## 1 Introduction
However, such methods are based on assumptions about the boundary layer height and dynamics, as well as the atmospheric stability and clouds, which are not always true and can lead to considerable biases in the wind energy potential estimation [16; 17]. The WRF model is one of the most commonly widely used meteorological models for simulating the wind regime and for wind resource assessment studies [18; 19; 20; 21]. Minimizing errors in wind simulation involves testing and selecting an appropriate numerical and physical configuration tailored to the specific region of interest, along with the utilization of high-resolution terrain data, when accessible [22]. WRF was used to simulate the planetary boundary layer over the period 2011 to 2015, aiming to assess the wind resources in eastern Iran [23]. Wind simulations via the WRF model have been used in many studies to investigate dust rising, transportation and propagation in the Middle East [24; 25; 26; 27]. Furthermore, several studies have employed numerical models in the evaluation of the wind energy resources in various areas around the world [28; 29; 30; 31]. Nonetheless, there are several sources of errors and uncertainty in numerical model simulations, such as the representation of sub-grid physical processes (like the ones related to the surface layer, SL, and the planetary boundary layer, PBL) that cannot be explicitly resolved by the models [17; 32]. To consider these processes in numerical weather prediction (NWP) models, some assumptions and approximations are included in the models that allow them to implicitly represent these unresolved processes, called physical parametrizations. WRF is a complex model containing some numerical, dynamical and physical options that can be individually chosen by the user [33; 34; 35]. The choice of a given set of physical parameterizations can have a significant impact in wind simulation and wind energy estimation over a given area. Several studies have dealt with the evaluation of the sensitivity of the WRF model to make the choice of PBL parameterizations in wind simulations [36; 37; 38; 39; 40; 41; 42; 43; 44; 45; 46; 47]. These studies revealed that the simulation of the wind field is sensitive to the physical parameterization's selection, and that the performance of these parameterizations vary significantly according to the studied geographical region, highlighting the need to carry out sensitivity studies to determine the optimal model configuration for the simulation of the wind regime in a specific area. Iran is currently very dependent on fossil fuels in terms of its energy demand and economic exports [48; 49; 50]. So, under a climate change scenario in the Middle East [51; 52], in the future, Iran will have to implement renewable energy systems for the purposes of covering increased energy demands. The need for wind energy resource assessment in various parts of Iran has gained growing importance, aiming to expand the country's energy resources and to reduce fossil fuel consumption [48; 53; 54]. For this issue, sources of accurate wind data are very crucial. Initial studies using wind measurements revealed that Iran has an attractive wind energy potential [55; 56]. However, because of the country's vastness and the lack of consistent wind measurement campaigns, and/or a dense meteorological network for wind measurements in remote areas of the country, it is presently very difficult to map the areas of the country with exploitable wind energy potential. Therefore, the use of NWP simulated data is an inevitable necessity, and the most significant gap in this issue is the lack of evaluation of the performance of different model schemes, as well as the absence of long-term simulations of wind fields in this vast and highly complex topographic region. This subject has received little attention so far, and only a limited number of studies have been conducted using NWP models to evaluate the wind energy potential in Iran [45], while all studies focused on the eastern part of the country [57; 58].