摘要
人-地系统模式双向耦合的运行,存在着人-地数据时空尺度不相匹配的障碍.为使二者相匹配,在空间尺度上,提出通过经济模型将行政单元统计数据转变为网格数据的运行路径,并设计了“面积权重折算法”的数据转换方法,使经济系统的行政单元数据与地球系统模式的网格数据相匹配;在时间尺度上,将选取的不同时间尺度的经济统计数据整合到年际范围,使其与地球系统模式的时间步长尺度相一致.运用该方法分别对中国大陆和世界各国的人口、GDP、CO2排放等进行网格化处理,结果表明其特征与实际分布相一致.新方法结果可信度高,为人-地系统模式的双向耦合提供了可靠的变量运转的基础.
The bidirectional coupled operation of the human-Earth system model is hindered by the spatial and temporal mismatch of the Earth system data and comprehensive economic system data. The Earth system model uses geologically gridded data whereas the economic evaluation model uses national or regional administrative statistical data. In addition, the Earth system model and economic evaluation system model are generally not synchronized because they use different time steps.Thus, the modeling methodologies and operational trajectories are totally different, thereby making it difficult to operate them in a single model. To match the two types of data on spatial scales, we proposed transforming the statistical data collected in administrative units into gridded data by using economic models and the inverse operation to convert the gridded data into administrative data. On temporal scales, we proposed to streamline the selected economic data for various time scales to the same time step used by the Earth system model(e.g., both on a "per year" basis). For the first time, we designed an "area-weighted conversion method", which can be used in a forward direction to convert administrative data into gridded data or in a backward direction to transform gridded data into administrative data, thereby matching the economic data in administrative units with the gridded data in the Earth system model. The practical steps in the areaweighted conversion method are as follows. First, using the Lambert projection, net grids are built with 1°×1° latitude and longitude resolution using the base map for China and the global base map, respectively, thereby yielding 3795 cells for the Chinese mainland and 62640 cells for the globe. Next, in Arc GIS, the net grid is built and the factors are converted into areal units, and then connected to the base map with the economic indices per unit area. Connecting the names of the administrative entities is a crucial step. Using the union operation in the analysis tools, the established net grid cuts the base map into irregular shapes. The exported table of properties contains the areas of the irregular shapes and economic indices per unit area. Finally, after applying the weights to the data mentioned above, the map is reconnected to the Arc GIS net grid. Using the forward and backward methods, we connected the data in the Earth system model and economic evaluation model, and operated them in a coupled manner. Our study was based on data for 2010–2018 obtained from the China National Bureau of Statistics and the United Nations’ databases. We applied the proposed method to data for the Chinese mainland and other countries, such as populations, GDP, and CO2 emissions, with a 1°×1° grid spatial scale and statistical data at various temporal scales were converted into a per year basis. The simulation and test results were satisfactory. The distributions of various indices and characteristics were consistent with reality, thereby indicating that the proposed method is capable of providing a reliable basis for the bidirectional coupled variable operation of the human-Earth system model.Our future research will involve feeding the spatial-temporal matched data converted using our method into the humanEarth system model to conduct simulations, analyzing the result and impacts, and further improving the spatial-temporal resolution and real-time capability.
作者
丑洁明
董文杰
王淑瑜
涂钢
胡川叶
Jieming Chou;Wenjie Dong;Shuyu Wang;Gang Tu;Chuanye Hu(State Key Laboratory of Earth Surface Processes and Resource Ecology,Beijing Normal University,Beijing 100875,China;School of Atmospheric Sciences,Sun Yat-sen University,Guangzhou 519082,China;School of Atmospheric Sciences,Nanjing University,Nanjing 210043,China;Institute of Meteorological Science of Jilin Province,Jilin Province Key Laboratory for Changbai Mountain Meteorology and Climate Change,Laboratory of Research for Middle-High Latitude Circulation System and East Asian Monsoon,Changchun 130062,China;National Climate Center,China Meteorological Administration,Beijing 100081,China)
出处
《科学通报》
EI
CAS
CSCD
北大核心
2021年第4期526-532,共7页
Chinese Science Bulletin
基金
国家重点研发计划(2016YFA0602703,2018YFC1509003)
国家自然科学基金(42075167)资助。
关键词
模型
耦合
气候变化
数据网格化
时空匹配
model,coupling
climate change
data grid
spatiotemporal matching
