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A global survey on the seasonal variation of the marginal distribution of daily precipitation
Publikationstyp
Journal Article
Date Issued
2016-05-12
Sprache
English
Journal
Volume
94
Start Page
131
End Page
145
Citation
Advances in Water Resources 94: 131-145 (2016)
Publisher DOI
Scopus ID
Publisher
Elsevier
To characterize the seasonal variation of the marginal distribution of daily precipitation, it is important to find which statistical characteristics of daily precipitation actually vary the most from month-to-month and which could be regarded to be invariant. Relevant to the latter issue is the question whether there is a single model capable to describe effectively the nonzero daily precipitation for every month worldwide. To study these questions we introduce and apply a novel test for seasonal variation (SV-Test) and explore the performance of two flexible distributions in a massive analysis of approximately 170,000 monthly daily precipitation records at more than 14,000 stations from all over the globe. The analysis indicates that: (a) the shape characteristics of the marginal distribution of daily precipitation, generally, vary over the months, (b) commonly used distributions such as the Exponential, Gamma, Weibull, Lognormal, and the Pareto, are incapable to describe "universally" the daily precipitation, (c) exponential-tail distributions like the Exponential, mixed Exponentials or the Gamma can severely underestimate the magnitude of extreme events and thus may be a wrong choice, and (d) the Burr type XII and the Generalized Gamma distributions are two good models, with the latter performing exceptionally well.
Subjects
Burr type XII distribution
Daily precipitation
Generalized gamma distribution
Marginal distribution
Seasonal variation
Spatial variation
DDC Class
600: Technology