Abstract
Abstract. Chemistry transport models (CTMs) play an important role in understanding fluxes and atmospheric distribution of carbon dioxide (CO2). They have been widely used for modeling CO2 transport through forward simulations and inferring fluxes through inversion systems. With the increasing availability of high-resolution observations, it has been become possible to estimate CO2 fluxes at higher spatial resolution. In this work, we implemented CO2 transport in the Model for Prediction Across Scales – Atmosphere (MPAS-A). The objective is to use the variable-resolution capability of MPAS-A to enable a high-resolution CO2 simulation in a limited region with a global model. Treating CO2 as an inert tracer, we implemented in MPAS-A (v6.3) the CO2 transport processes, including advection, vertical mixing by boundary layer scheme, and convective transport. We first evaluated the newly implemented model's tracer mass conservation and then its CO2 simulation accuracy. A 1-year (2014) MPAS-A simulation is evaluated at the global scale using CO2 measurements from 50 near-surface stations and 18 Total Carbon Column Observing Network (TCCON) stations. The simulation is also compared with two global models: National Oceanic and Atmospheric Administration (NOAA) CarbonTracker v2019 (CT2019) and European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS). A second set of simulation (2016–2018) is used to evaluate MPAS-A at regional scale using Atmospheric Carbon and Transport – America (ACT-America) aircraft CO2 measurements over the eastern United States. This simulation is also compared with CT2019 and a 27 km WRF-Chem simulation. The global-scale evaluations show that MPAS-A is capable of representing the spatial and temporal CO2 variation with a comparable level of accuracy as IFS of similar horizontal resolution. The regional-scale evaluations show that MPAS-A is capable of representing the observed atmospheric CO2 spatial structures related to the midlatitude synoptic weather system, including the warm versus cold sector distinction, boundary layer to free troposphere difference, and frontal boundary CO2 enhancement. MPAS-A's performance in representing these CO2 spatial structures is comparable to the global model CT2019 and regional model WRF-Chem.
Highlights
Carbon dioxide (CO2) is the most important greenhouse gas, and our knowledge about its sources and sinks still has large gaps
The simulation accuracy of MPAS-A is compared with three established CO2 modeling systems based on the same observational data: WRF-Chem (Skamarock et al, 2008; Feng et al, 2019), CarbonTracker (v2019, CarbonTracker v2019 (CT2019) hereafter) (Jacobson et al, 2020), and the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS) (Agusti-Panareda et al, 2014, 2019)
Two sets of simulations over a 60–15 km variable-resolution global domain were conducted for a model accuracy evaluation using an extensive aircraft measurements over the eastern United States and near-surface hourly measurements from surface and tower stations distributed across the globe
Summary
Carbon dioxide (CO2) is the most important greenhouse gas, and our knowledge about its sources and sinks still has large gaps. When the CO2 lateral boundary is optimized, an inversion system adjusts its CO2 fields at the boundary prescribed by a parent global model in addition to adjusting surface fluxes This could be problematic for inversion systems that use satellite-derived column-averaged CO2 measurements (XCO2) because model–data mismatches in the free troposphere (FT) are often originated from outside a regional model’s limited-area domain (Feng et al, 2019; Lauvaux and Davis, 2014). The objective of the present paper is to provide an alternative high-resolution CO2 transport modeling approach to regional transport models This approach is to use a global variable-resolution model which allows for local grid refinement that enables high-resolution simulation over an interested region without incurring the prohibitively high computational cost or the lateral boundary condition. The simulation accuracy of MPAS-A is compared with three established CO2 modeling systems based on the same observational data: WRF-Chem (Skamarock et al, 2008; Feng et al, 2019), CarbonTracker (v2019, CT2019 hereafter) (Jacobson et al, 2020), and the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecasting System (IFS) (Agusti-Panareda et al, 2014, 2019)
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