Satellite Radiometer Precipitation Profiles from SSMIS F16

Version 07 data provides consistent precipitation retrievals from the SSMIS sensor on the DMSP F16 satellite. The Goddard Profiling (2AGPROF) algorithm uses a Bayesian method with an a-priori database to estimate mean rain rate and vertical hydrometeor structure. Data is processed by the GES DISC for the Global Precipitation Measurement (GPM) mission.

Use Cases

• Estimate mean rain rate from retrieved brightness temperature (Tb) observations for regional hydrological studies.
• Analyze the vertical structure of cloud and precipitation hydrometeors to improve atmospheric process models.
• Compare precipitation retrievals and their uncertainty across different sensor types (e.g., SSMIS, GMI, AMSR2) within the GPM constellation.
• Validate forecast models using near-real-time (NRT) product data which incorporates GANAL forecast fields.
• Create long-term climate records by analyzing standard products that use GANAL analysis or climate products that use ECMWF reanalysis.

Strengths

• Algorithm provides consistent retrievals across multiple passive microwave sensors in the GPM constellation.
• Products offer three processing levels (NRT, standard, climate) with different ancillary data for varied use cases.
• Bayesian method is parametric, suited for a multi-satellite constellation approach.

Limitations

• Specific spatial resolution, temporal coverage, row count, and sample size for the SSMIS F16 product are not provided.
• The a-priori database for initial algorithm versions was constructed from various sources, potentially introducing early version inconsistencies.
• Older data versions are superseded and unavailable, limiting historical analysis to the current version's methodology.

Provenance

Source

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

Collection Method

Retrievals from the SSMIS passive microwave radiometer on the DMSP F16 satellite using the Goddard Profiling (2AGPROF) Bayesian algorithm.

Time Range

Temporal coverage is not explicitly stated, but data contributes to the bulk of 3-hour global coverage achieved by GPM.

Freshness

Data is processed in near-real-time (within 3 hours), standard (within 48 hours), and climate (within 3 months) latencies.

Geography

Global spatial coverage from satellite observations.