Articles | Volume 19, issue 10
Biogeosciences, 19, 2557–2581, 2022
https://doi.org/10.5194/bg-19-2557-2022

Special issue: Microwave remote sensing for improved understanding of vegetation–water...

Biogeosciences, 19, 2557–2581, 2022
https://doi.org/10.5194/bg-19-2557-2022
Research article
19 May 2022
Research article | 19 May 2022

Assimilation of passive microwave vegetation optical depth in LDAS-Monde: a case study over the continental USA

Anthony Mucia et al.

Data sets

The global long-term microwave vegetation optical depth climate archive VODCA (1.0) L. Moesinger, W. Dorigo, R. De Jeu, R. Van der Schalie, T. Scanlon, I. Teubner, and M. Forkel https://doi.org/10.5281/zenodo.2575599

ESA Soil Moisture Climate Change Initiative (Soil_Moisture_cci): COMBINED Product, Version 04.7 (https://data.ceda.ac.uk/neodc/esacci/soil_moisture/data/daily_files/COMBINED/v04.7) W. Dorigo, W. Preimesberger, A. Pasik, L. Moesinger, R. Van der Schalie, S. Hahn, T. Scanlon, W. Wagner, A. Gruber, R. Kidd, C. Paulik, C. Reimer, and R. De Jeu https://doi.org/10.5285/0683e320d8634a37aa1d9ef62dd41a0d

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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.
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