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Yongsheng Chen and Chris Snyder

Abstract

Observations of hurricane position, which in practice might be available from satellite or radar imagery, can be easily assimilated with an ensemble Kalman filter (EnKF) given an operator that computes the position of the vortex in the background forecast. The simple linear updating scheme used in the EnKF is effective for small displacements of forecasted vortices from the true position; this situation is operationally relevant since hurricane position is often available frequently in time. When displacements of the forecasted vortices are comparable to the vortex size, non-Gaussian effects become significant and the EnKF’s linear update begins to degrade. Simulations using a simple two-dimensional barotropic model demonstrate the potential of the technique and show that the track forecast initialized with the EnKF analysis is improved. The assimilation of observations of the vortex shape and intensity, along with position, extends the technique’s effectiveness to larger displacements of the forecasted vortices than when assimilating position alone.

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Yongsheng Chen and M. K. Yau

Abstract

Highly asymmetric structures in a landfalling hurricane can lead to the formation of heavy rains, wind gusts, and tornados at prefered locations relative to the center of the hurricane. In this study, the development of asymmetric structures in an explicitly simulated idealized hurricane during landfall was investigated.

It was found that the boundary layer friction and its associated convection produce a low-level positive potential vorticity (PV) band ahead of the hurricane. The interaction between the PV band and the eyewall PV ring leads to a temporary weakening and reintensifying cycle. Asymmetric structures arise from the near discontinuity of the surface friction and the latent heat flux. The breaking of the eyewall in the rear quadrants is favorable for the intrusion of the low moist entropy air into the core. Consequently, PV increases significantly in the core, in and just above the boundary layer due to the stabilization. After the hurricane makes landfall, the diabatic heating in the eyewall is reduced and cannot generate enough PV to maintain the PV ring in the middle and upper troposphere. The PV ring evolves into a monopolar structure through the nonlinear mixing process.

The Eliassen–Palm (EP) flux and its divergence in the Eulerian mean equations in isentropic coordinates are applied to explore the wave dynamics and wave–mean flow interactions. The vortex Rossby wave–related eddy momentum and heat transports, indicated by the EP flux, vary as a response to the evolution of the PV structure. The wave–mean flow interaction has a significant effect on the tangential wind, which is dominated by the mean circulation, especially the symmetric diabatic heating. Together with the asymmetric diabatic heating, the waves tend to counteract the effect of the mean circulation.

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Yongsheng Chen and M. K. Yau

Abstract

An initially axisymmetric hurricane was explicitly simulated using the high-resolution PSU–NCAR nonhydrostatic mesoscale model (MM5). Spiral potential vorticity (PV) bands that formed in the model were analyzed. It was shown that PV bands and cloud bands are strongly coupled. The PV anomalies in and at the top of the boundary layer interact with friction to produce upward motion that gives rise to the inner cloud bands. The propagation properties of the PV bands were studied and found to be consistent with predictions of vortex Rossby wave theory.

In the control simulation with full physics, continuous generation of PV through latent heat release in the eyewall and spiral rainbands maintain a “bowl-shape” PV field. Inward transport of high PV by the vortex Rossby waves and the process of nonlinear mixing tend to increase the inner-core PV and in turn intensify the hurricane. On the other hand, frictional and PV mixing processes acted linearly to spin down the hurricane to a midlevel vortex in a dry run, which indicates that a monopolar PV structure is the asymptotic stable state in the absence of condensation.

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Yongsheng Chen, Gilbert Brunet, and M. K. Yau

Abstract

The theory of empirical normal modes (ENMs) was applied in a diagnostic study of the inner spiral bands formed in a simulated hurricane using the high-resolution Pennsylvania State University–National Center for Atmospheric Research (PSU–NCAR) nonhydrostatic mesoscale model version 5 (MM5). The ENM method has the capability to decompose simultaneously wind and thermal fields into dynamically consistent and orthogonal modes with respect to wave activities.

For wavenumber 1 and 2 anomalies, it was found that the leading modes are vortex Rossby waves. These modes explain 70%–80% of the statistical variances in a 24-h period. Gravity waves have small contribution in terms of wave activities.

Analysis of the Eliassen–Palm (EP) flux and its time-mean divergence shows that vortex Rossby waves are generated in the eyewall region where the radial gradient of the basic-state potential vorticity is large. In general, these waves propagate outward in the lower troposphere and inward in the upper troposphere. Consequently, they transport eddy momentum radially inward and outward, respectively. The wave activities also propagate slowly upward inside the eyewall and downward outside. The associated eddy heat transport tends to warm the air in the eye region. The vortex Rossby waves lead to, through wave–mean flow interaction as indicated by the divergence of the EP flux, an acceleration of the mean tangential wind in the lower and middle troposphere inside and outside the eyewall and a deceleration aloft in the eyewall region.

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Craig S. Schwartz, Zhiquan Liu, Yongsheng Chen, and Xiang-Yu Huang

Abstract

Two parallel experiments were designed to evaluate whether assimilating microwave radiances with a cyclic, limited-area ensemble adjustment Kalman filter (EAKF) could improve track, intensity, and precipitation forecasts of Typhoon Morakot (2009). The experiments were configured identically, except that one assimilated microwave radiances and the other did not. Both experiments produced EAKF analyses every 6 h between 1800 UTC 3 August and 1200 UTC 9 August 2009, and the mean analyses initialized 72-h Weather Research and Forecasting model forecasts. Examination of individual forecasts and average error statistics revealed that assimilating microwave radiances ultimately resulted in better intensity forecasts compared to when radiances were withheld. However, radiance assimilation did not substantially impact track forecasts, and the impact on precipitation forecasts was mixed. Overall, net positive results suggest that assimilating microwave radiances with a limited-area EAKF system is beneficial for tropical cyclone prediction, but additional studies are needed.

