Geostatistical modeling of high resolution climate change scenarion data

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41320%2F11%3A49790" target="_blank" >RIV/60460709:41320/11:49790 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Geostatistical modeling of high resolution climate change scenarion data
Original language description
Geostatistical prediction of annual mean air temperature and precipitation data was carried out for the reference (1961?1990) and distant future (2071?2100) climates. In particular, we used kriging of residuals, universal kriging with external drift, andexternal drift kriging in the scope of IRF-k (intrinsic random functions of order k). Prediction based on linear regression of elevation data was used as a complementary technique. We found that all kriging-based techniques outperformed the linear regression-based approach, yielding mean square error lower by 53?75%. External drift kriging in the scope of IRF-k produced slightly better results for most of the climate variables analysed. The poorest results were achieved in the case of annual mean air temperature for the period 1961?1990, where the variogram of residuals was very erratic.
Czech name
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Czech description
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Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
DG - Atmospheric sciences, meteorology
OECD FORD branch
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Project
<a href="/en/project/QH91097" target="_blank" >QH91097: Analysis of the climate change impacts on the distribution and voltinism of Ips typographus in spruce forests of the Czech Republic as underlying information for their sustainable management</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2011
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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