State Key Laboratory of Numerical Modeling for Atmospheric Sciences
and Geophysical Fluid Dynamics (LASG), Institute of Atmospheric Physics,
Chinese Academy of Sciences, Beijing, China
Fangli Qiao
First Institute of Oceanography, Ministry of Natural Resources,
Qingdao, China
Key Lab of Marine Science and Numerical Modeling, Ministry of
Natural Resources, Qingdao, China
Ministry of Education Key Laboratory for Earth System Modeling,
Department of Earth System Science, Tsinghua University, Beijing, China
State Key Laboratory of Numerical Modeling for Atmospheric Sciences
and Geophysical Fluid Dynamics (LASG), Institute of Atmospheric Physics,
Chinese Academy of Sciences, Beijing, China
Viewed
Total article views: 2,796 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
BibTeX
EndNote
1,885
777
134
2,796
119
169
HTML: 1,885
PDF: 777
XML: 134
Total: 2,796
BibTeX: 119
EndNote: 169
Views and downloads (calculated since 11 May 2020)
Cumulative views and downloads
(calculated since 11 May 2020)
Total article views: 1,851 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
BibTeX
EndNote
1,324
440
87
1,851
69
115
HTML: 1,324
PDF: 440
XML: 87
Total: 1,851
BibTeX: 69
EndNote: 115
Views and downloads (calculated since 12 May 2021)
Cumulative views and downloads
(calculated since 12 May 2021)
Total article views: 945 (including HTML, PDF, and XML)
HTML
PDF
XML
Total
BibTeX
EndNote
561
337
47
945
50
54
HTML: 561
PDF: 337
XML: 47
Total: 945
BibTeX: 50
EndNote: 54
Views and downloads (calculated since 11 May 2020)
Cumulative views and downloads
(calculated since 11 May 2020)
Viewed (geographical distribution)
Total article views: 2,796 (including HTML, PDF, and XML)
Thereof 2,603 with geography defined
and 193 with unknown origin.
Total article views: 1,851 (including HTML, PDF, and XML)
Thereof 1,802 with geography defined
and 49 with unknown origin.
Total article views: 945 (including HTML, PDF, and XML)
Thereof 801 with geography defined
and 144 with unknown origin.
Data assimilation (DA) provides better initial states of model runs by combining observations and models. This work focuses on the technical challenges in developing a coupled ensemble-based DA system and proposes a new DA framework DAFCC1 based on C-Coupler2. DAFCC1 enables users to conveniently integrate a DA method into a model with automatic and efficient data exchanges. A sample DA system that combines GSI/EnKF and FIO-AOW demonstrates the effectiveness of DAFCC1.
Data assimilation (DA) provides better initial states of model runs by combining observations...
