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observed and idealized flows in this study are performed using the atmospheric module of the Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS; Hodur 1997 ). The COAMPS model is based on a finite-difference approximation to the fully compressible, nonhydrostatic equations and uses a terrain-following vertical coordinate transformation. In the real data forecasts, the finite-difference schemes are of second-order accuracy in time and space, while the idealized simulations use a fourth
observed and idealized flows in this study are performed using the atmospheric module of the Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS; Hodur 1997 ). The COAMPS model is based on a finite-difference approximation to the fully compressible, nonhydrostatic equations and uses a terrain-following vertical coordinate transformation. In the real data forecasts, the finite-difference schemes are of second-order accuracy in time and space, while the idealized simulations use a fourth
propagation of uncertainties in the specification of initial conditions, the predictability of forecasts for mesoscale motions with spatial scales on the order of 10 km would be limited to time scales on the order of 1 h. This discouraging prospect has largely been supplanted by a more optimistic view based on experiences with high-resolution NWP models demonstrating that realistic mesoscale circulations can be generated during the forecast without having to specify mesoscale precursors to these
propagation of uncertainties in the specification of initial conditions, the predictability of forecasts for mesoscale motions with spatial scales on the order of 10 km would be limited to time scales on the order of 1 h. This discouraging prospect has largely been supplanted by a more optimistic view based on experiences with high-resolution NWP models demonstrating that realistic mesoscale circulations can be generated during the forecast without having to specify mesoscale precursors to these
1. Introduction Accurately forecasting orographically generated internal gravity waves is a significant challenge for mesoscale numerical weather prediction (NWP) models. More commonly known as mountain waves, these features occur when stably stratified air is forced over a topographic barrier. While NWP models have steadily advanced over the last several decades, opportunities to verify model forecasts of mountain waves against observations are limited to a handful of field campaigns. Several
1. Introduction Accurately forecasting orographically generated internal gravity waves is a significant challenge for mesoscale numerical weather prediction (NWP) models. More commonly known as mountain waves, these features occur when stably stratified air is forced over a topographic barrier. While NWP models have steadily advanced over the last several decades, opportunities to verify model forecasts of mountain waves against observations are limited to a handful of field campaigns. Several
including sensitivity of mountain-wave predictions to the model formulation. During the Terrain-Induced Rotor Experiment (T-REX; Grubišić et al. 2008 ), high-resolution forecasts were routinely conducted to assist in mission planning using a number of different three-dimensional nonhydrostatic numerical models such as the Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS 1 ; Hodur 1997 ), two dynamical cores of the Weather Research and Forecasting model (WRF), namely the Advanced Research
including sensitivity of mountain-wave predictions to the model formulation. During the Terrain-Induced Rotor Experiment (T-REX; Grubišić et al. 2008 ), high-resolution forecasts were routinely conducted to assist in mission planning using a number of different three-dimensional nonhydrostatic numerical models such as the Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS 1 ; Hodur 1997 ), two dynamical cores of the Weather Research and Forecasting model (WRF), namely the Advanced Research
1. Introduction Over mountain areas the evolution of the boundary layer is particularly complex as a result of the interaction between boundary layer turbulence and thermally induced mesoscale wind systems, such as the slope and valley winds (e.g., Rotach et al. 2008 ). As the horizontal resolution of operational forecasts progresses to finer resolution, a larger spectrum of thermally induced wind systems can be explicitly resolved. It is therefore useful to document the current state
1. Introduction Over mountain areas the evolution of the boundary layer is particularly complex as a result of the interaction between boundary layer turbulence and thermally induced mesoscale wind systems, such as the slope and valley winds (e.g., Rotach et al. 2008 ). As the horizontal resolution of operational forecasts progresses to finer resolution, a larger spectrum of thermally induced wind systems can be explicitly resolved. It is therefore useful to document the current state
