• Article published in Nature E&E

    A new study using GLEAM shows a maximum of vegetation water use at mesic aridity conditions.

    Version 3.1 datasets

    A new version (v3.1) of the GLEAM global datasets of land evaporation and root-zone soil moisture is now available from the Downloads section.

    State of the Climate

    The land evaporation section of the BAMS State of the Climate report for last year is already published and ready to download.

    GLEAM-HR project granted

    The GLEAM-HR project will investigate the applicability of GLEAM at hyper-resolution using forcing data produced by VanderSat for The Netherlands.

  • Method

    Global Land Evaporation Amsterdam Model

     

    AMSR-E

    General

    GLEAM (Global Land Evaporation Amsterdam Model) is a set of algorithms that separately estimate the different components of land evaporation (or 'evapotranspiration’): transpiration, bare-soil evaporation, interception loss, open-water evaporation and sublimation. Additionally, GLEAM provides surface and root-zone soil moisture, potential evaporation and evaporative stress conditions.

     

    The rationale of the method is to maximize the recovery of information on evaporation contained in current satellite observations of climatic and environmental variables.

     

    GLEAM concept

    Description

    The Priestley and Taylor equation used in GLEAM calculates potential evaporation based on observations of surface net radiation and near-surface air temperature. Estimates of potential evaporation for the land fractions of bare soil, tall canopy and short canopy are converted into actual evaporation using a multiplicative evaporative stress factor based on observations of microwave Vegetation Optical Depth (VOD) and estimates of root-zone soil moisture. The latter is calculated using a multi-layer running-water balance. To try to correct for random forcing errors, observations of surface soil moisture are also assimilated into the soil profile. Interception loss is calculated separately in GLEAM using a Gash analytical model. Finally, estimates of actual evaporation for water bodies and regions covered by ice and/or snow are obtained using an adaptation of the Priestley and Taylor equation.

     

    Key features

    1. Consideration of soil constraint on evaporation.

    2. Detailed parameterization of forest interception.

    3. Extensive use of microwave observations, which is an asset under cloudy conditions.

  • Datasets

    General

    Since its development in 2011, GLEAM has been continuously revised and updated. Recently, a third version of the model (GLEAM v3) has been developed, and three datasets produced using this version of the model are currently available under Downloads.

     

    The GLEAM v3 includes:

    1. A new data assimilation scheme that has been validated for Australia (Martens et al., 2016) and that has been optimised to work at the global scale.
    2. An updated water balance module that describes the infiltration rates as a function of the vertical gradient in soil moisture.
    3. Updated evaporative stress functions that combine the vegetation optical depth and the root-zone soil moisture estimates.

    This version is described in detail by Martens et al. (2017, GMD).

    Evaporation Components from GLEAM

    Version 3.1 datasets

    Differences between GLEAM v3.1 and the previous GLEAM v3.0 are:

    1. The data assimilation system has been switched off over deserts.
    2. Dynamic land cover fractions retrieved from MODIS are used for the v3.1b and c datasets.
    3. The v3.1a dataset has been extended until 2016.
    4. File size has been reduced, yet the format remains the same.

    The three v3.1 datasets differ only in their forcing and spatio-temporal coverage.

    1. GLEAM_v3.1a: a global dataset spanning the 37-year period 1980–2016. The dataset is based on reanalysis net radiation and air temperature, satellite and gauged-based precipitation, VOD, soil moisture, and snow water equivalent.
    2. GLEAM_v3.1b: a 50°N–50°S dataset spanning the 13-year period 2003–2015 and driven exclusively by satellite data.
    3. GLEAM_v3.1c: a 50°N–50°S dataset spanning the 5-year period 2011–2015 and driven exclusively by satellite data, including VOD and soil moisture from SMOS.

    For more detailed information, users are directed to the readme file on the server.

