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.

Runoff data were used to better select historically significant precipitation events. The suggested criterion Q_x expresses the increase of a stream runoff over up to four days in a row. Tests confirmed that Q_x maxima correspond to maxima of areal precipitation in the respective catchment. Ten significant precipitation events in summer half-years from 1951 to 2002 were selected in 25 catchments each, and further studied in respect to spatial extent, simultaneous occurrence in various river basins, seasonal distribution, and temporal variability. Four regions were recognised within Central Europe that show related seasonality and simultaneous occurrence of events. The main coincidence of significant precipitation events was confirmed between the Austrian Alps and Bohemia and Saxony on one hand, and Moravia, Silesia, and Western Slovakia on the other hand. Significant events typically emerge here during peak summer, in the south-eastern area of the Alps during autumn months, in the South-Eastern Carpathians from May to July, and in Western Germany in spring or autumn. Episodes with less significant precipitation events (around 1960 and 1990) alternate with inverse episodes (1970's, second half of the 1990's). A reasonable selection of reference events opens the door to a quantitative evaluation of dynamic and thermodynamic conditions typical for heavy rains in various parts of Central Europe.

This paper presents three indices for evaluation of hydrometeorological extremes, considering them as areal precipitation events and trans-basin floods. In contrast to common precipitation indices, the weather extremity index (WEI) reflects not only the highest precipitation amounts at individual gauges but also the rarity of the amounts, the size of the affected area, and the duration of the event. Furthermore, the aspect of precipitation seasonality was considered when defining the weather abnormality index (WAI), which enables the detection of precipitation extremes throughout the year. The precipitation indices are complemented with the flood extremity index (FEI) employing peak discharge data. A unified design of the three indices, based on return periods of station data, enables one to compare easily inter-annual and seasonal distributions of precipitation extremes and large floods. The indices were employed in evaluation of 50 hydrometeorological extremes of each type (extreme precipitation events, seasonally abnormal precipitation events, and large floods) during the period 1961–2010 in the Czech Republic. A preliminary study of discrepancies among historic values of the indices indicated that variations in the frequency and/or magnitude of floods can generally be due not only to variations in the magnitude of precipitation events but also to variations in their seasonal distribution and other factors, primarily the antecedent saturation.

The strongest Czech windstorms from 1961 to 2010 were evaluated using a weather extremity index. The index combines the return periods of station wind gusts and the size of the affected area allowing determination of the duration of individual events. Of 50 extreme wind events (EWEs), most were synoptic-scale windstorms that occurred between the end of October and the beginning of March. However, six EWEs were categorized as the convective-scale windstorms. Four of the strongest Czech and European windstorms were related to one other (Kyrill, the November 1984 storm, Vivian and Wiebke, and Jeanette). Approximately 90% of the synoptic-scale windstorms were characterized by strong westerly or northwesterly flow at the 850 hPa level and a north–south temperature gradient at the 500 hPa level. The remaining (rather weaker) synoptic-scale events were characterized by southerly flow and a west–east temperature gradient at the 850 and 500 hPa levels, respectively. To determine the abnormality of windstorms by season, a weather abnormality index was used to evaluate 50 abnormal wind events (AWEs). Throughout the summer, as well as in half of May and September, AWEs were categorized as the convective-scale windstorms accompanied by weak 850 hPa winds. Apart from two events with easterly winds, the remaining AWEs were accompanied by winds from the southwest and a strong west–east temperature gradient at the 850 hPa level. Ten of the latter events occurred in the last two ten-day periods of July and first two ten-day periods of August. All of the events followed hot episodes, and seven of them followed one of the 25 extreme high-temperature events. A less pronounced relationship between wind and temperature anomalies was present in the colder half of the year from October to March: three of the strongest Czech EWEs were associated with abnormal high-temperature events (AHEs).