The climatological features and the long-term trends of sea surface temperature (SST) were analyzed for South China Sea (SCS) for period 1982-2012, using a high resolution AVHRR Pathfinder satellite SST data. Results show that the annual mean SST decreased with the increase of latitude in the SCS, and greater temperature gradient appeared in the areas closer to land, with the isotherms being in the direction of southwest to northeast. The maximum and minimum SST in the SCS appeared in summer and winter, respectively; There was a relatively low temperature area on the east of Indochina Peninsula and Hainan Island in summer, caused by cold water upwelling related to the southwest monsoon. The linear trend of annual mean SST in the SCS is 0.100℃ per decade in the past 30 years, and from the end of the 20th century to the beginning of the 21st century, the SST was in a high value, with the highest SST occurring in 1998. In the past 30 years, there was a warming trend for SCS in each season, and the largest increase was 0.194℃ per decade in winter, and the smallest one is 0.086℃per decade in autumn, and the trends in summer and spring are 0.121℃ per decade and 0.107℃ per decade, respectively. The most significant warming was in Taiwan Strait and the southeastern coast of Mainland China, and the maximum increase rate even exceeded 0.7℃ per decade.
The ensemble mean of simulated temperature and precipitation of CMIP5 and CMIP3 in arid areas of Northwest China was compared, the results showed that CMIP5 was more close to the observed value. Comparing with CMIP3, the correlation coefficient of CMIP5 was improved by 0.15 for year, 0.13 in spring, 0.24 in summer and 0.02 in autumn, while decreased by 0.07 in winter. CMIP5 simulated better trend of mean temperature than CMIP3 in the arid area of Northwest China, the biases reduced by 0.03℃per decade for year, 0.1℃per decade for spring, 0.01℃per decade for summer, 0.06℃per decade for autumn and 0.14℃per decade for winter, respectively. The annual and seasonal bias of CMIP5 was 1-2℃ lower than CMIP3 in the arid area of Northwest China, but temperature for both CMIP3 and CMIP5 were 3-6℃ and 1-4℃ higher than observation in Tianshan Mountains, especially in summer, which was reached to 6℃ and 4℃, respectively. Two models showed little difference in the correlation coefficient between simulated and observed precipitation, which was lower than 0.1, but the bias was still higher. The precision of precipitation trend for CMIP5 was lower than CMIP3, the biases increased by 0.67 mm per decade for year, 0.23 mm per decade for spring, 0.51 mm per decade for summer, 0.11 mm per decade for autumn, and 0.14 mm per decade for winter, respectively. The root mean square error of precipitation of CMIP5 was decreased by 77.6 mm, 25.5 mm, 25.0 mm, 18.8 mm and 13.9 mm for annual, spring, summer, autumn and winter, respectively. In spatial, CMIP5 still simulated higher annual and seasonal precipitation, but was better than CMIP3. Conversely, CMIP3 and CMIP5 gave lower annual and seasonal precipitation in the Tianshan Mountains, which was 50 mm lower than the observation.
Based on the daily maximum temperature data at Urumqi meteorological station, we established the database of temperature-rising process of Urumqi city during the period of January 1 1951 to December 31 2015. A comprehensive strength index IZ was defined in terms of the intensity values and ranks of the temperature-rising process, and sorted the extreme temperature-rising processes in Urumqi according to IZ index percentile ranking. Thus, the change characteristics of the process sustained days, frequency and intensity were analyzed. The results showed that there were a total of 567 extreme temperature-rising processes in Urumqi during 1951-2015, and the average was 8.7 times per year. The maximum strength of the extreme temperature-rising process occurred in March 14-16, 2009. The average of sustained days was 3.25 d, and the number of sustained 2 d process was the most, accounting for 23.1% of the 567 extreme temperature-rising processes in Urumqi. The longest sustained days of extreme temperature-rising process was in April (5.37 d), and the shortest was in January (2.29 d) and December (2.37 d) during 1951-2015. The annual sustained days of extreme temperature-rising processes decreased slightly, and the linear trend was not significant in the past 65 years. The extreme temperature-rising process was mainly concentrated in the period of December?April, accounting for 64.3%, and the least was only 1.9% in July of Urumqi. In the past 65 years, the frequency of extreme temperature-rising process was not significantly increased linearly, more than mean frequency after 1980s and increased in the beginning of 2010s of the inter-annual variability of frequency. Both the intensity and its inter-annual variability of extreme temperature-rising process were more than the average in 1950s and 1960s in Urumqi. The intensity gradually was weakened, and the inter-annual variability was decreased from 1970s to 2010s. Both the intensity and its inter-annual variability were increased by the beginning of 21 century.
