Performance evaluation of NCEP/NCAR reanalysis blended with observation-based datasets for estimating reference evapotranspiration across Iran

Abstract

Computing crop reference evapotranspiration (ETo) with the FAO Penman-Monteith method (PM-ETo) requires maximum and minimum air temperature, shortwave radiation, relative air humidity, and wind speed that are often unavailable in many places. The use of reanalysis data, which is common in climate studies, represents an alternative to observation data for the mentioned weather variables when are not available. This study focuses on the use of the National Center for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR)reanalysis blended with gridded data sets for computing monthly PM-ETo at 43 synoptic stations distributed across Iran. First, with a set of statistical indicators, the reanalysis weather variables required for computing ETo were compared with observation data, where a good match was obtained for solar radiation, maximum temperature, and minimum temperature. In contrast, at most of the studied stations, the reanalysis wind speed and relative humidity showed large errors when compared with observations. The PM-ETo computed with the blended reanalysis data were also compared with those obtained using observations. The results show that the PM-ETo computed from blended reanalysis compares relatively well with the ETo computedfrom observation at most of the studied stations. However, the spatial pattern of performance indicators reveal extremely poor results for the coastal locations of the Caspian Sea in the north and the Persian Gulf and Oman Sea in the south of Iran. Results suggest that, except for wind speed and relative humidity, the blended reanalysis products are suitable forestimatingETo in inland areas of Iran despitesome degree of overestimationat most of the studied stations.