The GMI CTM was developed in the 1990s under the auspices of the NASA Atmospheric Effects of Aviation Project (AEAP). Its first application was the assessment of the impact of a fleet of high-speed civil transports on the abundances of stratospheric ozone, total inorganic nitrogen, and H2O [Kinnison et al., 2001].
The GMI CTM project was designed to:
The mantra of ‘model evaluation’ is what set GMI apart from other modeling efforts of the 1990s and 2000s. Many model studies made vague claims that their model had ‘reasonable agreement’ with observations, whatever that means. From its earliest publications, the GMI project has striven to make comparisons with observations that permit a physical interpretation of the model’s behavior, with the goal of determining whether model behavior – even when realistic in appearance - is right for the right reasons. Physically based model evaluation is essential for model credibility. The number one goal of GMI is to produce simulations that realistically simulate the physical processes the model represents.
Early GMI studies investigated the sensitivity to numerical transport schemes [Rotman et al., 2001] and evaluated transport characteristics of the GMI-CTM to input meteorological fields [Douglass et al., 1999]. In the late 1990's, GMI assessed the effects of aircraft exhaust on lower stratospheric ozone [Kinnison et al., 2001]. To that end, the GMI science team developed 'objective grading criteria', that is, semi-quantitative, objective, observation-based tests that were used to grade the behavior of simulations. To assess the effects of a supersonic aircraft fleet flying mostly in the northern hemisphere, the tests focused primarily on northern hemisphere lower stratospheric temperature and transport characteristics. Three simulations using different meteorological data sets (from GISS, MACCM2 (ancestor of WACCM), and GEOS-Strat) were objectively graded to determine which one was the most realistic [Douglass et al., 1999].
For much of its history, the GMI CTM served as a testbed for different model inputs. The modular framework of the GMI CTM, described in Rotman et al. , offered the ability to incorporate different components and inputs, such as meteorological fields, chemical and microphysical mechanisms, source gas emissions, deposition schemes, and other processes determining atmospheric composition. It was compliant with the Earth System Modeling Framework (ESMF), thus facilitating incorporation of new model components. GMI was used as a tool to expand parameter space in sensitivity studies and test parameterizations in general circulation models (GCMs). GMI has always sought to understand and constrain the uncertainties in model results through intercomparison of simulations and testing with observations – a high priority for this project.
Dr. Jose Rodriguez was the Project Scientist for GMI from its inception around 1995 until his retirement in 2016. Dr. Susan Strahan has served as the Project Manager since 2004 and continues to support new simulations and updates to the mechanisms. The GMI CTM can currently be compiled with 4 chemical mechanisms: troposphere-stratosphere, aerosol, coupled troposphere-stratosphere-aerosol, and a tracer suite for process diagnostics. In the first 10-15 years of GMI, mechanisms for the troposphere, stratosphere, and aerosols were separately developed and tested. The work on these mechanisms was respectively led by Dr. Jennifer Logan (Harvard University, now retired), Dr. Anne Douglass (NASA/GSFC, now retired), and Dr. Joyce Penner (University of Michigan). The combined stratosphere-troposphere mechanism was initially implemented and evaluated by Dr. Bryan Duncan (NASA/GSFC) and Dr. Strahan in 2004. Dr. Huisheng Bian (NASA/GSFC), with assistance from Mr. Steve Steenrod, was responsible for the development and testing of the coupled aerosol-chemistry mechanism. Dr. Strahan and Mr. Steve Steenrod developed and implemented the tracer mechanism. This mechanism, offering dozens of tracer options, can be used to diagnose advective and convective transport on varying time scales, deposition, scavenging, and more.
Over the past 2 decades GMI has developed tests that include temperature, transport barrier formation, tropical ascent, polar descent, and meridional transport and mixing in the upper troposphere and stratosphere. Some of these tests became part of the evaluations used in the Chemistry-Climate Model Evaluation (CCMVal) for Stratospheric Processes and their Role in Climate [SPARC, 2010]. More information on transport and chemistry tests can be found in publications by Douglass et al. , Strahan and Douglass , Douglass et al. , Considine et al. , Strahan and Polansky , and Strahan et al. [2007, 2009, 2011, 2013, 2016]. Evaluation methods developed by GMI members have been used as a basis to understand the differences between chemistry climate model projections of ozone recovery, and to demonstrate why models with realistic transport provide better ozone predictions [Douglass et al., 2012 & 2014].
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.J. 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.
Douglass, A.R., P.S. Connell, R.S. Stolarski, and S.E. Strahan (2004), Radicals and reservoirs in the GMI chemistry and transport model: comparison to measurements, J. Geophys. Res., 109, D16302, doi:10.1029/2004JD004632.
Douglass, A.R., R.S. Stolarski, S.E. Strahan, and L.D. Oman (2012), Understanding Differences in Upper Stratospheric Ozone Response to Changes in Chlorine and Temperature as Computed Using CCMVal Models, J. Geophys. Res., 117, doi:10.1029/2012JD017483.
Douglass, A.R., S.E. Strahan, L.D. Oman, and R.S. Stolarski (2014), Understanding differences in chemistry climate model projections of stratospheric ozone, J. Geophys. Res., 119, doi:10.1029/2013JD021159.
Kinnison, D.E., P. S. Connell, J. M. Rodriguez, D. A. Rotman, D. B. Considine, J. Tannahill, R. Ramaroson, P. J. Rasch, A. R. Douglass, S. L. Baughcum, L. Coy, D. W. Waugh, S. R. Kawa, and M. J. Prather (2001), The Global Modeling Initiative Assessment Model: Application to High-Speed Civil Transport Perturbation, J. Geophys. Res., 106, 1693-1711.
Rotman, D.A., J.R. Tannahill, D.E. Kinnison, P.S. Connell, D. Bergmann, D. Proctor, J.M. Rodriguez, S.J. Lin, R.B. Rood, M.J. Prather, P.J. Rasch, D.B. Considine, R. Ramaroson, S.R. Kawa (2001), The Global Modeling Initiative assessment model: Model description, integration and testing of the transport shell, J. Geophys. Res., 106, 1669-1691.
SPARC CCMVal (2010), SPARC Report on the Evaluation of Chemistry-Climate Models, V. Eyring, T.G. Shepherd, D.W. Waugh (Eds.), SPARC Report No. 5, WCRP-132, WMO/TD-No. 1526,
Strahan, S.E. and A.R. Douglass (2004), Evaluating the credibility of transport processes in simulations of ozone recovery using the Global Modeling Initiative three-dimensional model, J. Geophys. Res., 109, D05110, doi:10.1029/2003JD004238.
Strahan, S.E. and B.C. Polansky (2006), Meteorological implementation issues in chemistry and transport models,Atmos. Chem. Phys., 6, 2895-2910.
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., M.R. Schoeberl, and S.D. Steenrod (2009), The impact of tropical recirculation on polar composition, Atmos. Chem. Phys., 9, 2471-2480.
Strahan, S.E., A.R. Douglass, R.S. Stolarski, et al. (2011), Using transport diagnostics to understand chemistry climate model ozone simulations, J. Geophys. Res., 116, doi:10.1029/2010JD015360.
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, doi:10.1002/jgrd.50181.
Strahan, S. E., A.R. Douglass, S.D. Steenrod (2016), Chemical and Dynamical Impacts of Stratospheric Sudden Warmings on Arctic Ozone Variability, J. Geophys. Res., 121, 11,836–11,851, doi:10.1002/2016JD025128