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Stochastic simulation of daily rainfall fields conditioned on atmospheric circulation patterns and orographic effects.
dc.contributor.author | Sapriza Azuri, Gonzalo |
dc.contributor.author | Jódar Bermúdez, Jorge |
dc.contributor.author | Gupta, Hoshi V. |
dc.contributor.author | Carrera Ramírez, Jesús |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament d'Enginyeria del Terreny, Cartogràfica i Geofísica |
dc.date.accessioned | 2013-02-25T15:41:13Z |
dc.date.available | 2013-02-25T15:41:13Z |
dc.date.created | 2012 |
dc.date.issued | 2012 |
dc.identifier.citation | Sapriza, G. [et al.]. Stochastic simulation of daily rainfall fields conditioned on atmospheric circulation patterns and orographic effects.. A: European Conference on Geostatistics for Environmental Applications. "Proceedings of the IX European Conference on Geostatistic for Environmental Applications". Valencia: Universitat Politècnica de València, 2012, p. 265-272. |
dc.identifier.isbn | 978-84-8363-924-5 |
dc.identifier.uri | http://hdl.handle.net/2117/17963 |
dc.description.abstract | The objective of the current work is to present a methodology for simulation of stochastic spatial distributed rainfall fields at the daily time step. For this purpose, we develop a geo-stochastic rainfall generating process (SRGP) to generate spatially distributed rainfall fields at daily time scale, that respect the spatial correlation structure of historically observed precipitation, while taking into account important factors that influence the development of observed spatial patterns. For each day, a spatially distributed rainfall field is generated from a pre-specified SRGP, selected based on atmospheric synoptic conditions relevant for that day. Each SRGP is simulated by applying the concept of double kriging, as the product of the spatial amount of rainfall and the spatial occurrence of rainfall by sequential simulation (sequential Gaussian simulation and sequential indicator simulation respectively). The SRGP can account for spatial rainfall nonstationarity related to orographic effects, and can be incorporated as part of a downscaling technique in the context of climate change impact studies. A case study for the Upper Guadiana basin (Spain) is presented that shows the ability of the method to reproduce various spatio-temporal characteristics of precipitation. |
dc.format.extent | 8 p. |
dc.language.iso | eng |
dc.publisher | Universitat Politècnica de València |
dc.subject | Àrees temàtiques de la UPC::Enginyeria civil::Geologia::Hidrologia subterrània |
dc.subject.lcsh | Rain and rainfall -- Mathematical models |
dc.subject.lcsh | Geo-stochastic rainfall generating process |
dc.title | Stochastic simulation of daily rainfall fields conditioned on atmospheric circulation patterns and orographic effects. |
dc.type | Conference report |
dc.contributor.group | Universitat Politècnica de Catalunya. GHS - Grup d'Hidrologia Subterrània |
dc.description.peerreviewed | Peer Reviewed |
dc.rights.access | Open Access |
local.identifier.drac | 11112527 |
dc.description.version | Postprint (published version) |
local.citation.author | Sapriza, G.; Jódar, J.; Gupta, H.V.; Carrera, J. |
local.citation.contributor | European Conference on Geostatistics for Environmental Applications |
local.citation.pubplace | Valencia |
local.citation.publicationName | Proceedings of the IX European Conference on Geostatistic for Environmental Applications |
local.citation.startingPage | 265 |
local.citation.endingPage | 272 |