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

Authors :
Peng, Jian
Kharbouche, Said
Muller, Jan-Peter
Danne, Olaf
Blessing, Simon
Giering, Ralf
Gobron, Nadine
Ludwig, Ralf
Müller, Benjamin
Leng, Guoyong
Lees, Thomas
Dadson, Simon
Source :
Journal of Hydrology. Jan2020, Vol. 580, pN.PAG-N.PAG. 1p.
Publication Year :
2020

Abstract

• The newly developed global long-term QA4ECV albedo and LAI datasets were applied for latent and sensible heat fluxes estimation. • The QA4ECV LAI leads to worse latent heat flux estimation due to its use of effective LAI rather than green leaf LAI. • The combined use of QA4ECV albedo and GLOBMAP LAI was suggested for latent and sensible heat fluxes estimation based on HOLAPS. 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 (LAI) 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 long-term 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/m2 for hourly (monthly) latent heat flux, and 80.5 (24.5) W/m2 for sensible heat flux, which are comparable to estimates with MODIS and other reported studies. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
00221694
Volume :
580
Database :
Academic Search Index
Journal :
Journal of Hydrology
Publication Type :
Academic Journal
Accession number :
141607298
Full Text :
https://doi.org/10.1016/j.jhydrol.2019.124245