Abstract
A model for estimating mean monthly total time occurrence for 1-min precipitation rates from monthly climatological variables has been developed. The model has two components: an estimation algorithm for the mean monthly percentage of time in which precipitation occurs and a set of algorithms to derive the mean cumulative distribution function of precipitation rates for a calendar month. Both components were developed using stepwise linear regression analysis applied to a database containing 10 years of 1-min precipitation data from 34 sites throughout the 48 contiguous states of the United States. The required climatological variables are the mean monthly temperature, the mean monthly temperature range, the mean monthly precipitation, and the mean number of days per month with precipitation (based on three commonly used threshold values to define a day with precipitation).
