• ERC grant to investigate droughts using GLEAM

    The newly granted DRY-2-DRY project will investigate drought self-intensification and self-propagation via land–atmospheric feedbacks.

    Version 3.0 datasets

    A new version (v3.0) of the GLEAM global datasets of land evaporation and root-zone soil moisture is now available from the Downloads section.

    State of the Climate 2015 published

    The BAMS State of the Climate Report 2015 has been published. Results based on an analysis of GLEAM data show the impact of the strong 2015 El Niño event on the global water cycle.

    GLEAM v3 paper published

    A paper describing the novel aspects of GLEAM v3 and the validation of the v3.0 datasets against in situ data has been published online in GMDD. Please note that this paper serves as an official reference for the v3.0 datasets. Check the user policy here.

  • Method

    Global Land Evaporation Amsterdam Model

     

    General

    GLEAM (Global Land Evaporation Amsterdam Model) is a set of algorithms that separately estimate the different components of land evaporation (i.e. 'evapotranspiration'). These include 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 about evaporation contained in current satellite observations of climatic and environmental variables.

     

    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 the Priestley and Taylor equation adapted for ice and super-cooled waters.

     

    Key features

    1. The consideration of soil moisture constraints acting on evaporation

    2. The detailed parameterization of tall-canopy interception loss

    3. The 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 v3.0) has been developed, and three datasets produced using this version of the model are currently available under Downloads.

     

    The GLEAM v3.0 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. (2016, GMDD); a short description is provided below, including a list of the differences from the previous BETA version.

    Version 3.0 datasets

    Differences between this final GLEAM v3.0 and the previous BETA version are:

    1. The data assimilation of surface soil moisture has been switched on.
    2. Datasets have been subject to extensive validation based on in situ measurements of surface soil moisture and evaporation across the globe. Results from these exercises indicate an improved performance relative to the version 2.0 by Miralles et al. (2014).
    3. Datasets have been updated to near present.

    The three v3.0 datasets differ only in their forcing and spatio-temporal coverage.

    1. GLEAM_v3.0a: a global dataset spanning the 35-year period 1980–2014. The dataset are based on reanalysis net radiation and air temperature, satellite and gauged-based precipitation, VOD, soil moisture, and snow water equivalents.
    2. GLEAM_v3.0b: a 50°N–50°S dataset spanning the 13-year period 2003–2015, and driven exclusively by satellite data.
    3. GLEAM_v3.0c: 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 Discussions, doi: 10.5194/gmd-2016-162, 2016.

    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.

  • Highlights

    . . . from the GLEAM front

     

    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–atmospheric feedbacks. The work will take place over the next five years and will contribute to improving our understanding of drought evolution.

    GLEAM v3 paper published

    08/08/2016

    A paper describing the novel aspects of GLEAM v3 and the validation of the v3.0 datasets against in situ data has been published online in GMDD. Results show the added skill of the new set of algorithms. Please note that this paper serves as an official reference for the v3.0 datasets. Check user policy.

    BAMS State of the Climate in 2015 published

    08/08/2016

    The BAMS State of the Climate Report 2015 has been published. Results based on an analysis of GLEAM data show the impact of the strong 2015 El Niño on the terrestrial water cycle. Evaporation anomalies reflects the overlaying effects of multi-decadal climate trends and internal oscillations.

    MSWEP paper online

    06/06/2016

    The Multi-Source Weighted-Ensemble Precipitation (MSWEP) dataset is a new precipitation product selected as forcing for the GLEAM v3.0a dataset. The rationale of MSWEP is to optimally merge precipitation data retrieved from satellite-, gauge- and reanalysis products. The discussion paper describing the full methodology can be found here.

    Version 3.0 datasets

    19/05/2016

    A new version (v3.0) 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 BETA version.

  • 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 v3.0: satellite-based land evaporation and root-zone soil moisture, Geoscientific Model Development Discussions, doi: 10.5194/gmd-2016-162, 2016.
    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, doi: 10.1016/j.jag.2015.09.012, 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, doi: 10.5194/hess-15-453-2011, 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, doi: 10.5194/hess-15-967-2011, 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, doi: 10.1029/2009JD013530, 2010.

    Selected publications using GLEAM data

    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. Reichle, R.H., Koster, R.D., De Lannoy, G.J.M., Forman, B.A., Liu, Q., Mahanama, S.P.P., Toure, A.: Assessment and enhancement of MERRA land surface hydrology estimates, Journal of Climate, 24, 6322–6338, 2011.
    8. Shen, M., Piao, S., Jeong, S.-J., Zhou, L., Zeng, Z., Ciais, P., Chen, D., Huang, M., Jin, C.-S., Li, L.Z.X., Li, Y., Myneni, R.B., Yang, K., Zhang, G., Zhang, Y., and Yao, T.: Evaporative cooling over the Tibetan Plateau induced by vegetation growthProceedings of the National Academy of Sciences USA, 112, 9299–9304, 2015.
    9. Stegehuis, A.I., Vautard, R., Ciais, P., Teuling, A.J., Miralles, D.G., Wild, M.: An observation-constrained multi-physics WRF ensemble for simulating European mega heat waves, Geoscientific Model Development, 8, 2285–2298, 2015.
    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.