NOAA-21 ATMS Radiometer Precipitation Profiles

GPM's GPROF algorithm retrieves precipitation profiles from the NOAA-21 ATMS passive microwave sensor using a Bayesian method. The dataset provides mean rain rate, vertical cloud structure, and hydrometeor profiles with uncertainty estimates. Version 07 is maintained by the GES DISC.

Use Cases

• Analyze mean_rain_rate and precipitation_vertical_structure to validate and improve global climate models.
• Compare brightness_temperature (Tb) observations with simulated Tb from the a-priori database for sensor calibration studies.
• Assess hydrometeor_profiles and their uncertainty for research on cloud microphysics and storm development.
• Utilize the consistent data record from multiple constellation sensors for long-term precipitation trend analysis.

Strengths

• Provides consistent retrievals across multiple satellite sensors in the GPM constellation.
• Algorithm uses a parametric Bayesian method suitable for a multi-sensor approach.

Limitations

• Specific row count, spatial resolution, and temporal coverage details are not provided in the input.
• Ancillary data sources (GANAL, ECMWF) differ between near-realtime, standard, and climate products, affecting cross-product consistency.

Provenance

Source

GES DISC (Goddard Earth Sciences Data and Information Services Center)

Collection Method

Retrievals from NOAA-21 Advanced Technology Microwave Sounder (ATMS) using the GPROF Bayesian algorithm.

Time Range

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Freshness

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Geography

Global coverage from satellite observations.