Climate & weather

NASA GPM Project

Version 07 is the current version of the data set. Older versions will no longer be available and have been superseded by Version 07. 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...

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Data coverage

Version 07 is the current version of the data set. Older versions will no longer be available and have been superseded by Version 07. 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. The 2AGPROF (also known as, GPM GPROF (Level 2)) algorithm retrieves consistent precipitation and related science fields from the following GMI and partner passive microwave sensors: + TMI (TRMM) + GMI, (GPM) + SSMI (DMSP F15), SSMIS (DMSP F16, F17, F18, F19) + AMSR2 (GCOM-W1) + MHS (NOAA 18,19) + MHS (METOP A,B) + ATMS (NPP) + SAPHIR (MT1) This provides the bulk of the 3-hour coverage achieved by GPM. For each sensor, there are near-realtime (NRT) products, standard products, and climate products. These differ only in the amount of data that are available within 3 hours, 48 hours, and 3 months of collection, as well as the ancillary data used. The NRT product uses GANAL forecast fields. Standard products use the GANAL analysis product, while the climate product uses ECMWF reanalysis in order to allow for consistent data records with earlier missions. These earlier data may be archived separately. The main strength of the product is the large sampling provided. The GPM radiometer algorithms are Bayesian-type algorithms. These algorithms search an a-priori database of potential rain profiles and retrieve a weighted average of these entries based upon the proximity of the observed brightness temperature (Tb) to the simulated Tb corresponding to each rain profile. By using the same a-priori database of rain profiles, with appropriate simulated Tb for each constellation sensor, the Bayesian method is completely parametric and thus well suited for GPM's constellation approach. The a-priori information will be supplied by the combined algorithm supplied by GPM's core satellite as soon after launch as feasible. Databases for V0 of the algorithm had to be constructed from various sources as described in the ATBD. The solution provides a mean rain rate as well as the vertical structure of cloud and precipitation hydrometeors and their uncertainty. GPM1CAQUAAMSRE All 1C products have a common L1C data structure, simple and generic. Each L1C swath includes scan time, latitude and longitude, scan status, quality, incidence angle, Sun glint angle, and the intercalibrated brightness temperature (Tc). One or more swaths are included in a product. The radiometer data are recalibrated to a common basis so that precipitation products derived from them are consistent. 1CSSMIS contains common calibrated brightness temperature from the SSMIS passive microwave instruments flown on the DMSP satellites. Swath S1 has 3 low frequency channels (19V 19H 22V). Swath S2 has 2 low frequency channels (37V 37H). Swath S3 has 4 high frequency channels (150H 183+/-1H 183+/-3H 183+/-7H). S4 has 2 high frequency channels (91V 91H). All the above frequencies are in GHz. Earth observations for all four swaths are taken during a 144o segment of the instrument rotation when SSMIS scans in the direction of foreward satellite motion. We define the spacecraft vector (v) at the center of this segment. GPM2AGPROFNOAA15AMSUBCLIM 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. The 2AGPROF (Goddard Profiling) algorithm retrieves consistent precipitation and related science fields from the following GMI and partner passive microwave sensors: + TMI (TRMM) + GMI, (GPM) + SSMI (DMSP F11, F13, F14, F15); SSMIS (DMSP F16, F17, F18, F19) + AMSR2 (GCOM-W1) + MHS (NOAA 18,19) + MHS (METOP A,B) + ATMS (NPP) + SAPHIR (MT1) This provides the bulk of the 3-hour coverage achieved by GPM. For each sensor, there are nearrealtime (NRT) products, standard products, and climate products. These differ only in the amount of data that are available within 3 hours, 48 hours, and 3 months of collection, as well as the ancillary data used. The NRT product uses GANAL forecast fields. Standard products use the GANAL analysis product, while the climate product uses ECMWF reanalysis in order to allow for consistent data records with earlier missions. These earlier data may be archived separately. The main strength of the product is the large sampling provided. The GPM radiometer algorithms are Bayesian-type algorithms. These algorithms search an apriori database of potential rain profiles and retrieve a weighted average of these entries based upon the proximity of the observed brightness temperature (Tb) to the simulated Tb corresponding to each rain profile. By using the same a-priori database of rain profiles, with appropriate simulated Tb for each constellation sensor, the Bayesian method is completely parametric and thus well suited for GPM's constellation approach. The a-priori information will be supplied by the combined algorithm supplied by GPM's core satellite as soon after launch as feasible. Databases for V0 of the algorithm had to be constructed from various sources as described in the ATBD. The solution provides a mean rain rate as well as the vertical structure of cloud and precipitation hydrometeors and their uncertainty GPM3GPROFNOAA15AMSUBDAYCLIM 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. GPM2AGPROFNOAA20ATMSCLIM Version 07 is the current version of the data set. 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. The 2AGPROF (also known as, GPM GPROF (Level 2)) algorithm retrieves consistent precipitation and related science fields from the following GMI and partner passive microwave sensors: GMI, SSMI (DMSP F15), SSMIS (DMSP F16, F17, F18) AMSR2 (GCOM-W1), TMI MHS (NOAA 18&19, METOP A&B), ATMS (SNPP and NOAA-

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