Articles | Volume 14, issue 8
Geosci. Model Dev., 14, 5217–5238, 2021
https://doi.org/10.5194/gmd-14-5217-2021
Geosci. Model Dev., 14, 5217–5238, 2021
https://doi.org/10.5194/gmd-14-5217-2021

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 et al.

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Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on gmd-2021-33', Anonymous Referee #1, 27 Apr 2021
    • AC2: 'Reply on RC1', Xin Huang, 04 Jun 2021
  • RC2: 'Comment on gmd-2021-33', Anonymous Referee #2, 11 May 2021
    • AC3: 'Reply on RC2', Xin Huang, 04 Jun 2021
  • CEC1: 'Comment on gmd-2021-33', Juan Antonio Añel, 14 May 2021
    • AC1: 'Reply on CEC1', Xin Huang, 14 May 2021

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Xin Huang on behalf of the Authors (29 Jun 2021)  Author's response    Author's tracked changes    Manuscript
ED: Referee Nomination & Report Request started (30 Jun 2021) by Hisashi Sato
RR by Anonymous Referee #2 (14 Jul 2021)
ED: Publish as is (15 Jul 2021) by Hisashi Sato
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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.