Improving Land Surface Processes in TAPM. Part 2: Low Wind Stable Conditions
Low wind conditions (U < 2 m/s), are particularly important for the science of air pollution because it is under these conditions that the highest ground-level concentrations are often experienced, and because the state of the lower atmosphere, governing the dispersion of contaminant plumes, is often least well defined and predictable. Prognostic models, such as CSIRO’s TAPM, based on the standard turbulence theories generally do reasonably well at simulating low winds when the atmospheric is unstable, but perform relatively poorly when the stratification is stable (e.g. on clear nights). In this paper, the original TAPM model together with the following improvements and modifications made to it is examined for its performance for low winds:
• Use of a vegetative canopy, heat diffusion equation for soil temperature, and Richards’ equation for soil moisture content.
• Inclusion of the CABLE land-surface scheme.
• Modifications to the Monin-Obukhov similarity for fluxes at the lowest model level.
For model validation, we use data from the CASES99 field campaign conducted in Kansas (USA) in October 1999 and routinely measured data from the Cardington facility of the UK Meteorological Office. These datasets are well suited for the current model validation purposes because the measurement sites are relatively flat with low vegetation, and involve multilevel measurements of winds and turbulent fluxes from meteorological towers, in addition to other data such as soil moisture, temperature, and humidity. Results on the model performance are presented, and the effects of changes in various model parameters on the predictions are discussed.