The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLII-2/W13
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W13, 1729–1733, 2019
https://doi.org/10.5194/isprs-archives-XLII-2-W13-1729-2019
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-2/W13, 1729–1733, 2019
https://doi.org/10.5194/isprs-archives-XLII-2-W13-1729-2019

  05 Jun 2019

05 Jun 2019

REMOTE SENSING OF GLOBAL MONTHLY EVAPOTRANSPIRATION WITH AN ENERGY BALANCE (EB) MODEL

X. Chen1,2, Z. Su3, and Y. Ma1,2 X. Chen et al.
  • 1Key Laboratory of Tibetan Environment Changes and Land Surface Processes, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China
  • 2CAS Center for Excellence in Tibetan Plateau Earth Sciences, Chinese Academy of Sciences, Beijing, China
  • 3Faculty of Geo-Information Science and Earth Observation, University of Twente, Enschede, The Netherlands

Keywords: canopy-air interaction, thermal remote sensing, monthly evapotranspiration, energy balance

Abstract. A global monthly evapotranspiration (ET) product without spatial-temporal gaps for 2000–2017 is delivered by using an energy balance (EB) algorithm and MODIS satellite data. It provides us with a moderate resolution estimate of ET without spatial-temporal gaps on a global scale. The model is driven by monthly remote sensing land surface temperature and ERA-Interim meteorological data. A global turbulent exchange parameterization scheme was developed for global momentum and heat roughness length calculation with remote sensing information. The global roughness length was used in the energy balance model, which uses monthly land-air temperature gradient to estimate the turbulent sensible heat, and take the latent heat flux as a residual of the available energy. This study produced an ET product for global landmass, at a monthly time step and 0.05-degree spatial resolution. The performance of ET data has been evaluated in comparison to hundreds flux sites measurements representing a broad range of land covers and climates. The ET product has a mean bias of 3.3 mm/month, RMSE value of 36.9 mm/month. The monthly ET product can be used to study the global energy and hydrological cycles at either seasonal or inter-annual temporal resolution.