Climate change and related impact
A broad accumulation of evidence, including that from global-scale detection and attribution
studies resulted in the strong conclusion of the Intergovernmental Panel on Climate Change
Fourth Assessment Report (IPCC AR4) that most of the warming observed over the last 50
years is attributable to human activities. Some recent studies have begun to assess whether the
climate response to external forcing is detectable on regional scales. In addition, other studies
are now evaluating the prospects of detecting externally forced change in oceanic variables
despite the scarcity of the observed datasets. The current assessments of potential impacts of
climate change are still deficient in terms of regional details, extreme events distribution as well
as in terms of characterisation of uncertainty associated to them.
All these developments are important, because ultimately, policy makers will be strongly
influenced by evidence of impacts in regions that are of direct interest to them, and by evidence
that anthropogenic greenhouse gas emissions are having an influence on the occurrence of high
impact climate events such as heat waves and flooding.
This project aims to address these various questions by using state-of-the-art climate models
of various high-resolution, new downscaling strategies and improved statistical algorithms
(detection and attribution techniques, changes in extreme event distribution ...).
studies resulted in the strong conclusion of the Intergovernmental Panel on Climate Change
Fourth Assessment Report (IPCC AR4) that most of the warming observed over the last 50
years is attributable to human activities. Some recent studies have begun to assess whether the
climate response to external forcing is detectable on regional scales. In addition, other studies
are now evaluating the prospects of detecting externally forced change in oceanic variables
despite the scarcity of the observed datasets. The current assessments of potential impacts of
climate change are still deficient in terms of regional details, extreme events distribution as well
as in terms of characterisation of uncertainty associated to them.
All these developments are important, because ultimately, policy makers will be strongly
influenced by evidence of impacts in regions that are of direct interest to them, and by evidence
that anthropogenic greenhouse gas emissions are having an influence on the occurrence of high
impact climate events such as heat waves and flooding.
This project aims to address these various questions by using state-of-the-art climate models
of various high-resolution, new downscaling strategies and improved statistical algorithms
(detection and attribution techniques, changes in extreme event distribution ...).
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