Based on the ground and sounding meteorological data, the hydrological changes of the Aksu River Basin during 1960-2015 were analyzed, and the role of upper atmosphere climate in runoff reproducing was discussed. The results show that under the background of global warming, the surface air temperature in Aksu River Basin increased significantly with an rate of 0.18℃/10a (ranging from -0.09 to 0.43℃/10a), and the precipitation increased at a rate of 10.42 mm/10a (ranging from 2.23 to 21.11 mm/10a). For the climate at the upper atmosphere, the 0℃ level heights of Almaty, Yining and Kuqa generally increased, and the increase reached 88.9 m, 29.4 m and 7.2 m in 1990-2015 compared to those in 1960-1989, respectively. The combination of near surface air temperature and precipitation and upper 0℃ level heights can significantly improve the reproducing performance of summer runoff in the Aksu River Basin.
Shanxi province is located on the border of monsoon in the north of China, which is across multiple latitudes. The mountains and basins in the study area are staggered. Therefore, the influential factors of precipitation in the study area are complicated. Based on the daily precipitation data of 14 rain gauging stations in Shanxi from 1957 to 2014, the precipitation concentration index (CI) and extreme precipitation index (R95p, R99p) were calculated at annual scale and multi-year scale. Mann-Kendall method was utilized to analyze the spatio-temporal variation of precipitation concentration, and its influential factors. The results showed that the positive correlation between R99p and CI at annual scale is significant, which means high precipitation concentration will increase the possibility of extreme precipitation. Precipitation concentration shows obvious differences in latitudinal zonality and local space at multi-year scale. Due to a temperate continental monsoon type, the precipitation concentration degree is relatively low and the change range is relatively narrow (0.59-0.64). In general, the concentration of precipitation is decreasing at inter annual scale, and the descending trend of Wutaishan, Youyu, Wuzhai and Yuncheng is significant at the 0.05 significance level. The possibility of extreme precipitation in the central basin area is greater than that in the plateau high-mountain area due to the higher CI value and insignificant declined trends detected. The correlation between multi-year scale precipitation CI and elevation, latitude, longitude, mean annual precipitation and mean annual rainy days is not significant. The higher elevation and larger amplitude make the influence of elevation on the concentration of precipitation at annual scale increase. The correlation between precipitation CI and NAO, ENSO air-sea interaction and EASMI is not significant. However, there is a significant negative correlation between annual CI and PDO. The possibility of extreme precipitation is greater when PDO is negative with the Western Pacific Subtropical High westward and stronger. The results demonstrated geographic conditions and air-sea interactions exert a complex influence on precipitation concentration at a regional scale.
Based on data of the surface wind speed at Shijiazhuang city meteorological station (simplified as Shijiazhuang station) and four rural meteorological stations during 1972-2012, urbanization effect on the surface wind speed series at Shijiazhuang station was analyzed using an urban-rural difference method. The results showed that: (1) In 1972-2012, there were very significant decreased trends on annual and seasonal mean wind speeds, mean maximum wind speeds of 10 min and gale days at Shijiazhuang station, and the annual mean decreased trends were -0.15 (m/s)/10a, -1.05 (m/s)/10a and -2.90 d/10a respectively. Annual mean wind speed of rural stations showed weakly decreased trend, the decreased trend on annual mean maximum wind speed of 10 min was more obvious, and the decreased trend on annual gale days was very significant. The decreased trends on annual mean wind speed, annual mean maximum wind speed of 10 min and annual gale days at rural stations were -0.02 (m/s)/10a, -0.21 (m/s)/10a, and 2.19 d/10a, respectively; (2) In the study period, urbanization effect on the annual mean wind speed at Shijiazhuang station was -0.13 (m/s)/10a, which was very significant, and the urbanization contribution reached 86.0%, indicating that the urbanization effect is large and significant. Urbanization effect on the mean wind speeds of the urban station in spring, summer, autumn and winter were -0.16 (m/s)/10a, -0.10 (m/s)/10a, -0.13 (m/s)/10a and -0.15 (m/s)/10a respectively, and the urbanization contributions were 82.8%, 87.6%, 88.6% and 85.4%, respectively; (3) Urbanization effect on the annual mean maximum wind speed of 10 min at the urban station was -0.84 (m/s)/10a, and the urbanization contribution was 79.7%. Urbanization effects on the seasonal mean maximum wind speed of 10 min were -0.94 (m/s)/10a, -0.80 (m/s)/10a, -0.60 (m/s)/10a and -1.01 (m/s)/10a, respectively for spring, summer, autumn and winter, with the urbanization contributions of 90.4%, 78.6%, 64.9% and 79.1%, respectively; (4) Urbanization effect on the annual gale days at Shijiazhuang station was not significant, but the urbanization effect on the winter gale days was large and significant.
