Vijay Tallapragada
National Oceanic and Atmospheric Administration
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Publication
Featured researches published by Vijay Tallapragada.
Journal of the Atmospheric Sciences | 2013
Sundararaman G. Gopalakrishnan; Frank D. Marks; Jun A. Zhang; Xuejin Zhang; Jian-Wen Bao; Vijay Tallapragada
AbstractThe Hurricane Weather Research and Forecasting (HWRF) system was used in an idealized framework to gain a fundamental understanding of the variability in tropical cyclone (TC) structure and intensity prediction that may arise due to vertical diffusion. The modeling system uses the Medium-Range Forecast parameterization scheme. Flight-level data collected by a NOAA WP-3D research aircraft during the eyewall penetration of category 5 Hurricane Hugo (1989) at an altitude of about 450–500 m and Hurricane Allen (1980) were used as the basis to best match the modeled eddy diffusivities with wind speed. While reduction of the eddy diffusivity to a quarter of its original value produced the best match with the observations, such a reduction revealed a significant decrease in the height of the inflow layer as well which, in turn, drastically affected the size and intensity changes in the modeled TC. The cross-isobaric flow (inflow) was observed to be stronger with the decrease in the inflow depth. Stronger...
Monthly Weather Review | 2014
Vijay Tallapragada; Chanh Kieu; Young Kwon; Samuel Trahan; Qingfu Liu; Zhan Zhang; In-Hyuk Kwon
AbstractIn this work, a high-resolution triple-nested implementation of the National Centers for Environmental Prediction (NCEP) operational Hurricane Weather Research and Forecasting Model (HWRF) for the 2012 hurricane season is evaluated. Statistics of retrospective experiments for the 2010–11 hurricane seasons show that the new configuration demonstrates significant improvement compared to the 2011 operational HWRF in terms of storm track, intensity, size, dynamical constraints between mass and wind field, and initial vortex imbalance. Specifically, the 5-day track and intensify forecast errors are improved by about 19% and 7% for the North Atlantic basin, and by 9% and 30% for the eastern Pacific basin, respectively. Verifications of storm size in terms of wind radii at 34-, 50-, and 64-kt (17.5, 25.7, and 32.9 m s−1) thresholds at different quadrants show dramatic improvement with most of the overestimation of the storm size in previous operational HWRF versions removed at all forecast times. In addi...
Monthly Weather Review | 2015
Jun A. Zhang; David S. Nolan; Robert F. Rogers; Vijay Tallapragada
AbstractAs part of the Hurricane Forecast Improvement Project (HFIP), recent boundary layer physics upgrades in the operational Hurricane Weather Research and Forecasting (HWRF) Model have benefited from analyses of in situ aircraft observations in the low-level eyewall region of major hurricanes. This study evaluates the impact of these improvements to the vertical diffusion in the boundary layer on the simulated track, intensity, and structure of four hurricanes using retrospective HWRF forecasts. Structural metrics developed from observational composites are used in the model evaluation process. The results show improvements in track and intensity forecasts in response to the improvement of the vertical diffusion. The results also demonstrate substantial improvements in the simulated storm size, surface inflow angle, near-surface wind profile, and kinematic boundary layer heights in simulations with the improved physics, while only minor improvements are found in the thermodynamic boundary layer height...
Bulletin of the American Meteorological Society | 2015
Ligia Bernardet; Vijay Tallapragada; S. Bao; Samuel Trahan; Young Kwon; Qingfu Liu; Mingjing Tong; Mrinal K. Biswas; T. Brown; D. Stark; L. Carson; Richard M. Yablonsky; E. Uhlhorn; S. Gopalakrishnan; Xuejin Zhang; Timothy Marchok; B. Kuo; R. Gall
AbstractThe Hurricane Weather Research and Forecasting Model (HWRF) is an operational model used to provide numerical guidance in support of tropical cyclone forecasting at the National Hurricane Center. HWRF is a complex multicomponent system, consisting of the Weather Research and Forecasting (WRF) atmospheric model coupled to the Princeton Ocean Model for Tropical Cyclones (POM-TC), a sophisticated initialization package including a data assimilation system and a set of postprocessing and vortex tracking tools. HWRF’s development is centralized at the Environmental Modeling Center of NOAA’s National Weather Service, but it incorporates contributions from a variety of scientists spread out over several governmental laboratories and academic institutions. This distributed development scenario poses significant challenges: a large number of scientists need to learn how to use the model, operational and research codes need to stay synchronized to avoid divergence, and promising new capabilities need to be ...
Geophysical Research Letters | 2014
Chanh Kieu; Vijay Tallapragada; Wallace Hogsett
In this study, the tropical cyclone structure at the onset of rapid intensification (RI) is examined using the cloud-permitting version of the Hurricane Weather Research and Forecast (HWRF) model. Idealized experiments with different vortex initial vertical structures in different environments show that the HWRF model vortex possesses a specific constraint in the dynamical and thermodynamic structure at the RI onset including (i) a warm anomaly of 1–3°K, (ii) a moist column with relative humidity > 90% within the storm central region, and (iii) low-level tangential flow ≥12 m s−1. Regardless of vortex structures or environment conditions applied in this study, model vortex does not intensify if the above constraint is not established. Such a requirement in the model moisture and dynamical structure at the RI onset can explain why the RI onset is much delayed in dry experiments as compared to the onset in moist experiments.
