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=5100
HTTP 200 OK
Allow: GET, HEAD, OPTIONS
Content-Type: application/json
Vary: Accept

{
    "count": 10256,
    "next": "https://api.catalogue.ceda.ac.uk/api/v2/observations/?format=api&limit=100&offset=5200",
    "previous": "https://api.catalogue.ceda.ac.uk/api/v2/observations/?format=api&limit=100&offset=5000",
    "results": [
        {
            "ob_id": 24798,
            "uuid": "00d1b3dc5f8748078b028d140422ae57",
            "title": "FAAM C012 Instrument Test 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 FAAM Test, Calibration, Training and Non-science Flights and other non-specified flight projects (Instrument) project.",
            "keywords": "Instrument, FAAM, airborne, atmospheric measurments",
            "publicationState": "published",
            "dataPublishedTime": "2017-06-07T10:46:25.625087",
            "doiPublishedTime": null,
            "updateFrequency": "asNeeded",
            "status": "ongoing",
            "result_field": {
                "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/24797/?format=api",
                "dataPath": "/badc/faam/data/2017/c012-may-11",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 825310977,
                "numberOfFiles": 29,
                "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/6721/?format=api",
            "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/4264/?format=api",
            "nonGeographicFlag": false,
            "phenomena": [
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3220/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3221/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3222/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3223/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3224/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3225/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3226/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3227/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3228/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3229/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3230/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3231/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3232/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3233/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3234/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3235/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3236/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3237/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3238/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3239/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3240/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3241/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3242/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3243/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3244/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3245/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3246/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3247/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3248/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3249/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3250/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3251/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3252/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3253/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3254/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3255/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3256/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3257/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3258/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3259/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3260/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3261/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3262/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3263/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3264/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3265/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3266/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3267/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3268/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3269/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3270/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3271/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3272/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3273/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3274/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3275/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3276/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3277/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3278/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3279/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3280/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3281/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3282/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3283/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3284/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3285/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3286/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3287/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3288/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3289/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3290/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3291/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3292/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3293/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3294/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/3295/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/14474/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/14836/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/14837/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/14838/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/14839/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/14840/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/14841/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/14842/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/14843/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/14845/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/14846/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/14847/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/14848/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/14849/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/14850/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/14851/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/14857/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/14916/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/14917/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/14919/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/14921/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/14924/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/14926/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/14927/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/14928/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/14931/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/14946/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/14947/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15161/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15163/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15166/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15167/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15168/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15169/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15170/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15171/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15172/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15173/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15174/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15175/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15176/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15177/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15178/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15179/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15180/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15182/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15185/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15188/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15189/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15192/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15193/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15194/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15195/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15196/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15197/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15198/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15200/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15203/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15204/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15208/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15210/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15211/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15212/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15213/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15220/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15223/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15241/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15242/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15243/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15244/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15245/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15246/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15247/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15248/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15249/?format=api",
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                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15252/?format=api",
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                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15330/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15331/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15332/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15333/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15334/?format=api",
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                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15336/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15337/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15338/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15339/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15340/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15341/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15342/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15343/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15344/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15345/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15346/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15347/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15800/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15801/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15810/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15811/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15814/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15815/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15824/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15825/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15831/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15833/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/15834/?format=api",
