![三好 建正 https://static.aminer.cn/upload/avatar/1524/341/173/53f369bcdabfae4b349a769f_0.jpg](https://avatarcdn.aminer.cn/upload/avatar/1524/341/173/53f369bcdabfae4b349a769f_0.jpg!160)
Takemasa Miyoshi(三好 建正)
Research
Department of Atmospheric and Oceanic Science
University of Maryland, College Park;RIKEN Center for Computational Science;Application Laboratory, Japan Agency for Marine-Earth Science and Technology;RIKEN Cluster for Pioneering Research;RIKEN interdisciplinary Theoretical and Mathematical Sciences Program
Follow
Claim
分享
Follow
Claim
分享
基本信息
views: 187
![](https://originalfileserver.aminer.cn/sys/aminer/icon/show-trajectory.png)
Bio
Since 2012, Dr. Miyoshi has been leading the Data Assimilation Research Team in RIKEN Center for Computational Science (R-CCS), working towards advancing the science of data assimilation with a deep commitment to education. Dr. Miyoshi's scientific achievements include more than 110 peer-reviewed publications and more than 130 invited conference presentations including the Core Science Keynote at the American Meteorological Society Annual Meeting (2015). Dr. Miyoshi has been recognized by several prestigious awards such as the Yamamoto-Syono Award by the Meteorological Society of Japan (2008), the Young Scientists' Prize by the Minister of Education, Culture, Sports, Science and Technology (2014), the Japan Geosciences Union Nishida Prize (2015), the Meteorological Society of Japan Award (2016) - the highest award of the society, the Yomiuri Gold Medal Prize (2018), and the Commendation by the Prime Minister for Disaster Prevention (2020).
Research Interests
Data assimilation with chaotic dynamical systems such as the weather system. Predictability, control, and synchronization of chaos. Improving numerical weather prediction (NWP) through data assimilation with particular focus on high-impact weather including Tropical Cyclones (Hurricanes and Typhoons).
Theoretical development on data assimilation, including an algorithmic design for efficient computations and methodological development for nonlinear, non-Gaussian applications
Pioneering new applications of data assimilation for various high-performance-computer simulations
Advancing data assimilation for making sense of "Big Data"
Local Ensemble Transform Kalman Filter (LETKF)
Honors and Awards
2020 Commendation by the Prime Minister for Disaster Prevention, September 1, 2020 (防災功労者内閣総理大臣表彰、2020年9月1日)
2018 Excellent Achievement Award, HPCI (High Performance Computing Infrastructure) Project Report Meeting Program Committee, November 2, 2018 (HPCI利用研究課題優秀成果賞、2018年11月2日「ゲリラ豪雨予測を目指した「ビッグデータ同化」の研究」)
2018 RIKEN BAIHO Award (RIKEN Excellent Achievement Award), For FY2017 excellent achievement on Research and Development for Research to Fuse Data Analysis with Simulations, June 5, 2018 (理研梅峰賞)
2018 Gold Medal Prize, Yomiuri Techno Forum (読売テクノ・フォーラム ゴールド・メダル賞、2018年4月25日「ビッグデータ同化によるゲリラ豪雨予測の研究」)
2017 Progress in Earth and Planetary Science (PEPS) The Most Cited Paper Award 2017, Japan Geoscience Union, "The Non-hydrostatic Icosahedral Atmospheric Model: description and development" by Satoh et al.(2017年5月)
2017 Editor's Award, Monthly Weather Review, American Meteorological Society, For prompt and detailed reviews of a large number of manuscripts (January 2017, American Meteorological Society Annual Meeting, Seattle, WA)
2016 Progress in Earth and Planetary Science (PEPS) The Most Accessed Paper Award 2016, Japan Geoscience Union, "The Non-hydrostatic Icosahedral Atmospheric Model: description and development" by Satoh et al.(2016年5月22日)
2016 Meteorological Society of Japan Award (2016年度日本気象学会賞、2016年5月19日「アンサンブルカルマンフィルタによるデータ同化の高度化に関する研究」)
2015 Japan Geoscience Union Nishida Prize 2014 "Studies on advanced data assimilation for improving numerical weather prediction using the local ensemble transform Kalman filter" (2014年度地球惑星科学振興西田賞、2015年5月27日「局所アンサンブル変換カルマンフィルタによる数値データ同化手法の高度化の研究」)
2014 The Young Scientists' Prize, The Commendation for Science and Technology by the Minister of Education, Culture, Sports, Science and Technology (科学技術分野の文部科学大臣表彰 若手科学者賞、2014年4月15日「地球環境シミュレーションにおけるデータ同化の研究」)
2014 Hydraulic Engineering Paper Award, Committee on Hydroscience and Hydraulic Engineering, Japan Society of Civil Engineers (土木学会水工学委員会 水工学論文賞、2014年3月4日「アンサンブルカルマンフィルタを用いた水同位体比データ同化に向けた理想化実験」)
2008 Yamamoto-Syono Award, Meteorological Society of Japan (日本気象学会 山本・正野論文賞、2008年11月20日「Local Ensemble Transform Kalman Filtering with an AGCM at a T159/L48 resolution. Mon. Wea. Rev., 135 (2007), 3841-3861. (by Miyoshi T. and S. Yamane)」)
2006 Accepted participant of the ESF-JSPS Frontier Science Conference Series for Young Researchers, Nynashamn, Sweden (official URL)(Japanese report)
2003-2005 Japanese Government Long-term Fellowship
1996 First Japanese Delegate of National Youth Science Camp, WV, USA
Research Interests
Data assimilation with chaotic dynamical systems such as the weather system. Predictability, control, and synchronization of chaos. Improving numerical weather prediction (NWP) through data assimilation with particular focus on high-impact weather including Tropical Cyclones (Hurricanes and Typhoons).
