Beyond skill scores: exploring sub‐seasonal forecast value through a case‐study of French month‐ahead energy prediction,Quarterly Journal of the Royal Meteorological Society

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Beyond skill scores: exploring sub‐seasonal forecast value through a case‐study of French month‐ahead energy prediction
Quarterly Journal of the Royal Meteorological Society ( IF 3.0 ) Pub Date : 2020-07-06 , DOI: 10.1002/qj.3863
Joshua Dorrington ₁ , Isla Finney ₂ , Tim Palmer ₁ , Antje Weisheimer _{1,

3}

Affiliation

We quantify the value of sub‐seasonal forecasts for a real‐world prediction problem: the forecasting of French month‐ahead energy demand. Using surface temperature as a predictor, we construct a trading strategy and assess the financial value of using meteorological forecasts, based on actual energy demand and price data. We show that forecasts with lead times greater than two weeks can have value for this application, both on their own and in conjunction with shorter‐range forecasts, especially during boreal winter. We consider a cost/loss framework based on this example, and show that, while it captures the performance of the short‐range forecasts well, it misses the marginal value present in medium‐range forecasts. We also contrast our assessment of forecast value to that given by traditional skill scores, which we show could be misleading if used in isolation. We emphasise the importance of basing assessment of forecast skill on variables actually used by end‐users.

中文翻译：

超越技能得分：通过法国提前月能源预测的案例研究来探索亚季节的预测价值

我们对一个现实世界中的预测问题量化了次季节预测的价值：法国未来月能源需求的预测。我们使用地表温度作为预测指标，构建交易策略，并根据实际的能源需求和价格数据评估使用气象预测的财务价值。我们显示，提前期超过两周的预测对于此应用程序具有价值，无论是单独使用还是与较短范围的预测结合使用，尤其是在寒冬期间。我们考虑基于此示例的成本/损失框架，并表明，尽管它很好地捕获了短期预测的性能，但是却错过了中期预测中存在的边际价值。我们还将预测值的评估与传统技能得分的评估进行对比，如果单独使用，我们展示的结果可能会产生误导。我们强调根据最终用户实际使用的变量对预测技能进行评估的重要性。

更新日期：2020-07-06

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