Spatial disaggregation of Sahelian rain fields: A new application of the Gibbs sampler

H. Onibon, T. Lebel, A. Afouda, Gilles Guillot

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

The present study is in the framework of the pending research actions on the hydrological impacts of the drought that struck West Africa for almost 30 years, starting at the end of the 1960s. It centred on solving the spatial-scale problems existing between the rain fields, as they are presently available, and those necessary for the hydrological models. The proposed method is based on the coupling of the Gibbs sampler and the acceptance-rejection algorithm for the simulation of meta-Gaussian rain fields able to characterize an integral value representative for a given area by respecting the statistical properties of point rain depths. It is applied to the conditional simulation of rain fields observed at the Niamey Degree Square raingauge during the EPSAT-Niger campaign. The model performance is evaluated by comparing the simulated statistical rain field properties with those observed for high-resolution Sahelian area. According to the results of this validation, the proposed model provides an elegant and convenient answer to the conditional simulation of Sahelian rain fields.
Original languageEnglish
Title of host publicationRegional Hydrological Impacts of Climatic Change : Hydroclimatic Variability
Publication date2005
Pages211-218
ISBN (Print)978-1-901502-13-8
Publication statusPublished - 2005
Externally publishedYes
EventInternational Symposium on Regional Hydrological Impacts of Climatic Variability and Change - Foz do Iguaco, Brazil
Duration: 3 Apr 20059 Apr 2005

Conference

ConferenceInternational Symposium on Regional Hydrological Impacts of Climatic Variability and Change
Country/TerritoryBrazil
CityFoz do Iguaco
Period03/04/200509/04/2005
SeriesIAHS Publications Series (Red Books)
Volume296
ISSN0144-7815

Keywords

  • Gaussian model
  • Gibbs sampler
  • Model
  • Rainfall
  • Observation
  • Scale
  • Simulation

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