  • User policy

    regarding GLEAM datasets

    Datasets are freely available and can be downloaded after submitting your email. Use of the data is subject to the following terms and conditions:

    Acknowledgements

    Whenever GLEAM datasets are used in a scientific publication, the following references should be cited:

    1. Martens, B., Miralles, D.G., Lievens, H., van der Schalie, R., de Jeu, R.A.M., Fernández-Prieto, D., Beck, H.E., Dorigo, W.A., and Verhoest, N.E.C.: GLEAM v3: satellite-based land evaporation and root-zone soil moisture, Geoscientific Model Development, 10, 1903–1925, doi: 10.5194/gmd-10-1903-2017, 2017.

    2. Miralles, D.G., Holmes, T.R.H., de Jeu, R.A.M., Gash, J.H., Meesters, A.G.C.A., Dolman, A.J.: Global land-surface evaporation estimated from satellite-based observations, Hydrology and Earth System Sciences, 15, 453–469, doi: 10.5194/hess-15-453-2011, 2011.

    Scientific use

    GLEAM datasets will not be used for commercial purposes.

    Feedback

    Any feedback about the datasets and/or website are highly appreciated and can be sent through email to brecht.martens@ugent.be or diego.miralles@ugent.be.

  • Publications

    Methodology description

    1. Martens, B., Miralles, D.G., Lievens, H., van der Schalie, R., de Jeu, R.A.M., Fernández-Prieto, D., Beck, H.E., Dorigo, W.A., and Verhoest, N.E.C.: GLEAM v3: satellite-based land evaporation and root-zone soil moisture, Geoscientific Model Development, 10, 1903–1925, 2017.
    2. Martens, B., Miralles, D.G., Lievens, H., Fernández-Prieto, D., Verhoest, N.E.C.: Improving terrestrial evaporation estimates over continental Australia through assimilation of SMOS soil moisture, International Journal of Applied Earth Observations and Geoinformation, 48, 146–162,  2016.
    3. Miralles, D.G., Holmes, T.R.H., de Jeu, R.A.M., Gash, J.H., Meesters, A.G.C.A., Dolman, A.J.: Global land-surface evaporation estimated from satellite-based observations, Hydrology and Earth System Sciences, 15, 453–469, 2011.
    4. Miralles, D.G., de Jeu, R.A.M., Gash, J.H., Holmes, T.R.H., Dolman, A.J.: Magnitude and variability of land evaporation and its components at the global scale, Hydrology and Earth System Sciences, 15, 967–981, 2011.
    5. Miralles, D.G., Gash, J.H., Holmes, T.R.H., de Jeu, R.A.M., Dolman, A.J.: Global canopy interception from satellite observations, Journal of Geophysical Research, 115, D16122, 2010.

    Recent (selected) publications using GLEAM data

    1. Good, S.P., Moore, G.W., Miralles, D.G. (2017). A mesic maximum in biological water use demarcates biome sensitivity to aridity shifts. Nature Ecology & Evolution, doi: 10.1038/s41559-017-0371-8
    2. Forzieri, G., Alkama, R., Miralles, D.G., Cescatti, A.: Satellites reveal contrasting responses of regional climate to the widespread greening of Earth, Science, doi: 10.1126/science.aal1727, 2017.
    3. Teuling, A.J., Taylor, C.M., Meirink, J.F., Melsen, L.A., Miralles, D.G., van Heerwaarden, C.C., Vautard, R., Stegehuis, A.I., Nabuurs, G.-J., de Arellano, J.V.-G.: Observational evidence for cloud cover enhancement over western European forests, Nature Communications, 8, 14065, 2017.

