Cloud liquid water assumption of Precipitation Retrieval Algorithms for the Dual-frequency Precipitation Radar onboard the GPM Core Observatory
Abstract
An assumption related to clouds is one of uncertain factors in precipitation retrievals by the Dual-frequency Precipitation Radar (DPR) onboard the Global Precipitation Measurement (GPM) Core Observatory. While an attenuation due to cloud ice is negligibly small for Ku- and Ka-bands, attenuation by cloud liquid water is larger in the Ka-band and estimating precipitation intensity with high accuracy from Ka-band observations can require developing a method to estimate the attenuation due to cloud liquid water content (CLWC).
This paper describes a CLWC database used in the DPR Level-2 algorithm for the GPM V06A product. In the algorithm, the CLWC value is assumed using the database with inputs of precipitation-related variables, temperature, and geolocation information. A calculation of the database was made using the 3.5-km-mesh global atmospheric simulation derived from the NICAM global cloud-system resolving model. Impacts of current CLWC assumptions for surface precipitation estimates were evaluated by comparisons of precipitation retrieval results between default values and 0 mg/m3 of the CLWC. The impacts were quantified by the Normalized Mean Absolute Difference (NMAD) and the NMAD values showed 2.3% for the Ku, 9.9% for the Ka, and 6.5% for the Dual-Frequency algorithms in global averages, while they were larger in the tropics than in high latitudes.- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2020
- Bibcode:
- 2020AGUFMH200.0002K
- Keywords:
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- 3354 Precipitation;
- ATMOSPHERIC PROCESSES;
- 3360 Remote sensing;
- ATMOSPHERIC PROCESSES;
- 1854 Precipitation;
- HYDROLOGY;
- 1855 Remote sensing;
- HYDROLOGY