Get a list of Observation objects.

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                    "abstract": "The monsoon supplies the majority of water for agriculture and industry in South Asia, and is therefore critical to the well-being of a billion people. Active and break periods in the monsoon have a major influence on the success of farming, while year-to-year variations in the rainfall have economic consequences on an international scale. The growing population and developing economy mean that understanding and predicting the monsoon is therefore vital. Despite this, our capability to model the monsoon, and to make forecasts on scales from days to the season ahead is limited by large errors that develop quickly. The relatively poor performance of weather prediction models over India is due to a very strong and complex relationship between the land, ocean and atmosphere, which are linked by the process of convection, in the form of the rain-bringing cumulonimbus clouds. Forecast errors occur primarily because the convective clouds are not accurately linked to the large-scale circulation or to the surface conditions, and these errors persist to long time scales. Worldwide, weather and climate forecast models are gaining resolution, and yet the errors in monsoon rainfall are not diminishing. A lack of detailed observations of the land, ocean and atmospheric parts of the monsoon system, on a range of temporal and spatial scales, is preventing a more thorough understanding of processes in monsoon convective clouds and at the land surface, and their interaction with the large-scale circulation. \r\n\r\nThe project used a programme of new measurements over India and the adjacent oceans to advance monsoon forecasting capability in the Indo-UK community. The first detachment of the FAAM research aircraft to India, in combination with an intensive ground-based observation campaign, will gather new observations of the land surface, the boundary layer structure over land and ocean, and atmospheric profiles. We will institute a new long-term series of measurements of energy and water exchanges at the land surface. Research measurements from one monsoon season will be combined with long-term observations on the Indian operational networks. Observations will be focused on two transects: in the northern plains of India, covering a range of surface types from irrigated to rain-fed agriculture, and wet to dry climatic zones; and across the Western Ghats, with transitions from land to ocean and across orography. The observational analysis will represent a unique and unprecedented characterization of monsoon processes linking the land, ocean and atmospheric patterns which control the rainfall. Long-term measurements will allow the computation of statistical relationships between the various factors. \r\n\r\nThe observational analysis fed directly into improved forecasting at the Met Office and NCMRWF. The Met Office Unified Model, which is used for weather forecasting at both institutions, was set up in a range of different ways for the observational period. In particular, the project pioneered the test development of a new 100m-resolution atmospheric model, which greatly improved the representation of land-ocean-atmosphere interactions. Another priority was to improve land surface modelling in monsoon forecasts. By comparing the results of the very high resolution models on small domains with lower-resolution models representing the global weather patterns, it was possible to describe the key processes controlling monsoon rainfall, and to indicate how these need to be represented in different applications, such as weather predictions or climate predictions. 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                "abstract": "The HadISD station data were produced by the Met Office Hadley Centre. Individual station data within the ISD were selected selected on the basis of their length of record and reporting frequency.  A merging algorithm using their location, elevation and station name identified candidates suitable to combine together. All stations were passed through a suite of automated quality control tests designed to remove bad data whilst keeping the extremes. None of the ISD flags were used in this process. The QC tests focussed on the temperature, dewpoint temperature and sea-level pressure variables, although some were applied to the wind speed and direction and cloud data. The data files also contain other variables which were pulled through from the raw ISD record, but have had no QC applied (e.g. cloud base and precipitation depth). \r\n\r\nNotes:\r\n1. These data have not yet been homogenised and so trend fitting should be undertaken with caution. The homogeneity has been assessed and results are available from the Met Office Hadley Centre HadISD website: http://www.metoffice.gov.uk/hadobs/hadisd/. \r\n2. A long-standing bug (affecting versions v2.0.2_2017p through to v3.3.0.2022f), was discovered in autumn 2023 whereby the neighbour checks (and associated [un]flagging for some other tests) were not being implemented. This was corrected for the later version v3.4.0.2023f to HadISD. For more details see the posts on the HadISD blog: https://hadisd.blogspot.com/2023/10/bug-in-buddy-checks.html & https://hadisd.blogspot.com/2024/01/hadisd-v3402023f-future-look.html(v2.0.2_2017p through to v3.3.0.2022f), and as noted this has been fixed for v3.4.02023f.\r\n\r\n\r\nFor further details see: \r\nDunn, R. J. H., et al., (2016), Expanding HadISD: quality-controlled, sub-daily station data from 1931, Geoscientific Instrumentation, Methods and Data Systems, and Dunn, R. J. H., et al. (2012), HadISD: A Quality Controlled global synoptic report database for selected variables at long-term stations\r\nfrom 1973-2011, Climate of the Past.\r\nDunn, R. J. H., et al. (2014), Pairwise Homogeneity Assessment of HadISD, Climate of the Past, 10, 1501-1522 (see Docs for links to publications)."
