Journal cover Journal topic
Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
Journal topic

Journal metrics

IF value: 5.240
IF5.240
IF 5-year value: 5.768
IF 5-year
5.768
CiteScore value: 8.9
CiteScore
8.9
SNIP value: 1.713
SNIP1.713
IPP value: 5.53
IPP5.53
SJR value: 3.18
SJR3.18
Scimago H <br class='widget-line-break'>index value: 71
Scimago H
index
71
h5-index value: 51
h5-index51
GMD | Articles | Volume 13, issue 7
Geosci. Model Dev., 13, 3145–3177, 2020
https://doi.org/10.5194/gmd-13-3145-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Geosci. Model Dev., 13, 3145–3177, 2020
https://doi.org/10.5194/gmd-13-3145-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

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 et al.

Viewed

Total article views: 1,887 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
1,584 279 24 1,887 19 20
  • HTML: 1,584
  • PDF: 279
  • XML: 24
  • Total: 1,887
  • BibTeX: 19
  • EndNote: 20
Views and downloads (calculated since 07 Nov 2019)
Cumulative views and downloads (calculated since 07 Nov 2019)

Viewed (geographical distribution)

Total article views: 1,624 (including HTML, PDF, and XML) Thereof 1,622 with geography defined and 2 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Saved (final revised paper)

No saved metrics found.

Saved (preprint)

No saved metrics found.

Discussed (final revised paper)

No discussed metrics found.

Discussed (preprint)

No discussed metrics found.
Latest update: 22 Sep 2020
Publications Copernicus
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.
A new data assimilation system with a 4D local ensemble transform Kalman filter for the whole...
Citation