    4. Guillod, B.P., Orlowsky, B, Miralles, D.G., Teuling, A.J., Seneviratne, S.I.: Reconciling spatial and temporal soil moisture effects on afternoon rainfall, Nature Communications, 6, 1–6, 2015.
    5. Greve, P., Orlowsky, B., Mueller, B., Sheffield, J., Reichstein, M., Seneviratne S.I.: Global assessment of trends in wetting and drying over land, Nature Geoscience, 7, 716–721, 2014.
    6. Jasechko, S., Sharp, Z.D., Gibson, J.J., Birks, S.J., Yi, Y., Fawcett, P.J.: Terrestrial water fluxes dominated by transpiration, Nature, 496, 347–350, 2013.
    7. Lettenmaier, D.P., Alsdorf, D., Dozier, J., Huffman, G.J., Pan, M., Wood E.F.: Inroads of remote sensing into hydrologic science during the WRR era, Water Resources Research, 51, 2015.
    8. Miralles, D.G., Teuling, A.J., van Heerwaarden, C.C., Vilà-Guerau de Arellano, J.: Mega-heatwave temperatures due to combined soil dessiccation and atmospheric heat accumulation, Nature Geoscience, 7, 2014.
    9. Miralles, D.G., van den Berg, M.J., Gash, J.H., Parinussa, R.M., de Jeu, R.A.M., Beck, H.E., Holmes, T, Jiménez, C., Verhoest, N.E.C., Dorigo, W.A., Teuling, A.J., Dolman, A.J.: El Niño–La Niña cycle and recent trends in continental evaporation, Nature Climate Change, 4, 122–126, 2014.
    10. Zhang, Y., Peña-Arancibia, J.L., McVicar, T.R., Chiew, F.H.S., Vaze, J., Liu, C., Lu, X., Zheng, H., Wang., Y., Liu, Y.Y., Miralles, D.G., Pan M.: Multi-decadal trends in global terrestrial evapotranspiration and its components, Scientific Reports, 5, 19124, 2016.

  • Highlights

    . . . from the GLEAM front

     

    Dry-2-Dry ERC project

    Mesic maximum in transpiration

    15/11/2017

    A 'wet-gets-wetter and dry-gets-drier' world will yield a relative decrease in plants use of water. New study led by Dr. Stephen Good from Oregon State University recently published in Nature Ecology & Evolution.

    BAMS State of the Climate

    BAMS State of the Climate report

    25/08/2017

    The State of the Climate report of the Bulletin of the American Meteorological Society (BAMS) for 2016 has just been published. Results based on GLEAM reflect the progressive increase in land evaporation in the Northern Hemisphere for 1980–2016.

    Version 3.1 datasets

    30/05/2017

    A new version (v3.1) of the GLEAM global datasets of land evaporation and root-zone soil moisture is now available from the Downloads section. This version replaces the previous v3.0 version. Updates are described in the readme file that can be found in the data server.

    Local climatic effects of global greening

    28/05/2017

    A new study in Science journal using GLEAM shows the effect of wide-spread greening on the local cooling of semiarid regions via transpiration, and the warming of high latitudes through a reduction in surface albedo. This coupling is intensified during extreme years.

    GLEAM version 3 article

    17/05/2017

    The final paper describing the novel aspects of GLEAM v3 and the validation of the v3 datasets against in situ data has been published in GMD. This paper serves as an official reference for the v3 datasets. Check our user policy.

    GLEAM-HR project

    GLEAM-HR project granted

    12/04/2017

    The GLEAM-HR project will investigate the possibility to apply GLEAM at hyper-resolution using fine-scale satellite-based forcing data produced by VanderSat. Initially, the fine-scale evaporation product will only be produced for The Netherlands. The work will take place over the next year.

    Remote Sensing of Environment paper

    New article on data assimilation

    19/02/2017

    A new paper describing the benefits of jointly assimilating radar backscatter and radiometer brightness temperature observations to improve soil moisture and land evaporation estimates in GLEAM has been published in Remote Sensing of the Environment.

    MSWEP precipitation dataset

    MSWEP: high-accuracy rainfall record

    06/02/2016

    The Multi-Source Weighted-Ensemble Precipitation (MSWEP) dataset is a new precipitation product, selected as forcing for the GLEAM v3a dataset. The rationale of MSWEP is to optimally merge precipitation data retrieved from satellite-, gauge- and reanalysis products. The HESS paper describing MSWEP can be found here.

    Dry-2-Dry ERC project

    New ERC grant using GLEAM

    29/09/2016

    The ERC-granted DRY–2–DRY project will investigate drought self-intensification and self-propagation via land feedbacks. The work will take place over the next five years and will contribute to improving our understanding of drought evolution.

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