Intensified impacts on mortality due to compound winter extremes in the Czech Republic

Abstract

Although impacts of extremely cold temperatures on human health have been widely studied, adverse effects of other extreme weather phenomena have so far received much less attention. We employed a high-quality long-term mortality time series (1982–2017) to evaluate impacts of extreme winter weather in the Czech Republic. We aimed to clarify whether compound events of extreme weather cause larger impacts on mortality than do each type of extreme if evaluated individually. Using daily data from the E-OBS and ERA5 datasets, we analyzed 9 types of extreme events: extreme wind gust, precipitation, snowfall, and sudden temperature and pressure changes. Relative mortality deviations from the adjusted baseline were used to estimate the immediate effect of the selected extreme events on excess mortality. The impact was adjusted for the effect of extreme cold.Extreme events associated with sudden rise of minimum temperature and pressure drops had generally significant impact on excess mortality (3.7% and 1.4% increase). The impacts were even more pronounced if these events occurred simultaneously or were compounded with other types of extremes, such as heavy precipitation, snowfall, maximum temperature rise, and their combinations (increase as great as 14.4%). Effects of some compound events were significant even for combinations of extremes having no significant impact on mortality when evaluated separately. On the other hand, a “protective” effect of pressure increases reduced the risk for its compound events. Meteorological patterns during extreme events linked to excess mortality indicate passage of a low-pressure system northerly from the study domain. We identified extreme winter weather events other than cold temperatures with significant impact on excess mortality. Our results suggest that occurrence of compound extreme events strengthen the impacts on mortality and therefore analysis of multiple meteorological parameters is a useful approach in defining adverse weather conditions.