COMPARATWE EVALUATION OF FREQUENCY DISTRIBUTIONS FOR LOUISIANA EXTREME RAINFALL¹

Abstract

A comparative study of five popular frequency distributions and three parameter estimation methods was conducted by using 92 Louisiana rainfall data sets. Computed results showed that the log‐Pearson type 3 (LPEAR3) distribution was the most appropriate probability distribution for the Louisiana rainfall data. Furthermore, the method of moments was found to be the best estimation method for the LPEAR3 distribution based on descriptive performance indices. A first‐order error analysis was performed on the parameters of the LPEAR3 distribution. Computed results showed that the predicted quantiles of the LPEAR3 distribution were most sensitive to the population mean and relatively insensitive to the coefficient of the skewness of the distribution.

A comparison of techniques to produce quantile estimates of heavy rainfall in arid and mountainous environments: a test case in western Texas

“…The probability distributions include Gumbel (GMBL), which was used to produce TP40; Log Pearson Type III (LGP3), found to best fit heavy rainfall series in Louisiana by Naghavi et al (1993); the Beta-P (BTAP), found to best fit heavy rainfall extremes in the north-eastern United States by Wilks & Cember (1993); the Three Parameter Log Normal(PLGN), which was a distribution investigated by Wilks (1993); and the fourparameter Wakeby (WKBY) distribution. In addition, two alternative regression methods were examined including the Huff-Angel (H-A) method used by Huff & Angel (1992) in the midwestern United States, and the Southern Regional Climate Center method (SRCC) developed by Faiers et al (1997).…”

HEAVY RAINFALL DISTRIBUTIONS BY SEASON IN LOUISIANA: SYNOPTIC INTERPRETATIONS AND QUANTILE ESTIMATES1

“…No previous studies have identified a single probability distribution which would provide the best fit for seasonal series of extreme rainfall in this region. It should be noted that Naghavi et at. (1993) found that the log-Pearson type 3 distribution best fit Louisiana extreme rainfall data; however, these results are only valid for annual series data (rather than partial duration series) and for annual storm distributions (rather than seasonal).…”

Comparison of predicted annual maximum rainfall for Calabar metropolis using statistical approach

“…Fitzgerald 8 carried out the analysis of rainfall extremes for a single station and at a regional scale using a Generalized Pareto Distribution (GPD) for the exceedances. Naghavi et al 9 compared five popular distributions and three parameter estimation methods using Louisiana rainfall data sets.…”