Description:

The "CLIM" products differ from their "regular" counterparts (without the "CLIM" in the name) by the ancillary data they use. They are Climate-Reference products, which requires homogeneous ancillary data over the climate time series. Hence, the ECMWF-Interim (European Centre for Medium-Range Weather Forecasts, 2-3 months lag behind the regular production) reanalysis is used as ancillary data to derive surface and atmospheric conditions required by the GPROF algorithm for the "CLIM" output. The GPROF databases are also adjusted accordingly for these climate-referenced retrievals. 3GPROF products provide global gridded monthly/daily precipitation averages from multiple satellites that can be used for climate studies. The 3GPROF products are based on retrievals from high-quality microwave sensors, which are sensitive to liquid and ice-phase precipitation hydrometeors in the atmosphere.

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Temporal Extent:

Start: 2002-06-01T00:00:00.000Z

End: 2009-12-31T23:59:59.999Z

Spatial Extent:

Minimum Bounding Rectangle: -90 -180 90 180

GES_DISC Short Name: GPM_3GPROFNOAA17AMSUB_CLIM Version ID: 07 Unique ID: C2264135904-GES_DISC

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Description:

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 HIRS3_N17 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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Temporal Extent:

Start: 2002-07-31T00:00:00.000Z

End: 2011-11-30T23:59:59.000Z

Spatial Extent:

Minimum Bounding Rectangle: -90 -180 90 180

GES_DISC Short Name: M2_HIRS3_N17 Version ID: 1 Unique ID: C3944482531-GES_DISC

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Description:

Version 5 of the Coral Reef Temperature Anomaly Database (CoRTAD) is a global, 4 km, sea surface temperature (SST) and related thermal stress metrics dataset for 1982-01-02 to 2012-12-28. The CoRTAD contains weekly-averaged SSTs, SST anomaly (SSTA, weekly SST minus weekly climatological SST), thermal stress anomaly (TSA, weekly SST minus the maximum weekly climatological SST), SSTA Degree Heating Week (SSTA_DHW, sum of previous 12 weeks when SSTA is greater than or equal to 1 degree C), SSTA Frequency (number of times over previous 52 weeks that SSTA is greater than or equal to 1 degree C), TSA DHW (TSA_DHW, also known as a Degree Heating Week, sum of previous 12 weeks when TSA is greater than or equal to 1 degree C), and TSA Frequency (number of times over previous 52 weeks that TSA is greater than or equal to 1 degree C). In addition, the CoRTAD includes ancillary sea ice concentration and marine wind speed data. These data are the fifth in the series of CoRTAD datasets originally created in association with Elizabeth Selig (Director, Marine Science, Conservation International) and John Bruno (University of North Carolina; UNC - Chapel Hill). This dataset is based on the Pathfinder V5.2 dataset, and is created with support from the NOAA Coral Reef Conservation Program.

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Temporal Extent:

Start: 1982-01-02T00:00:00.000Z

End: 2012-12-28T00:00:00.000Z

Spatial Extent:

Minimum Bounding Rectangle: -90 -180 90 180

NOAA_NCEI Short Name: 10.7289/v5cz3545 Version ID: Not Applicable Unique ID: C2089376220-NOAA_NCEI

Description:

