Characterizing and visualizing spatio-temporal patterns in hourly precipitation records
2012 (English)In: Journal of Theoretical and Applied Climatology, ISSN 0177-798X, E-ISSN 1434-4483, Vol. 109, no 3-4, 333-343 p.Article in journal (Refereed) Published
We develop new techniques to summarize and visualize spatial patterns of coincidence in weather events such as more or less heavy precipitation at a network of meteorological stations. The cosine similarity measure, which has a simple probabilistic interpretation for vectors of binary data, is generalized to characterize spatial dependencies of events that may reach different stations with a variable time lag. More specifically, we reduce such patterns into three parameters (dominant time lag, maximum cross-similarity, and window-maximum similarity) that can easily be computed for each pair of stations in a network. Furthermore, we visualize such threeparameter summaries by using colour-coded maps of dependencies to a given reference station and distance-decay plots for the entire network. Applications to hourly precipitation data from a network of 93 stations in Sweden illustrate how this method can be used to explore spatial patterns in the temporal synchrony of precipitation events.
Place, publisher, year, edition, pages
Springer, 2012. Vol. 109, no 3-4, 333-343 p.
precipitation; hourly rainfall records; spatial dependence; time lag; cosine similarity
Probability Theory and Statistics
IdentifiersURN: urn:nbn:se:liu:diva-71297DOI: 10.1007/s00704-011-0574-xISI: 000307243900002OAI: oai:DiVA.org:liu-71297DiVA: diva2:447073
funding agencies|Swedish Research Council (VR)||Gothenburg Atmospheric Science Centre (GAC)||FORMAS|2007-1048-8700*51|2011-10-102011-10-102012-11-01Bibliographically approved