Observation List – Django REST framework

Get a list of Observation objects.

### Available end points:

- `/observations/` - Will list all Results in the database
- `/observations.json` - Will return all Results in json format. This can
also be achieved by using the accept header. `application/json`
- `/observations/<object_id>/` - Returns Results object with that id

### Available Methods:

- `GET`
- `HEAD`

### Available filters:

- `title`
- `uuid`
- `keywords`
- `status`
- `result_field`
- `discoveryKeywords`
- `updateFrequency`
- `nonGeographicFlag`
- `publicationState`
- `permissions`

### How to use filters:

These filters can be used like django query filters using __ for related model relationships.

- `/observations/?uuid=d594d53df2612bbd89c2e0e770b5c1a0`
- `/observations/?status=completed`
- `/observations/?results_field__dataPath__startswith=/neodc/esacci`
- `/observations/?discoveryKeywords__name=ESACCI`
- `/observations/?nonGeographicFlag=True`

Filters can be stacked to build an 'AND' relationship. E.g.

- `/observations/?publicationState__in=published,citable&nonGeographicFlag=True`
- `/observations/?publicationState__in=published,citable&discoveryKeyword__name=NDGO0003`

GET /api/v2/observations/?format=api&offset=9300

HTTP 200 OK
Allow: GET, HEAD, OPTIONS
Content-Type: application/json
Vary: Accept

