Abstract
Short range weather forecasting and atmospheric boundary layer (ABL) processes are studied by using a one-dimensional ABL model where the horizontal advection terms are neglected. The ability of the model, the Florida State University atmospheric boundary layer (FSU1DPBL) model, to forecast minimum temperature is investigated in terms of thermal advection effects. The model is used for 12-, 24-, and 36-h forecasts of minimum temperatures. The minimum temperatures obtained from the model forecasts are compared with observations. The investigation is confined to days meeting criteria representative of clear and calm synoptic conditions. Errors between observations and model results are determined using thermal advection analysis in the boundary layer since horizontal thermal advection affects cooling rates at night. The errors are found to be strongly correlated with thermal advection in the lowest part of the ABL. By carrying out some case studies, it is seen that the model is more prone to errors in dry conditions. It is also confirmed that the strong thermal advection aloft getting closer and closer to the ground largely explains the difference in minimum temperatures between the model and observations. The results show that the model is also a useful tool for the short-range weather forecasting since it is not computationally expensive. The model is able to simulate well the nighttime minimum temperatures, and can be used operationally.