社会经济排放情景的降尺度与变尺度研究

发布时间：2018-01-21 00:25

本文关键词： 气候变化降尺度变尺度社会经济情景　出处：《清华大学》2013年硕士论文　论文类型：学位论文

【摘要】：气候变化是人类社会面临的全球性挑战。大气中CO_2以及其他温室气体的累积排放是导致全球变暖或其他显著的气候、生态和社会变化的主要原因，进而对人类的生产生活产生极大的影响。因此，对未来不同情景下的社会、经济、排放等数据进行预估，是进一步比较、研究的基础，也是各国做出减排承诺及推行减缓、适应政策的重要依据。目前，已有部分社会经济排放情景对未来的发展趋势进行了预估，但这些情景提供的数据集中于全球范围的区域尺度，而各国的数据支持和政策分析需要更为精细的国家尺度的数据。进一步地，由于经济、环境等指标与地理要素之间存在着极为紧密的关系，因此地理网格尺度数据的获得也变得尤为重要。为解决情景提供的区域尺度的数据与所需要的国家或者网格尺度的数据间存在的差距，本文介绍、运用及改进两种降尺度算法及一种变尺度算法得到更为精细级别的数据，以供具体的政策分析参考。本文运用降尺度方法将情景提供的区域数据降解至国家尺度，得到了世界184个国家和地区2005年至2100年的人口、GDP以及化石燃料燃烧所产生的CO_2排放数据；运用变尺度方法将我国2005年至2100年的国家级、省级、市级的人口、GDP和排放数据降解至1093个网格尺度（1°经度1°纬度，大约100km100km），得到各地理网格的具体信息。本文运用所得到的国家尺度或网格尺度的数据，结合部分缔约方提供的减排承诺，对相应的承诺进行具体分析。针对降尺度得到的国家级别的数据，，将国家和地区的数据进行比较，并主要从公平性及温升两个方面将照常情景及承诺情景下的排放路径进行对比分析。针对变尺度得到的网格级别的数据，将网格数据的分布及变化进行地图化展示，并与我国国家气候中心提供的网格级别的温度、降水信息相结合，分析网格变量之间的关系。本文证明了降尺度及变尺度方法的可行性和可靠性；所得到的结果可作为重要的基础数据供后续的研究使用；同时，本文从多角度对具体数据进行了比较和分析，为进一步的政策制定提供了参考。
[Abstract]:Climate change is a global challenge for human society. The cumulative emissions of CO_2 and other greenhouse gases in the atmosphere are the main causes of global warming or other significant climate, ecological and social changes. Therefore, the prediction of social, economic and emission data under different scenarios in the future is the basis for further comparison and research. It is also an important basis for countries to make emission reduction commitments and implement mitigation and adaptation policies. At present, some social and economic emission scenarios have predicted the future development trend. However, the data provided by these scenarios focus on a global regional scale, while data support and policy analysis by countries require more sophisticated data on a national scale. Further, because of the economy. There is a close relationship between environment and geographical elements, so the acquisition of geographic grid scale data becomes more and more important. This paper describes the gap between the regional scale data provided by the scenario and the country or grid scale data needed. Two downscaling algorithms and a variable scale algorithm are used to obtain more refined data. For the reference of specific policy analysis, this paper uses the downscale method to degrade the regional data provided by the scenario to the national scale, and obtains the population of 184 countries and regions in the world from 2005 to 2100. GDP and CO_2 emissions from fossil fuel combustion; The national, provincial and municipal population GDP and emission data of China from 2005 to 2100 were degraded to 1 掳longitude and 1 掳latitude on 1093 grid scales by using the variable scale method. About 100 km 100 km, get the specific information of grid. This paper uses the data obtained at the national scale or grid scale, combined with the emission reduction commitments provided by some parties, to make a specific analysis of the corresponding commitments. The data of countries and regions are compared, and the emission paths under the same scenario and commitment scenario are compared and analyzed mainly from the aspects of fairness and temperature rise. The distribution and variation of grid data are shown on a map, and the relationship between grid variables is analyzed by combining the grid level temperature and precipitation information provided by the National Climate Center of China. The feasibility and reliability of the downscaling and variable scale methods are proved in this paper. The results obtained can be used as important basic data for subsequent studies; At the same time, this paper compares and analyzes the specific data from various angles, which provides a reference for further policy making.
【学位授予单位】：清华大学
【学位级别】：硕士
【学位授予年份】：2013
【分类号】：X24;F124.5

【共引文献】