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Analysis Of Spatiotemporal Variation Of Surface Temperature And Effects Of Afforestation On Surface Temperature

Posted on:2022-01-04Degree:MasterType:Thesis
Country:ChinaCandidate:L P WangFull Text:PDF
GTID:2480306509969919Subject:Physical geography
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Land Surface temperature is an important parameter that characterizes the physical processes of the surface,and is a driving factor in the energy exchange between the surface and the atmosphere.It is widely used in basic disciplines such as climate,hydrology,ecology,and meteorology,and is a key parameter in many basic disciplines.China has a vast territory,large climate differences,and a large population.Researching China's climate change in the context of global climate change is of great significance for maintaining the food security of China and the world as well as the sustained and stable development of social economy.The maximum land surface temperature avoids cloud and rain weather from obtaining accurate surface temperature data from thermal infrared remote sensing,and the annual change is relatively stable,but it is highly sensitive to major land use transfers,droughts and heat waves.In recent years,as China's afforestation plan continues,vegetation coverage has continued to grow.Under the influence of human factors,China's land cover has changed,which in turn affects China's surface environmental factors.Therefore,it is important to study the impact of afforestation on land surface temperature in a large midlatitude country like China.This paper mainly uses MYD11A1 surface temperature data to analyze the temporal and spatial characteristics of the annual maximum surface temperature using empirical orthogonal method,climate tendency rate,and linear correlation analysis method.In addition,the He(2018)method was used to obtain the influence of afforestation on the annual maximum surface temperature in the Loess Plateau.Because not all regions have significant vegetation change areas,in order to study the impact of afforestation in China on surface temperature,the IBM method was used to determine the impact of afforestation on surface temperature,and to obtain the effects of radiation and non-radiation on surface temperature.The main research conclusions of this paper are as follows:(1)The annual maximum value of China's surface temperature is 328.7K in the temperate continental climate zone.The highest annual maximum value of surface temperature is in the Turpan Basin of Xinjiang.(2)The long-term series analysis of the annual maximum value of China's surface temperature shows a slight cooling trend as a whole,and the national average surface temperature climate tendency rate is-0.06K/(10a).The regional analysis of the long-term series trend of the annual maximum surface temperature in China shows that the long-term series of the annual maximum surface temperature in the temperate continental climate zone of China shows a weak warming trend,and the warming trend of the plateau mountain climate zone is more intense with a value of 0.56 K/(10a)The plateau has a significant effect on the amplification of climate change.The linear correlation coefficients of the tropical monsoon climate zone and the subtropical monsoon climate zone both show a cooling trend.(3)Studies have shown that the significant cooling trend in the Loess Plateau is closely related to vegetation growth,and the climatic tendency rate of the annual maximum surface temperature drop due to vegetation growth is-1.36 K/(10a).(4)Research on the potential impact of afforestation on the surface temperature in China shows that afforestation in high latitudes has a warming effect in cold seasons,while in warm seasons all dimensions have a cooling effect,and its annual changes also show similar characteristics.In addition,deciduous broad-leaved forests and afforestation have similar characteristics in the potential impact changes on surface temperature,while evergreen coniferous forests and evergreen broad-leaved forests both show a cooling effect.
Keywords/Search Tags:Annual maximum land surface temperature, Time and space changes, MODIS data, Afforestation, IBM method
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