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        {
            "ob_id": 24807,
            "uuid": "a3614fb00ff74999a5187d3a3767d96d",
            "title": "Soil-atmosphere flux measurements calculated from concentration of methane and nitrous oxide taken from the Pastaza-Marañón foreland basin, Peru",
            "abstract": "The research team collected data on soil-atmosphere exchange of trace gases and environmental variables during four field campaigns (two wet seasons, two dry seasons) the lowland tropical peatland forests of the Pastaza-Marañón foreland basin in Peru. The campaigns took place over a 27 month period, extending from February 2012 to May 2014. \r\n\r\nThis dataset contains measurements from field sampling of soil-atmosphere fluxes concentrated on 4 dominant vegetation types in the lowland tropical peatland forests of the Pastaza-Marañón foreland basin. Vegetation types included; forested vegetation, forested [short pole] vegetation, Mauritia flexuosa-dominated palm swamp, and mixed palm swamp. They were measured at 5 different sites in Peru including; Buena Vista, Miraflores, San Jorge, Quistococha, and Charo.    \r\n\r\nGreenhouse gas (GHG) fluxes were captured from both floodplain systems and nutrient-poor bogs in order to account for underlying differences in biogeochemistry that may arise from variations in hydrology.\r\n\r\nParameters include methane and nitrous oxide fluxes, air/soil temperatures, soil pH, soil electrical conductivity, soil dissolved oxygen content, and water table depth. \r\n\r\nSee documentation and data lineage for data quality. \r\n\r\nThese data were collected in support of the NERC project: Amazonian peatlands - A potentially important but poorly characterised source of atmospheric methane and nitrous oxide (NE/I015469/2)",
            "keywords": "methane, nitrous oxide, peat, tropical peatland,  Pastaza-Marañón foreland basin, Amazonia, Peru",
            "publicationState": "citable",
            "dataPublishedTime": "2017-07-24T16:13:44",
            "doiPublishedTime": "2017-08-25T11:00:23",
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                "volume": 161215,
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            ],
            "dataLineage": "Gas samples were collected using a static chamber approach, samples stored in vials (Exetainers), and later analysed using a gas chromatograph with flame ionisation detector for methane detection and an electron capture detector for nitrous oxide quantification. Environmental variables were collected concomitantly, including air temperature, soil temperature, soil pH, soil electrical conductivity, soil dissolved oxygen content, and water table depth. Temperature was determined using a thermocouple; pH, electrical conductivity, and dissolved oxygen using a HACH® rugged outdoor HQ30D multi meter and pH, LDO or EC probe. Water table depth was measured using a depth measure. \r\n\r\nDiffusive gas fluxes were determined by using the JMP IN version 11 (SAS Institute, Inc., Cary, North Carolina, USA) statistical package to plot best-fit lines to the data for headspace concentration against time for individual flux chambers, with fluxes calculated from linear or non-linear regressions depending on the individual concentration trend against time. Gas mixing ratios (ppm) were converted to areal fluxes by using the Ideal Gas Law to solve for the quantity of gas in the headspace (on a mole or mass basis) and normalized by the surface area of each static flux chamber. Ebullition-derived methane fluxes were also quantified in our chambers where evidence of ebullition was found. This evidence consisted of either: (i) rapid, non-linear increases in methane concentration over time; (ii) abrupt, stochastic increases in methane concentration over time; or (iii) an abrupt stochastic increase in methane concentration, followed by a linear decline in concentration. For observations following pattern (i), flux was calculated by fitting a quadratic regression equation to the data (P < 0.05), and methane flux determined from the initial steep rise in CH4 concentration. For data following pattern (ii), the ebullition rate was determined by calculating the total methane production over the course of the bubble event, in-line with prior work conducted by the investigators. Last, for data following pattern (iii), a best-fit line was plotted to the methane concentration data after the bubble event, and a net rate of methane uptake calculated from the gradient of the line. Observations following patterns (i) and (ii) were categorized as “ebullition” (i.e. net efflux) whereas observations following pattern (iii) were categorized as “ebullition-driven methane uptake” (i.e. net influx). \r\n\r\nFlux data were removed (i.e. filtered) from the dataset if: (i) the change in gas concentration over time was not found to be statistically significant (alpha level of 0.05); (ii) evidence were found that an individual static flux chamber was not gas-tight (evidenced by a negative carbon dioxide flux); (iii) evidence were found that two or more Exetainers had been compromised by incomplete evacuation or leakage; or (iv) other evidence that an individual flux chamber had been compromised (e.g. evidence from field observations that the static flux chamber had been disturbed during the measurement process).",
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            "ob_id": 24809,
            "uuid": "88f3a3de77354692aeada98c5dad599b",
            "title": "APHH: Atmospheric dispersion model footprint plots made at the IAP-Beijing site during the summer and winter campaigns",
            "abstract": "The Met Office's Numerical Atmospheric-dispersion Modelling Environment (NAME) was used at the University of Leicester to produce atmospheric dispersion footprints centred on Beijing for use by the projects under the Atmospheric Pollution & Human Health in a Chinese Megacity (APHH) programme. These footprints are created by model runs in which thousands of particles are released from the chosen location and are tracked backwards in time.",
            "keywords": "APHH, NAME, dispersion, Beijing",
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                "volume": 61558635435,
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                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/22387/?format=api"
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            "dataLineage": "Data produced by APHH project participants at University of Leicester and uploaded to CEDA archive",
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            "ob_id": 24811,
            "uuid": "95809f64ed7f41329cadae3f41906b55",
            "title": "ESA Antarctic Ice Sheet Climate Change Initiative (Antarctic_Ice_Sheet_cci): Grounding Line Locations for the Ferringo, Pine Island, Thwaites, Smith, Kohler and Pope Glaciers, Antarctica, 1995-2017, v2.0",
            "abstract": "Grounding line locations (GLL) data for the Ferringo, Pine Island, Thwaites, Smith, Kohler and Pope Glaciers in Antarctica, produced by the ESA Antarctic Ice Sheet Climate Change Initiative (CCI) project. The grounding lines  have been derived from satellite observations from the ERS-1/2 and Copernicus Sentinel-1 instruments, acquired in the period from 1995-2017.",
            "keywords": "Antarctica, ice sheets, glaciers, grounding line location",
            "publicationState": "removed",
            "dataPublishedTime": "2017-04-27T23:00:00",
            "doiPublishedTime": null,
            "updateFrequency": "notPlanned",
            "status": "deprecated",
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                "dataPath": "/neodc/esacci/ice_sheets_antarctica/data/grounding_line_locations/Ferrigno_PineIS_Thwaites_Smith_Pope_Kohler/v2.0/",
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                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 1128,
                "numberOfFiles": 1,
                "fileFormat": "ESRI shapefile, KML and WKT in textfile (CSV)"
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            "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/6725/?format=api",
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            "title": "ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): Ancillary data used for the \"Active\", \"Passive\" and \"Combined\" products, Version 03.2",
            "abstract": "These ancillary datasets were used in the production of the \"Active\", \"Passive\" and \"Combined\" soil moisture data products, created as part of the European Space Agency's (ESA) Soil Moisture Climate Change Initiative (CCI) project. The set of ancillary datasets include datasets of Average Vegetation Optical Depth data from AMSR-E, Soil Porosity, Topographic Complexity and Wetland fraction, as well as a Land Mask.  This version of the ancillary datasets were used in the production of the v03.2 Soil Moisture CCI data.\r\n\r\nThe \"Active\" \"Passive\" and \"Combined\" soil moisture products which they were used in the development of are fusions of scatterometer and radiometer soil moisture products, derived from the AMI-WS, ASCAT, SMMR, SSM/I, TMI, AMSR-E, WindSat, AMSR2 and SMOS satellite instruments. To access these products or for further details on them please see their dataset records. Additional reference documents and information relating to them can also be found on the CCI Soil Moisture project website.\r\n\r\nSoil moisture CCI data should be cited using all three of the following references:\r\n\r\n1. Dorigo, W.A., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A., Haas, E., Hamer, D. P. Hirschi, M., Ikonen, J., De Jeu, R. Kidd, R. Lahoz, W., Liu, Y.Y., Miralles, D., Lecomte, P. (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. In Remote Sensing of Environment, 2017, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2017.07.001\r\n\r\n2. Gruber, A., Dorigo, W. A., Crow, W., Wagner W. (2017). Triple Collocation-Based Merging of Satellite Soil Moisture Retrievals. IEEE Transactions on Geoscience and Remote Sensing. PP. 1-13. 10.1109/TGRS.2017.2734070\r\n\r\n3. Liu, Y.Y., Dorigo, W.A., Parinussa, R.M., de Jeu, R.A.M. , Wagner, W., McCabe, M.F., Evans, J.P., van Dijk, A.I.J.M. (2012). Trend-preserving blending of passive and active microwave soil moisture retrievals, Remote Sensing of Environment, 123, 280-297, doi: 10.1016/j.rse.2012.03.014",
            "keywords": "ESA, Soil Moisture, CCI, Ancillary",
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            "title": "Poles Apart: Why has Antarctic sea ice increased and why don't coupled climate models reproduce observations, climate model data",
            "abstract": "Data produced in support of the NERC project Poles Apart (2014 - 2017) that investigated the atmospheric drivers of changes in surface wind forcing using the UK Chemistry and Aerosols (UKCA) model. \r\n\r\nTen HadGEM3 model simulations were undertaken. Monthly model data was taken from the final 30 years of each simulation and a number of variables of interest, e.g. temperature and precipitation were extracted and analysed. \r\n\r\nThe temporal range for the perturbed simulations is 1980-2013, and the control simulations are valid between 1841-1900.\r\n\r\nSee the detailed experiment documentation for the Unified Model experiment ids and their corresponding description (these have been used to organise the data).",
