The First Quasi-Equilibrium Tropical Circulation Model---Implementation and Simulation

Ning Zeng, J. David Neelin and Chia Chou
Department of Atmospheric Sciences and
Institute of Geophysics and Planetary Physics
University of California, Los Angeles

The first quasi-equilibrium tropical circulation model QTCM1 is implemented and tested. The formulation, described by Neelin and Zeng, uses a Galerkin framework in the vertical, but with basis functions tailored to quasi-equilibrium deep convective physics via analytical solutions. QTCM1 retains a single vertical structure of temperature and humidity. For a balanced treatment of dynamics and sub-grid scale physics, a physics parameterization package of intermediate complexity is developed. These include a linearized longwave radiation scheme, a simple cloud prediction method, simple shortwave radiation schemes, and an intermediate land-surface model.

The simulated climatology has a reasonable spatial pattern and seasonal evolution of the tropical convergence zones, including over land regions. Outgoing longwave radiation and net surface heat flux both appear satisfactory. The Asian monsoon is slightly weak but depicts the northward progression of the monsoon onset, and a monsoon wind shear index exhibits interannual variability associated with observed SST that is similar to general circulation model (GCM) results. The extent and position of the main El Ni\~no/Southern Oscillation rainfall anomalies are simulated, as well as a number of the observed tropical and subtropical teleconnections. The seasonal cycle and interannual variability of the Amazon water budget, including evapotranspiration, interception loss, surface and subsurface runoff, illustrate reasonable simulation of the hydrologic cycle. Sensitivity studies on effects of topography, evaporation formulation, and land-surface processes are also conducted. While the results are imperfect with respect to observations, many aspects are comparable to or better than GCMs of the previous generation. Considering the complexity of these simulated phenomena, the model is computationally light and easy to diagnose. It thus provides a new tool filling the niche between GCMs and simpler models.