Long-term variability of temperature and precipitation in the Czech Lands: an attribution analysis
Among the key problems associated with the study of climate variability and its evolution are identification of the factors responsible for observed changes and quantification of their effects. Here, correlation and regression analysis are employed to detect the imprints of selected natural forcings...
| Published in: | Climatic Change |
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| Main Authors: | , , , , |
| Format: | Article in Journal/Newspaper |
| Language: | English |
| Published: |
2014
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| Subjects: | |
| Online Access: | https://doi.org/10.1007/s10584-014-1147-7 http://hdl.handle.net/11104/0244444 |
| Summary: | Among the key problems associated with the study of climate variability and its evolution are identification of the factors responsible for observed changes and quantification of their effects. Here, correlation and regression analysis are employed to detect the imprints of selected natural forcings (solar and volcanic activity) and anthropogenic influences (amounts of greenhouse gases—GHGs—and atmospheric aerosols), as well as prominent climatic oscillations (Southern Oscillation—SO, North Atlantic Oscillation—NAO, Atlantic Multidecadal Oscillation—AMO) in the Czech annual and monthly temperature and precipitation series for the 1866–2010 period. We show that the long-term evolution of Czech temperature change is dominated by the influence of an increasing concentration of anthropogenic GHGs (explaining most of the observed warming), combined with substantially lower, and generally statistically insignificant, contributions from the sulphate aerosols (mild cooling) and variations in solar activity (mild warming), but with no distinct imprint from major volcanic eruptions. A significant portion of the observed short-term temperature variability can be linked to the influence of NAO. The contributions from SO and AMO are substantially weaker in magnitude. Aside from NAO, no major influence from the explanatory variables was found in the precipitation series. Nonlinear forms of regression were used to test for nonlinear interactions between the predictors and temperature/precipitation; the nonlinearities disclosed were, however, very weak, or not detectable at all. In addition to the outcomes of the attribution analysis for the Czech series, results for European and global land temperatures are also shown and discussed. |
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