论文标题
地中海的极端降水事件：时空特征和与大规模大气流图案的联系
Extreme precipitation events in the Mediterranean: Spatiotemporal characteristics and connection to large-scale atmospheric flow patterns
论文作者
论文摘要
地中海受到极端降水事件（EPE）的强烈影响，有时会导致对社会，经济和环境的负面影响。了解这种自然危害及其驱动因素对于减轻相关风险至关重要。在这里，使用ECMWF的ERE5数据集分析了1979年至2019年之间地中海的EPES。 EPE是根据日常分布的第99个百分点确定的（P99）。根据季节性和时空依赖性评估不同的EPE特征。为了更好地了解与大规模大气流动模式的联系，使用经验正交函数（EOF）分析和随后的K-均值聚类来量化天气制度对EPE频率的重要性。对三个不同变量进行了分析，描述了对流层下部和中部的大气变异性：海平面压力（SLP），850 hPa的温度（T850）（T850）（T850）和500 hPa（Z500）的地理电位高度。结果表明，EPES发生的明显空间划分，冬季（秋季）是东部（西部）地中海频率最高的季节。具有高度的时间依赖性，其中20％的EPES（所有研究的网格细胞的中值）发生在同一位置的P99事件后长达1周。局部地形是时空连接的关键调节仪，即使对于遥远的位置，也可以大大提高了EPES同时存在的可能性。聚类清楚地表明，在该地区内不同位置的EPES发生期间，不同的概要大气条件的流行。结果表明，基于SLP和Z500的组合的聚类可以将EPES的条件概率提高超过三（3）次（所有网格单元的中位数），而P99 EPES的名义概率是1％。
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.