{
    "count": 10253,
    "next": "https://api.catalogue.ceda.ac.uk/api/v2/observations/?format=api&limit=100&offset=9400",
    "previous": "https://api.catalogue.ceda.ac.uk/api/v2/observations/?format=api&limit=100&offset=9200",
    "results": [
        {
            "ob_id": 41094,
            "uuid": "75e787d0e6c54c65b85a03b3ec38e41a",
            "title": "FAAM C353 MEWS flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft",
            "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for MEWS FAAM Aircraft Project project.",
            "keywords": "MEWS, FAAM, airborne, atmospheric measurments",
            "publicationState": "published",
            "dataPublishedTime": "2023-11-27T16:00:52",
            "doiPublishedTime": null,
            "updateFrequency": "notPlanned",
            "status": "ongoing",
            "result_field": {
                "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/41093/?format=api",
                "dataPath": "/badc/faam/data/2023/c353-aug-22",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 7744361143,
                "numberOfFiles": 42,
                "fileFormat": "Data are netCDF and NASA-Ames formatted. Ancillary files may be plain ASCII or PDF formatted. Image files may be PNG formatted."
            },
            "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/11424/?format=api",
            "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/4309/?format=api",
            "nonGeographicFlag": false,
            "phenomena": [
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50967/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50969/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50970/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50971/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50973/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50978/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50979/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50982/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50983/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50984/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50985/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50986/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50987/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50988/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50989/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50990/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50991/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50992/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50993/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50994/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50995/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50996/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50997/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50998/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50999/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51000/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51001/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51002/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51003/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51004/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51005/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51006/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51007/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51008/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51009/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51010/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51011/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51012/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51013/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51014/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51015/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51016/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51017/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51018/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51019/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51020/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51021/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51022/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51023/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51024/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51025/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51026/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51027/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51028/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51029/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51030/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51031/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51032/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51033/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51034/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51035/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51036/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51037/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51038/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51039/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51040/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51041/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51042/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51044/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51045/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51054/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51055/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51056/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51057/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51058/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51059/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51060/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51061/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51062/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51063/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51064/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51065/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51066/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51067/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51068/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51069/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51070/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51071/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51072/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51073/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51074/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51075/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51076/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51077/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51078/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51079/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51080/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51081/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51082/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51083/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51084/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51087/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/54967/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/54971/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/54975/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/54976/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/60089/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/60090/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/60091/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/60092/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/60093/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/60094/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/60095/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/60096/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/60097/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/60098/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/60099/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/60100/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/60101/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/60102/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/60103/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/60104/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/60105/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/60106/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/60107/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/60108/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/60109/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/60110/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/60111/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/60112/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/60113/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/60114/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/60115/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/60116/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/60117/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/60118/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/60119/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/62669/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/62671/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/62678/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/73930/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/73931/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/73932/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/73933/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/73934/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/73935/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/73936/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/73937/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/73938/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/73939/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/73940/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/73941/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/73942/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/73943/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/73944/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/73945/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/73946/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/73947/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/73948/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/73949/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/73950/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/73951/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/73952/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/73953/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/73954/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/73955/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/73956/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/73957/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/73958/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/73959/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/73960/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/73961/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/73962/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/73963/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/73964/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/73965/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/73966/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/73967/?format=api"
            ],
            "dataLineage": "Data were collected by instrument scientists during the flight before preparation and delivery for archiving at the Centre for Environmental Data Analysis (CEDA).",
            "removedDataTime": null,
            "removedDataReason": "",
            "language": "English",
            "identifier_set": [],
            "projects": [
                "https://api.catalogue.ceda.ac.uk/api/v2/projects/41092/?format=api"
            ],
            "observationcollection_set": [
                "https://api.catalogue.ceda.ac.uk/api/v2/observationcollections/5782/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/observationcollections/41095/?format=api"
            ],
            "responsiblepartyinfo_set": [
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/199874/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/199875/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/199876/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/199877/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/199878/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/199879/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/199880/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/199881/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/199882/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/199883/?format=api"
