Next Article in Journal
The VIF and MSE in Raise Regression
Next Article in Special Issue
On Convergence Rates of Some Limits
Previous Article in Journal
On the Solvability of Fourth-Order Two-Point Boundary Value Problems
Previous Article in Special Issue
A Generalized Equilibrium Transform with Application to Error Bounds in the Rényi Theorem with No Support Constraints

Open AccessArticle

# Probability Models and Statistical Tests for Extreme Precipitation Based on Generalized Negative Binomial Distributions

by 1,2,3,4 and 1,2,3,*
1
Moscow Center for Fundamental and Applied Mathematics, Lomonosov Moscow State University, 119991 Moscow, Russia
2
Faculty of Computational Mathematics and Cybernetics, Lomonosov Moscow State University, 119991 Moscow, Russia
3
Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences, 119333 Moscow, Russia
4
Department of Mathematics, School of Science, Hangzhou Dianzi University, Hangzhou 310018, China
*
Author to whom correspondence should be addressed.
Mathematics 2020, 8(4), 604; https://doi.org/10.3390/math8040604
Received: 4 April 2020 / Revised: 12 April 2020 / Accepted: 14 April 2020 / Published: 16 April 2020
(This article belongs to the Special Issue Stability Problems for Stochastic Models: Theory and Applications)
Mathematical models are proposed for statistical regularities of maximum daily precipitation within a wet period and total precipitation volume per wet period. The proposed models are based on the generalized negative binomial (GNB) distribution of the duration of a wet period. The GNB distribution is a mixed Poisson distribution, the mixing distribution being generalized gamma (GG). The GNB distribution demonstrates excellent fit with real data of durations of wet periods measured in days. By means of limit theorems for statistics constructed from samples with random sizes having the GNB distribution, asymptotic approximations are proposed for the distributions of maximum daily precipitation volume within a wet period and total precipitation volume for a wet period. It is shown that the exponent power parameter in the mixing GG distribution matches slow global climate trends. The bounds for the accuracy of the proposed approximations are presented. Several tests for daily precipitation, total precipitation volume and precipitation intensities to be abnormally extremal are proposed and compared to the traditional PoT-method. The results of the application of this test to real data are presented. View Full-Text
Show Figures

Figure 1

MDPI and ACS Style

Korolev, V.; Gorshenin, A. Probability Models and Statistical Tests for Extreme Precipitation Based on Generalized Negative Binomial Distributions. Mathematics 2020, 8, 604.