{"id":"gpm-imerg-hhr","type":"Collection","links":[{"rel":"items","type":"application/geo+json","href":"https://planetarycomputer.microsoft.com/api/stac/v1/collections/gpm-imerg-hhr/items"},{"rel":"parent","type":"application/json","href":"https://planetarycomputer.microsoft.com/api/stac/v1/"},{"rel":"root","type":"application/json","href":"https://planetarycomputer.microsoft.com/api/stac/v1/"},{"rel":"self","type":"application/json","href":"https://planetarycomputer.microsoft.com/api/stac/v1/collections/gpm-imerg-hhr"},{"rel":"license","href":"https://lpdaac.usgs.gov/data/data-citation-and-policies/","title":"LP DAAC - Data Citation and Policies"},{"rel":"http://www.opengis.net/def/rel/ogc/1.0/queryables","type":"application/schema+json","title":"Queryables","href":"https://planetarycomputer.microsoft.com/api/stac/v1/collections/gpm-imerg-hhr/queryables"},{"rel":"describedby","href":"https://planetarycomputer.microsoft.com/dataset/gpm-imerg-hhr","title":"Human readable dataset overview and reference","type":"text/html"}],"title":"GPM IMERG","assets":{"thumbnail":{"href":"https://ai4edatasetspublicassets.blob.core.windows.net/assets/pc_thumbnails/gpm-imerg-hhr.png","role":["thumbnail"],"type":"image/png","title":"gpm-imerg-hhr thumbnail"},"zarr-abfs":{"href":"abfs://imerg/gpm-imerg-hhr.zarr","type":"application/vnd+zarr","roles":["data","zarr"],"description":"Azure Blob File System URI of the gpm-imerg-hhr Zarr Group on Azure Blob Storage for use with adlfs.","xarray:open_kwargs":{"use_cftime":true,"consolidated":true},"xarray:storage_options":{"account_name":"ai4edataeuwest"}}},"extent":{"spatial":{"bbox":[[-180,-90,180,90]]},"temporal":{"interval":[["2000-06-01T00:00:00Z","2021-05-31T23:30:00Z"]]}},"license":"proprietary","sci:doi":"10.5067/GPM/IMERG/3B-HH/06","keywords":["IMERG","GPM","Precipitation"],"providers":[{"url":"https://developmentseed.org/","name":"Development Seed","roles":["processor"]},{"url":"https://planetarycomputer.microsoft.com","name":"Microsoft","roles":["host","processor"]},{"url":"https://gpm.nasa.gov/data/directory","name":"NASA","roles":["producer"]}],"description":"The Integrated Multi-satellitE Retrievals for GPM (IMERG) algorithm combines information from the [GPM satellite constellation](https://gpm.nasa.gov/missions/gpm/constellation) to estimate precipitation over the majority of the Earth's surface. This algorithm is particularly valuable over the majority of the Earth's surface that lacks precipitation-measuring instruments on the ground. Now in the latest Version 06 release of IMERG the algorithm fuses the early precipitation estimates collected during the operation of the TRMM satellite (2000 - 2015) with more recent precipitation estimates collected during operation of the GPM satellite (2014 - present). The longer the record, the more valuable it is, as researchers and application developers will attest. By being able to compare and contrast past and present data, researchers are better informed to make climate and weather models more accurate, better understand normal and extreme rain and snowfall around the world, and strengthen applications for current and future disasters, disease, resource management, energy production and food security.