TY - JOUR
T1 - Effect of flux and its uncertainty on tall tower CO2 concentration simulation in the agricultural domain
AU - Hu, Cheng
AU - Zhang, Mi
AU - Xiao, Wei
AU - Wang, Yong Wei
AU - Wang, Wei
AU - Tim, Griffis
AU - Liu, Shou Dong
AU - Li, Xu Hui
N1 - Publisher Copyright:
© 2017 Editorial Board of Chinese Journal of Agrometeorology. All rights reserved.
PY - 2017/8/20
Y1 - 2017/8/20
N2 - Based on the CO2 concentration observations in U. S. Corn belt, which was measured at 100m height of a tall tower, hourly CO2 concentration was simulated for the growing season (June-September, 2008) with the WRF-STILT model. And the effect of flux uncertainty on modeled CO2 concentration was also analyzed. The results showed as: (1) WRF-STILT model can simulate the observed strong diurnal variation in growing season, with RMSE be 13. 70μmolmol-1, and it was overestimated by 7. 26μmolmol-1, the shape and area of intense footprint zonesare different for different months (September>August>June>July). (2) The difference of regional average anthropogenic CO2 flux for EDGAR and Carbon Tracker was within 6%, when both of them were at the same spatial resolution, the simulated CO2 enhancement difference was close to 10%. (3) Spatial resolution can lead to large bias in the modeled CO2 enhancement, when using 1o emissions, the simulated CO2 enhancement was only 0. 4 times of the results using 0. 1o emissions, and with the decreases of spatial resolution, the modeled bias increases. (4) Daytime and nighttime NEE of Carbon Tracker is 2. 26 and 1. 56 times that of tall tower NEE observations, and the misrepresentatives of underlying land use categories can lead to about 12μmolmol-1 bias in the modeled results, which may be the potential reason of bias high for 7. 26μmolmol-1. Our study concludes that when combing WRF-STILT model with high quality CO2 flux, the strong diurnal variation of CO2 concentration can be well simulated, and the uncertainty of CO2 flux is the main reason for modeled CO2 concentration bias, it also indicates the potential of evaluating and retrieving prior CO2 flux.
AB - Based on the CO2 concentration observations in U. S. Corn belt, which was measured at 100m height of a tall tower, hourly CO2 concentration was simulated for the growing season (June-September, 2008) with the WRF-STILT model. And the effect of flux uncertainty on modeled CO2 concentration was also analyzed. The results showed as: (1) WRF-STILT model can simulate the observed strong diurnal variation in growing season, with RMSE be 13. 70μmolmol-1, and it was overestimated by 7. 26μmolmol-1, the shape and area of intense footprint zonesare different for different months (September>August>June>July). (2) The difference of regional average anthropogenic CO2 flux for EDGAR and Carbon Tracker was within 6%, when both of them were at the same spatial resolution, the simulated CO2 enhancement difference was close to 10%. (3) Spatial resolution can lead to large bias in the modeled CO2 enhancement, when using 1o emissions, the simulated CO2 enhancement was only 0. 4 times of the results using 0. 1o emissions, and with the decreases of spatial resolution, the modeled bias increases. (4) Daytime and nighttime NEE of Carbon Tracker is 2. 26 and 1. 56 times that of tall tower NEE observations, and the misrepresentatives of underlying land use categories can lead to about 12μmolmol-1 bias in the modeled results, which may be the potential reason of bias high for 7. 26μmolmol-1. Our study concludes that when combing WRF-STILT model with high quality CO2 flux, the strong diurnal variation of CO2 concentration can be well simulated, and the uncertainty of CO2 flux is the main reason for modeled CO2 concentration bias, it also indicates the potential of evaluating and retrieving prior CO2 flux.
KW - Eddy covariance
KW - Flux uncertainty
KW - Fossil emissions
KW - WRF-STILT model
UR - http://www.scopus.com/inward/record.url?scp=85049347169&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85049347169&partnerID=8YFLogxK
U2 - 10.3969/j.issn.1000-6362.2017.08.001
DO - 10.3969/j.issn.1000-6362.2017.08.001
M3 - Article
AN - SCOPUS:85049347169
SN - 1000-6362
VL - 38
SP - 469
EP - 480
JO - Chinese Journal of Agrometeorology
JF - Chinese Journal of Agrometeorology
IS - 8
ER -