r\nprocessor for MIPAS and the application to the time series is highly desired.\r\nThe proposed MIPAS cloud processor follows the requirements of the statement of work of the ESA-ITT\r\nAO/1-5255/06/I-OL. Therefore the development and application of the processor is so far restricted to the first\r\n\r\nDetailed information on the data available at:measurement period of MIPAS from July 2002 to March 2004 (spectral high resolution (HR) mode). After\r\n2004 MIPAS is operating with slightly reduced resolution (RR-mode). A transfer of the prototype processor\r\nfor application of the RR mode has been taken into account during the algorithm development. It is desirable,\r\nthat this will be also considered in the realisation phase of the prototype processor.\r\nPrimary task of the software is to retrieve cloud properties from the MIPAS L1B spectra. This contains various\r\nitems of interest:\r\n• the detection of cloudy spectra in the L1B data\r\n• to classify various cloud types in the measurements (e.g. polar stratospheric clouds, liquids and ice\r\nclouds)\r\n• to retrieve cloud top information on height, temperature, pressure\r\n• to retrieve profile information on cloud parameters (e.g.. extinction, ice water path or integrated limb\r\npath quantities like volume/area density path)\r\n• information on microphysical parameter like effective radius of the particle size distribution (PSD) or\r\nVolume and Area densities.\r\nThe retrievability of the cloud parameters like the ones above have been investigated in a feasibility study of\r\nthe MIPclouds project\r\n\r\n1) Spang, R., Remedios, J. J., and Barkley, M., Colour Indices for the Detection and Differentiation of Cloud Types in Infra-red Limb Emission Spectra, Adv. Space Res., 33, pp.1041-1047, 2004.\r\n2) Spang, R., Arndt, K., Dudhia, A., Höpfner, M., Hoffmann, L., Hurley, J., Grainger, R. G., Griessbach, S., Poulsen, C., Remedios, J. J., Riese, M., Sembhi, H., Siddans, R., Waterfall, A., and Zehner, C.: Fast cloud parameter retrievals of MIPAS/Envisat, Atmos. Chem. Phys., 12, 7135-7164, doi:10.5194/acp-12-7135- 2012, 2012.\r\n 3) Sembhi, H., Remedios, J., Trent, T., Moore, D. P., Spang, R., Massie, S., and Vernier, J.-P.: MIPAS detection of cloud and aerosol particle occurrence in the UTLS with comparison to HIRDLS and CALIOP, Atmos. Meas. Tech., 5, 2537- 2553, doi:10.5194/amtd-5-2537-2012, 2012\r\n4) Hurley, J., Dudhia, A., and Grainger, R. G.: Retrieval of macrophysical cloud parameters from MIPAS: algorithm description, Atmos. Meas. Tech., 4, 683- 704, doi:10.5194/amt-4-20 683-2011, 2011.\"", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 11449, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 3946, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/846/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/11447/?format=api", "relatedTo": { "ob_id": 11449, "uuid": "f9c56f83e09845029eac0ac84f256d60", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [] }, { "ob_id": 25281, "computationComponent": [ { "ob_id": 3852, "uuid": "635d2b5e4a634a81b7e56867f6e1c626", "title": "Meteosat Second Generation 2 (MSG-2) or METEOSAT-9", "abstract": "This computation involved: deployed on Meteosat Second Generation 2 (MSG-2) or METEOSAT-9.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 25280, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 11379, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/2658/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/3853/?format=api", "relatedTo": { "ob_id": 25280, "uuid": "8b1f29db1c304ce2a849cc727f64ff0a", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [] }, { "ob_id": 25284, "computationComponent": [ { "ob_id": 2649, "uuid": "507b05c935b24f4aa8bdbbfbe57743e6", "title": "Meteosat Second Generation 1 (MSG-1) or METEOSAT-8", "abstract": "Deployed on Meteosat Second Generation 1 (MSG-1) or METEOSAT-8. Launched on 28 August 2002, the first Meteosat Second Generation (MSG) satellite became operational on 29 January 2004, when it was redesignated Meteosat-8. Since then it has continuously returned highly detailed imagery of Europe, the North Atlantic and Africa every 15 minutes, for operational use by meteorologists.\r\n MSG-1 has a nominal lifetime of seven years.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 25283, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 11380, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/2650/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/3847/?format=api", "relatedTo": { "ob_id": 25283, "uuid": "dccff4060dc5494ab784789234e8abfd", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [] }, { "ob_id": 25440, "computationComponent": [ { "ob_id": 13192, "uuid": "74e36a898d694a70bc8b0412720741e3", "title": "Level 1C processing algorithm applied to Sentinel 2 raw data", "abstract": "This computation involves the Level 1 processing algorithm applied to raw Multispectral Instrument (MSI) data. Level-1C processing includes radiometric and geometric corrections including ortho-rectification and spatial registration on a global reference system with sub-pixel accuracy. This processing produces the level 1C data as well as quicklook images for the user.", "keywords": "Multispectral Instrument, Sentinel 2, level 1C, algorithm, MSI", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 25439, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 11412, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/25277/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/13182/?format=api", "relatedTo": { "ob_id": 25439, "uuid": "18f84df32d934058862f2c3990885a4c", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/105713/?format=api" ] }, { "ob_id": 25535, "computationComponent": [ { "ob_id": 10905, "uuid": "8578ab59341f4b5fb99360c974605e42", "title": "Deployed on Aqua Satellite, part of the Earth Observation System Afternoon Constellation (EOS-PM)", "abstract": "Deployed on Aqua Satellite, part of the Earth Observation System Afternoon Constellation (EOS-PM). Aqua, launched on 4th April 2002, is a polar-orbiting satellite within the Afternoon Constellation (A-Train) that have equator crossings around 13:30 and 01:30 under NASA's Earth Obseration System (EOS). The satellite carries Atmospheric Infrared Sounder (AIRS), Advanced Microwave Sounding Unit (AMSU-A), Humidity Sounder for Brazil (HSB), Advanced Microwave Scanning Radiometer for EOS (AMSR-E), Moderate-Resolution Imaging Spectroradiometer (MODIS) and Clouds and the Earth's Radiant Energy System (CERES), and these collect data on the Earth's atmospheric conditions, snow and ice, sea surface temperature and ocean productivity, and soil moisture.\r\n\r\nAqua is the only satellite in the Aqua mission, and it is a part of the Afternoon Constellation, a group of polar-orbiting satellites sharing the same orbit that all have equator crossings around 13:30 and 01:30. The Satellite was launched on 4th April 2002.\r\n\r\nThe Atmospheric Infrared Sounder (AIRS)</li>\r\nThe Advanced Microwave Sounding Unit (AMSU-A)</li>\r\nThe Humidity Sounder for Brazil (HSB)</li>\r\nThe Advanced Microwave Scanning Radiometer for EOS (AMSR-E)</li>\r\nThe Moderate-Resolution Imaging Spectroradiometer (MODIS)</li>\r\nThe Clouds and the Earth's Radiant Energy System (CERES)</li>\r\n\r\nThese instruments collects data on atmospheric conditions, snow and ice, sea surface temperature and ocean productivity and soil moisture.\r\n", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 10908, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 3842, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/10906/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/10898/?format=api", "relatedTo": { "ob_id": 10908, "uuid": "e280896efade4dd3ae8ee6e0b65dcf46", "short_code": "acq" } }, { "ob_id": 11762, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/10897/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/10898/?format=api", "relatedTo": { "ob_id": 10908, "uuid": "e280896efade4dd3ae8ee6e0b65dcf46", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [] }, { "ob_id": 25537, "computationComponent": [ { "ob_id": 25536, "uuid": "f19ecd7640a347b1b96418584a217164", "title": "MODIS Aqua and Terra Satellite: C6.1 Level 1B Computation", "abstract": "This ATBD documentation attached to the catalogues describes how MODIS operates in space and provides the equations implemented by the L1B software to generate the MODIS MOD02 (Terra) and MYD02 (Aqua) data products. It is a summary document that presents the formulae and error budgets used to transform MODIS DN to radiance and reflectance. It describes the current (Collection 6), post -launch MODIS \r\ncalibration process and supersedes previous ATBDs [Barker et al. (Version 1), 1994] [MCST \r\n(Version 2), May 1997] [MCST (Version 3), December 14, 2005] Analysis of instrumental on-orbit performance by MCST and investigation of L1B products by the Science Team have resulted in several L1B software updates and improvements. This ATBD corresponds to the Version 6.0 Terra and Aqua software releases. Prior to 2006, the MCST and the Science Data Support Team (SDST) provided software deliveries to the Goddard Distributed Archive and Analysis Center (GDAAC). Subsequently, the MODIS Adaptive Processing System (MODAPS) assumed the data production role formerly under\r\ntaken by the GDAAC. Product files are currently distributed using the Level 1 and Atmosphere and Archive Distribution System \r\n\r\n\r\nThe MODIS Adaptive Processing System (MODAPS) is currently generating an improved Collection 6.1 (061) for all MODIS Level-1 (L1) and higher-level Level-2 (L2) & Level-3 (L3) Atmosphere Team products. This decision to create a new improved Collection 6.1 (061) was driven by the need to address a number of issues in the current Collection 6 (006) Level-1B (L1B) data. These L1B issues had a negative impact in varying degrees in downstream MODIS Atmosphere Level-2 (L2) and Level-3 (L3) products, which are more fully described below. \r\n\r\nThe MODIS Atmosphere Team decided to use this reprocessing opportunity to implement some science improvements in their L2 and L3 products. The documents below describe Collection 6.1 (061) changes to L1B as well as all impacted (or improved) L2 and L3 MODIS Atmosphere data. Collection 6.1 reprocessing began in late summer 2017; began to be publically released beginning on 15 October 2017; and is expected to be completed by early summer 2018.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 10908, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 3842, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/10906/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/10898/?format=api", "relatedTo": { "ob_id": 10908, "uuid": "e280896efade4dd3ae8ee6e0b65dcf46", "short_code": "acq" } }, { "ob_id": 11762, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/10897/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/10898/?format=api", "relatedTo": { "ob_id": 10908, "uuid": "e280896efade4dd3ae8ee6e0b65dcf46", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [] }, { "ob_id": 25857, "computationComponent": [ { "ob_id": 25856, "uuid": "9b400f465efa4f978e84dad046f0f7d9", "title": "MODIS Fire_CCI Burned Area Computation", "abstract": "The ESA Fire Disturbance Climate Change Initiative (CCI) project has produced maps of global burned areas developed from satellite observations.\r\n\r\nThe Burned Area (BA) algorithm used for producing the final Fire_CCI BA product is a hybrid approach, combining information on active fires and temporal changes in relectance. The algorithm is described in the Fire_CCI Algorithm Theoretical Basis Document (Lizundia et al. 2018).", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 25855, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 11731, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/10897/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/10898/?format=api", "relatedTo": { "ob_id": 25855, "uuid": "280deb3b3c7f46d0a29a80cb60c3c448", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/108184/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/108185/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/108186/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/108187/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/108183/?format=api" ] }, { "ob_id": 25889, "computationComponent": [ { "ob_id": 27369, "uuid": "44691ecfb5c7420f9e93dea1070d3e86", "title": "Global sulphur dioxide (SO2) column amounts from the Infrared Atmospheric Sounding Interferometer (IASI)", "abstract": "The Walker et al. (2011, 2012) linear retrieval developed for the Infrared Atmospheric Sounding Interferometer (IASI) on the Metop satellites has been used to process the IASI Metop-A data to produce an effect SO2 column amount. The linear retrieval output for each orbit has then been averaged for each month to obtain an average effective SO2 column amount in Dobson Units (DU). In this application, the retrieval uses the ν3 absorption band (centred at 7.3 μm) and SO2 was assumed to be evenly distributed between the surface and 20 km. Literature: Taylor et al. (2018) Exploring the utility of IASI for monitoring volcanic SO2 emissions, in review at JGR: Atmospheres. Walker et al. (2011) An effective method for the detection of trace species demonstrated using the MetOp Infrared Atmospheric Sounding Interferometer, Atmospheric Measurement Techniques, 4: 1567-1580, doi:10.5194/amt-4-1567-2011. Walker et al. (2012) Improved detection of sulphur dioxide in volcanic plumes using satellite-based hyperspectral infrared", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 25888, "independentInstrument": [ 8300 ], "instrumentplatformpair_set": [ { "ob_id": 11733, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/8207/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/8300/?format=api", "relatedTo": { "ob_id": 25888, "uuid": "c3939529f22c44b6b36736ac5c633470", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/108243/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/108244/?format=api" ] }, { "ob_id": 26033, "computationComponent": [ { "ob_id": 26035, "uuid": "2db4843135244d7f886b2b0056c03e42", "title": "GlobTemperature Level-2 MODIS Land Surface Temperature (LST) algorithm", "abstract": "The GlobTemperature Level-2 MODIS Land Surface Temperature (LST) algorithm derives LST data from L1B calibrated radiances from the MODIS instruments on the Aqua and Terra Satellites. It uses a generalized split-window (SW) approach to estimate Land Surface Temperature as a linear function of clear-sky TOA (top of atmosphere) brightness temperatures from MODIS bands 31 and 32 centred on 11 and 12 microns respectively.