A numerical study of the impact of vegetation cover on cold-air pool formation in an idealized valley

While a great deal is known about cold-air pool formation, maintenance, and erosion inside basins and valleys, and a number of numerical modeling studies have examined the impact of land cover on slope flows, relatively little is known of the impact of vegetation cover on cold-air pool evolution. A lack of observations makes numerical modeling a useful tool, but until recently the dual requirements of fine grid spacing and the presence of a canopy sub-model made investigating this problem difficult.

In this study, fine-scale numerical simulations using the Advanced Regional Prediction System (ARPS) are performed to examine the impact of vegetation on diurnal cold-air pool development inside an idealized valley. Recently, the Advanced Regional Prediction System (ARPS) atmospheric model has been modified to allow simulation of flow through a multi-layer canopy (ARPS-CANOPY). The effects of vegetation elements (e.g., branches, leaves) on drag, turbulence production/dissipation, radiation transfer, and the surface energy budget are accounted for through modifications to the original ARPS model equations and physical parameterization schemes.

We examine the impact of vegetation cover inside an idealized valley on cold-air pool evolution in four cases: (i) vegetation along the lower valley sidewall, (ii) vegetation along the upper valley sidewall, (iii) both lower and upper valley sidewall vegetation, and (iv) no vegetation. For each vegetation case, profiles of frontal area density (Af) are specified, where Af is defined as the frontal area of canopy elements (e.g., leaves, needles) per unit ground area per unit vertical distance in the canopy. Cold-air pool characteristics are compared between cases during the development of the cold-air pool and once the cold-air pool reaches maturity. Findings gleaned from this study have relevance to numerical prediction of cold pool development as well as air quality prediction.