Articles | Volume 13, issue 7
https://doi.org/10.5194/gmd-13-3145-2020
https://doi.org/10.5194/gmd-13-3145-2020
Development and technical paper
 | 
13 Jul 2020
Development and technical paper |  | 13 Jul 2020

An ensemble Kalman filter data assimilation system for the whole neutral atmosphere

Dai Koshin, Kaoru Sato, Kazuyuki Miyazaki, and Shingo Watanabe

Related authors

An update on the 4D-LETKF data assimilation system for the whole neutral atmosphere
Dai Koshin, Kaoru Sato, Masashi Kohma, and Shingo Watanabe
Geosci. Model Dev., 15, 2293–2307, https://doi.org/10.5194/gmd-15-2293-2022,https://doi.org/10.5194/gmd-15-2293-2022, 2022
Short summary
Intercomparison of middle atmospheric meteorological analyses for the Northern Hemisphere winter 2009–2010
John P. McCormack, V. Lynn Harvey, Cora E. Randall, Nicholas Pedatella, Dai Koshin, Kaoru Sato, Lawrence Coy, Shingo Watanabe, Fabrizio Sassi, and Laura A. Holt
Atmos. Chem. Phys., 21, 17577–17605, https://doi.org/10.5194/acp-21-17577-2021,https://doi.org/10.5194/acp-21-17577-2021, 2021
Short summary

Related subject area

Atmospheric sciences
Observational operator for fair model evaluation with ground NO2 measurements
Li Fang, Jianbing Jin, Arjo Segers, Ke Li, Ji Xia, Wei Han, Baojie Li, Hai Xiang Lin, Lei Zhu, Song Liu, and Hong Liao
Geosci. Model Dev., 17, 8267–8282, https://doi.org/10.5194/gmd-17-8267-2024,https://doi.org/10.5194/gmd-17-8267-2024, 2024
Short summary
Valid time shifting ensemble Kalman filter (VTS-EnKF) for dust storm forecasting
Mijie Pang, Jianbing Jin, Arjo Segers, Huiya Jiang, Wei Han, Batjargal Buyantogtokh, Ji Xia, Li Fang, Jiandong Li, Hai Xiang Lin, and Hong Liao
Geosci. Model Dev., 17, 8223–8242, https://doi.org/10.5194/gmd-17-8223-2024,https://doi.org/10.5194/gmd-17-8223-2024, 2024
Short summary
An updated parameterization of the unstable atmospheric surface layer in the Weather Research and Forecasting (WRF) modeling system
Prabhakar Namdev, Maithili Sharan, Piyush Srivastava, and Saroj Kanta Mishra
Geosci. Model Dev., 17, 8093–8114, https://doi.org/10.5194/gmd-17-8093-2024,https://doi.org/10.5194/gmd-17-8093-2024, 2024
Short summary
The impact of cloud microphysics and ice nucleation on Southern Ocean clouds assessed with single-column modeling and instrument simulators
Andrew Gettelman, Richard Forbes, Roger Marchand, Chih-Chieh Chen, and Mark Fielding
Geosci. Model Dev., 17, 8069–8092, https://doi.org/10.5194/gmd-17-8069-2024,https://doi.org/10.5194/gmd-17-8069-2024, 2024
Short summary
An updated aerosol simulation in the Community Earth System Model (v2.1.3): dust and marine aerosol emissions and secondary organic aerosol formation
Yujuan Wang, Peng Zhang, Jie Li, Yaman Liu, Yanxu Zhang, Jiawei Li, and Zhiwei Han
Geosci. Model Dev., 17, 7995–8021, https://doi.org/10.5194/gmd-17-7995-2024,https://doi.org/10.5194/gmd-17-7995-2024, 2024
Short summary

Cited articles

Akmaev, R. A.: Whole Atmosphere Modeling: Connecting Terrestrial and Space Weather, Rev. Geophys., 49, RG4004, https://doi.org/10.1029/2011RG000364, 2011. 
Baldwin, M. P. and Dunkerton, T. J.: Stratospheric Harbingers of Anomalous Weather Regimes, Science, 294, 581–584, https://doi.org/10.1126/science.1063315, 2001. 
Batubara, M., Suryana, R., Manik, T., and Sitompul, P.: Kototabang – West Sumatera meteor radar: System design and initial results of a large scale meteor echo, TSSA, 17–21, https://doi.org/10.1109/TSSA.2011.6095399, 2011. 
Becker, E.: Mean-Flow Effects of Thermal Tides in the Mesosphere and Lower Thermosphere, J. Atmos. Sci., 74, 2043–2063, https://doi.org/10.1175/JAS-D-16-0194.1, 2017. 
Becker, E. and Vadas, S. L.: Secondary Gravity Waves in the Winter Mesosphere: Results From a High-Resolution Global Circulation Model, J. Geophys. Res.-Atmos., 123, 2605–2627, https://doi.org/10.1002/2017JD027460, 2018. 
Download
Short summary
A new data assimilation system with a 4D local ensemble transform Kalman filter for the whole neutral atmosphere is developed using a T42L124 general circulation model. A conventional observation dataset and bias-corrected satellite temperature data are assimilated. After the improvements of the forecast model, the assimilation parameters are optimized. The minimum optimal number of ensembles is also examined. Results are evaluated using the reanalysis data and independent radar observations.