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Eric A. Hendricks and Michael T. Montgomery

Abstract

On 9–10 September 2002, multiple mesovortices were captured in great detail by rapid scan visible satellite imagery in subtropical, then later, Tropical Storm Gustav. These mesovortices were observed as low-level cloud swirls while the low-level structure of the storm was exposed due to vertical shearing. They are shown to form most plausibly via vortex tube stretching associated with deep convection; they become decoupled from the convective towers by vertical shear; they are advected with the low-level circulation; finally they initiate new hot towers on their boundaries. Partial evidence of an axisymmetrizing mesovortex and its hypothesized role in the parent vortex spinup is presented. Observations from the mesoscale and synoptic scale are synthesized to provide a multiscale perspective of the intensification of Gustav that occurred on 10 September. The most important large-scale factors were the concurrent relaxation of the 850–200-hPa-deep layer vertical wind shear from 10–15 to 5–10 m s−1 and movement over pockets of very warm sea surface temperatures (approximately 29.5°–30.5°C). The mesoscale observations are not sufficient alone to determine the precise role of the deep convection and mesovortices in the intensification. However, qualitative comparisons are made between the mesoscale processes observed in Gustav and recent full-physics and idealized numerical simulations to obtain additional insight.

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Eric A. Hendricks, Michael T. Montgomery, and Christopher A. Davis

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A high-resolution (3-km horizontal grid spacing) near-cloud-resolving numerical simulation of the formation of Hurricane Diana (1984) is used to examine the contribution of deep convective processes to tropical cyclone formation. This study is focused on the 3-km horizontal grid spacing simulation because this simulation was previously found to furnish an accurate forecast of the later stages of the observed storm life cycle. The numerical simulation reveals the presence of vortical hot towers, or cores of deep cumulonimbus convection possessing strong vertical vorticity, that arise from buoyancy-induced stretching of local absolute vertical vorticity in a vorticity-rich prehurricane environment.

At near-cloud-resolving scales, these vortical hot towers are the preferred mode of convection. They are demonstrated to be the most important influence to the formation of the tropical storm via a two-stage evolutionary process: (i) preconditioning of the local environment via diabatic production of multiple small-scale lower-tropospheric cyclonic potential vorticity (PV) anomalies, and (ii) multiple mergers and axisymmetrization of these low-level PV anomalies. The local warm-core formation and tangential momentum spinup are shown to be dominated by the organizational process of the diabatically generated PV anomalies; the former process being accomplished by the strong vertical vorticity in the hot tower cores, which effectively traps the latent heat from moist convection. In addition to the organizational process of the PV anomalies, the cyclogenesis is enhanced by the aggregate diabatic heating associated with the vortical hot towers, which produces a net influx of low-level mean angular momentum throughout the genesis.

Simpler models are examined to elucidate the underlying dynamics of tropical cyclogenesis in this case study. Using the Sawyer–Eliassen balanced vortex model to diagnose the macroscale evolution, the cyclogenesis of Diana is demonstrated to proceed in approximate gradient and hydrostatic balance at many instances, where local radial and vertical accelerations are small. Using a shallow water primitive equation model, a characteristic “moist” (diabatic) vortex merger in the cloud-resolving numerical simulation is captured in a large part by the barotropic model. Since a moist merger results in a stronger vortex and occurs twice as fast as a dry merger, it is inferred (consistent with related work) that a net low-level convergence can accelerate and intensify the merger process in the real atmosphere.

Although the findings reported herein are based on a sole case study and thus cannot yet be generalized, it is believed the results are sufficiently interesting to warrant further idealized simulations of this nature.

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Eric A. Hendricks, Brian D. McNoldy, and Wayne H. Schubert

Abstract

Hurricane Dolly (2008) exhibited dramatic inner-core structural variability during a 6-h rapid intensification and deepening event just prior to making landfall in southern Texas at 1800 UTC 23 July. In particular, the eyewall was highly asymmetric from 0634–1243 UTC, with azimuthal wavenumber m = 4–7 patterns in the eyewall radar reflectivity and prominent mesovortex and polygonal eyewall signatures. Evidence is presented that the most likely cause of the high-wavenumber asymmetries is a convectively modified form of barotropic instability of the thin eyewall potential vorticity ring. The rapid intensification and deepening event occurred while Dolly was in a favorable environment with weak deep-layer vertical wind shear and warm sea surface temperatures; however, the environmental conditions were becoming less favorable during the period of rapid intensification. Therefore, it is plausible that the internal vortex dynamics were dominant contributors to the rapid intensification and deepening.

