Extreme precipitation events in the Mediterranean: Spatiotemporal characteristics and connection to large‐scale atmospheric flow patterns,International Journal of Climatology

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Extreme precipitation events in the Mediterranean: Spatiotemporal characteristics and connection to large‐scale atmospheric flow patterns
International Journal of Climatology ( IF 3.5 ) Pub Date : 2021-01-25 , DOI: 10.1002/joc.6985
Nikolaos Mastrantonas _{1,

2} , Pedro Herrera‐Lormendez ₁ , Linus Magnusson ₂ , Florian Pappenberger ₂ , Jörg Matschullat ₁

Affiliation

The Mediterranean is strongly affected by Extreme Precipitation Events (EPEs), sometimes leading to negative impacts on society, economy, and the environment. Understanding such natural hazards and their drivers is essential to mitigate related risks. Here, EPEs over the Mediterranean between 1979 and 2019 are analyzed, using ERA5 dataset from ECMWF. EPEs are determined based on the 99th percentile of the daily distribution (P99). The different EPE characteristics are assessed, based on seasonality and spatiotemporal dependencies. To better understand the connection to large-scale atmospheric flow patterns, Empirical Orthogonal Function (EOF) analysis and subsequent K-means clustering are used to quantify the importance of weather regimes to EPE frequency. The analysis is performed for three different variables, depicting atmospheric variability in the lower and middle troposphere: Sea level pressure (SLP), temperature at 850 hPa (T850), and geopotential height at 500 hPa (Z500). Results show a clear spatial division in EPEs occurrence, with winter (autumn) being the season of highest EPEs frequency for the eastern (western) Mediterranean. There is a high degree of temporal dependencies with 20% of the EPEs (median value of all studied grid-cells), occurring up to 1 week after a preceding P99 event at the same location. Local orography is a key modulator of the spatiotemporal connections and substantially enhances the probability of co-occurrence of EPEs even for distant locations. The clustering clearly demonstrates the prevalence of distinct synoptic-scale atmospheric conditions during the occurrence of EPEs for different locations within the region. Results indicate that clustering based on a combination of SLP and Z500 can increase the conditional probability of EPEs by more than three (3) times (median value for all grid cells) from the nominal probability of 1% for the P99 EPEs.

中文翻译：

地中海极端降水事件：时空特征及其与大尺度大气流动模式的联系

地中海受到极端降水事件 (EPE) 的强烈影响，有时会对社会、经济和环境产生负面影响。了解此类自然灾害及其驱动因素对于减轻相关风险至关重要。在这里，使用来自 ECMWF 的 ERA5 数据集分析了 1979 年至 2019 年间地中海上空的 EPE。EPE 根据每日分布的第 99 个百分位 (P99) 确定。根据季节性和时空依赖性，评估不同的 EPE 特性。为了更好地理解与大规模大气流动模式的联系，经验正交函数 (EOF) 分析和随后的 K 均值聚类用于量化天气状况对 EPE 频率的重要性。对三个不同的变量进行分析，描绘对流层中低层大气变化：海平面压力 (SLP)、850 hPa (T850) 的温度和 500 hPa (Z500) 的位势高度。结果显示 EPEs 发生的空间划分明显，冬季（秋季）是东（西）地中海 EPEs 频率最高的季节。有 20% 的 EPE（所有研究网格单元的中值）存在高度的时间依赖性，发生在同一位置的先前 P99 事件后长达 1 周。局部地形是时空连接的关键调节器，即使对于遥远的位置，也大大提高了 EPE 共现的可能性。聚类清楚地表明，在该地区不同位置的 EPE 发生期间，不同天气尺度大气条件的普遍性。

更新日期：2021-01-25

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