Preprints
https://doi.org/10.5194/hessd-11-12731-2014
https://doi.org/10.5194/hessd-11-12731-2014
17 Nov 2014
 | 17 Nov 2014
Status: this preprint was under review for the journal HESS. A revision for further review has not been submitted.

Spatial extremes modeling applied to extreme precipitation data in the state of Paraná

R. A. Olinda, J. Blanchet, C. A. C. dos Santos, V. A. Ozaki, and P. J. Ribeiro Jr.

Abstract. Most of the mathematical models developed for rare events are based on probabilistic models for extremes. Although the tools for statistical modeling of univariate and multivariate extremes are well developed, the extension of these tools to model spatial extremes includes an area of very active research nowadays. A natural approach to such a modeling is the theory of extreme spatial and the max-stable process, characterized by the extension of infinite dimensions of multivariate extreme value theory, and making it possible then to incorporate the existing correlation functions in geostatistics and therefore verify the extremal dependence by means of the extreme coefficient and the Madogram. This work describes the application of such processes in modeling the spatial maximum dependence of maximum monthly rainfall from the state of Paraná, based on historical series observed in weather stations. The proposed models consider the Euclidean space and a transformation referred to as space weather, which may explain the presence of directional effects resulting from synoptic weather patterns. This method is based on the theorem proposed for de Haan and on the models of Smith and Schlather. The isotropic and anisotropic behavior of these models is also verified via Monte Carlo simulation. Estimates are made through pairwise likelihood maximum and the models are compared using the Takeuchi Information Criterion. By modeling the dependence of spatial maxima, applied to maximum monthly rainfall data from the state of Paraná, it was possible to identify directional effects resulting from meteorological phenomena, which, in turn, are important for proper management of risks and environmental disasters in countries with its economy heavily dependent on agribusiness.

R. A. Olinda, J. Blanchet, C. A. C. dos Santos, V. A. Ozaki, and P. J. Ribeiro Jr.
 
Status: closed (peer review stopped)
Status: closed (peer review stopped)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
 
Status: closed (peer review stopped)
Status: closed (peer review stopped)
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement
R. A. Olinda, J. Blanchet, C. A. C. dos Santos, V. A. Ozaki, and P. J. Ribeiro Jr.
R. A. Olinda, J. Blanchet, C. A. C. dos Santos, V. A. Ozaki, and P. J. Ribeiro Jr.

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