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Eric A. Hendricks, Melinda S. Peng, Xuyang Ge, and Tim Li

Abstract

A dynamic initialization scheme for tropical cyclone structure and intensity in numerical prediction systems is described and tested. The procedure involves the removal of the analyzed vortex and, then, insertion of a new vortex that is dynamically initialized to the observed surface pressure into the numerical model initial conditions. This new vortex has the potential to be more balanced, and to have a more realistic boundary layer structure than by adding synthetic data in the data assimilation procedure to initialize the tropical cyclone in a model. The dynamic initialization scheme was tested on multiple tropical cyclones during 2008 and 2009 in the North Atlantic and western North Pacific Ocean basins using the Naval Research Laboratory’s tropical cyclone version of the Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS-TC). The use of this initialization procedure yielded significant improvements in intensity forecasts, with no degradation in track performance. Mean absolute errors in the maximum sustained surface wind were reduced by approximately 5 kt for all lead times up to 72 h.

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Eric A. Hendricks, Melinda S. Peng, and Tim Li

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Three different dynamic initialization schemes for tropical cyclone (TC) prediction in numerical prediction systems are described and evaluated. The first scheme involves the removal of the analyzed vortex, followed by the insertion of a dynamically initialized vortex into the model analyses. This scheme is referred to as the tropical cyclone dynamic initialization scheme (TCDI) because the TC component is nudged to the observed surface pressure in an independent three-dimensional primitive equation model prior to insertion. The second scheme is a 12-h relaxation to the analyses' horizontal momentum before the forecast integration begins, and is called the dynamic initialization (DI) scheme. The third scheme is a combination of the previous two schemes, and is called the two-stage dynamic initialization scheme (TCDI/DI). In the first stage, TCDI is implemented in order to improve the representation of the TC vortex. In the second stage, DI is invoked in order to improve the balance between the inserted TC vortex and its environment. All three dynamic initialization schemes are compared with a control (CNTL) scheme, which creates the initial vortex using synthetic TC observations that match the observed intensity and structure in a three-dimensional variational data assimilation (3DVAR) system. The four schemes are tested on 120 cases in the North Atlantic and western North Pacific basins during 2010 and 2011 using the Naval Research Laboratory's TC prediction model: Coupled Ocean–Atmosphere Mesoscale Prediction System-Tropical Cyclones (COAMPS-TC). It is demonstrated that TCDI/DI performed the best overall with regard to intensity forecasts, reducing the average minimum central pressure error for all lead times by 24.4% compared to the CNTL scheme.

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Eric A. Hendricks, Melinda S. Peng, Bing Fu, and Tim Li

Abstract

Composite analysis is used to examine environmental and climatology and persistence characteristics of tropical cyclones (TCs) undergoing different intensity changes in the western North Pacific (WPAC) and North Atlantic (ATL) ocean basins. Using the cumulative distribution functions of 24-h intensity changes from the 2003–08 best-track data, four intensity change bins are defined: rapidly intensifying (RI), intensifying, neutral, and weakening. The Navy Operational Global Atmospheric Prediction System daily 0000 and 1200 UTC global analysis and Tropical Rainfall Measuring Mission Microwave Imager data are then used as proxies for the real atmosphere, and composites of various environmental fields believed relevant to TC intensity change are made in the vicinity of the TCs. These composites give the average characteristics near the TC, prior to undergoing a given intensity change episode.

For the environmental variables, statistically significant differences are examined between RI storms and the other groups. While some environmental differences were found between RI and weakening/neutral TCs in both basins, an interesting result from this study is that the environment of RI TCs and intensifying TCs is quite similar. This indicates that the rate of intensification is only weakly dependent on the environmental conditions, on average, provided the environment is favorable. Notable exceptions were that in the WPAC, RI events occurred in environments with significantly larger conditional instability than intensifying events. In the ATL, RI events occurred in environments with weaker deep-layer shear than intensifying events. An important finding of this work is that SSTs are similar between intensifying and rapidly intensifying TCs, indicating that the rate of intensification is not critically dependent on SST.

The TCs in both basins were more intense prior to undergoing an RI episode than an intensifying or neutral episode. In the WPAC, the three groups had similar translational speeds and headings, and average initial position. In the ATL, RI storms were located farther south than intensifying and neutral storms, and had a larger translational speed and a more westward component to the heading.

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Eric A. Hendricks, Jason C. Knievel, and Yi Wang

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The multilayer urban canopy models (UCMs) building effect parameterization (BEP) and BEP + building energy model (BEM; a building energy model integrated in BEP) are added to the Yonsei University (YSU) planetary boundary layer (PBL) parameterization in the Weather Research and Forecasting (WRF) Model. The additions allow for the first analysis of the detailed effects of buildings on the urban boundary layer in a nonlocal closure scheme. The modified YSU PBL parameterization is compared with the other 1.5-order local PBL parameterizations that predict turbulent kinetic energy (TKE), Mellor–Yamada–Janjić and Bougeault–Lacarerre, using both ideal and real cases. The ideal-case evaluation confirms that BEP and BEP+BEM produce the expected results in the YSU PBL parameterization because the simulations are qualitatively similar to the TKE-based PBL parameterizations in which the multilayer UCMs have long existed. The modified YSU PBL parameterization is further evaluated for a real case. Similar to the ideal case, there are larger differences among the different UCMs (simple bulk scheme, BEP, and BEP+BEM) than across the PBL parameterizations when the UCM is held fixed. Based on evaluation against urban near-surface wind and temperature observations for this case, the BEP and BEP+BEM simulations are superior to the simple bulk scheme for each PBL parameterization.

