Abstract
Abstract. After an overview of existing methods, we present a novel method of "event-adjusted" evaluation of extremeness of weather and climate events. It is based on optimization of both the considered area and the time duration for every event. The method consists of three steps: (i) estimation of return periods of a representative variable at individual sites, performed separately for various time windows; (ii) spatial interpolation of the point return period data; and (iii) searching the area and the time window in which the extremeness of the event was maximum. The extremeness is quantified as the common logarithm of the spatial geometric mean of the return periods multiplied by the radius of a circle of the same area as the one over which the geometric mean is taken. The maximum product is referred to as the weather extremity index (WEI). Two precipitation events, which affected the Czech Republic in May and in August 2010, were evaluated by the WEI for illustration. Validation of the method on sufficiently long data series is still needed. Moreover, the WEI is generally applicable regardless of the studied phenomenon (heavy rains, heat waves, windstorms, etc.). This makes it possible to study various weather and climate extremes from the viewpoint of possible recent and future changes in their frequency, seasonal distribution, and circulation conditions accompanying them.
Highlights
Weather and climate extremes have long been the focus of atmospheric sciences because of their significant social and economic impacts (Cutter et al, 2008)
Area–duration (SAD) curves were combined, one for each considered time window. Another example of the graphical approach to weather extremity evaluation is the visualization of heavy rainfalls by severity graphs and diagrams suggested by Ramos et al (2005). (The term “severity” is used by them with a different meaning than by Beniston et al, 2007.) These visualization tools are based on two concepts: intensity– duration–frequency (IDF) curves
Extra-heavy rains that reached their maximum on 16 May were associated with a cyclone passing from the Mediterranean northeastward, which became nearly stationary over Ukraine for several days
Summary
Weather and climate extremes have long been the focus of atmospheric sciences because of their significant social and economic impacts (Cutter et al, 2008). In the 1980s, Wigley (1988; reprinted in 2009) showed that even a small shift in the mean and variance of a climate variable might lead to a strong shift in the frequency of respective weather and climate extremes Since this time, many studies have focused on the analysis of past and possible future trends in extremes (e.g., Alexander et al, 2006; Klein Tank et al, 2006). One of the crucial challenges to authors of both presented types of studies is the correct selection of extreme events and evaluation of their extremeness. The extremeness of climate events can be evaluated by similar methods when only the type of input data makes the difference (e.g., daily and monthly sums for weather and climate extremes, respectively). We lastly compare this method with other methods and discuss the benefits and limits of the proposed method (Sect. 5)
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