How frequent is a 20 mm rainfall event in London? What is the expected output of a planned wind power plant? What is the likelihood of frost in Burgundy in late April? Individuals, companies, and policy makers use weather and climate data to make decisions. Providing this information used to be the task of experts, but today we find such information conveniently on web portals. Globally complete, highly processed weather and climate data products are available freely, in a ready-to-use form, downloadable via web-interfaces. This is first of all a commendable achievement. By providing information on extremes, these data also contribute to increase the resilience of society towards climatic changes. However, the ease-of-use changes our relation to climate data. We tend to forget how the climate information was generated.
Data coverage in 1947 for surface pressure. See more in the WIREs review.
In WIREs Climate Change, Stefan Brönnimann and Jeannine Wintzer from the University of Bern recall the diverse origins of climate data and demonstrate that historical and present-day contexts imprint on the data.
Where, what, why and how for people measure depends on social, economic and political factors; and these factors change over time. This becomes evident in maps of data coverage. For instance, coverage for 1947 displays boundaries of nation states, world trade routes and a colonial world. Maps for later decades show geopolitics, development, but also the ambition to create global monitoring networks. Future data maps might show mobile communication, which already today is used to extract weather information.
Brönnimann and Wintzer argue that climate data should not be seen just as values of physical variables. Climate data are also societal products, and the historical and present-day contexts that are imprinted on climate data are important in their own right. The authors term awareness of and sensitivity to this context-dependence “climate data empathy” and argue that context should be seen as a source of information to be communicated along with the data. Context provides added value to data products; it may help designing communication strategies and avoiding pitfalls in dealing with current data.
More generally, it may also contribute to raising awareness of the contingency of environmental data. So, knowing the frequency of late frost in Burgundy is helpful. But knowing why weather stations were put up in that region in the first place may already tells us something about the susceptibility of agriculture.
Kindly contributed by the Authors.
