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.

中文翻译：

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量化极端降水及其与热带国家大规模气候振荡的关系，新加坡：1980–2018

定义了极端降水指数（EPI）来量化新加坡（赤道附近的典型热带国家）的极端降水量。本文利用非参数Mann-Kendall检验和Sen斜率研究了基于17个EPI的极端降水的时空变化，并利用相关性和小波方法进一步探讨了极端降水与四个全球大尺度气候振荡之间的线性和非线性关系。分析，在1980年至2018年期间在新加坡进行。结果表明，不同EPI，地区和站点的极端降水趋势有所不同。增长趋势主导了17个EPI中的13个。EPI的趋势分散且不规则地分布。不同EPI之间的互相关分析表明，湿日年总降水量（PRCPTOT）与其他EPI密切相关。综合分析的结果表明，厄尔尼诺南方涛动（ENSO）对西南季风季节（SMS）降水的影响比PRTCPTOT和东北季风季节（NMS）的影响更大。SMS降水量综合表明，ENSO对干咒的影响大于对湿咒的影响。线性和非线性关系表明，所有气候振荡都与降水呈负相关。小波相干性和相位差与相关分析的结果一致，表明使用气候振荡作为潜在预测因子可以预测极端降水。