Abstract

Nine precipitation regimes over South China are obtained by applying the Self-Organizing Map (SOM) technique to the sub-daily precipitation during the pre-monsoon season (April to June) of 1979–2015. These nine regimes are distinct from each other in terms of precipitation amount and spatial pattern. The relationships between precipitation and different atmospheric dynamic and thermodynamic factors (large-scale divergence, water vapor flux, low-level jet, precipitable water, convective available potential energy (CAPE), and K index) are explored under the nine regimes. The upper-level divergence performs best in indicating the geographic positions of precipitation centers, which are also modulated by the orientations of low-level jets. The estimation of water vapor transport reveals that there are two major moisture sources for the precipitation during the pre-monsoon season, i.e., the Bay of Bengal (for all the nine regimes) and the South China Sea and West Pacific Ocean (for five regimes). Furthermore, the occurrence probability of more precipitation increases with the water vapor transported from the South China Sea and West Pacific Ocean. Compared to CAPE, K index performs better in indicating the precipitation centers and has a tighter relationship with area-average precipitation. The precipitable water exhibits complicated relationships with spatial patterns and amounts of precipitation, indicating that it may be not a good indicator for precipitation during pre-monsoon season over South China. Estimation of the persistence and transformation probabilities for precipitation regimes reveals that the persistence probabilities basically decrease with the precipitation amounts, and the transformations between different precipitation regimes are inclined to be associated with the southward shifts of precipitation centers.

Highlights

  • South China, a region with the most abundant precipitation over East Asia, has a long rainy season lasting from April to September

  • Our study focuses on the relationship between different precipitation regimes and associated meteorological factors, the persistence and transformations of the precipitation regimes, and analyzing the heavy precipitation events during AMJ over South China from the perspective of precipitation regimes

  • We used six meteorological factors to analyze the characteristics associated with different precipitation regimes over South China during AMJ 1979–2015: large-scale divergence, water vapor flux for the lower troposphere, low-level jet, precipitable water, CAPE, and K index

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Summary

Introduction

South China, a region with the most abundant precipitation over East Asia, has a long rainy season lasting from April to September. Based on composite analysis for the whole rainy season (AMJ), Ding and Wang [1] analyzed the climatological characteristics of the low-level circulation (wind fields on 850 hPa) and water vapor transport, and quantitatively estimated the moisture budgets for the precipitation over South China. This study will examine the characteristics of precipitation with different amounts and spatial patterns during AMJ over South China, and explores the relationships between precipitation and multiple atmospheric dynamic and thermodynamic factors. Our study focuses on the relationship between different precipitation regimes and associated meteorological factors, the persistence and transformations of the precipitation regimes, and analyzing the heavy precipitation events during AMJ over South China from the perspective of precipitation regimes.

Data and Methods
Self-Organizing Map
Dynamic and Thermodynamic Factors
Validation of the ERA-Interim Precipitation Data
The Optimal Number of Regimes
Precipitation Regimes over South China
Dynamic Factors Associated with Different Precipitation Regimes
Water Vapor Flux
Low-Level Jet
Precipitable Water
Convective Available Potential Energy
K Index
A Further Comparison between CAPE and K Index
Persistence and Transformations of the Precipitation Regimes
Heavy Precipitation Events
Conclusions

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