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)\uffc2\uffa0a revised formulation of the evaporative stress, (2)\uffc2\uffa0an optimized drainage algorithm, and (3)\uffc2\uffa0a new soil moisture data assimilation system. GLEAM\uffc2\uffa0v3 is used to produce three new data sets of terrestrial evaporation and root-zone soil moisture, including a 36-year data set spanning 1980\uffe2\uff80\uff932015, 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\uffe2\uff80\uff932015) and observations from the Soil Moisture and Ocean Salinity (SMOS) satellite in the v3c data set (spanning 2011\uffe2\uff80\uff932015). 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\uffe2\uff80\uff93atmosphere feedbacks.
", "keywords": ["TERRESTRIAL WATER FLUXES", "QE1-996.5", "PONDEROSA PINE", "CARBON-DIOXIDE EXCHANGE", "WACMOS-ET PROJECT", "TRIPLE COLLOCATION ANALYSIS", "DATA ASSIMILATION SYSTEM", "Geology", "15. Life on land", "01 natural sciences", "DECIDUOUS FOREST", "EDDY-COVARIANCE", "PARAMETER RETRIEVAL MODEL", "13. Climate action", "Earth and Environmental Sciences", "ENERGY-BALANCE", "14. Life underwater", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://gmd.copernicus.org/articles/10/1903/2017/gmd-10-1903-2017.pdf"}, {"href": "https://doi.org/10.5194/gmd-10-1903-2017"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Geoscientific%20Model%20Development", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.5194/gmd-10-1903-2017", "name": "item", "description": "10.5194/gmd-10-1903-2017", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5194/gmd-10-1903-2017"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2016-08-05T00:00:00Z"}}, {"id": "10.1029/2020wr028752", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:16:42Z", "type": "Journal Article", "created": "2021-10-17", "title": "Are Remote Sensing Evapotranspiration Models Reliable Across South American Ecoregions", "description": "AbstractMany remote sensing\uffe2\uff80\uff90based evapotranspiration (RSBET) algorithms have been proposed in the past decades and evaluated using flux tower data, mainly over North America and Europe. Model evaluation across South America has been done locally or using only a single algorithm at a time. Here, we provide the first evaluation of multiple RSBET models, at a daily scale, across a wide variety of biomes, climate zones, and land uses in South America. We used meteorological data from 25 flux towers to force four RSBET models: Priestley\uffe2\uff80\uff93Taylor Jet Propulsion Laboratory (PT\uffe2\uff80\uff90JPL), Global Land Evaporation Amsterdam Model (GLEAM), Penman\uffe2\uff80\uff93Monteith Mu model (PM\uffe2\uff80\uff90MOD), and Penman\uffe2\uff80\uff93Monteith Nagler model (PM\uffe2\uff80\uff90VI). was predicted satisfactorily by all four models, with correlations consistently higher () for GLEAM and PT\uffe2\uff80\uff90JPL, and PM\uffe2\uff80\uff90MOD and PM\uffe2\uff80\uff90VI presenting overall better responses in terms of percent bias (%). As for PM\uffe2\uff80\uff90VI, this outcome is expected, given that the model requires calibration with local data. Model skill seems to be unrelated to land\uffe2\uff80\uff90use but instead presented some dependency on biome and climate, with the models producing the best results for wet to moderately wet environments. Our findings show the suitability of individual models for a number of combinations of land cover types, biomes, and climates. At the same time, no model outperformed the others for all conditions, which emphasizes the need for adapting individual algorithms to take into account intrinsic characteristics of climates and ecosystems in South America.
