H200-0002
Cloud liquid water assumption of Precipitation Retrieval Algorithms for the Dual-frequency Precipitation Radar onboard the GPM Core Observatory
Wednesday, 16 December 2020
Poster
Takuji Kubota, JAXA Japan Aerospace Exploration Agency, EORC, Sagamihara, Japan, Shinta Seto, Nagasaki University, Nagasaki, Japan, Satoh Masaki, Atmosphere and Ocean Research Institute, The University of Tokyo, Kashiwa, Japan, Tomoe Nasuno, Japan Agency for Marine-Earth Science and Technology, Kanagawa, Japan, Toshio Iguchi, University of Maryland, Greenbelt, United States, Takeshi Masaki, RESTEC, Tsukuba, Japan, John M. Kwiatkowski, George Mason University Fairfax, Fairfax, United States and Riko Oki, JAXA Japan Aerospace Exploration Agency, Sagamihara, Japan
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.