            ],
            "procedureAcquisition": "https://api.catalogue.ceda.ac.uk/api/v2/acquisitions/41096/?format=api",
            "procedureCompositeProcess": null,
            "procedureComputation": null,
            "permissions": [
                {
                    "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/2522/?format=api",
                    "useLimitation": null,
                    "accessConstraints": null,
                    "accessCategory": "registered",
                    "accessRoles": null,
                    "label": "registered: None group",
                    "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                    "licenceClassifications": "any"
                }
            ],
            "discoveryKeywords": []
        },
        {
            "ob_id": 41099,
            "uuid": "4aa5d4d0a22443f4bc16b5ea7956dd33",
            "title": "FAAM C355 WESCON flight: Airborne atmospheric measurements from core and non-core instrument suites on board the BAE-146 aircraft",
            "abstract": "Airborne atmospheric measurements from core and non-core instrument suites data on board the FAAM BAE-146 aircraft collected for WESCON FAAM Aircraft Project project.",
            "keywords": "WESCON, FAAM, airborne, atmospheric measurments",
            "publicationState": "published",
            "dataPublishedTime": "2023-11-27T16:19:21",
            "doiPublishedTime": null,
            "updateFrequency": "notPlanned",
            "status": "ongoing",
            "result_field": {
                "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/41098/?format=api",
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            "title": "ESA Permafrost Climate Change Initiative (Permafrost_cci): Permafrost active layer thickness for the Northern Hemisphere, v4.0",
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            "uuid": "20ec12f5d1f94e99aff2ed796264ee65",
            "title": "ESA Permafrost Climate Change Initiative (Permafrost_cci): Permafrost Ground Temperature for the Northern Hemisphere, v4.0",
            "abstract": "This dataset contains v4.0 permafrost ground temperature data produced as part of the European Space Agency's (ESA) Climate Change Initiative (CCI) Permafrost project. It forms part of the third version of their Climate Research Data Package (CRDP v3). It is derived from a thermal model driven and constrained by satellite data. CRDPv3 covers the years from 1997 to 2021. Grid products of CDRP v3 are released in annual files, covering the start to the end of the Julian year. This corresponds to average annual ground temperatures and is provided for specific depths (surface, 1m, 2m, 5m , 10m). \r\n\r\nCase A: It covers the Northern Hemisphere (north of 30°) for the period 2003-2021 based on MODIS \r\nLand Surface temperature merged with downscaled ERA5 reanalysis near-surface air temperature data. \r\nCase B: It covers the Northern Hemisphere (north of 30°) for the period 1997-2002 based on downscaled \r\nERA5 reanalysis near-surface air temperature data which are bias-corrected with the Case A product for \r\nthe overlap period 2003-2021 using a pixel-specific statistics for each day of the year.",
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            "uuid": "8cd84a935fdf4e28b8f42b95ebeee657",
            "title": "EXSCALABAR optical data from SASSO project - Version 0",
            "abstract": "This dataset contains data from the University of Manchester EXtinction, SCattering and Absorption of Light for AirBorne Aerosol Research (EXSCALABAR) collected at the University of Exeter, between May and June 2019, and at the University of Manchester, between January 2020 as part of the Soot Aerodynamic Size Selection for Optical properties (SASSO) project. EXSCALABAR is a custom-built aerosol optical spectroscopy instrument. In this study, it was used to measure the absorption and extinction coefficients of particles at 405 nm and 660 nm. These data were then used to derive the refractive index of the aerosols.\r\nThis version 0 dataset contains light absorption/extinction coefficient at multiple wavelengths. The EXSCALABAR is operated by Met office scientists.",
            "keywords": "EXSCALABAR,aerosol absorption coefficient,aerosol extinction coefficient",
            "publicationState": "published",
            "dataPublishedTime": "2024-08-01T15:51:05",
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                "volume": 11300447,
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            "uuid": "180b9636108a46c99611a288f60bb894",
            "title": "Aerosol Mass Spectrometer (AMS) data from SASSO project- Version 0",
            "abstract": "This dataset contains real-time measurements organic aerosol mass concentration data from the University of Manchester Aerosol Mass Spectrometer (AMS). These data were collected at the University of Exeter, between May and June 2019 as part of the Soot Aerodynamic Size Selection for Optical properties (SASSO) project. Combined with the black carbon mass concentration measured by the Single Particle Soot Photometer (SP2), this information can be used to identify the burning phase (pyrolysis, flaming, or smouldering) in wood combustion experiments.\r\nThis version 0 dataset contains organic mass concentration. The AMS is operated by University of Manchester scientists.",
            "keywords": "AMS, Organic mass concentration, man-ams",
            "publicationState": "published",
            "dataPublishedTime": "2024-07-30T09:57:01",
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                "volume": 9767526,
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            "uuid": "3fa0152b55fd4a3b8357fdfcfc55f45d",
            "title": "NOx and O3 gas data from SASSO project - Version 0",
            "abstract": "This dataset contains data from the University of Manchester nitrogen oxides (NOx) monitor and ozone (O3) monitor collected at the University of Manchester, between January and February 2020 as part of the Soot Aerodynamic Size Selection for Optical properties (SASSO) project. The NOx and O3 concentrations inside the chamber were measured in real time during the experiment. \r\n\r\nNO, NO2, and NOx concentrations were measured using the NOx analyzer (Model 42i, Thermo Scientific), while O3 concentration was measured using the O3 analyzer (Model 49C, Thermo Scientific). These data reveal the conditions for each experiment.\r\n\r\nThis version 0 dataset contains NO, NO2, NOx and O3 concentration. The NOx monitor and O3 monitor are operated by University of Manchester scientists.",
            "keywords": "NOX, O3, SASSO",
            "publicationState": "published",
            "dataPublishedTime": "2024-08-01T15:57:38",
            "doiPublishedTime": null,
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                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 440773,
                "numberOfFiles": 5,
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            "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/11496/?format=api",
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            "nonGeographicFlag": true,
            "phenomena": [],
            "dataLineage": "Data were produced by the SASSO project and supplied for archiving at the Centre for Environmental Data Analysis (CEDA).",
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            "language": "English",
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            "projects": [
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            "observationcollection_set": [],
            "responsiblepartyinfo_set": [
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201312/?format=api",
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                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201315/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201316/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201317/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/202885/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201319/?format=api"
            ],
            "procedureAcquisition": "https://api.catalogue.ceda.ac.uk/api/v2/acquisitions/43067/?format=api",
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            "permissions": [
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        {
            "ob_id": 41353,
            "uuid": "a93252bc9a0a489c978d77b2b365e2e7",
            "title": "Scanning Mobility Particle Sizer (SMPS) data from SASSO project - Version 0",
            "abstract": "This dataset contains number size distribution of monodisperse secondary organic aerosols (SOA) data from the University of Manchester Scanning Mobility Particle Sizer (SMPS) collected at the University of Manchester, between January and February 2020 as part of the Soot Aerodynamic Size Selection for Optical properties (SASSO) project. These data were used to derive the refractive index of the SOA.\r\nThis version 0 dataset contains particle size distribution. The SMPS is operated by University of Manchester scientists.",
            "keywords": "SMPS, Size distribution, SASSO",
            "publicationState": "published",
            "dataPublishedTime": "2024-07-31T12:34:56",
            "doiPublishedTime": null,
            "updateFrequency": "notPlanned",
            "status": "completed",
            "result_field": {
                "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/41628/?format=api",
                "dataPath": "/badc/deposited2024/SASSO/SASSO_MAN_SMPS_LABdata",
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                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 5418,
                "numberOfFiles": 3,
                "fileFormat": "Data are BADC-CSV formatted"
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            "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/11497/?format=api",
            "geographicExtent": null,
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            "phenomena": [],
            "dataLineage": "Data were produced by the SASSO project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA).",
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            "language": "English",
            "identifier_set": [],
            "projects": [
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                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/202887/?format=api",
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                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201322/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201323/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201324/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201325/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201326/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201320/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201327/?format=api"
            ],
            "procedureAcquisition": "https://api.catalogue.ceda.ac.uk/api/v2/acquisitions/41354/?format=api",
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            "permissions": [
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        {
            "ob_id": 41356,
            "uuid": "25e39573126840d5bbb843902afc729b",
            "title": "Differential Mobility Particle Sizer (DMPS) data from SASSO project - Version 0",
            "abstract": "This dataset contains number size distribution data from the University of Manchester Differential Mobility Particle Sizer (DMPS). The custom-built DMPS measured the evolution of size distribution for polydisperse particles formed from the ozonolysis of α-pinene (13/01/2020) or cresol (10/01/2020) in the Manchester aerosol chamber. Additionally, similar measurements were conducted under the same conditions but with black carbon (BC) as the seed (23/01/2020: BC + α-pinene; 22/01/2020: BC + cresol). These data were collected at the University of Manchester, between January and February 2020 as part of the Soot Aerodynamic Size Selection for Optical properties (SASSO) project. This information can reveal the evolution of the particles inside the chamber.\r\n\r\nThis version 0 dataset contains particle size distribution. The DMPS is operated by University of Manchester scientists.",
            "keywords": "DMPS, Particle size distribution, SASSO",
            "publicationState": "published",
            "dataPublishedTime": "2024-09-04T14:08:17",
            "doiPublishedTime": null,
            "updateFrequency": "notPlanned",
            "status": "completed",
            "result_field": {
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                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 91925,
                "numberOfFiles": 5,
                "fileFormat": "Data are BADC-CSV formatted"
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            "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/11498/?format=api",
