Author(s): Van-Thanh-Van Nguyen
Linked Author(s): Van-Thanh-Van Nguyen
Keywords: Extreme rainfall processes; Downscaling methods; Urban water infrastructure design; Climate change impacts; Climate models;
Abstract: Global and regional climate models have been extensively used in many climate change impact studies. However, due to the current limitations on detailed physical modelling and computational capability, outputs from these models are commonly provided at coarse spatial and temporal scales. Consequently, these outputs are not suitable for impact assessment studies at short time scales (e.g., sub-daily durations) for a given local site or for different locations over a given urban area. Hence, the main challenge is how to establish the linkages between the large-scale climate variability and the local observed characteristics of short-duration extreme rainfalls over an urban watershed scale. If this linkage could be established, then the projected change of climate conditions available at global or regional scales could be used to predict the resulting change of the local precipitations and the resulting urban runoff characteristics. Therefore, the overall objective of the present paper is to provide an overview of some recent progress in the modeling of extreme rainfall processes in a changing climate over a wide range of spatial and temporal scales. In particular, the main focus of this paper is on recently developed statistical downscaling (SD) methods for linking large-scale climate predictors to the observed daily and sub-daily rainfall extremes at a single site as well as at many sites concurrently. Examples of various applications using data from different climatic conditions in Canada will be presented to illustrate the feasibility and accuracy of the proposed SD methods.