Articles | Volume 10, issue 5
Geosci. Model Dev., 10, 1903–1925, 2017
https://doi.org/10.5194/gmd-10-1903-2017
Geosci. Model Dev., 10, 1903–1925, 2017
https://doi.org/10.5194/gmd-10-1903-2017

Model description paper 17 May 2017

Model description paper | 17 May 2017

GLEAM v3: satellite-based land evaporation and root-zone soil moisture

Brecht Martens et al.

Related authors

ERA5-Land: A state-of-the-art global reanalysis dataset for land applications
Joaquín Muñoz-Sabater, Emanuel Dutra, Anna Agustí-Panareda, Clément Albergel, Gabriele Arduini, Gianpaolo Balsamo, Souhail Boussetta, Margarita Choulga, Shaun Harrigan, Hans Hersbach, Brecht Martens, Diego G. Miralles, María Piles, Nemesio J. Rodríguez-Fernández, Ervin Zsoter, Carlo Buontempo, and Jean-Noël Thépaut
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2021-82,https://doi.org/10.5194/essd-2021-82, 2021
Preprint under review for ESSD
Short summary
Evaluating the land-surface energy partitioning in ERA5
Brecht Martens, Dominik L. Schumacher, Hendrik Wouters, Joaquín Muñoz-Sabater, Niko E. C. Verhoest, and Diego G. Miralles
Geosci. Model Dev., 13, 4159–4181, https://doi.org/10.5194/gmd-13-4159-2020,https://doi.org/10.5194/gmd-13-4159-2020, 2020
Short summary
Global biosphere–climate interaction: a causal appraisal of observations and models over multiple temporal scales
Jeroen Claessen, Annalisa Molini, Brecht Martens, Matteo Detto, Matthias Demuzere, and Diego G. Miralles
Biogeosciences, 16, 4851–4874, https://doi.org/10.5194/bg-16-4851-2019,https://doi.org/10.5194/bg-16-4851-2019, 2019
Short summary
Exploring the merging of the global land evaporation WACMOS-ET products based on local tower measurements
Carlos Jiménez, Brecht Martens, Diego M. Miralles, Joshua B. Fisher, Hylke E. Beck, and Diego Fernández-Prieto
Hydrol. Earth Syst. Sci., 22, 4513–4533, https://doi.org/10.5194/hess-22-4513-2018,https://doi.org/10.5194/hess-22-4513-2018, 2018
Short summary
Evaluating and improving the Community Land Model's sensitivity to land cover
Ronny Meier, Edouard L. Davin, Quentin Lejeune, Mathias Hauser, Yan Li, Brecht Martens, Natalie M. Schultz, Shannon Sterling, and Wim Thiery
Biogeosciences, 15, 4731–4757, https://doi.org/10.5194/bg-15-4731-2018,https://doi.org/10.5194/bg-15-4731-2018, 2018
Short summary

Related subject area

Hydrology
Parametrization of a lake water dynamics model MLake in the ISBA-CTRIP land surface system (SURFEX v8.1)
Thibault Guinaldo, Simon Munier, Patrick Le Moigne, Aaron Boone, Bertrand Decharme, Margarita Choulga, and Delphine J. Leroux
Geosci. Model Dev., 14, 1309–1344, https://doi.org/10.5194/gmd-14-1309-2021,https://doi.org/10.5194/gmd-14-1309-2021, 2021
Short summary
The global water resources and use model WaterGAP v2.2d: model description and evaluation
Hannes Müller Schmied, Denise Cáceres, Stephanie Eisner, Martina Flörke, Claudia Herbert, Christoph Niemann, Thedini Asali Peiris, Eklavyya Popat, Felix Theodor Portmann, Robert Reinecke, Maike Schumacher, Somayeh Shadkam, Camelia-Eliza Telteu, Tim Trautmann, and Petra Döll
Geosci. Model Dev., 14, 1037–1079, https://doi.org/10.5194/gmd-14-1037-2021,https://doi.org/10.5194/gmd-14-1037-2021, 2021
Short summary
Shyft v4.8: a framework for uncertainty assessment and distributed hydrologic modeling for operational hydrology
John F. Burkhart, Felix N. Matt, Sigbjørn Helset, Yisak Sultan Abdella, Ola Skavhaug, and Olga Silantyeva
Geosci. Model Dev., 14, 821–842, https://doi.org/10.5194/gmd-14-821-2021,https://doi.org/10.5194/gmd-14-821-2021, 2021
Short summary
A distributed simple dynamical systems approach (dS2 v1.0) for computationally efficient hydrological modelling at high spatio-temporal resolution
Joost Buitink, Lieke A. Melsen, James W. Kirchner, and Adriaan J. Teuling
Geosci. Model Dev., 13, 6093–6110, https://doi.org/10.5194/gmd-13-6093-2020,https://doi.org/10.5194/gmd-13-6093-2020, 2020
Short summary
Simulating second-generation herbaceous bioenergy crop yield using the global hydrological model H08 (v.bio1)
Zhipin Ai, Naota Hanasaki, Vera Heck, Tomoko Hasegawa, and Shinichiro Fujimori
Geosci. Model Dev., 13, 6077–6092, https://doi.org/10.5194/gmd-13-6077-2020,https://doi.org/10.5194/gmd-13-6077-2020, 2020
Short summary

Cited articles

Amos, B., Arkebauer, T. J., and Doran, J. W.: Soil surface fluxes of greenhouse gases in an irrigated maize-based agroecosystem, Soil Sci. Soc. Am. J., 69, 387–395, https://doi.org/10.2136/sssaj2005.0387, 2005.
Arain, M. A. and Restrepo-Coupe, N.: Net ecosystem production in a temperate pine plantation in southeastern Canada, Agr. Forest Meteorol., 128, 223–241, 2005.
Ardö, J., Mölder, M., El-Tahir, B. A., and Elkhidir, H. A. M.: Seasonal variation of carbon fluxes in a sparse savanna in semi arid Sudan, Carbon Balance and Management, 3, 1–18, https://doi.org/10.1186/1750-0680-3-7, 2008.
Armstrong, R., Brodzik, M., Knowles, K., and Savoie, M.: Global Monthly EASE-Grid Snow Water Equivalent Climatology, Version 1, https://doi.org/10.5067/KJVERY3MIBPS, 2005.
Aubinet, M., Chermanne, B., Vandenhaute, M., Longdoz, B., Yernaux, M., and Laitat, E.: Long term carbon dioxide exchange above a mixed forest in the Belgian Ardennes, Agr. Forest Meteorol., 108, 293–315, 2001.
Download
Short summary
Terrestrial evaporation is a key component of the hydrological cycle and reliable data sets of this variable are of major importance. The Global Land Evaporation Amsterdam Model (GLEAM, www.GLEAM.eu) is a set of algorithms which estimates evaporation based on satellite observations. The third version of GLEAM, presented in this study, includes an improved parameterization of different model components. As a result, the accuracy of the GLEAM data sets has been improved upon previous versions.