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Assessing reference evapotranspiration estimation from reanalysis weather products. An application to the Iberian Peninsula
Author(s) -
Martins Diogo S.,
Paredes Paula,
Raziei Tayeb,
Pires Carlos,
Cadima Jorge,
Pereira Luis S.
Publication year - 2017
Publication title -
international journal of climatology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.58
H-Index - 166
eISSN - 1097-0088
pISSN - 0899-8418
DOI - 10.1002/joc.4852
Subject(s) - evapotranspiration , mean squared error , wind speed , shortwave radiation , environmental science , climatology , meteorology , peninsula , relative humidity , air temperature , mathematics , geography , statistics , radiation , geology , ecology , physics , archaeology , quantum mechanics , biology
Computing crop reference evapotranspiration ( ET o ) with the FAO Penman–Monteith method ( PM‐ET o ) requires maximum and minimum air temperature, shortwave radiation, relative air humidity and wind speed. These data are often not available, thus requiring alternative computation procedures. Although some proposed approximations may provide ET o values with small estimation errors, the physics of the ET processes may then not be well described. The use of reanalysis data, which is common in climate studies, represents an alternative to observation data for the weather variables referred above, when these are not available. This study focuses on the use of the National Center for Environmental Prediction/National Center for Atmospheric Research ( NCEP / NCAR ) blended reanalysis products with gridded data sets for the computation of PM‐ET o in the Iberian Peninsula. A monthly time step was adopted. The PM‐ET o time series computed with the blended reanalysis data sets were compared with those obtained using observations for 130 weather stations in the Iberian Peninsula. Results show that the PM‐ET o computed with blended reanalysis compares well with the series computed from observation data (average root mean square error, RMSE = 0.49 mm day −1 ). The weather variables derived from reanalysis were also compared with observation data. Results supported the quality of ET o computations because, overall, there was a good match between solar radiation (average RMSE = 1.76 MJm −2 day −1 ) and maximum temperature (average RMSE = 1.48 °C) derived from reanalysis and in situ observations. By contrast, the wind speed from reanalysis highly overestimated observations and this is likely a reason for the slight overestimation of ET o computed from reanalysis (percentage bias, PBIAS >20% in 89% of cases). In addition, the reanalysis products are apparently influenced by modelled warming, which contributes to overestimation of the minimum temperature and, to a lesser extent, of the relative humidity. The spatial pattern of accuracy indicators reveals that poorer results correspond to the southern and south‐eastern coastal areas of Iberia, where climate is semi‐arid. The compatibility of the PM‐ET o computed with monthly inputs and of the daily ET o cumulated to the month using the PM‐ET o equation was confirmed, thus allowing to extend conclusions of this study to daily computations. Alternative reanalysis products were also assessed. Tests for ERA ‐Interim reanalysis products revealed overestimation of ET o and those for NCEP / NCAR Reanalysis II have shown large underestimation. Results suggest that the blended reanalysis products are suitable for the estimation of ET o in Iberia since they integrate an appropriate correction of radiation and temperature, which proved essential for the good estimation results obtained.