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            "title": "CRU TS3.24.01: Climatic Research Unit (CRU) Time-Series (TS) Version 3.24.01 of High Resolution Gridded Data of Month-by-month Variation in Climate (Jan. 1901- Dec. 2015)",
            "abstract": "The gridded CRU TS (time-series) 3.24.01 data are month-by-month variations in climate over the period 1901-2015, 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 3.24.01 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. 2015.\r\n\r\nCRU TS 3.24.01 data were produced using the same methodology as for the 3.21 datasets. In addition to updating the dataset with 2015 data, some new stations have been added for TMP and PRE only. This release should be used in place of v3.24 which has been withdrawn. Known issues predating this release remain.\r\n\r\nThe CRU TS 3.24.01 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.",
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            "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. This is the latest version available, superseding 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 3.24.01  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)",
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            "abstract": "The Natural Environment Research Council (NERC) Mesosphere-Stratosphere-Troposphere (MST) Radar is operated by the Science and Technology Facilities Council (STFC) at the Radar Facility's (MSTRF's) site in Capel Dewi, near Aberystwyth, Mid-Wales. \r\n\r\nThis dataset contains time-series of vertical profiles of derived atmospheric dynamics (wind speed, direction) and structure (indications of refractive index structures and turbulence) from observations taken from the 46.5 MHz pulsed Doppler radar. It is primarily used for making atmospheric observations over the approximate altitude range 2 - 20 km, i.e. of the free troposphere (above the boundary layer) and the lower stratosphere, known as the \"ST-mode\". Additional observations are made over the approximate altitude range 56 - 96 km, i.e. covering the mesosphere - known as the \"M-mode\" (see related dataset); hence the term \"MST\" radar.\r\n\r\nThe instrument has been in operation, using the Doppler Beam Swinging technique (see linked documentation for further details), since late 1989. It was initially operated on a campaign basis, but switched to quasi-continuous observations (i.e. close to 24-7 operation) in late 1997. In 2011 the radar system underwent renovation with significant improvements in radar performance. \r\n\r\nThe version 4.0 (v4.0) data processing scheme is closely related to the version 3 (v3) scheme and uses v3 Cartesian files as input. The main difference is that the horizontal wind components in the v4 Cardinal files represent time averages, which have a smaller random measurement error compared to the single cycle estimates in the v3 Cartesian files.\r\n\r\nData products available from the v4 Cardinal files include time-series profiles of:\r\n - eastward wind\r\n - northward wind\r\n - upward wind\r\n - (radar return) signal power (giving an indication of atmospheric structure) - also known as echo power\r\n - (beam broadening) corrected spectral width (giving a measure of turbulence intensity)\r\n - tropopause altitude and sharpness\r\n\r\nA full list of variables will be added to this record in due course.\r\n\r\nQuick look plots for these data are available  - see related links under the \"docs\" tab below.\r\n\r\nNote - some files are released marked as '-suspect'. These have been released to permit early access to the data where the majority of data are known to pass quality control, but a small, limited part of the data have been identified as being 'suspect'. An internal remark about the suspect data may be found within the file's metadata 'comments' attribute.",
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            "title": "CRU TS4.00: Climatic Research Unit (CRU) Time-Series (TS) version 4.00 of high-resolution gridded data of month-by-month variation in climate (Jan. 1901- Dec. 2015)",
            "abstract": "The gridded Climatic Research Unit (CRU) Time-series (TS) data version 4.00 data are month-by-month variations in climate over the period 1901-2015, provided on high-resolution (0.5x0.5 degree) grids, produced by CRU at the University of East Anglia.\r\n\r\nThe CRU TS4.00 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 2015.\r\n\r\nThe CRU TS4.00 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 TS4.00 is a full release, differing only in methodology from the existing current release, v3.24.01. Both are released concurrently to support comparative evaluations between these two versions.\r\n\r\nThe CRU TS4.00 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 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.\r\n\r\nAll CRU TS output files are actual values - NOT anomalies.",
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            "title": "CRU CY4.00: Climatic Research Unit (CRU) year-by-year variation of selected climate variables by country (CY) version 4.00 (Jan. 1901 - Dec. 2015)",
            "abstract": "The Climatic Research Unit (CRU) Country (CY) data version 4.00 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 CY3.23 data to include 2015. CRU CY4.00 is a full release, differing only in methodology from the existing current release, v3.24.01. Both are released concurrently to support comparative evaluations between these two versions. 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 CY4.00 is derived directly from the CRU TS4.00 dataset. CRU CY version 4.00 spans the period 1901-2015 for 289 countries.\r\n\r\nTo understand the CRU CY4.00 dataset, it is important to understand the construction and limitations of the underlying dataset, CRU TS4.00. It is therefore recommended that all users read the Harris et al, 2020 paper and the CRU TS4.00 release notes listed in the online documentation on this record.\r\n\r\nCRU CY data are available for download to all CEDA users.",
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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 4.00 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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                "abstract": "This computation involved: UEA Climate Research Unit (CRU) High Resolution gridding software deployed on UEA Climate Research Unit (CRU) computer system. For details about the production of CRU TS and CRU CY datasets, please refer to Harris et al. (2020) - see Details/Docs tab, moderated by the Release Notes for v4.00 (which outline the new gridding process)"
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                    "abstract": "The Climatic Research Unit at the University of East Anglia is producing various resolution gridded datasets.\r\nSome of those datasets are stored at CEDA-BADC."
