Fingerprinting Heatwaves and Cold Spells and Assessing Their Response to Climate Change Using Large Deviation Theory,Physical Review Letters

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Fingerprinting Heatwaves and Cold Spells and Assessing Their Response to Climate Change Using Large Deviation Theory
Physical Review Letters ( IF 8.1 ) Pub Date : 2021-07-27 , DOI: 10.1103/physrevlett.127.058701
Vera Melinda Galfi ₁ , Valerio Lucarini ₂

Affiliation

Extreme events provide relevant insights into the dynamics of climate and their understanding is key for mitigating the impact of climate variability and climate change. By applying large deviation theory to a state-of-the-art Earth system model, we define the climatology of persistent heatwaves and cold spells in key target geographical regions by estimating the rate functions for the surface temperature, and we assess the impact of increasing

{CO}_{2}

concentration on such persistent anomalies. Hence, we can better quantify the increasing hazard due to heatwaves in a warmer climate. We show that two 2010 high impact events—summer Russian heatwave and winter Dzud in Mongolia—are associated with atmospheric patterns that are exceptional compared to the typical ones but typical compared to the climatology of extremes. Their dynamics is encoded in the natural variability of the climate. Finally, we propose and test an approximate formula for the return times of large and persistent temperature fluctuations from easily accessible statistical properties.

中文翻译：

对热浪和寒潮进行指纹识别并使用大偏差理论评估它们对气候变化的响应

极端事件提供了对气候动态的相关见解，对它们的理解是减轻气候变率和气候变化影响的关键。通过将大偏差理论应用于最先进的地球系统模型，我们通过估计地表温度的速率函数来定义关键目标地理区域持续热浪和寒潮的气候学，并评估增加的影响

{二氧化碳}_{2}

专注于这种持续的异常现象。因此，我们可以更好地量化在温暖气候下因热浪而增加的危害。我们表明，2010 年的两个高影响事件——俄罗斯夏季热浪和蒙古冬季 Dzud——与大气模式有关，这些模式与典型事件相比是异常的，但与极端气候学相比是典型的。它们的动态被编码在气候的自然变化中。最后，我们从易于获取的统计属性中提出并测试了一个近似公式，用于计算大而持久的温度波动的返回时间。

更新日期：2021-07-27

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