A Study of Precipitation Patterns through Stochastic Ordering

Abstract

The study of spatial and temporal changes in precipitation patterns is important to agriculture and natural ecosystems. These changes can be described by some climate change indices. Because these indices often have skewed probability distributions, some common statistical procedures become either inappropriate or less powerful when they are applied to the indices. A nonparametric approach based on stochastic ordering is proposed, which does not make any assumption on the shape of the distribution. This approach is applied to the average length of the period between two adjacent precipitation days, which is called the average number of consecutive dry days (ACDD). This approach is shown to be able to reveal some patterns in precipitation that other approaches do not. Using daily precipitations at 756 stations in China from 1960 to 2015, this work compares the ACDDs in three periods, 1960–1965, 1985–1990, and 2010–2015 for each province in China. The results show that ACDD increases stochastically from the period 1960–1965 to either the period 1985–1990 or the period 2010–2015, or from the period 1985–1990 to the period 2010–2015 in all but three provinces in China.

A Study for Consecutive Precipitation Pattern Based on Stochastic Ordering

“…The resulting clusters is shown on Figure 6, which is plotted in a dendogram. We note that the resulting clusters in this current article is different from the clusters in the article of Nan Ni and Hao Zhang [24], especially in cluster 3 and cluster 4. In our result, these five provinces，Fujian, Guangdong, Guangxi, Hainan, Yunnan are classified into cluster 4.…”

“…Stochastic ordering is a powerful statistical procedure and would be helpful that could detect changes, which has a higher power than the existing test procedure. The idea of stochastic ordering is first proposed by Moshe Shaked and George Shanthikumar [22], and this statistical method has been used in survival analysis [23] and operations research [24]. From a statistical point of view, if the cumulative distribution function of a random variable is less than or equal to that of another variable, then the random variable is called as stochastically larger than another random variable.…”

“…We are so lucky that we have resource for reference. Nan Ni and Hao Zhang made a research on precipitation pattern through Stochastic Ordering, where the summer consecutive dry days in three periods of time, 1960-1965, 1985-1990 and 2010-2015 are compared [24]. This is the first time that this research method has been applied to the study of extreme climate events.…”

“…The statistical test also confirms what be shown on Figure 4 and Figure 5. [24], we choose the same three periods of time, 1960-1965, 1985-1990, and 2010-2015. The average summer consecutive precipitations of each province in China are compared in the three time periods by applying the EI Barmi-McKeague test.…”

Variation in Seasonal Precipitation over Gaza (Palestine) and Its Sensitivity to Teleconnection Patterns

“…No autocorrelation was found in the SP trend at any station. These methods, linear least square, prewhitening, and Mann Kendall, are widely used to analyze rainfall data within time series [6,10,[42][43][44][45][46].…”