\r\n\r\nThe GlobTemperature MODIS product also provides a full breakdown of the pixel level uncertainty budget. The uncertainty analysis takes into account the expected performance of the retrieval algorithm under varying surface and atmospheric conditions, with these uncertainties categorised into a 3-component model: random, locally correlated and systematic. The locally correlated component is further split into surface and atmospheric conditions.", "keywords": "Land Surface Temperature, LST, University of Leicester", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 26034, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 11766, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/10906/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/10898/?format=api", "relatedTo": { "ob_id": 26034, "uuid": "85bb8321bc8b42f9a39cb6d83fabe79e", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/108949/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/108983/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/108984/?format=api" ] }, { "ob_id": 26037, "computationComponent": [ { "ob_id": 26035, "uuid": "2db4843135244d7f886b2b0056c03e42", "title": "GlobTemperature Level-2 MODIS Land Surface Temperature (LST) algorithm", "abstract": "The GlobTemperature Level-2 MODIS Land Surface Temperature (LST) algorithm derives LST data from L1B calibrated radiances from the MODIS instruments on the Aqua and Terra Satellites. It uses a generalized split-window (SW) approach to estimate Land Surface Temperature as a linear function of clear-sky TOA (top of atmosphere) brightness temperatures from MODIS bands 31 and 32 centred on 11 and 12 microns respectively.\r\n\r\nThe GlobTemperature MODIS product also provides a full breakdown of the pixel level uncertainty budget. The uncertainty analysis takes into account the expected performance of the retrieval algorithm under varying surface and atmospheric conditions, with these uncertainties categorised into a 3-component model: random, locally correlated and systematic. The locally correlated component is further split into surface and atmospheric conditions.", "keywords": "Land Surface Temperature, LST, University of Leicester", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 25855, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 11731, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/10897/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/10898/?format=api", "relatedTo": { "ob_id": 25855, "uuid": "280deb3b3c7f46d0a29a80cb60c3c448", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/108992/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/108993/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/108994/?format=api" ] }, { "ob_id": 26083, "computationComponent": [], "acquisitionComponent": [], "identifier_set": [], "responsiblepartyinfo_set": [] }, { "ob_id": 26084, "computationComponent": [], "acquisitionComponent": [], "identifier_set": [], "responsiblepartyinfo_set": [] }, { "ob_id": 26442, "computationComponent": [ { "ob_id": 26446, "uuid": "117c8b62457a4b2d999a55884f5df22e", "title": "Level 2 Carbon Monoxide (CO) total column processing algorithm applied to Sentinel 5P TROPOspheric Monitoring Instrument (TROPOMI) raw data", "abstract": "This computation involves the Level 2 processing algorithm applied to raw TROPOspheric Monitoring Instrument (TROPOMI) data. The retrieval algorithm requires several input fields:\r\n• The measured Earth radiance and solar irradiance spectra including noise estimate, solar and viewing\r\ngeometry, and information of geo-location.\r\n• ECMWF temperature, water vapor, and pressure profiles, and geo-potential height.\r\n• An estimate of the CH4 field using a chemistry transport model, e.g. Transport Model 5 (TM5, [RD33]).\r\n• An estimate of the CO column from a chemistry transport model (e.g. TM5).\r\nThe retrieval is performed in two steps: first, as part of the SWIR preprocessing module, the vertically integrated amount of methane is retrieved from a dedicated fit window of the SWIR band between 2315 and 2324 nm using a non-scattering radiative transfer model. The extent of lightpath shortening and enhancement due to atmospheric scattering by clouds and aerosols can be indicated by comparing the retrieved CH4 column with a priori knowledge. If the difference ∆CH4 exceeds a certain threshold, observations are strongly contaminated by clouds and are rejected. In a second step, the SICOR full physics retrieval approach is used to infer CO columns from the adjacent spectral window, 2324-2338 nm. Here, the methane absorption features are used to infer information on atmospheric scattering by clouds and aerosols, which passed the cloud filter, together with the atmospheric CO and H2O abundances, surface albedo, and spectral calibration of the reflectance spectrum. The scattering layer has a triangular height distribution of fixed geometrical thickness, and its optical depth and height are parameters to be retrieved. This step of the retrieval relies on accurate a priori knowledge of CH4 which will be provided within an accuracy of ±3 % by a dedicated methane forecast using the TM5 atmospheric transport model. The atmospheric scattering is described by a two-stream radiative transfer model. Finally, the retrieval product consists of a CO column estimate including a column averaging kernel and a random error estimate. For more information on the processing algorithm please look at the ATBD document on the TROPOMI CO webpage.", "keywords": "Sentinel, ESA, VIIRS", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 26443, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 11891, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/26439/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/26444/?format=api", "relatedTo": { "ob_id": 26443, "uuid": "929d929b043242e69de7b5373acfb611", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/111165/?format=api" ] }, { "ob_id": 26458, "computationComponent": [ { "ob_id": 26457, "uuid": "fe199a094ee04ba2a6c5ac6ac11b879b", "title": "Level 2 Ozone (O3) total column processing algorithm applied to Sentinel 5P TROPOspheric Monitoring Instrument (TROPOMI) raw data", "abstract": "This computation involves the Level 2 processing algorithm applied to raw TROPOspheric Monitoring Instrument (TROPOMI) data. The one-step OFFL algorithm (S5P_TO3_GODFIT) comprises a non-linear least-squares inversion based on the direct comparison of simulated and measured backscattered\r\nradiances. Simulated radiances are computed (again for a multiple scattering atmosphere) at all nominal wavelengths in the UV fitting window, along with corresponding analytically derived weighting functions for total ozone, albedo and effective temperature. The algorithm also contains closure fitting coefficients and a semi-empirical correction for Ring interference. Although more accurate, the S5P_TO3_GODFIT algorithm involves many more RT simulations than S5P_TO3_DOAS, and is, therefore, slower by an order of magnitude approximately. This is currently the main driver for the selection of S5P_TO3_DOAS for the\r\nNRTI product. For more information on the processing of the O3 product please refer to the ATBD document.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 26443, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 11891, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/26439/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/26444/?format=api", "relatedTo": { "ob_id": 26443, "uuid": "929d929b043242e69de7b5373acfb611", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/111206/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/145832/?format=api" ] }, { "ob_id": 26462, "computationComponent": [ { "ob_id": 26460, "uuid": "b79b6f6063ee408cb5a93ec7b34923da", "title": "Level 2 Nitrogen Dioxide (NO2) total column processing algorithm applied to Sentinel 5P TROPOspheric Monitoring Instrument (TROPOMI) raw data", "abstract": "This computation involves the Level 2 processing algorithm applied to raw TROPOspheric Monitoring Instrument (TROPOMI) data. The TROPOMI NO2 processing system is based on the DOMINO and QA4ECV processing systems, with improvements related to specific TROPOMI aspects and new scientific insights. The basis for the processing at KNMI is a retrieval-assimilation-modeling system that uses the 3-dimensional global TM5 chemistry transport model as an essential element. The retrieval consists of a three-step procedure, performed on each measured Level-1b spectrum:\r\n1. the retrieval of a total NO2 slant column density (Ns) from the Level-1b radiance and irradiance spectra\r\nmeasured by TROPOMI using a DOAS (Differential Optical Absorption Spectroscopy) method,\r\n2. the separation of the Ns into a stratospheric and a tropospheric part on the basis of\r\ninformation coming from a data assimilation system, and\r\n3. the conversion of the tropospheric slant column density into a tropospheric vertical column density and of the stratospheric slant column density into a stratospheric vertical column density, by applying an appropriate AMF based on a look-up table of altitude-dependent AMFs and actual, daily information on the vertical distribution of NO2 from the TM5-MP model on a 1-degree by 1-degree grid. The altitude-dependent AMF depends on the satellite geometry, terrain height, cloud fraction and height and surface albedo.\r\nThese steps are described in detail in the ATBD document.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 26443, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 11891, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/26439/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/26444/?format=api", "relatedTo": { "ob_id": 26443, "uuid": "929d929b043242e69de7b5373acfb611", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/111227/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/143701/?format=api" ] }, { "ob_id": 26492, "computationComponent": [ { "ob_id": 26491, "uuid": "4192e2f0403348c4b94f28e65c56f7c7", "title": "Level 2 Cloud processing algorithm applied to Sentinel 5P TROPOspheric Monitoring Instrument (TROPOMI) raw data", "abstract": "This computation involves the Level 2 processing algorithm applied to raw TROPOspheric Monitoring Instrument (TROPOMI) data.\r\nOptical Cloud Recognition Algorithm (OCRA) is the S5P_CLOUD_OCRA heritage. In OCRA, optical sensor measurements are divided into two components: a cloud-free background and a remainder expressing the influence of clouds. OCRA was first developed for GOME in the late 1990s, when enough data from the three sub-pixel broad-band PMDs (Polarization Measurement Devices) had accumulated to allow for the construction of the global cloud-free composite which is the key element in the algorithm. Over the course of the 16-year GOME record, the\r\nalgorithm was refined and the cloud-free composite adjusted as more data became available. OCRA has also been applied to SCIAMACHY and GOME-2. Initial cloud-free composites for these sensors were based on GOME data before dedicated measurements became available from SCIAMACHY and GOME-2. For S5P_CLOUD_OCRA, the initial cloud-free composite will be based on GOME-2 and OMI (see section 5.2). Retrieval of Cloud Information using Neural Networks (ROCINN) is the S5P_CLOUD_ROCINN heritage. ROCINN is based on the comparison of measured and simulated satellite sun-normalized radiances in and near the O2 A-band, and it uses a neural network algorithm to retrieve cloud-top height and cloud-top albedo. ROCINN uses the cloud fraction input from OCRA as one starting point. Early versions of ROCINN used a transmittance model to compute simulated radiances, but the latest versions are based on the use of the VLIDORT radiative transfer scattering model.\r\nFor GOME and GOME-2, ROCINN Version 2.0 is the current operational algorithm in the GDP [GOME Data Processor]. This version is based on the assumption that clouds are simply Lambertian reflecting surfaces so the two main retrieval products are the cloud-top height and the cloud-top albedo itself. This is the “clouds-as-reflecting-boundaries” (CRB) model; see for example [van Roozendael et al., 2006] for GOME and [Loyola et al., 2011] for GOME 2.\r\nAlthough ROCINN 2.0 is the heritage algorithm, there is an important point of departure for S5P. For TROPOMI/S5P, ROCINN Version 3.0 was initially used, which is based on a more realistic treatment of clouds as optically uniform layers of light-scattering particles (water droplets). This is the “clouds-as-layers\" (CAL) model – here, the two main retrieval products are the cloud-top height and the cloud optical thickness. Details of this algorithm prototype may be found in [Schuessler et al., 2014]. Although the CAL model will be the default for S5P, it has been requested that the CRB method should also be retained as an option. CAL is the preferred method for the relatively small TROPOMI/S5P ground pixels (5.5 x 3.5\r\nkm2). The CRB approach works best with large pixels such as those from GOME (footprint 320 x 40 km2). [Schuessler et al., 2014] has shown that for the smaller GOME-2 pixels, CAL retrieval produces more reliable cloud information than that from CRB, not only with regard to the accuracy of the cloud parameters themselves but also with regard to the effect of cloud parameter uncertainties on total ozone accuracy. In OCRA, the intensity is regarded as a linear function of the radiometric cloud cover, and in\r\nROCINN, TOA radiances for partially cloudy scenarios are computed using a linearly weighted mean of the clear-sky and fully-cloudy calculations, the weighting factor being the cloud fraction. In the context of this IPA model, the two algorithms are consistent. With the notably smaller pixel size that comes with higher spatial resolution, 3-D cloud radiative effects will become an important consideration in error budgeting for the cloud algorithms. For more information on the processing chain please see the ATBD document.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 26443, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 11891, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/26439/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/26444/?format=api", "relatedTo": { "ob_id": 26443, "uuid": "929d929b043242e69de7b5373acfb611", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/111340/?format=api" ] }, { "ob_id": 26501, "computationComponent": [ { "ob_id": 26500, "uuid": "867132d84abe4fe6b2e4cccb16647985", "title": "Level 2 UV Aerosol Index processing algorithm applied to Sentinel 5P TROPOspheric Monitoring Instrument (TROPOMI) raw data", "abstract": "This computation involves the Level 2 processing algorithm applied to raw TROPOspheric Monitoring Instrument (TROPOMI) data. MORE INFORMATION TO FOLLOW", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 26443, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 11891, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/26439/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/26444/?format=api", "relatedTo": { "ob_id": 26443, "uuid": "929d929b043242e69de7b5373acfb611", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/111369/?format=api" ] }, { "ob_id": 26518, "computationComponent": [ { "ob_id": 26519, "uuid": "179a8c9a1cd2402cb3d753071b0606a7", "title": "Level 2 processing algorithm applied to Sentinel 1 raw data, Instrument Processing Facility (IPF) version 3", "abstract": "Level-2 consists of geo-located geophysical products derived from Level-1. Level-2 Ocean (OCN) products for wind, wave and currents applications may contain the following geophysical components derived from the SAR data:\r\n- Ocean Wind field (OWI)\r\n- Ocean Swell spectra (OSW)\r\n- Surface Radial Velocity (RVL)\r\nThe availability of components depends on the acquisition mode. The OSW component cannot be generated from IW and EW mode, since individual looks with sufficient time separation are required. The obtained inter look time separation within one burst is too short due to the progressive scanning (i.e. short dwell time).