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            "dataLineage": "Data were produced by the SASSO project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA).",
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            "language": "English",
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            "responsiblepartyinfo_set": [
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201330/?format=api",
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                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201332/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201333/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201334/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201335/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201337/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/204556/?format=api"
            ],
            "procedureAcquisition": "https://api.catalogue.ceda.ac.uk/api/v2/acquisitions/41357/?format=api",
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            "ob_id": 41358,
            "uuid": "8175ede3a1d642deba8f4cce49d7bda8",
            "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column-averaged methane from Sentinel-5P, generated with the WFM-DOAS algorithm, version 1.8,  November 2017 - October 2023",
            "abstract": "This product is the column-average dry-air mole fraction of atmospheric methane, denoted XCH4. It has been retrieved from radiance measurements from the TROPOspheric Monitoring Instrument (TROPOMI) on the Sentinel-5 Precursor satellite in the 2.3 µm spectral range of the solar spectral range, using the Weighting Function Modified Differential Optical Absorption Spectroscopy (WFM-DOAS or WFMD) retrieval algorithm. This dataset is also referred to as CH4_S5P_WFMD. This version of the product is version 1.8, and covers the period from November 2017 - October 2023. \r\n\r\nThe WFMD algorithm is based on iteratively fitting a simulated radiance spectrum to the measured spectrum using a least-squares method. The algorithm is very fast as it is based on a radiative transfer model based look-up table scheme. The product is limited to cloud-free scenes on the Earth's day side.\r\n\r\nThese data were produced as part of the European Space Agency's (ESA) Greenhouse Gases (GHG) Climate Change Initiative (CCI) project.\r\n\r\nWhen citing this dataset, please also cite the following peer-reviewed publication:  \r\nSchneising, O., Buchwitz, M., Hachmeister, J., Vanselow, S., Reuter, M., Buschmann, M., Bovensmann, H., and Burrows, J. P.: Advances in retrieving XCH4 and XCO from Sentinel-5 Precursor: improvements in the scientific TROPOMI/WFMD algorithm, Atmos. Meas. Tech., 16, 669–694, https://doi.org/10.5194/amt-16-669-2023, 2023.",
            "keywords": "ESA, CCI, satellite, Sentinel-5 Precursor, TROPOMI, atmosphere, methane, carbon monoxide",
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            "dataPublishedTime": "2024-02-19T11:30:56",
            "doiPublishedTime": null,
            "updateFrequency": "notPlanned",
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                "dataPath": "/neodc/esacci/ghg/data/cci_plus/CH4_S5P_WFMD/v1.8",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 126935347162,
                "numberOfFiles": 2136,
                "fileFormat": "Data are in netCDF format."
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            "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/11555/?format=api",
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                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/74658/?format=api",
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                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/74660/?format=api"
            ],
            "dataLineage": "Data were processed by the ESA Climate Change Initiative (CCI) Greenhouse Gas project team and supplied to CEDA as part of the ESA CCI Open Data Portal.",
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            "ob_id": 41379,
            "uuid": "bd67917f85d54d80927ff0134120ccd9",
            "title": "ESA Snow Climate Change Initiative (Snow_cci): Snow Cover Fraction Viewable (SCFV) composite from AVHRR data of all platforms (1982 – 2022)",
            "abstract": "This dataset contains Daily Snow Cover Fraction of viewable snow from AVHRR, produced by the Snow project of the ESA Climate Change Initiative programme.  \r\n\r\nSnow cover fraction viewable (SCFV) indicates the area of snow viewable from space over land surfaces. In forested areas this refers to snow viewable on top of the forest canopy. The SCFV is given in percentage (%) per pixel. \r\n\r\nThe global SCFV product is available at about 5 km pixel size for all land areas, excluding Antarctica and Greenland ice sheets. The coastal zones of Greenland are included.\r\n\r\nThe SCFV time series provides daily products for the period 1982-2018. \r\n\r\nThe product is based on medium resolution optical satellite data from the Advanced Very High Resolution Radiometer (AVHRR). Clouds are masked using the Cloud CCI cloud v3.0 mask product. \r\n\r\nThe retrieval method of the snow_cci SCFV product from AVHRR data has been further developed and improved based on the ESA GlobSnow approach described by Metsämäki et al. (2015) and complemented with a pre- and post-classification module. All cloud free pixels are then used for the snow extent mapping, using spectral bands centred at about 0.630 µm and 1.61 µm (channel 3a or the reflective part of channel 3b (ref3b)), and an emissive band centred at about 10.8 µm. The snow_cci snow cover mapping algorithm is a three-step approach: first, a strict pre-classification is applied to identify all cloud free pixels which are certainly snow free. For all remaining pixels, the snow_cci SCFV retrieval method is applied.  Finally, a post-processing removes erroneous snow pixels caused either by falsely classified clouds in the tropics or by unreliable ref3b values at a global scale. \r\n\r\nThe following auxiliary data set is used for product generation: ESA CCI Land Cover from 2000; water bodies and permanent snow and ice areas are masked based on this dataset. Both classes were separately aggregated to the pixel spacing of the SCF product. Water areas are masked if more than 50 percent of the pixel is classified as water; permanent snow and ice areas are masked if more than 50 percent are identified as such areas in the aggregated map.\r\n\r\nThe SCFV product is aimed to serve the needs for users working in the cryosphere and climate research and monitoring activities, including the detection of variability and trends, climate modelling and aspects of hydrology, meteorology and biology.\r\n\r\nThe Remote Sensing Research Group of the University of Bern is responsible for the SCFV product development and generation. ENVEO developed and prepared all auxiliary data sets used for the product generation. \r\n\r\nThe SCFV AVHRR product comprises one longer data gap of 92 between November 1994 and January 1995, and 16 individual daily gaps, resulting in a 99% data coverage over the entire study period of 37 years.",
            "keywords": "ESA, CCI, Snow, Snow Cover Fraction",
            "publicationState": "working",
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            "updateFrequency": "notPlanned",
            "status": "underDevelopment",
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            "nonGeographicFlag": false,
            "phenomena": [],
            "dataLineage": "The snow_cci SCFV product based on AVHRR was developed and processed at the University of Bern in the frame of ESA CCI+ Snow project. The AVHRR baseline FCDR was pre-processed using pyGAC and pySTAT in the frame of the ESA CCI Cloud project (Devasthale et al. 2017, Stengel et al. 2020). \r\n\r\nThe final product is quality checked.",
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            "language": "English",
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                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201389/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201390/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201391/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201392/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201393/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201394/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201395/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201396/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201397/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201398/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201399/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201400/?format=api",
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            "procedureAcquisition": null,
            "procedureCompositeProcess": "https://api.catalogue.ceda.ac.uk/api/v2/composites/33470/?format=api",
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        {
            "ob_id": 41380,
            "uuid": "c32dae91c2884e0681d34e91c1bb9ad6",
            "title": "ESA Snow Climate Change Initiative (Snow_cci): Snow Cover Fraction on Ground (SCFG) composite from AVHRR data of all platforms (1982 – 2022)",
            "abstract": "This dataset contains Daily Snow Cover Fraction (snow on ground) from AVHRR, produced by the Snow project of the ESA Climate Change Initiative programme. \r\n\r\nSnow cover fraction on ground (SCFG) indicates the area of snow observed from space over land surfaces, in forested areas corrected for the transmissivity of the forest canopy. The SCFG is given in percentage (%) per pixel. \r\n\r\nThe global SCFG product is available at about 5 km pixel size for all land areas, excluding Antarctica and Greenland ice sheets. The coastal zones of Greenland are included.\r\n\r\nThe SCFG time series provides daily products for the period 1982-2018. \r\n\r\nThe product is based on medium resolution optical satellite data from the Advanced Very High Resolution Radiometer (AVHRR). Clouds are masked using the Cloud CCI cloud v3.0 mask product. \r\n\r\nThe retrieval method of the snow_cci SCFG product from AVHRR data has been further developed and improved based on the ESA GlobSnow approach described by Metsämäki et al. (2015) and complemented with a pre-classification module. All cloud free pixels are then used for the snow extent mapping, using spectral bands centred at about 0.63 µm and 1.61 µm (channel 3a or the reflective part of channel 3b (ref3b)), and an emissive band centred at about 10.8 µm. The snow_cci snow cover mapping algorithm is a three-step approach: first, a strict pre-classification is applied to identify all cloud free pixels which are certainly snow free. For all remaining pixels, the snow_cci SCFG retrieval method is applied. Finally, a post-processing removes erroneous snow pixels caused either by falsely classified clouds in the tropics or by unreliable ref3b values at a global scale. \r\n\r\nThe following auxiliary data sets are used for product generation: i) ESA CCI Land Cover from 2000; water bodies and permanent snow and ice areas are masked based on this dataset. Both classes were separately aggregated to the pixel spacing of the SCF product. Water areas are masked if more than 50 percent of the pixel is classified as water, permanent snow and ice areas are masked if more than 50 percent are identified as such areas in the aggregated map; ii) Forest canopy transmissivity map; this layer is based on the tree cover classes of the ESA CCI Land Cover 2000 data set and the tree cover density map from Landsat data for the year 2000 (Hansen et al., Science, 2013, DOI: 10.1126/science.1244693). This layer is used to apply a forest canopy correction and estimate in forested areas the fractional snow cover on ground.\r\n\r\nThe SCFG product is aimed to serve the needs of users working in cryosphere and climate research and monitoring activities, including the detection of variability and trends, climate modelling and aspects of hydrology, meteorology, and biology.\r\n\r\nThe Remote Sensing Research Group of the University of Bern is responsible for the SCFG product development and generation. ENVEO developed and prepared all auxiliary data sets used for the product generation.\r\n\r\nThe SCFG AVHRR product comprises one longer data gap of 92 between November 1994 and January 1995, and 16 individual daily gaps, resulting in a 99% data coverage over the entire study period of 37 years.",
            "keywords": "ESA, CCI, Snow, Snow Cover Fraction",
            "publicationState": "working",
            "dataPublishedTime": null,
            "doiPublishedTime": null,
            "updateFrequency": "notPlanned",
            "status": "underDevelopment",
            "result_field": null,
            "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/11204/?format=api",
            "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/2614/?format=api",
            "nonGeographicFlag": false,
            "phenomena": [],
