Updating probable maximum precipitation for Hong Kong under intensifying extreme precipitation events

Abstract

Probable maximum precipitation (PMP) is defined as the greatest depth of precipitation that is physically possible over a particular location after a storm. Changes in the frequency and intensity of precipitation extremes associated with climate change may alter established PMP values, calling for updated approaches for estimating PMP to inform water resources management. In this study, we established a framework to update PMP for Hong Kong, a major coastal metropolis in south China where precipitation extremes are intensifying in a changing climate. The methods explored are adaptations of a traditional statistical method, a local storm moisture maximization method, and a storm transposition method. As inputs to the associated models, (1) data from annual maximum rainfall series at various durations (4-, 6-, 12-, 24-h) from 1884 to 2015 in Hong Kong and its surrounding regions, Taiwan; (2) dewpoint data at an hourly resolution spanning from 1984 to 2015 in Hong Kong; and (3) hourly rainfall and dewpoint data observed during three major typhoons in Taiwan were incorporated. Although our data were available until 2015, it is worth noting that no more recent extreme precipitation events have surpassed the values recorded during the study period. Finally, we present a new dataset of the updated point- and area-scale PMP values for Hong Kong for multiple durations (4-, 6-, 12-, 24-h). These updated values were assessed and verified to be reasonable through comparisons with regional storm records, PMP estimates from adjacent areas, and historical PMP values for Hong Kong. The updated PMP values for Hong Kong can serve as a reference for the design of hydraulic structures and preparation for extreme precipitation events. Further, the proposed framework for updating PMP values can be transferred to other coastal metropolises for flood design.