- 著者
- Koji Terasaki Shunji Kotsuki Takemasa Miyoshi
- 出版者
- Meteorological Society of Japan
- 雑誌
- SOLA (ISSN:13496476)
- 巻号頁・発行日
- vol.15, pp.41-46, 2019 (Released:2019-02-28)
- 参考文献数
- 29
- 被引用文献数
- 7
This study investigates the long-term stability of the global atmospheric data assimilation system, incorporating the Local Ensemble Transform Kalman Filter (LETKF) with the Nonhydrostatic ICosahedral Atmospheric Model (NICAM). The NICAM-LETKF system assimilates conventional observations, advanced microwave sounding unit–A (AMSU-A) radiances, and global satellite mapping of precipitation (GSMaP) data. The long-term stability of the data assimilation system can be investigated only by running an expensive long-term experiment. This study successfully performed a data assimilation experiment with more than 2 years of data, using the relaxation to prior spread (RTPS) method for covariance inflation. Analysis fields indicate a stable physical performance compared with the ERA-interim data for the entire experimental period.
- 著者
- Koji Terasaki Shunji Kotsuki Takemasa Miyoshi
- 出版者
- Meteorological Society of Japan
- 雑誌
- SOLA (ISSN:13496476)
- 巻号頁・発行日
- pp.2019-009, (Released:2019-01-31)
- 被引用文献数
- 7
This study investigates the long-term stability of the global atmospheric data assimilation system, incorporating the Local Ensemble Transform Kalman Filter (LETKF) with the Nonhydrostatic ICosahedral Atmospheric Model (NICAM). The NICAM-LETKF system assimilates conventional observations, advanced microwave sounding unit–A (AMSU-A) radiances, and global satellite mapping of precipitation (GSMaP) data. The long-term stability of the data assimilation system can be investigated only by running an expensive long-term experiment. This study successfully performed a data assimilation experiment with more than 2 years of data, using the relaxation to prior spread (RTPS) method for covariance inflation. Analysis fields indicate a stable physical performance compared with the ERA-interim data for the entire experimental period.
- 著者
- Shunji Kotsuki Koji Terasaki Kaya Kanemaru Masaki Satoh Takuji Kubota Takemasa Miyoshi
- 出版者
- Meteorological Society of Japan
- 雑誌
- SOLA (ISSN:13496476)
- 巻号頁・発行日
- vol.15A, pp.1-7, 2019 (Released:2019-01-26)
- 参考文献数
- 25
- 被引用文献数
- 26
This paper is the first publication presenting the predictability of the record-breaking rainfall in Japan in July 2018 (RJJ18), the severest flood-related disaster since 1982. Of the three successive precipitation stages in RJJ18, this study investigates synoptic-scale predictability of the third-stage precipitation using the near-real-time global atmospheric data assimilation system named NEXRA. With NEXRA, intense precipitation in western Japan on July 6 was well predicted 3 days in advance. Comparing forecasts at different initial times revealed that the predictability of the intense rains was tied to the generation of a low-pressure system in the middle of the frontal system over the Sea of Japan. Observation impact estimates showed that radiosondes in Kyusyu and off the east coast of China significantly reduced the forecast errors. Since the forecast errors grew more rapidly during RJJ18, data assimilation played a crucial role in improving the predictability.