Advanced

TransCom model simulations of hourly atmospheric CO2 : analysis of synoptic-scale variations for the period 2002-2003

Patra, P. K.; Law, R. M.; Peters, W.; Roedenbeck, C.; Takigawa, M.; Aulagnier, C.; Baker, I.; Bergmann, D. J.; Bousquet, P. and Brandt, J., et al. (2008) In Global Biogeochemical Cycles 22(4). p.1-16
Abstract
The ability to reliably estimate CO2 fluxes from current in situ atmospheric CO2 measurements and future satellite CO2 measurements is dependent on transport model performance at synoptic and shorter timescales. The TransCom continuous experiment was designed to evaluate the performance of forward transport model simulations at hourly, daily, and synoptic timescales, and we focus on the latter two in this paper. Twenty-five transport models or model variants submitted hourly time series of nine predetermined tracers (seven for CO2) at 280 locations. We extracted synoptic-scale variability from daily averaged CO2 time series using a digital filter and analyzed the results by comparing them to atmospheric measurements at 35 locations. The... (More)
The ability to reliably estimate CO2 fluxes from current in situ atmospheric CO2 measurements and future satellite CO2 measurements is dependent on transport model performance at synoptic and shorter timescales. The TransCom continuous experiment was designed to evaluate the performance of forward transport model simulations at hourly, daily, and synoptic timescales, and we focus on the latter two in this paper. Twenty-five transport models or model variants submitted hourly time series of nine predetermined tracers (seven for CO2) at 280 locations. We extracted synoptic-scale variability from daily averaged CO2 time series using a digital filter and analyzed the results by comparing them to atmospheric measurements at 35 locations. The correlations between modeled and observed synoptic CO2 variabilities were almost always largest with zero time lag and statistically significant for most models and most locations. Generally, the model results using diurnally varying land fluxes were closer to the observations compared to those obtained using monthly mean or daily average fluxes, and winter was often better simulated than summer. Model results at higher spatial resolution compared better with observations, mostly because these models were able to sample closer to the measurement site location. The amplitude and correlation of model-data variability is strongly model and season dependent. Overall similarity in modeled synoptic CO2 variability suggests that the first-order transport mechanisms are fairly well parameterized in the models, and no clear distinction was found between the meteorological analyses in capturing the synoptic-scale dynamics. (Less)
Please use this url to cite or link to this publication:
author
, et al. (More)
(Less)
publishing date
type
Contribution to journal
publication status
published
subject
in
Global Biogeochemical Cycles
volume
22
issue
4
pages
1 - 16
publisher
American Geophysical Union
external identifiers
  • wos:000261244400001
  • other:Article number GB4013
  • scopus:64549101121
ISSN
0886-6236
DOI
10.1029/2007GB003081
language
English
LU publication?
no
id
ba84a81d-ef89-4d7f-9acb-0df9675e0c15 (old id 4623931)
date added to LUP
2014-10-14 14:56:25
date last changed
2017-10-22 04:24:18
@article{ba84a81d-ef89-4d7f-9acb-0df9675e0c15,
  abstract     = {The ability to reliably estimate CO2 fluxes from current in situ atmospheric CO2 measurements and future satellite CO2 measurements is dependent on transport model performance at synoptic and shorter timescales. The TransCom continuous experiment was designed to evaluate the performance of forward transport model simulations at hourly, daily, and synoptic timescales, and we focus on the latter two in this paper. Twenty-five transport models or model variants submitted hourly time series of nine predetermined tracers (seven for CO2) at 280 locations. We extracted synoptic-scale variability from daily averaged CO2 time series using a digital filter and analyzed the results by comparing them to atmospheric measurements at 35 locations. The correlations between modeled and observed synoptic CO2 variabilities were almost always largest with zero time lag and statistically significant for most models and most locations. Generally, the model results using diurnally varying land fluxes were closer to the observations compared to those obtained using monthly mean or daily average fluxes, and winter was often better simulated than summer. Model results at higher spatial resolution compared better with observations, mostly because these models were able to sample closer to the measurement site location. The amplitude and correlation of model-data variability is strongly model and season dependent. Overall similarity in modeled synoptic CO2 variability suggests that the first-order transport mechanisms are fairly well parameterized in the models, and no clear distinction was found between the meteorological analyses in capturing the synoptic-scale dynamics.},
  author       = {Patra, P. K. and Law, R. M. and Peters, W. and Roedenbeck, C. and Takigawa, M. and Aulagnier, C. and Baker, I. and Bergmann, D. J. and Bousquet, P. and Brandt, J. and Bruhwiler, L. and Cameron-Smith, P. J. and Christensen, J. H. and Delage, F. and Denning, A. S. and Fan, S. and Geels, C. and Houweling, S. and Imasu, R. and Karstens, Ute and Kawa, S. R. and Kleist, J. and Krol, M. C. and Lin, S. -J. and Lokupitiya, R. and Maki, T. and Maksyutov, S. and Niwa, Y. and Onishi, R. and Parazoo, N. and Pieterse, G. and Rivier, L. and Satoh, M. and Serrar, S. and Taguchi, S. and Vautard, R. and Vermeulen, Alex and Zhu, Z.},
  issn         = {0886-6236},
  language     = {eng},
  number       = {4},
  pages        = {1--16},
  publisher    = {American Geophysical Union},
  series       = {Global Biogeochemical Cycles},
  title        = {TransCom model simulations of hourly atmospheric CO2 : analysis of synoptic-scale variations for the period 2002-2003},
  url          = {http://dx.doi.org/10.1029/2007GB003081},
  volume       = {22},
  year         = {2008},
}