Based on the historical return data of the BCC-CSM seasonal climate prediction model and the monthly data of the surface precipitation in China provided by the National Meteorological Information Center, the factors affecting the forecast results were compared and discussed in this study by multiple methods. The summer precipitation of China in 2014 and 2015 is predicted by using LSTM network. The results show that the prediction ability of the LSTM network is better than that of the stepwise regression, Back Propagation neural network and BCC models. Parameter optimization has a great influence on the prediction effect of LSTM network. The important parameters include the number of hidden layer nodes, training times and learning rate. Selecting suitable starting months is helpful to improve the accuracy of seasonal forecast, and the forecast effect of summer precipitation is better by using the data reported from April. The sea ice component factors have made a positive contribution to seasonal precipitation forecast. In the summer precipitation return experiment in 2014 and 2015, the LSTM network has the ability to predict the overall precipitation situation. Ps score are 74 and 71, anomaly sign consistency rates are 55.63% and 55.25%. The average Ps score is higher than the national consultation and business model in the same period.
Based on the daily precipitation data with different RCP scenarios from the five global climate models (GCMs) in the Fifth phase of Coupled Model Intercomparison Project (CMIP5), also as the main models in the Inter-Sector Impact Model Intercomparison Project (ISIMIP), the frequency and intensity of extreme precipitation in the Hanjiang River basin in the period of 2016-2060 were analyzed with the indices maximum consecutive 5-day precipitation (RX5d), percentages of extreme precipitation in the annual total volume (PEP), annual total precipitation when daily precipitation greater than 95th percentile (R95p) and simple daily intensity index (SDII) under different scenarios. GFDL-ESM2M, the best GCM from the five, which is selected through the test of the simulation performance with the meteorological station data in the historical period of 1961-2005, was used to interpret the projection results. At the same time the other GCMs were also taken in the projection in order to show the uncertainty. The results are as follows. Under RCP4.5 scenario the extreme precipitation indices increase the most, in detail R95p, PEP and RX5day increase by 12.5%, 3.2 percentage points and 8.2% respectively, relative to the reference period of 1961-2005. SDII increases very slightly. PEP increases in all three RCP scenarios, especially more in the northwest and southeast of the basin area; R95p shows a certain amount of increase in the most basin area, while the southeastern and northern parts have more increase; RX5d increases under RCP2.6 and RCP4.5 scenarios, but it decreases under RCP8.5 scenario in general. As to the uncertainty of these four indices, SDII is the lowest, while RX5d is the highest. The regions with relatively higher projection uncertainty are mainly in the eastern, southeastern and northwestern parts of the basin.
In order to explore the applicability potential for China’s reanalyzed meteorological dataset CN05.1 in watershed hydrological modeling, the SWAT hydrological model was driven by CN05.1 dataset and traditional meteorological station data, respectively, by taking the Kaidu River basin the as research area in this paper. The comparison between the two simulation results was carried out by using evaluation factors such as coefficient of determination (R 2), Nash efficiency coefficient (NSE) and relative error (Re). Finally, two precipitation data correction methods were used to correct the CN05.1 precipitation data and the hydrological simulation results were evaluated. The results are as follows. (1) CN05.1 meteorological data has certain applicability in the hydrometeorological simulation of the Kaidu River basin. (2) Hydrological simulation based on SWAT model shows that CN05.1 data-driven hydrological simulation accuracy is higher than traditional meteorological station data, and the R 2 over the period of calibration (1995-2005) and verification period (2006-2016) is 0.81 and 0.73, NSE is 0.81 and 0.72, and Re is -0.97% and 0.39%, respectively. (3) The two kinds of correction data can both simulate the process of runoff change well, but runoff simulation based on spatial relationship correction method shows better effect, and the R 2 and NSE are above 0.72, |Re| is less than 1.7%. Therefore, the corrected CN05.1 precipitation data can compensate for the lack of data in the traditional meteorological station and the unsatisfactory peak value of the CN05.1 meteorological data in the runoff simulation to a certain extent.
It is of great scientific significance to study the relationship between urban surface cover and land surface temperature (LST) for improving urban ecological environment. Based on the Landsat TM data, this paper uses the linear spectral hybrid analysis model to extract the impervious surface land information. Combined with the LST and surface heat flux, the spatial-temporal variation characteristics and inter relationships of the impervious surface area (ISA) and the LST are analyzed. The results show that the ISA of Beijing increased rapidly from 1984 to 2014. The medium coverage of ISA decreased, while high coverage increased remarkably. The LST decreased from the city center to the suburbs, and the high temperature area was expanding continuously. There was a significant positive correlation between the LST and ISA, and the rate of the LST rise was the fastest when ISA was at 0.6-0.9. So reducing ISA can alleviate the phenomenon of high temperature area concentration.
