首页 | 本学科首页   官方微博 | 高级检索  
     检索      


Effects of complex terrain on net surface longwave radiation in China
Authors:Xiaochen?Zhu  Xinfa?Qiu  Email author" target="_blank">Yan?ZengEmail author  Wei?Ren  Bo?Tao  Jiaqi?Gao  Haobo?Liu  Yunjuan?Tan
Institution:1.School of Geography and Remote Sensing,Nanjing University of Information Science and Technology,Nanjing,China;2.Department of Plant and Soil Sciences,University of Kentucky,Lexington,USA;3.College of Applied Meteorology,Nanjing University of Information Science and Technology,Nanjing,China;4.Climate Centre of Jiangsu Province,Jiangsu Provincial Meteorological Bureau,Nanjing,China;5.College of Atmospheric Science,Nanjing University of Information Science and Technology,Nanjing,China;6.Shanghai Meteorological Bureau,Shanghai,China
Abstract:Net surface longwave radiation (NSLR) is one of key meteorological factors and is strongly influenced by cloud cover, surface temperature, humidity, and local micrometeorological conditions as well as terrain conditions. Realistically estimating NSLR is vitally important for understanding surface radiation balance and investigating micrometeorological factors of air pollution dispersion, especially in regions with complicated terrain. In this study, we proposed a distributed model for estimating NSLR by considering effects of complex local terrain conditions in China. Meteorological data (including mean temperature, relative humidity, and sunshine percentage) and observed NSLR data from 1993 to 2001 together with the digital elevation model data were used to parametrize the model and account for the effects of atmospheric factors and surface terrain factors according to the isotropic principle. The monthly NSLR during 1961–2000 was estimated at a spatial resolution of 1 km. Topographic analysis suggests that the distribution characteristics of NSLR with elevation or slope are consistent with those of field observations. In particular, the estimated NSLR is favorably comparable with site-level observations on the Tibetan Plateau (average relative error < 11%). Our results indicate that this model can describe microscale distribution features in mountainous areas in detail and that this improved approach can be used for NSLR spatial estimation in other regions with complicated terrain.
Keywords:
本文献已被 SpringerLink 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号