Articles | Volume 19, issue 10
https://doi.org/10.5194/bg-19-2557-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-19-2557-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
19 May 2022
Research article |
| 19 May 2022
| 19 May 2022
Assimilation of passive microwave vegetation optical depth in LDAS-Monde: a case study over the continental USA
Anthony Mucia
CNRM, Université de Toulouse, Météo-France, CNRS, 31057, Toulouse, France
Bertrand Bonan
CNRM, Université de Toulouse, Météo-France, CNRS, 31057, Toulouse, France
Clément Albergel
CNRM, Université de Toulouse, Météo-France, CNRS, 31057, Toulouse, France
European Space Agency Climate Office, ECSAT, Harwell Campus, Oxfordshire, Didcot, OX11 0FD, UK
Yongjun Zheng
CNRM, Université de Toulouse, Météo-France, CNRS, 31057, Toulouse, France
Jean-Christophe Calvet
CORRESPONDING AUTHOR
CNRM, Université de Toulouse, Météo-France, CNRS, 31057, Toulouse, France
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Short summary
For the first time, microwave vegetation optical depth data are assimilated in a land surface model in order to analyze leaf area index and root zone soil moisture. The advantage of microwave products is the higher observation frequency. A large variety of independent datasets are used to verify the added value of the assimilation. It is shown that the assimilation is able to improve the representation of soil moisture, vegetation conditions, and terrestrial water and carbon fluxes.
For the first time, microwave vegetation optical depth data are assimilated in a land surface...
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