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Abstract:
The EU project Weather Impacts on Natural, Social and Economic Systems (WISE) has analysed impacts of current climate variability to evaluate the sensitivity of today’s society to extreme weather. Unlike studies of anticipated impacts of climate change, WISE did not rely on scenarios and projections, but on existing and newly collected data. The research involved (i) the statistical modelling of meteorological and sectoral time series, aimed at quantifying the impacts of changing weather variables on sector output, (ii) a population survey, aimed at investigating public perception of and behavioural response to unusually hot and dry summers and mild winters, and (iii) a management survey, aimed at obtaining insight into managers’ awareness and perception of the importance of extreme weather on their operations.
The three activities revealed a wealth of data and information, providing relevant insights into Germany’s sensitivity to and perception of extreme weather events. Sectors that were analysed included agriculture, outdoor fire, water supply, human health, electricity and gas consumption, tourism and the insurance industry. It appears from the statistical modelling that extreme weather can have impressive impacts on all sectors, especially when expressed in monetary terms. However, weather variability is generally considered a manageable risk, to which sectors in Germany appear reasonably well-adapted. The population and management surveys reveal both positive and negative impacts of extreme weather. People generally respond to these impacts by adjusting their activities. The utilities (electricity, gas and water) indicate that they are robust to the current level of weather variability and do not consider climate change an important threat to their operations. The tourism sector experiences impacts but typically takes a reactive approach to adaptation, although it is also developing weather-insensitive products.
It appears that the results of the statistical analyses do not always correspond to the perceptions of the population and managers. For example, while people state that they (try to) use less water during hot and dry spells, both the statistical analyses and the management survey suggest that they use more. Such discrepancies are particularly interesting from a policy perspective, because they may undermine public or managerial acceptability of adaptation or mitigation measures, depending on which perception prevails when the measures are designed.
