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Da-Lin Zhang
,
Lin Zhu
,
Xuejin Zhang
, and
Vijay Tallapragada

Abstract

A 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 larger intensity variability and bifurcation rate occur at later stages. These intensity differences are found to be closely related to inner-core structural changes, and they are attributable to how much latent heat could be released in higher-VGR layers, followed by how much moisture content in nearby layers is converged. Hurricane intensity with higher VGRs is shown to be much less sensitive to varying background flows, and stronger hurricane vortices at the model initial time are less sensitive to the vertical distribution of VGR; the opposite is true for relatively uniform VGRs or weaker hurricane vortices. Results reveal that higher VGRs with a near-parabolic or Ω shape tend to produce smoother intensity variations and more typical inner-core structures.

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Ghassan J. Alaka Jr.
,
Xuejin Zhang
, and
Sundararaman G. Gopalakrishnan

Abstract

To forecast tropical cyclone (TC) intensity and structure changes with fidelity, numerical weather prediction models must be “high definition,” i.e., horizontal grid spacing ≤ 3 km, so that they permit clouds and convection and resolve sharp gradients of momentum and moisture in the eyewall and rainbands. Storm-following nests are computationally efficient at fine resolutions, providing a practical approach to improve TC intensity forecasts. Under the Hurricane Forecast Improvement Project, the operational Hurricane Weather Research and Forecasting (HWRF) system was developed to include telescopic, storm-following nests for a single TC per model integration. Subsequently, HWRF evolved into a state-of-the-art tool for TC predictions around the globe, although its single-storm nesting approach does not adequately simulate TC–TC interactions as they are observed. Basin-scale HWRF (HWRF-B) was developed later with a multistorm nesting approach to improve the simulation of TC–TC interactions by producing high-resolution forecasts for multiple TCs simultaneously. In this study, the multistorm nesting approach in HWRF-B was compared with a single-storm nesting approach using an otherwise identical model configuration. The multistorm approach demonstrated TC intensity forecast improvements, including more realistic TC–TC interactions. Storm-following nests developed in HWRF and HWRF-B will be foundational to NOAA’s next-generation hurricane application in the Unified Forecast System.

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Sundararaman G. Gopalakrishnan
,
Frank Marks Jr.
,
Jun A. Zhang
,
Xuejin Zhang
,
Jian-Wen Bao
, and
Vijay Tallapragada

Abstract

The 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 inflow not only increased the spin of the storm, enhancing the generalized Coriolis term in the equations of motion for tangential velocity, but also resulted in enhanced equivalent potential temperature in the boundary layer, a stronger and warmer core, and, subsequently, a stronger storm. More importantly, rapid acceleration of the inflow not only produced a stronger outflow at the top of the inflow layer, more consistent with observations, but also a smaller inner core that was less than half the size of the original.

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Sundararaman G. Gopalakrishnan
,
Frank Marks Jr.
,
Jun A. Zhang
,
Xuejin Zhang
,
Jian-Wen Bao
, and
Vijay Tallapragada
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Andrew T. Hazelton
,
Xuejin Zhang
,
Sundararaman Gopalakrishnan
,
William Ramstrom
,
Frank Marks
, and
Jun A. Zhang

Abstract

The FV3GFS is the current operational Global Forecast System (GFS) at the National Centers for Environmental Prediction (NCEP), which combines a finite-volume cubed sphere dynamical core (FV3) and GFS physics. In this study, FV3GFS is used to gain understanding of rapid intensification (RI) of tropical cyclones (TCs) in shear. The analysis demonstrates the importance of TC structure in a complex system like Hurricane Michael, which intensified to a category 5 hurricane over the Gulf of Mexico despite over 20 kt (10 m s−1) of vertical wind shear. Michael’s RI is examined using a global-nest FV3GFS ensemble with the nest at 3-km resolution. The ensemble shows a range of peak intensities from 77 to 159 kt (40–82 m s−1). