A New Look at Storm Separation Technique in Estimation of Probable Maximum Precipitation in Mountainous Areas

Abstract

Storm separation is a key step when carrying out storm transposition analysis for Probable Maximum Precipitation (PMP) estimation in mountainous areas. The World Meteorological Organization (WMO) has recommended the step-duration-orographic-intensification-factor (SDOIF) method since 2009 as an effective storm separation technique to identify the amounts of precipitation caused by topography from those caused by atmospheric dynamics. The orographic intensification factors (OIFs) are usually developed based on annual maximum rainfall series under such assumption that the mechanism of annual maximum rainfalls is close to that of the PMP-level rainfall. In this paper, an alternative storm separation technique using rainfall quantiles, instead of annual maximum rainfalls, with rare return periods estimated via Regional L-moments Analysis (RLMA) to calculate the OIFs is proposed. Based on Taiwan’s historical 4- and 24-h precipitation data, comparisons of the OIFs obtained from annual maximum rainfalls with that from extreme rainfall quantiles at different return periods, as well as the PMP estimates of Hong Kong from transposing the different corresponding separated nonorographic rainfalls, were conducted. The results show that the OIFs obtained from rainfall quantiles with certain rare probabilities are more stable and reasonable in terms of stability and spatial distribution pattern.

Variation and attribution of probable maximum precipitation of China using high-resolution dataset in a changing climate

“…However, a consistent spatial variability and distribution is reported between Yang et al (2018) and our study (Figure 3a), where PMP generally increases from upper to lower reach. We also find overestimations of HRLT PMP (~350 mm/d) in the Hong Kong Island of South China, which is apparently lower than results based on site data (e.g., 1753 mm/d in Lan et al, 2017 andLiao et al, 2020). Such underestimations, on the one hand, are the consequence of different calculation algorithms, data sources, and uncertainties.…”

Estimating Typhoon-Induced Maximum Flood for Spillway Safety Assessment—Case Studies in Taiwan

“…They concluded that the physical approach could provide the most reliable estimates for PMP. Liao et al [13] developed a new storm separation technique using rainfall quantiles with rare return periods estimated via regional L-moments analysis to calculate the orographic intensification factors for PMP estimation. Considering typhoon is the primary reason for significant flooding in Taiwan, Wang et al [14] developed a typhoon rainstorm model for PMP estimation.…”