| 全球气候数据集生成及气候变化应用研究 |
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| 引用本文： | 梁顺林,唐世浩,张杰,徐冰,程洁,程晓,宫鹏,贾坤,江波,李爱农,刘素红,邱红,肖志强,谢先红,杨军,杨俊刚,姚云军,于贵瑞,张晓通,赵祥.全球气候数据集生成及气候变化应用研究[J].遥感学报,2016,20(6):1491-1499. |
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| 作者姓名： | 梁顺林 唐世浩 张杰 徐冰 程洁 程晓 宫鹏 贾坤 江波 李爱农 刘素红 邱红 肖志强 谢先红 杨军 杨俊刚 姚云军 于贵瑞 张晓通 赵祥 |
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| 作者单位： | 遥感科学国家重点实验室, 北京师范大学地理与遥感科学学院, 北京 100875,中国气象局中国遥感卫星辐射测量和定标重点开放实验室 国家卫星气象中心, 北京 100081,国家海洋局第一海洋研究所, 山东 青岛 266061,地球系统数值模拟教育部重点实验室, 清华大学地球系统科学研究中心, 北京 100084,遥感科学国家重点实验室, 北京师范大学地理与遥感科学学院, 北京 100875,遥感科学国家重点实验室, 北京师范大学全球变化与地球系统科学学院, 北京 100875,地球系统数值模拟教育部重点实验室, 清华大学地球系统科学研究中心, 北京 100084,遥感科学国家重点实验室, 北京师范大学地理与遥感科学学院, 北京 100875,遥感科学国家重点实验室, 北京师范大学地理与遥感科学学院, 北京 100875,中国科学院水利部成都山地灾害与环境研究所, 四川 成都 610041,遥感科学国家重点实验室, 北京师范大学地理与遥感科学学院, 北京 100875,中国气象局中国遥感卫星辐射测量和定标重点开放实验室 国家卫星气象中心, 北京 100081,遥感科学国家重点实验室, 北京师范大学地理与遥感科学学院, 北京 100875,遥感科学国家重点实验室, 北京师范大学地理与遥感科学学院, 北京 100875,地球系统数值模拟教育部重点实验室, 清华大学地球系统科学研究中心, 北京 100084,国家海洋局第一海洋研究所, 山东 青岛 266061,遥感科学国家重点实验室, 北京师范大学地理与遥感科学学院, 北京 100875,中国科学院地理科学与资源研究所, 北京 100101,遥感科学国家重点实验室, 北京师范大学地理与遥感科学学院, 北京 100875,遥感科学国家重点实验室, 北京师范大学地理与遥感科学学院, 北京 100875 |
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| 基金项目： | 国家重点研发计划项目（编号：2016YFA0600100） |
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| 摘 要： | 科技部在"十三五"期间部署的国家重点研发计划"全球变化及应对"专项资助了"全球气候数据集生成及气候变化关键过程和要素监测"研究项目。项目围绕由全球气候观测系统提出的基本气候变量,完善地空天基观测体系,生成中国首套以遥感数据为主体的涵盖大气、海洋和陆表长时间序列、高精度、高时空一致性的产品,即气候数据集,动态监测全球变化关键过程和要素。
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| 关 键 词： | 定量遥感 气候数据集 气候变化 |
| 收稿时间： | 2016/9/20 0:00:00 |
| 修稿时间： | 2016/9/25 0:00:00 |
Production of the global climate data records and applications to climate change studies |
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| Liang Shunlin,TANG Shihao,ZHANG Jie,XU Bing,CHENG Jie,CHENG Xiao,GONG Peng,JIA Kun,JIANG Bo,LI Ainong,LIU Suhong,QIU Hong,XIAO Zhiqiang,XIE Xianhong,YANG Jun,YANG Jungang,YAO Yunjun,YU Guirui,ZHANG Xiaotong and ZHAO Xiang.Production of the global climate data records and applications to climate change studies[J].Journal of Remote Sensing,2016,20(6):1491-1499. |
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| Authors: | Liang Shunlin TANG Shihao ZHANG Jie XU Bing CHENG Jie CHENG Xiao GONG Peng JIA Kun JIANG Bo LI Ainong LIU Suhong QIU Hong XIAO Zhiqiang XIE Xianhong YANG Jun YANG Jungang YAO Yunjun YU Guirui ZHANG Xiaotong and ZHAO Xiang |
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| Institution: | State Key Laboratory of Remote Sensing Science, School of Geography, Beijing Normal University, Beijing 100875, China,Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites, National Satellite Meteorological Center, CMA, Beijing 100081, China,First Institute of Oceanography, SOA, Qingdao 266061, China,Ministry of Education Key Laboratory for Earth System Modeling, Center for Earth System Science, Tsinghua University, Beijing 100084, China,State Key Laboratory of Remote Sensing Science, School of Geography, Beijing Normal University, Beijing 100875, China,College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China,Ministry of Education Key Laboratory for Earth System Modeling, Center for Earth System Science, Tsinghua University, Beijing 100084, China,State Key Laboratory of Remote Sensing Science, School of Geography, Beijing Normal University, Beijing 100875, China,State Key Laboratory of Remote Sensing Science, School of Geography, Beijing Normal University, Beijing 100875, China,Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, China,State Key Laboratory of Remote Sensing Science, School of Geography, Beijing Normal University, Beijing 100875, China,Key Laboratory of Radiometric Calibration and Validation for Environmental Satellites, National Satellite Meteorological Center, CMA, Beijing 100081, China,State Key Laboratory of Remote Sensing Science, School of Geography, Beijing Normal University, Beijing 100875, China,State Key Laboratory of Remote Sensing Science, School of Geography, Beijing Normal University, Beijing 100875, China,Ministry of Education Key Laboratory for Earth System Modeling, Center for Earth System Science, Tsinghua University, Beijing 100084, China,First Institute of Oceanography, SOA, Qingdao 266061, China,State Key Laboratory of Remote Sensing Science, School of Geography, Beijing Normal University, Beijing 100875, China,Key Laboratory of Ecosystem Network Observation and Modeling, Synthesis Research Center of Chinese Ecosystem Research Network, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China,State Key Laboratory of Remote Sensing Science, School of Geography, Beijing Normal University, Beijing 100875, China and State Key Laboratory of Remote Sensing Science, School of Geography, Beijing Normal University, Beijing 100875, China |
