The quality of a numerical weather forecast is influenced by uncertainties that may arise from the initial conditions or the design of the model itself. Specifically, our evaluation of a limited area model wind speed forecasts over Romania shows that forecast errors are significant in areas with complex topography, or other local characteristics. The purpose of this paper is to reduce these errors obtained from a deterministic model forecast. A bias correction method that post-processes the model output was implemented in order to improve the accuracy of the wind speed prediction. The new forecast was evaluated using standard statistical scores, for winter and summer seasons of the year 2016, at six stations in Romania located in areas with different topography. The corrected forecast was also compared to that obtained from a simple linear regression model using both simulated and observed wind speed data. The results show that the application of such methods generally leads to an improvement of the wind speed forecast. Furthermore, the reduction in the forecast error depends both on the particularities of the area and the period under review.

中文翻译：

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一种应用于罗马尼亚模拟风速的后处理方法

数值天气预报的质量受到初始条件或模型本身设计可能产生的不确定性的影响。具体来说，我们对罗马尼亚有限区域模型风速预测的评估表明，在具有复杂地形或其他地方特征的地区，预测误差很大。本文的目的是减少从确定性模型预测中获得的这些误差。实施了对模型输出进行后处理的偏差校正方法，以提高风速预测的准确性。新的预测是使用 2016 年冬季和夏季的标准统计分数在罗马尼亚位于不同地形地区的六个站点进行评估的。校正后的预测也与使用模拟和观察到的风速数据从简单线性回归模型获得的预测进行了比较。结果表明，这些方法的应用通常会导致风速预测的改进。此外，预测误差的减少取决于区域和审查期间的特殊性。