            "dataLineage": "The snow_cci SCFG product based on AVHRR was developed and processed at the University of Bern in the frame of ESA CCI+ Snow project. The AVHRR baseline FCDR was pre-processed using pyGAC and pySTAT in the frame of the ESA CCI Cloud project (Devasthale et al. 2017, Stengel et al. 2020). \r\nThe final product is quality checked.\r\n\r\nData were produced by the project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA).",
            "removedDataTime": null,
            "removedDataReason": "",
            "language": "English",
            "identifier_set": [],
            "projects": [
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            "responsiblepartyinfo_set": [
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201402/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201403/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201404/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201405/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201406/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201407/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201408/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201409/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201410/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201411/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201412/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201413/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201414/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201415/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201416/?format=api"
            ],
            "procedureAcquisition": null,
            "procedureCompositeProcess": "https://api.catalogue.ceda.ac.uk/api/v2/composites/33471/?format=api",
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        {
            "ob_id": 41381,
            "uuid": "0c37b06d024d4f8eb6f7ffc0c66d3b4e",
            "title": "Wind speed and direction data from Gill sonic windmaster instrument at London Honor Oak Park Air Quality Supersite",
            "abstract": "One minute wind speed and wind direction data at 16m above ground level from a Gill Sonic Windmaster instruments at the London Honor Oak Park Air Quality Supersite (LHOP) for the Integrated Research Observation System for Clean Air (OSCA) project, 2021 onwards.",
            "keywords": "HOP,OSCA,London,wind",
            "publicationState": "published",
            "dataPublishedTime": "2024-02-12T10:15:05",
            "doiPublishedTime": null,
            "updateFrequency": "notPlanned",
            "status": "ongoing",
            "result_field": {
                "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/41461/?format=api",
                "dataPath": "/badc/osca/data/london/OSCA_LHOP_Sonic_Windmaster/",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 36999214,
                "numberOfFiles": 35,
                "fileFormat": "NetCDF"
            },
            "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/11513/?format=api",
            "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/4123/?format=api",
            "nonGeographicFlag": false,
            "phenomena": [
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/61969/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/75316/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/75317/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/75318/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/75319/?format=api"
            ],
            "dataLineage": "Data is saved directly from the instrument to the computer, before being transferred to the general database, where it is processed, automatically averaged over minute time intervals and flagged where data is suspect. Once complete, data is uploaded to CEDA for archiving.",
            "removedDataTime": null,
            "removedDataReason": "",
            "language": "English",
            "identifier_set": [],
            "projects": [
                "https://api.catalogue.ceda.ac.uk/api/v2/projects/37963/?format=api"
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                "https://api.catalogue.ceda.ac.uk/api/v2/observationcollections/37907/?format=api"
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            "responsiblepartyinfo_set": [
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                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201417/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201418/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201419/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201420/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201421/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201422/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201429/?format=api"
            ],
            "procedureAcquisition": "https://api.catalogue.ceda.ac.uk/api/v2/acquisitions/41386/?format=api",
            "procedureCompositeProcess": null,
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            "permissions": [
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                    "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/2522/?format=api",
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                    "label": "registered: None group",
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        {
            "ob_id": 41388,
            "uuid": "b82b58d085d0433b821f4ae31cb608de",
            "title": "HadISD: Global sub-daily, surface meteorological station data, 1931-2023, v3.4.0.2023f",
            "abstract": "This is version v3.4.0.2023f of Met Office Hadley Centre's Integrated Surface Database, HadISD. These data are global sub-daily surface meteorological data.\r\n\r\nThis update (v3.4.0.2023f) to HadISD corrects a long-standing bug which was discovered in autumn 2023 whereby the neighbour checks (and associated [un]flagging for some other tests) were not being implemented. For more details see the posts on the HadISD blog: https://hadisd.blogspot.com/2023/10/bug-in-buddy-checks.html & https://hadisd.blogspot.com/2024/01/hadisd-v3402023f-future-look.html\r\n\r\nThe quality controlled variables in this dataset are: temperature, dewpoint temperature, sea-level pressure, wind speed and direction, cloud data (total, low, mid and high level). Past significant weather and precipitation data are also included, but have not been quality controlled, so their quality and completeness cannot be guaranteed. Quality control flags and data values which have been removed during the quality control process are provided in the qc_flags and flagged_values fields, and ancillary data files show the station listing with a station listing with IDs, names and location information. \r\n\r\nThe data are provided as one NetCDF file per station. Files in the station_data folder station data files have the format \"station_code\"_HadISD_HadOBS_19310101-20240101_v3.4.1.2023f.nc. The station codes can be found under the docs tab. The station codes file has five columns as follows: 1) station code, 2) station name 3) station latitude 4) station longitude 5) station height.\r\n\r\nTo keep informed about updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nFor more detailed information e.g bug fixes, routine updates and other exploratory analysis, see the HadISD blog: http://hadisd.blogspot.co.uk/\r\n\r\nReferences:\r\nWhen using the dataset in a paper you must cite the following papers (see Docs for link to the publications) and this dataset (using the \"citable as\" reference) :\r\n\r\nDunn, R. J. H., (2019), HadISD version 3: monthly updates, Hadley Centre Technical Note.\r\n\r\nDunn, R. J. H., Willett, K. M., Parker, D. E., and Mitchell, L.: Expanding HadISD: quality-controlled, sub-daily station data from 1931, Geosci. Instrum. Method. Data Syst., 5, 473-491, doi:10.5194/gi-5-473-2016, 2016.\r\n\r\nDunn, R. J. H., et al. (2012), HadISD: A Quality Controlled global synoptic report database for selected variables at long-term stations from 1973-2011, Clim. Past, 8, 1649-1679, 2012, doi:10.5194/cp-8-1649-2012\r\n\r\nSmith, A., N. Lott, and R. Vose, 2011: The Integrated Surface Database: Recent Developments and Partnerships. Bulletin of the American Meteorological Society, 92, 704–708, doi:10.1175/2011BAMS3015.1\r\n\r\nFor a homogeneity assessment of HadISD please see this following reference\r\n\r\nDunn, R. J. H., K. M. Willett, C. P. Morice, and D. E. Parker. \"Pairwise homogeneity assessment of HadISD.\" Climate of the Past 10, no. 4 (2014): 1501-1522. doi:10.5194/cp-10-1501-2014, 2014.",
            "keywords": "HadISD, temperature, dewpoint, pressure, wind, speed, direction, cloud, precipitation",
            "publicationState": "citable",
            "dataPublishedTime": "2024-02-23T09:22:32",
            "doiPublishedTime": "2024-02-23T14:10:49",
            "updateFrequency": "notPlanned",
            "status": "superseded",
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                "dataPath": "/badc/ukmo-hadobs/data/insitu/MOHC/HadOBS/HadISD/subdaily/HadISDTable/r1/v3-4-0-2023f/",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 55510914661,
                "numberOfFiles": 9687,
                "fileFormat": "Data are NetCDF formatted."
            },
            "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/11514/?format=api",
            "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/529/?format=api",
            "nonGeographicFlag": false,
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                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/54778/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/54780/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/54781/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/54782/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/54783/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/54784/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/54785/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/54786/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/54787/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/54788/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/54789/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/54790/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/54791/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/54792/?format=api",
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                    "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
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                }
            ],
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        },
        {
            "ob_id": 41419,
            "uuid": "6068c32dd69c442881925607c0ddea7c",
            "title": "Global 3-D TOMCAT CTM Tropospheric Ozone Simulations",
            "abstract": "Global 3-D simulations of tropospheric ozone (TO3) from the TOMCAT chemical transport model (1996-2016) output at two satellite local solar overpass times (09.30 & 13.30 LST). The ozone data (2-daily overpass times) is provided as 3-D fields on the 2.8°×2.8° horizontal model grid. Atmospheric pressure (Pa) and temperature (K) have also included to provide vertical information on the ozone distribution up to 10 hPa. The ozone data has units of mass mixing ratio (1.0E-9). This work was undertaken primarily as long-term science activities of the NERC - National Centre for Earth Observation.",
            "keywords": "Tropospheric Ozone,Ozone,Air Quality,TOMCAT",
            "publicationState": "preview",
            "dataPublishedTime": null,
            "doiPublishedTime": null,
            "updateFrequency": "notPlanned",
            "status": "pending",
            "result_field": null,
            "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/11538/?format=api",
            "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/4130/?format=api",
            "nonGeographicFlag": false,
            "phenomena": [],
            "dataLineage": "These TOMCAT simulations are from the most recent version of the model building on the work of:\r\n\r\nChipperfield (2007): https://rmets.onlinelibrary.wiley.com/doi/10.1256/qj.05.51\r\nRichards et al. (2013): https://acp.copernicus.org/articles/13/2331/2013/\r\nMonks et al. (2017): https://gmd.copernicus.org/articles/10/3025/2017/\r\nRowlinson et al. (2019): https://acp.copernicus.org/articles/19/8669/2019/\r\n\r\nOverall, these TOMCAT simulations were produced by a project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA).",
            "removedDataTime": null,
            "removedDataReason": "",
            "language": "English",
            "identifier_set": [],
            "projects": [],
            "observationcollection_set": [],
            "responsiblepartyinfo_set": [
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201882/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201883/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201884/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201885/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201886/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201887/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201888/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201889/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201890/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201891/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201892/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201893/?format=api"