\n\nFor more, see the [IMERG homepage](https://gpm.nasa.gov/data/imerg) The [IMERG Technical documentation](https://gpm.nasa.gov/sites/default/files/2020-10/IMERG_doc_201006.pdf) provides more information on the algorithm, input datasets, and output products.","sci:citation":"Huffman, G.J., E.F. Stocker, D.T. Bolvin, E.J. Nelkin, Jackson Tan (2019), GPM IMERG Final Precipitation L3 Half Hourly 0.1 degree x 0.1 degree V06, Greenbelt, MD, Goddard Earth Sciences Data and Information Services Center (GES DISC)","stac_version":"1.0.0","cube:variables":{"lat_bnds":{"type":"auxiliary","unit":"degrees_north","attrs":{"Units":"degrees_north","units":"degrees_north","coordinates":"lat latv","DimensionNames":"lat,latv"},"shape":[1800,2],"chunks":[1800,2],"dimensions":["lat","latv"]},"lon_bnds":{"type":"auxiliary","unit":"degrees_east","attrs":{"Units":"degrees_east","units":"degrees_east","coordinates":"lon lonv","DimensionNames":"lon,lonv"},"shape":[3600,2],"chunks":[3600,2],"dimensions":["lon","lonv"]},"time_bnds":{"type":"auxiliary","attrs":{"Units":"seconds since 1970-01-01 00:00:00 UTC","coordinates":"time nv","DimensionNames":"time,nv"},"shape":[368160,2],"chunks":[12,2],"dimensions":["time","nv"]},"randomError":{"type":"data","unit":"mm/hr","attrs":{"Units":"mm/hr","units":"mm/hr","DimensionNames":"time,lon,lat","CodeMissingValue":"-9999.9"},"shape":[368160,3600,1800],"chunks":[12,3600,1800],"dimensions":["time","lon","lat"]},"HQprecipSource":{"type":"data","attrs":{"DimensionNames":"time,lon,lat","CodeMissingValue":"-9999"},"shape":[368160,3600,1800],"chunks":[12,3600,1800],"dimensions":["time","lon","lat"]},"HQprecipitation":{"type":"data","unit":"mm/hr","attrs":{"Units":"mm/hr","units":"mm/hr","DimensionNames":"time,lon,lat","CodeMissingValue":"-9999.9"},"shape":[368160,3600,1800],"chunks":[12,3600,1800],"dimensions":["time","lon","lat"]},"IRprecipitation":{"type":"data","unit":"mm/hr","attrs":{"Units":"mm/hr","units":"mm/hr","DimensionNames":"time,lon,lat","CodeMissingValue":"-9999.9"},"shape":[368160,3600,1800],"chunks":[12,3600,1800],"dimensions":["time","lon","lat"]},"precipitationCal":{"type":"data","unit":"mm/hr","attrs":{"Units":"mm/hr","units":"mm/hr","DimensionNames":"time,lon,lat","CodeMissingValue":"-9999.9"},"shape":[368160,3600,1800],"chunks":[12,3600,1800],"dimensions":["time","lon","lat"]},"HQobservationTime":{"type":"data","attrs":{"Units":"minutes","DimensionNames":"time,lon,lat","CodeMissingValue":"-9999"},"shape":[368160,3600,1800],"chunks":[12,3600,1800],"dimensions":["time","lon","lat"]},"precipitationUncal":{"type":"data","unit":"mm/hr","attrs":{"Units":"mm/hr","units":"mm/hr","DimensionNames":"time,lon,lat","CodeMissingValue":"-9999.9"},"shape":[368160,3600,1800],"chunks":[12,3600,1800],"dimensions":["time","lon","lat"]},"IRkalmanFilterWeight":{"type":"data","attrs":{"DimensionNames":"time,lon,lat","CodeMissingValue":"-9999"},"shape":[368160,3600,1800],"chunks":[12,3600,1800],"dimensions":["time","lon","lat"]},"precipitationQualityIndex":{"type":"data","attrs":{"DimensionNames":"time,lon,lat","CodeMissingValue":"-9999.9"},"shape":[368160,3600,1800],"chunks":[12,3600,1800],"dimensions":["time","lon","lat"]},"probabilityLiquidPrecipitation":{"type":"data","unit":"percent","attrs":{"Units":"percent","units":"percent","DimensionNames":"time,lon,lat","CodeMissingValue":"-9999"},"shape":[368160,3600,1800],"chunks":[12,3600,1800],"dimensions":["time","lon","lat"]}},"msft:container":"imerg","cube:dimensions":{"lat":{"axis":"y","type":"spatial","extent":[-89.94999694824219,89.94999694824219],"reference_system":4326},"lon":{"axis":"x","type":"spatial","extent":[-179.9499969482422,179.9499969482422],"reference_system":4326},"time":{"step":"P0DT0H30M0S","type":"temporal","extent":["2000-06-01T00:00:00Z","2021-05-31T23:30:00Z"]}},"stac_extensions":["https://stac-extensions.github.io/xarray-assets/v1.0.0/schema.json","https://stac-extensions.github.io/scientific/v1.0.0/schema.json","https://stac-extensions.github.io/datacube/v2.0.0/schema.json"],"msft:storage_account":"ai4edataeuwest","msft:short_description":"The Integrated Multi-satellitE Retrievals for GPM (IMERG) algorithm combines information from the GPM satellite constellation to estimate precipitation over the majority of the Earth's surface.","msft:region":"westeurope"}