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GPM MHS on NOAA-19 (GPROF) Radiometer Precipitation Profiling L2A 1.5 hours 17 km V05 (GPM_2AGPROFNOAA19MHS) at GES DISC

Version 5 is the current version of the data set. Version 4 is no longer available and has been superseded by Version 5. 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 (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.

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