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

Abstract

Abstract. This study assesses the advantages of using a coupled atmospheric-tracer transport model, comprising a global Eulerian model and a global Lagrangian particle dispersion model, to improve the reproducibility of tracer-gas variations affected by the near-field surface emissions and transport around observation sites. The ability to resolve variability in atmospheric composition on an hourly time-scale and a spatial scale of several kilometers would be beneficial for analyzing data from continuous ground-based monitoring and from upcoming space-based observations. The coupled model yields an increase in the horizontal resolution of transport and fluxes, and has been tested in regional-scale studies of atmospheric chemistry. By applying the Lagrangian component to the global domain, we extend this approach to the global scale, thereby enabling computationally efficient global inverse modeling and data assimilation. To validate the coupled model, we compare model-simulated CO 2 concentrations with continuous observations at three sites: two operated by the National Oceanic and Atmospheric Administration, USA, and one operated by the National Institute for Environmental Studies, Japan. As the goal of this study is limited to introducing the new modeling approach, we selected a transport simulation at these three sites to demonstrate how the model may perform at various geographical areas. The coupled model provides improved agreement between modeled and observed CO 2 concentrations in comparison to the Eulerian model. In an area where variability in CO 2 concentration is dominated by a fossil fuel signal, the correlation coefficient between modeled and observed concentrations increases by between 0.05 to 0.1 from the original values of 0.5-0.6 achieved with the Eulerian model.

Analysis of ΔO<sub>2</sub>/ΔCO<sub>2</sub> ratios for the pollution events observed at Hateruma Island, Japan

“…In order to include larger scale background influence, we also use a global coupled Eulerian-Lagrangian transport model (coupled model) developed by Koyama et al (2011). It is comprised of a global Eulerian transport model, the NIES-TM , and a regional LPDM, FLEXPART.…”

FLEXINVERT: an atmospheric Bayesian inversion framework for determining surface fluxes of trace species using an optimized grid

“…A drawback of both these approaches, however, is that only the coarse-resolution Eulerian model is used to calculate the background mixing ratios at the receptors and, thus, is more susceptible to transport errors. We use a different approach and couple the LPDM, run on a global scale, to an Eulerian model at the time boundary, such as done by Koyama et al (2011). This approach utilizes the more accurate transport of the LPDM to calculate the background at the receptors.…”

Adjoint of the global Eulerian–Lagrangian coupled atmospheric transport model (A-GELCA v1.0): development and validation

“…Coupling can be performed in several ways; e.g., a regional-scale LPDM can be coupled to a global Eulerian model at a regional domain boundary (Rödenbeck et al, 2009;Rigby et al, 2011), or a global-scale LPDM can be coupled to an Eulerian model at the time boundary (Koyama et al, 2011;Thompson and Stohl, 2014).…”