Characteristics of snow season and snowfall during the period of Olympic Winter Games were analyzed by using the datasets of daily precipitation and weather phenomena from 1960 to 2014 at Chongli of Zhangjiakou. The paper reveals that the earliest beginning snowfall date is October 13, the latest ending snowfall date is April 30, mean beginning snowfall date for years is November 2 and mean ending snowfall date for years is April 6; the longest snow season is 190 days, while the shortest one is 123 days, mean length of snow season for years is 156 days. Maximum spells without snowfall in snow seasons mostly concentrate in late December to late January. Before February 4?20, which is planned for the Olympic Winter Games in 2022, more snowfall amounts but less snowfall days occurred in early November; while the difference in snowfall amounts and snowfall days are little in other ten-day periods. In February 4?20, snowfall occurs once every 4?5 days on average, most of which are light snow and moderate snow, the probability of heavy snow is low. These results can provide reference for making full advantage of snow resources, competition schedules planning and weather prediction during the Olympic Winter Games.
The HadCM3L climate model was used to investigate climate response to an abrupt quadrupling of atmospheric CO2 and 4% increase in solar irradiance. Modeling results show that a quadrupling of CO2 and 4% increase in solar irradiance cause approximately the same global mean surface temperature change by the end of 1000-year simulations, but the precipitation responses are substantially different. The difference is mainly due to the different fast response of the climate system, which occurs over a short time period (about one month) before sea surface warms significantly. During this period, over land, the physiological effect of CO2 reduces the plant transpiration. Over ocean, the radiation effect of CO2 leads to the increase of the temperature in the lower atmosphere, which occurs much faster than the warming of sea surface temperature. This increases vertical stability of the lower atmosphere, suppressing evaporation over ocean. Consequently, during the period of fast response (about one month), precipitation decreases in land and ocean areas. Compare to the effects of physiological effects of CO2, the radiation effect of CO2 has more important effect on the climate system at the time scale longer than a few years. But on a short time scale of one month, the physiological effect of CO2 has a greater impact over land.
Based on future climate data under RCP4.5 scenario generated from the regional climate modeling system (PRECIS), climatic northern boundary of winter wheat would move northward 147.8 km in 2071-2097 and possible planting area would increase by 1.86 ×105 km2 relative to 1981-2010. The variations of agro-climatic resources under RCP4.5 scenario in the potential northward region of winter wheat were analyzed based on the nine selected indexes of agro-climatic resources. Results indicated that: (1) compared with the climate baseline (1961-1990), the light resource in potential northward region would decrease; heat resource would significantly increase with an enhanced variability in the last 30 years of the 21st century; precipitation resource shows an overall slight increasing trend but with an greater fluctuation; (2) in the time slice 2030T (2021—2050), 2050T (2041—2070), and 2070T (2061—2090), light resource would decrease more in the northeast of study area, while less in the southwest; heat resource would increase more in northern area than southern part; precipitation resource would increase obviously in northeast of the potential northward region.
On the basis of ecological physiology characteristics of winter wheat and mathematical statistics method, the suitability function was constructed about temperature, precipitation and sunshine, respectively by using the 1960-2016 meteorological data from 37 stations in Huaibei Plain of Anhui province. In order to express the synergetic effect of meteorological factors and yields, winter wheat climate suitability modeling across the whole growth stage was established by combining the above single factor suitability function. On the other hand, agricultural climate annual assessment model was also established based on crop climatic suitability index. Results indicated that the suitability indexes in each growth stage of winter wheat were different. All single factor climatic suitability indexes were higher in the filling-milk stage, yet lower during the reviving-jointing stage. The lowest precipitation suitability appeared at the tillering stage. The temperature suitability of winter wheat in Huaibei plain of Anhui province kept higher level, following the sunshine, and precipitation became less suitable. Heat resource was abundant, and precipitation was the main limiting factor for the growth. The climatic suitability at the tillering stage was not only low, but also the variation coefficient was large, which indicated that Huaibei Plain was prone to autumn-winter successive drought, with the fluctuation of winter wheat yield. The distribution of winter wheat climate suitability in eastern areas was higher than that in northern areas, and planting risk were relatively high in western Huaibei and area along Huaihe River. The temperature suitability in the whole growth stage of winter wheat showed an significant increasing trend during 1961-2016, and the suitability index of precipitation showed a similar trend but not significantly, while the suitability index of sunshine showed an obvious downward trend. Due to the interaction between the three factors of temperature, precipitation and sunshine, the climate suitability index had not an obvious linear trend on the whole. From the spatial change of view, it increased slightly in the eastern Huaibei, while decreased slightly in the west and areas along the Huaihe River. From the view of probability density distribution, Huaibei Plain was in the middle of climate suitability level for most of the years, and the occurrence probability of the lower climatic suitability was greater than that of the higher one. In addition, winter wheat climate annual assessment was carried out based on the climate suitability classification, and the evaluation results and real grade of climate yield abundance were coincident. The accuracy of the assessment model can basically meet the needs of agro-meteorological operation and services.
