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International Satellite Cloud Climatology Project (ISCCP) Stage D2 Monthly Cloud Products - Revised Algorithm in Hierarchical Data Format
https://cmr.earthdata.nasa.gov/search/concepts/C3880704243-LARC_CLOUD.xmlDescription:The ISCCP_D2 data set contains monthly, 280 KM equal-area grid data from various polar and geostationary satellites. Climatological Summary Product contents contain monthly average of D1 quantities including mean diurnal cycle, distribution and properties of total cloudiness and cloud types. The International Satellite Cloud Climatology Project (ISCCP), the first project of the World Climate Research Program (WCRP), was established in 1982 (WMO-35 1982, Schiffer and Rossow 1983): - To produce a global, reduced resolution, calibrated and normalized radiance data set containing basic information on the properties of the atmosphere from which cloud parameters can be derived. - To stimulate and coordinate basic research on techniques for inferring the physical properties of clouds from the condensed radiance data set and to apply the resulting algorithms to derive and validate a global cloud climatology for improving the parameterization of clouds in climate models. - To promote research using ISCCP data that contributes to improved understanding of the Earth's radiation budget and hydrological cycle. Since 1983 an international group of institutions has collected and analyzed satellite radiance measurements from up to five geostationary and two polar orbiting satellites to infer the global distribution of cloud properties and their diurnal, seasonal and interannual variations. The primary focus of the first phase of the project (1983-1995) was the elucidation of the role of clouds in the radiation budget (top of the atmosphere and surface). In the second phase of the project (1995 onwards) the analysis also concerns improving understanding of clouds in the global hydrological cycle. The ISCCP analysis combines satellite-measured radiances (Stage B3 data, Schiffer and Rossow 1985), Rossow et al. 1987) with the TOVS atmospheric temperature-humidity and ice/snow correlative data sets to obtain information about clouds and the surface. The analysis method first determines the presence of absence of clouds in each individual image pixel and retrieves the radiometric properties of the cloud for each cloudy pixel and of the surface for each clear pixel. The pixel analysis is performed separately for each satellite radiance data set and the results reported in the Stage DX data product, which has a nominal resolution of 30 km and 3 hours. The Stage D1 product is produced by summarizing the pixel-level results every 3 hours on an equal-area map with 280 km resolution and merging the results from separate satellites with the atmospheric and ice/snow data sets to produce global coverage at each time. The Stage D2 data product is produced by averaging the Stage D1 data over each month, first at each of the eight three hour time intervals and then over all time intervals.
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Polygon: -90 -180 -90 180 90 180 90 -180 -90 -180LARC_CLOUD Short Name: ISCCP_D2 Version ID: 1 Unique ID: C3880704243-LARC_CLOUD
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International Satellite Cloud Climatology Project (ISCCP) Stage DX Pixel Level Cloud Product - Revised Algorithm in Binary Format
https://cmr.earthdata.nasa.gov/search/concepts/C3880704255-LARC_CLOUD.xmlDescription:ISCCP_DX_1 is the International Satellite Cloud Climatology Project (ISCCP) Stage DX Pixel Level Cloud Product - Revised Algorithm in Binary Format data set. It contains 3-hourly, 30 KM satellite image projection data from various polar and geostationary satellites. Pixel Level Cloud Product contents include calibrated radiances, cloud detection results, and cloud and surface properties from radiative analysis. Data collection for this data set is complete. ISCCP was the first project of the World Climate Research Program (WCRP) and was established in 1982 (WMO-35 1982, Schiffer and Rossow 1983) to: produce a global, reduced resolution, calibrated and normalized radiance data set containing basic information on the properties of the atmosphere from which cloud parameters can be derived; stimulate and coordinate basic research on techniques for inferring the physical properties of clouds from the condensed radiance data set and to apply the resulting algorithms to derive and validate a global cloud climatology for improving the parameterization of clouds in climate models; and promote research using ISCCP data that contributes to improved understanding of the Earth's radiation budget and hydrological cycle. Starting in 1983, an international group of institutions collected and analyzed satellite radiance measurements from up to five geostationary and two polar orbiting satellites to infer the global distribution of cloud properties and their diurnal, seasonal and inter-annual