A quantile mapping method called RQUANT was applied to the bias correction on the temperature (including daily mean temperature, daily maximum temperature, and daily minimum temperature) simulation of a regional climate model (RegCM4). Assessment on the correction effect was carried out, focusing on the simulation of climatological mean, interannual variation, extreme temperature, and agro-climatic conditions. Results show that this correction method is capable of improving the simulation of mean state of temperature. The biases of the correction results on mean temperature are within ±0.5℃. It can also significantly improve the simulation of both extreme temperature and agro-climatic conditions. However, it has little correction effect on interannual variation. Considering the good performance of this method on correcting precipitation simulation in previous study, it implies that the RQUANT method can be used on climate change projection simulations, and these bias corrected simulations would be more useful and reliable for climate change and climate change impact studies.
Based on the comprehensive strength index of regional high temperature process, the daily maximum temperature of 2452 national stations from January 1961 to August 2017 and the NCEP/NCAR reanalysis data in 2017 were used to analyze the characteristics of regional high temperature process in 2017, as well as the formation mechanism of the second regional high temperature event in summer of 2017. In 2017, regional high temperature event over China showed features of high intensity, long duration, and large coverage. Under the background of climate warming, the maximum influence domain of the single regional high temperature process in China was extending obviously. In the early July of 2017, the powerful continental high pressure controlled the northern part of China, which caused the high temperature event with a wide range of influence and a long duration. In the late July, the vast southern region of China was under the control of the subtropical ridge. The strong downdraft and anti-cyclonic circulation made the atmosphere more stable, which finally led to the formation of high temperature weather.
As an objective identification method of seasonal division, the multi-factors climate state similarity measurement has been widely used in climate change research, climate monitoring and short-term climate prediction operations in recent years. The key point of the method lies in the fusion of multi factors and the selection of typical fields. In the multi-factors climate state similarity measurement, the typical field is the climate state anomaly field which can represent the winter and summer climate states. There were three different typical attempts in this paper (1) mean climate state typical field for 60 years, (2) mean climate state typical field for 30 years, and (3) mean climate state typical field for every year. Impacts of the typical field’s selection on the seasonal division by the multi-factors climate state similarity measurement have been analyzed, then, taking the Central China area in 1998 and 2013 as an example, the accuracy of the seasonal division results of third typical field is discussed. The results showed that, the typical field as the classification index of the multi-factors climate state similarity measurement is crucial to the seasonal division results and climate change research. The differences between the climate state typical field of a single year and multi-year average are interdecadal, and are bigger in the turning period of climate state change. The division results can accurately reflect the changes of the climate state and the regional atmospheric circulation in central China in 1998 and 2013.
Based on the daily temperature data of 88 meteorological stations in the Qinling-Daba Mountains from 1975 to 2016 and the 16 extreme temperature indices, the spatial distribution of extreme temperature thresholds and the elevation dependence of extreme temperature events were analyzed. The results show that there exist obvious differences in spatial distribution of the extreme temperature threshold, it shows that the cold extreme temperature threshold reduces from the northwest to the southeast while the hot one is opposite. On the whole, the increase of warm extreme events (SU25、TR20、TX90P、TN90P、WSDI) are greater than the decrease of cold events (FD0、ID0、TX10P、TN10P、CSDI) in range. The trend of frost days, cool nights, summer days, warm days and high temperature extremum (TXx、TXn) are obvious in the whole area. The increase of growing season length in the western region are more significant, the change rates of most stations range from 3 to 6 d per decade. The cold extreme temperature threshold is positively correlated with altitude by ?0.36℃/100m while the hot one by 0.5℃/100m. It is significant in positive correlation between the trend of extremal indices and altitude and it has obvious altitude dependence. With the elevation of altitude, the trends of extremal indices increase more obvious.
The rational allocation of heat and water provides favorable climatic conditions for agricultural production. It is important to make clear the matching and variation rule of heat and water for guiding agricultural production. Based on the data of daily precipitation and temperature from 1961 to 2014 in Northeast China agricultural zone (NCAZ), the variation law of inner-annual inhomogeneous distribution of precipitation (IIDP) and its response to regional warming in NCAZ were analyzed. The results show that: (1) In 1961-2014, the trends was found and characterized by decreasing IIDP, increasing inter-annual variation of IIDP and being more early precipitation concentration period (PCP) consistently in the whole NCAZ; (2) The decrease rate of IIDP was larger in the middle of NCAZ, contrast to smaller value in southern and northern part of NCAZ; (3) The IIDP depended on air temperature strongly, which showed obvious asynchronism and inter-regional difference with precipitation concentration degree (PCD) being behind air temperature on short period and beyond on long period mainly. In a more warming world, the advance of PCP keeps simultaneous heat and precipitation stable, but the decrease of IIDP and the increase of the inter-annual variation may increase the risk of summer drought in NCAZ. The results can provide a reference for formulating scientific farmland water management strategies.