\r\n\r\nThe metadata referring to OWI are derived from an internally processed GRD product. The metadata referring to RVL (and OSW, for SM and WV mode) are derived from an internally processed SLC product.\r\n\r\nFor more information on the changes for this processing version please see the Sentinel 1 document libary under the docs tab.", "keywords": "Synthetic Aperture Radar, Sentinel 1, Level 1, algorithm, SAR", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 12318, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 4316, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/12319/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/12313/?format=api", "relatedTo": { "ob_id": 12318, "uuid": "f95b77f14a554727a1975802b25ad8a7", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/146150/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/146151/?format=api" ] }, { "ob_id": 26522, "computationComponent": [ { "ob_id": 32756, "uuid": "1d05ff37e7124eaa8dbc7a3aedbba431", "title": "Level 2 processing algorithm applied to Sentinel 1 raw data, Instrument Processing Facility (IPF) version 2", "abstract": "Level-2 consists of geo-located geophysical products derived from Level-1. Level-2 Ocean (OCN) products for wind, wave and currents applications may contain the following geophysical components derived from the SAR data:\r\n- Ocean Wind field (OWI)\r\n- Ocean Swell spectra (OSW)\r\n- Surface Radial Velocity (RVL)\r\nThe availability of components depends on the acquisition mode. The OSW component cannot be generated from IW and EW mode, since individual looks with sufficient time separation are required. The obtained inter look time separation within one burst is too short due to the progressive scanning (i.e. short dwell time).\r\n\r\nThe metadata referring to OWI are derived from an internally processed GRD product. The metadata referring to RVL (and OSW, for SM and WV mode) are derived from an internally processed SLC product.\r\n\r\nFor more information on the changes for this processing version please see the Sentinel 1 document libary under the docs tab.", "keywords": "Synthetic Aperture Radar, Sentinel 1, Level 2, algorithm, SAR", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 20018, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 10863, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/20017/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/12313/?format=api", "relatedTo": { "ob_id": 20018, "uuid": "c28a3a6627354dd19363ac971116b0d8", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/111441/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/146193/?format=api" ] }, { "ob_id": 26540, "computationComponent": [ { "ob_id": 26541, "uuid": "1b075ab7d69b41ee981cc832d6306a44", "title": "Level 1B processing algorithm applied to Sentinel 5P TROPOspheric Monitoring Instrument (TROPOMI) raw data", "abstract": "This computation involves the Level 1b processing algorithm applied to raw TROPOspheric Monitoring Instrument (TROPOMI) data.\r\n\r\nThe Earth radiance measurements form the bulk of the measurements. Apart from the optical properties of the instrument, there is some flexibility in the electronics that determine the Earth's radiance ground pixel size. The co-addition period determines the ground pixel size in the along-track direction. Row binning (which is possible for UVN-DEMs only) determines the ground pixel size across track. The parameter space is limited, however, as choosing a smaller ground pixel size will increase the data rate and will decrease the signal-to-noise ratio for the individual ground pixels. The data rate is limited by both internal interfaces within the instrument as well as by the platform’s on-board storage and down-link capabilities. \r\nFor the Earth's radiance measurements, the co-addition period can be set to either 1080ms or 840ms. This\r\neffectively results in a ground pixel size of approximately 7km or 5.5km along-track. The co-addition period is set in the instrument configuration, initially, the nominal operations phase was started with 1080ms. For the SWIR-DEM, which contains a CMOS detector, row binning is not supported. This means that, effectively, the binning factor is 1 for the SWIR bands (Band 7 and Band 8), resulting in a ground pixel size across-track between 7km at the center and 34km at the edges of the across-track field of view. The ground pixel size varies across-track since the spatial dispersion (degrees/pixel) is constant, resulting in a ground pixel size that becomes larger towards the edges of the across-track field of view due to the Earth’s curvature.\r\nApart from the binning factor and the co-addition period, the remaining configuration parameters for\r\nthe Earth radiance measurements, including exposure time and gains, have been optimized during in-flight\r\ncommissioning for the best signal-to-noise ratio while minimizing the saturation of the detector or electronics. This optimization was based on scenes with the highest radiance levels, typically clouded scenes. Since the highest radiance level changes as a function of latitude, a total of five different settings for different latitude zones are created. For bands 4 and 6 saturation, it has not been possible to exclude saturation completely due to instrument limitations.\r\n\r\nFor more information please see the ATBD document linked in the docs tab.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 26443, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 11891, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/26439/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/26444/?format=api", "relatedTo": { "ob_id": 26443, "uuid": "929d929b043242e69de7b5373acfb611", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/111512/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/143694/?format=api" ] }, { "ob_id": 26605, "computationComponent": [ { "ob_id": 26607, "uuid": "17e38b85b0c546799f21bf640b5c219c", "title": "Along Track Scanning Radiometers combined Surface Temperature (AAST) dataset (v2.1) algorithm", "abstract": "The AAST Combined Surface Temperature dataset (CST_L3S_v2.1) has been produced by the University of Leicester. The algorithm combines products produced by the following projects : Ice (and snow) Surface Temperatures (ISTs) and Land Surface Temperatures (LSTs) used to produce this dataset are sourced from the GlobTemperature Level 2 LST V2.1 product; Sea Surface Temperature (SSTs) are from the ATSR SST L2P V3.0 product.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 26606, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 11921, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/7813/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/8097/?format=api", "relatedTo": { "ob_id": 26606, "uuid": "1a76d161e8c3409cb75509c7f6fb0461", "short_code": "acq" } }, { "ob_id": 11922, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/846/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/8076/?format=api", "relatedTo": { "ob_id": 26606, "uuid": "1a76d161e8c3409cb75509c7f6fb0461", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/111832/?format=api" ] }, { "ob_id": 26618, "computationComponent": [ { "ob_id": 26619, "uuid": "115628bd9118415ab47a4b41aa6dc0a6", "title": "ESA Fire_cci Burned Area SFD algorithm", "abstract": "The Burned Area (BA) algorithm used for producing the Fire_CCI Burned Area product is described in the Fire_CCI Algoirthm Theoretical Basis Document (Bastarrika and Roteta, 2018), available at https://www.esa-fire-cci.org/documents", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 13191, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 4334, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/13187/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/13182/?format=api", "relatedTo": { "ob_id": 13191, "uuid": "e05a470bb02a4bf5bba845b1fcc3aca6", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/111872/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/111874/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/111875/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/111871/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/111873/?format=api" ] }, { "ob_id": 26681, "computationComponent": [ { "ob_id": 26680, "uuid": "04595e17816a4455af8fe6ad596cbf8f", "title": "Terrestrial Laser Scanner raw data computation process", "abstract": "The terrestrial laser scanner data was proceesing using software created by Andrew Burt UCL project colleagues detailed belowed", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 26679, "independentInstrument": [ 27223 ], "instrumentplatformpair_set": [] } ], "identifier_set": [], "responsiblepartyinfo_set": [] }, { "ob_id": 26728, "computationComponent": [ { "ob_id": 26727, "uuid": "0f5670b1168c4ba5a7b8c9da6b29c5a6", "title": "The ESA CCI Greenland Ice Sheets Cryosat2 Surface Elevation Change product", "abstract": "The algorithms used to derive the product are explained in detail in Simonsen, S. B. and Sørensen, L. S. (2017) ‘Implications of changing scattering properties on Greenland ice sheet volume change from Cryosat-2 altimetry’, Remote Sensing of Environment. Elsevier Inc., 190, pp. 207–216. doi: 10.1016/j.rse.2016.12.012.. \r\n\r\nThe approach used corresponds to Least Squares Method (LSM) as described in the paper, in which the slope within each grid cell is accounted for by subtraction of the GIMP DEM; the data are corrected for both backscatter and leading edge width; and the LSM is solved at 1 km grid resolution (2 km search radius) and averaged in the post-processing to 5 km grid resolution and with a correlation length of 10/20 km.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 26734, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 11941, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/26733/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/26732/?format=api", "relatedTo": { "ob_id": 26734, "uuid": "eda0664efbab45bf82345cd5d257d7df", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [] }, { "ob_id": 26740, "computationComponent": [ { "ob_id": 26736, "uuid": "c5f0267d809340a58cae305cd3dd8678", "title": "ESA CCI Greenland Ice Sheet Surface Elevation Change from SARAL-Altika", "abstract": "This new experimental product of surface elevation change is based on data from the AltiKa-instrument onboard the France (CNES)/Indian (ISRO) SARAL satellite (Verron et al. 2015). The AktiKa altimeter utilizes Ka-band radar signals, which have less penetration in the upper snow. However, the surface slope and roughness has an imprint in the derived signal and the new product is only available for the flatter central parts of the Greenland ice sheet.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 26739, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 11942, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/26738/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/26737/?format=api", "relatedTo": { "ob_id": 26739, "uuid": "f5b84d9fcc604cdeb18d38a10c34d3b5", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [] }, { "ob_id": 26788, "computationComponent": [ { "ob_id": 26787, "uuid": "7b2b77861e3344ae83499ee9a98f8baa", "title": "Ice Velocity derived by the ESA Greenland Ice Sheets Climate Change Initiative project.", "abstract": "Ice velocities for the Greenland Ice Sheet have been derived by the ESA CCI Greenland Ice Sheet project. Further details are available from http://esa-icesheets-greenland-cci.org/", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 12318, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 4316, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/12319/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/12313/?format=api", "relatedTo": { "ob_id": 12318, "uuid": "f95b77f14a554727a1975802b25ad8a7", "short_code": "acq" } } ] }, { "ob_id": 20018, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 10863, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/20017/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/12313/?format=api", "relatedTo": { "ob_id": 20018, "uuid": "c28a3a6627354dd19363ac971116b0d8", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [] }, { "ob_id": 26805, "computationComponent": [ { "ob_id": 26804, "uuid": "0e31667819b3481484fc28d8f1d613a5", "title": "Optical Ice velocity derived from intensity tracking of Sentinel 2 data", "abstract": "Optical Ice Velocity time series and seasonality products have been derived from intensity-tracking of Sentinel 2 data as part of the ESA Climate Change Initiative (CCI) Greenland Ice Sheet project.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 13191, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 4334, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/13187/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/13182/?format=api", "relatedTo": { "ob_id": 13191, "uuid": "e05a470bb02a4bf5bba845b1fcc3aca6", "short_code": "acq" } } ] }, { "ob_id": 25439, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 11412, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/25277/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/13182/?format=api", "relatedTo": { "ob_id": 25439, "uuid": "18f84df32d934058862f2c3990885a4c", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [] }, { "ob_id": 26817, "computationComponent": [ { "ob_id": 26818, "uuid": "e1a0c71adc7a4bf19c239f99b24134f9", "title": "Ice velocity time series derived from intensity tracking of ERS-1, ERS-2 and ENVISAT data for the Greenland Ice Sheet CCI project.", "abstract": "Ice Velocity time series have been derived from intensity-tracking of ERS-1, ERS-2 and Envisat data for the ESA Climate Change Initiative (CCI) Greenland Ice Sheet project.