Stability and contagion measures for spatial extreme value analyzes

Cecília Fonseca; Helena Ferreira; Luísa Pereira; Ana Paula Martins

Kybernetika (2014)

  • Volume: 50, Issue: 6, page 914-928
  • ISSN: 0023-5954

Abstract

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As part of global climate change an accelerated hydrologic cycle (including an increase in heavy precipitation) is anticipated (Trenberth [20, 21]). So, it is of great importance to be able to quantify high-impact hydrologic relationships, for example, the impact that an extreme precipitation (or temperature) in a location has on a surrounding region. Building on the Multivariate Extreme Value Theory we propose a contagion index and a stability index. The contagion index makes it possible to quantify the effect that an exceedance above a high threshold can have on a region. The stability index reflects the expected number of crossings of a high threshold in a region associated to a specific location i , given the occurrence of at least one crossing at that location. We will find some relations with well-known extremal dependence measures found in the literature, which will provide immediate estimators. For these estimators an application to the annual maxima precipitation in Portuguese regions is presented.

How to cite

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Fonseca, Cecília, et al. "Stability and contagion measures for spatial extreme value analyzes." Kybernetika 50.6 (2014): 914-928. <http://eudml.org/doc/262162>.

@article{Fonseca2014,
abstract = {As part of global climate change an accelerated hydrologic cycle (including an increase in heavy precipitation) is anticipated (Trenberth [20, 21]). So, it is of great importance to be able to quantify high-impact hydrologic relationships, for example, the impact that an extreme precipitation (or temperature) in a location has on a surrounding region. Building on the Multivariate Extreme Value Theory we propose a contagion index and a stability index. The contagion index makes it possible to quantify the effect that an exceedance above a high threshold can have on a region. The stability index reflects the expected number of crossings of a high threshold in a region associated to a specific location $i$, given the occurrence of at least one crossing at that location. We will find some relations with well-known extremal dependence measures found in the literature, which will provide immediate estimators. For these estimators an application to the annual maxima precipitation in Portuguese regions is presented.},
author = {Fonseca, Cecília, Ferreira, Helena, Pereira, Luísa, Martins, Ana Paula},
journal = {Kybernetika},
keywords = {spatial extremes; max-stable processes; extremal dependence; climate change; multivariate extreme value theory; hydrologic relationships; contagion measures; spatial extremes; max-stable processes; extremal dependence},
language = {eng},
number = {6},
pages = {914-928},
publisher = {Institute of Information Theory and Automation AS CR},
title = {Stability and contagion measures for spatial extreme value analyzes},
url = {http://eudml.org/doc/262162},
volume = {50},
year = {2014},
}

TY - JOUR
AU - Fonseca, Cecília
AU - Ferreira, Helena
AU - Pereira, Luísa
AU - Martins, Ana Paula
TI - Stability and contagion measures for spatial extreme value analyzes
JO - Kybernetika
PY - 2014
PB - Institute of Information Theory and Automation AS CR
VL - 50
IS - 6
SP - 914
EP - 928
AB - As part of global climate change an accelerated hydrologic cycle (including an increase in heavy precipitation) is anticipated (Trenberth [20, 21]). So, it is of great importance to be able to quantify high-impact hydrologic relationships, for example, the impact that an extreme precipitation (or temperature) in a location has on a surrounding region. Building on the Multivariate Extreme Value Theory we propose a contagion index and a stability index. The contagion index makes it possible to quantify the effect that an exceedance above a high threshold can have on a region. The stability index reflects the expected number of crossings of a high threshold in a region associated to a specific location $i$, given the occurrence of at least one crossing at that location. We will find some relations with well-known extremal dependence measures found in the literature, which will provide immediate estimators. For these estimators an application to the annual maxima precipitation in Portuguese regions is presented.
LA - eng
KW - spatial extremes; max-stable processes; extremal dependence; climate change; multivariate extreme value theory; hydrologic relationships; contagion measures; spatial extremes; max-stable processes; extremal dependence
UR - http://eudml.org/doc/262162
ER -

References

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