Increasing frequency and precipitation intensity of convective storms in the Peruvian Central Andes: Projections from convection‐permitting regional climate simulations

IF 3 3区 地球科学 Q2 METEOROLOGY & ATMOSPHERIC SCIENCES
Yongjie Huang, Ming Xue, Xiao‐Ming Hu, Elinor Martin, H. Novoa, Renee A. McPherson, Changhai Liu, Mengye Chen, Yang Hong, Andres Perez, Isaac Yanqui Morales, José Luis Ticona Jara, Auria Julieta Flores Luna
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Abstract

To explore the potential impacts of climate change on precipitation and mesoscale convective systems (MCSs) in the Peruvian Central Andes, a region with complex terrain, two future convection‐permitting regional climate simulations and one historical one are conducted using the Weather Research and Forecasting (WRF) model. All simulations adopt consistent model configurations and two nested domains with grid spacings of 15 and 3 km covering the entire South America and the Peruvian Central Andes, respectively. The historical run, spanning 2014–2019, is driven by ERA5 reanalysis, and the future simulations, covering the period 2070–2080, are driven by a bias‐corrected global dataset derived from the Coupled Model Intercomparison Project Phase 6 (CMIP6) ensemble under the SSP2‐4.5 and SSP5‐8.5 emission scenarios. Results show geographically dependent changes in annual precipitation, with a consistent rise in the frequency of intense hourly precipitation across all regions examined. The western Amazon Basin shows a decrease in annual precipitation, while increases exist in parts of the Peruvian west coast and the east slope of the Andes under both future scenarios. In the warming scenarios, there is an overall increase in the frequency, precipitation intensity, and size of MCSs east of the Andes, with MCS precipitation volume increasing by up to ∼22.2%. Despite consistently enhanced synoptic‐scale low‐level jets in future scenarios, changes in low‐level dynamic convergence are inhomogeneous and predominantly influence annual precipitation changes. The increased convective available potential energy (CAPE), convective inhibition (CIN), and precipitable water (PW) in a warming climate suppress weak convection, while fostering a more unstable and moisture‐rich atmosphere, facilitating more intense convection and the formation and intensification of heavy precipitation‐producing MCSs. The study highlights the value of convection‐permitting climate simulations in projecting future severe weather hazards and informing climate adaptation strategies, especially in regions characterized by complex terrain.
秘鲁中安第斯山脉对流风暴频率和降水强度的增加:对流允许区域气候模拟预测
秘鲁中安第斯山脉地形复杂,为了探索气候变化对该地区降水和中尺度对流系统(MCSs)的潜在影响,我们利用天气研究与预报(WRF)模式进行了两次未来对流允许区域气候模拟和一次历史模拟。所有模拟均采用一致的模式配置和两个嵌套域,网格间距分别为 15 千米和 3 千米,覆盖整个南美洲和秘鲁中安第斯山脉。2014-2019年的历史运行由ERA5再分析驱动,2070-2080年的未来模拟由SSP2-4.5和SSP5-8.5排放情景下的耦合模式相互比较项目第六阶段(CMIP6)集合中的偏差校正全球数据集驱动。结果表明,年降水量的变化与地理位置有关,在所有研究地区,每小时强降水的频率持续上升。亚马逊盆地西部的年降水量有所减少,而秘鲁西海岸和安第斯山脉东坡的部分地区在两种未来情景下的年降水量都有所增加。在气候变暖的情景下,安第斯山脉以东地区的多云天气频率、降水强度和降水量总体上都有所增加,多云天气降水量增加了 22.2%。尽管在未来情景中,同步尺度低空喷流持续增强,但低空动态辐合的变化是不均匀的,主要影响年降水量的变化。气候变暖时对流可用势能(CAPE)、对流抑制(CIN)和可降水量(PW)的增加会抑制弱对流,同时促进大气更加不稳定和富含水汽,有利于更强烈的对流以及产生强降水的多层大气环流的形成和加强。该研究强调了允许对流的气候模拟在预测未来恶劣天气危害和为气候适应战略提供信息方面的价值,尤其是在地形复杂的地区。
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来源期刊
CiteScore
16.80
自引率
4.50%
发文量
163
审稿时长
3-8 weeks
期刊介绍: The Quarterly Journal of the Royal Meteorological Society is a journal published by the Royal Meteorological Society. It aims to communicate and document new research in the atmospheric sciences and related fields. The journal is considered one of the leading publications in meteorology worldwide. It accepts articles, comprehensive review articles, and comments on published papers. It is published eight times a year, with additional special issues. The Quarterly Journal has a wide readership of scientists in the atmospheric and related fields. It is indexed and abstracted in various databases, including Advanced Polymers Abstracts, Agricultural Engineering Abstracts, CAB Abstracts, CABDirect, COMPENDEX, CSA Civil Engineering Abstracts, Earthquake Engineering Abstracts, Engineered Materials Abstracts, Science Citation Index, SCOPUS, Web of Science, and more.
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