", "keywords": ["ATMOSPHERE WATER FLUX", "550", "VEGETATION INDEX", "Penman-Monteith", "RIPARIAN EVAPOTRANSPIRATION", "0207 environmental engineering", "02 engineering and technology", "SURFACE-TEMPERATURE", "01 natural sciences", "transpiration", "SEMIARID ENVIRONMENT", "CARBON-DIOXIDE", "ENERGY-BALANCE CLOSURE", "https://purl.org/becyt/ford/1.5", "https://purl.org/becyt/ford/1", "Water Science and Technology", "0105 earth and related environmental sciences", "RAINFALL INTERCEPTION", "PRIESTLEY-TAYLOR", "WACMOS-ET PROJECT", "TRANSPIRATION", "15. Life on land", "EDDY COVARIANCE MEASUREMENTS", "name=Water and Environmental Engineering", "MODIS", "13. Climate action", "Earth and Environmental Sciences", "Priestley-Taylor", "PENMAN-MONTEITH", "/dk/atira/pure/core/keywords/water_and_environmental_engineering"]}, "links": [{"href": "https://centaur.reading.ac.uk/101236/1/agujournaltemplateDinizetal.pdf"}, {"href": "https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2020WR028752"}, {"href": "https://doi.org/10.1029/2020wr028752"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Water%20Resources%20Research", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1029/2020wr028752", "name": "item", "description": "10.1029/2020wr028752", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1029/2020wr028752"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-11-01T00:00:00Z"}}, {"id": "10.3390/rs10111720", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-20T16:19:10Z", "type": "Journal Article", "created": "2018-10-31", "title": "Towards Estimating Land Evaporation at Field Scales Using GLEAM", "description": "The evaporation of water from land into the atmosphere is a key component of the hydrological cycle. Accurate estimates of this flux are essential for proper water management and irrigation scheduling. However, continuous and qualitative information on land evaporation is currently not available at the required spatio-temporal scales for agricultural applications and regional-scale water management. Here, we apply the Global Land Evaporation Amsterdam Model (GLEAM) at 100 m spatial resolution and daily time steps to provide estimates of land evaporation over The Netherlands, Flanders, and western Germany for the period 2013\uffe2\uff80\uff932017. By making extensive use of microwave-based geophysical observations, we are able to provide data under all weather conditions. The soil moisture estimates from GLEAM at high resolution compare well with in situ measurements of surface soil moisture, resulting in a median temporal correlation coefficient of 0.76 across 29 sites. Estimates of terrestrial evaporation are also evaluated using in situ eddy-covariance measurements from five sites, and compared to estimates from the coarse-scale GLEAM v3.2b, land evaporation from the Satellite Application Facility on Land Surface Analysis (LSA-SAF), and reference grass evaporation based on Makkink\uffe2\uff80\uff99s equation. All datasets compare similarly with in situ measurements and differences in the temporal statistics are small, with correlation coefficients against in situ data ranging from 0.65 to 0.95, depending on the site. Evaporation estimates from GLEAM-HR are typically bounded by the high values of the Makkink evaporation and the low values from LSA-SAF. While GLEAM-HR and LSA-SAF show the highest spatial detail, their geographical patterns diverge strongly due to differences in model assumptions, model parameterizations, and forcing data. The separate consideration of rainfall interception loss by tall vegetation in GLEAM-HR is a key cause of this divergence: while LSA-SAF reports maximum annual evaporation volumes in the Green Heart of The Netherlands, an area dominated by shrubs and grasses, GLEAM-HR shows its maximum in the national parks of the Veluwe and Heuvelrug, both densely-forested regions where rainfall interception loss is a dominant process. The pioneering dataset presented here is unique in that it provides observational-based estimates at high resolution under all weather conditions, and represents a viable alternative to traditional visible and infrared models to retrieve evaporation at field scales.
", "keywords": ["microwave remote sensing", "EVAPOTRANSPIRATION", "WACMOS-ET PROJECT", "Science", "FLUXNET", "Q", "LSA-SAF", "15. Life on land", "01 natural sciences", "6. Clean water", "MODEL", "CARBON", "VARIABILITY", "terrestrial evaporation", "root-zone soil moisture", "13. Climate action", "Earth and Environmental Sciences", "SURFACE EVAPORATION", "GLOBAL DATABASE", "WATER", "SOIL-MOISTURE RETRIEVALS", "terrestrial evaporation; root-zone soil moisture; microwave remote sensing; GLEAM; LSA-SAF", "GLEAM", "0105 earth and related environmental sciences"]}, "links": [{"href": "http://www.mdpi.com/2072-4292/10/11/1720/pdf"}, {"href": "https://doi.org/10.3390/rs10111720"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Remote%20Sensing", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3390/rs10111720", "name": "item", "description": "10.3390/rs10111720", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3390/rs10111720"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-10-31T00:00:00Z"}}], "links": [{"rel": "self", "type": "application/geo+json", "title": "This document as GeoJSON", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=WACMOS-ET+PROJECT&f=json", "hreflang": "en-US"}, {"rel": "alternate", "type": "text/html", "title": "This document as HTML", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=WACMOS-ET+PROJECT&f=html", "hreflang": "en-US"}, {"rel": "collection", "type": "application/json", "title": "Collection URL", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main", "hreflang": "en-US"}, {"type": "application/geo+json", "rel": "first", "title": "items (first)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=WACMOS-ET+PROJECT&", "hreflang": "en-US"}, {"rel": "last", "type": "application/geo+json", "title": "items (last)", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items?keywords=WACMOS-ET+PROJECT&offset=3", "hreflang": "en-US"}], "numberMatched": 3, "numberReturned": 3, "distributedFeatures": [], "timeStamp": "2026-09-20T21:01:07.921138Z"}