All numerical weather prediction models used for the wind industry need to produce their forecasts starting from the main synoptic hours 00, 06, 12, and 18 UTC, once the analysis becomes available. The six-hour latency time between two consecutive model runs calls for strategies to fill the gap by providing new accurate predictions having, at least, hourly frequency. This is done to accommodate the request of frequent, accurate and fresh information from traders and system regulators to continuously adapt their work strategies. Here, we propose a strategy where quasi-real time observed wind speed and weather model predictions are combined by means of a novel Ensemble Model Output Statistics (EMOS) strategy. The success of our strategy is measured by comparisons against observed wind speed from SYNOP stations over Italy in the years 2018 and 2019.
翻译:用于风产业的所有数字天气预测模型都需要在得到分析后,从主要天气时点00、06、12和18世界协调时开始作出预测。连续两个模型之间的6小时间隔时间要求制定战略,提供至少每小时频率的新的准确预测,以填补差距。这样做是为了满足贸易商和系统监管者不断要求经常、准确和最新信息的要求,以不断调整工作战略。这里,我们提出了一个战略,即通过新的综合模型产出统计战略,将半实时观测风速和天气模型预测结合起来。我们的战略的成功是通过2018年和2019年意大利SYNOP台站观测到的风速进行比较来衡量的。