The influence of climate change on the natural environmental and socio-economic system leads to a series of adverse effects. With the development of socio-economy, climate change hazards interact with the environmental and socio-economic risk bearing body and form the spatial-temporal patterns of climate change risk. The systematic expression of the spatial-temporal patterns is the scientific foundation of climate changes adaptation. Based on the RCP8.5 climate scenario data from 2021 to 2050, we analyzed the variation trend and rate of temperature and precipitation, and assessed the hazard of extreme climate events including drought, heat wave and flood. Then, economy, population, food production and ecosystem were selected as the risk bearing bodies to assess the possible impacts of climate change as the indices qualifying the comprehensive climate change risk. Under the guidance of systematic principle, predominating factor principle, as well as the space consecution principle, we proposed a scheme of three-level regional division system for the comprehensive climate change risk regionalization in China. Finally, the Chinese mainland was divided into 8 climate change sensitive zones, 19 danger zones of extreme events and 46 comprehensive risk zones of bearing body. The result shows that the climate changes high risk zones in China under the RCP8.5 climate scenario from 2021 to 2050 include North China weak warming and precipitation increased sensitive zone, North China Plain heat wave danger zone, population-economy-food high risk zone, South China-Southwest China weak warming and precipitation increased sensitive zone, Yunnan-Guizhou mountain heat wave danger zone, ecosystem-economy-food-population high risk zone; coastal South China flood-heat wave danger zone, ecosystem-food-economy-population high risk zone. The comprehensive climate change risk regionalization of China covers the climate change scenarios, the extreme events, and the possible lost information of the socio-economy and ecosystem, which can provide scientific and technological support for national and local governments to cope with the climate change and risk management.

Changes in hydrological processes and water resources under climate change in the Tianshan Mountains of Central Asia have been investigated based on data analysis and paper review. Under the context of global warming hiatus, temperature of the Tianshan Mountains in Central Asia has been in a state of high variability, which has accelerated the melting of glacier and snow. Warming has resulted in a series of changes in water resources. Snowfall fraction decreased from 11%-24% in 1960-1998 to 9%-21% in 2000-2014, 97.25% of the glaciers retreated in the last 50 years; and water storage decreased at a rate of -3.72 mm/a during 2003-2014. Warming has led to changes in mountainous hydrological processes and water resources. The runoff in the Tianshan Mountains has increased due to the accelerated glacier/snow melt, however, the runoff will decrease in the long term under continuous warming and current precipitation conditions.

In this paper, the literatures about the drought and flood disasters in Baoji region during the Ming and Qing dynasties were collected and sorted. The drought and flood disaster chains were discussed, while the response to climate change in Baoji region during 1368-1911 years was analyzed by using the accumulative anomaly method, moving average method and wavelet analysis and so on. The results showed that 297 events of drought and flood disasters occurred in Baoji during 1368-1911, while drought occurred 191 times and flood 106 times, accounting for 64.31% and 35.69%, respectively. There were obvious stage characteristics for drought and flood disasters, with drought episodes mainly observed from 1368 to 1644, while during 1645-1804 a fluctuant phase emerged, and the period 1805-1911 experienced drought episodes, presenting the alternating drought-wet period on the whole. Meanwhile there were three periods (70a, 110a and 170a) of oscillation on time scale of drought and flood existence, which had relationship with sunspot activity cycle. Drought and flood disasters had obvious variations in space; the northern and eastern parts of the Weihe river basin were prone to drought and flood. The occurrence of drought and flood disaster chains was a response to global climate change during the Ming and Qing dynasties in Baoji. Since the 1760s, the global climate deterioration has led to frequent extreme drought and flood disaster events.

Using NDVI3g vegetation index, we defined 18 phenological metrics to investigate phenology change in the Tibetan Plateau (TP). Considering heterogeneity of vegetation phenology, we divided TP into 8 vegetation clusters according to 1:1000000 vegetation cluster map. Using partial least regression (PLS) method, we investigated impacts of climate variables such as temperature, precipitation and solar radiation on vegetation phenology. Results indicated that: (1) Turning points of the date of the start of growing season (SOS) metrics are mainly observed during 1997-2000, before which SOS advanced 2-3 d/a. Turning points of the date of the end of growing season (EOS) and length of growing season (LOS) metrics are found during 2005 and 2004-2007, respectively. Before the turning point, EOS has a delayed tendency of 1-2 d/10a, and LOS has a lengthening tendency of 1-2 d/10a. After the turning point, the tendency of SOS and EOS metrics is questionable. Meanwhile, lengthening of LOS is not statistically significant; (2) Alpine meadows and alpine shrub meadows are subject to the most remarkable changes. Lengthening LOS of alpine meadow is mainly due to advanced SOS and delayed EOS. Nevertheless, lengthening LOS of alpine shrub meadow is attributed mainly to advanced SOS; (3) Using PLS method, we quantified impacts of meteorological variables such as temperature, precipitation and solar radiation on phenology changes of alpine meadows and alpine shrub meadows, indicating that temperature is the dominant meteorological factor affecting vegetation phenology. In these two regions, autumn of last year and early winter temperature of last year have a positive effect on SOS. Firstly, increased temperature in this period would postpone last year's EOS, and hence indirectly delay SOS of the current year; Secondly, warming autumn and early winter have the potential to negatively impact fulfilment of chilling requirements, leading to delay of SOS. Except summer, minimum temperature has a similar effect on vegetation phenology, when compared to average and maximum temperature. Furthermore, precipitation effects on phenology fluctuate widely across different months. Precipitation of the autumn and winter/spring of the last year has a negative/positive effect on SOS. Besides, precipitation acts as the key driver constraining vegetation growth in August, during which precipitation has a positive impact on EOS. Therefore, solar radiation can exert impacts on vegetation phenology mainly during summer and early fall. Our research will provide a scientific support for the improvement of vegetation phenology model.

Flowering phenology is of great importance for flower tourism planning, landscape arrangement, and pollen allergy forecast. Previous studies mainly focused on the changes in the first flowering date of plants, but rarely examined the spatiotemporal changes in flowering duration. In this study, we systematically analyzed the changes in flowering durations for 23 woody plants at 42 sites from China Phenological Observation Network (CPON) during 1963-2012. Through investigations on the spatiotemporal patterns, interspecific difference, and the forms of change in flowering durations, the following conclusions are drawn. (1) Out of all the 259-time series, flowering durations have lengthened in 159-time series (61.39%), where 21.24% have lengthened significantly. The extending trends for shrub species are found to be more significant than those for tree species. (2) Most flowering durations in the south of Northeast China, East China, and Central China exhibited trends of shortening, but those in the north of Northeast China, North China, parts of Southwest China, and South China exhibited extending trends. The strongest trend (0.94 d/a) occurred at around 20°N. The mean trend of flowering duration (0.28 d/a) in western China (87°E-112°E) was larger than that in eastern China (0.05 d/a). (3) The overall changes in flowering duration could be identified into three stages: 1963-1980 (shorter), 1981-1997 (close to multi-year average) and 2001-2012 (longer), although evident difference existed among species. (4) As for the time series with extending flowering duration, 43.39% were induced by a much earlier first flowering date than the end of flowering date. For the time series with shortening flowering duration, 62% were caused by a more advanced trend at the end of flowering date than at the first flowering date.