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Eric A. Hendricks, Steve R. Diehl, Donald A. Burrows, and Robert Keith

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An urban dispersion modeling system was evaluated using the Joint Urban 2003 field data. The system consists of a fast-running urban airflow model (RUSTIC, for Realistic Urban Spread and Transport of Intrusive Contaminants) that is coupled with a Lagrangian particle transport and diffusion model (MESO) that uses random-walk tracer diffusion techniques. Surface measurements from fast-response and integrated bag samplers were used to evaluate model performance in predicting near-field (less than 1 km from the source) dispersion in the Oklahoma City, Oklahoma, central business district. Comparisons were made for six different intense operating periods (IOPs) composed of three different release locations and stable nighttime and unstable daytime meteorological conditions. Overall, the models were shown to have an underprediction bias of 47%. A possible influence to this underprediction is that the higher density of sulfur hexafluoride in comparison with air was not taken into account in the simulations. The models were capable of predicting 42% of the sampler data within a factor of 2 and 83% of the data within a factor of 10. When the effects of large-scale atmospheric turbulence were included, the models were shown to be capable of predicting 51% of the data within a factor of 2. The results were further broken down into performance for varying meteorological conditions. For daytime releases, the models performed reasonably well; for nighttime releases the models performed more poorly. Two possible causes of the poorer nighttime comparisons are (a) an inability to model the suppression of vertical turbulence because of the assumption of isotropy in RUSTIC’s k–ω turbulence model and (b) difficulty in modeling the light and variable inflow winds. The best comparisons were found for the three continuous daytime releases of IOP-4. It was hypothesized that these good comparisons were a result of steadier inflow conditions combined with the fact that the release site was more exposed and closer to the sodar used for the inflow meteorological conditions.

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Donald A. Burrows, Eric A. Hendricks, Steve R. Diehl, and Robert Keith

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The Realistic Urban Spread and Transport of Intrusive Contaminants (RUSTIC) model has been developed as a simplified computational fluid dynamics model with a kω turbulence model to be used to provide moderately fast simulations of turbulent airflow in an urban environment. RUSTIC simulations were compared with wind tunnel measurements to refine and “calibrate” the parameters for the kω model. RUSTIC simulations were then run and compared with data from five different periods during the Joint Urban 2003 experiment. Predictions from RUSTIC were compared with data from 33 near-surface sonic anemometers as well as 8 sonic anemometers on a 90-m tower and a sodar wind profiler located in the Oklahoma City, Oklahoma, central business district. The data were subdivided into daytime and nighttime datasets and then the daytime data were further subdivided into exposed and sheltered sonic anemometers. While there was little difference between day and night for wind speed and direction comparisons, there was considerable difference for the turbulence kinetic energy (TKE) comparisons. In the nighttime cases, RUSTIC overpredicted the TKE but without any correlation between model and observations. On the other hand, for the daytime cases, RUSTIC underpredicted the TKE values and correlated well with the observations. RUSTIC predicted both winds and TKE much better for the exposed sonic anemometers than for the sheltered ones. For the 90-m tower location downwind of the central business district, RUSTIC predicted the vertical profile of wind speed and direction very closely but underestimated the TKE.

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Steve R. Diehl, Donald A. Burrows, Eric A. Hendricks, and Robert Keith

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Two models have been developed to predict airflow and dispersion in urban environments. The first model, the Realistic Urban Spread and Transport of Intrusive Contaminants (RUSTIC) model, is a fast-running urban airflow code that rapidly converges to a numerical solution of a modified set of the compressible Navier–Stokes equations. RUSTIC uses the kω turbulence model with a buoyancy production term to handle atmospheric stability effects. The second model, “MESO,” is a Lagrangian particle transport and dispersion code that predicts concentrations of a released chemical or biological agent in urban or rural areas. As a preliminary validation of the models, concentrations simulated by MESO are compared with experimental data from wind-tunnel testing of dispersion around both a multistory rectangular building and a single-story L-shaped building. For the rectangular building, trace gas is forced out at the base of the downwind side, whereas for the L-shaped building, trace gas is forced out of a side door in the inner corner of the “L.” The MESO–RUSTIC combination is set up with the initial conditions of the wind-tunnel experiment, and the steady-state concentrations simulated by the models are compared with the wind-tunnel data. For the multistory building, a dense set of detector locations was available downwind at ground level. For the L-shaped building, concentration data were available at three heights in a lateral plane at a distance of one building height downwind of the lee side. A favorable comparison between model simulations and test data is shown for both buildings.

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