14:45 〜 15:00
[ACG37-17] Development for assimilation of AMSR3 humidity-sounding channels over land and sea ice using a dynamic emissivity retrieval
キーワード：マイクロ波輝度温度データ同化、数値予報
JAXA’s Advanced Microwave Scanning Radiometer 2 (AMSR2) has been operated on orbit since May 2012 and its microwave radiance data have been assimilated in the JMA’s numerical weather prediction (NWP) systems. The assimilation of microwave radiance data has significantly improved NWP skills. In this context, JAXA plans to operate AMSR3 carried by the Global Observing SATellite for Greenhouse gases and Water cycle (GOSAT-GW). JMA is preparing for assimilation of microwave radiance data from AMSR3.
AMSR3 will have additional three high-frequency channels (165.5 GHz, 183±3 GHz and 183±7 GHz, V-pol). The observations at 183 GHz channels near the water vapor absorption line are designed to measure humidity profile. The observation at 165.5 GHz has information on solid particles in the atmosphere. And these observations are sensitive to the surface properties under dry atmospheric conditions. Therefore, an accurate surface emissivity is one of the important factors for simulating brightness temperatures for data assimilation. To obtain accurate surface emissivity over land and sea ice, dynamic emissivity retrieval (DE) method is applicable (Karbou et al., 2005, Baordo and Geer, 2016). We attempt to apply this method to the humidity-sounding sensors (ATMS, SSMIS, MHS, GMI, MWHS-2) that are already assimilated in the JMA’s NWP systems. We investigated the effect of DE method by comparing observed brightness temperatures with model equivalents for December 2022. As a result, biases and standard deviations between observation and simulation were decreased especially over sea ice area. The reduced errors in the simulated brightness temperature are expected to bring better NWP skills. The results of data assimilation experiments will be presented.
AMSR3 will have additional three high-frequency channels (165.5 GHz, 183±3 GHz and 183±7 GHz, V-pol). The observations at 183 GHz channels near the water vapor absorption line are designed to measure humidity profile. The observation at 165.5 GHz has information on solid particles in the atmosphere. And these observations are sensitive to the surface properties under dry atmospheric conditions. Therefore, an accurate surface emissivity is one of the important factors for simulating brightness temperatures for data assimilation. To obtain accurate surface emissivity over land and sea ice, dynamic emissivity retrieval (DE) method is applicable (Karbou et al., 2005, Baordo and Geer, 2016). We attempt to apply this method to the humidity-sounding sensors (ATMS, SSMIS, MHS, GMI, MWHS-2) that are already assimilated in the JMA’s NWP systems. We investigated the effect of DE method by comparing observed brightness temperatures with model equivalents for December 2022. As a result, biases and standard deviations between observation and simulation were decreased especially over sea ice area. The reduced errors in the simulated brightness temperature are expected to bring better NWP skills. The results of data assimilation experiments will be presented.