@article{Irvem_Ozbuldu_2023, title={Evaluation of the performance of CFSR reanalysis data set for estimating reference evapotranspiration (ET0) in Turkey}, url={https://riviste.fupress.net/index.php/IJAm/article/view/1325}, DOI={10.36253/ijam-1325}, abstractNote={<p class="p1">Evapotranspiration is a key process and a necessary parameter for hydrological, meteorological, and agricultural studies. However, the calculation of actual evapotranspiration is very challenging and costly. Therefore, reference evapotranspiration (ET<sub>0</sub>) calculated using meteorological data is generally preferred over actual evapotranspiration. However, it is challenging to get complete and accurate data from meteorology stations in rural and mountainous regions. This study examined the suitability of the Climate Forecast System Reanalysis (CFSR) reanalysis data set as an alternative to meteorological observation stations to compute seasonal reference evapotranspiration for seven different climatic regions of Turkey. The ET<sub>0</sub> calculations using the CFSR reanalysis dataset for 1987-2017 were compared to data at 259 weather stations observed in Turkey. As a result of statistical evaluations, it has been determined that the most successful predicted season is winter (Cā€™ = 0.64-0.89, SPAEF= 0.63-0.81). The most successful estimations for this season were obtained from coastal areas with low elevations. The weakest estimations were obtained for the summer season (Cā€™ = 0.52-0.85, SPAEF= 0.59-0.77). These results show that the ET<sub>0</sub> estimation ability of the CFSR reanalysis dataset is satisfactory for the study area. In addition, it has been observed that CFSR tends to overestimate the observation data, especially in the southern and western regions. These findings indicate that the results of the ET<sub>0</sub> calculation using the CFSR reanalysis data set are relatively successful for the study area. However, the data should be evaluated with observation data before being used, especially in the summer models.</p>}, number={2}, journal={Italian Journal of Agrometeorology}, author={Irvem, Ahmet and Ozbuldu, Mustafa}, year={2023}, month={Jan.}, pages={49ā€“61} }