Heavy tailed durations of regional rainfall

Harry Pavlopoulos; Jan Picek; Jana Jurečková

Applications of Mathematics (2008)

  • Volume: 53, Issue: 3, page 249-265
  • ISSN: 0862-7940

Abstract

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Durations of rain events and drought events over a given region provide important information about the water resources of the region. Of particular interest is the shape of upper tails of the probability distributions of such durations. Recent research suggests that the underlying probability distributions of such durations have heavy tails of hyperbolic type, across a wide range of spatial scales from 2 km to 120 km. These findings are based on radar measurements of spatially averaged rain rate (SARR) over a tropical oceanic region. The present work performs a nonparametric inference on the Pareto tail-index of wet and dry durations at each of those spatial scales, based on the same data, and compares it with conclusions based on the classical Hill estimator. The results are compared and discussed.

How to cite

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Pavlopoulos, Harry, Picek, Jan, and Jurečková, Jana. "Heavy tailed durations of regional rainfall." Applications of Mathematics 53.3 (2008): 249-265. <http://eudml.org/doc/37782>.

@article{Pavlopoulos2008,
abstract = {Durations of rain events and drought events over a given region provide important information about the water resources of the region. Of particular interest is the shape of upper tails of the probability distributions of such durations. Recent research suggests that the underlying probability distributions of such durations have heavy tails of hyperbolic type, across a wide range of spatial scales from 2 km to 120 km. These findings are based on radar measurements of spatially averaged rain rate (SARR) over a tropical oceanic region. The present work performs a nonparametric inference on the Pareto tail-index of wet and dry durations at each of those spatial scales, based on the same data, and compares it with conclusions based on the classical Hill estimator. The results are compared and discussed.},
author = {Pavlopoulos, Harry, Picek, Jan, Jurečková, Jana},
journal = {Applications of Mathematics},
keywords = {wet and dry durations of regional rainfall; quantile multiscaling; heavy tails; Pareto tail-index; semi-parametric statistical inference; wet and dry durations of regional rainfall; quantile multiscaling; heavy tails; Pareto tail-index; semi-parametric statistical inference},
language = {eng},
number = {3},
pages = {249-265},
publisher = {Institute of Mathematics, Academy of Sciences of the Czech Republic},
title = {Heavy tailed durations of regional rainfall},
url = {http://eudml.org/doc/37782},
volume = {53},
year = {2008},
}

TY - JOUR
AU - Pavlopoulos, Harry
AU - Picek, Jan
AU - Jurečková, Jana
TI - Heavy tailed durations of regional rainfall
JO - Applications of Mathematics
PY - 2008
PB - Institute of Mathematics, Academy of Sciences of the Czech Republic
VL - 53
IS - 3
SP - 249
EP - 265
AB - Durations of rain events and drought events over a given region provide important information about the water resources of the region. Of particular interest is the shape of upper tails of the probability distributions of such durations. Recent research suggests that the underlying probability distributions of such durations have heavy tails of hyperbolic type, across a wide range of spatial scales from 2 km to 120 km. These findings are based on radar measurements of spatially averaged rain rate (SARR) over a tropical oceanic region. The present work performs a nonparametric inference on the Pareto tail-index of wet and dry durations at each of those spatial scales, based on the same data, and compares it with conclusions based on the classical Hill estimator. The results are compared and discussed.
LA - eng
KW - wet and dry durations of regional rainfall; quantile multiscaling; heavy tails; Pareto tail-index; semi-parametric statistical inference; wet and dry durations of regional rainfall; quantile multiscaling; heavy tails; Pareto tail-index; semi-parametric statistical inference
UR - http://eudml.org/doc/37782
ER -

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