Search Results

You are looking at 1 - 10 of 11 items for

  • Author or Editor: Rangarao V. Madala x
  • Refine by Access: All Content x
Clear All Modify Search
Rangarao V. Madala

Abstract

A new method for the numerical solution of elliptic difference equations called stabilized error vector propagation (SEVP) is derived. This method has most of the advantages of the error vector propagation algorithm and, in addition, is stable for all grid sizes. By solving Poisson's equation with Dirichlet boundary conditions, SEVP is found to be 3 to 10 times faster than competitive direct methods on a vector computer and requires an order of magnitude smaller computer memory. SEVP is at least 10 times faster than successive overrelaxation. Applications of this method to algorithms using both five- and nine- point stencils as well as stretched grids are discussed.

Full access
Simon Wei-Jen Chang and Rangarao V. Madala

Abstract

No abstract available.

Full access
Keith D. Sashegyi and Rangarao V. Madala

Abstract

The vertical-mode initialization procedure of Bourke and MeGregor is applied to a limited-area weather prediction model that is formulated in flux form and is shown to be successful in reducing the undesirable gravity-wave oscillations in integrations of the numerical model. Alternative boundary conditions are developed for the scheme so that the changes to the wind at the lateral boundaries of the model are consistent with the changes in the integrated mass divergence and vorticity over the domain. The convergence of the modified scheme is shown to be rapid for two different grids. For a grid with significant topography along the lateral boundaries, use of increased diffusion in the boundary zone is shown to negatively impact the convergence of the scheme. Model integrations are performed to show the effectiveness of the scheme with improved boundary conditions in removing the gravity-wave oscillations. The results are compared with the damping of the gravity waves in the boundary zone by the time-integration scheme and by different lateral boundary treatments. The influence of noisy boundary values is also tested.

Full access
Simon W. Chang and Rangarao V. Madala

Abstract

A three-dimensional numerical model with a domain of 3000 km×3000 km and horizontal resolution of 60 km is used to study the influence of sea surface temperature (SST) on the behavior of tropical cyclones translating with mean flows in the Northern Hemisphere.

We find that tropical cyclones tend to move into regions of warmer SST when a gradient of SST is perpendicular to the mean ambient flow vector (MAFV). The model results also indicated that a region of warmer SST situated to the right side of the MAFV is more favorable for storm intensification than to the left side due to the asymmetries in air-sea energy exchanges associated with translating tropical cyclones. The model tropical cyclone intensifies and has greater rightward deflection in its path relative to the MAFV when translating into the region of warmer SST. The model tropical cyclone intensifies when its center travels along a warm strip, while it weakens along, but does not move away from, a cool strip.

The results suggest that the SST distribution not only affects the intensity and path of tropical cyclones frictionally, but also affects them thermally. The enhanced evaporation and convergence over the warm SST provide a favorable condition for the growth of the tropical cyclone, and lead to a gradual shift of the storm center toward the warm ocean.

Full access
Dewey E. Harms, Sethu Raman, and Rangarao V. Madala

Four-dimensional data-assimilation methods, along with the most commonly used objective analysis and initialization techniques, are examined from a historical perspective. Operational techniques, including intermittent data assimilation and Newtonian nudging, and next-generation methods (Kalman–Bucy filtering and the adjoint method) are briefly described. Several methods are compared, with primary emphasis being placed on recent papers dealing with the operational assimilation techniques. Ongoing and future research is outlined, and some important implications of this research are discussed.

Full access
Frank H. Ruggiero, Keith D. Sashegyi, Rangarao V. Madala, and Sethu Raman

Abstract

A technique is described that adds diabatic forcing from stratiform precipitation to a vertical normal-mode initialization of a mesoscale model. The technique uses observed precipitation amounts and cloud-top height estimations with analyzed thermodynamic and kinematic fields to vertically distribute diabatic heating that arises from stratiform precipitation. Simulation experiments reveal the importance of incorporating this heating into the initialization. An adiabatic initialization recovered about 65%–75% of the maximum upward vertical motions, whereas a diabatic initialization, with respect to stratiform precipitation, recovered nearly all the original vertical motions. A real-data case study is presented using combined rain gauge-satellite precipitation analyses with cloud-top heights estimated from Geostationary Operational Environmental Satellite infrared brightness temperatures. The short-term precipitation forecasts from a diabatically initialized model, with respect to stratiform precipitation, demonstrate improvement over forecasts from an adiabatically initialized model.

