Simulation of variability in atmospheric carbon dioxide using a global coupled Eulerian - Lagrangian transport model

Abstract

This study assesses the advantages of using a coupled atmospheric- tracertransport model, comprising a global Eulerian model and a global Lagrangianparticle dispersion model, to improve the reproducibility of tracer-gasvariations affected by the near-field surface emissions and transport aroundobservation sites. The ability to resolve variability in atmosphericcomposition on an hourly time-scale and a spatial scale of severalkilometers would be beneficial for analyzing data from continuousground-based monitoring and from upcoming space-based observations. Thecoupled model yields an increase in the horizontal resolution of transportand fluxes, and has been tested in regional-scale studies of atmosphericchemistry. By applying the Lagrangian component to the global domain, weextend this approach to the global scale, thereby enabling computationallyefficient global inverse modeling and data assimilation. To validate thecoupled model, we compare model-simulated CO2 concentrations withcontinuous observations at three sites: two operated by the National Oceanicand Atmospheric Administration, USA, and one operated by the NationalInstitute for Environmental Studies, Japan. As the goal of this study islimited to introducing the new modeling approach, we selected a transportsimulation at these three sites to demonstrate how the model may perform atvarious geographical areas. The coupled model provides improved agreementbetween modeled and observed CO2 concentrations in comparison to theEulerian model. In an area where variability in CO2 concentration isdominated by a fossil fuel signal, the correlation coefficient betweenmodeled and observed concentrations increases by between 0.05 to 0.1 fromthe original values of 0.5-0.6 achieved with the Eulerian model. © 2011 Author(s).