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Evaluating common land model energy fluxes using FLUXNET data.

Authors :
Zhang, Xiangxiang
Dai, Yongjiu
Cui, Hongzhi
Dickinson, Robert
Zhu, Siguang
Wei, Nan
Yan, Binyan
Yuan, Hua
Shangguan, Wei
Wang, Lili
Fu, Wenting
Source :
Advances in Atmospheric Sciences. Sep2017, Vol. 34 Issue 9, p1035-1046. 12p.
Publication Year :
2017

Abstract

Given the crucial role of land surface processes in global and regional climates, there is a pressing need to test and verify the performance of land surface models via comparisons to observations. In this study, the eddy covariance measurements from 20 FLUXNET sites spanning more than 100 site-years were utilized to evaluate the performance of the Common Land Model (CoLM) over different vegetation types in various climate zones. A decomposition method was employed to separate both the observed and simulated energy fluxes, i.e., the sensible heat flux, latent heat flux, net radiation, and ground heat flux, at three timescales ranging from stepwise (30 min) to monthly. A comparison between the simulations and observations indicated that CoLM produced satisfactory simulations of all four energy fluxes, although the different indexes did not exhibit consistent results among the different fluxes. A strong agreement between the simulations and observations was found for the seasonal cycles at the 20 sites, whereas CoLM underestimated the latent heat flux at the sites with distinct dry and wet seasons, which might be associated with its weakness in simulating soil water during the dry season. CoLM cannot explicitly simulate the midday depression of leaf gas exchange, which may explain why CoLM also has a maximum diurnal bias at noon in the summer. Of the eight selected vegetation types analyzed, CoLM performs best for evergreen broadleaf forests and worst for croplands and wetlands. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
02561530
Volume :
34
Issue :
9
Database :
Academic Search Index
Journal :
Advances in Atmospheric Sciences
Publication Type :
Academic Journal
Accession number :
124484463
Full Text :
https://doi.org/10.1007/s00376-017-6251-y