2023年7月1日的气候预报一些地区计算如下,根据该地区的气象记录,日期:- - - - - -日期的预测高平均高的那个地区的气象监测站,可能一些权重加权方案。——这个日期的预测低平均低的那个地区的气象监测站,又可能是一些权重加权方案。-沉淀的机会是产品的比例过去的7月第一个记录,任何在该地区气象站测量大量的降水多个气象站的百分比,并观察沉淀在这些天。问题就变成了如何熟练的预测是基于当前和最近的气候预报气象数据相比?如果它是一个抛硬币的两个将接近观察,不妨使用气候预报。这枚硬币扔边界目前约为一百一十天。抛硬币边界使用7天。在那之前,四、五天,在此之前,只有两或三天,就一天。在此之前,这是天气谚语,如“晚上天红,水手“喜悦”,这本身就是一个抛硬币。更定性的方法是一种技巧得分。 For example, suppose the meteorological forecast for the high temperature for some day in the future is $H_f$ (f for forecast) while the climatological forecast is $H_r$ (r for reference). Wait until that day passes and note the actual high temperature $H_p$. The skill score for the meteorological forecast is $$SS_H = \frac{H_f - H_r}{H_p - H_r}$$ There are multiple schemes by which skill scores for multiple scores, multiple metrics, and multiple regions are combined. Weather forecasts are a bit more skillful at predicting high and low temperatures than they are at predicting chance of precipitation. I'm not sure what combination scheme is used in determining that the ten day forecast remains a coin toss compared to the climatological forecast. References: [Murphy, Allan H., and Edward S. Epstein. "Skill scores and correlation coefficients in model verification." Monthly weather review 117.3 (1989): 572-582.](https://journals.ametsoc.org/downloadpdf/journals/mwre/117/3/1520-0493_1989_117_0572_ssacci_2_0_co_2.pdf) [Wheatcroft, Edward. "Interpreting the skill score form of forecast performance metrics." International Journal of Forecasting 35.2 (2019): 573-579.](https://www.lse.ac.uk/CATS/Assets/PDFs/Publications/Papers/2019/Interpreting-the-skill-score-form-of-forecast-performance-metrics.pdf)