A 12‐year radar‐based climatology of daily and sub‐daily extreme precipitation over the Swiss Alps

Abstract

The characterization of the alpine extreme precipitation is the basis to study the projected changes in frequency and intensity of heavy rainfall and is needed to improve the resilience of communities to high‐impact weather. Climatological features of extreme daily and sub‐daily precipitation are documented here for the Swiss Alps and surrounding regions at a high spatial resolution (1 km2). The basis is 12 years of data from rain gauges and CombiPrecip, a rainfall field produced by locally adjusting the radar precipitation map to the values measured by rain gauges. The agreement between rain gauges and CombiPrecip concerning both the timing and the magnitude of the extreme events is quantified by cross‐validation; overall, it increases with diminishing the severity of the extremes and increasing accumulation time. If the extremes represent on average the 10 most intense rainfall accumulations per year, in general 50–65% of rain gauges extremes are extremes also for CombiPrecip, 40–50% of CombiPrecip extremes are not extremes according to rain gauges, and CombiPrecip extremes are till 7% lower than rain gauges extremes. The maps presented in this paper show that both daily and sub‐daily extremes are more intense along the alpine slopes compared to the crest of the Alps in all seasons, with the Lago Maggiore region showing the largest values. The fraction of yearly rainfall due to extremes is generally smaller in the Alps than in flat terrain. Extreme 1‐hr precipitation is more clustered in time in the inner Alps, but is less frequent, and exhibits a strong diurnal cycle in summer. The paper also shows that sub‐daily and daily extremes occur essentially over the same 24‐hr period.

Characterizing precipitation events leading to surface water flood damage over large regions of complex terrain

“…The relative thresholds model provides similar results over whole Switzerland with its high variability of landscapes and terrain characteristics. While the absolute values of precipitation maxima are highly variable in space [39], we could show that thresholds based on local relative quantiles are [3] showed that SWFs are more frequent in the Jura mountains and the Western Plateau than in the Alpine areas and identified a few hot spot areas in Switzerland in terms of claim numbers. The presented approach covers these hot spots as well as cold spots.…”

“…We considered precipitation up to 30 d before the start of the precipitation events, similar to Froidevaux et al [26]. The weather classes stem from Panziera et al [39] and are based on geopotential height fields at 500 hPa. Thirteen classes describing the predominant flow direction are available every 6 h. The weather pattern assigned to each precipitation event was the closest in time before or exactly at the precipitation event start.…”

“…The precipitation characteristics over the complex topography of Switzerland are highly variable in space [2,39] and the spatial precipitation patterns may differ from the distribution of damage locations. To consider this variability, we have derived local quantiles at grid cell level in addition to the precipitation characteristics' absolute values.…”

“…Precipitation in Switzerland is strongly related to its complex orography, such as the main Alpine ridge and the lower Jura Mountains in the northwest of the country at the border with France and Germany. Climatologically, the inner-Alpine valleys are generally drier while the northern and southern rims of the Alps receive more precipitation [36][37][38][39][40]. There is a fundamental difference in the daily precipitation frequency distribution between the areas north and south of the Alps [40].…”

Bulk and structural convergence at convection‐resolving scales in real‐case simulations of summertime moist convection over land

“…Panziera et al . () observed peaks in extreme rainfall over the Jura mountains and the Northern Alps in their high‐resolution radar‐based precipitation climatology over Switzerland. Features such as cloud self‐organization, gust fronts from earlier clouds and precipitation‐driven cold pools are also better represented in CRMs than in coarser‐resolution models and contribute to a more realistic simulation of the diurnal cycle of convection (e.g.…”