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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]

Around the intensity, frequency, duration, accumulated temperature, and even extremes of high-temperature events, nine selected temperature-related indices were used to explore the space and time changes of rice heat stress in Jiangxi province, southeast China. Several statistical methods including Mann-Kendall trend test (M-K test) and principal component analysis (PCA) were used in this study, and main results were listed as follows: (1) The changes in the intensity indices for high-temperature events were more significant, it was mainly embodied in that more than 80 % of stations had positive trends. (2) R-mode PCA was applied to the multiannual average values of nine selected indices of whole stations, and the results showed that the higher hazard for rice heat stress could be mainly detected in the middle and northeast area of Jiangxi. (3) S-mode PCA was applied to the integrated heat stress index series, and the results demonstrated that Jiangxi could be divided into four sub-regions with different variability in rice heat stress. However, all the sub-regions are dominated by increasing tendencies in rice heat stress since 1990. (4) Further analysis indicated that the western north Pacific sub-tropical high (WPSH) had the significant dominant influence on the rice heat stress in Jiangxi province. [ABSTRACT FROM AUTHOR]

Hand, foot, and mouth disease (HFMD) is one of the most common communicable diseases in China, and current climate change had been recognized as a significant contributor. Nevertheless, no reliable models have been put forward to predict the dynamics of HFMD cases based on short-term weather variations. The present study aimed to examine the association between weather factors and HFMD, and to explore the accuracy of seasonal auto-regressive integrated moving average (SARIMA) model with local weather conditions in forecasting HFMD. Weather and HFMD data from 2009 to 2014 in Huainan, China, were used. Poisson regression model combined with a distributed lag non-linear model (DLNM) was applied to examine the relationship between weather factors and HFMD. The forecasting model for HFMD was performed by using the SARIMA model. The results showed that temperature rise was significantly associated with an elevated risk of HFMD. Yet, no correlations between relative humidity, barometric pressure and rainfall, and HFMD were observed. SARIMA models with temperature variable fitted HFMD data better than the model without it (s R increased, while the BIC decreased), and the SARIMA (0, 1, 1)(0, 1, 0) offered the best fit for HFMD data. In addition, compared with females and nursery children, males and scattered children may be more suitable for using SARIMA model to predict the number of HFMD cases and it has high precision. In conclusion, high temperature could increase the risk of contracting HFMD. SARIMA model with temperature variable can effectively improve its forecast accuracy, which can provide valuable information for the policy makers and public health to construct a best-fitting model and optimize HFMD prevention. [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]

Recent shifts in phenology reflect the biological response to current climate change. Aiming to enhance our understanding of phenological responses to climate change, we developed, calibrated and validated spatio-temporal models of first leaf date (FLD) for 20 broadleaved deciduous plants in China. Using daily meteorological data from the Chinese Meteorological Administration and the Community Climate System Model, version 3 (CCSM3) created using three IPCC scenarios (A2, A1B and B1), we described the FLD time series of each species over the past 50 years, extrapolating from these results to simulate estimated FLD changes for each species during the twenty-first century. Model validation suggests that our spatio-temporal models can simulate FLD accurately with R (explained variance) >0.60. Model simulations show that, from 1952 to 2007, the FLD in China advanced at a rate of −1.14 days decade on average. Furthermore, changes in FLD showed noticeable variation between regions, with clearer advances observed in the north than in the south of the country. The model indicates that the advances in FLD observed from 1952-2007 in China will continue over the twenty-first century, although significant differences among species and different climate scenarios are expected. The average trend of FLD advance in China during the twenty-first century is modeled as being −1.92 days decade under the A2 scenario, −1.10 days decade under the A1B scenario and −0.74 days decade under the B2 scenario. The spatial pattern of FLD change for the period 2011-2099 is modeled as being similar but showing some difference from patterns in the 1952-2007 period. At the interspecific level, early-leafing species were found to show a greater advance in FLD, while species with larger distributions tended to show a weaker advance in FLD. These simulated changes in phenology may have significant implications for plant distribution as well as ecosystem structure and function. [ABSTRACT FROM AUTHOR]

The timing of phenological events is highly responsive to global environmental change, and shifts in a phenological phase can affect terrestrial ecosystems, agriculture and economics. We analyzed changes in phenology for the spring season in China that occurred between the 1960's and the 2000's using four methods: species-level observations, meta-analysis, satellite measurements and phenology modeling. Previous analyses have rarely been reported due to sparse observations. Our results suggest that spring in China has started on average 2.88 days earlier per decade in response to spring warming by −4.93 days per degree Celsius over the last three decades. The shift towards an earlier start of spring was faster in two forest biomes (spring started on average 3.90 days earlier per decade) than in three grassland biomes (spring started on average 0.95 day earlier per decade). This difference was probably due to increased precipitation impacts in the grassland biomes. Interannual variations in the start of spring were most likely attributed to annual fluctuations in spring temperature (∼40%) and in large-scale circulation anomalies (∼20%). [ABSTRACT FROM AUTHOR]