With the large-scale development of wind farms, its influence on climate is concerned. Since 2000, a few of studies have been carried out in countries such as the U.S. and Europe. China is still in the infancy, and the review of existing research can guide the further development of this work. The research progress, methods, influence mechanism and research results of impacts of wind farms on climate were summarized. A large number of observation and simulation results show that wind farms caused the rise of surface temperature and attenuation of downwind speed, it also affected precipitation, evaporation and other meteorological elements indirectly. The conclusion that wind farm has an influence on local climate change has reliability. Some model simulating results show that large-scale wind farm groups in the future may have an impact on global climate and further exploration is needed.
Urbanization is a key aspect of development that is relevant to studies of mitigation, adaptation to climate change, and its impacts. Based on the data of urban and rural population in 31 provinces of China published by the National Bureau of Statistics from 2005 to 2015 and the data of GDP per capita in each province in 2015, combined with the shared socioeconomic pathways (SSPs) proposed by the IPCC and Logistic model, the levels of urbanization in 31 provinces (autonomous regions and municipalities) in China were projected from 2016 to 2050. This paper will be beneficial to the research of numerous uncertainties in the process of urbanization under different economic development pathways and be helpful for the decision making in different provinces. The results show that by 2050, the urbanization levels of all provinces (excluding Tianjin, Beijing, Shanghai and Tibet) under the five typical SSPs will converge to about 75%. Among them, under SSP1, SSP3, SSP4, and SSP5, the urbanization levels of all provinces will converge. Under SSP2, the overall urbanization level of the country from the east to the west will gradually decrease, and the spatial distribution of urbanization will have obvious step-down. In addition, under the SSPs, it basically shows that the urbanization of the west and the middle will be fast while the eastern slow and the spatial distribution pattern of the southwest is fast but the northeast is slow under SSPs. Differences across SSPs by 2050 may be small in the high-income region where the urbanization level is already high and the uncertainty in future urbanization trend is rather small. In contrast, many middle-income and low-income provinces are in the midst of the urbanization transition, with a big difference across the 5 pathways.
The changes of chilling injury events on China’s rubber during 2031-2060 were analysed by spatial analyst with historical meteorological data in 1981-2010, future climate scenarios, industry standard of Rubber Chilling Grade (QX/T 169-2012). Future climate scenarios were HadGEM2-ES simulation with RCP2.6 and RCP8.5 emission pathways. The results show that the chilling injury events of rubber plantation would decrease in 2031-2060 under both RCP2.6 and RCP8.5 scenarios, the sub suitable area (III) and the part suitable area (IV) would more highlight, and would move toward higher level suitable area. The latitude of chilling injury center was located from 22.5°N to 23.5°N during 1981-2010, and might move northward in both the RCP2.6 (24.0°-24.5°N) and the RCP8.5 (23.5°-24.0°N). The chilling injury events would reduce in future scenarios compare with the baseline, except Yunnan rubber plantation. There might be differences between two RCPs for Yunnan rubber plantation in the future, because in the RCP2.6 light and severe chilling injury would decrease, medium and heavy chilling injury would increase; but in the RCP8.5 light and heavy chilling injury would decrease, medium and severe chilling injury would increase. The research results can be valuable for defense of chilling injury on China’s rubber and layout of rubber planting in the future. The RCP2.6, comparing the changes of the two RCPs over the baseline, would have more impact on light and sever chilling injury of rubber than RCP8.5, and would have less impact on medium and heavy chilling injury of rubber than RCP8.5.
Through the adaptive governance, by which institutional arrangements and ecological knowledge are tested and revised in a dynamic, bottom-up, ongoing, self-organized, learning by doing process, different systems including social-economic system, natural ecosystem and local knowledge and culture system should be considered into the process of decision-making. Comparing three cases in Inner Mongolia, this article evaluates their climate change risk and social vulnerability, and explores the reasons of different adaptation capacity to climate extreme events, and illustrates the possibility to apply adaptive governance to the endeavor of decreasing the local vulnerability. We found that different herders have different strategies for coping with natural disasters because they have different social capital and social memory. Some herders could move out their livestock from drought area by using their social capital; some herders could reorganize grassland use and livestock moving based on their social memory; but some herders could only buy more and more fodder and forage. This research showed that introducing adaptive governance at local level may meet the different requirements of different stakeholders to adapt climate change, promote disciplinary cooperation between natural, social and management sciences. Therefore, adaptive governance has the same view with “Future Earth” on the conceptions of “co-design, co-produce, co-deliver”, which can be developed as practical experiment in local adaptation to climate change.
Based on a questionnaire survey of corporate managers on climate change in North China, Pearl River Delta, Hunan and Hubei provinces from 2012 to 2015, two first level indices were constructed: climate change awareness index and index of business responses to climate change. Through the descriptive statistics of the survey results and the contingency table analysis, the following conclusions are conducted: the climate change awareness index is at a general level and is significantly affected by age, industry type and business type; index of business response to climate change is also at a general level and there is a large gap between different respondents, and climate change awareness level, future expectations and independent intellectual property ownership have significant influences on it.