Assistant Professor
Department of Atmospheric and Oceanic Science
University of Maryland, College Park
(Current CV)
What's New
- Goodbye Masaru! (04/04/2012)
- Professor Takeshi Enomoto (Kyoto U) visited UMD and NCEP (03/17/2012)
- A paper on WRF-LETKF has been published (03/02/2012)
- Dr. Kosuke Ito (National Taiwan U) visited NCEP and UMD (02/29/2012)
- A paper on observation error correlations has been accepted (02/04/2012)
Research Interests (more details)
Data assimilation with chaotic dynamical systems, including the weather systems and other components of the earth system. Improving numerical weather prediction through data assimilation, with particular focus on high-impact weather including tropical cyclones (Hurricanes and Typhoons).
- Chaotic dynamical systems, finding the order from chaos
- Predictability, control, and synchronization of chaos
- Improving numerical weather prediction (NWP) through theoretical and practical developments of data assimilation
- Local Ensemble Transform Kalman Filter (LETKF) of weather, ocean, and Matian atmosphere
- Making the most use of satellite observations
- Error correlations with Air-Sea-Land interfaces
- Estimating model parameters using data assimilation
Biographical Sketch (Complete CV)
Upon completing the B.S. degree in theoretical physics from the Kyoto University in 2000, Dr. Takemasa Miyoshi started his professional career as a civil servant at the Japanese Meteorological Agency (JMA). After two years of administrative work at the Planning Division, Dr. Miyoshi started working on numerical weather prediction (NWP) at the Numerical Prediction Division and developed the three-dimensional variational (3D-Var) data assimilation system from scratch for the operational nonhydrostatic regional NWP model. In 2003, Dr. Miyoshi received the Japanese government fellowship to study at the University of Maryland (UMD), and completed both M.S. and Ph.D. degrees on ensemble data assimilation within two years. Many studies have been published using the experimental system that Dr. Miyoshi developed for his dissertation. In 2005, Dr. Miyoshi moved back to JMA and was in charge of developing the JMA's next generation global/regional ensemble data assimilation systems. During the four years at JMA, Dr. Miyoshi came to be recognized as a leading scientist in the field of data assimilation; he was asked to give invited talks at several international conferences and to be a member of the organizing committee of the World Meteorological Organization's data assimilation symposium in Melbourne, the most prestigious conference in the field. In 2008, Dr. Miyoshi received the Yamamoto-Syono Award from the Japanese Meteorological Society. In 2009, Dr. Miyoshi moved to UMD and has been working towards his goals of advancing the science of data assimilation as well as a deep commitment to education.
- Degrees
- 2005 Ph.D. in Meteorology, University of Maryland, College Park, Maryland
- 2004 M.S. in Meteorology, University of Maryland, College Park, Maryland
- 2000 B.S. in Physics, Faculty of Science, Kyoto University, Kyoto, Japan
- Positions
- 2011-present Assistant Professor, University of Maryland, College Park, Maryland
- 2009-2011 Research Assistant Professor, University of Maryland, College Park, Maryland
- 2009 Visiting Assistant Researcher, University of California, Los Angeles, California
- 2005-2008 Scientific Official, Numerical Prediction Division, Japan Meteorological Agency
- 2003-2005 Graduate Student, University of Maryland, College Park, Maryland
- 2002-2003 Scientific Official, Numerical Prediction Division, Japan Meteorological Agency
- 2000-2002 Technical Official, Planning Division, Japan Meteorological Agency
- Awards
- 2008 Yamamoto-Syono Award, Meteorological Society of Japan
- 2003-2005 Japanese Government Long-term Fellowship
Five Selected Papers (Complete List of Publications)
- Miyoshi, T. and M. Kunii, 2012: The Local Ensemble Transform Kalman Filter with the Weather Research and Forecasting Model: Experiments with Real Observations. Pure and Appl. Geophys., 169, 321-333. doi:10.1007/s00024-011-0373-4
- Miyoshi, T., 2011: The Gaussian Approach to Adaptive Covariance Inflation and Its Implementation with the Local Ensemble Transform Kalman Filter. Mon. Wea. Rev., 139, 1519-1535. doi:10.1175/2010MWR3570.1
- Miyoshi, T., Y. Sato, and T. Kadowaki, 2010: Ensemble Kalman filter and 4D-Var inter-comparison with the Japanese operational global analysis and prediction system. Mon. Wea. Rev., 138, 2846-2866. doi:10.1175/2010MWR3209.1
- Miyoshi, T. and S. Yamane, 2007: Local ensemble transform Kalman filtering with an AGCM at a T159/L48 resolution. Mon. Wea. Rev., 135, 3841-3861. doi:10.1175/2007MWR1873.1
- Miyoshi, T. and K. Aranami 2006: Applying a Four-dimensional Local Ensemble Transform Kalman Filter (4D-LETKF) to the JMA Nonhydrostatic Model (NHM). SOLA, 2, 128-131. doi:10.2151/sola.2006-033