The meteorological station routine data, including the phase state of precipitation (rain or snow), surface temperature and surface relative humidity in Beijing and Zhangjiakou, were analyzed in order to investigate the proper conditions for snowmaking, and to evaluate the snowmaking hours. The results show that the precipitation phase state is closely dependent on surface relative humidity as well as surface air temperature, the relations of surface relative humidity to surface air temperature can be obtained at each weather stations by using the regression analysis. If considering to classify the precipitation phase state by temperature only, the snow frequency is above 95% among the stations within Zhangjiakou administrative area when the surface temperature is below-0.8℃, under the calculations of the temperature and occurrence frequency of different phase state of precipitation. The snowmaking hours of 2022 Winter Olympic Games were calculated by using the regional automatic weather station temperature near the field from 2014 to 2016. It’s found that the snowmaking hours is sufficient in Winter Olympic Games period, but insufficient in the Paralympic Games period, so the snowmaking and snow-storing are suggested in order to keep enough snow for the race.

Based on homogeneous precipitation data and GPCC lattice data, the annual precipitation series from 1901 to 2017 that could represent the Zhejiang province was constructed by using the stepwise regression method, and characteristics of the precipitation series were analyzed through the Morlet wavelet analysis and MK method. Results showed that monthly precipitation series of 68 stations in Zhejiang from 1951 to 2017 were homogeneous by using RHtest method, and the fitting equations had nice fitting results for each stations. Combined with the fitted values, incomplete observation precipitation data were preprocessed by using interpolation and extension, annual precipitation series were constructed in Zhejiang province from 1901 to 2017. The characteristic analysis showed that there was no obvious long-term trend of precipitation in Zhejiang province from 1901 to 2017. Wavelet analysis showed that the significant oscillation period of precipitation cycle was about 56 a and 35 a for annual precipitation over Zhejiang from 1901 to 2017. A precipitation catastrophe appeared in 1960 for annual mean from a rainy period to a less rainy period. The climatic tendency of precipitation was distributed high in the northeast and low in the southwest, with a range of -15.6 to 19.1 mm/10a in Zhejiang province from 1901 to 2017. The average relative variation of precipitation was distributed low in the north and high in the south, with a range of 11.1% to 20.2%.

Daily meteorological data during 1966-2015 were used to analyze the spatio-temporal distribution characteristics of relative humidity (RH) in the north and south slopes of the Tianshan Mountains by using Mann-Kendall trend test. In addition, sensitivity coefficient and relative contribution were calculated to assess the impact of temperature, precipitation, reference evapotranspiration, wind speed and sunshine duration on RH. The results revealed that RH in the north slope exhibited fluctuating downward trend, but in the south slope it showed the opposite trend. Furthermore, the RH showed a rising gradient from south to north slope. As for seasonal RH, an upward trend was found in summer, autumn and winter, but a downward trend was observed in spring in the entire Tianshan Mountains. Sensitivity analysis indicated that RH was negatively related to temperature, reference evapotranspiration, wind speed and sunshine duration, but positively related to precipitation. Moreover, RH was the most sensitive to sunshine duration, reference evapotranspiration and wind speed, but precipitation was most insensitive, whether in north or south slope. Spatially, the high value area of sensitivity coefficient of precipitation was located in the Ili Valley, while others were located in the south slope. Contribution analysis suggested that the impact of reference evapotranspiration on RH was much larger than other factors. The high contribution area of sunshine duration was distributed in the Ili Valley (north slope), but that of wind speed, precipitation and temperature in Kizilsu (south slope).

In this study, 1.5℃ warming and 2.0℃ warming scenarios were determined by four sets of data from CMIP5 models including IPSL-CM5A-LR (RCP2.6), GFDL-ESM2M (RCP4.5 and RCP6.0), NorESM1-M (RCP4.5). Simulations of wheat grain yield were performed using the DSSAT v4.5 crop model. Results show that: (1) The air temperature within the wheat growing season would increase 1.17℃ and 1.81℃ above the pre-industrial levels, respectively, at the global warming of 1.5℃and 2.0℃. The warming degree of spring wheat areas in China is higher than that of winter wheat areas. Among the spring wheat areas, the Xinjiang Spring Wheat Area has the largest temperature rise, and the Northwest Spring Wheat Area the smallest. Regarding of winter wheat areas, the maximum and the minimum temperature variation are Southwest Winter Wheat Area and Huang-Huai Winter Wheat Area, respectively. (2) Precipitation in China’s wheat growing season increases by 9.1% and 11.3%, respectively, at the global warming of 1.5℃and 2.0℃, relative to the historical period (1986-2005). The increase of precipitation in spring wheat areas is slightly larger than that of the winter wheat areas. The precipitation in the Xinjiang Spring Wheat Area is lower than that in the historical period. The largest increase of precipitation in spring wheat areas is the Northern Spring Wheat Area. In the winter wheat areas, the Northern and the Huang-Huai Winter Wheat Area shows a larger increase of rainfall, while the precipitation of South China Winter Wheat Area and the Southwest Winter Wheat Area increases slightly. (3) With 1.5℃and 2.0℃warming scenarios, wheat production in China is estimated to reduce by 5.2% and 4.6%, respectively, relative to the historical period (1986-2005). The difference between the two warming scenarios is not significant. With global warming, China’s spring wheat yield mainly shows an increase trend, and the winter wheat yield mainly shows a decrease trend. The largest yield decrease occur’s in the South China Winter Wheat Area and Qinghai-Tibet Spring Wheat Area. The largest yield increase occur’s in the Northwest Spring Wheat Area. The ratio of yield reduction area shows a trend of decreasing first and then increasing from north to south. The South China Winter Wheat Area has the maximum ratio, while the Northern Winter Wheat Area the minimum ratio.

