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2013•Atmospheric Science LettersRequires access

Comparative assessment of evapotranspiration derived from NCEP and ECMWF global datasets through Weather Research and Forecasting model

Prashant K. Srivastava, Dawei Han, Miguel A. Rico‐Ramirez, Tanvir Islam

Open publisher page 80 citations

Abstract

Abstract In many hydro‐meteorological applications, it is not always possible to get access to in situ weather measurements, especially for the ungauged catchments. This study explores the performances of downscaled weather data for Reference Evapotranspiration (ETo) retrieval using the global European Centre for Medium Range Weather Forecasts (ECMWF) ERA interim and National Centers for Environmental Prediction (NCEP) reanalysis data, simulated through Weather Research and Forecasting (WRF) mesoscale model. The range of the Nash‐Sutcliffe efficiency calculated for the ECMWF pooled datasets derived ETo varies from 0.31 to 0.87, while for NCEP it is found to be 0.11 to 0.38. Bias and Root Mean Square Error (RMSE) are also indicating a very high discrepancy in the NCEP ETo (Bias = −0.05; RMSE = 0.11) as compared to ECMWF (Bias = 0.00; RMSE = 0.06). The overall findings reveal that ECMWF downscaled products have a much better performance than the NCEP's counterparts. Copyright © 2013 Royal Meteorological Society

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What this paper is about

Abstract In many hydro‐meteorological applications, it is not always possible to get access to in situ weather measurements, especially for the ungauged catchments. This study explores the performances of downscaled weather data for Reference Evapotranspiration (ETo) retrieval using the global European Centre for Medium Range Weather Forecasts (ECMWF) ERA interim and National Centers for Environmental Prediction (NCEP) reanalysis data, simulated through Weather Research and Forecasting (WRF) mesoscale model. The range of the Nash‐Sutcliffe efficiency calculated for the ECMWF pooled datasets derived ETo varies from 0.31 to 0.87, while for NCEP it is found to be 0.11 to 0.38. Bias and Root Mean Square Error (RMSE) are also indicating a very high discrepancy in the NCEP ETo (Bias = −0.05; RMSE = 0.11) as compared to ECMWF (Bias = 0.00; RMSE = 0.06). The overall findings reveal that ECMWF downscaled products have a much better performance than the NCEP's counterparts. Copyright © 2013 Royal Meteorological Society

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Available abstract

Abstract In many hydro‐meteorological applications, it is not always possible to get access to in situ weather measurements, especially for the ungauged catchments. This study explores the performances of downscaled weather data for Reference Evapotranspiration (ETo) retrieval using the global European Centre for Medium Range Weather Forecasts (ECMWF) ERA interim and National Centers for Environmental Prediction (NCEP) reanalysis data, simulated through Weather Research and Forecasting (WRF) mesoscale model. The range of the Nash‐Sutcliffe efficiency calculated for the ECMWF pooled datasets derived ETo varies from 0.31 to 0.87, while for NCEP it is found to be 0.11 to 0.38. Bias and Root Mean Square Error (RMSE) are also indicating a very high discrepancy in the NCEP ETo (Bias = −0.05; RMSE = 0.11) as compared to ECMWF (Bias = 0.00; RMSE = 0.06). The overall findings reveal that ECMWF downscaled products have a much better performance than the NCEP's counterparts. Copyright © 2013 Royal Meteorological Society

Key concepts: Weather Research and Forecasting Model, Environmental science, Mean squared error, Evapotranspiration, Climatology, Mesoscale meteorology, Meteorology, Global Forecast System

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