摘要
为弥补缺失农田灌溉资料对模型结果的影响,提高CoLM模型地表水热通量的估算精度,基于集合卡尔曼滤波算法,将表观热惯量(ATI)作为土壤水分的代表值,同化到CoLM(Common Land Model)模型中。选取黑河流域玉米下垫面的大满站,同化MODIS表观热惯量到模型中,将同化结果与模型估算结果、观测值相对比。结果显示:同化后得到的地表水热通量明显比模拟结果更加接近观测值,而MODIS表观热惯量数据的质量和数量也是影响同化结果精度的重要因素,表明表观热惯量的同化能够填补农田灌溉资料的缺失,改进模型地表水热通量的估算结果。
Apparent thermal inertia(ATI)characterizes the resistance to surface temperature changes,which can indicate changes in surface soil moisture.As a proxy of soil moisture,based on Ensemble Kalman filter algorithm(EnKF),ATI was assimilated into the Common Land Model(CoLM)to improve model estimation accuracy of surface water and energy fluxes as the missing of irrigation information.We selected Daman site over Heihe watershed,a corn farmland,assimilated MODIS ATI into CoLM,and compared assimilation estimation to simulation and observation.Results show that assimilation estimation is closer to observation.And the quality and quantity of MODIS ATI data are both important factors for data assimilation results.This indicates that the assimilation of ATI makes up the missing of irrigation information,and is able to improve CoLM estimation accuracy of surface water and energy fluxes.
出处
《中国科技论文》
CAS
北大核心
2016年第3期251-257,共7页
China Sciencepaper
基金
高等学校博士学科点专项科研基金资助项目(20120003120017)
国家自然科学基金资助项目(41201330)
遥感科学国家重点实验室自由探索/青年人才项目(15ZY-02)
关键词
数据同化
表观热惯量
显热通量
潜热通量
土壤水分
data assimilation
apparent thermal inertia
sensible heat flux
latent heat flux
soil moisture