variations. The primary focus of the first phase of the project (1983-1995) was the elucidation of the role of clouds in the radiation budget (top of the atmosphere and surface). In the second phase of the project (1995 onward) the analysis was also concerned with improving understanding of clouds in the global hydrological cycle. The ISCCP analysis combined satellite-measured radiances (Stage B3 data, Schiffer and Rossow 1985, Rossow et al. 1987) with the Tiros Operational Vertical Sounder (TOVS) atmospheric temperature-humidity and ice/snow correlative data sets to obtain information about clouds and the surface. The analysis method first determined the presence of or absence of clouds in each individual image pixel and retrieved the radiometric properties of the cloud for each cloudy pixel and of the surface for each clear pixel. The pixel analysis was performed separately for each satellite radiance data set and the results were reported in the Stage DX data product, which had a nominal resolution of 30 km and 3 hours. The Stage D1 product was produced by summarizing the pixel-level results every 3 hours on an equal-area map with 280 km resolution and merging the results from separate satellites with the atmospheric and ice/snow data sets to produce global coverage at each time. The Stage D2 data product was produced by averaging the Stage D1 data over each month, first at each of the eight three hour time intervals and then over all time intervals.
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Polygon: -90 -180 -90 180 90 180 90 -180 -90 -180LARC_CLOUD Short Name: ISCCP_DX Version ID: 1 Unique ID: C3880704255-LARC_CLOUD
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GHRSST Level 4 K10_SST Global 10 km Analyzed Sea Surface Temperature from Naval Oceanographic Office (NAVO) in GDS2.0
https://cmr.earthdata.nasa.gov/search/concepts/C2036881956-POCLOUD.xmlDescription:This is a Group for High Resolution Sea Surface Temperature (GHRSST) Level 4 sea surface temperature (SST) analysis dataset produced daily on an operational basis by the Naval Oceanographic Office (NAVO) on a global 0.1x0.1 degree grid. The K10 (NAVO 10-km gridded SST analyzed product) L4 analysis uses SST observations from the following instruments: Advanced Very High Resolution Radiometer (AVHRR), Visible Infrared Imaging Radiometer Suite (VIIRS), and Spinning Enhanced Visible and InfraRed Imager (SEVIRI). The AVHRR data for this comes from the MetOp-A, MetOp-B, and NOAA-19 satellites; VIIRS data is sourced from the Suomi_NPP satellite; SEVIRI data comes from the Meteosat-8 and -11 satellites. The age (time-lag), reliability, and resolution of the data are used in the weighted average with the analysis tuned to represent SST at a reference depth of 1-meter. Input data from the AVHRR Pathfinder 9km climatology dataset (1985-1999) is used when no new satellite SST retrievals are available after 34 days. Comparing with its predecessor (DOI: https://doi.org/10.5067/GHK10-L4N01 ), this updated dataset has no major changes in Level-4 interpolated K10 algorithm, except for using different satellite instrument data, and updating metadata and file format. The major updates include: (a) updated and enhanced the granule-level metadata information, (b) converted the SST file from GHRSST Data Specification (GDS) v1.0 to v2.0, (c) added the sea_ice_fraction variable to the product, and (d) updated the filename convention to reflect compliance with GDS v2.0.
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Minimum Bounding Rectangle: -90 -180 90 180POCLOUD Short Name: K10_SST-NAVO-L4-GLOB-v01 Version ID: 1.0 Unique ID: C2036881956-POCLOUD
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MERRA-2 Monthly Gridded Innovations and Observations SEVIRI_M09 0.5 x 0.625 degree V1 (M2_SEVIRI_M09)
https://cmr.earthdata.nasa.gov/search/concepts/C3944483118-GES_DISC.xmlDescription:The MERRA-2 Gridded Innovations and Observations (GIO) dataset provides assimilated observations and key statistics generated during observational data assimilation. GIO data are created by binning observations and innovations onto grids consistent with MERRA-2 specifications and storing them in NetCDF format for convenient access. This dataset serves multiple purposes: it shows which data was assimilated (where and when), enables systematic evaluation of observing system impacts in reanalysis, provides a resource for teaching data assimilation concepts, and offers training data for machine learning and artificial intelligence applications. This collection includes monthly mean and standard deviation values for brightness temperature (mean_obs, stdv_obs) from satellite sensor SEVIRI_M09 along with observation data counts (nobs_obs), and assimilation statistics, including: (a) forecast departure, or observation minus forecast (OmF) (mean_omf, stdv_omf); (b) analysis departure, or observation minus analysis (OmA) (mean_oma, stdv_oma); and (c) bias corrections for satellite radiances (mean_bias, stdv_bias).
