Articles | Volume 14, issue 6
https://doi.org/10.5194/esd-14-1239-2023
https://doi.org/10.5194/esd-14-1239-2023
Research article
 | 
29 Nov 2023
Research article |  | 29 Nov 2023

Interannual land cover and vegetation variability based on remote sensing data in the HTESSEL land surface model: implementation and effects on simulated water dynamics

Fransje van Oorschot, Ruud J. van der Ent, Markus Hrachowitz, Emanuele Di Carlo, Franco Catalano, Souhail Boussetta, Gianpaolo Balsamo, and Andrea Alessandri

Data sets

Dataset underlying van Oorschot et al. (2023) Fransje van Oorschot https://doi.org/10.5281/zenodo.8307861

Model code and software

fvanoorschot/python_scripts_vanoorschot2023: van Oorschot et al. 2023 Fransje van Oorschot https://doi.org/10.5281/zenodo.8254556

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Short summary
Vegetation largely controls land hydrology by transporting water from the subsurface to the atmosphere through roots and is highly variable in space and time. However, current land surface models have limitations in capturing this variability at a global scale, limiting accurate modeling of land hydrology. We found that satellite-based vegetation variability considerably improved modeled land hydrology and therefore has potential to improve climate predictions of, for example, droughts.
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