This dataset contains Daily Snow Cover Fraction of viewable snow from AVHRR, produced by the Snow project of the ESA Climate Change Initiative programme. Snow cover fraction viewable (SCFV) indicates the area of snow viewable from space over land surfaces. In forested areas this refers to snow viewable on top of the forest canopy. The SCFV is given in percentage (%) per pixel. The global SCFV product is available at about 5 km pixel size for all land areas, excluding Antarctica and Greenland ice sheets. The coastal zones of Greenland are included.The SCFV time series provides daily products for the period 1979-2023. The product V4.0 is based on EUMETSAT Fundamental Data Record (FDR) medium resolution optical satellite data from the Advanced Very High Resolution Radiometer (AVHRR). Clouds are masked using the CLARA-A3 cloud product. The retrieval method of the snow_cci SCFV product from AVHRR data has been further developed and improved based on the ESA GlobSnow approach described by Metsämäki et al. (2015) and complemented with a pre- and post-classification module. All cloud free pixels are then used for the snow extent mapping, using spectral bands centred at about 0.63 µm and 1.61 µm (channel 3a or the reflective part of channel 3b (ref3b)), and an emissive band centred at about 10.8 µm. The snow_cci snow cover mapping algorithm is a three-step approach: first, a strict pre-classification is applied to identify all cloud free pixels which are certainly snow free. For all remaining pixels, the snow_cci SCFV retrieval method is applied. Finally, a post-processing removes erroneous snow pixels caused either by falsely classified clouds in the tropics or by unreliable ref3b values at a global scale. The following auxiliary data set is used for product generation: ESA CCI Land Cover from 2000; water bodies and permanent snow and ice areas are masked based on this dataset. Both classes were separately aggregated to the pixel spacing of the SCF product. Water areas are masked if more than 50 percent of the pixel is classified as water, permanent snow and ice areas are masked if more than 50 percent are identified as such areas in the aggregated map. RMSE is retrieved from a statistical model and added as pixel-wise information.The SCFV product is aimed to serve the needs for users working in the cryosphere and climate research and monitoring activities, including the detection of variability and trends, climate modelling and aspects of hydrology, meteorology and biology.The Remote Sensing Research Group of the University of Bern, in cooperation with Gamma Remote Sensing is responsible for the SCFV product development and generation. ENVEO (ENVironmental Earth Observation IT GmbH) developed and prepared all auxiliary data sets used for the product generation. The SCFV AVHRR product comprises a few data gaps in 1979 – 1986 (1979: 22.-24.Feb.; 01.-07.Oct.; 03.-04.Nov.; 07.Nov.; 17.-18.Nov.; 1980: 22.-27.Feb.; 01.March; 03.March; 15.-20.March; 30.March – 02.April; 26.-29.June; 12.-19.July; 12.-18.Dec.; 1981: 09.-11.May; 01.-03.Aug.; 14.-23.Aug.; 1982: 28.- 31.May; 25.-26. Oct.; 1983: 27.- 31. July; 01.- 02. and 06. Aug.; 1984: 14.-15.Jan.; 06. Dec.; 1985: 01.- 24.Feb; 1986: 15. March), resulting in a 99% data coverage over the entire study period of 43 years.

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Temporal Extent:

Start: 1979-01-01T00:00:00.000Z

End: 2023-12-31T23:59:59.000Z

Spatial Extent:

Minimum Bounding Rectangle: -90 -180 90 180

FEDEO Short Name: 3c71c04cf08a410fac2c680cbf88cfd7 Version ID: NA Unique ID: C4017534711-FEDEO

Description:

This v2.1 SST_cci Advanced Very High Resolution Radiometer (AVHRR) level 3 uncollated data (L3U) Climate Data Record (CDR) consists of stable, low-bias sea surface temperature (SST) data from the AVHRR series of satellite instruments. It covers the period between 08/1981 and 12/2016. This L3U product provides these SST data on a 0.05 regular latitude-longitude grid with with a single orbit per file.The dataset has been produced as part of the European Space Agency (ESA) Climate Change Initiative Sea Surface Temperature project(ESA SST_cci). The data products from SST_cci accurately map the surface temperature of the global oceans over the period 1981 to 2016 using observations from many satellites. The data provide independently quantified SSTs to a quality suitable for climate research.This CDR Version 2.1 product supercedes the CDR Version 2.0 product. Data are made freely and openly available under a Creative Commons License by Attribution (CC By 4.0) https://creativecommons.org/licenses/by/4.0/ .When citing this dataset please also cite the associated data paper: Merchant, C.J., Embury, O., Bulgin, C.E., Block T., Corlett, G.K., Fiedler, E., Good, S.A., Mittaz, J., Rayner, N.A., Berry, D., Eastwood, S., Taylor, M., Tsushima, Y., Waterfall, A., Wilson, R., Donlon, C. Satellite-based time-series of sea-surface temperature since 1981 for climate applications, Scientific Data 6:223 (2019). http://doi.org/10.1038/s41597-019-0236-x

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Temporal Extent:

Start: 1981-08-23T23:00:00.000Z

End: 2016-12-31T23:59:59.000Z

Spatial Extent:

Minimum Bounding Rectangle: -90 -180 90 180

FEDEO Short Name: 42f7230ab55641cdac1bba84eabd446a Version ID: NA Unique ID: C2548142559-FEDEO