Models

The GMI-CTM uses the Flux Form Semi-Lagrangian dynamical core of Lin and Rood [1996]. It can be integrated with any vertical resolution and coordinate supplied by the input meteorological fields; horizontal resolutions of 1° x 1.25°, 2° x 2.5°, and 4° x 5° are currently used. Most simulations use a hybrid sigma-pressure coordinate with terrain-following levels near the surface, transitioning to constant pressure levels near 150 hPa. Previous GMI experiments have used meteorological input from both general circulation models (GCMs), forecasts, and data assimilation systems (DAS). GCM fields used to-date include GISS II’ and NCAR CCM2 [Douglass et al., 1999], the Finite Volume GCM (FVGCM) [Duncan et al., 2007; Strahan et al., 2007], and GEOS chemistry climate model (CCM).  Over the years, the GMI CTM has been integrated with many versions of NASA Goddard DAS fields, from the original ‘GEOS-Strat’ to MERRA [Strahan et al., 2013] and MERRA-2.  The CTM has parameterized tropospheric physical processes including convection, boundary layer turbulent transport, wet scavenging in convective updrafts, wet and dry deposition, and anthropogenic, natural and biogenic emissions.

GMI CTM simulations can be integrated with different mechanisms. The stratosphere-troposphere (‘Combo’) mechanism contains roughly 120 gas phase species and includes heterogeneous chemical reactions involved in polar ozone depletion. There is a coupled chemistry-aerosol mechanism, which allows coupling between the Combo mechanism and an aerosol model similar to GOCART. For diagnosis of transport processes on a wide range of temporal and spatial scales, there is a tracer suite currently containing 35 tracers. These mechanisms are described below.

 

The Stratospheric-Tropospheric (‘Combo’) Model

 

The GMI combined tropospheric-stratospheric chemical mechanism was first described in Duncan et al. [2007]. The stratospheric portion of the mechanism came from the Lawrence Livermore National Lab ‘Impact’ model [Rotman et al., 2004, and references therein], while the tropospheric component was originally developed for the Harvard University GEOS-Chem tropospheric CTM [Horowitz et al., 1998]. The mechanism contains approximately 120 species, 322 thermal reactions, and 82 photolytic decompositions, including both stratospheric halogen chemistry and tropospheric non-methane hydrocarbon chemistry. The chemical mechanism is integrated using the SMVGEAR-II solver of Jacobson [1995]. Photolytic decomposition uses the Fast-jx photolysis scheme, which is an outgrowth of the Fast-j scheme of Wild et al. [2000] for tropospheric photolytic reactions, and the Fast-j2 scheme of Bian and Prather [2002], which treats stratospheric photolytic reactions. Heterogeneous chemical reactions on stratospheric sulfate aerosols as well as Type 1 and Type 2 PSCs are treated as described in Considine et al. [2000] and Considine et al. [2004]. Details of updates to the mechanism, reaction rates, cross sections, and emissions for particular simulations can be found on the Simulations page.

 

Aerosol Model

 

The GMI aerosol module can be directly coupled to the GMI-CTM advection core [Liu et al., 2007; Bian et al., 2009]. This approach is able to simulate five major atmospheric aerosol components: black carbon, organic carbon, sulfate, dust, and sea salt. The aerosol module includes primary emissions, chemical production of sulfate in clear air and in-cloud aqueous phase, gravitational sedimentation, dry deposition, wet scavenging in and below clouds, and hygroscopic growth. Model outputs include SO2 (fossil fuel and natural), DMS, H2O2, sulfate (fossil fuel and natural, 3 size bins), black carbon (biomass burning and natural), organic matter (fossil fuel, biomass burning, and natural), mineral dust (5 size bins), and sea salt (4 size bins).

 

Coupled Chemistry-Aerosol Model 

 

The GMI model can be integrated with the ‘Combo’ chemistry module coupled to its aerosol module, called the coupled chemistry-aerosol module. This version improves previous aerosol simulations by including two more atmospheric aerosol components: nitrate and ammonium. This chemistry module simulates 154 gas and aerosol species with 337 thermal reactions and 81 photolytic decompositions. The sulfate gas phase chemistry is now treated along with all other species in the ‘Combo’ chemical mechanism. Aerosol nitrate and ammonium are calculated by a thermodynamic equilibrium model RPMARES, adopted from GEOS-CHEM, for a system of SO42-  -NO3- -NH4+-H2O. An irreversible absorption of HNO3 on mineral dust and sea salt is also included.

