Two-Component Extreme Value Distributions for Convective and Stratiform Precipitation

Abstract:

Characteristics of precipitation extremes are important in many practical applications, including hydrological modelling, design of hydraulic structures, urban planning, etc. Numerous studies have examined the distributions of precipitation extremes in observed data and climate model simulations, using methods of local or regional frequency analysis of different complexity. Rather surprisingly, little attention has been given to the possibility of modelling probabilities of precipitation extremes using a two-component generalized extreme value (TCEV) distribution for precipitation extremes of predominantly convective and stratiform origin. The probable reason is the lack of long-term series of precipitation data disaggregated according to their origin into convective or stratiform.

We apply a recently proposed algorithm for disaggregating station precipitation data (Rulfová and Kyselý 2013), and analyze disaggregated 6-hour precipitation amounts with respect to their characteristics at 11 stations in the Czech Republic over 1982-2010. The TCEV distribution is used for estimating high quantiles, and the results are compared with fitting a single generalized extreme value (GEV) distribution. Regional frequency modelling, which takes into account all data from the 11 stations to describe the extreme value distribution at any site is considered to reduce random and climatologically irrelevant variations in the estimates of the model parameters and high quantiles. The model developed in this study allows the location parameter to vary over the region, while the dispersion coefficient (the ratio of the scale and location parameters) and the shape parameter are assumed to be constant over the region. The adequacy of this regional model is tested thoroughly. The use of nonparametric and parametric bootstrap methods to construct confidence intervals for high quantiles is discussed.

Reference:

Rulfová, Z., Kyselý, J., 2013. Disaggregating convective and stratiform precipitation from station weather data. Atmospheric Research 134, 100-115.