            ],
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        },
        {
            "ob_id": 41420,
            "uuid": "87afd9f974c6424290435bd9a418f71a",
            "title": "DCMEX: meteorological data from Langmuir ground station for the New Mexico field campaign 2022",
            "abstract": "Meteorological data was collected by the University of Manchester at Langmuir ground station in the Magdalena Mountains, New Mexico, between July and August 2022 as part of the Deep Convective Microphysics Experiment (DCMEX) project.\r\n\r\nThis dataset contains meteorological data from two ground meteorological stations. A Gill MaxiMet GMX600 meteorological station was installed at the Langmuir Laboratory main building (33.97495N, 107.18100W, ~3255 m) next to the Digitel aerosol filter sampler and provides measurements of wind speed, wind direction, temperature, humidity, pressure, and precipitation rate. A second meteorological station, a Vaisalla WTX536 meteorological station, was installed at the Langmuir Kiva-2 laboratory next to the Digitel aerosol filter sampler and provides measurements of wind speed, wind direction, temperature, humidity, pressure, and precipitation rate. The meteorological stations are supported by the University of Manchester scientists.",
            "keywords": "wind speed, wind direction, temperature, humidity, pressure, and precipitation",
            "publicationState": "citable",
            "dataPublishedTime": "2024-02-06T09:35:24",
            "doiPublishedTime": "2024-05-01T08:54:20.111494",
            "updateFrequency": "notPlanned",
            "status": "completed",
            "result_field": {
                "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/41432/?format=api",
                "dataPath": "/badc/dcmex/data/DCMEX2022_Ground_Met/",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 4333090,
                "numberOfFiles": 5,
                "fileFormat": "BADC-CSV"
            },
            "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/11544/?format=api",
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                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/84648/?format=api",
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                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/84650/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/84651/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/84652/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/84653/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/84654/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/84655/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/84656/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/84657/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/84658/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/84659/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/84660/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/84661/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/84662/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/84663/?format=api"
            ],
            "dataLineage": "Data were collected by the University of Manchester instrument scientist before preparation for archiving and delivery to CEDA.",
            "removedDataTime": null,
            "removedDataReason": "",
            "language": "English",
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                "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/12864/?format=api"
            ],
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                "https://api.catalogue.ceda.ac.uk/api/v2/projects/38131/?format=api"
            ],
            "observationcollection_set": [
                "https://api.catalogue.ceda.ac.uk/api/v2/observationcollections/38137/?format=api"
            ],
            "responsiblepartyinfo_set": [
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201894/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201895/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201896/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201897/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201898/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201899/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201904/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/202008/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201905/?format=api"
            ],
            "procedureAcquisition": "https://api.catalogue.ceda.ac.uk/api/v2/acquisitions/41430/?format=api",
            "procedureCompositeProcess": null,
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            "permissions": [
                {
                    "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/2526/?format=api",
                    "useLimitation": null,
                    "accessConstraints": null,
                    "accessCategory": "public",
                    "accessRoles": null,
                    "label": "public: None group",
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                }
            ],
            "discoveryKeywords": [
                {
                    "ob_id": 1138,
                    "name": "NDGO0003"
                }
            ]
        },
        {
            "ob_id": 41421,
            "uuid": "3acecae819b84507ad4d62f87cf35155",
            "title": "Met Office Wind-Driven Rain (WDR)",
            "abstract": "This dataset contains the annual index of wind-driven rain (sum of all wind-driven rain spells in each year) derived from the UK Climate Projections (UKCP18) for a range of future global warming levels provided on a 5 km British National Grid (BNG). The annual index is calculated for eight wall orientations corresponding to the cardinal and ordinal points of the compass. \r\n\r\nWind-driven rain occurs when falling rain is blown by a horizontal wind so that it falls diagonally towards the ground. The annual index of wind-driven rain is the sum of all wind-driven rain spells for a given wall orientation and time period. It’s measured as the volume of rain blown from a given direction in the absence of any obstructions, with units of litres per square metre per year.\r\n\r\nWind-driven rain is calculated from hourly weather and climate data using an industry-standard formula from ISO 15927–3:2009, which is based on the product of wind speed and rainfall totals. Wind-driven rain is only calculated if the wind would strike a given wall orientation. A wind-driven rain spell is defined as a wet period separated by at least 96 hours with little or no rain (below a threshold of 0.001 litres per m2 per hour).\r\n\r\nThe annual index of wind-driven rain is calculated for a baseline (historical) period of 1981-2000 (corresponding to 0.61°C warming) and for global warming levels of 2.0°C and 4.0°C above the pre-industrial period (defined as 1850-1900). The warming between the pre-industrial period and baseline is the average value from six datasets of global mean temperatures available on the Met Office Climate Dashboard: https://climate.metoffice.cloud/dashboard.html.\r\n\r\nThe magnitudes of 1 in 3 year wind-driven rain spells (i.e. wet spells that would be expected to occur, on average, once every three years) are used to divide the UK into four zones in Approved Document C of the buildings regulations. The magnitudes of 1 in 3 year wind-driven rain spells were calculated for the baseline period (1981-2000) and 20-year periods corresponding to 2°C and 4°C of warming. The magnitudes of all wet spells (here, sum of hourly values of the wind-driven rain metric, I) were calculated, and the largest wet spell in each year was found (in the accompanying report, the magnitude of a wet spell is given the symbol Is' [\"Is prime\"] and has units of litres per metre-squared per spell). For each time period, the largest spells in all years and ensemble members were pooled together. A Gumbel distribution was fitted to the pooled data and used to estimate the magnitude of the 1 in 3 year wet spells across the UK.\r\n\r\nWind-driven rain is required for buildings standards. It is a major source of moisture in walls. Areas subject to very high levels of wind-driven rain may not be suitable for cavity-wall insulation. Under certain circumstances, cavity-wall insulation can enhance the transfer of moisture through walls to the inside of a building causing mould and damp problems.",
            "keywords": "wind-driven rain, Met Office, UKCP18, DESNZ",
            "publicationState": "citable",
            "dataPublishedTime": "2025-01-09T13:49:29",
            "doiPublishedTime": "2025-01-20T09:37:35.881054",
            "updateFrequency": "",
            "status": "completed",
            "result_field": {
                "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/41582/?format=api",
                "dataPath": "/badc/deposited2023/wind_driven_rain",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 1049280170,
                "numberOfFiles": 40,
                "fileFormat": "The data are provided in NetCDF."
            },
            "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/11546/?format=api",
            "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/4137/?format=api",
            "nonGeographicFlag": false,
            "phenomena": [
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/6023/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/11484/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/11485/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/11486/?format=api",
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                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51185/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51186/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51187/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51188/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/51189/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/62353/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/75237/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/75238/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/75239/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/75240/?format=api"
            ],
            "dataLineage": "Wind-driven rain was derived from hourly climate data produced as part of the UKCP18 Local climate projections. Data were produced by the project team and supplied for archiving at the Centre for Environmental Data Analysis (CEDA).",
            "removedDataTime": null,
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            "language": "English",
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                "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/13224/?format=api"
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            ],
            "observationcollection_set": [
                "https://api.catalogue.ceda.ac.uk/api/v2/observationcollections/41667/?format=api"
            ],
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                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201917/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201907/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201908/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201909/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201910/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201911/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201912/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201913/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201906/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201914/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201915/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201916/?format=api"
            ],
            "procedureAcquisition": null,
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            "procedureComputation": "https://api.catalogue.ceda.ac.uk/api/v2/computations/41668/?format=api",
            "permissions": [
                {
                    "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/2526/?format=api",
                    "useLimitation": null,
                    "accessConstraints": null,
                    "accessCategory": "public",
                    "accessRoles": null,
                    "label": "public: None group",
                    "licenceURL": "http://www.nationalarchives.gov.uk/doc/open-government-licence/version/3/",
                    "licenceClassifications": "any"
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        },
        {
            "ob_id": 41425,
            "uuid": "c14874e943cc453a8e63ce5841ecc9b0",
