Journal cover Journal topic
Hydrology and Earth System Sciences An interactive open-access journal of the European Geosciences Union
Hydrol. Earth Syst. Sci., 21, 3557-3577, 2017
https://doi.org/10.5194/hess-21-3557-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Research article
14 Jul 2017
Incorporating remote sensing-based ET estimates into the Community Land Model version 4.5
Dagang Wang et al.

Data sets

GLEAM ET dataset version 3.0a
Global Land Evaporation Amsterdam Model (GLEAM) team
http://www.GLEAM.eu
MOD16 Global Terrestrial Evapotranspiration dataset
Numerical Terradynamic Simulation Group (NTSG)
http://www.ntsg.umt.edu/project/mod16
FLUXNET-MTE ET dataset
Max Planck Institute for Biogeochemistry
https://www.bgc-jena.mpg.de/geodb/projects/Data.php
Global streamflow characteristic dataset, multi-year annual average
Amsterdam Critical Zone Hydrology Group
http://hydrology-amsterdam.nl/valorisation/GSCD.html
North American Soil Moisture Database (NASMD) soil moisture dataset
Department of Geography's Climate Science Lab at Texas A&M University
http://soilmoisture.tamu.edu/
Latent flux measurements
AmeriFlux network
http://ameriflux.lbl.gov/
Publications Copernicus
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Short summary
Land surface models bear substantial biases. To reduce model biases, we apply a simple but efficient bias correction method to a land surface model. We first derive a relationship between observations and model simulations, and apply this relationship in the application period. While the bias correction method improves model-based estimates without improving the model physical parameterization, results do provide guidance for physically based model development effort.
Land surface models bear substantial biases. To reduce model biases, we apply a simple but...
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