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            "title": "Cloud Index retrievals from MIPAS ENVISAT L1B using MIPclouds algorithm",
            "abstract": "This data set contains retrievals from  Michelson Interferometer for Passive Atmospheric Sounding on Envisat  (MIPAS-ENVISAT) cloud and aerosol  and  contains information on derived cloud-top height (km), cloud-top temperature (K), cloud extinction (cm-1), with uncertainties. It also includes the measured radiance in the three cloud microwindow bands (832.0-834.4 cm-1, 1232.3-1234.4 cm-1, 1973.0-1983.0 cm-1), with noise equivalent spectral radiance values. Cloud index values are also included which can be used to distinguish different clouds types based on the index value.",
            "keywords": "MIPAS, Cloud Index, ENVISAT, cloud-top, cloud extinction",
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            "title": "HadCRUT4: gridded dataset of global historical surface temperature anomalies, version 4.5.0.0",
            "abstract": "This is the HadCRUT.4.5.0.0 version of the HadCRUT4 data. \r\n\r\nData are available for each month since January 1850, on a 5 degree grid. \r\nThe gridded data are a blend of the CRUTEM4 land-surface air temperature dataset and the HadSST3 sea-surface temperature (SST) dataset. The dataset is presented as an ensemble of 100 dataset realisations that sample the distribution of uncertainty in the global temperature record. \r\n\r\nThe data consist of 100 ensemble members and the ensemble median, each are available as a separate file where the fourth component of the filename denotes the ensemble member or median. In addition, the variance information is provided under the name uncorrelated. Full error covariance data are available from the Met Office (see the link to the HadCRUT4 homepage in Docs) \r\n\r\nTo keep up to date with updates, news and announcements follow the HadOBS team on twitter @metofficeHadOBS.\r\n\r\nReferences:\r\nWhen using the dataset in a paper you must cite the following paper (see Docs for link to the publication) and this dataset (using the \"citable as\" reference) :\r\n\r\nMorice, C. P., J. J. Kennedy, N. A. Rayner, and P. D. Jones (2012), Quantifying uncertainties in global and regional temperature change using an ensemble of observational estimates: The HadCRUT4 dataset, J. Geophys. Res., 117, D08101, doi:10.1029/2011JD017187",
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            "title": "__MUST_UPDATE__20170818174601__ Atmospheric Retrievals from MIPAS/Envisat at Oxford v1.2",
            "abstract": "This dataset contains atmospheric profiles from the Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) on Envisat, processed with the Oxford L2 retrieval algorithm MORSE. This differs from the European Space Agency L2 products in that it uses an optimal estimation approach rather than a regularised least squares fit, and has additional molecules.\r\n\r\nThe dataset was produced by Anu Dudhia, University of Oxford and National Centre for Earth Observation (NCEO).",
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            "title": "Measurements of N2O5, ClNO2, HCOOH, HNO3 and HCN at the Weybourne Atmospheric Observatory",
            "abstract": "Chemical ionisation mass spectrometer (CIMS) measurements of N2O5, ClNO2 and other halogenated species to understand the overall oxidation budget at the Weybourne Atmospheric Observatory rural marine site.\r\n\r\n",
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            "title": "Met Éireann LIDARNET Knock Airport Vaisala CL31 ceilometer cloud base and backscatter data",
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            "abstract": "This dataset contains O3, CO, NO, NO2, NOy and SO2 measurements made at the IAP-Beijing site during the summer and winter APHH-Beijing campaign for the Atmospheric Pollution & Human Health in a Chinese Megacity (APHH) programme.",
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            "uuid": "fc867884cef243c5adbd081f3b14c709",
            "title": "Ice nucleation by fertile soil dusts: relative importance of mineral and biogenic components: Ice active site density verses temperature for a number soil samples",
            "abstract": "These data are associated with Ice nucleation by fertile soil dusts: relative importance of mineral and biogenic components, by D. O’Sullivan, B. J. Murray, T. L. Malkin, T. F. Whale, N. S. Umo, J. D. Atkinson, H. C. Price, K. J. Baustian, J. Browse, and M. E. Webb. Atmos. Chem. Phys., 14, 1853–1867, 2014 www.atmos-chem-phys.net/14/1853/2014/ doi:10.5194/acp-14-1853-2014. The lab measurement data comprise Ice active site density verses temperature for a number of samples.  The data are in CSV format.",
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            "title": "The relevance of nanoscale biological fragments for ice nucleation in clouds: Ice active site density verses temperature for a number soil, fungus and pollen samples.",
            "abstract": "These data are associated with The relevance of nanoscale biological fragments for ice nucleation in clouds, by D. O'Sullivan, B. J. Murray, J. F. Ross, T. F. Whale, H. C. Price, J. D. Atkinson, N. S. Umo & M. E. Webb. Scientific Reports, DOI: 10.1038/srep08082. The lab measurement data comprise Ice active site density verses temperature for a number of samples.  The data are in CSV format.",
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            "title": "The Organization of Tropical Rainfall: Idealised MetUM model output for convective aggregation studies",
            "abstract": "This dataset comprises of model output from 11 runs of the Met Office Unified Model (MetUM) in idealised radiative-convective equilibrium mode. All runs have fixed constant sea surface temperature (SST) and doubly-periodic lateral boundary conditions. These runs were used in several papers on convective self-aggregation: principally in Holloway and Woolnough (2016, Journal of Advances in Modeling Earth Systems) but also in Holloway (2017, Journal of Advances in Modeling Earth Systems).\r\n\r\nAll runs use the \"New Dynamics\" dynamical core, MetUM version 7.5, as described in Holloway and Woolnough (2016). The simulations are run with 4-km horizontal grid spacing. They all have a horizontal domain size of 576 km X 576 km (or 144 X 144 grid points), with 70 vertical levels. They were all run for 40 days except for the two runs with lower Sea Surface Temperatures, SSTs (295 K and 290 K) which were run for only 20 days.\r\n\r\nThe model output includes hourly model-level prognostic variables (temperature, specific humidity, pressure, wind components, liquid water, ice water) as well as some model-level increments to temperature and specific humidity. There are also many fields containing surface variables and fluxes (averaged over each hour or every 15 minutes).\r\n",
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        {
            "ob_id": 25031,
            "uuid": "7838d170275d460887b3043de0c71679",
            "title": "The Organization of Tropical Rainfall: Realistic MetUM model output for convective aggregation studies",
            "abstract": "This dataset comprises of model output from 25 runs (5 case studies, with 5 runs in each case study) of the Met Office Unified Model (MetUM) in realistic limited-area one-way nesting mode. The output data include values for model fields (e.g. temperature, humidity, winds, pressure) at model grid points over regularly spaced time intervals. These runs were used in a paper on convective aggregation: Holloway (2017, Journal of Advances in Modeling Earth Systems). \r\n\r\nAll runs use the \"\"New Dynamics\"\" dynamical core, MetUM version 7.5, as described in Holloway (2017). The simulations are run with 4-km horizontal grid spacing. They all have a horizontal domain size of 20 degrees latitude X 20 degrees longitude (or 574 X 574 grid points, although the grid points in the outer 8 points on all sides, the \"\"rim\"\", should be discarded before analysis), with 70 vertical levels. All runs are initialised from operational analyses from the European Centre for Medium-Range Weather Forecasting (ECMWF) taken from actual cases. Lateral boundary conditions are comprised of 6-hourly ECMWF analyses, and the model is relaxed to these conditions in and near the outer rim as described in Holloway (2017). Sea surface temperatures (SST) are taken from the initial ECMWF analysis and are held constant in time for the 15 days (but are not constant in space). There are small land regions in four of the case studies which include an interactive land surface model.\r\n\r\nEach simulation was run for 15 days. The model output includes hourly model-level prognostic variables (temperature, specific humidity, pressure, wind components, liquid water, ice water) as well as some model-level increments to temperature and specific humidity. There are also many fields containing surface variables and fluxes (averaged over each hour or every 15 minutes). Note that the \"\"control\"\" simulations have slightly more available data than the other four runs in each of the five case studies.\r\n\r\nThe five case studies are centred on the equator and occur between 2008 and 2010. See Holloway (2017) for further details:\r\nhttp://onlinelibrary.wiley.com/doi/10.1002/2017MS000980/full \r\n\r\n\r\nFor each case, there are five runs:\r\n1) control (interactive radiation, interactive surface fluxes)\r\n2) constant radiative cooling run (radiative cooling over sea points is prescribed from domain-time mean of control run)\r\n3) constant surface flux run (surface latent and sensible heat fluxes over sea points are prescribed from domain-time mean of control run)\r\n4) constant radiative cooling and constant surface flux run (combination of 2 and 3 above)\r\n5) no rain evaporation run (rain is prevented from evaporating in the atmosphere)\"\r\n",
            "keywords": "tropical convection, Tropics, MetUM",
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            "dataPublishedTime": "2018-06-14T13:30:25",
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                "volume": 11325828430287,
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            "title": "ACID-PRUF: Measurements of freezing fraction of water solution droplets solute and suspended matter during the immersion freezing of pollen extracts",
            "abstract": "ACID-PRUF was a three year NERC directed programme that investigated the complex interaction of aerosols and clouds. The overall aims of ACID-PRUF were to reduce the uncertainty in the radiative forcing associated with the aerosol indirect effects though a targeted laboratory and modelling programme. \r\n\r\nThis dataset collection contains measurements of freezing fraction of water solution droplets-solute and suspended matter during the immersion freezing of pollen extracts (birch pollen, Betula fontinalis occidentalis, Sigma-Aldrich, P6895-1G), with a  new cold electrodynamic balance (CEDB).",
            "keywords": "ACID-PRUF, pollen, aerosols, clouds",
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            "title": "GloCAEM: Atmospheric electricity measurements at Syowa Station (10m pole), East Ongul Island, Antarctica",