            "title": "ESA Greenhouse Gases Climate Change Initiative (GHG_cci): Column-averaged methane from GOSAT-2, generated with the SRFP (RemoTeC) full physics retrieval algorithm (CH4_GO2_SRFP), version 2.0.2",
            "abstract": "This dataset contains column-averaged dry-air mole fractions (mixing ratios) of methane (XCH4). It has been produced using Near Infrared (NIR) and Shortwave Infrared (SWIR) spectra acquired from the Thermal and Near Infrared Sensor for Carbon Observations - Fourier Transform Spectrometer-2 (TANSO-FTS-2) onboard the Japanese Greenhouse gases Observing Satellite (GOSAT-2), using the Remote Sensing of Greenhouse Gases for Carbon Cycle Modeling (RemoTeC) SRON Full Physics (SRFP) retrieval algorithm. Results are provided for the individual GOSAT-2 spatial footprints.\r\n\r\nThese data have been produced as part of the European Space Agency (ESA)'s Climate Change Initiative (CCI) programme.",
            "keywords": "ESA, CCI, satellite, atmosphere, methane, CH4",
            "publicationState": "citable",
            "dataPublishedTime": "2024-02-19T12:06:18",
            "doiPublishedTime": "2024-03-08T09:45:59.256938",
            "updateFrequency": "notPlanned",
            "status": "completed",
            "result_field": {
                "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/41493/?format=api",
                "dataPath": "/neodc/esacci/ghg/data/cci_plus/CH4_GO2_SRFP/v2.0.2",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 2034850071,
                "numberOfFiles": 1001,
                "fileFormat": "The data are in netCDF format."
            },
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                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/66439/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/66440/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/66441/?format=api",
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                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/66444/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/66445/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/66446/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/66449/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/66450/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/66451/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/66452/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/66453/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/66454/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/66455/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/66456/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/66457/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/66458/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/66459/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/66461/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/66462/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/66463/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/66464/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/66465/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/66466/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/66467/?format=api"
            ],
            "dataLineage": "Data were processed by the ESA CCI GHG project team and supplied to CEDA as part of the ESA CCI Open Data Portal Project. These data have been produced as part of the European Space Agency (ESA)'s Climate Change Initiative (CCI+) programme.",
            "removedDataTime": null,
            "removedDataReason": "",
            "language": "English",
            "identifier_set": [
                "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/12849/?format=api"
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                "https://api.catalogue.ceda.ac.uk/api/v2/projects/13295/?format=api"
            ],
            "observationcollection_set": [
                "https://api.catalogue.ceda.ac.uk/api/v2/observationcollections/12808/?format=api"
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                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/202163/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201940/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201941/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201942/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201943/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201944/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201945/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201939/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201938/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/201950/?format=api"
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            "uuid": "77a0e1e3bcbb49a5b4c89fe9cc90a788",
            "title": "DCMEX: aerosol number-size distribution data from Langmuir ground station for the New Mexico field campaign 2022 - Version 1.0",
            "abstract": "Aerosol number-size distribution data collected by the University of Manchester at the Kiva-2 site at Langmuir ground station in the Magdalena Mountains, New Mexico, between July and August 2022 as part of the Deep Convective Microphysics Experiment (DCMEX) project. Instrument supplied by the National Centre for Atmospheric Science - Atmospheric Measurement and Observation Facility (NCAS-AMOF).\r\n\r\nThis version 1.0 dataset contains the aerosol size distribution data from the Kiva-2 site at Langmuir Laboratory. A GRIMM Optical Particle Counter (OPC) model 1.108 was installed at the Langmuir Laboratory Kiva-2 site (33.97495N, 107.18100W, ~3255 m). The GRIMM OPC was supported by AMOF and the University of Manchester scientists.",
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            "title": "BICEP/NCEO: Marine phytoplankton carbon OC-CCI v4.2 monthly composites, 9km resolution, 1998-2020 ",
            "abstract": "A spectrally-resolved photoacclimation model was unified with a primary production model that simulated photosynthesis as a function of irradiance using a two-parameter photosynthesis versus irradiance (P-I) function to estimate the carbon content of marine phytoplankton based on ocean-colour remote sensing products (Sathyendranath et al. 2020a and references therein for details). The photoacclimation model contains a maximum chlorophyll-to-carbon ratio for three different phytoplankton size classes (pico-, nano- and microphytoplankton) that was inferred from field data, as in Sathyendranath et al. (2020). \r\n\r\nData are provided as netCDF files containing carbon products for pico-, nano- and microphytoplankton (C_picophyto, C_nanophyto and C_microphyto, respectively, in mg C m-3) and the total phytoplankton community (C_phyto in mg C m-3) for the period of 1998 to 2020 at 9 km spatial resolution. Additional variables that were used for the calculation are also provided.",
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            "title": "BICEP/NCEO: Marine phytoplankton carbon OC-CCI v4.2 monthly composites, 9km resolution, 1998-2020",
            "abstract": "A spectrally-resolved photoacclimation model was unified with a primary production model that simulated photosynthesis as a function of irradiance using a two-parameter photosynthesis versus irradiance (P-I) function to estimate the carbon content of marine phytoplankton based on ocean-colour remote sensing products (Sathyendranath et al. 2020a and references therein for details). The photoacclimation model contains a maximum chlorophyll-to-carbon ratio for three different phytoplankton size classes (pico-, nano- and microphytoplankton) that was inferred from field data, as in Sathyendranath et al. (2020). \r\n\r\nData are provided as netCDF files containing carbon products for pico-, nano- and microphytoplankton (C_picophyto, C_nanophyto and C_microphyto, respectively, in mg C m-3) and the total phytoplankton community (C_phyto in mg C m-3) for the period of 1998 to 2020 at 9 km spatial resolution. Additional variables that were used for the calculation are also provided.",
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            "title": "BICEP/NCEO: Marine Phytoplankton Carbon OC-CCI v4.2 monthly composites, 9km resolution, 1998-2020",
            "abstract": "A spectrally-resolved photoacclimation model was unified with a primary production model that simulated photosynthesis as a function of irradiance using a two-parameter photosynthesis versus irradiance (P-I) function to estimate the carbon content of marine phytoplankton based on ocean-colour remote sensing products (Sathyendranath et al. 2020a and references therein for details). The photoacclimation model contains a maximum chlorophyll-to-carbon ratio for three different phytoplankton size classes (pico-, nano- and microphytoplankton) that was inferred from field data, as in Sathyendranath et al. (2020). \r\n\r\nData are provided as netCDF files containing carbon products for pico-, nano- and microphytoplankton (C_picophyto, C_nanophyto and C_microphyto, respectively, in mg C m-3) and the total phytoplankton community (C_phyto in mg C m-3) for the period of 1998 to 2020 at 9 km spatial resolution. Additional variables that were used for the calculation are also provided.",
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            "uuid": "d32244e674dd438ca4d321560daad755",
            "title": "ESA River Discharge Climate Change Initiative (RD_cci): Combined river discharge product, v1.0",
            "abstract": "This dataset contains river discharge (Q) data in cubic meters per second (m3/s) from the ESA Climate Change Initiative River Discharge project (RD_cci).\r\n\r\nThese river discharge time series have been computed at different locations by the combination of data derived from satellite altimeters and multispectral sensors. Two levels of combination are implemented based on the original products: Level-2, in which the data has been derived by merging multi-mission multispectral time series (called CM) and the water level product derived by radar altimeters (called Altimetry),  and Level-3, in which the river discharge products obtained from altimeters and multispectral sensors are used. The river discharges are derived following several approaches:\r\n\r\n1) L2 Merged river discharge:\r\n\r\na) COPULA Altimetry – CM: by a bivariate cumulative distribution function (CDF) which is applied between the multispectral indices and the water level from altimetry to get their joint probability distribution. \r\n\r\nb) RIDESAT Altimetry - CM: by a three-parameter non-linear relationship that merges the multispectral indices and the water level from altimetry\r\n\r\n\r\n2) L3 Merged river discharge:\r\n\r\na) Altimetry - CM cal_BestFIT: by the combination of river discharges obtained by the procedure of BestFIT applied to the multispectral and river discharges obtained by the altimetry through a weighted approach\r\n\r\nb) Altimetry – CM cal_Copula: by the combination of river discharges obtained by the procedure of Copula applied to the multispectral and river discharges obtained by the altimetry through a weighted approach\r\n\r\nc) Altimetry – CM uncal_CDF: by the combination of river discharges obtained by the procedure of CDF applied to the multispectral and the altimetry through a weighted approach",
            "keywords": "river discharge, CCI",
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            "title": "ESA River Discharge Climate Change Initiative (RD_cci): Multispectral indices-based River Discharge Product, v1.2",
            "abstract": "This dataset contains river discharge (Q) data in cubic meters per second (m3/s) from the ESA Climate Change Initiative River Discharge project (RD_cci).  \r\n\r\nThese river discharge time series have been computed at different locations from several satellite multispectral missions (Landsat-5, -7, -8, -9, MODIS Aqua, MODIS Terra, Sentinel-3 A/B OLCI, Sentinel-2 MSI). At each location, time series are provided for each available single sensor and then merged in a unique time series.  These multi-mission, multispectral time series are also referred to as CM.  The river discharges are derived following several approaches:\r\n\r\nCalibrated CM approach - best fit regression (cal-BestFit): by non-linear regression relationship between the multi-mission time series and the ground observed river discharge;\r\n\r\nCalibrated CM approach - copula regression (cal-copula): by a bivariate cumulative distribution function which is applied between the multi-mission time series and the ground observed river discharge to get their joint probability distribution;\r\n\r\nUncalibrated CM approach – CDF (uncal_CDF): by Cumulative Distribution Function curves calculated to generate the percentiles associated to the discharges from the reflectance time series.",
            "keywords": "river discharge, CCI, multispectral",
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                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/75234/?format=api"
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            "dataLineage": "Data were produced by the River Discharge CCI project, and supplied to CEDA for archiving as part of the CCI Open Data Portal.",
