Reliable wind speed data is crucial for applications such as estimating local (future) wind power. Global Climate Models (GCMs) and Regional Climate Models (RCMs) provide forecasts over multi-decadal periods. However, their outputs vary substantially, and higher-resolution models come with increased computational demands. In this study, we analyze how the spatial resolution of different GCMs and RCMs affects the reliability of simulated wind speeds and wind power, using ERA5 data as a reference. We present a systematic procedure for model evaluation for wind resource assessment as a downstream task. Our results show that higher-resolution GCMs and RCMs do not necessarily preserve wind speeds more accurately. Instead, the choice of model, both for GCMs and RCMs, is more important than the resolution or GCM boundary conditions. The IPSL model preserves the wind speed distribution particularly well in Europe, producing the most accurate wind power forecasts relative to ERA5 data.

翻译：可靠的风速数据对于估算局部（未来）风电功率等应用至关重要。全球气候模式（GCMs）和区域气候模式（RCMs）可提供多年代际尺度的预测。然而，其输出结果存在显著差异，且更高分辨率的模型会带来更大的计算需求。本研究以ERA5数据为参考，分析了不同GCMs和RCMs的空间分辨率如何影响模拟风速与风电功率的可靠性。我们提出了一种针对风资源评估这一下游任务的系统化模型评估流程。结果表明，更高分辨率的GCMs和RCMs未必能更准确地保持风速特征。相反，对于GCMs和RCMs而言，模型选择比分辨率或GCM边界条件更为关键。IPSL模型在欧洲地区能特别完好地保持风速分布特征，相对于ERA5数据可生成最精确的风电功率预测。