1. Introduction and overview of the event Foehn, as defined by the WMO (1992) , is a “wind warmed and dried [adiabatically] by descent, in general on the lee side of a mountain.” Crucial to foehn is that the virtual potential temperature of the descending upstream air mass is at least as low as the virtual potential temperature in the downstream valley. This requirement was shown by Mayr and Armi (2008) for the Alps with data from the Mesoscale Alpine Programme ( Mayr et al. 2004 ). As a
1. Introduction and overview of the event Foehn, as defined by the WMO (1992) , is a “wind warmed and dried [adiabatically] by descent, in general on the lee side of a mountain.” Crucial to foehn is that the virtual potential temperature of the descending upstream air mass is at least as low as the virtual potential temperature in the downstream valley. This requirement was shown by Mayr and Armi (2008) for the Alps with data from the Mesoscale Alpine Programme ( Mayr et al. 2004 ). As a
1. Introduction Moist processes have been largely ignored in the majority of mountain-wave studies, partially because of the complexity associated with moisture and microphysical processes. Studies of the interaction between moist airflow and mesoscale topography can be broadly classified into two categories. The first category includes quasi-analytical studies with highly simplified representations of moist processes. For example, a set of two-dimensional steady-state linear wave solutions
1. Introduction Moist processes have been largely ignored in the majority of mountain-wave studies, partially because of the complexity associated with moisture and microphysical processes. Studies of the interaction between moist airflow and mesoscale topography can be broadly classified into two categories. The first category includes quasi-analytical studies with highly simplified representations of moist processes. For example, a set of two-dimensional steady-state linear wave solutions
(dry) Lake exhibits strong temporal and spatial variations. The dust lofting and transport processes are complicated by small-scale circulations, downslope winds, mountain waves, and turbulence induced by the surrounding high mountains. The objective of this study is to use the PM-10 and meteorological observations obtained during T-REX and a high-resolution numerical simulation to provide some new insights into the role of mesoscale dynamics and turbulence in lofting and transporting fine
(dry) Lake exhibits strong temporal and spatial variations. The dust lofting and transport processes are complicated by small-scale circulations, downslope winds, mountain waves, and turbulence induced by the surrounding high mountains. The objective of this study is to use the PM-10 and meteorological observations obtained during T-REX and a high-resolution numerical simulation to provide some new insights into the role of mesoscale dynamics and turbulence in lofting and transporting fine
understanding of the complex interactions between the synoptic- and mesoscale environments contributes to the difficulty of making accurate wind and pollution forecasts. Several studies have documented high wind events and evaluated model predictions of these storms. Cohn et al. (2004) documented a dramatic windstorm that moved over the Sierra Nevada from the west using two radar wind-profiling systems operated by the National Center for Atmospheric Research (NCAR) in the Reno and Washoe basins east of
understanding of the complex interactions between the synoptic- and mesoscale environments contributes to the difficulty of making accurate wind and pollution forecasts. Several studies have documented high wind events and evaluated model predictions of these storms. Cohn et al. (2004) documented a dramatic windstorm that moved over the Sierra Nevada from the west using two radar wind-profiling systems operated by the National Center for Atmospheric Research (NCAR) in the Reno and Washoe basins east of
forecasters, climatologists, mesoscale and regional climate modelers, and for selecting optimal sites and timing of observational field campaigns, 1 existence of such climatologies is clearly important. Additionally, availability of climatologies for different mountain ranges that are known for the generation of lee waves ( Auer 1992 ; Mitchell et al. 1990 ; Smith 1976 ; Vosper and Mobbs 1996 ) would allow for easier generalization of physical process study findings obtained in one region to other
forecasters, climatologists, mesoscale and regional climate modelers, and for selecting optimal sites and timing of observational field campaigns, 1 existence of such climatologies is clearly important. Additionally, availability of climatologies for different mountain ranges that are known for the generation of lee waves ( Auer 1992 ; Mitchell et al. 1990 ; Smith 1976 ; Vosper and Mobbs 1996 ) would allow for easier generalization of physical process study findings obtained in one region to other