            "abstract": "Global Coordination of Atmospheric Electricity Measurements (GloCAEM) project brought these experts together to make the first steps towards an effective global network for FW atmospheric electricity monitoring by holding workshops to discuss measurement practises and instrumentation, as well as establish recording and archiving procedures to archive electric field data in a standardised, easily accessible format, then by creating a central data repository. This project was funded in the UK under NERC grant NE/N013689/1.\r\n\r\nThis dataset contains measurements of atmospheric electricity and electric potential gradient made using a Boltek EFM 100 Instrument mounted on a 10m pole and operated by the National Institute of Polar Research and Japan Meteorological Agency at Syowa Station,  East Ongul Island, Antarctica.",
            "keywords": "GloCAEM, GEC, electric potential, electric field",
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        {
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            "uuid": "0cea8d7aca57427fae92241348ae9b03",
            "title": "Managing the Risks, Impacts and Uncertainties of drought and water Scarcity (MaRIUS) project: Large set of   potential past and future climate time series for the UK from the weather@home2 model",
            "abstract": "Large data sets created within the MaRIUS project (Managing the Risks, Impacts and Uncertainties of drought and water Scarcity). \r\nThree time periods are covered: historical baseline (BS: 1900-2006), near-future (NF: 2020-2049) and far-future (FF: 2070-2099), whereby the RCP8.5 is assumed for future time slices. The 30-year baseline to which future time slices should be compared to are years 2075-2004 of the historical baseline, since oceanic variability in future time slices is based on these years.\r\nOne set of 100 time series is available for the historical baseline, while 5 sets of about 85-100 time series are available for each future time slice. The five sets sample climate model uncertainty by sampling a range of sea surface temperature warming patterns as follows: nf and ff use the median warming pattern of CMIP5 climate models. The four others sets are called nf-pYYz (near future) and ff-pYYz (far future) whereby 'YY' stands for the percentile of global mean SST warming (YY=10 or 90) and 'z' stands for the North Atlantic SST gradient (z=n for minimum, z=x for maximum). All natural forcings (e.g., volcanoes) in the future time slices are replications of years 1975-2004, while anthropogenic forcings (e.g., CO2 concentrations) follow the high-emission scenario RCP8.5.\r\nThe time series were created from single-year simulations that have been stitched together while ensuring continuity in the slowly-evolving variability (see Guillod et al., Hydrol. Earth Syst. Sci., 2017 for details). Therefore, for each set (e.g., near_future_p10n), a 'stitching table' is provided alongside with data from individual yearly simulations, which contains the simulation ID ('umid') for each year and each individual time series (i.e., each column within the table list the umid for each year of the time series).\r\nData are gridded NetCDF V3 files, provided on a rotated longitude-latitude grid at a 0.22 degree resolution (European CORDEX grid) over a domain encompassing the United Kingdom. A subset of variables are available at daily, 5-days, and monthly temporal resolutions, based on a calendar with 360 days a year (30 days per month). Included are only data from HadRM3P, the regional climate model within weather@home2. After unpacking yearly *tgz files for a given time slice and scenario (e.g., near_future_p10n) within a directory with the relevant name, the data are structured as follows:\r\ntimeslice / year / umid / temporalResolution / WAH_umid_variable_temporalResolution_g2_year.nc\r\nwhere:\r\n- The temporal resolution ('temporalResolution') available depends on the variable, but it can be 'daily', 'monthly', or '5days'\r\n- 'timeslice' can be one of: 'baseline', 'near_future', 'near_future_p10n', 'near_future_p10x', 'near_future_p90n', 'near_future_p90x', 'far_future', 'far_future_p10n', 'far_future_p10x', 'far_future_p90n', 'far_future_p90x'.\r\n- 'year' is the year of the simulation and data.\r\n- 'umid' is the ID of the simulation, to be read from the stitching table.\r\n- 'variable' is the variable, following CMOR conventions (see also Table 3 in Guillod et al., Hydrol. Earth Syst. Sci., 2017).\r\nFurther details about the data, including validation of the climate time series and analyses of some changes in the future projections, can be found in the PDF documentation as well as in Guillod et al., 2017b. A detailed validation of the model (weather@home2) can be found in Guillod et al., 2017a (see list of references below).\r\n",
            "keywords": "",
            "publicationState": "citable",
            "dataPublishedTime": "2017-09-08T11:48:14",
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                "volume": 1104985878692,
                "numberOfFiles": 422,
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            "dataLineage": "The Weather@Home2 climate simulation environment uses the HadAM3P Atmosphere-only General Circulation Model (AGCM) with an embedded Regional Climate Model (RCM) variant, HadRM3P, both from the UK Met Office Hadley Centre. Unlike the original Weather@Home, Weather@Home2 uses a more sophisticated land-surface model, MOSES2. These models are based upon the atmospheric component of HadCM3, a well documented and widely used coupled ocean – atmosphere model. HadRM3P is the regional model used in the Providing Regional Climates for Impacts Studies project (PRECIS)10, also originating from the UK Met Office.",
            "removedDataTime": null,
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        {
            "ob_id": 25058,
            "uuid": "5f75fcb0c58740d99b07953797bc041e",
            "title": "ESA Sea Ice Climate Change Initiative (Sea_Ice_cci):  Sea Ice Concentration Climate Data Record from the AMSR-E and AMSR-2 instruments at 50km grid spacing, version 2.1",
            "abstract": "The dataset provides a Climate Data Record of Sea Ice Concentration (SIC) for the polar regions, derived from medium resolution passive microwave satellite data from the Advanced Microwave Scanning Radiometer series (AMSR-E and AMSR-2).  It is processed with an algorithm using coarse resolution (6 GHz and 37 GHz) imaging channels, and has been gridded at 50km grid spacing. This version of the product is v2.1, which is an extension of the version 2.0 Sea_Ice_cci dataset and has identical data until 2015-12-25.\r\n\r\nThis product was generated in the context of the ESA Climate Change Initiative Programme (ESA CCI) by the Sea_Ice_CCI project. The EUMETSAT OSI SAF contributed with access and re-use of part of its processing software and facilities.\r\n\r\nA SIC CDR at 25km grid spacing is also available.",
            "keywords": "Sea Ice, ESA, CCI, Arctic, Antarctic",
            "publicationState": "citable",
            "dataPublishedTime": "2017-10-06T11:09:54",
            "doiPublishedTime": "2017-10-05T15:08:03",
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                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 58075249855,
                "numberOfFiles": 10275,
                "fileFormat": "Data are netCDF formatted"
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            "dataLineage": "Data were processed by the ESA CCI Sea Ice project team.\r\n\r\nContribution of the EUMETSAT OSI SAF to the production of this dataset is acknowledged. EUMETSAT OSI SAF provided access and allowed re-use of its SIC reprocessing software and data hosting facilities. The reprocessing chain was further updated with the new algorithms and knowledge from the ESA CCI Sea Ice project. \r\n\r\nData were supplied to CEDA in the context of the ESA CCI Open Data Portal Project",
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        {
            "ob_id": 25059,
            "uuid": "b241a7f536a244749662360bd7839312",
            "title": "S-RIP: Zonal-mean dynamical variables of global atmospheric reanalyses on pressure levels",
            "abstract": "This dataset contains zonal-mean atmospheric diagnostics computed from reanalysis datasets on pressure levels. Primary variables include temperature, geopotential height, and the three-dimensional wind field. Advanced diagnostics include zonal covariance terms that can be used to compute, for instance, eddy kinetic energy and eddy fluxes. Terms from the primitive zonal-mean momentum equation and the transformed Eulerian momentum equation are also provided.\r\n\r\nThis dataset was produced to facilitate the comparison of reanalysis datasets for the collaborators of the SPARC- Reanalysis Intercomparison Project (S-RIP) project. The dataset is substantially smaller in size compared to the full three dimensional reanalysis fields and uses unified numerical methods. The dataset includes all global reanalyses available at the time of its development and will be extended to new reanalysis products in the future.",
            "keywords": "S-RIP, Zonal mean, Pressure levels, Momentum equation, Transformed Eulerian mean, TEM, E-P flux",
            "publicationState": "citable",
            "dataPublishedTime": "2017-11-28T16:32:41",
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                "fileFormat": "Data are netCDF formatted"
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                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/57142/?format=api"
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            "dataLineage": "The dataset was created for the SPARC- Reanalysis Intercomparison Project (S-RIP). Data has been archived at the Centre for Environmental Data Anaylsis (CEDA).",
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        {
            "ob_id": 25063,
            "uuid": "c311c7948e8a47b299f8f9c7ae6cb9af",
            "title": "CRU TS3.25: Climatic Research Unit (CRU) Time-Series (TS) Version 3.25 of High-Resolution Gridded Data of Month-by-month Variation in Climate (Jan. 1901- Dec. 2016)",
            "abstract": "This version of CRU TS is superseded by version 4.01. It is being made available to assist with users moving to the new process. No further releases of version 3 are planned.\r\n\r\nThe gridded CRU TS (time-series) 3.25 data are month-by-month variations in climate over the period 1901-2016, on high-resolution (0.5x0.5 degree) grids, produced by the Climatic Research Unit (CRU) at the University of East Anglia.\r\n\r\nCRU TS 3.25 variables are cloud cover, diurnal temperature range, frost day frequency, PET, precipitation, daily mean temperature, monthly average daily maximum and minimum temperature, and vapour pressure for the period Jan. 1901 - Dec. 2016.\r\n\r\nCRU TS 3.25 data were produced using the same methodology as for the 3.21, 3.22, 3.23 and 3.24.01 datasets. This version contains updates the dataset with 2016 data, some new stations have been added for TMP and PRE only. This release is the latest release of the CRU TS data.  Known issues predating this release remain.\r\n\r\nThe CRU TS 3.25 data are monthly gridded fields based on monthly observational data, which are calculated from daily or sub-daily data by National Meteorological Services and other external agents. The ASCII and NetCDF data files both contain monthly mean values for the various parameters.\r\n\r\nAll CRU TS output files are actual values - NOT anomalies.",
            "keywords": "CRU, CRU TS, atmosphere, earth science, climate",
            "publicationState": "citable",
            "dataPublishedTime": "2017-09-22T09:27:54",
            "doiPublishedTime": "2017-12-05T14:04:00",
            "updateFrequency": "notPlanned",
            "status": "completed",
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                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 8304901978,
                "numberOfFiles": 607,
                "fileFormat": "Data are provided in ASCII and NetCDF formats."