Natural Hazards | 2012
Monica Laureano Bozeman; Dev Niyogi; Sundararaman G. Gopalakrishnan; Frank D. Marks; Xuejin Zhang; Vijay Tallapragada
While tropical cyclones (TCs) usually decay after landfall, Tropical Storm Fay (2008) initially developed a storm central eye over South Florida by anomalous intensification overland. Unique to the Florida peninsula are Lake Okeechobee and the Everglades, which may have provided a surface feedback as the TC tracked near these features around the time of peak intensity. Analysis is done with the use of an ensemble model-based approach with the Developmental Testbed Center (DTC) version of the Hurricane WRF (HWRF) model using an outer domain and a storm-centered moving nest with 27- and 9-km grid spacing, respectively. Choice of land surface parameterization and small-scale surface features may influence TC structure, dictate the rate of TC decay, and even the anomalous intensification after landfall in model experiments. Results indicate that the HWRF model track and intensity forecasts are sensitive to three features in the model framework: land surface parameterization, initial boundary conditions, and the choice of planetary boundary layer (PBL) scheme. Land surface parameterizations such as the Geophysical Fluid Dynamics Laboratory (GFDL) Slab and Noah land surface models (LSMs) dominate the changes in storm track, while initial conditions and PBL schemes cause the largest changes in the TC intensity overland. Land surface heterogeneity in Florida from removing surface features in model simulations shows a small role in the forecast intensity change with no substantial alterations to TC track.
Geophysical Research Letters | 2015
Ping Zhu; Zhenduo Zhu; Sundararaman G. Gopalakrishnan; Robert Black; Frank D. Marks; Vijay Tallapragada; Jun A. Zhang; Xuejin Zhang; Cen Gao
Two idealized simulations by the Hurricane Weather Research and Forecast (HWRF) model are presented to examine the impact of model physics on the simulated eyewall replacement cycle (ERC). While no ERC is produced in the control simulation that uses the operational HWRF physics, the sensitivity experiment with different model physics generates an ERC that possesses key features of observed ERCs in real tropical cyclones. Likely reasons for the control simulation not producing ERC include lack of outer rainband convection at the far radii from the eyewall, excessive ice hydrometeors in the eyewall, and enhanced moat shallow convection, which all tend to prevent the formation of a persistent moat between the eyewall and outer rainband. Less evaporative cooling from precipitation in the outer rainband region in the control simulation produces a more stable and dryer environment that inhibits the development of systematic convection at the far radii from the eyewall.
Journal of the Atmospheric Sciences | 2016
Chanh Kieu; Vijay Tallapragada; Da-Lin Zhang; Zachary Moon
AbstractThis study examines the formation of a double warm-core (DWC) structure in intense tropical cyclones (TCs) that was captured in almost all supertyphoon cases during the 2012–14 real-time typhoon forecasts in the northwestern Pacific basin with the Hurricane Weather Research and Forecasting Model (HWRF). By using an idealized configuration of HWRF to focus on the intrinsic mechanism of the DWC formation, it is shown that the development of DWC in intense TCs is accompanied by a thin inflow layer above the typical upper outflow layer. The development of this thin inflow layer in the lower stratosphere (~100–75 hPa), which is associated with an inward pressure gradient force induced by cooling at the cloud top, signifies intricate interaction of TCs with the lower stratosphere as TCs become sufficiently intense, which has not been examined previously. Specifically, it is demonstrated that a higher-level inflow can advect potentially warm air from the lower stratosphere toward the inner-core region, t...
Monthly Weather Review | 2015
Da-Lin Zhang; Lin Zhu; Xuejin Zhang; Vijay Tallapragada
AbstractA series of 5-day numerical simulations of idealized hurricane vortices under the influence of different background flows is performed by varying vertical grid resolution (VGR) in different portions of the atmosphere with the operational version of the Hurricane Weather Research and Forecasting Model in order to study the sensitivity of hurricane intensity forecasts to different distributions of VGR. Increasing VGR from 21 to 43 levels produces stronger hurricanes, whereas increasing it further to 64 levels does not intensify the storms further, but intensity fluctuations are much reduced. Moreover, increasing the lower-level VGRs generates stronger storms, but the opposite is true for increased upper-level VGRs. On average, adding mean flow increases intensity fluctuations and variability (between the strongest and weakest hurricanes), whereas adding vertical wind shear (VWS) delays hurricane intensification and then causes more rapid growth in intensity variability. The stronger the VWS, the lar...
Journal of the Atmospheric Sciences | 2016
Zhaoxia Pu; Shixuan Zhang; Mingjing Tong; Vijay Tallapragada
AbstractAn initial vortex spindown, or strong adjustment to the structure and intensity of a hurricane’s initial vortex, presents a significant problem in hurricane forecasting, as with the NCEP Hurricane Weather Research and Forecasting Model (HWRF), because it can cause significantly degraded intensity forecasts. In this study, the influence of the self-consistent regional ensemble background error covariance on assimilating hurricane inner-core tail Doppler radar (TDR) observations in HWRF is examined with the NCEP gridpoint statistical interpolation (GSI)-based ensemble–three-dimensional variational (3DVAR) hybrid data assimilation system. It is found that the resolution of the background error covariance term, coming from the ensemble forecasts, has notable influence on the assimilation of hurricane inner-core observations and subsequent forecasting results. Specifically, the use of ensemble forecasting at high-resolution native grids results in significant reduction of the vortex spindown problem an...
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Dive into the Vijay Tallapragada's collaboration.
Sundararaman G. Gopalakrishnan
Atlantic Oceanographic and Meteorological Laboratory
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