Estimating the Probable Maximum Precipitation by Physical Methods Using Satellite and Radiolocation Observation Data: Case Study of the Middle Urals

Abstract

The study considers the methods for evaluating the maximal possible daily storm rainfall (MPR) in the Middle Ural based on a combination of ground, aerological, satellite, and radiolocation data. The methods under consideration represent an alternative to statistical estimation approaches. MPR is evaluated using the total moisture content of cloud systems, described in terms of their stationarity or dynamics over time. The considered methods include evaluating moisture content based on the characteristics of vertical temperature distribution in the troposphere, convection rate, and the height of the upper cloud boundary. The estimates of the probable maximum precipitation, made for the conditions of stable or cloud-dependent moisture content, are comparable with the maximums evaluated by Hershfield statistical method. The probable maximums determined by physical methods are close to the values with exceedance probability of 0.01–0.001%, evaluated with the use of lognormal distribution. The method for evaluating the probable maximum precipitation can be used in engineering practice.