Seasonal evaluation of evapotranspiration fluxes from MODIS satellite and mesoscale model downscaled global reanalysis datasets

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• 作者：Prashant K. Srivastava ; Dawei Han ; Tanvir Islam…
• 刊名：Theoretical and Applied Climatology
• 出版年：2016
• 出版时间：April 2016
• 年：2016
• 卷：124
• 期：1-2
• 页码：461-473
• 全文大小：668 KB
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• 作者单位：Prashant K. Srivastava (1) (2) (3)
  Dawei Han (3)
  Tanvir Islam (3) (4) (5)
  George P. Petropoulos (6)
  Manika Gupta (7)
  Qiang Dai (3)
  
  1. Hydrological Sciences, NASA Goddard Space Flight Center, Greenbelt, MD, 20771, USA
  2. Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, 20742, USA
  3. Department of Civil Engineering, University of Bristol, Bristol, UK
  4. NOAA/NESDIS Center for Satellite Applications and Research, College Park, MD, 20740, USA
  5. Cooperative Institute for Research in the Atmosphere, Colorado State University, Fort Collins, CO, 80523-1375, USA
  6. Department of Geography and Earth Sciences, University of Aberystwyth, Aberystwyth, Dyfed, SY23 3DB, UK
  7. Water Resources, Department of Civil Engineering, IIT Delhi, Delhi, 110 016, India
  
• 刊物类别：Earth and Environmental Science
• 刊物主题：Earth sciences
  Meteorology and Climatology
  Atmospheric Protection, Air Quality Control and Air Pollution
  Climate Change
  Waste Water Technology, Water Pollution Control, Water Management and Aquatic Pollution
  
• 出版者：Springer Wien
• ISSN：1434-4483

文摘

Reference evapotranspiration (ETo) is an important variable in hydrological modeling, which is not always available, especially for ungauged catchments. Satellite data, such as those available from the MODerate Resolution Imaging Spectroradiometer (MODIS), and global datasets via the European Centre for Medium Range Weather Forecasts (ECMWF) reanalysis (ERA) interim and National Centers for Environmental Prediction (NCEP) reanalysis are important sources of information for ETo. This study explored the seasonal performances of MODIS (MOD16) and Weather Research and Forecasting (WRF) model downscaled global reanalysis datasets, such as ERA interim and NCEP-derived ETo, against ground-based datasets. Overall, on the basis of the statistical metrics computed, ETo derived from ERA interim and MODIS were more accurate in comparison to the estimates from NCEP for all the seasons. The pooled datasets also revealed a similar performance to the seasonal assessment with higher agreement for the ERA interim (r = 0.96, RMSE = 2.76 mm/8 days; bias = 0.24 mm/8 days), followed by MODIS (r = 0.95, RMSE = 7.66 mm/8 days; bias = −7.17 mm/8 days) and NCEP (r = 0.76, RMSE = 11.81 mm/8 days; bias = −10.20 mm/8 days). The only limitation with downscaling ERA interim reanalysis datasets using WRF is that it is time-consuming in contrast to the readily available MODIS operational product for use in mesoscale studies and practical applications.