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 26819, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 11948, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/846/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/7820/?format=api", "relatedTo": { "ob_id": 26819, "uuid": "6b48128600594b008cf996276027e258", "short_code": "acq" } }, { "ob_id": 11949, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/7805/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/7806/?format=api", "relatedTo": { "ob_id": 26819, "uuid": "6b48128600594b008cf996276027e258", "short_code": "acq" } }, { "ob_id": 11950, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/7813/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/7806/?format=api", "relatedTo": { "ob_id": 26819, "uuid": "6b48128600594b008cf996276027e258", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [] }, { "ob_id": 26833, "computationComponent": [ { "ob_id": 26787, "uuid": "7b2b77861e3344ae83499ee9a98f8baa", "title": "Ice Velocity derived by the ESA Greenland Ice Sheets Climate Change Initiative project.", "abstract": "Ice velocities for the Greenland Ice Sheet have been derived by the ESA CCI Greenland Ice Sheet project. Further details are available from http://esa-icesheets-greenland-cci.org/", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 12318, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 4316, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/12319/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/12313/?format=api", "relatedTo": { "ob_id": 12318, "uuid": "f95b77f14a554727a1975802b25ad8a7", "short_code": "acq" } } ] }, { "ob_id": 20018, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 10863, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/20017/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/12313/?format=api", "relatedTo": { "ob_id": 20018, "uuid": "c28a3a6627354dd19363ac971116b0d8", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [] }, { "ob_id": 26906, "computationComponent": [ { "ob_id": 26910, "uuid": "cb0903908c3145029f39299f417a159d", "title": "QA4ECV computation to produce polar sea-ice data", "abstract": "This dataset was created using a specially processed MISR sea ice albedo product (that was generated at Langley Research Center using Rayleigh correction) combining this with a cloud mask of a sea ice mask product, MOD29, which is derived from the MODerate Resolution Imaging Spectroradiometer (MODIS), which is also, like MISR, onboard the Terra satellite.\r\n\r\nFour daily sea ice products have been created, each with a different averaging time window (24 h, 7 days, 15 days, 31 days). For each time window, the number of samples, mean and standard deviation of MISR cloud-free sea ice albedo is calculated. These products are on a predefined polar stereographic grid at three spatial resolutions (1 km, 5 km, 25 km).", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 26907, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 11962, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/10897/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/10972/?format=api", "relatedTo": { "ob_id": 26907, "uuid": "a6d1307175b642868bc2e9dc207bbf0a", "short_code": "acq" } } ] }, { "ob_id": 26908, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 11963, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/10897/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/10898/?format=api", "relatedTo": { "ob_id": 26908, "uuid": "a4fa0ef63d3b4f0faf25761935af8de2", "short_code": "acq" } } ] }, { "ob_id": 26909, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 11964, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/10897/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/10898/?format=api", "relatedTo": { "ob_id": 26909, "uuid": "b3b98a8c683a435a8a62d2d016eecb8a", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/112950/?format=api" ] }, { "ob_id": 26988, "computationComponent": [ { "ob_id": 19040, "uuid": "826fb42295b4469c95b0fd6573aec1c8", "title": "Level 1 processing algorithm applied to Sentinel 3 Sea and Land Surface Temperature Radiometer (SLSTR) raw data", "abstract": "This computation involves the Level 1 processing algorithm applied to raw Sea and Land Surface Temperature Radiometer (SLSTR) data. Level 1 processing uses Level-0 products to compute radiometric measurements for each SLSTR channel in both views. This includes radiometric calibration for thermal and solar channels, several tests concerning surface and cloud flagging, and the determination of pixels' properties such as day/night, position in the instrument grid or geographical position.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 26989, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 11993, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/26990/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/19032/?format=api", "relatedTo": { "ob_id": 26989, "uuid": "39afd744667c4cc1972c79719df2355a", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/113242/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/113243/?format=api" ] }, { "ob_id": 27067, "computationComponent": [ { "ob_id": 27066, "uuid": "0faed9d18356467c9d8ce52390f40009", "title": "Calving Front locations derived by the ESA Greenland Ice Sheets Climate Change Initiative project.", "abstract": "Calving Front Locations have been derived for Glaciers on the Greenland Ice Sheet as part of the ESA Greenland Ice Sheet Climate Change Initiative project. The calving front locations have been derived by manual delineation using ERS-1/2, Envisat and Sentinel-1 SAR (Synthetic Aperture Radar) data and LANDSAT 5,7,8 satellite imagery. The digitized calving fronts are stored in ESRI vector shape-file format and include metadata information on the sensor and processing steps in the corresponding attribute table.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 7808, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 2462, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/7805/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/7806/?format=api", "relatedTo": { "ob_id": 7808, "uuid": "dff95844e3da4741ac99d6c56fafaab3", "short_code": "acq" } } ] }, { "ob_id": 7815, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 2463, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/7813/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/7806/?format=api", "relatedTo": { "ob_id": 7815, "uuid": "8589456ae3f74b0fab74763efeb5f3e0", "short_code": "acq" } } ] }, { "ob_id": 7822, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 2464, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/846/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/7820/?format=api", "relatedTo": { "ob_id": 7822, "uuid": "abfe76bc99f54510a02046b21744c545", "short_code": "acq" } } ] }, { "ob_id": 12318, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 4316, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/12319/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/12313/?format=api", "relatedTo": { "ob_id": 12318, "uuid": "f95b77f14a554727a1975802b25ad8a7", "short_code": "acq" } } ] }, { "ob_id": 12363, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 4806, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/12358/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/12365/?format=api", "relatedTo": { "ob_id": 12363, "uuid": "6b99193d62cd44fa9239d3b02991887d", "short_code": "acq" } } ] }, { "ob_id": 27068, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 11996, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/8246/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/7872/?format=api", "relatedTo": { "ob_id": 27068, "uuid": "812b78639c2740f98090d73e5a8f938e", "short_code": "acq" } } ] }, { "ob_id": 27069, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 11997, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/8256/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/8257/?format=api", "relatedTo": { "ob_id": 27069, "uuid": "bcffa57f3a064c9cbefe9b4cf688d848", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/113422/?format=api" ] }, { "ob_id": 27120, "computationComponent": [ { "ob_id": 27119, "uuid": "a0400dada10f46f9916a38c3e4276601", "title": "Algorithm for the ESA Soil Moisture Climate Change Initiative", "abstract": "The ESA Soil Moisture Climate Change Initiative is deriving information on soil moisture from active and passive satellite sensors. For information on the algorithm see the Algorithm Theoretical Baseline Documents.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 27123, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 11998, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/8207/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/27121/?format=api", "relatedTo": { "ob_id": 27123, "uuid": "87dbbd450a154503905de1e2928aa012", "short_code": "acq" } }, { "ob_id": 11999, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/8299/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/27121/?format=api", "relatedTo": { "ob_id": 27123, "uuid": "87dbbd450a154503905de1e2928aa012", "short_code": "acq" } }, { "ob_id": 12000, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/7805/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/27122/?format=api", "relatedTo": { "ob_id": 27123, "uuid": "87dbbd450a154503905de1e2928aa012", "short_code": "acq" } }, { "ob_id": 12001, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/7813/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/27122/?format=api", "relatedTo": { "ob_id": 27123, "uuid": "87dbbd450a154503905de1e2928aa012", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/113651/?format=api" ] }, { "ob_id": 27140, "computationComponent": [ { "ob_id": 27119, "uuid": "a0400dada10f46f9916a38c3e4276601", "title": "Algorithm for the ESA Soil Moisture Climate Change Initiative", "abstract": "The ESA Soil Moisture Climate Change Initiative is deriving information on soil moisture from active and passive satellite sensors. For information on the algorithm see the Algorithm Theoretical Baseline Documents.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 27134, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 12006, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/458/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/2636/?format=api", "relatedTo": { "ob_id": 27134, "uuid": "ae2f123cb3fe42968601fec75bb03b44", "short_code": "acq" } }, { "ob_id": 12007, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/2629/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/2630/?format=api", "relatedTo": { "ob_id": 27134, "uuid": "ae2f123cb3fe42968601fec75bb03b44", "short_code": "acq" } }, { "ob_id": 12008, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/27135/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/27126/?format=api", "relatedTo": { "ob_id": 27134, "uuid": "ae2f123cb3fe42968601fec75bb03b44", "short_code": "acq" } }, { "ob_id": 12009, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/10906/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/14485/?format=api", "relatedTo": { "ob_id": 27134, "uuid": "ae2f123cb3fe42968601fec75bb03b44", "short_code": "acq" } }, { "ob_id": 12010, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/25273/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/25272/?format=api", "relatedTo": { "ob_id": 27134, "uuid": "ae2f123cb3fe42968601fec75bb03b44", "short_code": "acq" } }, { "ob_id": 12011, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/27130/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/27125/?format=api", "relatedTo": { "ob_id": 27134, "uuid": "ae2f123cb3fe42968601fec75bb03b44", "short_code": "acq" } }, { "ob_id": 12012, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/27128/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/27124/?format=api", "relatedTo": { "ob_id": 27134, "uuid": "ae2f123cb3fe42968601fec75bb03b44", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/113703/?format=api" ] }, { "ob_id": 27141, "computationComponent": [ { "ob_id": 27119, "uuid": "a0400dada10f46f9916a38c3e4276601", "title": "Algorithm for the ESA Soil Moisture Climate Change Initiative", "abstract": "The ESA Soil Moisture Climate Change Initiative is deriving information on soil moisture from active and passive satellite sensors. For information on the algorithm see the Algorithm Theoretical Baseline Documents.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 27139, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 12013, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/27128/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/27124/?format=api", "relatedTo": { "ob_id": 27139, "uuid": "01cdc29dd6674a369f3c1f7a30af3d98", "short_code": "acq" } }, { "ob_id": 12014, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/27130/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/27125/?format=api", "relatedTo": { "ob_id": 27139, "uuid": "01cdc29dd6674a369f3c1f7a30af3d98", "short_code": "acq" } }, { "ob_id": 12015, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/25273/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/25272/?format=api", "relatedTo": { "ob_id": 27139, "uuid": "01cdc29dd6674a369f3c1f7a30af3d98", "short_code": "acq" } }, { "ob_id": 12016, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/10906/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/14485/?format=api", "relatedTo": { "ob_id": 27139, "uuid": "01cdc29dd6674a369f3c1f7a30af3d98", "short_code": "acq" } }, { "ob_id": 12017, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/27135/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/27126/?format=api", "relatedTo": { "ob_id": 27139, "uuid": "01cdc29dd6674a369f3c1f7a30af3d98", "short_code": "acq" } }, { "ob_id": 12018, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/2629/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/2630/?format=api", "relatedTo": { "ob_id": 27139, "uuid": "01cdc29dd6674a369f3c1f7a30af3d98", "short_code": "acq" } }, { "ob_id": 12019, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/458/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/2636/?format=api", "relatedTo": { "ob_id": 27139, "uuid": "01cdc29dd6674a369f3c1f7a30af3d98", "short_code": "acq" } }, { "ob_id": 12020, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/8207/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/27121/?format=api", "relatedTo": { "ob_id": 27139, "uuid": "01cdc29dd6674a369f3c1f7a30af3d98", "short_code": "acq" } }, { "ob_id": 12021, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/8299/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/27121/?format=api", "relatedTo": { "ob_id": 27139, "uuid": "01cdc29dd6674a369f3c1f7a30af3d98", "short_code": "acq" } }, { "ob_id": 12022, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/7805/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/27122/?format=api", "relatedTo": { "ob_id": 27139, "uuid": "01cdc29dd6674a369f3c1f7a30af3d98", "short_code": "acq" } }, { "ob_id": 12023, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/7813/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/27122/?format=api", "relatedTo": { "ob_id": 27139, "uuid": "01cdc29dd6674a369f3c1f7a30af3d98", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/113704/?format=api" ] }, { "ob_id": 27173, "computationComponent": [ { "ob_id": 27171, "uuid": "021e524dfb064502b3eec9434514ff7b", "title": "Derivation of the EUSTACE/AASTI global clear-sky ice surface temperature data from the AVHRR series on the satellite swath with estimates of uncertainty components", "abstract": "Global clear-sky ice surface temperature data has been derived from thermal infrared satellite measurements from the AVHRR (Advanced Very High Resolution Radiometer) series.