Full access
Keith D. Sashegyi, Dewey E. Harms, Rangarao V. Madala, and Sethu Raman

Abstract

The successive correction scheme of Bratseth, which converges to optimum interpolation, is applied for the numerical analysis of data collected during the Genesis of Atlantic Lows Experiment. A first guess for the analysis is provided by a 12-h forecast produced by integrating a limited-area model from a prior coarse operational analysis. Initially, univariate analyses of the mass and wind fields are produced. To achieve the coupling of the mass and wind fields, additional iterations on the geopotential are performed by extrapolating the geopotential to grid points, using improving estimates of the geostrophic wind. This improved geostrophic wind is then used to update the geostrophic component of the initial univariate wind analysis. Use of a background forecast produces much improved mesoscale structures in the analysis. Enhanced gradients of the geopotential and larger wind shears are the result of the coupling of the mass and wind fields, particularly in regions of lower data density. Application of the vertical mode initialization scheme of Bourke and McGregor is used to diagnose the divergent component of the mesoscale circulations produced with the analysis scheme.

Full access
Frank H. Ruggiero, Keith D. Sashegyi, Rangarao V. Madala, and Sethu Raman

Abstract

A system for the frequent intermittent assimilation of surface observations into a mesoscale model is described. The assimilation begins by transforming the surface observations to model coordinates. Next, the lowest-level model fields of potential temperature, relative humidity, u and v component winds, and surface pressure are updated by an objective analysis using the successive correction approach. The deviations of the analysis from the first guess at the lowest model layer are then used to adjust the other model layers within the planetary boundary layer. The PBL adjustment is carried out by using the model's values of eddy diffusivity, which are nudged to reflect the updated conditions, to determine the influence of the lowest-layer deviations on the other model layers. Results from a case study indicate that the frequent intermittent assimilation of surface data can provide superior mososcale analyses and forecasts compared to assimilation of synoptic data only. The inclusion of the PBL adjustment procedure is an important part of generating the better forecasts. Extrapolation of the results here suggests that two-dimensional data can be successfully assimilated into a model provided there is a mechanism to smoothly blend the data into the third dimension.

Full access
Frank H. Ruggiero, Keith D. Sashegyi, Alan E. Lipton, Rangarao V. Madala, and Sethu Raman

Abstract

A satellite–model coupled procedure for assimilating geostationary satellite sounder data was adapted to a mesoscale analysis and forecast system jointly developed by the Naval Research Laboratory and the Air Force Research Laboratory. The coupled procedure involves the use of the model output fields as the first guess for the thermodynamic retrievals. Atmospheric thermodynamic profiles and ground temperatures were retrieved from observed radiances of the VISSR Atmospheric Sounder (VAS) on board the Geostationary Operational Environmental Satellite. The successive corrections objective analysis scheme in the mesoscale analysis and forecast system was modified to consider the horizontal spatial correlation of the satellite data. The procedure was tested using a wintertime case from the 1986 Genesis of Atlantic Lows Experiment project. The retrievals generated by the coupled method were modestly improved relative to independent stand-alone retrievals. Coupled analyses and forecasts of temperature and moisture fields compared favorably to forecasts from a control run without the VAS assimilation.

Full access
Dewey E. Harms, Rangarao V. Madala, Sethu Raman, and Keith D. Sashegyi

Abstract

Diabatic forcing has been incorporated into a nonlinear normal-mode initialization scheme to provide more realistic initial conditions and to alleviate the problem of the spinup time of the Naval Research Laboratory Limited-Area Numerical Weather Prediction Model. Latent heating profiles are computed from the observed rainfall and from the model-generated convective rainfall at locations where there were no observations. The latent heating is distributed in the vertical according to the cumulus convective parameterization scheme (Kuo scheme) of the model. The results of a case study from the Genesis of Atlantic Lows Experiment indicated that model spinup of forecast rainfall can be reduced when diabatic initialization with merging of heat and/or rain is used.

Full access