Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 13, issue 7
Articles | Volume 13, issue 7
https://doi.org/10.5194/gmd-13-3145-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-13-3145-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 13, issue 7
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

Data sets

MLS/Aura Level 2 Temperature V004 M. Schwartz, N. Livesey, and W. Read https://doi.org/10.5067/Aura/MLS/DATA2021

NCEP ADP Global Upper Air and Surface Weather Observations (PREPBUFR format) National Centers for Environmental Prediction/National Weather Service/NOAA/U.S. Department of Commerce https://doi.org/10.5065/Z83F-N512

PANSY radar observational data PANSY Research Group http://pansy.eps.s.u-tokyo.ac.jp/

Aura MLS data GES DISC https://doi.org/10.5067/Aura/MLS/DATA2021

Meteor radar data from Kototabang IUGONET http://search.iugonet.org/metadata/001/00000158

Model code and software

LETKF code T. Miyoshi https://github.com/takemasa-miyoshi/letkf

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.
Read more