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                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/25979/?format=api"
            ],
            "dataLineage": "CRU TS 3.00 data files acquired directly from CRU in 2007. CRU provided the BADC with software to generate the CRU datasets in 2010, and this was used to produce CRU TS 3.10 at the BADC in early 2011.\r\n\r\nIn July 2012, systematic errors were discovered in the CRUTS v3.10 process. The effect was, in some cases, to reduce the gridded values for PRE and therefore WET. Values of FRS were found to be unrealistic in some areas due to the algorithms used for synthetic generation. The files (pre, frs and wet) were immediately removed from BADC. The corrected run for precipitation, based on the v3.10 precipitation station data, was generated as a direct replacement and given the version number 3.10.01. There were no corrected runs produced for wet and frs.\r\n\r\nCRU TS 3.20 was produced in December 2012.\r\nIn March 2013, CRU TS observation databases for TMP and PRE variables were provided by CRU. Others are in preparation. In july 2013, two errors were found in the PRE and WET variables of CRU TS v3.20. These have been repaired in CRU TS v3.21. Details of the errors found are available in the Release Notes in the archive.\r\n\r\nCRU TS 3.21 was provided to CEDA for archival in July 2013 by CRU.\r\n\r\nCRU TS 3.22 was provided to CEDA for archival in July 2014 by CRU.\r\n\r\nCRU TS 3.23 was provided to CEDA in October 2015 by CRU. \r\n\r\nCRU TS 3.24 was provided to CEDA for archival in July 2016. This version CRU TSv3.24 has been withdrawn due to quality issues.\r\n\r\nCRU TS 3.24.01  was provided to CEDA for archival in January 2017. \r\n\r\nCRU TS 3.25  was provided to CEDA for archival in September 2017. This is the latest version available and is a replacement of the withdrawn dataset 3.24.01, it supersedes all previous data versions (which are available to allow user comparisons)",
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            "language": "English",
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            "uuid": "237c618d8b2e49cf8e61d01780f11650",
            "title": "CRU CY3.25: Climatic Research Unit (CRU) Year-by-Year Variation of Selected Climate Variables by CountrY (CY) version 3.25 (Jan. 1901 - Dec. 2016)",
            "abstract": "This version of CRU CY is superseded by version 4.01. It is being made available to assist with users moving to the new process. No further releases of version 3 are planned. \r\n\r\nAn updated set of country definitions have been introduced with this version. Please see the appropriate Release Notes. The data are available as text files with the extension '.per' and can be opened by most text editors.\r\n\r\nThe CRU CY version 3.25 dataset consists of ten climate variables for country averages at a monthly, seasonal and annual frequency; including cloud cover, diurnal temperature range, frost day frequency, precipitation, daily mean temperature, monthly average daily maximum and minimum temperature, vapour pressure and potential evapotranspiration. \r\n\r\nThis dataset was produced in 2017 by the Climatic Research Unit (CRU) at the University of East Anglia and extends CRU CY 3.24.01.\r\n\r\nSpatial averages are calculated using area-weighted means. CRU CY3.25 is derived directly from the CRU TS3.25 dataset. CRU CY version 3.25 spans the period 1901-2016 for 289 countries.\r\n\r\nTo understand the CRU-CY3.25 dataset, it is important to understand the construction and limitations of the underlying dataset, CRU TS3.25. It is therefore recommended that all users read the Harris et al, 2014 paper listed in the online documentation on this record.\r\n\r\nCRU CY data are available for download to all CEDA users.",
            "keywords": "CRU, CRU CY, climate",
            "publicationState": "citable",
            "dataPublishedTime": "2017-09-22T09:25:17",
            "doiPublishedTime": "2017-12-04T08:59:40",
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                "fileFormat": "The CRU CY data are provided as text files with the extension \".per\", most text editors will open these files. See the linked file formats guide for more information."
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            "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/6777/?format=api",
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            "dataLineage": "CRU CY is derived directly from the CRU TS dataset, and version numbering is matched between the two datasets. Thus, the first official version of CRU CY was v3.21 as it is based on CRU TS v3.21.\r\n\r\nCRU CY 3.24 data files supplied to CEDA for long-term archival by CRU in October 2016.\r\n\r\nThe CRU CY 3.24 data were withdrawn in January 2017 due to known issues with the data.\r\n\r\nCRU CY 3.24.01 data files supplied to CEDA for long-term archival by CRU in January 2017.\r\n\r\nCRU CY 3.25 data files supplied to CEDA for long-term archival by CRU in September 2017.",
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                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/102689/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/102699/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/102698/?format=api",
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            "ob_id": 25065,
            "uuid": "d4e823f0172947c5ae6e6b265656c273",
            "title": "CRU CY4.01: Climatic Research Unit (CRU) year-by-year variation of selected climate variables by country (CY) version 4.01 (Jan. 1901 - Dec. 2016)",
            "abstract": "The Climatic Research Unit (CRU) Country (CY) data version 4.01 dataset consists of ten climate variables for  country averages at a monthly, seasonal and annual frequency; including cloud cover, diurnal temperature range, frost day frequency, precipitation, daily mean temperature, monthly average daily maximum and minimum temperature, vapour pressure and potential evapotranspiration. This version uses the updated set of country definitions, please see the appropriate Release Notes.\r\n\r\nThis dataset was produced in 2017 by CRU at the University of East Anglia and extends the CRU CY4.00 data to include 2016. CRU CY4.01 is a full release, differing only in methodology from the existing current version 3 release, v3.25. Both are released concurrently to support comparative evaluations between these two versions, however, this will be the last release of version 3. The data are available as text files with the extension '.per' and can be opened by most text editors.\r\n\r\nSpatial averages are calculated using area-weighted means. CRU CY4.01 is derived directly from the CRU TS4.01 dataset. CRU CY version 4.01 spans the period 1901-2016 for 289 countries.\r\n\r\nTo understand the CRU CY4.01 dataset, it is important to understand the construction and limitations of the underlying dataset, CRU TS4.01. It is therefore recommended that all users read the Harris et al, 2020 paper and the CRU TS4.01 release notes listed in the online documentation on this record.\r\n\r\nCRU CY data are available for download to all CEDA users.",
            "keywords": "CRU, CRU CY, climate",
            "publicationState": "citable",
            "dataPublishedTime": "2017-09-22T09:26:57",
            "doiPublishedTime": "2017-12-04T08:59:56",
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                "volume": 49331502,
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                "fileFormat": "The CRU CY data are provided as text files with the extension \".per\", most text editors will open these files. See the linked file formats guide for more information."
