Characterizing extreme rainfalls and constructing confidence intervals for IDF curves using Scaling‐GEV distribution model

Abstract

This article compares the performances of three fitting methods (SLmom, S1NCM, and S3NCM) to account for temporal characteristics of Annual Maximum Precipitations (AMPs) on daily and sub-daily time scales using scaling General Extreme Value (GEV) distribution at a local site. Based on simple scaling properties of AMPs, the temporal downscaling model (called Scaling-GEV) with parameter estimation methods are used to estimate sub-daily AMPs from observed daily data. The feasibility and accuracy of the suggested method were assessed using rainfall data available from Dorval in Quebec (Canada) and Seoul (South Korea) for the period 1961-1990. Presence of simple scaling properties of AMPs for two stations has shown that it is feasible to use the temporal downscaling method for describing the linkage between AMPs of different time scales. Numerical and graphical analyses revealed that the Scaling-GEV distribution by the Three-Non central moments (NCM) method (S3NCM) provides the most accurate estimates compared to observed data amongst three fitting methods. In addition, this study suggested a modified bootstrap technique to determine confidence intervals (CIs) CIs of extreme rainfall series using the simple scaling properties of extreme rainfalls and only daily AMPs. Although the CIs were constructed by only daily AMPs and the simple scaling properties, the observed sub-daily AMPs are generally within the 95% CI estimated.

An Integrated Extreme Rainfall Modeling Tool (SDExtreme) for Climate Change Impacts and Adaptation

“…In this section, we review the three steps, which are described in more detail in Yeo et al (2020) and Nguyen et al (2008).…”

“…The GEV distribution has been commonly used to describe the distribution of extreme rainfalls for different durations and to construct the IDF curves (Nguyen et al, 2008, Yeo et al, 2020. The cumulative distribution function, ( ), for the GEV distribution is given as 114…”

“…Satellite, Weather Research and Forecasting (WRF) model, and some statistical techniques are proposed to overcome the spatial scale limitation (Pizarro et al, 2018, Liew et al, 2014, Ombadi et al, 2018, Ouali and Cannon, 2018. Efforts to describe the association of extreme rainfalls at different time scales have been proposed and tested (Gupta and Waymire, 1990, Nhat et al, 2007, Vu et al, 2018, Yeo et al, 2020, however, it is unable to investigate climate change impacts on extreme rainfalls in the future time. By coupling climate change scenarios and the described temporal association, the IDF curves have been updated to account for the climate change impacts on extreme rainfalls and flooding (Nguyen et al, 2008, Vu et al, 2018, Yeo, 2014.…”

“…Outputs from these models, however, are not usually applicable for frequency analysis at a local site due to their coarse temporal resolutions. To incorporate the climate change conditions into frequency analyses, the scale invariance properties of AMPs are coupled to GCMs' outputs (Nguyen et al, 2008, Vu et al, 2018, Yeo et al, 2020.…”

“…The use of ensemble of multiple climate change models and the downscaling approaches have been suggested to represent the uncertainty. However, it also has the additional challenge to determine appropriate climate models for extreme rainfall events because the extreme values behave differently (Yeo et al, 2020). This paper introduces a software package that enables the construction of IDF curves and their CIs for the present and the future if a user has the historical annual maximum precipitation series and daily climate change scenarios' outputs.…”