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


Spatially explicit surface energy budget and partitioning with remote sensing and flux measurements in a boreal region of Interior Alaska
Authors:Shengli Huang  Devendra Dahal  Ramesh Singh  Heping Liu  Claudia Young  Shuguang Liu
Institution:1. ASRC Research and Technology Solutions (ARTS), Contractor to the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center, 47914 252nd Street, Sioux Falls, SD, 57198, USA
2. Stinger Ghaffarian Technologies (SGT), Inc., Contractor to the USGS EROS Center, Sioux Falls, SD, 57198, USA
3. Department of Civil and Environmental Engineering, Washington State University, Pullman, WA, 99164, USA
4. Earth Resources Technology (ERT), Inc., Contractor to the USGS EROS Center, Sioux Falls, SD, 57198, USA
5. USGS EROS Center, 47914 252nd Street, Sioux Falls, SD, 57198, USA
Abstract:Extrapolating energy fluxes between the ground surface and the atmospheric boundary layer from point-based measurements to spatially explicit landscape estimation is critical to understand and quantify the energy balance components and exchanges in the hydrosphere, atmosphere, and biosphere. This information is difficult to quantify and are often lacking. Using a Landsat image (acquired on 5 August 2004), the flux measurements from three eddy covariance flux towers (a 1987 burn, a 1999 burn, and an unburned control site) and a customized satellite-based surface energy balance model of Mapping Evapotranspiration at High Resolution with Internalized Calibration (METRIC), we estimated net radiation, sensible heat flux (H), latent heat flux (LE), and soil heat flux (G) for the boreal Yukon River Basin of Interior Alaska. The model requires user selection of two extreme conditions present within the image area to calibrate and anchor the sensible flux output. One is the “hot” condition which refers to a bare soil condition with specified residual evaporation rates. Another one is the “cold” condition which refers to a fully transpiring vegetation such as full-cover agricultural crops. We selected one bare field as the “hot” condition while we explored three different scenarios for the “cold” pixel because of the absence of larger expanses of agricultural fields within the image area. For this application over boreal forest, selecting agricultural fields whose evapotranspiration was assumed to be 1.05 times the alfalfa-based reference evapotranspiration as the “cold” pixel could result in large errors. Selecting an unburned flux tower site as the “cold” pixel could achieve acceptable results, but uncertainties remain about the energy balance closure of the flux towers. We found that METRIC performs reasonably well in partitioning energy fluxes in a boreal landscape.
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