*2.1. Ensemble Numerical Weather Prediction System*

The IMEPC's WRF-based ensemble weather forecasting system produces wind power forecasts over 100 wind farms distributed across the Inner Mongolia Autonomous Region. This system was jointly developed by the Inner Mongolia Meteorological Bureau, the US National Center for Atmospheric Research (NCAR), and Nanjing University of Information Science and Technology (NUIST); it started real-time operational forecasting in late 2019. The system uses the forecasts of the GEOS (USA), GEM (Canada), and GFS (USA) to derive the initial and boundary conditions to drive the WRF forecast members. The system is configured with 10 physical parameterization schemes, including 9 boundary layer schemes and 1 radiation scheme, and 3 stochastic kinetic energy backward feedback dynamical perturbation (SKEP) schemes, making up the 13 perturbation members that are driven by initial and boundary conditions derived from the global model forecasts of the GFS, GEM, and GEOS, respectively. The system constitutes a total of 39 ensemble forecast members.

The details of the 13 WRF members are listed in Table 1. Each member runs with the WRF real-time four-dimensional data assimilation system (WRF-RTFDDA) [23,53–55]. The operational ensemble forecast system runs with 3-hour data assimilation and forecast cycles, and each cycle produces 72-hour forecasts at a temporal resolution of 15 min. The system assimilates the observations of the hub-height wind speed (the wind turbine wind speed) and meteorological tower weather observations of the wind farms in the region, along with various conventional weather observations [56–58].

The ensemble model contains three forecast domains (Figure 1). Domain 2 and Domain 3 cover the central and western plateau regions of the Inner Mongolia Autonomous Region (40~45◦ N, 105~120◦ E), at 2.7 km grid intervals. Domains 2 and 3 are embedded in a coarser grid domain (Domain 1) with a grid size of 13.5 km. Most of the wind farms studied in this paper are located in Domains 2 and 3, featuring complex terrain including stratified high plains, stony hills, terraces, foothills, and inter-hill lowlands. The wind farms are mostly built around four major mountain ranges, including Langshan Mountain (LS), Seertengshan Mountain (SRTS), Ural Mountain (ULS), and Daqingshan Mountain (DQS), along with fan sites located near the Yinshan Mountains (YS), a low plain area to the south of the Hetao Plain (HTPY), and a high plain area near the Xilin Gol League (XLGL) (Figure 1b).


**Table 1.** Mesoscale ensemble prediction member names and parameterization scheme configuration.

#### *2.2. The Observations and Forecasts*

Verification statistics of the ensemble forecasts were calculated based on 411 representative wind turbine sites selected from 130 wind farms, with 1–4 wind turbine sites per wind farm, depending on the wind farm's size. The wind turbine sites are mainly distributed in central Inner Mongolia (Figure 1b). The analysis period was from 1 March to 15 April 2020. Wind speeds at the hub height of the wind turbines, ~50–80 m high from the ground, were retrieved from the SCADA (Supervisory Control and Data Acquisition System) of the wind turbines and averaged to 15-minute windows. To maintain the data continuity, for periods with less than an hour of missing data, a linear interpolation was used to fill in the gaps. For computing the verification statistics, forecasts of the ensemble numerical weather prediction were interpolated to the location and hub height of the selected turbines through a bilinear interpolation method, forming observation and forecast-matched pairs for direct comparison. With 411 wind turbines, 45 days, 72 h of forecasts per day at 15 min intervals, and 39 ensemble members, there were a total of 207,735,840 data samples processed in the verification computation.

To analyze the regional differences in the model forecasts, the wind farms were divided into seven sub-areas according to the distribution of wind farm clusters and topographic characteristics. These areas are marked in the cyan boxes in Figure 2. The wind farm sites in Area 1 are located on the northern slope of Langshan Mountain. The sites in Area 2 are mostly concentrated between Langshan Mountain and Seertengshan Mountain. Area 3 is over the southern part of the Loop Plain to the north of the mountain. Area 4 is between Seertengshan Mountain and Ural Mountain, and some of the turbine sites are close to the local mountain peaks. Area 5 is in the eastern part of Ural Mountain, with higher elevation. Area 6 is located in the relatively more complex area of Daqingshan Mountain to the west of Ural Mountain, with lower elevation, and the turbine sites are more dispersed. Finally, Area 7 is characterized by a high plain area with a flattering topography near the Xilin Gol League. The numbers of stations in these sub-areas are 22, 61, 13, 131, 72, 72, and 40, respectively.

#### *2.3. Evaluation Metrics*

The statistical verification of the ensemble forecasts includes calculation of systematic error (BIAS), mean absolute error (MAE), and correlation coefficient (CC) for all selected wind turbine sites and the wind turbine sites in each sub-area. The ensemble wind speed forecast performance is assessed by examining both individual metrics and their combinations. The three statistical variables are calculated based on the hub-height observed (Xo) and forecast (Xf) 15-minute mean wind speed pairs.

**Figure 1.** (**a**) Schematic diagram of the ensemble prediction domains for wind farms in the Inner Mongolia Autonomous Region. The horizontal resolution of the coarse-grid simulation domain is 13.5 km, and the horizontal resolution of the two-nested fine-grid simulation domain is 2.7 km. The colored background is the terrain. (**b**) Topography (color filled map) and distribution of test stations (black dots) in the study area. The black line in (**b**) marks the provincial boundary of the Inner Mongolia Autonomous Region, while Areas 1–7 mark the seven subregions enclosed by cyan-colored rectangles.

**Figure 2.** Diurnal variation in the observed wind speeds for the seven sub-areas. The red line is the median value, dark blue is 25–75%, and the light blue zone (including dark blue zone) is 5–95%. The x-axis represents the time (UTC).