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                    "title": "Climatic Research Unit (CRU): Year-by-Year Variation of Selected Climate Variables by CountrY (CY) v4",
                    "abstract": "The CRU CY datasets consists of country averages at a monthly, seasonal and annual frequency, for ten climate variables in 289 countries. Spatial averages are calculated using area-weighted means. Variables include cloud cover (cld), diurnal temperature range (dtr), frost day frequency (frs), precipitation (pre), daily mean temperature (tmp), monthly average daily maximum (tmx) and minimum (tmn) temperature, vapour pressure (vap), Potential Evapo-transpiration (pet) and wet day frequency (wet). The CRU CY datasets produced by the Climatic Research Unit (CRU) at the University of East Anglia.\r\n\r\nSpatial averages are calculated using area-weighted means. 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 is v3.21, as it is based on CRU TS v3.21 (1901-2012) and the latest version of CRU-CY is v4.03, as it is based on CRU TS v4.03. The data are available as text files with the extension '.per' and can be opened by most text editors.\r\n\r\nTo understand the CRU-CY dataset, it is important to understand the construction and limitations of the underlying dataset, CRU TS. It is therefore recommended that all users read the paper referenced below (Harris et al, 2014)."
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            "abstract": "The Cloud_cci ATSR2-AATSR dataset was generated within the Cloud_cci project (http://www.esa-cloud-cci.org) which was funded by the European Space Agency (ESA) as part of the ESA Climate Change Initiative (CCI) programme (Contract No.: 4000109870/13/I-NB). This dataset is one of the 6 datasets generated in Cloud_cci; all of them being based on passive-imager satellite measurements. This dataset is based on ATSR2 and AATSR (onboard ERS2 and ENVISAT) measurements and contains a variety of cloud properties which were derived employing the Community Cloud retrieval for Climate (CC4CL) retrieval system. The core cloud properties contained in the Cloud_cci ATSR2-AATSR dataset are cloud mask/fraction, cloud phase, cloud top pressure/height/temperature, cloud optical thickness, cloud effective radius and cloud liquid/ice water path. Spectral cloud albedo is also included as experimental product. Level-3C product files contain monthly averages and histograms of the mentioned cloud properties together with propagated uncertainty measures.",
            "creationDate": "2022-07-22T09:15:57.183554",
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                    "title": "ESA Cloud Climate Change Initiative (CCI) Dataset Collection",
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                    "title": "National Centre for Earth Observation (NCEO) partnered datasets",
                    "abstract": "The National Centre for Earth Observation (NCEO) has a proud tradition of being involved with some of the most successful international collaborations in the Earth observation. This Collection contains dataset generated and/or archived with the support of NCEO resource or scientific expertise. Some notable collaboration which generated data within this collection are as follows:\r\n\r\nThe European Space Agency (ESA)'s Climate Change Initiative (CCI) program. The program goal is to provide stable, long-term, satellite-based Essential Climate Variable (ECV) data products for climate modelers and researchers.\r\n\r\nThe EUSTACE (EU Surface Temperature for All Corners of Earth) project is produced publicly available daily estimates of surface air temperature since 1850 across the globe for the first time by combining surface and satellite data using novel statistical techniques.\r\n\r\nFIDUCEO has created new climate datasets from Earth Observations with a rigorous treatment of uncertainty informed by the discipline of metrology. This response to the need for enhanced credibility for climate data, to support rigorous science, decision-making and climate services. The project approach was to develop methodologies for generating Fundamental Climate Data Records (FCDRs) and Climate Data Records (CDRs) that are widely applicable and metrologically rigorous. \r\n\r\nThe “BACI” project translates satellite data streams into novel “essential biodiversity variables” by integrating ground-based observations. The trans-disciplinary project offers new insights into the functioning and state of ecosystems and biodiversity. BACI enables the user community to detect abrupt and transient changes of ecosystems and quantify the implications for regional biodiversity.