Jesse M. Canfield

A Large-Eddy Simulation Study of Atmospheric Boundary Layer Influence on Stratified Flows over Terrain

AbstractThe impact of atmospheric boundary layer (ABL) interactions with large-scale stably stratified flow over an isolated, two-dimensional hill is investigated using turbulence-resolving large-eddy simulations. The onset of internal gravity wave breaking and leeside flow response regimes of trapped lee waves and nonlinear breakdown (or hydraulic-jump-like state) as they depend on the classical inverse Froude number, Fr−1 = Nh/Ug, is explored in detail. Here, N is the Brunt–Vaisala frequency, h is the hill height, and Ug is the geostrophic wind. The results here demonstrate that the presence of a turbulent ABL influences mountain wave (MW) development in critical aspects, such as dissipation of trapped lee waves and amplified stagnation zone turbulence through Kelvin–Helmholtz instability. It is shown that the nature of interactions between the large-scale flow and the ABL is better characterized by a proposed inverse compensated Froude number, = N(h − zi)/Ug, where zi is the ABL height. In addition, it...

Using the photoload technique with double sampling to improve surface fuel loading estimates.

Accurate surface fuel load estimates based on the planar intercept method require a considerable amount of time and cost. Recently the photoload method has been proposed as an alternative for sampling of fine woody surface fuels. To evaluate the use of photoload fuel sampling, six simulated fuel beds of 100 photoload visual estimates and destructively sampled fuel loads were generated at three levels of fuel loading (0.016, 0.060, and 0.120  kg  m–2) and two levels of variability (coefficients of variation of ~42 and 85%). We assessed the accuracy and precision of simple random sampling with and without double sampling on surface fuel load estimation. Direct visual estimates often overestimated fuel loads where actual fuel loading was low and underestimated fuel loads where fuel loads were large. We found that double sampling with a classical regression estimation approach provided the most accurate and precise fuel load estimates, substantially improving the accuracy and precision achieved over standard photoload estimation when n ≥ 20 and double sampling rate ≥20%. These results indicate that fine woody fuel loading estimation with the photoload technique can be improved by incorporating a double sampling approach.