Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 14, issue 8
Articles | Volume 14, issue 8
https://doi.org/10.5194/gmd-14-5217-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-14-5217-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 14, issue 8
Development and technical paper
 | 
20 Aug 2021
Development and technical paper |  | 20 Aug 2021

A model-independent data assimilation (MIDA) module and its applications in ecology

Xin Huang, Dan Lu, Daniel M. Ricciuto, Paul J. Hanson, Andrew D. Richardson, Xuehe Lu, Ensheng Weng, Sheng Nie, Lifen Jiang, Enqing Hou, Igor F. Steinmacher, and Yiqi Luo

Viewed

Total article views: 5,010 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
3,526 1,401 83 5,010 49 57
  • HTML: 3,526
  • PDF: 1,401
  • XML: 83
  • Total: 5,010
  • BibTeX: 49
  • EndNote: 57
Views and downloads (calculated since 01 Apr 2021)
Cumulative views and downloads (calculated since 01 Apr 2021)

Viewed (geographical distribution)

Total article views: 5,010 (including HTML, PDF, and XML) Thereof 4,749 with geography defined and 261 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 11 Dec 2024
Download
Short summary
In the data-rich era, data assimilation is widely used to integrate abundant observations into models to reduce uncertainty in ecological forecasting. However, applications of data assimilation are restricted by highly technical requirements. To alleviate this technical burden, we developed a model-independent data assimilation (MIDA) module which is friendly to ecologists with limited programming skills. MIDA also supports a flexible switch of different models or observations in DA analysis.
Read more