\r\n\r\nFor information on the algorithms used to derive this data see e.g. the EUSTACE scientific user guide (coming soon).", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 27172, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 12026, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/1809/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/1817/?format=api", "relatedTo": { "ob_id": 27172, "uuid": "59821624b4164c3eb7d1994b2ee468cb", "short_code": "acq" } }, { "ob_id": 12027, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/1816/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/1817/?format=api", "relatedTo": { "ob_id": 27172, "uuid": "59821624b4164c3eb7d1994b2ee468cb", "short_code": "acq" } }, { "ob_id": 12028, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/1824/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/1817/?format=api", "relatedTo": { "ob_id": 27172, "uuid": "59821624b4164c3eb7d1994b2ee468cb", "short_code": "acq" } }, { "ob_id": 12029, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/1831/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/1817/?format=api", "relatedTo": { "ob_id": 27172, "uuid": "59821624b4164c3eb7d1994b2ee468cb", "short_code": "acq" } }, { "ob_id": 12030, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/27174/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/1817/?format=api", "relatedTo": { "ob_id": 27172, "uuid": "59821624b4164c3eb7d1994b2ee468cb", "short_code": "acq" } }, { "ob_id": 12031, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/27175/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/1817/?format=api", "relatedTo": { "ob_id": 27172, "uuid": "59821624b4164c3eb7d1994b2ee468cb", "short_code": "acq" } }, { "ob_id": 12032, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/8207/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/1817/?format=api", "relatedTo": { "ob_id": 27172, "uuid": "59821624b4164c3eb7d1994b2ee468cb", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/113812/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/113813/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/113811/?format=api" ] }, { "ob_id": 27205, "computationComponent": [ { "ob_id": 26680, "uuid": "04595e17816a4455af8fe6ad596cbf8f", "title": "Terrestrial Laser Scanner raw data computation process", "abstract": "The terrestrial laser scanner data was proceesing using software created by Andrew Burt UCL project colleagues detailed belowed", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 26679, "independentInstrument": [ 27223 ], "instrumentplatformpair_set": [] } ], "identifier_set": [], "responsiblepartyinfo_set": [] }, { "ob_id": 27213, "computationComponent": [ { "ob_id": 26680, "uuid": "04595e17816a4455af8fe6ad596cbf8f", "title": "Terrestrial Laser Scanner raw data computation process", "abstract": "The terrestrial laser scanner data was proceesing using software created by Andrew Burt UCL project colleagues detailed belowed", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 26679, "independentInstrument": [ 27223 ], "instrumentplatformpair_set": [] } ], "identifier_set": [], "responsiblepartyinfo_set": [] }, { "ob_id": 27215, "computationComponent": [ { "ob_id": 26680, "uuid": "04595e17816a4455af8fe6ad596cbf8f", "title": "Terrestrial Laser Scanner raw data computation process", "abstract": "The terrestrial laser scanner data was proceesing using software created by Andrew Burt UCL project colleagues detailed belowed", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 26679, "independentInstrument": [ 27223 ], "instrumentplatformpair_set": [] } ], "identifier_set": [], "responsiblepartyinfo_set": [] }, { "ob_id": 27395, "computationComponent": [ { "ob_id": 27396, "uuid": "28195716468d459f9d3c3860dcfa8cf9", "title": "ESA Fire_cci AVHRR-LTDR Burned Area algorithm", "abstract": "The Burned Area (BA) algorithm used for producing the Fire_CCI AVHRR-LTDR Burned Area product is described in the Fire_cci Algorithm Theoretical Basis Document (ATBD) for the AVHRR LTDR data, available from https://climate.esa.int/projects/fire/key-documents .", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 8453, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 2607, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/8450/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/8451/?format=api", "relatedTo": { "ob_id": 8453, "uuid": "bb890e4dd33645689c6fc769d9c1dc8f", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/114502/?format=api" ] }, { "ob_id": 27432, "computationComponent": [ { "ob_id": 11010, "uuid": "2d125dda9d6e44ed804191a3b7b41bc5", "title": "CCI SST Processor", "abstract": "This computation involved: CCI SST Processor. This processor was developed in the ESA Climate Change Initiative, Sea Surface Temperature Project", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7351/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7352/?format=api" ] } ], "acquisitionComponent": [ { "ob_id": 27431, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 12138, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/846/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/847/?format=api", "relatedTo": { "ob_id": 27431, "uuid": "b523533a42a34f848d56335b61c27c21", "short_code": "acq" } }, { "ob_id": 12139, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/7813/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/5566/?format=api", "relatedTo": { "ob_id": 27431, "uuid": "b523533a42a34f848d56335b61c27c21", "short_code": "acq" } }, { "ob_id": 12137, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/7805/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/8063/?format=api", "relatedTo": { "ob_id": 27431, "uuid": "b523533a42a34f848d56335b61c27c21", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [] }, { "ob_id": 27471, "computationComponent": [ { "ob_id": 27472, "uuid": "5874ad23f5cf445ea251dd1649ec1acd", "title": "Level 2 Methane (CH4) total column processing algorithm applied to Sentinel 5P TROPOspheric Monitoring Instrument (TROPOMI) raw data", "abstract": "This computation involves the Level 2 processing algorithm applied to raw TROPOspheric Monitoring Instrument (TROPOMI) data. The algorithm for retrieval of methane columns from the SENTINEL-5P instrument is based on earlier developments of a CO2 and CH4 retrieval algorithm from GOSAT, called RemoTeC [Butz et al., 2009; 2010; 2011; Schepers et al, 2012; Guerlet et al, 2013a].\r\n\r\nIn order to account for the effect of aerosols and cirrus, the algorithm retrieves the CH4 column simultaneously with the aerosol/cirrus amount (column integrated particle number concentration), a parameter related to the particle size distribution, and a parameter describing the height distribution. Here, the particle size distribution is described by a power-law function [Mishchenko et al, 1999] which only has two free parameters (related to amount and size). The choice of aerosol/cirrus parameters reflects the information content of the measurements as closely as possible. The retrieval algorithm uses the Level-1B reflectance measurements in the SWIR band and additionally in the NIR band between 757-774 nm (O2 A-band). Additional fit parameters are the surface albedo and its first-order spectral dependence in the two bands, and the total columns of carbon-monoxide and water vapor, respectively.\r\n\r\nIn order to obtain a proper characterisation of the retrieved CH4 column, it is important to first retrieve a vertical profile (layer averaged number density in different layers of the model atmosphere) and use this retrieved vertical profile to calculate the vertical column. It has been chosen to provide the vertical column as a product, and not the full profile because the Degrees of Freedom for Signal (DFS) of the retrieved CH4 profile is approximately 1. The inversion is performed using Phillips-Tikhonov regularization in combination with a reduced step size Gauss-Newton iteration scheme.\r\n\r\nThe forward model of the retrieval algorithm uses online radiative transfer calculations, fully including multiple scattering. Here, the radiative transfer model developed by Landgraf et al. [2001], and Hasekamp and Landgraf [2002; 2005] is being used. This model uses the Gauss-Seidel iterative method to solve the radiative transfer equation in a plane-parallel, vertically inhomogeneous atmosphere. To avoid time-consuming line-by-line calculations, the linear-k method developed by Hasekamp and Butz [2008] is employed. Absorption cross-sections of the relevant atmospheric trace gases are tabulated in a look-up table as functions of pressure and temperature. The optical properties of aerosols are also calculated from look-up tables as described in Dubovik et al. [2006].\r\n\r\nCloud Filtering\r\n\r\nAs for the CO vertical column retrieval, a pre-processing step is performed to discard ground pixels contaminated by clouds. For CH4, only cloud-free ground pixels will be kept. The baseline approach for cloud/cirrus flagging is to use the cloud mask from the VIIRS instrument (on Suomi-NPP satellite, flying in close formation with SENTINEL-5P). With its 1 km x 1 km ground pixel size, the VIIRS cloud mask is much more flexible in defining the area that is required to be cloud-free than the cloud flagging from TROPOMI itself. However, in case VIIRS data are not available, the cloud mask will be obtained from TROPOMI measurements using either:\r\n\r\n- A comparison between the apparent surface pressure in the TROPOMI Cloud Level-2 product with the \"true\" surface pressure in ECMWF.\r\n- The \"Two-band CH4 cloud filter\" and the \"Two-band H2O cloud filter\".", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 26443, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 11891, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/26439/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/26444/?format=api", "relatedTo": { "ob_id": 26443, "uuid": "929d929b043242e69de7b5373acfb611", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/114841/?format=api" ] }, { "ob_id": 27544, "computationComponent": [ { "ob_id": 27543, "uuid": "de7376f4f7fc45b8bd4d096af5781b8c", "title": "Analysis Ready Sentinel 1 data using SNAP toolbox.", "abstract": "Using the Sentinel SNAP toolbox to process Sentinel 1 GRD products. Each file had the following workflow applied to it: Apply orbit file, Correct for border anomalies, Thermal noise correction, Radiometric calibration, Terrain correction, Geometry.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 12318, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 4316, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/12319/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/12313/?format=api", "relatedTo": { "ob_id": 12318, "uuid": "f95b77f14a554727a1975802b25ad8a7", "short_code": "acq" } } ] }, { "ob_id": 20018, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 10863, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/20017/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/12313/?format=api", "relatedTo": { "ob_id": 20018, "uuid": "c28a3a6627354dd19363ac971116b0d8", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/115222/?format=api" ] }, { "ob_id": 27588, "computationComponent": [ { "ob_id": 11010, "uuid": "2d125dda9d6e44ed804191a3b7b41bc5", "title": "CCI SST Processor", "abstract": "This computation involved: CCI SST Processor. This processor was developed in the ESA Climate Change Initiative, Sea Surface Temperature Project", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7351/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/7352/?format=api" ] } ], "acquisitionComponent": [ { "ob_id": 27587, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 12163, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/1664/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/1802/?format=api", "relatedTo": { "ob_id": 27587, "uuid": "47ef9dc140ea41adb4a1f5b876b493e3", "short_code": "acq" } }, { "ob_id": 12164, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/1679/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/1802/?format=api", "relatedTo": { "ob_id": 27587, "uuid": "47ef9dc140ea41adb4a1f5b876b493e3", "short_code": "acq" } }, { "ob_id": 12165, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/1693/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/1802/?format=api", "relatedTo": { "ob_id": 27587, "uuid": "47ef9dc140ea41adb4a1f5b876b493e3", "short_code": "acq" } }, { "ob_id": 12166, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/1801/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/1802/?format=api", "relatedTo": { "ob_id": 27587, "uuid": "47ef9dc140ea41adb4a1f5b876b493e3", "short_code": "acq" } }, { "ob_id": 12167, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/1809/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/1802/?format=api", "relatedTo": { "ob_id": 27587, "uuid": "47ef9dc140ea41adb4a1f5b876b493e3", "short_code": "acq" } }, { "ob_id": 12168, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/1816/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/1817/?format=api", "relatedTo": { "ob_id": 27587, "uuid": "47ef9dc140ea41adb4a1f5b876b493e3", "short_code": "acq" } }, { "ob_id": 12169, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/1824/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/1817/?format=api", "relatedTo": { "ob_id": 27587, "uuid": "47ef9dc140ea41adb4a1f5b876b493e3", "short_code": "acq" } }, { "ob_id": 12170, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/1831/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/1817/?format=api", "relatedTo": { "ob_id": 27587, "uuid": "47ef9dc140ea41adb4a1f5b876b493e3", "short_code": "acq" } }, { "ob_id": 12171, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/27174/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/1817/?format=api", "relatedTo": { "ob_id": 27587, "uuid": "47ef9dc140ea41adb4a1f5b876b493e3", "short_code": "acq" } }, { "ob_id": 12172, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/27175/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/1817/?format=api", "relatedTo": { "ob_id": 27587, "uuid": "47ef9dc140ea41adb4a1f5b876b493e3", "short_code": "acq" } }, { "ob_id": 12173, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/8207/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/1817/?format=api", "relatedTo": { "ob_id": 27587, "uuid": "47ef9dc140ea41adb4a1f5b876b493e3", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/115367/?format=api" ] }, { "ob_id": 27742, "computationComponent": [ { "ob_id": 27741, "uuid": "707d3c37b8874838bfb50fd00c60154b", "title": "FIDUCEO Project Microwave FCDR Computation V4.1", "abstract": "Generated with FCDR_generator.m v4.1 (AMSU-B, MHS, SSMT2): See project docs for software and computation process and link to V4.1 processing software on Git Hub", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 27740, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 12199, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/27698/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/27695/?format=api", "relatedTo": { "ob_id": 27740, "uuid": "729634dd64a7484a9b821080cf50eeee", "short_code": "acq" } }, { "ob_id": 12200, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/27699/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/27695/?format=api", "relatedTo": { "ob_id": 27740, "uuid": "729634dd64a7484a9b821080cf50eeee", "short_code": "acq" } }, { "ob_id": 