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

Data sets

Dataset for four data assimilation studies with MIDA v1.0 Xin Huang https://doi.org/10.5281/zenodo.4762779

Model code and software

Source code of the Model Independent Data Assimilation (MIDA) software Xin Huang https://doi.org/10.5281/zenodo.4762725

Comparison of the time cost using embedded DA algorithm and MIDA with the DALEC model Xin Huang https://doi.org/10.5281/zenodo.4891319

Video supplement

Tutorial videos for Model Independent Data Assimilation (MIDA) module Xin Huang https://doi.org/10.5281/zenodo.4762777

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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.
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