 

Tracer Suite

 

The GMI tracer suite is designed to diagnose a wide range of atmospheric processes. The suite includes stratospheric ozone tracers for diagnosing the stratosphere’s influence on tropospheric ozone and a fixed-lifetime tracer for diagnosing the chemical tropopause following Prather et al. [2011].  There are also age-of-air tracers and fixed lifetime tracers for diagnosing transport from various regions on specific timescales, and tracers such as radon and lead-210 for diagnosing processes such as land and marine convection and deposition. Species in the tracer suite can be found here. Information on MERRA and MERRA2 tracer simulation can be found on the Simulations page.

 

 

References

 

Bian, H.S., and M.J. Prather (2002), Fast-J2: Accurate simulation of stratospheric photolysis in global chemical models, J. Atmos. Chem., 41, 281-296.

Bian, H., M. Chin, J. Rodriguez, H. Yu, J.E. Penner, S. Strahan (2009), Sensitivity of aerosol optical thickness and aerosol direct radiative effect to relative humidity, Atmos. Chem. Phys. 9, 2375-2386.

Considine, D.B., A.R. Douglass, P.S. Connell, D.E. Kinnison, and D.A. Rotman (2000),A polar stratospheric cloud parameterization for the global modeling initiative three-dimensional model and its response to stratospheric aircraft, J. Geophys. Res., 105, 3955-3975.

Considine, D.B., P.S. Connell, D.J. Bergmann, D.A. Rotman, and S.E. Strahan (2004), Sensitivity of Global Modeling Initiative model predictions of Antarctic ozone recovery to input meteorological fields, J. Geophys. Res., 109, D15301, doi:10.1029/2003JD004487.

Douglass, A.R., M.P. Prather, T.M. Hall, S.E. Strahan, P.J. Rasch, L.C. Sparling, L. Coy, and J.M. Rodriguez (1999), Choosing meteorological input for the global modeling initiative assessment of high speed aircraft, J. Geophys. Res., 104, 27,545-27,564.

Duncan, B.N., S.E. Strahan, Y. Yoshida, S.D. Steenrod, and N. Livesey (2007), Model study of cross-tropopause transport of biomass burning pollution, Atmos. Chem. Phys., 7, 3713-3736.

Horowitz, L.W., J. Liang, G.M. Gardner, and D. J. Jacob (1998), Export of reactive nitrogen from North America during summertime: Sensitivity to hydrocarbon chemistry, J. Geophys. Res., 103, 13,451–13,476.

Jacobson, M.Z. (1995), Computation of global photochemistry with SMVGEAR II, Atmos. Environ., Part A, 29, 2541-2546.

Lin, S. J., and R. B. Rood (1996), Multidimensional flux form semi-Lagrangian transport schemes, Mon. Weather Rev.,124, 2046-2070.

Liu, X., J. E. Penner, B. Das, D. Bergmann, J. M. Rodriguez, S. E. Strahan, M. Wang, and Y. Feng (2007), Uncertainties in global aerosol simulations: Assessment using three meteorological datasets, J. Geophys. Res., 112, D11212, doi:10.1029/2006JD008216.

Prather, M.J., X. Zhu, Q. Tang, J. Hsu, and J.L. Neu (2011), An atmospheric chemist in search of the tropopause, J. Geophys. Res., 116, 116, D04306, doi:10.1029/2010JD014939.

Rotman, D.A., C.S. Atherton, D.J. Bergmann, et al. (2004), IMPACT: the LLNL 3-D global atmospheric chemical transport model for the combined troposphere and stratosphere: Model description and analysis of ozone and other trace gases, J. Geophys. Res., 109, doi:10.1029/2002JD003155.

Strahan, S.E., B.N. Duncan, and P. Hoor (2007), Observationally derived transport diagnostics for the lowermost stratosphere and their application to the GMI chemistry and transport model (2007), Atmos. Chem. Phys., 7, 2435-2445.

Strahan, S.E., A.R. Douglass, and P.A. Newman (2013), The contributions of chemistry and transport to low arctic ozone in March 2011 derived from Aura MLS observations, J. Geophys. Res. 118, 1563-1576.

Wild, O., X. Zhu, and M.J. Prather (2000), Fast-j: Accurate simulation of in- and below-cloud photolysis in tropospheric chemical models, J. Atmos. Chem., 37, 245-282.