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                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/202102/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/202103/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/202104/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/205507/?format=api",
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                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/205511/?format=api",
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            "ob_id": 41458,
            "uuid": "44c930e1388f40728884fbdf7e28c109",
            "title": "ESA River Discharge Climate Change Initiative (RD_cci):  Altimetry-based River Discharge product, v1.0",
            "abstract": "This dataset comprises the altimetry-based river discharge (RD-ALTI) Climate Research Data Package (CRDP), derived from nadir radar altimeter missions by the ESA CCI River Discharge precursor project (RD_cci). \r\n\r\nIt provides long-term satellite river discharge (RD) time series at specified locations (defined in the \"Selection of river basins\" document, available at https://climate.esa.int/documents/2189/D2_CCI-Discharge-0004-RP_WP2_v1-1.pdf) River discharge (in m3/s) corresponds to the water volume passing through the river cross-section per unit of time. In this dataset, it is computed from a rating curve applied to long-term satellite altimeter water surface elevation (WSE) from https://catalogue.ceda.ac.uk/uuid/c5f0aa806ec444b4a4209b49efc4bb65. The rating curve is obtained by fitting the relationship between in-situ discharge and altimeter WSE with a power law following a Bayesian approach.",
            "keywords": "CCI, River Discharge, Altimeter",
            "publicationState": "citable",
            "dataPublishedTime": "2024-07-25T10:43:11",
            "doiPublishedTime": "2024-07-29T08:43:45",
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            "status": "completed",
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                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 6980385,
                "numberOfFiles": 101,
                "fileFormat": "Data are provided in both CSV and NetCDF format"
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            "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/11812/?format=api",
            "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/529/?format=api",
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                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/75233/?format=api"
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            "dataLineage": "Data were produced by the River Discharge CCI precursor project team, comprising Hydro Matters, LEGOS, and EOLA.\r\n\r\nData were supplied for archiving at the Centre for Environmental Data Analysis (CEDA) as part of the CCI Open Data Portal in the context of the CCI Knowledge Exchange Project.",
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                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/204540/?format=api",
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        {
            "ob_id": 41468,
            "uuid": "9c82a38dff8940b594fbbb939cf4b1eb",
            "title": "Deforestation and Climate Change scenarios with a regional climate model over Borneo (2005 – 2100).",
            "abstract": "This dataset contains simulations of the climate scenario RCP8.5 with and without total deforestation using the regional climate model RegCM4. The output was then used for calculations of the Fire Weather Index, and that data is also included. \r\nThe data is in two main formats: netcdf files from the regional climate model, and the txt files with Fire Weather Index. \r\nThe time periods covered are: \r\n2010 – 2029 RCP8.5, Control Land cover \r\n2010 – 2029 RCP8.5, Deforested Land cover\r\n2081 – 2099 RCP8.5, Control Land cover\r\n2081 – 2099 RCP8.5, Deforested Land cover\r\nThe last 15 years of each simulation was used. Each simulation was run for each initial conditions and boundary conditions of the models: HadGEM2-ES, MPI-ESM-MR, CSIRO-MK36, IPSL-CM5A-LR, CNRM-CM5, CanESM2, giving a total of 24 simulations.\r\n\r\nThese data are used in the paper, “Future Fire risk under Climate Change and Deforestation Scenarios in Tropical Borneo”. Davies-Barnard et al, 2023.",
            "keywords": "Regional climate model,fire,deforestation,Borneo,tropical deforestation and climate change",
            "publicationState": "preview",
            "dataPublishedTime": null,
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            "updateFrequency": "notPlanned",
            "status": "ongoing",
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                "volume": 56467817667,
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            "title": "Chamber reaction products identified from toluene/m-xylene oxidation using GCxGC TOFMS at the University of Birmingham",
            "abstract": "A list of reaction products from the  photo-oxidation of m-xylene and toluene in chamber experiments for the  Quantitative Attribution of Secondary Organic Aerosol in Beijing to its Precursors project which was  part of the Air Pollution and Human Health in Developing Megacities programme.\r\n\r\nA potential aerosol mass (PAM) chamber was used to investigate the oxidised products from the photo-oxidation of m-xylene and toluene. The chamber experiments were carried out with hydroxyl (OH) radical as oxidant in both high- and low-NOx conditions and the resultant aerosol samples were collected using quartz filters and analysed by the two dimensional Gas Chromatography Time-Of-Flight Mass Spectrometry (GC×GC-TOFMS) at the University of Birmingham.",
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            "ob_id": 41499,
            "uuid": "43eeb6248d7f435da2300edb34cc4bea",
            "title": "Daily Colour and Intensity Georeferenced Orthophotos of the Cliff and Beach at Happisburgh, Norfolk, UK (April-December 2019) version 2.",
            "abstract": "This dataset contains georeferenced orthophotos collected daily along a 450 metre coastal stretch at Happisburgh, UK, over a time span of 9 months (April 6, 2019 to December 23, 2019). The dataset contains 190 colour images and 190 intensity images in GEOTIFF format. The orthophotos are produced by projection of LiDAR (Light Detection And Ranging) scans of the coastal stretch. There are 190 images out of a possible 262 days, since only days when scans were performed from two locations are included, which did not happen every day due to weather conditions. The orthophotos are point-cloud renders of the scan data created using ScanLAB's proprietary point-cloud rendering engine. The colour orthophotos are rendered using the colour information projected onto the scan during post-process colourisation. The intensity orthophotos are rendered using the intensity data for each scan. The orthophotos are rendered using an orthographic virtual camera which frames the useful extents of the scan data and is orientated such that the rendered orthophoto is \"north-up\". The orthophotos are georeferenced using pythons GDAL library and ground-truth GPS measurements taken at the two TLS positions onsite. The procedure for this follows; 1) the ground-truth GPS positions were converted from OSGB 1936 / British National Grid to Latitude and Longitude., 2) The pixel resolution of the orthophotos was calculated from the pixel position of the two TLS in the orthophotos and the two ground truth GPS positions., 3) The GPS position of the top left pixel of the orthophoto was calculated using pixel position of a TLS and the pixel resolution., 4) A python script using the GDAL library applied the GPS metadata to the orthophoto and saved it in GEOTIFF format. These data were collected to better understand the dynamic of beach-cliff and shore platform interaction along soft cliffed coasts. This research was funded by the UK Natural Environment Research Council (NE/M004996/1; BLUE-coast project). The on-location LiDAR Scanning and Technical R&D operated by ScanLAB Projects Ltd was funded by Innovate UK's Audience of the Future Program (Multiscale 3D Scanning with Framerate for TV and Immersive Applications project). The first 6 months of LiDAR scans (April to September 2019) were funded by Innovate UK, and this project was continued by the NERC BLUE-coast funding for the last 3 months (October to December 2019). The files were re-submitted and this DOI represents the second version of the data.",
            "keywords": "",
            "publicationState": "citable",
            "dataPublishedTime": "2024-02-16T14:45:28",
            "doiPublishedTime": "2024-02-16T14:45:28",
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            "status": "completed",
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                "volume": 897,
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            "dataLineage": "The data are archived on the British Oceanographic Data Centre (BODC)'s space at the Centre for Environmental Data Analysis (CEDA) and assigned a DOI. No quality control procedures were applied by BODC.",
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                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/202225/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/202226/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/202227/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/202224/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/202223/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/202228/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/202229/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/202230/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/202231/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/202232/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/202233/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/202234/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/202235/?format=api"
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        {
            "ob_id": 41500,
            "uuid": "e652f0109f21401680bc3c0ac834a96e",
            "title": "Hydro-JULES: Global high-resolution drought datasets from 1981-2022 - Amendment to CHIRPS_GLEAM subset",
            "abstract": "This is a revised version of the Climate Hazards group InfraRed Precipitation with Station data (CHIRPS) Global Land Evaporation Amsterdam Model (GLEAM) data from the Hydro-JULES: Global high-resolution drought dataset (doi:10.5285/ac43da11867243a1bb414e1637802dec).\r\n\r\nThis version corrects some errors found in the previous version due to the model run errors in some areas.  The model has been re-run to accurately produce the dataset. \r\n\r\nThese are global scale high-resolution drought indices developed from a combination of precipitation and potential evapotranspiration datasets for the Hydro-JULES project. Climate Hazards group InfraRed Precipitation with Station data (CHIRPS), Multi-Source Weighted-Ensemble Precipitation (MSWEP) precipitation estimates, Global Land Evaporation Amsterdam Model (GLEAM) and Bristol Hourly potential evapotranspiration (hPET) estimates were used. The drought index is developed using the Standardized Precipitation-Evapotranspiration Index (SPEI). These high-resolution global scale drought indices are available from 1981-2022 at a monthly and 5km spatial resolution. The SPEI indices are available from 1-48 months. The datasets provide valuable information for the study and analysis of droughts at much higher resolution from global to local scale.  \r\n\r\nThese data were produced for Hydro-Jules (NE/S017380/1) and REACH (Foreign, Commonwealth and Development Office): Programme Code 201880.",
            "keywords": "NE/S017380/1, drought",
            "publicationState": "published",
            "dataPublishedTime": "2024-03-21T13:41:15",
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                "storageStatus": "online",
                "volume": 358190874903,
                "numberOfFiles": 98,
                "fileFormat": "NetCDF"
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                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/63233/?format=api"
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            "dataLineage": "Data were generated using Standardized Precipitation-Evapotranspiration Index (SPEI) at 5km horizontal resolution over the domain 180W-180E, 55S-85N. The dataset is available in NetCDF format.  Data were produced by the project team before uploading to CEDA.\r\nThis data is a replacement version of the Climate Hazards group InfraRed Precipitation with Station data (CHIRPS) Global Land Evaporation Amsterdam Model (GLEAM) section of the Hydro-JULES: Global high-resolution drought datasets from 1981-2022 (https://catalogue.ceda.ac.uk/uuid/ac43da11867243a1bb414e1637802dec/) following the post-publication identification of an error in the model run.",
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                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/202240/?format=api",
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