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| Abstract: | The research project entitled, "Generation of global climate data records and their use for monitoring the key variables and processes of climate change," was recently funded by the Chinese Ministry of Science and Technology under the Global Changes and Responses Program. This project focuses on the essential climate variables proposed by the global climate observing system. It aims to improve surface-air-space observing systems; produce long-term, highly accurate, and highly spatiotemporal consistent satellite products (i.e., climate data records, CDRs) of the atmosphere, ocean, and land surfaces; and monitor the key variables and processes of climate change dynamically. This project will produce the first CDR suite in China. This research project is divided into four. The first three sub-projects focus on the satellite product generation of the atmosphere, ocean, and land surfaces. Each of these three sub-project includes ground observation, inversion and fusion methods of remote sensing data, and production and application demonstration of climate dataset. Ground observation is mainly used for algorithm development, product validation, and application demonstration. Sub-project 4 will comprehensively assess these satellite products and use them for climate change studies. Sub-project 1 on the atmosphere will mainly focus on the variables that are essential for climate change studies, such as aerosol optical thickness, cloudiness, precipitation, CO2, ozone, solar incident radiation, reflected solar radiation, outgoing long wave radiation, and energy imbalance. Nine CDRs will be generated at the end. The application demonstration will be based on the long-term atmospheric climate dataset; it will be combined with foreign satellite-related products to study the global climate effects of aerosol, dynamic monitoring of polar ozone concentrations, energy balance of the Earth, and other applications. Sub-project 2 on the ocean will mainly focus on methods and techniques for producing a total of 21 products, including the balance components of ocean energy (i.e., shortwave incident solar radiation, shortwave broadband albedo, longwave downward radiation, emissivity, and net radiation), dynamic environmental parameters and processes of the ocean (i.e., sea surface wind, ocean wave, surface flow, sea surface temperature, sea surface salinity, sea surface temperature, and oceanic ice color (reflectance, chlorophyll concentration, particulate organic carbon, and primary productivity)), and sea ice (i.e., concentration, thickness, and drift).At the end, 17 of these will be generated as ocean CDRs. Their applications to the global ocean matter and energy transport will be demonstrated based on the global ocean climate data set for the major estuarine water changes of the world in response to global climate change. Sub-project 3 for land surfaces will mainly focus on 20 variables that characterize the key processes of climate change, including the global energy balance of land surfaces (i.e., shortwave incident radiation, shortwave broadband albedo, longwave downward radiation, land surface emissivity, land surface temperature, and net radiation), water cycle (i.e., evapotranspiration, water surface dynamics, and wetland), carbon cycle (i.e., leaf area index, fractional photo synthetically active radiation absorbed by green vegetation, vegetation coverage, forest biomass, gross primary productivity, net primary productivity, residential area, land cover, and fire burned area), and polar and cryosphere (i.e., elevation and area of ice surfaces, snow cover, snow water equivalent, and freezing and thawing of permafrost). At the end, 15 of these products will be generated as land CDRs. The application demonstration component will include assimilating these data products into land surface process models; analyzing the effect of these products on the diagnostic ability of temporal and spatial characteristics of climate change; and quantifying the scientific values of these products in characterizing regional carbon cycle, water cycle, and energy balance. The atmospheric, oceanic, and terrestrial CDRs will be analyzed in Sub-project 4 by using the key process of global change as the constraint. They will be tested based on their spatiotemporal and logical consistency. Basic global change indicators will be proposed based on the entire process of acquisition and analysis of information data of global change. We will also determine the states and trends of the key processes, evaluate their causes and effects comprehensively, and investigate direct evidence of the roles played by key processes and elements in global climate change. |
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| Keywords: | quantitative remote sensing climate data records climate change |
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