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

Panagoulia, D; Bardossy, A; Lourmas, G

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.publisher	GLOBAL NETWORK ENVIRONMENTAL SCIENCE & TECHNOLOGY	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