TY - JOUR
T1 - Improving the light use efficiency model for simulating terrestrial vegetation gross primary production by the inclusion of diffuse radiation across ecosystems in China
AU - Wang, Shaoqiang
AU - Huang, Kun
AU - Yan, Hao
AU - Yan, Huimin
AU - Zhou, Lei
AU - Wang, Huimin
AU - Zhang, Junhui
AU - Yan, Junhua
AU - Zhao, Liang
AU - Wang, Yanfen
AU - Shi, Peili
AU - Zhao, Fenghua
AU - Sun, Leigang
N1 - Publisher Copyright:
© 2015 Elsevier B.V.
PY - 2015/9/1
Y1 - 2015/9/1
N2 - Qualification of gross primary production (GPP) of terrestrial ecosystem over large areas is important in understanding the response of terrestrial ecosystem to global climate change. While light use efficiency (LUE) models were widely used in regional carbon budget estimates, few studies consider the effect of diffuse radiation on LUE caused by clouds using a big leaf model. Here we developed a cloudiness index light use efficiency (CI-LUE) model based on the MOD17 model algorithm to estimate the terrestrial ecosystem GPP, in which the base light use efficiency encompassed the cloudiness index, maximum LUE and clear sky LUE. GPP measured at seven sites from 2003 to 2007 in China were used to calibrate and validate the CI-LUE model. The results showed that at forest sites and cropland site the CI-LUE model outperformed the Vegetation Photosynthesis Model (VPM), Terrestrial Ecosystem Carbon flux model (TEC), MOD17 model algorithm driven by in situ meteorological measurements and MODIS GPP products, especially the R2 of simulated GPP against flux measurements at Dinghushan forest site increased from 0.17 (MODIS GPP products) to 0.61 (CI-LUE). Instead, VPM model had the best agreement with GPP measurements followed by CI-LUE model and lastly TEC model at two grassland sites. Meanwhile, GPP calculated by CI-LUE model has less underestimation under cloudy skies in comparison with MOD17 model. This study demonstrated the potential of the CI-LUE model in improving GPP simulations resulting from the inclusion of diffuse radiation in regulating the base light use efficiency and maximum light use efficiency.
AB - Qualification of gross primary production (GPP) of terrestrial ecosystem over large areas is important in understanding the response of terrestrial ecosystem to global climate change. While light use efficiency (LUE) models were widely used in regional carbon budget estimates, few studies consider the effect of diffuse radiation on LUE caused by clouds using a big leaf model. Here we developed a cloudiness index light use efficiency (CI-LUE) model based on the MOD17 model algorithm to estimate the terrestrial ecosystem GPP, in which the base light use efficiency encompassed the cloudiness index, maximum LUE and clear sky LUE. GPP measured at seven sites from 2003 to 2007 in China were used to calibrate and validate the CI-LUE model. The results showed that at forest sites and cropland site the CI-LUE model outperformed the Vegetation Photosynthesis Model (VPM), Terrestrial Ecosystem Carbon flux model (TEC), MOD17 model algorithm driven by in situ meteorological measurements and MODIS GPP products, especially the R2 of simulated GPP against flux measurements at Dinghushan forest site increased from 0.17 (MODIS GPP products) to 0.61 (CI-LUE). Instead, VPM model had the best agreement with GPP measurements followed by CI-LUE model and lastly TEC model at two grassland sites. Meanwhile, GPP calculated by CI-LUE model has less underestimation under cloudy skies in comparison with MOD17 model. This study demonstrated the potential of the CI-LUE model in improving GPP simulations resulting from the inclusion of diffuse radiation in regulating the base light use efficiency and maximum light use efficiency.
KW - Cloudiness index
KW - Cloudiness index light use efficiency (CI-LUE) model
KW - Eddy covariance flux
KW - MOD17 model
UR - https://www.scopus.com/pages/publications/84930636808
U2 - 10.1016/j.ecocom.2015.04.004
DO - 10.1016/j.ecocom.2015.04.004
M3 - 文章
AN - SCOPUS:84930636808
SN - 1476-945X
VL - 23
SP - 1
EP - 13
JO - Ecological Complexity
JF - Ecological Complexity
ER -