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Impact of direct assimilation of ground‐based microwave radiometer on numerical weather prediction: Accounting for interchannel observation error correlations
https://nied-repo.bosai.go.jp/records/7280
https://nied-repo.bosai.go.jp/records/7280a7ffc4bb-a5b2-40f8-8e08-a5d25617fe92
| Item type | researchmap(1) | |||||||||||||||||||||||
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| 公開日 | 2025-07-28 | |||||||||||||||||||||||
| タイトル | ||||||||||||||||||||||||
| 言語 | en | |||||||||||||||||||||||
| タイトル | Impact of direct assimilation of ground‐based microwave radiometer on numerical weather prediction: Accounting for interchannel observation error correlations | |||||||||||||||||||||||
| 言語 | ||||||||||||||||||||||||
| 言語 | eng | |||||||||||||||||||||||
| 著者 |
Yasutaka Ikuta
× Yasutaka Ikuta
× Hiromu Seko
× Kouichi Yoshimoto
× Kentaro Yamamoto
× Takuya Kawabata
× Hiroshi Ishimoto
× Kentaro Araki
× Takuya Tajiri
× Shingo Shimizu
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| 抄録 | ||||||||||||||||||||||||
| 内容記述タイプ | Other | |||||||||||||||||||||||
| 内容記述 | This study clarifies the impact of directly assimilating the brightness temperature from a ground‐based microwave radiometer (GMWR) on the accuracy of numerical weather prediction. The study focuses on heavy rainfall caused by quasi‐stationary band‐haped precipitation systems in Japan. We used the four‐dimensional variational method to assimilate the brightness temperatures observed by the GMWR network of the Japan Meteorological Agency. To efficiently handle interchannel observation error correlations, the observation term of the cost function was reformulated into the sum of squares of independent variables through a variable transformation based on the eigen‐decomposition of the observation error covariance matrix. Variational quality control was also applied to these independent variables, enabling dynamic quality control. As a result of GMWR assimilation, the accuracy of 12‐hour lead time precipitation forecasts was significantly improved, with notable reductions in biases in the water vapor and temperature fields, particularly in the lower troposphere. These results demonstrate that proper assimilation of GMWR data improves the accuracy of numerical weather prediction, especially for extreme weather events such as heavy rainfall. | |||||||||||||||||||||||
| 言語 | en | |||||||||||||||||||||||
| 書誌情報 |
en : Quarterly Journal of the Royal Meteorological Society 発行日 2025-07-21 |
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| 出版者 | ||||||||||||||||||||||||
| 言語 | en | |||||||||||||||||||||||
| 出版者 | Wiley | |||||||||||||||||||||||
| ISSN | ||||||||||||||||||||||||
| 収録物識別子タイプ | EISSN | |||||||||||||||||||||||
| 収録物識別子 | 1477-870X | |||||||||||||||||||||||
| DOI | ||||||||||||||||||||||||
| 関連識別子 | 10.1002/qj.5067 | |||||||||||||||||||||||
