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moisture, Coriolis forces, and without any physical parameterizations except for turbulent mixing. The lower boundary condition was free slip and the initial conditions consisted of potential flow over the terrain. This simulation used a horizontal resolution of 1 km, which is the same as the resolution of the inner mesh of the case-study simulation. The domain extended for 798 km in the horizontal, while the vertical grid consisted of 135 vertical layers extending to the same 30-km depth as the case
moisture, Coriolis forces, and without any physical parameterizations except for turbulent mixing. The lower boundary condition was free slip and the initial conditions consisted of potential flow over the terrain. This simulation used a horizontal resolution of 1 km, which is the same as the resolution of the inner mesh of the case-study simulation. The domain extended for 798 km in the horizontal, while the vertical grid consisted of 135 vertical layers extending to the same 30-km depth as the case
be well forecast knowing only the regional wind vector. No meteorological information regarding fronts, vertical wind shear, static stability, moisture, or diurnal/seasonal solar insolation is needed. Two mathematical properties of the wave drag matrix are important. Matrix symmetry = T leads to real eigenvalues and orthogonal eigenvectors. This property guarantees that there will be two perpendicular principal wind directions that will generate no transverse drag. A measure of the drag
be well forecast knowing only the regional wind vector. No meteorological information regarding fronts, vertical wind shear, static stability, moisture, or diurnal/seasonal solar insolation is needed. Two mathematical properties of the wave drag matrix are important. Matrix symmetry = T leads to real eigenvalues and orthogonal eigenvectors. This property guarantees that there will be two perpendicular principal wind directions that will generate no transverse drag. A measure of the drag
nonorographic gravity waves over the Southern Ocean emphasize the role of moisture . J. Geophys. Res. , 120 , 1278 – 1299 , doi: 10.1002/2014JD022332 . Preusse , P. , and Coauthors , 2009 : New perspectives on gravity wave remote sensing by spaceborne infrared limb imaging . Atmos. Meas. Tech. , 2 , 299 – 311 , doi: 10.5194/amt-2-299-2009 . Rapp , M. , B. Strelnikov , A. Müllemann , F.-J. Lübken , and D. Fritts , 2004 : Turbulence measurements and implications for gravity wave
nonorographic gravity waves over the Southern Ocean emphasize the role of moisture . J. Geophys. Res. , 120 , 1278 – 1299 , doi: 10.1002/2014JD022332 . Preusse , P. , and Coauthors , 2009 : New perspectives on gravity wave remote sensing by spaceborne infrared limb imaging . Atmos. Meas. Tech. , 2 , 299 – 311 , doi: 10.5194/amt-2-299-2009 . Rapp , M. , B. Strelnikov , A. Müllemann , F.-J. Lübken , and D. Fritts , 2004 : Turbulence measurements and implications for gravity wave
June and are kept constant throughout each simulation, covering 48 h. In the 2D WRF Model, open boundary conditions are used in flow direction. Note that horizontal winds are projected to a wind direction of 300° ( ), which is the direction of the Mt-A-2b transect ( Fig. 1 ). All idealized simulations are run without moisture and radiation effects. From both the WRF and the in situ flight-level data, vertical energy and momentum fluxes are calculated according to the method of Smith et al. (2008
June and are kept constant throughout each simulation, covering 48 h. In the 2D WRF Model, open boundary conditions are used in flow direction. Note that horizontal winds are projected to a wind direction of 300° ( ), which is the direction of the Mt-A-2b transect ( Fig. 1 ). All idealized simulations are run without moisture and radiation effects. From both the WRF and the in situ flight-level data, vertical energy and momentum fluxes are calculated according to the method of Smith et al. (2008
ensemble forecasts described in section 2b(2) employed stochastic kinetic energy backscatter (SKEB), as described in section 2b of Reynolds et al. (2011) , but with an additional convective dissipation mask based on moisture convergence (see section 3b of Reynolds et al. 2011 ) that enhances kinetic energy by introducing vorticity perturbations in areas where convective processes are likely to occur. 2) Data assimilation algorithm (i) Formulation The current NRL Atmospheric Variational DAS (NAVDAS
ensemble forecasts described in section 2b(2) employed stochastic kinetic energy backscatter (SKEB), as described in section 2b of Reynolds et al. (2011) , but with an additional convective dissipation mask based on moisture convergence (see section 3b of Reynolds et al. 2011 ) that enhances kinetic energy by introducing vorticity perturbations in areas where convective processes are likely to occur. 2) Data assimilation algorithm (i) Formulation The current NRL Atmospheric Variational DAS (NAVDAS