12201, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/27700/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/27695/?format=api", "relatedTo": { "ob_id": 27740, "uuid": "729634dd64a7484a9b821080cf50eeee", "short_code": "acq" } }, { "ob_id": 12202, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/27701/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/27695/?format=api", "relatedTo": { "ob_id": 27740, "uuid": "729634dd64a7484a9b821080cf50eeee", "short_code": "acq" } }, { "ob_id": 12203, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/1816/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/27696/?format=api", "relatedTo": { "ob_id": 27740, "uuid": "729634dd64a7484a9b821080cf50eeee", "short_code": "acq" } }, { "ob_id": 12204, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/1824/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/27696/?format=api", "relatedTo": { "ob_id": 27740, "uuid": "729634dd64a7484a9b821080cf50eeee", "short_code": "acq" } }, { "ob_id": 12205, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/1831/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/27696/?format=api", "relatedTo": { "ob_id": 27740, "uuid": "729634dd64a7484a9b821080cf50eeee", "short_code": "acq" } }, { "ob_id": 12206, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/27174/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/27697/?format=api", "relatedTo": { "ob_id": 27740, "uuid": "729634dd64a7484a9b821080cf50eeee", "short_code": "acq" } }, { "ob_id": 12208, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/8207/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/27697/?format=api", "relatedTo": { "ob_id": 27740, "uuid": "729634dd64a7484a9b821080cf50eeee", "short_code": "acq" } }, { "ob_id": 12209, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/8299/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/27697/?format=api", "relatedTo": { "ob_id": 27740, "uuid": "729634dd64a7484a9b821080cf50eeee", "short_code": "acq" } }, { "ob_id": 12207, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/27175/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/27697/?format=api", "relatedTo": { "ob_id": 27740, "uuid": "729634dd64a7484a9b821080cf50eeee", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [] }, { "ob_id": 27750, "computationComponent": [ { "ob_id": 27749, "uuid": "4478a940b5d8482c9ebf4f5b115285c3", "title": "FIDUCEO UTH CDR computation V1.2", "abstract": "FIDUCEO UTH CDR computation V1.2 was generated from the FIDUCEO microwave FCDR", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 27740, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 12199, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/27698/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/27695/?format=api", "relatedTo": { "ob_id": 27740, "uuid": "729634dd64a7484a9b821080cf50eeee", "short_code": "acq" } }, { "ob_id": 12200, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/27699/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/27695/?format=api", "relatedTo": { "ob_id": 27740, "uuid": "729634dd64a7484a9b821080cf50eeee", "short_code": "acq" } }, { "ob_id": 12201, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/27700/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/27695/?format=api", "relatedTo": { "ob_id": 27740, "uuid": "729634dd64a7484a9b821080cf50eeee", "short_code": "acq" } }, { "ob_id": 12202, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/27701/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/27695/?format=api", "relatedTo": { "ob_id": 27740, "uuid": "729634dd64a7484a9b821080cf50eeee", "short_code": "acq" } }, { "ob_id": 12203, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/1816/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/27696/?format=api", "relatedTo": { "ob_id": 27740, "uuid": "729634dd64a7484a9b821080cf50eeee", "short_code": "acq" } }, { "ob_id": 12204, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/1824/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/27696/?format=api", "relatedTo": { "ob_id": 27740, "uuid": "729634dd64a7484a9b821080cf50eeee", "short_code": "acq" } }, { "ob_id": 12205, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/1831/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/27696/?format=api", "relatedTo": { "ob_id": 27740, "uuid": "729634dd64a7484a9b821080cf50eeee", "short_code": "acq" } }, { "ob_id": 12206, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/27174/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/27697/?format=api", "relatedTo": { "ob_id": 27740, "uuid": "729634dd64a7484a9b821080cf50eeee", "short_code": "acq" } }, { "ob_id": 12208, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/8207/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/27697/?format=api", "relatedTo": { "ob_id": 27740, "uuid": "729634dd64a7484a9b821080cf50eeee", "short_code": "acq" } }, { "ob_id": 12209, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/8299/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/27697/?format=api", "relatedTo": { "ob_id": 27740, "uuid": "729634dd64a7484a9b821080cf50eeee", "short_code": "acq" } }, { "ob_id": 12207, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/27175/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/27697/?format=api", "relatedTo": { "ob_id": 27740, "uuid": "729634dd64a7484a9b821080cf50eeee", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [] }, { "ob_id": 27759, "computationComponent": [ { "ob_id": 27758, "uuid": "311661a2624a495080d9bbbf43874a66", "title": "FIDUCEO AOT and Albedo CDR v0.1.1", "abstract": "The FIDUCEO Aerosol Optical Depth and Albedo V0.1.1 data sets where generated in the same computational processed from the FIDUCEO MVIRI FCDRs archived at EUMETSAT. See MVIRI report and software links in documnetation for further detail.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 27757, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 12211, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/1845/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/1846/?format=api", "relatedTo": { "ob_id": 27757, "uuid": "bec822dd3c85460895d28fd4bc283dfa", "short_code": "acq" } }, { "ob_id": 12212, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/1860/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/1846/?format=api", "relatedTo": { "ob_id": 27757, "uuid": "bec822dd3c85460895d28fd4bc283dfa", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [] }, { "ob_id": 28027, "computationComponent": [ { "ob_id": 28022, "uuid": "aee5aafba1564245ba1e0d0590e47f85", "title": "UoL_FP: University of Leicester Full-Physics retrieval algorithm for retrieval of Solar Induced Fluorescence", "abstract": "The UoL-FP algorithm has been specially modified for use with Solar Induced Fluorescence (SIF). See the linked documentation for a description on both.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 28026, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 12219, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/28024/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/28023/?format=api", "relatedTo": { "ob_id": 28026, "uuid": "41c0f3f3834e4e208244911aa4ae2c6f", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [] }, { "ob_id": 28090, "computationComponent": [ { "ob_id": 28092, "uuid": "14a8098d70714cc1bf38f9dbcb82e5ed", "title": "FIDUCEO: AVHRR Fundamental Climate Data Record V1.0", "abstract": "The L1B data were generated from the onboard AVHRR instrument flying on various NOAA satellites, and subsequently processed by NOAA and archived in CLASS. The FIDUCEO team obtained the L1B data from the NOAA CLASS archive and processed it version v1.00 of the FCDR_AVHRR software. Please see the documentation for further information The data was produced using PATMOS-x Nov 2015 set of coefficients from CSPP.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 28091, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 12261, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/8207/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/8451/?format=api", "relatedTo": { "ob_id": 28091, "uuid": "44678a0f3db246c9afd4d3c92d3659c3", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [] }, { "ob_id": 28105, "computationComponent": [ { "ob_id": 28104, "uuid": "dd3bf5ee0cf14645af95ac5aff7eb39a", "title": "FIDUCEO: HIRS Fundamental Climate Data Record V1.0", "abstract": "Core input data are L1B data files obtained from the NOAA CLASS archive, Spectral response functions are obtained from NOAA NESDIS STAR, PRT coefficients are obtained from CPIDS and also provided by NOAA and it was processed using version v1.00 of the FCDR_HIRS software. Please see documentation for further information", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 28102, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 12265, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/1679/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/28103/?format=api", "relatedTo": { "ob_id": 28102, "uuid": "1151de63ae1f447eb8ae449e9e137dfc", "short_code": "acq" } }, { "ob_id": 12266, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/1686/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/28103/?format=api", "relatedTo": { "ob_id": 28102, "uuid": "1151de63ae1f447eb8ae449e9e137dfc", "short_code": "acq" } }, { "ob_id": 12267, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/1693/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/28103/?format=api", "relatedTo": { "ob_id": 28102, "uuid": "1151de63ae1f447eb8ae449e9e137dfc", "short_code": "acq" } }, { "ob_id": 12268, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/1801/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/28103/?format=api", "relatedTo": { "ob_id": 28102, "uuid": "1151de63ae1f447eb8ae449e9e137dfc", "short_code": "acq" } }, { "ob_id": 12269, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/1809/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/28103/?format=api", "relatedTo": { "ob_id": 28102, "uuid": "1151de63ae1f447eb8ae449e9e137dfc", "short_code": "acq" } }, { "ob_id": 12270, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/1816/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/28103/?format=api", "relatedTo": { "ob_id": 28102, "uuid": "1151de63ae1f447eb8ae449e9e137dfc", "short_code": "acq" } }, { "ob_id": 12271, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/1824/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/28103/?format=api", "relatedTo": { "ob_id": 28102, "uuid": "1151de63ae1f447eb8ae449e9e137dfc", "short_code": "acq" } }, { "ob_id": 12272, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/1831/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/28103/?format=api", "relatedTo": { "ob_id": 28102, "uuid": "1151de63ae1f447eb8ae449e9e137dfc", "short_code": "acq" } }, { "ob_id": 12273, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/27174/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/28103/?format=api", "relatedTo": { "ob_id": 28102, "uuid": "1151de63ae1f447eb8ae449e9e137dfc", "short_code": "acq" } }, { "ob_id": 12274, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/27175/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/28103/?format=api", "relatedTo": { "ob_id": 28102, "uuid": "1151de63ae1f447eb8ae449e9e137dfc", "short_code": "acq" } }, { "ob_id": 12275, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/8207/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/28103/?format=api", "relatedTo": { "ob_id": 28102, "uuid": "1151de63ae1f447eb8ae449e9e137dfc", "short_code": "acq" } }, { "ob_id": 12276, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/8299/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/28103/?format=api", "relatedTo": { "ob_id": 28102, "uuid": "1151de63ae1f447eb8ae449e9e137dfc", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [] }, { "ob_id": 28107, "computationComponent": [ { "ob_id": 28108, "uuid": "afce14d2a21c4d3592a63c4ae60a5703", "title": "FIDUCEO: AVHRR Enseble Fundamental Climate Data Record V1.0", "abstract": "The ensemble dataset was generated by first perturbing all of the input values (recorded counts, temperatures etc.) as well as model values (calibration coefficients and ICT temperature corrections) using their individual uncertainties as the standard deviation used in the random generation process. For single error sources which are uncorrelated a random generation scheme was used which samples the Gaussian distribution in 10 equal area segments and enables a small number of samples (in this case 10) to give a mean and variance that is closer to the expected values of zero and one than if a purely Gaussian random number generator was used. In the case of those parameters where a covariance matrix exists (the calibration parameters themselves) this was also sampled so as to capture the correct covariance with a small number of samples. The actual values of the Harmonisation/calibration parameters used for the infrared channels were generated in a two stage process. First, estimates of the non-linearity and instrument temperature terms were determined using SNO matchups using the AATSR as a reference. Then in a separate process small corrections to the bias and emissivity correction terms were found using sea surface temperature (SST) retrievals compared to the drifting buoy network to ensure that the Ensemble SST would be accurate. This was needed because the SNO matchups were concentrated at cloud like temperatures (240K-250K) and so had not sampled many SST like temperatures (>270K) leading to a small error in the Harmonised calibration for SST retrievals. When the new FCDR values are combined with the perturbed input values from the Ensemble files it is possible to generate a new set of perturbed Radiances/Brightness Temperatures which capture the underlying sources of uncertainty. These were then used as input into the AVHRR ESA CCI SST/Lake Water Surface Temperature (LWST) algorithms which also included a perturbation to the cloud detection threshold to derive a new baseline SST/LWST data together with perturbed SST/LWST values to create the SST/LWST Ensemble dataset. \r\n\r\nRelationship between the SST CDR and the ensemble\r\nThe FCDR ensemble is used to generate an SST ensemble product where the complete SST retrieval process is applied to each of the ensemble members directly generating 10 SST perturbations to the baseline SST. Also included in the SST ensemble is a variation in the cloud detection threshold which adds extra uncertainty to the ensemble in an attempt to capture uncertainties in the cloud detection process.