**1. Introduction**

Potential evapotranspiration (PET) plays an important role in the global terrestrial hydrology cycle. Additionally, PET is used for calculating the water needs of different crops and assessing hydrological and meteorological droughts, water balance analysis, and designing and operating irrigation projects [1]. The authors of [2] reported that, the Penman−Monteith (PM) equation is the standard model to compute the PET on various time scales. However, the authors of [3] reported that computing PET (using PM) is not recommended for arid/hyper-arid regions because it requires a surplus of soil moisture and it requires a large number of meteorological variables, which leads to greater uncertainty of the estimated PET.

**Citation:** Anwar, S.A.; Lazi´c, I. Estimating the Potential Evapotranspiration of Egypt Using a Regional Climate Model and a High-Resolution Reanalysis Dataset. *Environ. Sci. Proc.* **2023**, *25*, 29. https://doi.org/10.3390/ ECWS-7-14253

Academic Editor: Athanasios Loukas

Published: 16 March 2023

**Copyright:** © 2023 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

PET can be computed using simple empirical models, such as temperature-based methods [4,5], radiation-based methods [6] and physically processed-based models (e.g., [2]). Additionally, the authors of [2] reported that the Hargreaves−Samani (HS) method can be recommended directly after PM and it can operate on daily/monthly time scales. Estimating the PET (using HS equation) showed a reliable performance in computing the PET with respect to observations as reported by [7,8]. Further, calibrating the HS showed a reliable performance in computing the PET with respect to PM observations [9–11]. Recently, the authors of [3] calibrated the regional climate model (RegCM4) output using the Climate Research Unit (CRU) and a linear regression model (LRM) at specific locations. However, calibrating the coefficients of the HS equation over Egypt and the role of the lateral boundary condition (used to downscale the RegCM4) in simulating the PET were not considered until the present day. Therefore, the present study aims to:


Section 2 describes the study area and experiment design; Section 3 shows the results of the study. Section 4 provides the discussion and conclusion.

### **2. Materials and Methods**

### *2.1. Study Area*

A brief description of the study area is available in [3]; model domain dimension is covered in Section 2.2.

### *2.2. Model Description and Experiment Design*

This study used the Abdus Salam International Centre for Theoretical Physics (ICTP) regional climate model version 4.7 (hereafter RegCM-4.7.0; [13]). The RegCM is a broad model used for conducting long-term simulations and future regional climate projections in Intercomparison projects [14]. To address the influence of the lateral boundary condition on the simulated PET, two experiments were conducted over the period 1979–2017. The first two years were considered as spin-up to properly initialize the RegCM4 model following [15], so the actual analysis starts at 1981 and ends at 2017. The two experiments adopted both ERA-Interim reanalysis of 1.5 degrees (EIN15; [16]) and NCEP/NCAR reanalysis version 2 of 2.5 degrees (NNRP2; [17]) to downscale the RegCM4 model. The RegCM4 model domain (Figure 1) was customized with grid spacing of 25 km with 60 grid points in both zonal and meridional directions centered at 27◦ latitude and 30◦ longitude. Additionally, the following physical schemes were used in the present study: Emanuel convection scheme over land and ocean [18], radiation scheme of [19] and Holtslag boundary layer scheme [20]. The simulated PET was calculated using the default HS equation as:

$$\text{PET}\_{\text{HS}} = 0.0135 \times \text{SW} \times (\text{T2m} + 17.8) \tag{1}$$

The calibrated version is written as

$$\text{PET}\_{\text{HS}} = 0.0105 \times \text{SW} \times (\text{T2m} + 17.8) \tag{2}$$

Several attempts have been made to obtain a reasonable bias of the calibrated HS equation (using ERA5 as the observational dataset). It was found that swtiching the radiation coefficient from 0.0135 to 0.0105 gave more promising results than calibrating the temperature coefficient (17.8). Note that SW (global incident solar radiation) is expressed

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**Figure 1.** The figure shows the domain dimension and surface elevation (in meters). Please note that the RegCM4 model only supports elevation above mean sea level.

*2.3. Validation Data*

> Various reanalysis products were used to evaluate the RegCM4 performance:


Please note that both ERA5 and ERA5land were used to evaluate the simulated SW and T2m of the RegCM4 (since these fields were used as inputs of the HS equation) to take into account the influence of the horizontal grid spacing of the reanalysis product.

3. Station observation is a major source to monitor the PET changes both spatially and temporally. However, availability of long-term records was not sufficient to evaluate the RegCM4 performance (before and after calibrating the HS equation) in this study. Recently, a new high-resolution global gridded PET (hPET) product was developed [12]. This product uses the hourly meteorological variables provided by the offline land model of the ERA5 reanalysis product [21]. Additionally, it adopts the PM equation to compute the PET and it is integrated over the period 1981–2021 in 0.1-degree grid spacing over the global land area. In the present study, monthly mean PET data were used to evaluate the RegCM4 performance both spatially and for locations defined by [3] in Section 1.

For the purpose of the present study, all products were bilinearly interpolated on the RegCM4 curvilinear grid following [10,15].
