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Frameworks for Analysis of Regional, concurrent, Conditional and Non-Stationary Extremes in Geosciences

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Technical Report,01 Dec 2014,31 Aug 2015

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University of California - Irvine Irvine United States

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The objectives of this STIR project was to investigate the merit of the following model concepts 1 A model for regional non-stationary analysis of extremes with constant and time-varying exceedance probability concepts. This will allow analysis of extremes in geosciences across different spatial scales under non-stationary assumption. The model is named Process-informed Nonstationary Extreme Value Analysis ProNEVA and can integrate time or a physically-based covariate to describe change in statistics of extremes. The source code of the toolbox along with a Graphical User Interface GUI is already freely available to the public. 2 An empirical Bayesian-based extreme value model for assessing concurrent and conditional extremes. This will allow deriving and assessing the full distribution functions of concurrent joint extremes in a changing environment.3 A comprehensive and generalized framework for uncertainty assessment of extremes using the concept of Differential Evolution Markov Chain DE-MC. This model will allow deriving quantitative uncertainty estimates for extremes in a non-stationary world.

Subject Categories:

  • Meteorology
  • Statistics and Probability

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