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 28091, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 12261, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/8207/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/8451/?format=api", "relatedTo": { "ob_id": 28091, "uuid": "44678a0f3db246c9afd4d3c92d3659c3", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [] }, { "ob_id": 28244, "computationComponent": [ { "ob_id": 28243, "uuid": "b7d30f0de38b414fb5deefce4e17cab0", "title": "FIDUCEO: AVHRR Lake and Sea Surface Temperature Climate Data Record V1.0", "abstract": "The FIDUCEO AVHRR FCDR for MetOp-A has updated calibration parameters which have been harmonised using SNO (Simultaneous Nadir Overpass) matches using the AATSR as a reference as well as corrections for some of the dominant error sources. The Ensemble version has had corrections to two of the calibration parameters (this bias term and the emissivity correction term) to improve SSTs retrieved using the FIDUCEO brightness temperatures when compared to the drifting buoy network. It therefor has mixed references, one a satellite reference and another a virtual reference consisting of radiative transfer modelled brightness temperatures derived using the SST in-situ reference data.\r\n\r\nFor full information and links to software please see the documentation section", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 28091, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 12261, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/8207/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/8451/?format=api", "relatedTo": { "ob_id": 28091, "uuid": "44678a0f3db246c9afd4d3c92d3659c3", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [] }, { "ob_id": 28847, "computationComponent": [ { "ob_id": 28843, "uuid": "587fc6b61a3045ee82b191232d11e5b5", "title": "FIDUCEO AVHRR AOD computation V1.0", "abstract": "The algorithm used to produce the AVHRRAerosol demonstration dataset is described inthe doumentation along with links to the processing software. The AVHRR instrument, which was designed for cloud and land observations,is a weak instrument if it is used for the retrieval of a Climate Data Record (CDR) of Aerosol Optical Depth (AOD) over land, because of its small information content with practically only one useful channel with uncertain calibration. However, AVHRR offers a long historic record back to 1978 from the series of instruments flown on NOAA and METOP platforms.AOD can be inverted from top-of-atmosphere (TOA) reflectance measurements in the red band, (directional) surface albedo estimated from the mid-infraredchannel at 3.7 μm and a vegetation index, and byassuming optical properties of atmospheric aerosol (aerosol type) from a multi-model based climatology.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 28842, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 12280, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/1824/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/1817/?format=api", "relatedTo": { "ob_id": 28842, "uuid": "748307dfdae24eef936f3a92a72137fd", "short_code": "acq" } }, { "ob_id": 12281, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/27174/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/1817/?format=api", "relatedTo": { "ob_id": 28842, "uuid": "748307dfdae24eef936f3a92a72137fd", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [] }, { "ob_id": 29942, "computationComponent": [ { "ob_id": 29944, "uuid": "6ce5cfb061e94d2b8eca8943040b11f2", "title": "CCI Sea Surface Salinity retrieval", "abstract": "ESA CCI Sea Surface Salinity ECV Data has been produced at a spatial resolution of 50 km spatially resampled on 25 km EASE grid with a) a time resolution of 1 week and 1 day of time sampling and b) a time resolution of 1 month and 15 days of time sampling. For details of the algorithm see the documentation from the CCI Sea Surface Salinity project.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 29943, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 12284, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/27128/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/27124/?format=api", "relatedTo": { "ob_id": 29943, "uuid": "119a7746b29243f5bdb8e329f392bd9f", "short_code": "acq" } }, { "ob_id": 12285, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/29941/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/29938/?format=api", "relatedTo": { "ob_id": 29943, "uuid": "119a7746b29243f5bdb8e329f392bd9f", "short_code": "acq" } }, { "ob_id": 12286, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/29940/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/29939/?format=api", "relatedTo": { "ob_id": 29943, "uuid": "119a7746b29243f5bdb8e329f392bd9f", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [] }, { "ob_id": 29950, "computationComponent": [ { "ob_id": 29949, "uuid": "4d1e78942dc84ddb9fb5358d59491e1f", "title": "Bias corrected time-series data extracted from the global gridded surface meteorology dataset Global Soil Wetness Project Phase 3) for grid cells containing the ESM-SnowMIP reference sites", "abstract": "30-year (1980-2010) time-series have been extracted from a global gridded surface meteorology dataset (Global Soil Wetness Project Phase 3) for the grid cells containing the Earth System Model - Snow Model Intercomparison Project (ESM-SnowMIP) reference sites, interpolated to one-hour timesteps and bias corrected. Although applied to all sites. The bias corrections are particularly important for mountain sites that are hundreds of meters higher than the grid elevations; as a result, uncorrected air temperatures are too high and snowfall amounts are too low in comparison with in situ measurements.\r\n\r\nThe ten in situ sites are characterised as maritime (Sapporo, Japan), arctic (Sodankylä, Finland), boreal (Old Aspen, Old Jack Pine and Old Black Spruce, Saskatchewan, Canada) and mid-latitude alpine (Col de Porte, France; Reynolds Mountain East, Idaho, USA, Senator Beck and Swamp Angel, Colorado, USA; Weissfluhjoch, Switzerland). The locations of the in situ measurement sites are listed as follows: \r\n\r\nCDP (Col de Porte), Latitude: 45.29, Longitude: 5.77, Elevation: 1325.0 m, Location: France;\r\nOAS (Old Aspen), Latitude: 54.05, Longitude: -106.33, Location: Canada;\r\nOBS (Old Black Spruce), Latitude: 54.65, Longitude: -105.20, Location: Canada;\r\nOJP (Old Jack Pine), Latitude: 54.53, Longitude: -105.00, Location: Canada; \r\nRME (Reynolds Mountain East), Latitude: 43.19, Longitude: -116.78, Location: United States;\r\nSAP (Sapporo), Latitude: 43.06, Longitude: 141.33, Elevation: 17.0 m, Location: Japan;\r\nSNB (Senator Beck Basin Study Area (SBBSA)), Latitude: 37.91, Longitude: -107.73, Location: United States;\r\nSOD (Sodankyla), Latitude: 67.42, Longitude: 26.59, Location: Finland; \r\nSWA (Swamp Angel Study Plot (SASP)), Latitude: 37.91, Longitude: -107.71, Elevation: 3371.0 m, Location: United States; \r\nWFJ (Weissfluhjoch), Latitude: 46.83, Longitude: 9.81, Location: Switzerland.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 29948, "independentInstrument": [], "instrumentplatformpair_set": [] } ], "identifier_set": [], "responsiblepartyinfo_set": [] }, { "ob_id": 29957, "computationComponent": [ { "ob_id": 29955, "uuid": "c62c65712f674aeeaddffe5dc05d1ead", "title": "GlobBiomass retrieval algorithm used in the production of the Biomass CCI global dataset of forest above ground biomass for the year 2017.", "abstract": "The GlobBiomass retrieval algorithm is used to derive estimates of forest above-ground biomass (AGB) from satellite data for the year 2017 as part of the Biomass CCI project.\r\n\r\nFirst, per-pixel estimates of growing stock volume (GSV, unit: m3/ha) were obtained from spaceborne SAR images acquired in 2017 (ALOS-2 PALSAR-2, Sentinel-1) with the BIOMASAR algorithm, adapted specifically to ALOS-2 PALSAR-2 and Sentinel-1 data. Individual per-pixel GSV estimates were then combined with a set of merging rules to form the final per-pixel estimate of GSV. The retrieval was supported by LiDAR (ICESAT) data and auxiliary datasets . AGB was then obtained from GSV with a set of Biomass Expansion and Conversion Factors (BCEF) following approaches to extend on ground estimates of wood density and stem-to-total biomass expansion factors to obtain a global raster dataset.\r\n\r\nSee the Algorithm Theoretical Basis Document for details on the EO datasets, the biomass retrieval algorithms and the estimation of the BCEF (see http://cci.esa.int/biomass)", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 29956, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 12287, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/12319/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/12313/?format=api", "relatedTo": { "ob_id": 29956, "uuid": "c8b2caa776da4515833a1ba6aa3ddc0e", "short_code": "acq" } }, { "ob_id": 12288, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/29959/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/29958/?format=api", "relatedTo": { "ob_id": 29956, "uuid": "c8b2caa776da4515833a1ba6aa3ddc0e", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/129431/?format=api" ] }, { "ob_id": 29990, "computationComponent": [ { "ob_id": 27119, "uuid": "a0400dada10f46f9916a38c3e4276601", "title": "Algorithm for the ESA Soil Moisture Climate Change Initiative", "abstract": "The ESA Soil Moisture Climate Change Initiative is deriving information on soil moisture from active and passive satellite sensors. For information on the algorithm see the Algorithm Theoretical Baseline Documents.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 27123, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 11998, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/8207/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/27121/?format=api", "relatedTo": { "ob_id": 27123, "uuid": "87dbbd450a154503905de1e2928aa012", "short_code": "acq" } }, { "ob_id": 11999, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/8299/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/27121/?format=api", "relatedTo": { "ob_id": 27123, "uuid": "87dbbd450a154503905de1e2928aa012", "short_code": "acq" } }, { "ob_id": 12000, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/7805/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/27122/?format=api", "relatedTo": { "ob_id": 27123, "uuid": "87dbbd450a154503905de1e2928aa012", "short_code": "acq" } }, { "ob_id": 12001, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/7813/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/27122/?format=api", "relatedTo": { "ob_id": 27123, "uuid": "87dbbd450a154503905de1e2928aa012", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/129598/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/141776/?format=api" ] }, { "ob_id": 30084, "computationComponent": [ { "ob_id": 30049, "uuid": "ba783f690ea84c7ab5586d8427380e9f", "title": "Frontier Research System for Global Change version of the University of California, Irvine Chemical Transport Model (FRSGC/UCI CTM) deployed on Lancaster University High-End Computing cluster.", "abstract": "Frontier Research System for Global Change version of the University of California, Irvine Chemical Transport Model (FRSGC/UCI CTM) as documented in Wild 2007.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": 30192, "identifier_set": [] }, { "ob_id": 30082, "uuid": "56491145e8884252ba8a0a1acc32384d", "title": "Goddard Institute for Space Studies Global Climate Model (GISS GCM) deployed on NASA High-End Computing resources at Goddard Space Flight Center.", "abstract": "Goddard Institute for Space Studies Global Climate Model (GISS GCM) as documented in Shindell et al., 2013.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": 30191, "identifier_set": [] }, { "ob_id": 30083, "uuid": "90e7f8e26f784376a076c61f0df427c3", "title": "Community Atmosphere Model with Chemistry (CAM-Chem) deployed on the Cheyenne supercomputer at the Computational and Information Systems Laboratory (CISL) at NCAR.", "abstract": "Community Atmosphere Model with Chemistry (CAM-Chem) as documented in Lamarque et al., 2012.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": 30190, "identifier_set": [] } ], "acquisitionComponent": [], "identifier_set": [], "responsiblepartyinfo_set": [] }, { "ob_id": 30196, "computationComponent": [ { "ob_id": 30195, "uuid": "b67d618c878646289fc8cc7482f919ee", "title": "Computation for Defra and JNCC Sentinel-1 Analysis Ready Data", "abstract": "Sentinel-1 GRD products processed into a backscatter product using ESA SNAP. Processing included the following steps: apply orbit file, border and thermal noise removal, radiometric calibration, multilook, terrain correction using either the Aerial Photography Great Britain (APGB) 10m resolution DEM or the Ordnance Survey Northern Ireland (OSNI) 10m resolution DEM, radiometric normalisation (Kellndorfer approach, Kellndorfer et al., 1998) and refined Lee speckle filter. Data is outputted on a linear scale in dB. A final reprojection is applied to transform the data to either OSGB1936 (EPSG:27700) or TM65/Irish Grid (EPSG:29902) using GDAL. The processed product is stacked, containing VV_dB in Band 1 and VH_dB in Band 2. Please see individual image metadata for the versions of software used in processing.", "keywords": "", "inputDescription": 13, "outputDescription": 14, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 12318, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 4316, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/12319/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/12313/?format=api", "relatedTo": { "ob_id": 12318, "uuid": "f95b77f14a554727a1975802b25ad8a7", "short_code": "acq" } } ] }, { "ob_id": 20018, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 10863, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/20017/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/12313/?format=api", "relatedTo": { "ob_id": 20018, "uuid": "c28a3a6627354dd19363ac971116b0d8", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/130447/?format=api" ] }, { "ob_id": 30201, "computationComponent": [ { "ob_id": 30200, "uuid": "dd3549bd3c244c528ecfe752cbce1e5e", "title": "Computation for Defra and JNCC Sentinel-2 Analysis Ready Data", "abstract": "Sentinel-2 Level 1C products processed into a Level 2 surface reflectance product using ARCSI ( https://www.arcsi.remotesensing.info/ ). Processing used the following steps: re-projection to either OSGB 1936/British National Grid (EPSG27700) or TM65/Irish Grid (EPSG:29902), band sharpening to 10m (removing the native 60m ESA Bands 1, 9 and 10), cloud masking, atmospheric correction and topographic correction using either the Aerial Photography Great Britain (APGB) 10m resolution DEM or the Ordnance Survey Northern Ireland (OSNI) 10m resolution DEM. Please see individual image metadata for the versions of software used in processing.", "keywords": "", "inputDescription": 15, "outputDescription": 16, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 13191, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 4334, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/13187/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/13182/?format=api", "relatedTo": { "ob_id": 13191, "uuid": "e05a470bb02a4bf5bba845b1fcc3aca6", "short_code": "acq" } } ] }, { "ob_id": 25439, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 11412, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/25277/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/13182/?format=api", "relatedTo": { "ob_id": 25439, "uuid": "18f84df32d934058862f2c3990885a4c", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [] }, { "ob_id": 30282, "computationComponent": [ { "ob_id": 30289, "uuid": "d625d071da8441d99c5a152dc6ab48b7", "title": "UoL_FP: University of Leicester Full-Physics retrieval algorithm for retrieval of XCH_4 from GOSAT data", "abstract": "The GOSAT spectral data were inputted into the UoL-FP retrieval algorithm where the Proxy retrieval approach was used to obtain the column-averaged dry-air mole fraction of methane (XCH4). See the linked documentation for further information", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 28026, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 12219, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/28024/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/28023/?format=api", "relatedTo": { "ob_id": 28026, "uuid": "41c0f3f3834e4e208244911aa4ae2c6f", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/208078/?format=api" ] }, { "ob_id": 30496, "computationComponent": [ { "ob_id": 30493, "uuid": "865de05d71e74ea9ac7694462ce38821", "title": "ACSIS AO SST Computation", "abstract": "Interpolation using Kriging to infill gaps and estimate uncertainties. The spatial covariance used in the Kriging was derived from the CCI SST analysis residuals (CCI SST analysis minus the CCI SST climatology). After interpolation, bias corrections derived from the HadSST.4.0.0.0 dataset are applied.