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            "dataLineage": "The Climatic Research Unit (CRU) CY data are derived directly from the CRU TS data, and version numbering is matched between the two datasets. The CRU CY data are produced by the CRU unit at the University of East Anglia and passed to the Centre for Environmental Data Analysis (CEDA) for long term archival and distribution. Previous releases of CRU CY include:\r\n\r\nCRU CY 4.01 data were passed to CEDA for archival and distribution by CRU in September 2017\r\n\r\nCRU CY 4.00 data were passed to CEDA for archival and distribution by CRU in March 2017\r\n\r\nCRU CY 3.24.01 data files supplied to CEDA for long term archival by CRU in January 2017.\r\n\r\nThe CRU CY 3.24 data were withdrawn by CRU and CEDA in January 2017 due to known issues with the data.\r\n\r\nCRU CY 3.24 data files supplied to CEDA for long term archival by CRU in October 2016.",
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        {
            "ob_id": 25066,
            "uuid": "58a8802721c94c66ae45c3baa4d814d0",
            "title": "CRU TS4.01: Climatic Research Unit (CRU) Time-Series (TS) version 4.01 of high-resolution gridded data of month-by-month variation in climate (Jan. 1901- Dec. 2016)",
            "abstract": "The gridded Climatic Research Unit (CRU) Time-series (TS) data version 4.01 data are month-by-month variations in climate over the period 1901-2016, provided on high-resolution (0.5x0.5 degree) grids, produced by CRU at the University of East Anglia.\r\n\r\nThe CRU TS4.01 variables are cloud cover, diurnal temperature range, frost day frequency, potential evapotranspiration (PET), precipitation, daily mean temperature, monthly average daily maximum and minimum temperature, and vapour pressure for the period January 1901 - December 2016.\r\n\r\nThe CRU TS4.01 data were produced using angular-distance weighting (ADW) interpolation. All version 3 releases used triangulation routines in IDL. Please see the release notes for full details of this version update. CRU TS4.01 is a full release, differing only in methodology from the parallel release, v3.25. Both are released concurrently to support comparative evaluations between these two versions, however, this will be the last release of version 3.\r\n\r\nThe CRU TS4.01 data are monthly gridded fields based on monthly observational data calculated from daily or sub-daily data by National Meteorological Services and other external agents. The ASCII and NetCDF data files both contain monthly mean values for the various parameters. The NetCDF versions contain an additional integer variable, ’stn’, which provides, for each datum in the main variable, a count (between 0 and 8) of the number of stations used in that interpolation. The missing value code for 'stn' is -999.\r\n\r\nAll CRU TS output files are actual values - NOT anomalies.",
            "keywords": "CRU, CRU TS, atmosphere, earth science, climate",
            "publicationState": "citable",
            "dataPublishedTime": "2017-09-22T09:28:33",
            "doiPublishedTime": "2017-12-04T08:59:11",
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                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 34203448478,
                "numberOfFiles": 394,
                "fileFormat": "Data are provided in ASCII and NetCDF formats."
            },
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            "geographicExtent": "https://api.catalogue.ceda.ac.uk/api/v2/bboxes/513/?format=api",
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            "phenomena": [
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                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/52192/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/52193/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/56250/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/56251/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/56252/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/56253/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/56254/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/56255/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/56256/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/56257/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/56258/?format=api"
            ],
            "dataLineage": "The CRU TS data are produced by the Climatic Research Unit (CRU) at the University of East Anglia and are passed to the Centre for Environmental Data Analysis (CEDA) for long-term archival and distribution. Previous releases of the CRU TS data include:\r\n\r\nCRU TS 4.01 was provided to CEDA for archival in September 2017. \r\n\r\nCRU TS 4.00 was provided to CEDA for archival in March 2017. \r\n\r\nCRU TS 3.24.01  was provided to CEDA for archival in January 2017. This is the latest version available and is a replacement of the withdrawn dataset 3.24, it supersedes all previous data versions (which are available to allow user comparisons)\r\n\r\nCRU TS 3.24 was provided to CEDA for archival in July 2016. This is the latest version available, superseding all previous data versions (which are available to allow user comparisons), v3.24 has been withdrawn.\r\n\r\nCRU TS 3.23 was provided to CEDA in October 2015 by CRU. This is the latest version available, superseding all previous data versions (which are available to allow user comparisons).\r\n\r\nCRU TS 3.22 was provided to CEDA for archival in July 2014 by CRU.\r\n\r\nCRU TS 3.21 was provided to CEDA for archival in July 2013 by CRU.\r\n\r\nCRU TS 3.20 was produced in December 2012.\r\nIn March 2013, CRU TS observation databases for TMP and PRE variables were provided by CRU. Others are in preparation. In july 2013, two errors were found in the PRE and WET variables of CRU TS v3.20. These have been repaired in CRU TS v3.21. Details of the errors found are available in the Release Notes in the archive.\r\n\r\nCRU TS 3.10.01 In July 2012, systematic errors were discovered in the CRUTS v3.10 process. The effect was, in some cases, to reduce the gridded values for PRE and therefore WET. Values of FRS were found to be unrealistic in some areas due to the algorithms used for synthetic generation. The files (pre, frs and wet) were immediately removed from BADC. The corrected run for precipitation, based on the v3.10 precipitation station data, was generated as a direct replacement and given the version number 3.10.01. There were no corrected runs produced for wet and frs.\r\n\r\nCRU TS 3.00 data files acquired directly from CRU in 2007. CRU provided the BADC with software to generate the CRU datasets in 2010, and this was used to produce CRU TS 3.10 at the BADC in early 2011.",
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        {
            "ob_id": 25071,
            "uuid": "9b8f99f449c649778cb3febb14c0408c",
            "title": "UGAMP: 3-D ozone column monthly average 1986",
            "abstract": "The UK Universities Global Atmospheric Modelling Programme (UGAMP) ozone climatology project. This  dataset contains a 3-dimensional climatology of ozone monthly means, combining various satellite observations and ozone sonde data. The data are global and covers 1986.\r\n\r\nEach file contains a ligne of text followed by the variable itself, in free format.\r\n\r\nEvery single three-dimensional field var is stored as\r\n\r\n(((var(i, j, k), i=1, 144), j=1, 73), k=1, 47)\r\nwhere\r\ni is the longitude index (from 0°E to 357.5°E by 2.5°);\r\nj is the latitude index (from South Pole to North Pole by 2.5°);\r\nk is the level index (from top to bottom).\r\n\r\nEvery two-dimensional field (zonal means) is stored as\r\n\r\n((var(j, k), j=1, 73), k=1, 47)\r\nwith the same conventions as above.",
            "keywords": "UGAMp, Model, Climate, ozone",
            "publicationState": "published",
            "dataPublishedTime": "2007-01-08T15:41:10",
            "doiPublishedTime": null,
            "updateFrequency": "notPlanned",
            "status": "completed",
            "result_field": {
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                "dataPath": "/badc/ugamp-o3-climatology/data/y86",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 13891868,
                "numberOfFiles": 13,
                "fileFormat": "Data are ASCII formatted"
            },
            "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/6781/?format=api",
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                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/25394/?format=api"
            ],
            "dataLineage": "Data provided as is by the University of Reading from satellite observations (SBUV, SAGE II, SME, TOMS) as well as ozone sonde data provided by the Atmospheric Environment Service of Canada. Data is provided to the BADC where it is then stored.",
            "removedDataTime": null,
