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中国北方四类典型下垫面能量分配特征及其环境影响因子研究
引用本文:任雪塬,张强,岳平,杨金虎,闫昕旸.中国北方四类典型下垫面能量分配特征及其环境影响因子研究[J].高原气象,2021,40(1):109-122.
作者姓名:任雪塬  张强  岳平  杨金虎  闫昕旸
作者单位:兰州大学大气科学学院,甘肃兰州 730000;兰州大学大气科学学院,甘肃兰州 730000;中国气象局兰州干旱气象研究所/甘肃省干旱气候变化与减灾重点实验室/中国气象局干旱气候变化与减灾重点实验室,甘肃兰州730020;中国气象局兰州干旱气象研究所/甘肃省干旱气候变化与减灾重点实验室/中国气象局干旱气候变化与减灾重点实验室,甘肃兰州730020
基金项目:国家自然科学基金项目(41630426,91637106,41975016);干旱气象科学研究基金项目(IAM201913)。
摘    要:中国北方疆域辽阔,多种植被类型交错分布,陆面过程较为复杂.研究该区域地表能量平衡及分配过程,有助于进一步了解其生态系统的生产力及气候变化.本文使用"中国北方协同观测实验"观测资料,选取中国北方四种植被类型——高寒草甸、荒漠草地、玉米农田及半干旱草地,在深入认识地表能量分配特征的基础上,讨论了环境因子对能量分配的影响.结...

关 键 词:能量平衡  湍流通量  环境因子  典型下垫面

Study on Energy Partitioning and its Environmental Factors of Four Types of Typical Underlying Surfaces in North China
REN XueYuan,ZHANG Qiang,YUE Ping,YANG Jin,Hu,YAN Xin.Study on Energy Partitioning and its Environmental Factors of Four Types of Typical Underlying Surfaces in North China[J].Plateau Meteorology,2021,40(1):109-122.
Authors:REN XueYuan  ZHANG Qiang  YUE Ping  YANG Jin  Hu  YAN Xin
Institution:(College of Atmospheric Sciences,Lanzhou University,Lanzhou 730000,Gansu,China;Key Laboratory of Arid Climatic Change and Reducing Deserter of Gansu Province,Institute of Arid Meteorology,China Meteorological Administration,Lanzhou 730020,Gansu,China)
Abstract:Surface energy balance and distribution are the result of the interaction of vegetation,climate and other factors. The study of energy,especially the distribution of turbulent flux and its influencing factors,is of vital importance to regional water resources management,and is also of great significance for guiding scientific agricultural production. North China has a vast territory,a variety of vegetation types crisscross distribution,and the land surface process is more complex. Water vapor and precipitation caused by summer monsoon activities will change the underlying surface water,thermal characteristics and solar radiation forcing characteristics,which makes the factors affecting the characteristics of surface energy distribution more complicated. The study of surface energy balance and distribution process in this region is helpful to further understand the productivity and climate change of its ecosystem. Therefore,this paper analyzed the observation data of "Cooperative observation experiment in North China",and finally selects four vegetation types in north China,meadow,desert grassland,corn farmland and semi-arid grassland,which represents the vegetation types in the north of China to a certain extent. Based on a deep understanding of the characteristics of surface energy distribution,the effects of environmental factors on energy distribution are discussed. The results show each component of surface energy on a typical underlying surface presents a unimodal change trend,with obvious diurnal characteristics. Surface energy is uneven on each underlying surface. The energy closure of the above four typical underlying surfaces is 71%-91%,of which the semi-arid grassland is the largest and the corn farmland is the smallest. From the ratio of each energy component to net radiation,the net radiation of desert grassland and semi-arid grassland heats the atmosphere mainly in the form of sensible heat,and the percentage of sensible heat flux to net radiation is 29% and36%,respectively. Alpine meadow and corn farmland latent heat flux is dominant,accounting for 42% and 37%of the net radiation,respectively. Among the meteorological factors affecting the Bowen ratio which is the water and heat comprehensive parameters of each underlying surface,the semi-arid grassland is affected by the groundair temperature difference(R~2= 0.64)and vapor pressure deficit(R~2= 0.56),while the corn farmland is mainly affected by the ground and air temperature difference(R~2= 0.52). The Bowen ratio of the desert grassland is influenced by the ground-air temperature difference(R~2= 0.37)and average wind speed(R~2= 0.23). In addition,there is a significant exponential relationship between Bowen ratio and NDVI,and decreases with the increase of NDVI.
Keywords:Energy balance  turbulent flux  environmental factors  typical underlying surface
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