Based on the methods of linear regression, M-K and Pearson correlation analysis, the characteristics of the runoff change in the source region of Lancang River during 1960-2010 and its main influencing factors of temperature and precipitation were analyzed. Results show that there is a significant increasing trend of temperature in the source region of Lancang River and the winter temperature rise does the largest contribution (38%) to the annual increasing of temperature. The annual precipitation does not change significantly although there is a remarkable increasing trend of spring precipitation. The annual runoff in the study area exhibits no significant trend. However, both winter and spring runoff increase significantly. Correlation analysis shows that precipitation is the main controlling factor for the annual runoff. Monthly runoff change is also dominated by precipitation during the period with plentiful rainfall from June to October. However, the temperature has an important influence on runoff change during early spring and winter, which is attributed to the increasing temperature causing the accelerated melting of ice and snow. The quantitative analysis indicates that temperature has a larger contribution rate to runoff change than that of precipitation within early spring and winter.
Based on daily and hourly monitoring data of meteorological elements in the region of the Siming Mountains in Ningbo city, its climatic conditions were analyzed, and its ecoclimatic advantages were evaluated using comfort index of human body. The results indicate that from 1961 to 2017, the temperature in the region has continued to rise, the precipitation has increased, the daily peak of which has been concentrating at 16-18 o’clock without any significant change, the number of small wind days has grown, and the number of climatically comfortable days has increased considerably. Besides, the results also show that temperature is the main contributor to human comfort in the Siming Mountains, followed by relative humidity and wind velocity. In spring and autumn, there is a large number of comfortable days, with warm climate and the characteristic of sunny day and rainy night; in cool summer, it is an ideal summer resort. The annual comfort hour in the high altitude area is similar to that in the plain area, but the seasonal differences are obvious. The high altitude area is more comfortable in the summer, while the plain area is better in the rest of the year. In addition, according to the results of regional climate models, the temperature in the Siming Mountains tends to continue to increase, as well as the precipitation and the number of extreme high temperature events, while the number of extreme low temperature events is prone to decrease, combined with declined climatically comfortable days and significantly less of that in the summer but more of that in spring and autumn.
In the assessment of the impact of climate change on the hydrology and water resources by using hydrological models, it is generally assumed that the parameters of hydrological models are stationary through the historical and future periods without distinguishing the differences of the parameters of hydrological models under the influence of environmental changes. To solve this problem, Set Pair Analysis (SPA) method was used to partition wet, medium and dry years based on annual total precipitation and annual average runoff. The parameters of SWAT distributed hydrological model for different years of recurrence interval were calibrated by to explore the influence of parameters instationarity on the intra-annual and inter-annual distribution patterns of runoff. The results showed that when the times series were respectively classified into wet, medium and dry years by annual total precipitation and annual average runoff, 70% of the 50 years were of the same type (wet or dry). If only the data of an individual certain type (wet, medium and dry) are selected for calibration, the simulation accuracy will be lower than that of the overall consideration of wet, medium and dry years, mainly due to the simulated runoff is overestimated. When the same hydrological data and model parameters under different environmental conditions are used to derive the runoff process, from the perspective of inter-annual variation, the parameters of a specific type (wet, medium and dry) are used to generally generate the wetter results, which increases the proportion of wet years and decreases the proportion of dry years. While from the perspective of intra-annual variation, influenced by the parameters of different types, the concentration of runoff decreases which means the distribution tends to be more uniform, and the runoff concentration period is delayed. The results can provide reference for improving the reliability of hydrological simulation under changing environment in the future and are of great significance for the adaptive management of water resources under changing environment.
Nature-based Solutions (NbS), put forward in recent ten years but well aware more recently, is a cost-effective approach to address environmental and social-economic challenges human being is facing. With respective to climate change, NbS is a set of approaches for conservation, restoration and sustainable management of ecosystems to mitigate climate change, and to address impacts and challenges induced by climate changes on human beings and wildlife through services provided by ecosystems. These ecosystems include forest, cropland, grassland and wetland (coastal ecosystems), either natural or man-made. NbS is able to contribute 30 percent of mitigation targets set by Paris Agreement, and provide substantial environmental and social-economic co-benefits. However, NbS is not well paid attention in previous policies and actions including the Intended National Determinated Contribution (INDC) and funding flow into NbS for climate change is limited. To maximize the NbS potential, it is recommended to conduct researches on China’s NbS mitigation potential and its co-benefits, identify cost-effective priority NbS pathways, summarize domestic and oversea successful NbS cases, develop incentive policies for mainstreaming NbS, and to push for collaborative governance of multiple sectors.
