Multivariate stochastic downscaling models for generating precipitation and temperature scenarios of climate change based on atmospheric circulation

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dc.contributor.author Panagoulia, D en
dc.contributor.author Bardossy, A en
dc.contributor.author Lourmas, G en
dc.date.accessioned 2014-03-01T01:57:29Z
dc.date.available 2014-03-01T01:57:29Z
dc.date.issued 2008 en
dc.identifier.issn 1790-7632 en
dc.identifier.uri https://dspace.lib.ntua.gr/xmlui/handle/123456789/28430
dc.subject atmospheric circulation en
dc.subject automated objective classification en
dc.subject autoregressive model en
dc.subject fuzzy rules en
dc.subject global warming en
dc.subject multivariate stochastic downscaling en
dc.subject precipitation en
dc.subject temperature en
dc.subject.classification Environmental Sciences en
dc.subject.other SPACE-TIME SCALE en
dc.subject.other PATTERNS en
dc.subject.other OUTPUT en
dc.subject.other CLASSIFICATION en
dc.subject.other SIMULATION en
dc.subject.other FREQUENCY en
dc.subject.other RESPECT en
dc.subject.other GREECE en
dc.title Multivariate stochastic downscaling models for generating precipitation and temperature scenarios of climate change based on atmospheric circulation en
heal.type journalArticle en
heal.language English en
heal.publicationDate 2008 en
heal.abstract The spatial resolution of General Circulation Models (GCMs) is too coarse to represent regional climate changes at the scales required for environmental impact assessment. Therefore, downscaling of precipitation and temperature has to be carried out from the GCM grids to smaller scales of a few square kilometres. Daily precipitation and temperature are modelled as stochastic processes coupled to atmospheric circulation. Precipitation is linked to circulation patterns (CPS) using conditional model parameters. Temperature is modelled using a simple autoregressive model conditioned on atmospheric circulation and local daily precipitation. The models use an automated objective classification of daily atmospheric circulation patterns based on optimized fuzzy rules. Both temperature and precipitation are downscaled to several locations taking into account the CP dependent spatial correlation. The models were applied to the Mesochora medium-sized mountainous catchment in Central Greece for validation using observed precipitation and temperature and observed classified geo-potential heights (at 700 hPa). GCM scenarios of the ECHAM4 model for 1xCO(2) and 2xCO(2) cases were used to make climate change predictions (by using classified GCM geopotential heights). Simulated values agree fairly well with historical data. Most of the GCM results (incl. mean daily values, renewal process probabilities, spell lengths) under the 2xCO(2) case reflect a somewhat wetter and a more variable precipitation regime over the Mesochora catchment with significantly increased daily mean temperatures. en
heal.journalName GLOBAL NEST JOURNAL en
dc.identifier.isi ISI:000257936200018 en
dc.identifier.volume 10 en
dc.identifier.issue 2 en
dc.identifier.spage 263 en
dc.identifier.epage 272 en

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