Quantifying precipitation extremes and their relationships with large‐scale climate oscillations in a tropical country, Singapore: 1980–2018

Extreme precipitation indices (EPIs) were defined to quantify the precipitation extremes in Singapore, a typical tropical country situated near the equator. The paper investigated the spatial and temporal variability of precipitation extremes based on seventeen EPIs using non‐parametric Mann‐Kendall...

Full description

Saved in:
Bibliographic Details
Published in:Singapore journal of tropical geography 2020-09, Vol.41 (3), p.384-412
Main Authors: Jiang, Rengui, Cao, Ruijuan, Lu, Xi Xi, Xie, Jiancang, Zhao, Yong, Li, Fawen
Format: Article
Language:English
Subjects:
Coherence
Correlation analysis
El Nino
Equator
Extremes
large‐scale global climate oscillations
linear and nonlinear relationships
Monsoons
Oscillation
Precipitation
Precipitation extremes
Singapore
Southern Oscillation
spatiotemporal variability
Trends
Wind
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Extreme precipitation indices (EPIs) were defined to quantify the precipitation extremes in Singapore, a typical tropical country situated near the equator. The paper investigated the spatial and temporal variability of precipitation extremes based on seventeen EPIs using non‐parametric Mann‐Kendall test and Sen’s slope, and further explored the linear and nonlinear relationships between precipitation extremes and four large‐scale global climate oscillations using correlation and wavelet analysis, during the period of 1980–2018 in Singapore. The results indicated that the trends of precipitation extremes varied for different EPIs, regions and stations. Increasing trends dominated thirteen out of seventeen EPIs. The trends of EPIs were scattered and irregularly distributed. The cross‐correlation analysis between different EPIs demonstrated that annual total precipitation on wet days (PRCPTOT) was strongly correlated with other EPIs. The result of composite analysis indicated that El Niño Southern Oscillation (ENSO) exerted stronger impacts on southwest monsoon season (SMS) precipitation than PRCPTOT and northeast monsoon season (NMS) precipitation. The SMS precipitation composite suggested that ENSO created more influence on dry spells than wet spells. The linear and nonlinear relationships revealed that all climate oscillations were negatively correlated with precipitation. The wavelet coherence and phase differences were consistent with the results of correlation analysis, indicating possible prediction of precipitation extremes using climate oscillations as potential predictors.
ISSN:0129-7619
1467-9493
DOI:10.1111/sjtg.12329