We tentatively analyzed differences between global terrestrial net primary productivity (NPP) under global warming by the targeting temperature of the Pairs Agreement and that during 1986-2005. We addressed the changes in global terrestrial NPP, changes inrelating environmental factors (atmospheric CO2 concentration, temperature, precipitation, and radiation), and their contribution to the NPP changes under global warming of 1.5℃ and 2℃. The projected global terrestrial NPP increases in proportion to the warming magnitude based on the results from CMIP5 models that runs under the three representative concentration pathways (RCP2.6, RCP4.5 and RCP8.5). Changes in the projected environmental factors and NPP at given warming magnitude are generally consistent across the three RCPs. The increasing atmospheric CO2 concentration is the dominant factor that drives the total amount of global terrestrial NPP, while the contributions of other environmental factors are relatively small. The most notable increases in NPP locate in southeast China, central Africa, southeast U.S. and western Amazonia. The spatial pattern of NPP changes are mainly controlled by atmospheric CO2 concentration increase and warming, while precipitation and radiation contribute much fewer. The effects of increasing atmospheric CO2 concentration on NPP are stronger at lower latitudes but weaker at northern high latitudes. Warming benefits ecosystem NPP at northern high latitudes and Tibetan Plateau but strongly depletes ecosystem NPP at lower latitudes. Our analyses of global terrestrial ecosystem NPP changes under future global warming scenarios still have significant uncertainties due to limitations of current RCPs and earth system models, which needs further refinements.
From the perspective of model coupling, this paper introduces the research progress of the current damage function of integrated assessment model (IAM). It mainly analyzes the coupling function and existing scientific problems of the damage function from the point of view of the construction method of the damage function, the coupling of the damage function with the climate model and the economic model, and the coupling IAM with climate model, then discusses its improvement direction. On the construction method of the damage function, it mainly adopts the expert judgement, meta-analysis and statistical methods. However, each of them has both advantages and disadvantages. While coupling with the climate model, most of damage functions only contain the temperature rise as the climate change factor, which can’t express the precipitation and other climate change information. And it is calibrated by the annual average temperature at the global scale, which can’t reflect the regional differences and the seasonal changes and can’t directly describe the huge damage caused by extreme climate events. On the coupling with the economic model, the damage function based on the production sectors are lacking in the assessment function of indirect damages and the dynamic influence mechanism of economic growth. In view of above shortcomings of feedback mechanism of the economic impacts of climate change in IAM, the damage function mainly needs to be reconstructed from two directions, namely, the refinement of regional climate change factors and the subdivision of the economic sectors. Thus, it can closely link the climate module with economic module and comprehensively assess the economic damages from climate change. In addition, it is necessary to solve the problem of spatial and temporal scale mismatching in the coupling economic model and climate model to finally provide an important solution for the coupling of IAM model with the climate model and even the earth system model.
Based on national demographic and economic census and annual statistical yearbooks, this paper focused on the projection of national and provincial economy in China during 2020-2100, using Cobb-Douglas model under the five shared socioeconomic pathways (SSPs). The results show that: (1) national economy will keep rising up to 2070-2080 and then decline under sustainability (SSP1) and inequality (SSP4), while GDP will continue to grow under middle of the road (SSP2) and fossil-fueled development (SSP5) and stagnate after 2040 under regional rivalry (SSP3). (2) GDP can maintain about 6.0% growth rate before 2020s under all SSPs, but will slow down to less than 5.0% afterwards and may stagnate or even show negative growth. (3) The social and economic development policies have direct impacts on the provincial economic growth. GDP at the Jiangsu, Guangdong and Shandong provinces ranks in the top three under SSP1~SSP5 in 2020s. In 2090s, provinces ranks in the top three keep consistent with 2020s under SSP1 and SSP5, but Zhejiang will rank the second under SSP2, Henan enters the top three under SSP3, and the top three provinces will be changed as Guangdong, Jiangsu and Zhejiang under SSP4. (4) As for growth rate of GDP, Shandong and Zhejiang can stay above 6.0% under SSP1, SSP2 and SSP5 in 2020s, only Guangdong and Zhejiang provinces can maintain about 5.0% and some provinces might show negative growth under SSP3 and SSP4. In 2090s, all provincial GDP growth rate will be less than 1.0%.