\r\n\r\nThe UK Natural Environment Research Council has established a knowledge transfer network called NCAVEO (Network for Calibration and Validation of EO data - NCAVEO) which has as its aim the promotion and support of methodologies based upon quantitative, traceable measurements in Earth observation. \r\n\r\nThe Geostationary Earth Radiation Budget 1 & 2 instruments (GERB-1 and GERB-2) make accurate measurements of the Earth Radiation Budget. They are specifically designed to be mounted on a geostationary satellite and are carried onboard the Meteosat Second Generation satellites operated by EUMETSAT. They were produced by a European consortium led by the UK (NERC) together with Belgium, Italy, and EUMETSAT, with funding from national agencies.\r\n\r\nGloboLakes analysed 20 years of data from more than 1000 large lakes across the globe to determine 'what controls the differential sensitivity of lakes to environmental perturbation'. This was an ambitious project that was only possible by bringing together a consortium of scientists with complementary skills. These include expertise in remote sensing of freshwaters and processing large volumes of satellite images, collation and analysis of large-scale environmental data, environmental statistics and the assessment of data uncertainty, freshwater ecology and mechanisms of environmental change and the ability to produce lake models to forecast future lake conditions.\r\n\r\nThis SPEI collaboration consists of high spatial resolution Standardized Precipitation-Evapotranspiration Index (SPEI) drought dataset over the whole of Africa at different time scales from 1 month to 48 months. It is calculated based on precipitation estimates from the satellite-based Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) and potential evaporation estimates by the Global Land Evaporation Amsterdam Model (GLEAM)."
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            "abstract": "WCRP CMIP5: Met Office Hadley Centre (MOHC) HadCM3 model output for the decadal1963 experiment. These data cover the following realms: aerosol, atmos, land, landIce, ocean and seaIce; at the following frequencies: day and mon. The runs included the ensemble members: r10i2p1, r10i3p1, r1i2p1, r1i3p1, r2i2p1, r2i3p1, r3i2p1, r3i3p1, r4i2p1, r4i3p1, r5i2p1, r5i3p1, r6i2p1, r6i3p1, r7i2p1, r7i3p1, r8i2p1, r8i3p1, r9i2p1 and r9i3p1.\n\nThe WCRP Coupled Model Intercomparison Project, Phase 5 (CMIP5), was a global climate model intercomparison project, coordinated by PCMDI (Program For Climate Model Diagnosis and Intercomparison) on behalf of the World Climate Research Program (WCRP) and provided input for the Intergovernmental Panel on Climate Change (IPCC) 5th Assessment Report (AR5).",
            "creationDate": "2022-07-22T09:15:57.183554",
            "lastUpdatedDate": "2022-07-22T09:15:57.272326",
            "latestDataUpdateTime": "2020-04-30T22:07:43",
            "updateFrequency": "notPlanned",
            "dataLineage": "Data were produced and verified by Met Office Hadley Centre (MOHC) scientists before publication via the Earth Systems Grid Federation (ESGF) and a copy obtained by the Centre for Environmental Data Analysis (CEDA).",
            "removedDataReason": "",
            "keywords": "CMIP5, CMIP, WCRP, climate change, MOHC, HadCM3, decadal1963, aerosol, atmos, land, landIce, ocean, seaIce, day, mon",
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            "status": "completed",
            "dataPublishedTime": "2017-03-17T14:00:19.486405",
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                "westBoundLongitude": -180.0,
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                "northBoundLatitude": 90.0
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                "dataPath": "/badc/cmip5/data/cmip5/output1/MOHC/HadCM3/decadal1963/",
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                "storageLocation": "internal",
                "storageStatus": "online",
                "volume": 136784024903,
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                "fileFormat": "Data are netCDF formatted."
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                "startTime": "1963-11-01T12:00:00",
                "endTime": "1973-12-30T12:00:00"
            },
            "resultQuality": {
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                "explanation": "Please see the linked documentation \"CMIP5 Metadata Simulation Quality Control Report\" for quality control assessment for this simulation.",
                "passesTest": true,
                "resultTitle": "CMIP5 Data Quality Statement (external report)",
                "date": "2017-04-05"
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                "title": "Met Office Hadley Centre (MOHC) running: experiment decadal1963 using the HadCM3 model.",
                "abstract": "Met Office Hadley Centre (MOHC) running the decadal1963 experiment using the HadCM3 model. See linked documentation for available information for each component.\n\nPlease note the following are not recorded within the Earth System Documentation (ES-DOC) site : decadal1963 experiment and simulation details."
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