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 30495, "independentInstrument": [], "instrumentplatformpair_set": [] } ], "identifier_set": [], "responsiblepartyinfo_set": [] }, { "ob_id": 31819, "computationComponent": [ { "ob_id": 31818, "uuid": "98042648cc55470f8f96ea704107181e", "title": "Met Office Unified Model United Kingdom Variable resolution (UKV) version 8.2, run xkyib", "abstract": "Control experiment run of version version 8.2 of the Met Office Unified Model, United Kingdom Variable resolution (UKV) following operational configuration of the Unified Model.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] }, { "ob_id": 31820, "uuid": "d18395020fed4679a60e4d7c167917e5", "title": "Met Office Unified Model United Kingdom Variable resolution (UKV) version 8.2, run xldef", "abstract": "Perturbation experiment run of version 8.2 of the Met Office Unified Model, United Kingdom Variable resolution (UKV) following operational configuration of the Unified Model.\r\n\r\nHere the Gaussian potential temperature perturbations are added into the model. Full details of the perturbation method are described in Flack et al. (2018) Convective-\r\nScale Perturbation Growth Across the Spectrum of Convective Regimes, Monthly Weather Review, 146, 387-405, however I give a brief overview here:\r\n\r\nA Gaussian distribution (defined using random numbers between +/- 1 at each grid point, with the seed determined by the time the model is ran) is created at every grid point in the domain. A superposition is created and rescaled to 0.1 K so as to be an appropriate amplitude for boundary layer noise. Each of the Gaussian distributions have a standard deviation of 9km so as to be added onto an appropriate scale for the model. The perturbations are added in at a model hybrid height of 261.6 m (appro\r\nximately the 8th model level).", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/140345/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/140349/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/140350/?format=api" ] }, { "ob_id": 31850, "computationComponent": [ { "ob_id": 31853, "uuid": "4dee97358b894e5eb51503c297686518", "title": "Data assimilations run for FRANC: Doppler radar radial wind observations and associated observation-minus-model residuals from the Met Office UKV 3D Var assimilation scheme", "abstract": "The datasets were created by assimilating observations from the Met Office network of C band radars into the Met Office variable-resolution convection permitting model (UKV) using version 8.2 of the unified model. The assimilation scheme is a limited-area version of the Met Office 3D variational assimilation scheme that uses an incremental approach. We note that four datasets are provided to correspond with four different experiments. Further details of the observation, model, data assimilation and four experimental cases are given in Waller et al. 2016.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 5730, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 1724, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/999/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/1003/?format=api", "relatedTo": { "ob_id": 5730, "uuid": "d1e05d1fc4104335b4a7ba91f2f88df0", "short_code": "acq" } } ] }, { "ob_id": 5745, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 1730, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/5744/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/1003/?format=api", "relatedTo": { "ob_id": 5745, "uuid": "fe65340240cf466d904c0bf8ba35e16d", "short_code": "acq" } }, { "ob_id": 1731, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/5744/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/4778/?format=api", "relatedTo": { "ob_id": 5745, "uuid": "fe65340240cf466d904c0bf8ba35e16d", "short_code": "acq" } } ] }, { "ob_id": 5778, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 1750, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/1000/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/1003/?format=api", "relatedTo": { "ob_id": 5778, "uuid": "308e557d568942cdb2168ead70bc825c", "short_code": "acq" } } ] }, { "ob_id": 12234, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 5302, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/12233/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/1003/?format=api", "relatedTo": { "ob_id": 12234, "uuid": "a87b3ba6815a4935ae9c04d1766c84e9", "short_code": "acq" } } ] }, { "ob_id": 12236, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 5303, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/12235/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/1003/?format=api", "relatedTo": { "ob_id": 12236, "uuid": "80c29951379f46688b01d09f93153578", "short_code": "acq" } } ] }, { "ob_id": 31851, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 12390, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/31852/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/1003/?format=api", "relatedTo": { "ob_id": 31851, "uuid": "d445bcf8ebb349bea30631656e6717bc", "short_code": "acq" } }, { "ob_id": 12391, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/31852/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/4778/?format=api", "relatedTo": { "ob_id": 31851, "uuid": "d445bcf8ebb349bea30631656e6717bc", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/140583/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/140584/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/140598/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/140599/?format=api" ] }, { "ob_id": 31873, "computationComponent": [ { "ob_id": 31874, "uuid": "43f60a9940aa49c184ff890348dac088", "title": "UoL_FP: University of Leicester Full-Physics retrieval algorithm for retrieval of CO2 from TANSAT data", "abstract": "The University of Leicester Full-Physics Retrieval Algorithm (UoL-FP) is an optical estimation retrieval algorithm for TanSat (and other satellites). It is also known as OCFP as it was initially developed to work for the OCO (Orbiting Carbon Observatory) satellite, but has been adapted for other instruments.\r\n \r\nFor the CO2 Full Physics product, it utilises the O2-A absorption band along with the weak CO2 band located at 1.6 um respectively to retrieve XCO2 (the column-average dry-air mole fraction of atmospheric CO2). The explicit consideration of scattering by this approach reduces potential systematic biases due to clouds or aerosols.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 31875, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 12401, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/31876/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/31877/?format=api", "relatedTo": { "ob_id": 31875, "uuid": "ca5b979b19204cb19c7865ace44b6328", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/140732/?format=api" ] }, { "ob_id": 31954, "computationComponent": [ { "ob_id": 31952, "uuid": "73978b5dd534435abd858c94603661f5", "title": "Computation of altimeter coastal sea level anomalies based on the XTRACK/ALES processing", "abstract": "The altimeter coastal sea level anomalies products are based on the XTRACK/ALES processing. The products benefit from the spatial resolution provided by high-rate data, the Adaptive Leading Edge Subwaveform Retracker (ALES) and the post-processing strategy of the along-track (X-TRACK) algorithm, both developed for the processing of coastal altimetry data, as well as the best possible set of geophysical corrections. \r\n\r\nFor details of the processing see the Algorithm Theoretical Baseline Document in the linked documentation.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 31953, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 12404, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/30018/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/30019/?format=api", "relatedTo": { "ob_id": 31953, "uuid": "1a4fe170b116409bb7177cb098b7cb8f", "short_code": "acq" } }, { "ob_id": 12405, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/30020/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/30021/?format=api", "relatedTo": { "ob_id": 31953, "uuid": "1a4fe170b116409bb7177cb098b7cb8f", "short_code": "acq" } }, { "ob_id": 12406, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/30022/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/30023/?format=api", "relatedTo": { "ob_id": 31953, "uuid": "1a4fe170b116409bb7177cb098b7cb8f", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/141328/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/141329/?format=api" ] }, { "ob_id": 31991, "computationComponent": [ { "ob_id": 31990, "uuid": "4c9ae86990f24dd5bcfdb2eacc445d0b", "title": "Processing chain for the GERB-HR-ED01 rlut 1hrCM Obs4MIPS product", "abstract": "The GERB TOA outgoing longwave radiation (OLR) Obs4MIPs product has been generated from GERB level 2 HR OLR fluxes. There are three main stages. The first ingests the Edition 1 GERB HR OLR data and generates an area weighted flux product at 1° by 1° spatial resolution for every 15 minute time interval. In the second stage these data are averaged over time to produce an hourly averaged product. Each hour interval is defined as the time-centred mean at half-past the hour, e.g. 1030 UTC comprises of the mean of data from 1000 UTC, 1015 UTC, 1030 UTC and 1045 UTC (or from those slots in this window that are available). An hourly average is produced for a 1° by 1° grid cell if there is one or more observation from the four observation times available for that grid cell. The final processing stage averages the hourly mean fluxes over the days in the month to produce a one degree monthly mean product at hourly intervals. The number of data points (days per monthly hourly mean) contributing to each monthly mean are used to estimate the uncertainties associated with the product.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 25280, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 11379, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/2658/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/3853/?format=api", "relatedTo": { "ob_id": 25280, "uuid": "8b1f29db1c304ce2a849cc727f64ff0a", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/141664/?format=api" ] }, { "ob_id": 31994, "computationComponent": [ { "ob_id": 31993, "uuid": "eccc354ad6594ab19013a6cbd643034d", "title": "Processing chain for the GERB-HR-ED01 rsut 1hrCM Obs4MIPS product", "abstract": "The GERB TOA reflected shortwave radiation (RSW) Obs4MIPs product has been generated from GERB level 2 HR RSW fluxes. There are four main stages. The first is to take the Edition 1 GERB HR SW flux data with the user corrections applied and generate an albedo using knowledge of the incoming SW flux for each location and time. The albedo is then area weighted to create a 1° by 1° spatial resolution albedo for every 15 minute time interval. These data are then averaged over time to produce an hourly averaged albedo product for each day and converted back to TOA SW flux by multiplying the albedo by the incoming solar flux at the midpoint of the hour. Finally a monthly mean for each hourly time step is calculated. The number of data points (days per monthly hourly average) contributing to each monthly hourly mean are retained and are used to estimate the uncertainties associated with the product. For more detailed information please see: Bantges, R., Russell, J., & Brindley, H. (2021). GERB-HR-ED01 Top of atmosphere shortwave radiation monthly mean diurnal cycle product description. Zenodo. https://doi.org/10.5281/zenodo.4584631", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 25280, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 11379, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/2658/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/3853/?format=api", "relatedTo": { "ob_id": 25280, "uuid": "8b1f29db1c304ce2a849cc727f64ff0a", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/141678/?format=api" ] }, { "ob_id": 32009, "computationComponent": [ { "ob_id": 32010, "uuid": "5f1b78c424904c359c1c907b2bb176c2", "title": "Algorithm for the ESA Soil Moisture Climate Change Initiative, v05.2", "abstract": "The ESA Soil Moisture Climate Change Initiative is deriving information on soil moisture from active and passive satellite sensors. For information on the algorithm see the Algorithm Theoretical Baseline Document.", "keywords": "", "inputDescription": null, "outputDescription": null, "softwareReference": null, "identifier_set": [] } ], "acquisitionComponent": [ { "ob_id": 32011, "independentInstrument": [], "instrumentplatformpair_set": [ { "ob_id": 12407, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/8207/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/27121/?format=api", "relatedTo": { "ob_id": 32011, "uuid": "3b5a15073de0478ba33964ebb063ecb6", "short_code": "acq" } }, { "ob_id": 12408, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/8299/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/27121/?format=api", "relatedTo": { "ob_id": 32011, "uuid": "3b5a15073de0478ba33964ebb063ecb6", "short_code": "acq" } }, { "ob_id": 12409, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/7805/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/27122/?format=api", "relatedTo": { "ob_id": 32011, "uuid": "3b5a15073de0478ba33964ebb063ecb6", "short_code": "acq" } }, { "ob_id": 12410, "platform": "https://api.catalogue.ceda.ac.uk/api/v2/platforms/7813/?format=api", "instrument": "https://api.catalogue.ceda.ac.uk/api/v2/instruments/27122/?format=api", "relatedTo": { "ob_id": 32011, "uuid": "3b5a15073de0478ba33964ebb063ecb6", "short_code": "acq" } } ] } ], "identifier_set": [], "responsiblepartyinfo_set": [ "https://api.catalogue.ceda.ac.uk/api/v2/rpis/141777/?format=api", "https://api.catalogue.ceda.ac.uk/api/v2/rpis/141778/?format=api" ] } ] }