Influences of leaf area index and albedo on estimating energy fluxes with HOLAPS framework

doi:10.1016/j.jhydrol.2019.124245

	Influences of leaf area index and albedo on estimating energy fluxes with HOLAPS framework
	Peng, Jian 1,2,3; Kharbouche, Said 4; Muller, Jan-Peter 4; Danne, Olaf 5; Blessing, Simon 6; Giering, Ralf 6; Gobron, Nadine 7; Ludwig, Ralf 2; Mueller, Benjamin 2; Leng, Guoyong 8
刊名	JOURNAL OF HYDROLOGY
	2020
卷号	580 页码:13
关键词	HOLAPS Albedo Leaf area index QA4ECV MODIS GlobAlbedo GLOBMAP FLUXNET
ISSN号	0022-1694
DOI	10.1016/j.jhydrol.2019.124245
通讯作者	Peng, Jian(jian.peng@ouce.ox.ac.uk)
英文摘要	The High resOlution Land Atmosphere surface Parameters from Space (HOLAPS) programme provides a modeling system to maximize the use of satellite-based products and ensure internally consistent estimation of surface water and energy fluxes. Leaf area index (LAS) and land surface albedo are two key parameters for estimation of latent and sensible heat fluxes with HOLAPS. Thus, to facilitate the generation of long-term high accuracy latent and sensible heat fluxes, high quality global long-term LAI and land surface albedo datasets are essential. The Quality Assurance for Essential Climate Variables (QA4ECV) project released quality-assured longterm LAI and albedo datasets with traceable and reliable uncertainty information provided in the dataset. Taking MODIS-BNU-LAI and MODIS albedo as reference, different global long-term LAI and albedo datasets including GlobAlbedo, QA4ECV and GLOBMAP were investigated for estimation of latent/sensible heat fluxes with HOLAPS in this study. The results show that all albedo datasets show similar accuracy for estimation of latent and sensible heat fluxes when validated against FLUXNET observations. The QA4ECV LAI leads to worse latent heat flux estimation due to its use of effective LAI rather than green leaf LAI. Sensitivity analysis also shows that the HOLAPS estimated latent heat flux (LE) is more sensitive to uncertainty in LAI than land surface albedo. Overall, the combined use of QA4ECV albedo and GLOBMAP LAI is suggested for estimation of latent/sensible heat fluxes with HOLAPS. The root mean square differences (RMSD) between estimations and FLUXNET measurements are 54 (30) W/m(2) for hourly (monthly) latent heat flux, and 80.5 (24.5) W/m(2) for sensible heat flux, which are comparable to estimates with MODIS and other reported studies.
资助项目	QA4ECV (EU FP7 Project Quality Assurance for Essential Climate Variables (QA4ECV))[607405]
WOS关键词	CARBON-DIOXIDE EXCHANGE ; LAND-SURFACE EVAPORATION ; BALANCE SYSTEM SEBS ; SENSIBLE HEAT ; SENSITIVITY-ANALYSIS ; SCINTILLOMETER MEASUREMENTS ; INTERANNUAL VARIABILITY ; DECIDUOUS FOREST ; WATER-VAPOR ; PART I
WOS研究方向	Engineering ; Geology ; Water Resources
语种	英语
出版者	ELSEVIER
WOS记录号	WOS:000509620900074
资助机构	QA4ECV (EU FP7 Project Quality Assurance for Essential Climate Variables (QA4ECV))
内容类型	期刊论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/132345]
专题	中国科学院地理科学与资源研究所
通讯作者	Peng, Jian
作者单位	1.Univ Oxford, Sch Geog & Environm, Oxford OX1 3QY, England 2.Univ Munich LMU, Dept Geog, D-80333 Munich, Germany 3.Max Planck Inst Meteorol, D-20146 Hamburg, Germany 4.Univ Coll London, Dept Space & Climate Phys, Imaging Grp, Holmbury RH5 6NT, England 5.Brockmann Consult GmbH, Chrysanderstr 1, D-21029 Hamburg, Germany 6.FastOpt GmbH, Ispra, Italy 7.European Commiss, JRC, Ispra, Italy 8.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Water Cycle & Related Land Surface Proc, Beijing 100101, Peoples R China
推荐引用方式 GB/T 7714	Peng, Jian,Kharbouche, Said,Muller, Jan-Peter,et al. Influences of leaf area index and albedo on estimating energy fluxes with HOLAPS framework[J]. JOURNAL OF HYDROLOGY,2020,580:13.
APA	Peng, Jian.,Kharbouche, Said.,Muller, Jan-Peter.,Danne, Olaf.,Blessing, Simon.,...&Dadson, Simon.(2020).Influences of leaf area index and albedo on estimating energy fluxes with HOLAPS framework.JOURNAL OF HYDROLOGY,580,13.
MLA	Peng, Jian,et al."Influences of leaf area index and albedo on estimating energy fluxes with HOLAPS framework".JOURNAL OF HYDROLOGY 580(2020):13.