Based on five global climate model data recommended by The Inter-Sectoral Impact Model Inter-comparison Project (ISI-MIP) and Soil and Water Integrated Model (SWIM), the changes of river discharge under global warming of 1.5℃ and 2.0℃ in main stream of upper reaches of the Huaihe River were analyzed. The research results show as follows: the interannual variation of the runoff in the upper reaches of the Huaihe River decreased first and then increased under global warming of 1.5℃ and 2.0℃. The annual runoff at the global warming of 1.5℃ will increase by 9.5% relative to the reference period (1986-2005), while the increase under global warming of 2.0℃ is even more pronounced, reaching 17%. Secondly runoff in four seasons has an increase compared to the reference period under global warming of 1.5℃ and 2.0℃, and the spring runoff rises the most, reaching 24.4%, and the summer, autumn, and winter gains are 7.1%, 16.1%, and 13.5%, respectively. Under global warming of 2.0℃, the rate of increase of runoff in mainstream of the upper reaches of the Huaihe River in the four seasons is larger than under the global warming of 1.5℃. Finally, the maximum daily runoff of different global climate models differs greatly from each other while the average difference is small. Under global warming of 1.5℃ and 2.0℃, the number of days with daily flow exceeding the design flow of the Wangjiaba sluice, increases compared with the reference period, especially under global warming of 2.0℃, which is 22 times more than the reference period and 5.8 times more than under global warming of 1.5℃.

The rapid development of new energy not only reduces human’s reliance on traditional fossil energy, but also makes a significant contribution to mitigating global warming. With the growing installed capacity of photovoltaic (PV) power, people pay more and more attention on influences of PV power stations on climate and environment. To solve this problem, scholars at home and abroad began to do research on this field in 2000. This paper depends on the large amount of research results, summarizes the research methods, mechanism of influences and the influences of PV power stations on climate. The researches show that, PV power stations will produce PV heat island effect in desert areas, which causes a rise of local surface air temperature, while they could reduce the energy consumption in urban areas and reduce the urban heat island effect. Besides, PV power stations also have influences on albedo and the land surface balance, which has effects on local and even global climate, the scope and extent of the impacts have not been accurately concluded, and still need more researches.

In the last decade, several satellites have been launched for monitoring the carbon dioxide in the atmosphere. The validation of the satellite CO₂ products can evaluate the product accuracy, find the scope and limitations of application of the algorithm, which plays an important role in improving the quality of the satellite products. To better understand the research status, a review about the research methods of remote sensing of atmospheric CO₂ and the validation progress between satellite products and ground-based station was carried out, and the future development of the research field was also prospected in this paper.

The gap of energy-related-CO₂ emission pathways between the Nationally Determined Contributions (NDCs) submitted to United Nations Framework Convention on Climate Change (UNFCCC) and realizing the target of limiting temperature rise below 2℃ was researched based on an integrated assessment modal of climate change—Global Change Assessment Model (GCAM-TU). Results show that the NDCs are not enough to realize the target. Each country or party should enhance its NDC after 2030. The analyses of carbon intensity reduction, abatement costs, and carbon emission per capita of the main countries and parties demonstrate the great efforts and contributions of China in the process of global emission reduction. On the contrary, the commitments of regions like South Africa and Japan seem insufficient. To meet the commitment, the final energy consumption of China would reduce compared with the reference scenario, and the energy structure would have a further optimization.

After the Paris Agreement were signed, (I)NDCs ((intended) nationally determined contributions) become the important materials to obtain the information on climate financial needs for developing countries. The climate financial demands requested from developing countries keep increasing, while the financial supports from developed countries are imbalance and insufficiency, which has become the major contradiction of the climate financial issue. In this study, 151 (I)NDCs were analyzed to predict the future climate financial demand by developing countries. Out of the 151 developing countries, 84 countries have put forward specific amount of financial requests, whose total financial demands in the timeframe add up to US$4.4 trillion. According to the analysis of 48 countries which posed financial demand for mitigation and adaptation at the same time, the ratio of mitigation financial demand and adaptation financial demand is 6?4; and the analysis of 21 countries which posed financial demand from domestic and international at the same time, shows that the ratio between the two financial support origins is 3?7. By 2030, the cumulative emission reductions of developing countries will amount to approximately 119 Gt CO₂-eq, the average abatement cost estimated from the (I)NDCs is US$50/t CO₂-eq, which is much higher than the reasonable abatement cost estimated based on other research results. The demand for financial need of developing countries is expected to be US$1 trillion-4 trillion, averaging US$70 billion-260 billion per year, of which international financial demand is US$0.7 trillion-2.8 trillion, averaging US$50 billion-190 billion per year.

IPCC’s Fifth Assessment Report has further elaborated and clarified that the global mean temperature increase is nearly linearly proportional to the total cumulative carbon (CO₂) emissions. Despite the scientific uncertainties, the international community has reached certain scientific and political consensus on limiting the global mean temperature increase to below 2℃ relative to the pre-industrial level and the global cumulative carbon emissions (the carbon budget) compatible with this target. But how to incorporate the goal of carbon budget into policy decisions and practical actions is still a significant issue facing the policy makers. Therefore, the discussion to establish an effective integrated carbon budget management framework aimed at avoiding human-induced greenhouse gas emissions that danger the climate system, would be a positive approach in the new model of climate governance to realize the global emission reduction target, and with its scientific and political concepts to enable the policy dialogues and enhance actions.