Analogues of atmospheric circulation to probe extreme and rare events

Abstract:

Analogues of atmospheric circulation have had many applications, from weather prediction to the downscaling of climate variables. The main assumptions behind this methodology are that climate variables (such as temperature or precipitation) are linked a large-scale atmospheric predictand, which is usually taken as sea-level pressure, and that such predictands recur through time. They offer a possibility to estimate probability distributions of a climate variable, conditional to patterns of atmospheric circulation. In addition, this methodology allows the quantification of unusual weather patterns that have been observed. I will represent a way to use analogues of circulation for the detection/attribution of extreme events of precipitation and temperature. This approach will be illustrated on test cases, including the warm European winter of 2006/2007, the extremes of precipitation over Southern UK and northwestern France in January 2014, and the European summer of 2015. I will show how this analysis provides a low-cost estimate of the fraction of attributable risk (FAR) for extreme events that verify the above mentioned hypotheses. Such an analysis can be performed in continuous time with reanalysis data and meteorological observations.