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            "abstract": "The site was setup in 1995 to measure meteorology, trace gases, aerosols and their fluxes. It is (55ᵒ47’36” N, 3°14’41” W) an ombrotrophic peatland with an extensive fetch at an elevation of 270 m, lying 18 km SSW of Edinburgh, and can be categorised as a transitional lowland raised bog. The site is grazed with < 1 sheep ha^-1.\r\n\r\nDuring 2000s the site activity has increased and was established in 2006 as EMEP (European Monitoring and Evaluation Program, Level 2/3) supersite for the UK. Long term monitoring is led by NERC CEH with contributions from other organisations/research institutes including Ricardo AEA, BureauVeritas, NPL, the University of Birmingham and University of Edinburgh. In April 2014 the site was awarded WMO GAW regional station (World Meteorological Orgamisation Global Atmospheric Watch). In 2017 the site joined the ICOS network (Integrated Carbon Observation System).\r\n\r\nThe meteorological measurements were initially made to assist with interpretation of the fluxes and as such weren't installed with the intention of providing WMO standard measurements but since 2014 we have been moving towards these standards as well as enhancing instrumentation.\r\n\r\nThe dataset includes the following parameters at half hourly intervals, although not every variable is available from 1995 to 2016:\r\n-T_upper_Avg - initially used to estimate senisble heat fluxes, fine wire type-E thermocouple.\r\n-T_lower_Avg - initially used to estimate senisble heat fluxes, fine wire type-E thermocouple.\r\n-T_RHT_Avg - Temperature measured by a Vailsala relative humidity and temperature probe.\r\n-RH_RHT_Avg - Relative humidity measured by a Vailsala relative humidity and temperature probe.\r\n-P_Avg - atmospheric pressure at the sites elevation.\r\n-Tot_Solar_Avg - Total solar radiation measured by a Skye SKS1110.\r\n-PAR_Avg - Photosynthetically Averaged Radiation measured by a Skye SKP215.\r\n-NetRad_Avg - Net radiation, Kipp & Zonen NrLite.\r\n-Rainfall - tipping bucket rainfall.\r\n-SoilTavg - Average soil temperature from four type-E thermocouple probes.\r\n-Soil Heat Flux - calculated from two measurements of soil heat flux with Hukseflux HFP01 plates, corrected to surface flux using the standard formula.\r\n-Cs = Bd(Cd+fSWC.Cw)\r\n-SC = DTs.Cs.d/Dtime\r\n-SHF = Plate Average + SC\r\n-DTs = change in average soil temperature from start to end of measurement period (first and last two minutes); d = plate depth 0.2 m; Bd = soil bulk density, 100 kg m-3; cd = Specific Heat Dry Soil, 840J kg-1 K-1; fSWC = fractional soil water content, measured or 0.9; cw = Specific Capacilty Heat of Water, 4190 J kg-1 K-1; Dtime = measurement period, 1800 s\r\n-Soil Moisture - soil water content measured with TDR probes, campbell CS616\r\n-WindSpd (measured) - measured by a Gill R3 then Windmaster sonic anemometer at 3.6 m\r\n-WindSpd 10 m - for most of the time period this is estimated from the turbulence measurements and 3.6 m windspeed but from 22/06/2016 a Gill Windsonic 2D anemeometer measures at 10 m\r\n-Wind Dir - measured by the sonic anemometer at 3.6 m\r\n-snow_depth_Avg - Campbell Scientific SR50A-L Sonic Ranging Sensor\r\n-Present Weather - Vaisala FD12P Present Weather Sensor\r\n-1 hr Past Weather - Vaisala FD12P Present Weather Sensor\r\n-Visibility - Vaisala FD12P Present Weather Sensor\r\n-Evaporation - to be estimated from the water-vapout flux measurements\r\n\r\nFor modelling purposes gapfilled (variables with _gf suffixes) times series will be included, they are created by linearly initially interpolating across upto an hours missing data, filling with colocated measurements (adjusted by linear interpolation with the core data), filling with measurements from nearby sites (adjusted by linear interpolation with the core data).\r\nTa_gf\r\nP_gf\r\nRH_gf\r\nTotal_Solar_gf\r\nRainfall_gf\r\nWindspd 10m_gf\r\nWind Dir_gf",
            "keywords": "Auchencorth Moss, Meteorology, Temperature, Rainfall, Wind Speed, ICOS",
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            "title": "MICROSCOPE: NCAS mobile X-band radar scan data from Davidstow Airfield - Version 2",
            "abstract": "This dataset contains scan data from the National Centre for Atmospheric Science's (NCAS) mobile X-band radar collected at the Davidstow Airfield, Cornwall, between June and August 2013 as part of the MICROphysicS of COnvective PrEcipitation (MICROSCOPE) project.\r\n\r\nThis version 2 dataset contains improved metadata and uses a revised processing method to improve data accuracy. Users should also note the change in filenaming convention for this instrument whereby the volume number given after the date-time part is no longer provided.\r\n\r\nThe X-band radar is operated as part of the NCAS Atmospheric Measurement Facility's (AMF).",
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            "title": "CMIP5 20-Year AR5 Climatology Data for the IPCC DDC",
            "abstract": "CMIP5 monthly mean climatology fields matching those given in IPCC WG1 AR5 Annex I: Atlas of Global and Regional Climate Projections in Climate Change 2013, the Fifth Assessment Report (AR5) of the United Nations Intergovernmental Panel on Climate Change (IPCC). \r\nClimatologies have been calculated for global fields of Specific Humidity, Precipitation, Sea Level Pressure, Temperature, Wind and Downwelling Shortwave Radiation (Stoker et. al., 2013).  The CMIP5 climatologies, calculated by the Centre for Environmental Data Analysis (CEDA), match those described in table AI.1 in Stoker et al (2013).  Twenty-year AR5 climatologies and climatological anomalies are calculated for the averaging periods 2016-2035, 2046-2065, 2081-2100 for the CMIP5 scenario experiments rcp26, rcp45, rcp60 and rcp85. The climatologies are of global scope and are provided on latitude-longitude grids.",
            "keywords": "IPCC, AR5, CMIP5, Climatologies, piControl, 1pctCO2, historical, scenarios, rcp26, rcp45, rcp60, rcp85",
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                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/60438/?format=api"
            ],
            "dataLineage": "Climatologies and climatological anomalies have been calculated at CEDA from CMIP5 model output.\r\n\r\nTime Periods:\r\n- AR5 averaging periods: 2016-2035, 2046-2065, 2081-2100\r\n\r\nAnomaly Specification: \r\nAll values are taken as anomalies from the 1986->2005 mean (base line values).\r\n\r\nOutput:\r\n- Period mean of the monthly mean of the variables\r\n- 12 monthly values per climatology\r\n- Climatology is a 2D field\r\n- One climatology per model per scenario per variable per time period\r\n- CF compliant netCDF files\r\n\r\nDirectory Structure:\r\nThe output directory structure follows the DRS specification with the root directory being /derived.\r\nEach file has the extended attribute: clim-anom-ref5.  This indicates that it is a climatological mean anomaly (clim-anom) and that the reference period matches the AR5 reference period (ref5).\r\n\r\nMethod:\r\nThe algorithm follows the process below:\r\n\r\n- For every model:\r\n  - For every variable (if available):\r\n      calculate the 1986->2005 climatological (period average) monthly means (baseline) for the Historical experiment\r\n\r\n- For every model:\r\n  - For every variable (if available):\r\n      calculate the period average monthly means (baseline) of the last 20 years of the piControl run\r\n\r\n- For every model:\r\n  - For every experiment:\r\n    - For every time period:\r\n      - For every variable (if available):\r\n        calculate the climatological monthly mean for this (model, experiment, time period, variable) and subtract the relevant baseline\r\n\r\nCode:\r\nhttps://github.com/cedadev/ipcc_ddc_cmip5_clim_anoms/releases/tag/1.0",
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            "ob_id": 25101,
            "uuid": "6cf411099aa743ef81de0f96dd80bac0",
            "title": "CMIP5 20-Year Climatology Data for the IPCC DDC",
            "abstract": "CMIP5 monthly mean climatology fields matching those given in IPCC WG1 AR5 Annex I: Atlas of Global and Regional Climate Projections in Climate Change 2013, the Fifth Assessment Report (AR5) of the United Nations Intergovernmental Panel on Climate Change (IPCC). \r\nClimatologies have been calculated for global fields of Specific Humidity, Precipitation, Sea Level Pressure, Temperature, Wind and Downwelling Shortwave Radiation (Stoker et. al., 2013).  The CMIP5 climatologies, calculated by the Centre for Environmental Data Analysis (CEDA), match those described in table AI.1 in Stoker et al (2013).  Twenty-year climatologies and climatological anomalies are calculated for the CMIP5 experiments: piControl, 1pctCO2, historical, rcp26, rcp45, rcp60 and rcp85. The monthly climatology data covers the period from 1850-2100. The climatologies are of global scope and are provided on latitude-longitude grids.",
            "keywords": "IPCC, AR5, CMIP5, Climatologies, piControl, 1pctCO2, historical, scenarios, rcp26, rcp45, rcp60, rcp85",
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            "uuid": "ed9a2b24c8944d2f8f2d6c1e86bbe130",
            "title": "CMIP5 30-Year Climatology Data for the IPCC DDC",
            "abstract": "CMIP5 monthly mean climatology fields matching those given in IPCC WG1 AR5 Annex I: Atlas of Global and Regional Climate Projections in Climate Change 2013, the Fifth Assessment Report (AR5) of the United Nations Intergovernmental Panel on Climate Change (IPCC). \r\nClimatologies have been calculated for global fields of Specific Humidity, Precipitation, Sea Level Pressure, Temperature, Wind and Downwelling Shortwave Radiation (Stoker et. al., 2013).  The CMIP5 climatologies, calculated by the Centre for Environmental Data Analysis (CEDA), match those described in table AI.1 in Stoker et al (2013).  Thirty-year climatologies and climatological anomalies are calculated for the CMIP5 experiments: piControl, 1pctCO2, historical, rcp26, rcp45, rcp60 and rcp85. The monthly climatology data covers the period from 1850-2100. The climatologies are of global scope and are provided on latitude-longitude grids.",
            "keywords": "IPCC, AR5, CMIP5, Climatologies, piControl, 1pctCO2, historical, scenarios, rcp26, rcp45, rcp60, rcp85",
            "publicationState": "published",
            "dataPublishedTime": "2018-05-22T12:04:03",
            "doiPublishedTime": null,
            "updateFrequency": "",
            "status": "completed",
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                "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/25103/?format=api",
