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全球气候数据集生成及气候变化应用研究简
Production of the global climate data records and applications to climate change studies

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梁顺林 1   唐世浩 2   张杰 3   徐冰 4   程洁 1   程晓 5   宫鹏 4   贾坤 1   江波 1   李爱农 6   刘素红 1   邱红 2   肖志强 1   谢先红 1   杨军 4   杨俊刚 3   姚云军 1   于贵瑞 7   张晓通 1   赵祥 1  
文摘 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。
其他语种文摘 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, CO_2, 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).
来源 遥感学报 ,2016,20(6):1491-1499 【核心库】
DOI 10.11834/jrs.20166359
关键词 定量遥感 ; 气候数据集 ; 气候变化
地址

1. 北京师范大学地理与遥感科学学院, 遥感科学国家重点实验室, 北京, 100875  

2. 国家卫星气象中心, 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, 北京, 100081  

3. 国家海洋局第一海洋研究所, 山东, 青岛, 266061  

4. 清华大学地球系统科学研究中心, 地球系统数值模拟教育部重点实验室, 北京, 100084  

5. 北京师范大学全球变化与地球系统科学学院, 遥感科学国家重点实验室, 北京, 100875  

6. 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  

7. 中国科学院地理科学与资源研究所, 北京, 100101

语种 中文
文献类型 研究性论文
ISSN 1007-4619
学科 测绘学
基金 国家重点研发计划项目
文献收藏号 CSCD:5861296

参考文献 共 16 共1页

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引证文献 5

1 张杰 海洋气候数据集生成与分析简介 海洋科学进展,2019,37(2):325-331
被引 3

2 赵健 集成奇异谱分析和长短期记忆网络的区域海平面变化预测 同济大学学报. 自然科学版,2022,50(10):1508-1516
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