TY - JOUR
T1 - An exploratory study of spatial annual maximum of monthly precipitation in the northern region of Portugal
AU - Prata Gomes, D.
AU - Neves, M. M.
AU - Moreira, Elsa E.
N1 - info:eu-repo/grantAgreement/FCT/5876/147204/PT#
info:eu-repo/grantAgreement/FCT/3599-PPCDT/129815/PT#
info:eu-repo/grantAgreement/FCT/5876/135897/PT#
PY - 2016/8/1
Y1 - 2016/8/1
N2 - Adequately analyzing and modeling the extreme rainfall events is of great importance because of the effects that their magnitude and frequency can have on human life, agricultural productivity and economic aspects, among others. A single extreme event may affect several locations, and their spatial dependence has to be appropriately taken into account. Classical geostatistics is a well-developed field for dealing with location referenced data, but it is largely based on Gaussian processes and distributions, that are not appropriate for extremes. In this paper, an exploratory study of the annual maximum of monthly precipitation recorded in the northern area of Portugal from 1941 to 2006 at 32 locations is performed. The aim of this paper is to apply max-stable processes, a natural extension of multivariate extremes to the spatial set-up, to briefly describe the models considered and to estimate the required parameters to simulate prediction maps.
AB - Adequately analyzing and modeling the extreme rainfall events is of great importance because of the effects that their magnitude and frequency can have on human life, agricultural productivity and economic aspects, among others. A single extreme event may affect several locations, and their spatial dependence has to be appropriately taken into account. Classical geostatistics is a well-developed field for dealing with location referenced data, but it is largely based on Gaussian processes and distributions, that are not appropriate for extremes. In this paper, an exploratory study of the annual maximum of monthly precipitation recorded in the northern area of Portugal from 1941 to 2006 at 32 locations is performed. The aim of this paper is to apply max-stable processes, a natural extension of multivariate extremes to the spatial set-up, to briefly describe the models considered and to estimate the required parameters to simulate prediction maps.
KW - MAX-STABLE PROCESSES
KW - STOCHASTIC-PROCESSES
KW - EXTREMES
KW - RAINFALL
KW - MODEL
UR - http://www.scopus.com/inward/record.url?scp=84952683378&partnerID=8YFLogxK
U2 - 10.1016/j.pce.2015.12.001
DO - 10.1016/j.pce.2015.12.001
M3 - Article
AN - SCOPUS:84952683378
SN - 1474-7065
VL - 94
SP - 77
EP - 84
JO - Physics and Chemistry of the Earth
JF - Physics and Chemistry of the Earth
ER -