Contrails remain one of the most uncertain impacts of aviation on climate. Even the commonly-measured effect of radiative forcing is difficult to measure because the radiative effects of contrails depend on many parameters including contrail coverage, effective particle size, optical thickness, altitude, temperature, underlying background, latitude, and time of day and year.

Most previous attempts to simulate contrail climate effects on the global scale have estimated contrail cirrus coverage as a function of the model's relative humidity. Although the atmospheric conditions necessary for contrail formation are well defined, the diagnosis or prediction of such clouds is still complicated by uncertainties in modeling the atmospheric state in the upper troposphere. Considerable uncertainty remains in the coverage, optical depths and radiative forcings by climate-model-scale contrail simulations.

To improve the parameterization of contrails within climate-scale models, we combine meteorological data from high-resolution numerical weather analyses including the Rapid Update Cycle (RUC) and the University of Oklahoma Center for Analysis and Prediction of Storms Advanced Regional Prediction System (ARPS) with geostationary and high-resolution satellite data to formulate a conceptual model that can simulate the spreading and dissipation of contrails by using the meteorological conditions specified by the numerical models.  A case study comparing the radiative forcings of a simulated contrail outbreak over the ARM Southern Great Plains site in Oklahoma with the surface and satellite-measured forcings is also planned.