Choosing a probability distribution to represent daily precipitation depths is important for
precipitation frequency analysis, stochastic precipitation modeling and in climate trend …

Choosing a probability distribution to represent the precipitation depth at various durations
has long been a topic of interest in hydrology. Early study into the distribution of wet-day …

The probable rainfall is an excellent climatic parameter of information since it consists of the
highest/lowest expected rainfall for a particular period of the year considering a certain level …

The selection of an appropriate model depends mainly on the characteristics of available
rainfall data at the particular site. As a result, it is necessary to evaluate many available …

In this article, the Probable Maximum Precipitation (PMP) evaluation is done using a spatio-
temporal approach–Diaconu's method–for a set of data series collected in the Dobrudja …

This study presents a comprehensive analysis of the probability distribution of rainfall data in
Mizoram, a state in Northeast India, from 1986 to 2021 by 18 probability distributions. The …

The early growth stage is critical in the response of trees to climate change and variability. It
is not clear, however, what climate metrics are best to define the early-growth sensitivity in …

Statistical modeling of rainfall data is an active research area in agro-meteorology. The most
common models fitted to such datasets are exponential, gamma, log-normal, and Weibull …

Recent work has found that a one‐parameter Weibull model of wet day precipitation amount
based on the Weibull distribution provides a better fit to historical daily precipitation data for …

The probable extreme rainfall analysis can be of great importance for the development of
efficient models of risk management and mitigation. This study involves analyzing the …