Theoretical development on data assimilation, including an algorithmic design for efficient computations and methodological development for nonlinear, non-Gaussian applications
Pioneering new applications of data assimilation for various high-performance-computer simulations
Advancing data assimilation for making sense of "Big Data"
Local Ensemble Transform Kalman Filter (LETKF)
Honors and Awards
2020 Commendation by the Prime Minister for Disaster Prevention, September 1, 2020 (防災功労者内閣総理大臣表彰、2020年9月1日)
2018 Excellent Achievement Award, HPCI (High Performance Computing Infrastructure) Project Report Meeting Program Committee, November 2, 2018 (HPCI利用研究課題優秀成果賞、2018年11月2日「ゲリラ豪雨予測を目指した「ビッグデータ同化」の研究」)
2018 RIKEN BAIHO Award (RIKEN Excellent Achievement Award), For FY2017 excellent achievement on Research and Development for Research to Fuse Data Analysis with Simulations, June 5, 2018 (理研梅峰賞)
2018 Gold Medal Prize, Yomiuri Techno Forum (読売テクノ・フォーラム ゴールド・メダル賞、2018年4月25日「ビッグデータ同化によるゲリラ豪雨予測の研究」)
2017 Progress in Earth and Planetary Science (PEPS) The Most Cited Paper Award 2017, Japan Geoscience Union, "The Non-hydrostatic Icosahedral Atmospheric Model: description and development" by Satoh et al.(2017年5月)
2017 Editor's Award, Monthly Weather Review, American Meteorological Society, For prompt and detailed reviews of a large number of manuscripts (January 2017, American Meteorological Society Annual Meeting, Seattle, WA)
2016 Progress in Earth and Planetary Science (PEPS) The Most Accessed Paper Award 2016, Japan Geoscience Union, "The Non-hydrostatic Icosahedral Atmospheric Model: description and development" by Satoh et al.(2016年5月22日)
2016 Meteorological Society of Japan Award (2016年度日本気象学会賞、2016年5月19日「アンサンブルカルマンフィルタによるデータ同化の高度化に関する研究」)
2015 Japan Geoscience Union Nishida Prize 2014 "Studies on advanced data assimilation for improving numerical weather prediction using the local ensemble transform Kalman filter" (2014年度地球惑星科学振興西田賞、2015年5月27日「局所アンサンブル変換カルマンフィルタによる数値データ同化手法の高度化の研究」)
2014 The Young Scientists' Prize, The Commendation for Science and Technology by the Minister of Education, Culture, Sports, Science and Technology (科学技術分野の文部科学大臣表彰 若手科学者賞、2014年4月15日「地球環境シミュレーションにおけるデータ同化の研究」)
2014 Hydraulic Engineering Paper Award, Committee on Hydroscience and Hydraulic Engineering, Japan Society of Civil Engineers (土木学会水工学委員会 水工学論文賞、2014年3月4日「アンサンブルカルマンフィルタを用いた水同位体比データ同化に向けた理想化実験」)
2008 Yamamoto-Syono Award, Meteorological Society of Japan (日本気象学会 山本・正野論文賞、2008年11月20日「Local Ensemble Transform Kalman Filtering with an AGCM at a T159/L48 resolution. Mon. Wea. Rev., 135 (2007), 3841-3861. (by Miyoshi T. and S. Yamane)」)
2006 Accepted participant of the ESF-JSPS Frontier Science Conference Series for Young Researchers, Nynashamn, Sweden (official URL)(Japanese report)
2003-2005 Japanese Government Long-term Fellowship
1996 First Japanese Delegate of National Youth Science Camp, WV, USA
Research Interests
PapersAuthor StatisticsCo-AuthorSimilar Experts
By YearBy Citation主题筛选期刊级别筛选合作者筛选合作机构筛选
时间
引用量
主题
期刊级别
合作者
合作机构
Author Statistics
#Papers: 333
#Citation: 6266
H-Index: 41
G-Index: 75
Sociability: 6
Diversity: 1
Activity: 2
Co-Author
Co-Institution
D-Core
- 合作者
- 学生
- 导师
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn