Simulations of Mesoscale Flow Systems around Dugway Proving Ground Using the WRF Modeling System

It is widely recognized that regions with complex heterogeneous topography and land-use properties produce a variety of diurnal mesoscale and microscale flows, which can be modified or even masked by significant large-scale synoptic forcing. These flows can be produced through both dynamic and thermal-forcing processes. Recent field programs such as the Terrain-induced Rotor Experiment (T-REX), Mountain Terrain Atmospheric Modeling and Observations Program (MATERHORN), and Perdigao have been used to observe and model flow behaviors under different topographical and large-scale meteorological conditions. Using the Advanced research version of the Weather Research and Forecast (WRF-ARW) model, we applied multi-nesting using an interactive one-way nesting approach to resolve to a sub-kilometer inner-grid spacing (0.452 km). Our interest was in the intensive observation period 6 (IOP6) of the Fall 2012 MATERHORN campaign conducted over Dugway Proving Ground (DPG) in Utah. An initial review of the IOP6 suggested that a range of diurnal flows were present, and that a relatively small subset of model setup configurations would be able to capture the general flows of this period. The review also led us to believe that this same subset would be able to capture differences due to variations in choice of model boundary-layer physics, land surface physics, land use/soil type specifications, and larger-scale meteorological conditions. A high model vertical resolution was used, with 90 vertical sigma levels applied. The IOP6 spanned the period of 2012 0800 UTC 14 October–0800 UTC 15 October. Based upon a lack of deep convection and moist microphysics throughout IOP6, we included comparison of planetary boundary layer (PBL) turbulence parameterization schemes even at the sub-kilometer grid spacing. We focused upon the gross model performance over our inner nest; therefore, a detailed comparison of the effects of model horizontal resolution are excluded. For surface parameters of wind and temperature, we compare mean absolute error and bias scores throughout the period at a number of surface meteorological observing sites. We found that despite attention given to the boundary layer turbulence physics, radiation physics and model vertical resolution, the results seemed to indicate more impact from the choices of thermal soil conductivity parameterization, land surface/soil texture category classification (and associated static property-parameter values), and large-scale fo