The probability distribution of intense daily precipitation. Issue 5 (13th March 2015)

• Record Type: Journal Article
• Authors: Cavanaugh, Nicholas R.; Gershunov, Alexander; Panorska, Anna K.; Kozubowski, Tomasz J.
• Is Part Of: Geophysical research letters. Volume 42:Issue 5(2015:Mar.)
• Page Start: 1560
• Page End: 1567
• Publication Date: 2015-03-13
• Subjects: extreme -- Pareto -- probability -- precipitation -- weather station; Geophysics -- Periodicals; Planets -- Periodicals; Lunar geology -- Periodicals; 550
• DOI: 10.1002/2015GL063238
• Languages: English
• ISSNs: 0094-8276

Abstract

Abstract: The probability tail structure of over 22, 000 weather stations globally is examined in order to identify the physically and mathematically consistent distribution type for modeling the probability of intense daily precipitation and extremes. Results indicate that when aggregating data annually, most locations are to be considered heavy tailed with statistical significance. When aggregating data by season, it becomes evident that the thickness of the probability tail is related to the variability in precipitation causing events and thus that the fundamental cause of precipitation volatility is weather diversity. These results have both theoretical and practical implications for the modeling of high‐frequency climate variability worldwide. Key Points: Daily precipitation rates at weather stations are power law distributed Storm type diversity contributes to precipitation volatility