We apply random set theory to an analysis of future climate change. Bounds on cumulative probability are used to quantify uncertainties in natural and socio-economic factors that influence estimates of global mean temperature. We explore the link of random sets to lower envelopes of probability families bounded by cumulative probability intervals. By exploiting this link, a random set for a simple climate change model is constructed, and projected onto an estimate of global mean warming in the 21st century. Results show that warming estimates on this basis can generate very imprecise uncertainty models.
Keywords. climate change, climate sensitivity, imprecise probability, random sets, belief functions
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Authors addresses:
Elmar Kriegler
Potsdam Institute for Climate Impact Research
P.O. Box 60 12 03
D-14412 Potsdam
Hermann Held
PO Box 60 12 03
D-14412 Potsdam
E-mail addresses:
| Elmar Kriegler | kriegler@pik-potsdam.de |
| Hermann Held | held@pik-potsdam.de |