KONDO, Keiichi

Job title The 3rd Lab./Department of Observation and Data Assimilation Research
E-mail keiichi.kondo[at]mri-jma.go.jp
Personal
Expertise Data assimilation
Degree Doctor
Publications
  • Kondo, K., and T. Miyoshi, 2019: Non-Gaussian statistics in global atmospheric dynamics: a study with a 10240-member ensemble Kalman filter using an intermediate AGCM. Nonlin. Processes Geophys., 26, 211–225.
  • Hatfield, S., P. Duben, M. Chantry, K. Kondo, T. Miyoshi, 2018: Choosing the Optimal Numerical Precision for Data Assimilation in the Presence of Model Error. J. Adv. Modeling Earth Systems, 10, 2177-2191.
  • Yang S.-C., S.-H. Chen, K. Kondo, T. Miyoshi, Y.-C. Liou, Y.-L. Teng and H.-L. Chang, 2017: Multi-localization data assimilation for predicting heavy precipitation associated with a multi-scale weather system. J. Adv. Modeling Earth Systems, 9, 1684-1702.
  • Kondo, K., and T. Miyoshi, 2016: Impact of removing covariance localization in an ensemble Kalman filter: experiments with 10240 members using an intermediate AGCM. Mon. Wea. Rev., 144, 4849-4865.
  • Miyoshi, T., K. Kondo, and K. Terasaki, 2015: Numerical Weather Prediction with Big Ensemble Data Assimilation. Computer, 48, pp. 15-21.
  • Miyoshi, T., K. Kondo, and T. Imamura, 2014: 10240-member ensemble Kalman filtering with an intermediate AGCM. Geophys. Res. Lett., 41, 5264–5271.
  • Kondo, K., T. Miyoshi, and H. L. Tanaka, 2013: Parameter sensitivities of the dual-localization approach in the local ensemble transform Kalman filter. SOLA, 9, 174–178.
  • Miyoshi, T., and K. Kondo, 2013: A multi-scale localization approach to an ensemble Kalman filter. SOLA, 9, 170–173.
  • Kondo, K., and H. L. Tanaka, 2009: Applying the local ensemble transform Kalman filter to the nonhydrostatic icosahedral atmospheric model (NICAM). SOLA, 5, 121-124.
  • Kondo, K., and H. L. Tanaka, 2009: Comparison of the extended Kalman filter and the ensemble Kalman filter using the barotropic general circulation model. J. Meteor. Soc. Japan, 87, 347-359.
Project
  • Research on Data Assimilation Technologies and High-level Use of Observation Data
  • KAKENHI "Hybrid data assimilation methods with a particle filter for forecasts of extreme weather events (2021-2024)"
  • KAKENHI "Clarification of the interaction between Typhoon and upper atmosphere using new generation satellite observations (2019-2021)"
  • JAXA RA "Evaluation and improvement of satellite simulators and assimilation procedures using a global data assimilation system (2019-2022)"
  • Program for Promoting Researches on the Supercomputer Fugaku "Large Ensemble Atmospheric and Environmental Prediction for Disaster Prevention and Mitigation" Theme 1 "Short-range regional prediction", and Theme 3