Freezing-thawing process is an important factor controlling carbon dynamics in mid-high latitude regions. Recently, there has been a growing interest in the effects of freezing-thawing cycle (FTC) on soil carbon stability and associated bio-geochemical process in mid-high latitude regions under global warming. The effects of FTC on soil organic carbon mineralization in peatland of permafrost region are still unclear. In this study, we collected soil samples from active layer (0-15 cm and 15-30 cm) of an undisturbed permafrost peatland in the Great Hinggan Mountains, Northeast China, and then subjected them to FTC simulation and mineralization incubation experiments. Our goal was to characterize soil mineralization in peatland by FTC and to determine the corresponding influencing factors. The results showed that cumulative organic carbon mineralization including CO2 and CH4 ranged from 483 mg/kg to 2836 mg/kg. FTC significantly decreased peatland soil organic carbon mineralization in 0-15 cm and 15-30 cm layers, especially for the 15-30 cm soil layer that the decrease magnitude reached up to 76%. Notably, FTC obviously promoted CH4 emission, and the emission in 15-30 cm soil layer increased by up to 145%. Meanwhile, FTC significantly increased soil dissolved organic carbon (DOC) concentration, but reduced microbial biomass carbon (MBC) concentration and amylase, cellulase and sucrase activities. Lower enzyme activities and relatively inferior quality carbon were the reasons for the decreased soil organic mineralization in FTC treatment. Under global warming, compared with the effect of only temperature increase, FTC can decrease the soil organic carbon mineralization during the short incubation stage in the permafrost peatland of Great Hinggan Mountains.
Global climate change increases the possibility of disputes in international rivers. Avoiding such problems and effectively navigating the threats imposed by climate change will require substantial adaption measures and broader cooperation among the riparian countries in international river basins, while pursuing sustainable development. This paper reviews progress of studies in this field, and finds that the key factor of adaptive management is to establish a set of procedures for scientific assessment. Therefore, an adaptation assessment and management framework applied to impacts of climate change is developed. It includes qualitative description and analysis of the international river basins, semi-quantitative analyses of the potential impacts of future climate change and adaptive capacity across the basins, quantitative analysis of cost-benefit and assessment of adaptation options. This paper provides an effective framework tool and methodology for proposing more targeted adaption measures to combat climate change in international river basins.
This paper analyzes the essence of the deep uncertainties and its characteristic, which consists of scenario uncertainty, consequence uncertainty and alternative uncertainty, and points out the traditional “predict-then-act” risk assessment theories depends on the result of climate prediction leading to its incapable of dealing with deep uncertainties and providing robust decision. The theoretical basis of robust decision and three widely applied methods: Robust Decision Making, Info-Gap Decision Theory and Dynamic Adaptative Policy Pathway are introduced. The paper concludes that the Robust Decision Making embraces a full consideration of adaptation measures while is hard to understand with huge computation; Info-gap Decision Theory addresses on uncertainties which cannot be conveyed in probability but gives less consideration on the scenarios that the adaptation measures failed to meet the target; and Dynamic Adaptive Policy Pathway provides visualized solutions of adaptation pathway but with less consideration on social-economic uncertainties. As a result, the paper proposes a new idea of integrating the Robust Decision Making with Adaptation Pathway, which is able to deliver visualized solutions pathway to support the future decision making.
As one of the components of IPCC new research cycle, refinements to existing IPCC 2006 Guidelines for national GHG inventory has been initiated formally. The outcomes which would be used in conjunction with IPCC 2006 Guidelines, will be approved and published in 2019, facilitating the implantations of Paris Agreement which is applicable to all. There are three types of refinements, update, elaboration or new guidance, covering all volumes, namely, General part, Energy activities, Industrial process, AFOLU and Waste. Twelve experts from China are involved in. Recommend Chinese researchers publish the relevant research outs in qualified journals in English as soon as possible in order to improve the quotation rate of China’ research. Since China has own the capacity to follow the latest guidelines, this paper also recommends the national inventory team shift to IPCC 2006 Guidelines and its refinements completely in future GHG inventory compiling.
In this paper, the LMDI decomposition method is used to analyze the CO2 emission in the production sector in China during 2000-2014, and the CO2 projection model is established by combining the STIRPAT model to analyze the possible CO2 emission of China during 2017-2030. The results show that economic growth and energy intensity are the two most important factors influencing the change of CO2 emission in China. The contribution rates are 114.9% and -22.6%. Three routes are set, which are normal route, emission reduction route and radicals route, a total of 9 scenarios. Low carbon scenario of normal route and benchmark scenario of emission reduction route could achieve CO2 emissions peak in 2025, and low carbon scenario of emission reduction route could achieve peak emissions by 2020.