This study investigates the predictability of the 2018 Northern Europe heatwave using the GloSea5 forecast model from the perspective of land-atmosphere interactions. We focus on an inverse relationship wherein soil drying leads to increased temperatures and the model's ability to simulate this hypersensitivity in the soil moisture-temperature coupling on the dry side of a breakpoint defined as the soil moisture threshold below which land feedbacks nonlinearly amplify extreme heat. When evaluating forecast model performance in predicting this heatwave, we compare deterministic forecast scores (Hit Rate (HR) and True Skill Score (TSS)) for whether model Surface Soil Moisture (SSM) falls within the hypersensitive regime. GloSea5 exhibits enhanced prediction skill for the extreme heat event when the modelled soil moisture is within the hypersensitive regime. To understand the skill of the heatwave forecast for hit and missed cases of capturing SSM below the breakpoint, we first evaluate the climatological model performance for the water- and energy-limited processes, and then perform a comparison classified by whether SSM verifies on the dry side of the wilting point. The composite analysis demonstrates that the reproducibility of the breakpoint is tied to an improvement in climatological land coupling processes, mainly for classification in the water-limited coupling regime. Therefore, the results suggest that the process-based connection between soil moisture and temperature is a potential source for improving heatwave forecasts on subseasonal to seasonal (S2S) time scales.

中文翻译：

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2018 年北欧热浪土壤湿度-温度耦合在次季节预报中的作用

本研究利用GloSea5预报模型从陆地-大气相互作用的角度研究了2018年北欧热浪的可预测性。我们关注的是一种反比关系，其中土壤干燥导致温度升高，以及该模型在断点干燥侧模拟土壤湿度-温度耦合的超敏性的能力，该断点定义为土壤湿度阈值，低于该阈值，土地反馈会非线性放大极端热量。在评估预测模型在预测这场热浪方面的性能时，我们比较确定性预测得分（命中率 (HR) 和真实技能得分 (TSS)），以确定模型表面土壤湿度 (SSM) 是否属于超敏感范围。当模拟的土壤湿度处于超敏感状态时，GloSea5 表现出增强的极端高温事件预测能力。为了了解在断点以下捕获 SSM 的命中和错过情况的热浪预报技巧，我们首先评估水和能源限制过程的气候模型性能，然后根据 SSM 是否验证干燥进行分类进行比较萎蔫点的一侧。综合分析表明，断点的再现性与气候陆地耦合过程的改进有关，主要用于限水耦合机制的分类。因此，结果表明，土壤湿度和温度之间基于过程的联系是改进次季节到季节（S2S）时间尺度的热浪预报的潜在来源。