Communication about climate and climate change is made difficult by the complexity of these concepts. The ClimateEx project (http://sil.uc.edu/webapps/climateex/) implements a novel idea to simplify this communication by treating climate mathematically as a single entity instead of a set of separate climatic variables.
The current standard for communicating the spatial variability of climate around the globe is a map based on the Köppen–Geiger classification (KGC) of climates (see, e.g., http://koeppen-geiger.vu-wie.ac.at/). One way to communicate global climate change is to show a map of change in average annual temperatures and, separately, a map of change in total annual precipitation (see, e.g., the online tool Climate Inspector at https://gisclimatechange.ucar.edu/inspector).
ClimateEx uses the data science concept of similarity-based query and opens a significantly different avenue to exploring the variety of terrestrial climates as well as their temporal change. ClimateEx queries the WorldClim (www.worldclim.org/) global gridded climate dataset; within each cell of the grid is a set of data describing a local climate. In ClimateEx, this local climate is mathematically represented by a bivariate cyclic time series
ClimateEx produces closed-loop climatograms of the time series of the average monthly temperature and monthly sum of precipitation. These visualizations underscore the cyclic character of climate; the largest dot indicates the month of Jan, the second largest indicates Feb, and so on, to show a month-to-month climate progression. As an example, the climate in Oslo, Norway, is compared to (left) a similar climate in Helsinki, Finland; (right) to a dissimilar climate in Rome, Italy; and (middle) to two climates, in London, United Kingdom, and in Reykjavik, Iceland, that both have medium-range values of similarity when compared with Oslo but are different from each other. Insets show optimal paths used by the DTW algorithm to calculate values of dissimilarity.
Citation: Bulletin of the American Meteorological Society 99, 3; 10.1175/BAMS-D-16-0334.1
ClimateEx presents users with a visual spatial search tool: a map of the world to choose (by means of panning and zooming) a location of interest (a query). During the search, ClimateEx calculates values of D(query, Ci) for all cells in the WorldClim grid and yields a color-coded map of similarity to the climate of the queried location. Moreover, it shows the global distribution of similarity (1 – D) between the queried climate and climates elsewhere, even those that are very dissimilar. As an example, Fig. 2 (top) shows the results of the worldwide search for climates similar to that of Las Vegas, Nevada.
(top) ClimateEx is used to map the climate similarity for Las Vegas (a query), where whitish colors indicate similar climates. (bottom) ClimateEx is used to map climate change between 2000 and 2070, where whitish locations have the greatest predicted magnitude of climate change.
Citation: Bulletin of the American Meteorological Society 99, 3; 10.1175/BAMS-D-16-0334.1
The concept of dissimilarity between climates also communicates climate change. A global map of a magnitude of change in local climates is the result of calculating D(
In “spatial variability” mode, ClimateEx is an interactive alternative to the KGC map free from any particular classification scheme. In “temporal change” mode, ClimateEx shows the character of climate change by allowing comparison of climatograms for a location at two different times.
At present, ClimateEx is an exploration tool primarily for education and the general public. It offers a way to learn about variability and changes in global climate as it relates to the user’s own local climate experience. In our informal tests, most users started by searching for places having climates similar to those in their hometowns; they also checked a magnitude and character of climate change in places they have lived in or plan on moving to. Beyond education and general interest, ClimateEx is also intended as a test bed for the utility of the novel concept of climate similarity. The reader is invited to “play” with this easy-to-use online tool to see if employing this concept might be useful in other settings and climate communication projects.
FOR FURTHER READING
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