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991.
依据国家沈阳农田生态系统野外研究站2006-2010年监测数据,分析0-100cm 土层8个层次的地温、0-100 cm地温、地温极值、0-20 cm地温与气温的关系和土壤热通量的变化趋势。结果表明:从年际变化看,8个层次地温和地温极值呈下降趋势;0 cm层次地温变化受外界影响较大。研究区域年尺度0-20 cm地温与气温有比较一致的变化规律。作物生长季节,可分为4-7月气温上升和8-10月气温下降两阶段;这两个不同阶段的0-20 cm地温与气温分别做线性拟合,与整个生长季4-10月线性拟合相比,线性相关性可信度更高。土壤热通量受气温和土壤质量含水量影响年际变化较大,年尺度土壤热通量≥0 MJ/m2,该区域地表是热汇。 相似文献
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A coupled meteorology and aerosol/chemistry model WRF-Chem(Weather Research and Forecast model coupled with Chemistry) was used to conduct a pair of simulations with present-day(PD) and preindustrial(PI) emissions over East Asia to examine the aerosol indirect effect on clouds.As a result of an increase in aerosols in January,the cloud droplet number increased by 650 cm-3 over the ocean and East China,400 cm-3 over Central and Southwest China,and less than 200 cm-3 over North China.The cloud liquid water path(LWP) increased by 40-60 g m-2 over the ocean and Southeast China and 30 g m-2 over Central China;the LWP increased less than 5 g m-2 or decreased by 5 g m-2 over North China.The effective radius(Re) decreased by more than 4 μm over Southwest,Central,and Southeast China and 2μm over North China.In July,variations in cloud properties were more uniform;the cloud droplet number increased by approximately 250-400 cm-3,the LWP increased by approximately 30-50 g m-2,and Re decreased by approximately 3 ?m over most regions of China.In response to cloud property changes from PI to PD,shortwave(SW) cloud radiative forcing strengthened by 30 W m-2 over the ocean and 10 W m-2 over Southeast China,and it weakened slightly by approximately 2-10 W m-2 over Central and Southwest China in January.In July,SW cloud radiative forcing strengthened by 15 W m-2 over Southeast and North China and weakened by 10 W m-2 over Central China.The different responses of SW cloud radiative forcing in different regions was related to cloud feedbacks and natural variability. 相似文献
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Mehmet ?ahin B. Yi?it Y?ld?z Ozan ?enkal Vedat Pe?temalc? 《Journal of the Indian Society of Remote Sensing》2012,40(3):399-409
This study introduces artificial neural networks (ANNs) for the estimation of land surface temperature (LST) using meteorological and geographical data in Turkey (26?C45°E and 36?C42°N). A generalized regression neural network (GRNN) was used in the network. In order to train the neural network, meteorological and geographical data for the period from January 2002 to December 2002 for 10 stations (Adana, Afyon, Ankara, Eski?ehir, ?stanbul, ?zmir, Konya, Malatya, Rize, Sivas) spread over Turkey were used as training (six stations) and testing (four stations) data. Latitude, longitude, elevation and mean air temperature are used in the input layer of the network. Land surface temperature is the output. However, land surface temperature has been estimated as monthly mean by using NOAA-AVHRR satellite data in the thermal range over 10 stations in Turkey. The RMSE between the estimated and ground values for monthly mean with ANN temperature(LSTANN) and Becker and Li temperature(LSTB-L) method values have been found as 0.077?K and 0.091?K (training stations), 0.045?K and 0.003?K (testing stations), respectively. 相似文献
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对测绘类技能大赛的若干关键问题进行总结,分析竞赛项目设置,成果质量,参赛选手的技能、心理、业务作风及团结协作等方面的问题,提出建议和应对措施,特别是对评分体系中比赛用时成绩计算公式进行解剖分析,旨在完善测绘类技能大赛,提升测绘技能大赛的整体水平,从而达到提高实践教学质量、培养高质量测绘人才的目的。 相似文献
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