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Minimum Bounding Rectangle: -90 -180 90 180GES_DISC Short Name: M2_SEVIRI_M09 Version ID: 1 Unique ID: C3944483118-GES_DISC
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INFRARED GLOBAL GEOSTATIONARY COMPOSITE V1
https://cmr.earthdata.nasa.gov/search/concepts/C1996543397-GHRC_DAAC.xmlDescription:The Infrared Global Geostationary Composite dataset contains global composite images from the infrared channels of multiple weather satellites in geosynchronous orbit. These satellites include the Global Mobility Service (GMS) from Japan, the Geostationary Operational Environmental Satellite (GOES) from the United States, NOAA satellites, and the Meteorological Satellite (METEOSAT) from Europe spanning nearly the entire globe. The spatial resolution is 14 km before December 18, 2017, and 4 km after that with the data remapped into a Mercator projection. The data have not necessarily been cross-calibrated between sensors. The data are available in AREA McIDAS format from June 4, 1995, to January 24, 2024, and netCDF-4 format from January 25, 2024, to present.
Links: Temporal Extent: Spatial Extent:Minimum Bounding Rectangle: -61 -180 66 180GHRC_DAAC Short Name: globalir Version ID: 1 Unique ID: C1996543397-GHRC_DAAC
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Climatology for NOAA Coral Reef Watch (CRW) Daily Global 5km Satellite Coral Bleaching Heat Stress Monitoring Product Suite Version 3.1 for 1985-01-01 to 2012-12-31 (NCEI Accession 0185742)
https://cmr.earthdata.nasa.gov/search/concepts/C2089379091-NOAA_NCEI.xmlDescription:This package contains a set of 12 monthly mean (MM) climatologies, one for each calendar month, and the maximum monthly mean (MMM) climatology. Each climatology has global coverage at 0.05-degree (5km) spatial resolution. The climatologies were derived from NOAA Coral Reef Watch's (CRW) CoralTemp Version 1.0 product and are based on the 1985-2012 time period of the CoralTemp data. They are used in deriving CRW's Daily Global 5km Satellite Coral Bleaching Heat Stress Monitoring Product Suite Version 3.1. MMs are used to derive the SST Anomaly product, and the MMM is used to derive CRW's Coral Bleaching HotSpot, Degree Heating Week, and Bleaching Alert Area products.
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Minimum Bounding Rectangle: -90 -180 90 180NOAA_NCEI Short Name: gov.noaa.nodc:0185742 Version ID: Not Applicable Unique ID: C2089379091-NOAA_NCEI
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Ensemble Median Global sea surface temperature dataset from 1988-01-01 to 2019-02-28 (NCEI Accession 0187983)
https://cmr.earthdata.nasa.gov/search/concepts/C2089380638-NOAA_NCEI.xmlDescription:Ensemble Median Global sea surface temperature (EMSST) is a daily SST dataset constructed by Nagoya University from an ensemble of 18 global SST products for the period from January 1, 1988 to February 28, 2019. The data set includes SST calculated as an ensemble median on each 0.25 degree by 0.25 degree grids over global ice-free oceans. The data set also includes an ensemble mean, standard deviation, minimum, maximum, number and kind of source products used.
Links: Temporal Extent: Spatial Extent:Minimum Bounding Rectangle: -90 -180 90 180NOAA_NCEI Short Name: gov.noaa.nodc:0187983 Version ID: Not Applicable Unique ID: C2089380638-NOAA_NCEI
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