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高原气象  2019, Vol. 38 Issue (6): 1129-1139    DOI: 10.7522/j.issn.1000-0534.2018.00159
论文     
高分辨率大气强迫和植被功能型数据对青藏高原土壤温度模拟影响
沈润平1, 郭倩1, 陈萍萍1, 李鑫慧2, 王绍武1, 师春香3
1. 南京信息工程大学 地理科学学院, 江苏 南京 210044;
2. 南京信息工程大学 遥感与测绘工程学院, 江苏 南京 210044;
3. 国家气象信息中心, 北京 100081
Impact of High-Resolution Atmospheric Forcing and Plant Functional Types Datasets on Soil Temperature Simulation in the Qinghai-Tibetan Plateau
SHEN Runping1, GUO Qian1, CHEN Pingping1, LI Xinhui2, WANG Shaowu1, SHI Chunxiang3
1. School of Geographical Sciences, Nanjing University of Information Science & Technology, Nanjing 210044, Jiangsu, China;
2. School of Remote Sensing & Geomatics Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, Jiangsu, China;
3. National Meteorological Information Center, China Meteorological Administration, Beijing 100081, China
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摘要: 土壤温度是陆气相互作用以及陆面模式模拟的关键参量,但高分辨率时空连续的土壤温度获取困难,尤其是我国青藏高原地区,融合遥感资料的陆面模式模拟可以获得高时空分辨率的资料。研究制作了新的地表植被功能型融合数据(MVEG),然后利用最新的高时空分辨率的中国气象局陆面数据同化系统HRCLDAS-V1.0(1 km,1 h)驱动CLM模式对青藏高原2015年10 cm的土壤温度开展了模拟研究。结果表明,HRCLDAS-V1.0的大气强迫数据(1 km,1 h)显著降低了模式模拟的误差,MVEG可以改善对极值的模拟,并使土壤温度空间分布较为合理。CLDAS/CLM(6 km,1 h)模拟值整体比观测值偏高1℃左右,HRCLDAS/CLM(1 km,1 h)有所改进,模拟的土壤温度年平均偏差绝对值和均方根误差分别降低0.82和0.18℃。HR-MVEG/CLM(1 km,1 h,同时改进了植被功能型)的模拟值最接近观测值,年平均均方根误差减小0.27℃,且可以体现出土壤温度空间分布的细节特征。
关键词: 青藏高原HRCLDAS/CLM系统土壤温度植被功能型数据    
Abstract: Soil temperature is a key physical quantity in the land-atmosphere interaction, and also an important parameter in the research of land surface model simulation. However, it is very difficult to obtain the spatiotemporal continuous data in high resolution, especially in the Qinghai-Tibetan Plateau of China with high altitude and harsh environment. Land surface model simulation with fusion of remote sensing data sets provides a feasible and effective way to obtain soil temperature information with high spatial and temporal resolution. Meanwhile, atmospheric forcing data and plant functional type's data are both important input data of Community Land Model (CLM), and their quality affects the accuracy and reliability of simulation results. In this paper, a new surface plant functional types data (MVEG) was produced, based on multi-source remote sensing data fusion. And then several simulation experiments were carried out which focused on the simulation study of soil temperature (0~10 cm) on the Tibetan Plateau in 2015. These experiments were all about Community Land Model, but different atmospheric forcing data and plant functional type's data were inputted. The latest High Resolution China Meteorological Administration Land Data Assimilation System Version1.0 (HRCLDAS V1.0, 1 km, 1 h) was used to improve the spatial and temporal resolution of model simulation. And its influence on soil temperature simulation was explored, as well as its synergistic effect with MVEG. The results showed that HRCLDAS-V1.0 atmospheric forcing data (1 km, 1 h) had a great improvement effect, it could significantly reduce the error of model simulation. MVEG could improve the simulation of extremes and at the same time, the spatial distribution of soil temperature turned out to be more reasonable. The simulated value of CLDAS/CLM (6 km, 1 h) was larger than observation overall(about 1℃). In contrast, HRCLDAS/CLM (1 km, 1 h) could improve the simulation results. The absolute value of annual mean bias and RMSE of soil temperature (0~10 cm) in the HRCLDAS/CLM simulation experiment were reduced by 0.82℃, 0.18℃, respectively. The simulated value by HR-MVEG/CLM (1 km, 1 h, improved plant functional types) was the most close to the observed value with the RMSE of HR-MVEG/CLM decreased by 0.27℃. Moreover, HR-MVEG/CLM could reflect the detailed characteristics of soil temperature spatial distribution.
Key words: Qinghai-Tibetan Plateau    HRCLDAS/CLM system    soil temperature    plant functional types data
收稿日期: 2018-10-15 出版日期: 2019-11-25
ZTFLH:  P416.2  
基金资助: 国家自然科学基金重点项目(91437220)
作者简介: 沈润平(1963-),男,江西湖口人,教授,主要从事陆面过程遥感与模拟研究.E-mail:rpshen@nuist.edu.cn
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引用本文:

沈润平, 郭倩, 陈萍萍, 李鑫慧, 王绍武, 师春香. 高分辨率大气强迫和植被功能型数据对青藏高原土壤温度模拟影响[J]. 高原气象, 2019, 38(6): 1129-1139.

SHEN Runping, GUO Qian, CHEN Pingping, LI Xinhui, WANG Shaowu, SHI Chunxiang. Impact of High-Resolution Atmospheric Forcing and Plant Functional Types Datasets on Soil Temperature Simulation in the Qinghai-Tibetan Plateau. Plateau Meteorology, 2019, 38(6): 1129-1139.

链接本文:

http://www.gyqx.ac.cn/CN/10.7522/j.issn.1000-0534.2018.00159        http://www.gyqx.ac.cn/CN/Y2019/V38/I6/1129

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