Basing on the meteorological data from the 64 meteorology stations and the data of the main chemical components of the middle tobacco leaves from 2003 to 2012 in Henan flue-cured tobacco-growing areas, the variations of climatic factors and the main climatic characteristics that affected the chemical components of the middle tobacco leaves of Henan flue-cured tobacco-growing areas were revealed using the mathematical statistics. On the basis of the above, the changes of the chemical quality were studied under the two RCP (Representative Concentration Pathways) scenarios in future. The results showed as follows. From 2003 to 2012, in Henan flue-cured tobacco-growing areas, the heat factors and light factor increased, however, the trends didn’t show obvious significance, the water factors decreased significantly. At the maturity stage, the diurnal temperature range and maximum temperature increased obviously. During the fast growing stage and the maturity stage, the rainy days (daily precipitation ≥0.1 mm) and relative humidity decreased obviously. The light factor decreased during the root elongating stage and the fast growing stage and increased during the maturity stage, however, the trends didn’t show obvious significance. The main chemical components of the middle tobacco leaves had close relationship with meteorological factors and differed for different indexes in Henan flue-cured tobacco-growing areas. The obvious negative correlation was obtained between solar radiation during fast growing stage and the comprehensive evaluation value of chemical composition. The chemical quality of the flue-cured tobacco leaves in Henan flue-cured tobacco-growing areas would be decreasing because of the obvious increase of solar radiation during fast growing stage under the future climate change, especially under the scenario of RCP8.5.
Upland croplands are the main source of N2O emissions. Mitigation of N2O emissions from upland croplands will greatly contribute to an overall reduction of greenhouse gases from agriculture. Using 355 datasets extracted from 103 publications, a Meta-analysis was performed to investigate the mitigation options and potential of N2O emissions from wheat and maize fields in China. The results showed that application of inhibitors in wheat and maize fields reduced 36%-46% of the N2O emissions with an increase in crop yield. Cutting the application rates of nitrogen fertilizers by no more than 30% could reduce N2O emissions by 10%-18% without crop yield loss. Applications of slow (controlled-) release fertilizers and incorporations of crop residues could significantly mitigate N2O emissions from wheat fields, but the mitigation was not statistically significant in maize fields. The gross N2O emissions could be reduced by 9.29-13.90 Gg N2O-N per wheat season and 10.53-23.19 Gg N2O-N per maize season when different mitigation options were put into practices. The mitigation potential (MP) in wheat cultivation was particularly notable for Henan, Shandong, Hebei and Anhui provinces, accounting for 53% of the total MP in wheat fields. Heilongjiang, Jilin, Shandong, Hebei and Henan provinces showed high MP in maize cultivation, accounting for approximately 50% of the total MP in maize fields.
Carbon Generalized System of Preferences (carbon GSP) is one kind of Voluntary GHG Emission Reduction Mechanisms, which take residents as the main objects. It is an important exploration for taking subway travel as a low-carbon behavior into carbon GSP to build a low carbon society. This paper proposes two different carbon emission reduction calculation methods of subway travel, based on CCER methodology “Mass Rapid Transit Projects”, combined with the availability of traffic data and the purpose of carbon GSP. Carbon emission reductions of Guangzhou subway travel in 2015, as an example, were calculated by using these two methods. Under substitution method, the carbon emission reductions of Guangzhou subway travel were about 0.5419 kg CO2 per person, but under averaging method, this value was about 0.5155 kg CO2 per person. According to the passenger traffic of Guangzhou subway in 2015, the annual carbon emission reductions of Guangzhou subway system were about 1.30 million t CO2 under substitution method and 1.24 million t CO2 under averaging method, respectively. In these two methods, substitution method is designed based on the existing CCER methodology, which has theoretical basis. But in the actual calculation process, the setting of alternative travel patterns will greatly rely on the subjectivity of survey objects. In contrast, the baseline of averaging method is the current urban motorized travel patterns, less subjected to human disturbance. By contrast, the averaging method is more suitable for calculating subway travel carbon emission reductions of carbon GSP.
Enhancing capacity building in developing countries is an important prerequisite for global climate change actions. In the negotiating process of the United Nations Framework Convention on Climate Change, the capacity-building issue has been slow to move forward. Since the capacity-building framework for developing countries was identified at the seventh meeting of the Conference of the Parties (COP7), there has been no substantive progress in the development of capacity-building mechanisms. At the Paris Conference on Climate Change (COP21), the Parties unanimously adopted the Paris Agreement. For the first time, the Paris Agreement authorized the establishment of the Paris Capacity Building Committee (PCCB) through Subsidiary Body for Implementation (SBI). It will fully coordinate capacity-building support for developing countries and will oversee the 2016?2020 workplan for capacity-building to comprehensively and systematically promote and enhance capacity-building activities in developing countries to tackle climate change. In addition, the Paris Agreement also agreed to establish the Transparency Capacity-Building Initiative (CBIT) to strengthen the institutional and technical capacity around 2020. Subsequently, the Global Environment Facility (GEF) established the CBIT Trust Fund for the Initiative. Thus, a relatively complete international mechanism has been established on the issue of capacity-building under the Convention. Negotiations on future issues will move towards pragmatism and detail. As the global response to climate change is stepping into a new stage, China’s capacity-building issues in the negotiations should also be adjusted accordingly.