Comparison of regional and at-site approaches to modelling probabilities of heavy precipitation

✍ Scribed by Jan Kyselý; Ladislav Gaál; Jan Picek

• Publisher: John Wiley and Sons
• Year: 2010
• Tongue: English
• Weight: 913 KB
• Volume: 31
• Category: Article
• ISSN: 0899-8418
• DOI: 10.1002/joc.2182

✦ Synopsis

Abstract

Several approaches to estimating distributions of precipitation extremes are compared by means of simulation experiments, and their applications into observed data in the Czech Republic are evaluated. Regional frequency models, which take into account data in fixed or flexible ‘regions’ when fitting a distribution at any site, lead to estimates with much smaller errors compared to a single‐site analysis, and efficiently reduce random and climatologically irrelevant variations in the estimates of the model parameters and high quantiles. The region‐of‐influence (ROI) methodology with a built‐in regional homogeneity test is recognized as a useful approach, with the model based on proximity of sites outperforming the Hosking–Wallis regional frequency analysis. Comparison of estimates of the return period of a heavy precipitation event on 24 June 2009, which triggered a disastrous local flash flood, illustrates that the at‐site analysis leads to unrealistic and extremely uncertain estimates that strongly depend on whether or not a single outlying observation is involved in the sample, while all regional methods yield return periods in the same order of several hundreds of years, notwithstanding whether the 2009 data are included in the sample. The ROI method may be found useful for modelling probabilities of other meteorological variables, extremes of which are strongly influenced by sampling variability, and may also represent an efficient tool for ‘smoothing’ random variations in the estimates of model parameters and high quantiles of precipitation in high‐resolution regional climate model simulations. Copyright © 2010 Royal Meteorological Society