GLEAM v3

Satellite-based land evaporation and root-zone soil moisture

Dados Bibliográficos

ID23345145
AutoresBrecht Martens (0000-0002-7368-7953, Ghent University, autor correspondente), Diego G Miralles (0000-0001-6186-5751, Ghent University), Hans Lievens (0000-0002-6391-1691, Goddard Space Flight Center), Robin van der Schalie (Vrije Universiteit Amsterdam), Richard A M de Jeu, Richard de Jeu (0000-0002-4498-8984), Diego Fernández-Prieto, Diego Fernández‐Prieto (European Space Research Institute), Hylke E Beck (0000-0003-2553-9566, Joint Research Centre), Wouter Dorigo (0000-0001-8054-7572, TU Wien), Niko E C Verhoest (0000-0003-4116-8881, Ghent University)
Ano2017
Volume10
Fascículo5
Páginas1903-1925
Data de publicação2017-05-17
Peer ReviewedSim
Open AccessSim
TipoARTICLE
PeriódicoGeoscientific Model Development (JOURNAL)
Identificadores do periódicoISSN: 1991-959X • E-ISSN: 1991-9603
EditoraCopernicus GmbH (PUBLISHER • DE)
DOI10.5194/gmd-10-1903-2017
OpenAlexW2485420366
IdiomaEN
Citações recebidas64
Referências citadas115

The Global Land Evaporation Amsterdam Model (GLEAM) is a set of algorithms dedicated to the estimation of terrestrial evaporation and root-zone soil moisture from satellite data. Ever since its development in 2011, the model has been regularly revised, aiming at the optimal incorporation of new satellite-observed geophysical variables, and improving the representation of physical processes. In this study, the next version of this model (v3) is presented. Key changes relative to the previous version include (1) a revised formulation of the evaporative stress, (2) an optimized drainage algorithm, and (3) a new soil moisture data assimilation system. GLEAM v3 is used to produce three new data sets of terrestrial evaporation and root-zone soil moisture, including a 36-year data set spanning 1980–2015, referred to as v3a (based on satellite-observed soil moisture, vegetation optical depth and snow-water equivalent, reanalysis air temperature and radiation, and a multi-source precipitation product), and two satellite-based data sets. The latter share most of their forcing, except for the vegetation optical depth and soil moisture, which are based on observations from different passive and active C- and L-band microwave sensors (European Space Agency Climate Change Initiative, ESA CCI) for the v3b data set (spanning 2003–2015) and observations from the Soil Moisture and Ocean Salinity (SMOS) satellite in the v3c data set (spanning 2011–2015). Here, these three data sets are described in detail, compared against analogous data sets generated using the previous version of GLEAM (v2), and validated against measurements from 91 eddy-covariance towers and 2325 soil moisture sensors across a broad range of ecosystems. Results indicate that the quality of the v3 soil moisture is consistently better than the one from v2: average correlations against in situ surface soil moisture measurements increase from 0.61 to 0.64 in the case of the v3a data set and the representation of soil moisture in the second layer improves as well, with correlations increasing from 0.47 to 0.53. Similar improvements are observed for the v3b and c data sets. Despite regional differences, the quality of the evaporation fluxes remains overall similar to the one obtained using the previous version of GLEAM, with average correlations against eddy-covariance measurements ranging between 0.78 and 0.81 for the different data sets. These global data sets of terrestrial evaporation and root-zone soil moisture are now openly available at www.GLEAM.eu and may be used for large-scale hydrological applications, climate studies, or research on land–atmosphere feedbacks.

Atmospheric sciences · DNS root zone · Evaporation · Geography · Geotechnical engineering · Meteorology · Moisture · Physics · Root (linguistics) · Satellite · Soil water · Water content · Environmental Science · Geology · Meteorological Phenomena and Simulations · Precipitation Measurement and Analysis · Soil Moisture and Remote Sensing · Soil Science