2020年業績一覧
査読付原著論文
- Miyoshi, T., S. Kotsuki, K. Terasaki, S. Otsuka, G.-Y. Lien, H. Yashiro, H. Tomita, M. Satoh, and E. Kalnay, 2020: Precipitation Ensemble Data Assimilation in NWP Models. In: Levizzani V., Kidd C., Kirschbaum D., Kummerow C., Nakamura K., Turk F. (eds) Satellite Precipitation Measurement. Advances in Global Change Research, 69, Springer, 983-991. doi:10.1007/978-3-030-35798-6_25
- Chang, C., S. G. Penny, and S. Yang, 2020: Hybrid Gain Data Assimilation Using Variational Corrections in the Subspace Orthogonal to the Ensemble. Mon. Wea. Rev., 148, 2331-2350. https://doi.org/10.1175/MWR-D-19-0128.1
- Hsiang-Wen Cheng, Shu-Chih Yang, Yu-Chieng Liou, Ching-Sen Chen, 2020: An Investigation of the Sensitivity of Predicting a Severe Rainfall Event in Northern Taiwan to the Upstream Condition with a WRF-based Radar Data Assimilation System, SOLA, 2020, Volume 16, Pages 97-103
- Wu, P., S. Yang, C. Tsai, and H. Cheng, 2020: Convective-Scale Sampling Error and Its Impact on the Ensemble Radar Data Assimilation System: A Case Study of a Heavy Rainfall Event on 16 June 2008 in Taiwan. Mon. Wea. Rev., 148, 3631-3652. https://doi.org/10.1175/MWR-D-19-0319.1.
- Tandeo, P., P. Ailliot, M. Bocquet, A. Carrassi, T. Miyoshi, M. Pulido, and Y. Zhen, 2020: A Review of Innovation-Based Methods to Jointly Estimate Model and Observation Error Covariance Matrices in Ensemble Data Assimilation. Mon. Wea. Rev., 148, 3973-3994. https://doi.org/10.1175/MWR-D-19-0240.1
- Sawada, Y., 2020: Machine learning accelerates parameter optimization and uncertainty assessment of a land surface model, Journal of Geophysical Research - Atmospheres, 125, Issue20, e2020JD032688. https://doi.org/10.1029/2020JD032688
- Kotsuki, S., Pensoneault, A., Okazaki, A. and Miyoshi, T., 2020: Weight Structure of the Local Ensemble Transform Kalman Filter: A Case with an Intermediate AGCM., Quart. J. Roy. Meteorol. Soc., 146, Issue732, 3399-3415. doi:10.1002/qj.3852
- H. Yashiro, K. Terasaki, Y. Kawai, S. Kudo, T. Miyoshi, T. Imamura, K. Minami, H. Inoue, T. Nishiki, T. Saji, M. Satoh, and H. Tomita, 2020: A 1024-Member Ensemble Data Assimilation with 3.5-Km Mesh Global Weather Simulations, in SC20: International Conference for High Performance Computing, Networking, Storage and Analysis (SC), Atlanta, GA, US, 2020 pp. 1-10. doi: 10.1109/SC41405.2020.00005
- Amemiya, A. and Sato, K., 2020: Characterizing quasi-biweekly variability of the Asian monsoon anticyclone using potential vorticity and large-scale geopotential height field, Atmospheric Chemistry and Physics, 20, 13857-13876, 2020. https://doi.org/10.5194/acp-2020-424
- Necker, T., S. Geiss, M. Weissmann, J. Ruiz, T. Miyoshi, G.-Y. Lien, 2020: A convective-scale 1000-member ensemble simulation and potential applications. Quart. J. Roy. Meteor. Soc., 146, 1423-1442. doi:10.1002/qj.3744
- Necker, T., M. Weissmann, Y. Ruckstuhl, J. Anderson, and T. Miyoshi, 2020: Sampling error correction evaluated using a convective-scale 1000-member ensemble. Mon. Wea. Rev., 148, 1229-1249. doi:10.1175/MWR-D-19-0154.1
- Maejima, Y. and T. Miyoshi, 2020: Impact of the window length of four-dimensional local ensemble transform Kalman filter: a case of convective rain event. SOLA, 16, 37-42. doi:10.2151/sola.2020-007
- Amemiya, A., T. Honda, and T. Miyoshi, 2020: Improving the observation operator for the Phased Array Weather Radar in the SCALE-LETKF system. SOLA, 16, 6-11. doi:10.2151/sola.2020-002
- Kotsuki S., Y. Sato, and T. Miyoshi, 2020: Data Assimilation for Climate Research: Model Parameter Estimation of Large Scale Condensation Scheme. J. Geophys. Res., 125, e2019JD031304. doi:10.1029/2019JD031304
招待講演
- Kotsuki, S., Miyoshi, T., Kondo, K. and Potthast, R.: A Local Particle Filter and Its Gaussian Mixture Extension: Experiments with an Intermediate AGCM. RIKEN Data Assimilation Seminar, online, September 11, 2020.
- Keiichi Kondo, Shunji Kotsuki, Takemasa Miyoshi, A local particle filter based on non-Gaussian statistics using an intermediate AGCM, DA seminar, online, September 11, 2020.
- Takemasa Miyoshi, Big Data, Big Computation, and Machine Learning in Numerical Weather Prediction, Workshop on Data Assimilation and Uncertainty Quantification at the exascale, online, September 24, 2020.
- Takemasa Miyoshi, Big Data, Big Computation, and Machine Learning in Numerical Weather Prediction,Virtual Event: ECMWF-ESA Workshop on Machine Learning for Earth System Observation and Prediction, online, October 6, 2020.
- 三好 建正、ビッグデータとスーパーコンピュータによる豪雨予測 -世界最先端「ビッグデータ同化」の気象予測研究-、第25回日本難病看護学会 第8回日本難病医療ネットワーク学会合同学術集会、オンライン、2020年11月20日
- Takemasa Miyoshi, Predicting Sudden Local Storms by 30-second-update NWP Using Phased Array Weather Radar, KU-ITB Biweekly Webinar Series, online, November 27, 2020.
受賞
- 大石俊: 日本海洋学会奨励論文賞「Frontolysis by surface heat flux in the eastern Japan Sea: importance of mixed layer depth」 2020年11月28日.
- 三好建正: 令和2年度防災功労者内閣総理大臣表彰. 2020年9月1日.
- 大塚成徳: 令和元年度理化学研究所 桜舞賞 「新しい 3D 降水ナウキャスト手法の開発とリアルタイム実証」 2020年4月3日.
