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

Brecht Martens,Richard A M De Jeu,Hylke E Beck,Robin Van Der Schalie,Niko E C Verhoest,Diego Fernández-Prieto,Wouter A Dorigo,Hans Lievens,Diego G Miralles

doi:10.5194/gmd-10-1903-2017

Abstract

Abstract. 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.

Highlights

Climate change alters the complex interplay between land and atmosphere, significantly impacting different processes in the global hydrological cycle (Huntington, 2006; Wild et al, 2008; Miralles et al, 2014b)
Global Land Evaporation Amsterdam Model (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, 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 and observations from the Soil Moisture and Ocean Salinity (SMOS) satellite in the v3c data set. 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 eddycovariance towers and 2325 soil moisture sensors across a broad range of ecosystems
The main goal of this study is to present the new version of GLEAM and the resulting evaporation and root-zone soil moisture data sets, including a global validation using a large database of soil moisture measurements from 2325 in situ sensors, and evaporation measurements from 91 eddycovariance towers

Summary

Introduction

Climate change alters the complex interplay between land and atmosphere, significantly impacting different processes in the global hydrological cycle (Huntington, 2006; Wild et al, 2008; Miralles et al, 2014b) Analysing these impacts requires long-term, observational, and consistent data sets of essential hydrological variables, such as soil moisture, precipitation, and terrestrial evaporation (or “evapotranspiration”). The large-scale observation of terrestrial evaporation is hampered by the inability to sense this flux directly from satellites This crucial return flow of water from land into the atmosphere remains one of the most elusive and uncertain components of the global hydrological cycle (Dolman et al, 2014; Miralles et al, 2016b; Fisher et al, 2017). While in the near future, evaporation will remain undetectable from space, several models that combine remotely observable drivers of this flux (e.g. radiation, air temperature, soil moisture) have been developed and are being intensively used in recent years (Wang and Dickinson, 2012; McCabe et al, 2016)

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