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M. K. Yau, Yubao Liu, Da-Lin Zhang, and Yongsheng Chen

Abstract

The objectives of Part VI of this series of papers are to (a) simulate the finescale features of Hurricane Andrew (1992) using a cloud-resolving grid length of 2 km, (b) diagnose the formation of small-scale wind streaks, and (c) perform sensitivity experiments of varying surface fluxes on changes in storm inner-core structures and intensity.

As compared to observations and a previous 6-km model run, the results show that a higher-resolution explicit simulation could produce significant improvements in the structures and evolution of the inner-core eyewall and spiral rainbands, and in the organization of convection. The eyewall becomes much more compact and symmetric with its width decreased by half, and the radius of maximum wind is reduced by ∼10 to 20 km. A zone of deep and intense potential vorticity (PV) is formed at the edge of the eye. A ring of maximum PV is collocated in regions of maximum upward motion in the eyewall and interacts strongly with the eyewall convection. The convective cores in the eyewall are associated with small-scale wind streaks.

The formation of the wind streaks is diagnosed from an azimuthal momentum budget. The results reveal small-scale Lagrangian acceleration of the azimuthal flow. It is found that at the lowest model level of 40 m, the main contributor to the Lagrangian azimuthal wind tendency is the radial advection of angular momentum per unit radius. At an altitude of 1.24 km, vertical advection of the azimuthal wind, in addition to the radial advection of angular momentum per unit radius, plays important roles.

Results of a series of sensitivity tests, performed to examine the impact of several critical factors in the surface and boundary layer processes on the inner-core structures and the evolution of the hurricane intensity, are presented.

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Christopher Davis, Wei Wang, Shuyi S. Chen, Yongsheng Chen, Kristen Corbosiero, Mark DeMaria, Jimy Dudhia, Greg Holland, Joe Klemp, John Michalakes, Heather Reeves, Richard Rotunno, Chris Snyder, and Qingnong Xiao

Abstract

Real-time forecasts of five landfalling Atlantic hurricanes during 2005 using the Advanced Research Weather Research and Forecasting (WRF) (ARW) Model at grid spacings of 12 and 4 km revealed performance generally competitive with, and occasionally superior to, other operational forecasts for storm position and intensity. Recurring errors include 1) excessive intensification prior to landfall, 2) insufficient momentum exchange with the surface, and 3) inability to capture rapid intensification when observed. To address these errors several augmentations of the basic community model have been designed and tested as part of what is termed the Advanced Hurricane WRF (AHW) model. Based on sensitivity simulations of Katrina, the inner-core structure, particularly the size of the eye, was found to be sensitive to model resolution and surface momentum exchange. The forecast of rapid intensification and the structure of convective bands in Katrina were not significantly improved until the grid spacing approached 1 km. Coupling the atmospheric model to a columnar, mixed layer ocean model eliminated much of the erroneous intensification of Katrina prior to landfall noted in the real-time forecast.

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Dale Barker, Xiang-Yu Huang, Zhiquan Liu, Tom Auligné, Xin Zhang, Steven Rugg, Raji Ajjaji, Al Bourgeois, John Bray, Yongsheng Chen, Meral Demirtas, Yong-Run Guo, Tom Henderson, Wei Huang, Hui-Chuan Lin, John Michalakes, Syed Rizvi, and Xiaoyan Zhang

Data assimilation is the process by which observations are combined with short-range NWP model output to produce an analysis of the state of the atmosphere at a specified time. Since its inception in the late 1990s, the multiagency Weather Research and Forecasting (WRF) model effort has had a strong data assimilation component, dedicating two working groups to the subject. This article documents the history of the WRF data assimilation effort, and discusses the challenges associated with balancing academic, research, and operational data assimilation requirements in the context of the WRF effort to date. The WRF Model's Community Variational/Ensemble Data Assimilation System (WRFDA) has evolved over the past 10 years, and has resulted in over 30 refereed publications to date, as well as implementation in a wide range of real-time and operational NWP systems. This paper provides an overview of the scientific capabilities of WRFDA, and together with results from sample operation implementations at the U.S. Air Force Weather Agency (AFWA) and United Arab Emirates (UAE) Air Force and Air Defense Meteorological Department.

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Xiang-Yu Huang, Qingnong Xiao, Dale M. Barker, Xin Zhang, John Michalakes, Wei Huang, Tom Henderson, John Bray, Yongsheng Chen, Zaizhong Ma, Jimy Dudhia, Yongrun Guo, Xiaoyan Zhang, Duk-Jin Won, Hui-Chuan Lin, and Ying-Hwa Kuo

Abstract

The Weather Research and Forecasting (WRF) model–based variational data assimilation system (WRF-Var) has been extended from three- to four-dimensional variational data assimilation (WRF 4D-Var) to meet the increasing demand for improving initial model states in multiscale numerical simulations and forecasts. The initial goals of this development include operational applications and support to the research community. The formulation of WRF 4D-Var is described in this paper. WRF 4D-Var uses the WRF model as a constraint to impose a dynamic balance on the assimilation. It is shown to implicitly evolve the background error covariance and to produce the flow-dependent nature of the analysis increments. Preliminary results from real-data 4D-Var experiments in a quasi-operational setting are presented and the potential of WRF 4D-Var in research and operational applications are demonstrated. A wider distribution of the system to the research community will further develop its capabilities and to encourage testing under different weather conditions and model configurations.

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