Daily mean air temperature (TMP) is an important indicator for a climate change study and it reflects the daily changes of the maximum and minimum air temperature. Downscaling of a General Circulation Model (GCM) to a regional scale is important to ensure accurate simulation of the TMP. To address this issue, a comparison was conducted between Direct Downscaling (DIR) and one-way nesting (NEST) using a Regional Climate Model (RegCM4) in the period 1997-2017 over Egypt. The ERA-Interim reanalysis of 1.5 degrees (EIN15) was used as the atmospheric forcing to downscale the RegCM4 over Egypt, while the fifth generation ECMWF atmospheric reanalysis was used to evaluate the RegCM4 concerning the Total Cloud Cover (CLT), surface short and longwave radiation fluxes (RSDS and RLDS), ground temperature (TS), sensible heat flux (HFSS) and TMP. Results showed that there was no difference between DIR and NEST regarding the CLT and RSDS; while the NEST overestimated the RLDS more than the DIR particularly in the summer and autumn seasons in comparison with ERA5. Furthermore, the difference between DIR and NEST as the NEST overestimated the TS more than DIR in all seasons and in particular the summer and autumn seasons. This noted overestimation propagated to the HFSS explaining the high warm bias in the simulated TMP; which was higher in NEST than DIR. Such findings suggest that DIR was only affected by uncertainty associated with the EIN15. Additionally, this uncertainty was amplified using NEST because the uncertainty of EIN15 first propagated to the mother domain and then from the mother to the nested one. Despite of observed biases, DIR shows promising results more than NEST. Therefore, DIR can be recommended for future climate studies over Egypt.

Accurate forecast of the Potential Evapotranspiration (PET) at a location (where station observation is not available) is necessary in arid/hyper-arid regions (e.g., Egypt) to monitor daily agricultural activities. The Penman-Monteith equation is the standard physical method to compute the PET, but it requires many variables (mostly are calculated empirically). Instead, the Hargreaves-Samani (HS) method was used because it is recommended by the Food and Agriculture Organization and it requires only two variables: global incident solar radiation and daily mean air temperature. Additionally, regional climate models (e.g., RegCM4) can be an alternative tool to estimate the PET constrained by a long-term gridded PET data (Climate Research Unit; CRU) at any location. To accomplish this task, a 39-year simulation was conducted. The RegCM4 was driven by the ERA-Interim reanalysis with 60 km grid spacing. Preliminary results indicated that the RegCM4 was able to capture the monthly variability of the simulated PET with respect to the CRU; however the model overestimates the PET particularly in the summer months (June, July and August). Over all considered locations, performance of the RegCM4 was notably improved when a linear regression model (LRM; between RegCM4 and CRU) was used (indicated by a low bias between the corrected RegCM4 and CRU). In conclusion, the RegCM4 model can accurately calculate the PET at the location of interest by means of the HS equation and a LRM either in the present climate or under different future scenarios.