Numerical simulations of flow over steep terrain using 11 different nonhydrostatic numerical models are compared and analyzed. A basic benchmark case and five other test cases are simulated in a two-dimensional framework using an identical initial state is based on conditions on 25 March 2006 during Intensive Observation Period (IOP) 6 of the Terrain-Induced Rotor Experiment (T-REX), in which intense mountain-wave activity was observed. All of the models use an identical horizontal resolution of 1 km and the same vertical resolution. The six simulated test cases use various terrain heights: a 100-m bell shaped hill, a 1000-m idealized ridge that is steeper on the lee slope, a 2500-m ridge, and a cross Sierra terrain profile. The models are tested with both free slip and no slip lower boundary conditions.The results indicate a surprisingly diverse spectrum of simulated mountain wave characteristics including lee waves, hydraulic-like jump features, and gravity wave breaking. The vertical velocity standard deviation is over a factor of two larger in the free slip experiments relative to the no slip simulations. Nevertheless, the no slip simulations exhibit considerable variations in the wave characteristics. The vertical flux of horizontal momentum profiles vary significantly among the models, particularly for the case with realistic Sierra terrain. The results imply relatively low predictability of key characteristics of topographically-forced flows such as the strength of downslope winds and stratospheric wave breaking. The vertical flux of horizontal momentum, which is a domain integrated quantity, exhibits considerable spread among the models, particularly for the experiments with the 2500-m ridge and Sierra terrain. The diversity among the various model simulations, all initialized with identical initial states, suggests that model dynamical cores may be an important component of diversity for the design of mesoscale ensemble systems for topographically-forced flows. The inter-model differences are significantly larger than sensitivity experiments within a single modeling system. IntroductionThe fundamental linear theory for the generation of inviscid mountain waves forced by stratified air flow over two-dimensional obstacles has been established for several decades (e.g., Queney et al. 1960;Smith 1979;Smith 1989). Vertically propagating mountain waves often amplify in the stratosphere due to the decrease of atmospheric density with altitude and nonlinear processes, which may lead to overturning and turbulent breakdown (e.g., Lindzen 1988;Bacmeister and Schoeberl 1989). Mountain waves can have an important impact on the atmosphere due to their role in downslope windstorms (Klemp and Lilly 1975), clear-air turbulence (Clark et al. 2000), vertical mixing of water vapor, aerosols, and chemical constituents in the stratosphere (Dörnbrack and Dürbeck 1998), potential vorticity generation (Schär and Durran 1997), and orographic drag influence on the general circulation (Bretherton 1969;Ólafsson and Bougeau...

The Developmental Testbed Center used the Hurricane Weather Research and Forecasting (HWRF) system to test the sensitivity of tropical cyclone track and intensity forecasts to different convective schemes. A control configuration that employed the HWRF Simplified Arakawa Scheme (SAS) was compared with the Kain-Fritsch and Tiedtke schemes, as well as with a newer implementation of the SAS. A comprehensive test for Atlantic and Eastern North Pacific storms shows that the SAS scheme produces the best track forecasts. Even though the convective parameterization was absent in the inner 3 km nest, the intensity forecasts are sensitive to the choice of cumulus scheme on the outer grids. The impact of convective-scale heating on the environmental flow accumulates in time since the hurricane vortex is cycled in the HWRF model initialization. This study shows that, for a given forecast, the sensitivity to cumulus parameterization combines the influence of physics and initial conditions.

The Developmental Testbed Center (DTC) tested two convective parameterization schemes in the Hurricane Weather Research and Forecasting (HWRF) Model and compared them in terms of performance of forecasting tropical cyclones (TCs). Several TC forecasts were conducted with the scale-aware Simplified Arakawa Schubert (SAS) and Grell–Freitas (GF) convective schemes over the Atlantic basin. For this sample of over 100 cases, the storm track and intensity forecasts were superior for the GF scheme compared to SAS. A case study showed improved storm structure for GF when compared with radar observations. The GF run had increased inflow in the boundary layer, which resulted in higher angular momentum. An angular momentum budget analysis shows that the difference in the contribution of the eddy transport to the total angular momentum tendency is small between the two forecasts. The main difference is in the mean transport term, especially in the boundary layer. The temperature tendencies indicate higher contribution from the microphysics and cumulus heating above the boundary layer in the GF run. A temperature budget analysis indicated that both the temperature advection and diabatic heating were the dominant terms and they were larger near the storm center in the GF run than in the SAS run. The above results support the superior performance of the GF scheme for TC intensity forecast.

Abstract. Four multiscale numerical simulations of convective events are analyzed to determine the essential characteristics of a numerical model which lead to useful simulations of convective events. Although several universities and weather forecasting centers are currently running high-resolution forecast models, the predictability of convective events, especially in the warm season, is still an issue among researchers and forecasters in the meteorological community. This study shows that explicit simulations of convection depend on the high spatial resolution of physiography (particularly topography and top soil moisture), efficient communication between grids of different scales, and initialization procedures that incorporate mesoscale storm features. The purpose here is to contribute to the debate on predictability of convective events through the discussion of four simulations of midlatitude warm season convective events using a multiscale model. For each case, the most important forcing mechanisms that determined the timing and location of the events were identified, and the performance of the simulation in capturing the forcing mechanisms was analyzed. As a first approach to the problem, a subjective analysis of the forcing mechanisms was performed through the inspection of the observations and model fields at the time of convective development. Although we recognize that this case study approach may not provide general results, we believe that it can offer useful insight into the problem.These simulations were originally designed to study the dynamics of the specific convective events and not to forecast the events in real time. ]. The primary difference between the real-time efforts cited above and the approach used here is that we used a two-way-nested grid system. Single grids driven by previously computed forecast lateral boundaries were used in the other setups. Also, in the case of the CAPS setup, the lateral boundaries were generated by another model. Two advantages of the setup used here are the physical and numerical compatibility between the inner grid and its boundaries and the frequency with which the boundaries are updated (every time step). The main disadvantage is, of course, an increase in computer time. RAMS supports any number of two-way interactive nested grids. Since all grids except the coarsest can move to follow a meteorological feature, much memory and computer time can be saved for large mesoscale grids. Although each simulation used a different grid configuration, all simulations were multiscale in the sense that a large coarse grid (of the order of 80-km grid spacing) was used to capture synoptic scale features such as fronts and troughs, and nesting was done to allow explicit representation of moist convection in a subdomain. In some instances (as shown in Table 1), nested grids were initialized later in the simulation to save computer time. The timing to introduce a new grid was subjectively determined by inspection of the next coarsest grid for signs that convection was ...