Covers model selection, diagnostics, and forecasting in time series analysis, emphasizing the challenges of determining the model order based on autocorrelation and partial autocorrelation functions.
Explores the parameterization of atmospheric processes, including microphysics, turbulence, radiation, convection, and surface processes, to improve forecast accuracy and quantify uncertainties.