With the launch of China’s national carbon market at the end of 2017, 21 carbon emission trading systems have been put into operation worldwide. With the extensive development of carbon emission trading and the impact of the uncertainty of the product market, the default behavior of emission control firms is also increasingly diversified and complicated. Based on this, according to the prevailing business rules in the pilot areas of China’s carbon markets, this paper analyzes the ways of default behavior of the firms and the influence of supervision intensity on a carbon trading system with a savings mechanism and uncertain demand by introducing stochastic shocks into the product market. When the audit probability is high, the subjects will not generate systematic motivation to default on emissions, and obvious default on report under weak supervision settings will lead to an increase in total emissions. Faced with the impact of uncertainty, the savings mechanism can still promote the pollution sources of controlled emissions enterprises to distribute production in a relatively effective way. Therefore, this study gives the following suggestions: penalties for default should be graded, and penalties for reporting default should be greater than penalties for emission default; in order to improve the actual compliance rate, all localities should increase the proportion of spot checks on emission reports; the quota savings mechanism should be improved.
As China’ economy enters the “new normal”, this paper develops a comprehensive analysis framework and socioeconomic-energy system model that interlinks demographic change and energy system in order to analyze the urbanization process and its relation with China’s long-term CO2 emissions trend. The results show that, toward 2050, around 300 million people are expected to migrate from rural area to urban area with a flow trend of people moving gradually from small and medium city groups to large and super city groups. The population migration trend together with the living standard improvement will promote China’s infrastructure construction, industry production and energy service demand growth. In the Business as Usual (BAU) scenario, in 2050, total primary energy consumption will reach 8.4 Gtce in China, energy related CO2 emissions will grow to 17.6 Gt, which is 83% higher than 2013 level. While in the Low Carbon Transition (LCT) scenario, with technology innovation, total primary energy demand for China in 2050 could be controlled at around 6.1 Gtce, CO2 emissions would peak during 2020-2025 and decline quickly to 78% lower than BAU scenario. In the transition process, non-fossil fuel power generation and energy efficiency technologies have the largest mitigation potentials, and industry and power sectors would peak first before 2020, followed by building and transport sectors which peak around 2030. The total additional capital investment required for low carbon transition would account for 1.5% of GDP, therefore not a huge burden for the whole economy. It is technologically and economically feasible for China to implement new urbanization strategy.
The 25th session of the Conference of the Parties under United Nations Framework on Climate Change Convention has made some progress in part of the key items. However, it failed to reach agreement on the implementation rules of the market mechanism in Article 6 of the Paris Agreement, which is the most concerned issue in COP25 by all Parties. There are four main reasons for the insipid results of COP25. Firstly, it was overemphasized on calling for mitigation ambition enhancement from all Parties, but it failed to focus on the negotiations related to Article 6 of the Paris Agreement. Secondly, the COP president and some Parties were too eager to bring the ambition enhancement issue into the negotiation process, which has not been seen as a political consensus. It destroyed the negotiation atmosphere. Thirdly, various negotiation issues are managed in an unbalanced manner. Fourthly, the developed countries intended to evade their responsibilities under the Convention, which promoted greater solidarity of developing countries and pushed them to the opposite. Regarding the prospective future of global climate multilateral process, the negotiation on Article 6 of the Paris Agreement will continuously to be the crucial mission. The ambition enhancement will also be a key topic of discussion. However, overemphasizing the target of 1.5℃ may lead to the risk of renegotiation on the Paris Agreement. Meanwhile, the intention of developed countries to evade and transfer their responsibilities under the Convention is becoming more obvious. The global climate governance should focus on the ambition of commitment implementation, and in the meantime, advance the implementation of the Convention and its Paris Agreement.
Climate risks may cause tremendous mortality and property losses, and climate insurance is an effective measure to manage climate risks by transferring and spreading them. Firstly, based on the discrimination of the theoretical basis of the fundamental definition and the market mechanism of climate insurance, this study points out and analyzes two main problems of this kind of insurance: the dissatisfaction of Law of Large Numbers, the existence of moral hazards and feedback effects. Secondly, this paper teases out the development of climate insurance in developed countries, which is relatively mature: its function of transferring and spreading risks is relatively strong due to a portion of government subsidies to insurance premium, emergency government loans, reinsurance and insurance derivative instruments. However, it faces problems of adverse selection and moral hazards. Finally, this study analyzes the statuesque in China, finding the problems that the climate insurance products are quite limited and the public willingness to pay is relatively weak, and then proposes suggestions to perfect the climate insurance in China: first, to improve weather station infrastructure, to develop natural disaster risk maps, and to increase public and sensitive industries’ willingness to purchase climate insurance in order to make it meet the Law of Large Numbers; second, to urge insurance companies to consider non-economic cost when designing insurance products to avoid moral hazards and feedback effects in advance; third, to promote climate reinsurance and insurance derivatives at the proper time.
