Arbeitspapier

Semiparametric copula-based stochastic weather generator

Stochastic Weather Generators (SWGs) try to replicate the stochastic patterns of climatological variables characterized by high dimensionality, non-normal probability density functions and non-linear dependence relationships. However, conventional SWGs usually typify weather variables with not always justified probability distributions assuming linear dependence between variables. This research proposes an alternative SWG that introduces the advantages of the copula modeling into the replication of stochastic weather patterns. The semiparametric copula-based SWG introduces more exibility allowing researcher to model non-linear dependence structures independently of the marginals involved. Also, it can better model tail dependence, which would result in a more accurate reproduction of extreme weather events.

Language
Englisch

Bibliographic citation
Series: Working Papers ; No. 2013-09

Classification
Wirtschaft
Subject
weather generator
Archimedian copulas
Brownian Bridge
extreme weather
events replication

Event
Geistige Schöpfung
(who)
Juárez-Torres, Miriam
Richardson, James W.
Vedenov, Dmitry
Event
Veröffentlichung
(who)
Banco de México
(where)
Ciudad de México
(when)
2013

Handle
Last update
10.03.2025, 11:42 AM CET

Data provider

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Object type

  • Arbeitspapier

Associated

  • Juárez-Torres, Miriam
  • Richardson, James W.
  • Vedenov, Dmitry
  • Banco de México

Time of origin

  • 2013

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