Analysis of Climate Model Outputs Using Linear and Nonlinear Statistical Techniques

Kód výsledku v IS VaVaI

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Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Analysis of Climate Model Outputs Using Linear and Nonlinear Statistical Techniques

Popis výsledku v původním jazyce

Regional climate models (RCMs) are currently one of regularly applied tools for localization of global climate models (GCMs) outcomes. This study is focused on analyses of mean daily temperature and precipitation using linear and nonlinear statistical techniques. 48 grid points of the regional climate models HIRHAM and RCAO and 29 meteorological stations of the Czech Republic were compared in the period 1961-1990. Mean annual courses of mean daily temperature and precipitation in the period 2071-2100 were analyzed at selected HIRHAM and RCAO grid points for A2 and B2 emission scenarios [IPCC, 2007]. Furthermore, time-delayed average mutual information (AMI) and autocorrelation function were analyzed. AMI and autocorrelation function were calculated forone selected time series of each grid point of the Czech Republic and Europe with a time lag varying from 1 to 10 days. The values of average mutual information were compared with values of autocorrelation function.

Název v anglickém jazyce

Analysis of Climate Model Outputs Using Linear and Nonlinear Statistical Techniques

Popis výsledku anglicky

Regional climate models (RCMs) are currently one of regularly applied tools for localization of global climate models (GCMs) outcomes. This study is focused on analyses of mean daily temperature and precipitation using linear and nonlinear statistical techniques. 48 grid points of the regional climate models HIRHAM and RCAO and 29 meteorological stations of the Czech Republic were compared in the period 1961-1990. Mean annual courses of mean daily temperature and precipitation in the period 2071-2100 were analyzed at selected HIRHAM and RCAO grid points for A2 and B2 emission scenarios [IPCC, 2007]. Furthermore, time-delayed average mutual information (AMI) and autocorrelation function were analyzed. AMI and autocorrelation function were calculated forone selected time series of each grid point of the Czech Republic and Europe with a time lag varying from 1 to 10 days. The values of average mutual information were compared with values of autocorrelation function.

Druh

D - Stať ve sborníku

CEP obor

DG - Vědy o atmosféře, meteorologie

OECD FORD obor

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Projekt

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Návaznosti

Z - Vyzkumny zamer (s odkazem do CEZ)

Rok uplatnění

2009

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

WDS'09 Proceedings of Contributed Papers

ISBN

978-80-7378-103-3

ISSN

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e-ISSN

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Počet stran výsledku

6

Strana od-do

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Název nakladatele

Matfyzpress

Místo vydání

Prague

Místo konání akce

Prague

Datum konání akce

2. 6. 2009

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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