Analysis of Climate Model Outputs Using Linear and Nonlinear Statistical Techniques

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68378289%3A_____%2F09%3A00338107" target="_blank" >RIV/68378289:_____/09:00338107 - isvavai.cz</a>
Result on the web
—
DOI - Digital Object Identifier
—

Result language
angličtina
Original language name
Analysis of Climate Model Outputs Using Linear and Nonlinear Statistical Techniques
Original language description
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.
Czech name
—
Czech description
—

Publication year
2009
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Similar results(10)