利用集合天气预报确定中纬度风暴的事件归因

Shirin Ermis, Nicholas J Leach, F. Lott, S. Sparrow, Antje Weisheimer
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摘要

中纬度风暴每年都会造成广泛的破坏和保险损失,因此研究风暴如何随气候变化而变化势在必行。然而,气候变化对中纬度风暴的影响很难评估,因为与天气噪声相比,风速等变量的气候变化信号很小,而且需要高分辨率来表示风暴的动态过程。2022 年 2 月 18 日,中纬度气旋 "尤妮斯 "袭击了英国南部。在此,我们利用 ECMWF 集合预测系统评估了人为气候变化对尤尼斯的影响。该系统明显能够预测风暴,从而大大增强了我们对其模拟关键物理基本过程及其如何应对气候变化的能力的信心。利用修改后的温室气体浓度边界条件和改变后的三维海洋温度初始条件,除了预测当前气候外,我们还创建了两种 "尤妮斯 "风暴的反事实情景。我们比较了工业化前气候、当前气候和未来气候下风暴的强度和严重程度。我们的结果有力地表明,随着气候变化,尤尼斯风暴变得更加剧烈,而类似的风暴将随着人为因素的进一步影响而继续加强。这些结果在 8 天、4 天和 2 天的预报准备时间内都是一致的,增强了我们对这些结果的信心。对风暴合成物的分析表明,这一过程是由风暴暖传送带湿度增加导致涡度增加引起的。这与之前对极端风暴的研究结果一致。我们的方法是将不同提前期的预报结合起来,对单个事件进行事件归因,从而将事件特异性和对动态变化的关注与对强风风险变化的评估结合起来。还需要进一步开展工作,开发调整大气初始条件的方法,以便在使用天气预报的归因研究中使用,但我们表明,这种方法对于可靠和快速的归因系统是可行的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Event attribution of a midlatitude windstorm using ensemble weather forecasts
The widespread destruction and insurance losses incurred by midlatitude storms every year makes it an imperative to study how storms change with climate change. The impact of climate change on midlatitude windstorms, however, is hard to evaluate due to the small climate change signal in variables such as windspeed compared to the noise of weather, as well as the high resolutions required to represent the dynamic processes in the storms. The midlatitude cyclone Eunice hit the South of the UK on February 18, 2022. Here, we assess how Eunice was impacted by anthropogenic climate change using the ECMWF ensemble prediction system. This system was demonstrably able to predict the storm, thus significantly increasing our confidence in its ability to model the key physical underlying processes and how they repsond to climate change. Using modified boundary conditions for the greenhouse gas concentrations and changed initial conditions for the 3D ocean temperatures, we create two counterfactual scenarios of storm Eunice in addition to the forecast for the current climate. We compare the intensity and severity of the storm between the pre-industrial, current, and future climates. Our results robustly indicate that Eunice has become more intense with climate change and similar storms will continue to intensify with further anthropogenic forcing. These results are consistent across forecast lead times of eight, four and two days, increasing our confidence in them. Analysis of storm composites shows that this process is caused by increased vorticity production through increased humidity in the warm conveyor belt of the storm. This is consistent with previous studies on extreme windstorms. Our approach of combining forecasts at different lead times for event attribution of a single event enables combining event specificity and a focus on dynamic changes with the assessment of changes in risks from strong winds. Further work is needed to develop methods to adjust the initial conditions of the atmosphere for the use in attribution studies using weather forecasts but we show that this approach is viable for reliable and fast attribution systems.
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