Siliverstovs B.,ETH Zurich |
Otsch R.,University of Potsdam |
Kemfert C.,German Institute for Economic Research |
Jaeger C.C.,PIK |
And 2 more authors.
Stochastic Environmental Research and Risk Assessment | Year: 2010
This study models maximum temperatures in Switzerland monitored in twelve locations using the generalised extreme value (GEV) distribution. The parameters of the GEV distribution are determined within a Bayesian framework. We find that the parameters of the underlying distribution underwent a substantial change in the beginning of the 1980s. This change is characterised by an increase both in the level and the variability. We assess the likelihood of the heat wave of the summer 2003 using the fitted GEV distribution by accounting for the presence of a structural break. The estimation results do suggest that the heat wave of 2003 is not that statistically improbable if an appropriate methodology is used for dealing with nonstationarity. © 2009 Springer-Verlag.
Arnell N.W.,University of Reading |
Lowe J.A.,UK Met Office |
Brown S.,University of Southampton |
Brown S.,Tyndall Center for Climate Change Research |
And 13 more authors.
Nature Climate Change | Year: 2013
This study presents the first global-scale multi-sectoral regional assessment of the magnitude and uncertainty in the impacts of climate change avoided by emissions policies. The analysis suggests that the most stringent emissions policy considered here - which gives a 50% chance of remaining below a 2C temperature rise target - reduces impacts by 20-65% by 2100 relative to a 'business-as-usual' pathway which reaches 4C, and can delay impacts by several decades. The effects of mitigation policies vary between sectors and regions, and only a few are noticeable by 2030. The impacts avoided by 2100 are more strongly influenced by the date and level at which emissions peak than the rate of decline of emissions, with an earlier and lower emissions peak avoiding more impacts. The estimated proportion of impacts avoided at the global scale is relatively robust despite uncertainty in the spatial pattern of climate change, but the absolute amount of avoided impacts is considerably more variable and therefore uncertain. © 2013 Macmillan Publishers Limited. All rights reserved.