                "dataPath": "/badc/ipcc-ddc/data/CMIP5-climatologies-30a",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 64472648806,
                "numberOfFiles": 10538,
                "fileFormat": "NetCDF"
            },
            "timePeriod": "https://api.catalogue.ceda.ac.uk/api/v2/times/6790/?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/7795/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/25892/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50416/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50418/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50429/?format=api",
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                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50475/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50496/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50498/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50549/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50559/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50561/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50564/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50579/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50598/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50603/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/50608/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/52741/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/52755/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/54407/?format=api",
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                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/56259/?format=api"
            ],
            "dataLineage": "Climatologies and climatological anomalies have been calculated at CEDA from CMIP5 model output.\r\n\r\nTime periods:\r\n- periods are defined as being:\r\n    - Relative to 2000 for future scenarios (RCPy.x)\r\n    - Relative to 1900 for historical run \r\n    - Relative to the beginning of the experiment for the piControl and 1pctCO2 runs \r\n\r\n- Thirty year averaging periods: +01 to +30, +31 to +60, +61 to +90\r\n\r\nAnomaly specification: \r\nAll values are taken as anomalies from the 1986->2005 mean (base line values).\r\nFor the Historical and RCP simulations these base line values are taken from the Historical experiment.\r\nFor the 1pctCO2 and piControl simulations the base line values are taken from the last 20 years of the piControl experiment.\r\n\r\nOutput:\r\n- Period mean of the monthly mean of the variables\r\n- 12 monthly values per climatology\r\n- Climatology is a 2D field\r\n- One climatology per model per scenario per variable per time period\r\n- CF compliant netCDF files\r\n\r\nDirectory Structure:\r\nThe output directory structure follows the DRS specification with the root directory being /derived.\r\nEach file has the extended attribute: clim-anom-ref5.  This indicates that it is a climatological mean anomaly (clim-anom) and that the reference period matches the AR5 reference period (ref5).\r\n\r\nMethod:\r\nThe algorithm follows the process below:\r\n\r\n- For every model:\r\n  - For every variable (if available):\r\n      calculate the 1986->2005 climatological (period average) monthly means (baseline) for the Historical experiment\r\n\r\n- For every model:\r\n  - For every variable (if available):\r\n      calculate the period average monthly means (baseline) of the last 20 years of the piControl run\r\n\r\n- For every model:\r\n  - For every experiment:\r\n    - For every time period:\r\n      - For every variable (if available):\r\n        calculate the climatological monthly mean for this (model, experiment, time period, variable) and subtract the relevant baseline\r\n\r\nCode:\r\nhttps://github.com/cedadev/ipcc_ddc_cmip5_clim_anoms/releases/tag/1.0",
            "removedDataTime": null,
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            "language": "English",
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                "https://api.catalogue.ceda.ac.uk/api/v2/observationcollections/25092/?format=api"
            ],
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                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/102880/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/102881/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/102883/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/102884/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/102885/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/102886/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/111735/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/102878/?format=api",
                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/111736/?format=api"
            ],
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                    "label": "public: None group",
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                }
            ],
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                {
                    "ob_id": 1138,
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        },
        {
            "ob_id": 25105,
            "uuid": "28a48da1141447058f8d5323908e4b3d",
            "title": "INCOMPASS: Radiosonde measurements from the Indian Institute of Technology (IIT) airstrip, Kanpur, India",
            "abstract": "This dataset contains temperature, humidity, wind and GPS location information recorded from 137 radiosondes launched during July 2016 as part of the NERC/MoES Interaction of Convective Organization and Monsoon Precipitation, Atmosphere, Surface and Sea (INCOMPASS) field campaign. All radiosondes were launched from the airstrip of Indian Institute of Technology (IIT) Kanpur, Uttar Pradesh, northern India, from the location 26.519N, 80.233E, 126m above sea level. Launches took place between 5th July and 28th July at 00, 06, 12, 18UTC. The Vaisala RS41-SG  radiosondes were fitted to Totex TA350 balloons. \r\n\r\nThe data were collected as part of the INCOMPASS field campaign May-July 2016, funded by Natural Environmental Research Council (NERC) (NE/L01386X/1). The aim of the project was to improve the skill of rainfall prediction in operational weather and climate models by way of better understanding and representation of interactions between the land surface, boundary layer, convection, the large-scale environment and monsoon variability on a range of scales.",
            "keywords": "NERC, INCOMPASS, monsoon, radiosonde, temperature, humidity, wind",
            "publicationState": "citable",
            "dataPublishedTime": "2018-10-18T12:29:59",
            "doiPublishedTime": null,
            "updateFrequency": "",
            "status": "completed",
            "result_field": {
                "ob_id": "https://api.catalogue.ceda.ac.uk/api/v2/observations/26563/?format=api",
                "dataPath": "/badc/sa-monsoon/data/incompass/radiosondes",
                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 163663579,
                "numberOfFiles": 140,
                "fileFormat": "Data are netCDF formatted."
            },
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                "https://api.catalogue.ceda.ac.uk/api/v2/phenomona/56231/?format=api"
            ],
            "dataLineage": "The Vaisala MW41 DigiCora sounding station receives radiosonde measurements via telemetry and stores them in a packaged (zipped) format consisting of XML files.  Only the \"SynchronizedSoundingData.xml\" file has been used (one for each launch), and converted to Netcdf (by AG Turner during September 2018) using a program running in IDL8.5. The data were then sent to the Centre for Environmental Data Analysis (CEDA) for archiving.",
            "removedDataTime": null,
            "removedDataReason": "",
            "language": "English",
            "identifier_set": [
                "https://api.catalogue.ceda.ac.uk/api/v2/identifiers/9692/?format=api"
            ],
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                "https://api.catalogue.ceda.ac.uk/api/v2/projects/19201/?format=api"
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                "https://api.catalogue.ceda.ac.uk/api/v2/observationcollections/20240/?format=api"
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                "https://api.catalogue.ceda.ac.uk/api/v2/rpis/111621/?format=api",
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        {
            "ob_id": 25109,
            "uuid": "55b5d76a7edb42e39933c1edc37f7b90",
            "title": "ICE-D: NCAS mobile X-band radar scan data from the Praia International Airport, Santiago, Cape Verde, Version 1",
            "abstract": "This dataset contains scan data from the National Centre for Atmospheric Science's (NCAS) mobile X-band radar collected at Praia International Airport, Santiago, Cape Verde between July and August 2015 as part of the Ice in Clouds Experiment - Dust (ICE-D). The radar has Doppler and dual-polarisation capability and measures the location and intensity of precipitation, radial winds and polarisation parameters.\r\n\r\nThe X-band radar is operated as part of the NCAS Atmospheric Measurement Facility (AMF).",
            "keywords": "ICE-D, radar, clouds, microphysics, ice, rainfall, dust, convection, storms",
            "publicationState": "citable",
            "dataPublishedTime": "2018-01-08T13:13:23",
            "doiPublishedTime": null,
            "updateFrequency": "notPlanned",
            "status": "completed",
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                "oldDataPath": [],
                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 312053485190,
                "numberOfFiles": 13342,
                "fileFormat": "Data are netCDF formatted"
            },
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