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Although ski tourism in China is experiencing a boom, and the number of operating ski areas has significantly increased, the influence of climate change on the future development of China's ski industry has so far largely been overlooked. This paper addresses this important gap by applying the ski season simulation model SkiSim 2.0 at 116 ski areas. Four main indicators of climate change impact were examined: ski season length, operational ski days in economically important season segments, technically produced snow and snowmaking requirements. For all ski resorts in China and all climate change scenarios, average ski seasons are projected to shorten (− 4 to − 61% RCP 4.5; − 6 to − 79% RCP 8.5 in the 2050s) while snowmaking needs increase (27 to 51% RCP 4.5; 46 to 80% RCP 8.5 in the 2050s). The results indicate that high regional differences in climate change vulnerability exist. The implications for altered competitiveness and development potential of the ski industry in China are discussed. [ABSTRACT FROM AUTHOR]

The frequency, intensity, and duration of extreme temperature events are expected to rise in the future and increase the related health risks of human beings. Using a novel, nationwide dataset that links extreme temperature and mortality, we estimated the short-term and long-term effects of extreme temperature on mortality in China during 2002-2013. Both extreme hot and extreme cold had immediate and long-term effects on all-cause mortality. Annual deaths per 100,000 people due to extreme hot and cold in the long term were considerably larger compared to the short term. The change in cold spell duration indicator exhibited the greatest effects on annual deaths per 100,000 people among a set of extreme weather indicators. Furthermore, cities with low economic development levels were more vulnerable to extreme temperature, compared to cities with high economic development levels. Our results offer important policy implications for developing a regional-specific extreme weather plan to handle extreme temperature events in China. [ABSTRACT FROM AUTHOR]

Advance in spring plant phenology over the last several decades has been found in all continents of the Northern Hemisphere. Compared to the studies detecting phenological trends, the studies investigating the geographical pattern of phenological variability (including mean date and magnitude of variability) are rather limited. In this study, we analyzed spatial pattern of mean date and standard deviation (SD) of first bloom date (FBD) time series (≥15 years) for black locust ( Robinia pseudoacacia) at 22 stations in China, common lilac ( Syringa vulgaris) at 79 stations in the Western US and Chinese lilac ( Syringa chinensis) at 45 stations in the Eastern US. Subsequently, the impact of geographical factors (latitude, longitude, and altitude) on the mean date and SD was quantified by using the multiple regression analysis method. Meanwhile, the relationship between FBD variability and temperature sensitivity of FBD was examined. Results showed that the mean FBD highly depended on geographical factors for all the three species. Compared to the mean date, the dependence of SD of FBD time series on geographical factors was weaker. The geographical factors could only explain 13 to 31 % of spatial variance in SD of FBD. The negative regression coefficients of latitude ( P < 0.05 except black locust) indicated that FBD is more variable at lower latitude. At most of stations, significant and negative correlations between FBD and preseason temperature on interannual scale were found, but the temperature sensitivity varied among different stations. The magnitude of temperature sensitivity decreased with increasing latitude. In general, the locations at lower latitude had earlier and more variable spring phenophase and showed stronger phenological response to climate change than the locations at higher latitude. [ABSTRACT FROM AUTHOR]