Regional Characteristics of Long-Term Variability of Summer Precipitation in the Poyang Lake Basin and Possible Links with Large-Scale Circulations

Hua Zhu,Jiahu Jiang,Handan He,Ligang Xu,Yanxue Xu,Hongxiang Fan,Mingliang Jiang

doi:10.3390/atmos11101033

Abstract

Understanding the spatiotemporal regime of summer precipitation at local scales plays a key role in regional prevention and mitigation of floods disasters and water resources management. Previous works focused on spatiotemporal characteristics of a region as a whole but left the influence of associated physical factors on sub-regions unexplored. Based on the precipitation data of 77 meteorological stations in the Poyang Lake basin (PYLB) from 1959 to 2013, we have investigated regional characteristics of summer precipitation in the PYLB by integrating the rotated empirical orthogonal function (REOF) analysis with hierarchical clustering algorithm (HCA). Then the long-term variability of summer precipitation in sub-regions of the PYLB and possible links with large-scale circulations was investigated using multiple trend analyses, wavelet analysis and correlation analysis. The results indicate that summer precipitation variations in the PYLB were of very striking regional characteristics. The PYLB was divided into three independent sub-regions based on two leading REOF modes and silhouette coefficient (SC). These sub-regions were located in northern PYLB (sub-region I), central PYLB (sub-region II), and southern PYLB (sub-region III). The summer precipitation in different sub-regions exhibited distinct variation trends and periodicities, which was associated with different factors. All sub-regions show no trends over the whole period 1959–2013, rather they show trends in different periods. Trends per decade in annual summer precipitation in sub-region I and sub-region II were consistent for all periods with different start and end years. The oscillations periods with 2–3 years were found in summer precipitation of all the three sub-regions. Summer precipitation in sub-region I was significantly positively correlated with the previous Indian Ocean Dipole (IOD) event, but negatively correlated with East Asian Summer Monsoon (EASM). While summer precipitation in sub-region II and sub-region III showed weak teleconnections with climate indices. All of the results of this study are conducive to further understand both the regional climate variations in the PYLB and response to circulation patterns variations.

Highlights

The Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report indicated that global temperature was likely to rise by 1.5 ◦ C in advance, which would produce violent challengesAtmosphere 2020, 11, 1033; doi:10.3390/atmos11101033 www.mdpi.com/journal/atmosphereAtmosphere 2020, 11, 1033 in the climate of the Earth [1]
The interannual variability of mean summer rainfall in northern China was studied and the regional characteristics were revealed by rotated empirical orthogonal function (REOF) [9]
Empirical orthogonal function (EOF) decomposition was performed on the normalized summer precipitation during

Summary

Introduction

The Intergovernmental Panel on Climate Change (IPCC) Fifth Assessment Report indicated that global temperature was likely to rise by 1.5 ◦ C in advance, which would produce violent challengesAtmosphere 2020, 11, 1033; doi:10.3390/atmos11101033 www.mdpi.com/journal/atmosphereAtmosphere 2020, 11, 1033 in the climate of the Earth [1]. Studies on the basis of observational datasets at the global scale have suggested that extreme precipitation events have increased remarkably over many mid–latitude regions in the Northern Hemisphere, bringing about tremendous impacts of floods hazards [7]. The interannual variability of mean summer rainfall in northern China was studied and the regional characteristics were revealed by rotated empirical orthogonal function (REOF) [9]. Empirical orthogonal function (EOF)/REOF and Mann–Kendall testing method were used to study spatiotemporal changes of spring precipitation of South China and their relations to atmospheric circulations based on precipitation data and National Centers for Environmental Prediction (NCEP)/National Center for Atmospheric Research (NCAR) reanalysis [12]

Objectives

Methods

Results

Discussion

Conclusion