The Canadian atmospheric transport model for simulating greenhouse gas evolution on regional scales: GEM–MACH–GHG v.137-reg

Jinwoong Kim,Douglas Chan,Saroja M Polavarapu,Michael Neish

doi:10.5194/gmd-13-269-2020

Jinwoong Kim, Douglas Chan + Show 2 more

Open Access

https://doi.org/10.5194/gmd-13-269-2020

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Abstract

Abstract. In this study, we present the development of a regional atmospheric transport model for greenhouse gas (GHG) simulation based on an operational weather forecast model and a chemical transport model at Environment and Climate Change Canada (ECCC), with the goal of improving our understanding of the high-spatiotemporal-resolution interaction between the atmosphere and surface GHG fluxes over Canada and the United States. The regional model uses 10 km×10 km horizontal grid spacing and 80 vertical levels spanning the ground to 0.1 hPa. The lateral boundary conditions of meteorology and tracers are provided by the global transport model used for GHG simulation at ECCC. The performance of the regional model and added benefit of the regional model over our lower-resolution global models is investigated in terms of modelled CO2 concentration and meteorological forecast quality for multiple seasons in 2015. We find that our regional model has the capability to simulate the high spatial (horizontal and vertical) and temporal scales of atmospheric CO2 concentrations based on comparisons to surface and aircraft observations. In addition, the bias and standard deviation of forecast error in boreal summer are reduced by the regional model. Better representation of model topography in the regional model results in improved simulation of the CO2 diurnal cycle compared to the global model at Walnut Grove, California. The new regional model will form the basis of a flux inversion system that estimates regional-scale fluxes of GHGs over Canada.

Highlights

The global mean atmospheric carbon dioxide (CO2) concentration or mixing ratio has been increasing since the industrial revolution, mainly due to anthropogenic emissions into the atmosphere, while terrestrial and oceanic uptake moderate the increase in CO2 in the atmosphere (Canadell et al, 2007; Le Quéré et al, 2009)
lateral boundary conditions (LBCs) in regional deterministic prediction system (RDPS) were obtained from a global model forecast using a 33 km horizontal grid spacing (Caron et al, 2015), with a different model domain extent and vertical coordinate
The uncertainty of 24 h weather forecasts in the global model corresponding to the GLB90 experiment in this study is comparable with those of reanalyses provided by three operational centres; the monthly and zonal means of fields in 2009 and 2010 are within an acceptable range on global scales

Summary

Introduction

The global mean atmospheric carbon dioxide (CO2) concentration or mixing ratio (in mole fractions of dry air) has been increasing since the industrial revolution, mainly due to anthropogenic emissions into the atmosphere, while terrestrial and oceanic uptake moderate the increase in CO2 in the atmosphere (Canadell et al, 2007; Le Quéré et al, 2009). Apart from this global increase, information about each component affecting the global carbon budget and its uncertainties is estimated and updated regularly at the global scale using a wide range of methods and data (Le Quéré et al, 2009, 2018).

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