Journal of the Meteorological Society of Japan. Ser. II
Online ISSN : 2186-9057
Print ISSN : 0026-1165
Assimilation of Himawari-8 Clear Sky Radiance Data in JMA’s Global and Mesoscale NWP Systems
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JOURNALS FREE ACCESS Advance online publication

Article ID: 2018-037


 This article reports on the impacts of Himawari-8 Clear Sky Radiance (CSR) data assimilation in the global and mesoscale numerical weather prediction (NWP) systems of the Japan Meteorological Agency (JMA). Adoption of the Advanced Himawari Imager (AHI) on board JMA’s Himawari-8 and -9 satellites has enhanced observational capabilities in terms of spectral, horizontal, and temporal resolution. Improvements brought by the switchover from the Multi-functional Transport Satellite-2 (MTSAT-2) to the new-generation Himawari-8 satellite include an upgrade to the horizontal resolution of CSR data from 64 to 32 km and an increase in the number of available water vapor bands from one to three. CSR products are obtained every hour and distributed to the NWP community. The improved horizontal and spectral resolution of Himawari-8 CSR data provides new information on horizontal water vapor distribution and vertical profiles in data assimilation.

 In data assimilation experiments using JMA’s global NWP system, the assimilation of Himawari-8’s three water vapor bands significantly improved the tropospheric humidity field in analysis, especially in the lower troposphere, as compared to assimilation of the single MTSAT-2 water vapor channel. First-guess (FG) departure statistics for microwave humidity sounders indicated an improvement in the water vapor field, especially over Himawari-8 observation areas. Improved forecasting of tropospheric temperature, humidity, and wind fields for Himawari-8 observation areas was also seen.

 In data assimilation experiments using JMA’s mesoscale NWP system, a disastrous heavy precipitation event that took place in Japan’s Kanto-Tohoku region in 2015 was investigated. A single water vapor band of Himawari-8 CSR corresponding to MTSAT-2 was assimilated, resulting in enhanced contrast of the water vapor field between moist and dry areas, as well as a realistic representation of moist air flows from the ocean in analysis. The changes also improved mesoscale model heavy precipitation forecasts.

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