Investigation of the Historical Trends and Variability of Rainfall Patterns during the March–May Season in Rwanda

Atmosphere Pub Date : 2024-05-17 DOI:10.3390/atmos15050609
Constance Uwizewe, Jianping Li, Théogène Habumugisha, Ahmad Abdullahi Bello
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Abstract

This study explores the spatiotemporal variability and determinants of rainfall patterns during the March to May (MAM) season in Rwanda, incorporating an analysis of teleconnections with oceanic–atmospheric indices over the period 1983–2021. Utilizing the Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) dataset, the study employs a set of statistical tools including standardized anomalies, empirical orthogonal functions (EOF), Pearson correlation, the Mann–Kendall (MK) trend test, and Sen’s slope estimator to dissect the intricacies of rainfall variability, trends, and their association with large-scale climatic drivers. The findings reveal a distinct southwest to northwest rainfall gradient across Rwanda, with the MK test signaling a decline in annual precipitation, particularly in the southwest. The analysis for the MAM season reveals a general downtrend in rainfall, attributed in part to teleconnections with the Indian Ocean Sea surface temperatures (SSTs). Notably, the leading EOF mode for MAM rainfall demonstrates a unimodal pattern, explaining a significant 51.19% of total variance, and underscoring the pivotal role of atmospheric dynamics and moisture conveyance in shaping seasonal rainfall. The spatial correlation analysis suggests a modest linkage between MAM rainfall and the Indian Ocean Dipole, indicating that negative (positive) phases are likely to result in anomalously wet (dry) conditions in Rwanda. This comprehensive assessment highlights the intricate interplay between local rainfall patterns and global climatic phenomena, offering valuable insights into the meteorological underpinnings of rainfall variability during Rwanda’s critical MAM season.
卢旺达 3-5 月份降雨模式的历史趋势和变异性调查
本研究探讨了卢旺达 3 月至 5 月(MAM)季节降雨模式的时空变异性和决定因素,并结合了 1983-2021 年期间与海洋-大气指数的远程联系分析。该研究利用气候灾害小组红外降水站(CHIRPS)数据集,采用了一套统计工具,包括标准化异常、经验正交函数(EOF)、皮尔逊相关性、曼-肯德尔(MK)趋势检验和森斜率估计器,以剖析降雨量变化的复杂性、趋势及其与大尺度气候驱动因素的关联。研究结果表明,整个卢旺达的降雨量呈明显的西南至西北梯度,MK 检验表明年降水量下降,尤其是在西南部。对 MAM 季节的分析表明,降雨量呈总体下降趋势,部分原因在于与印度洋海面温度(SST)的遥感联系。值得注意的是,MAM 降雨量的主要 EOF 模式显示出一种单模式模式,解释了 51.19% 的显著总变异,并强调了大气动力学和水汽输送在形成季节性降雨中的关键作用。空间相关性分析表明,MAM 降水与印度洋偶极子之间存在一定联系,表明负(正)相位可能导致卢旺达出现异常的湿(干)条件。这项综合评估突出了当地降雨模式与全球气候现象之间错综复杂的相互作用,为卢旺达关键的 MAM 季节降雨量变化的气象基础提供了宝贵的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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