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

1980–2018

Dados Bibliográficos

ID20153395
AutoresRengui Jiang (0000-0002-3975-4059, State Key Laboratory of Eco‐hydraulics in Northwest Arid Region of China Xi'an University of Technology Xi’an China), Ruijuan Cao (State Key Laboratory of Eco‐hydraulics in Northwest Arid Region of China Xi'an University of Technology Xi’an China), Xixi Lu (0000-0002-2528-4631, Department of Geography National University of Singapore Singapore, autor correspondente), Jiancang Xie (0000-0002-0411-3294, State Key Laboratory of Eco‐hydraulics in Northwest Arid Region of China Xi'an University of Technology Xi’an China, autor correspondente), Yong Zhao (0000-0003-1926-9731, State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin China Institute of Water Resources and Hydropower Research Beijing China), Fawen Li (0000-0002-9342-3242, State Key Laboratory of Hydraulic Engineering Simulation and Safety Tianjin University Tianjin China)
Ano2020
Volume41
Fascículo3
Páginas384-412
Data de publicação2020-09-01
Peer ReviewedSim
Open AccessSim
TipoARTICLE
PeriódicoSingapore Journal of Tropical Geography (JOURNAL)
Identificadores do periódicoISSN: 0129-7619 • E-ISSN: 1467-9493
EditoraWiley (PUBLISHER • GB)
DOI10.1111/sjtg.12329
OpenAlexW3048571022
IdiomaEN
Citações recebidas2
Referências citadas53

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

Atmospheric sciences · Climatology · El Niño Southern Oscillation · Geography · Meteorology · Monsoon · Precipitation · Climate variability and models · Environmental Science · Geology · Hydrology and Drought Analysis · Meteorological Phenomena and Simulations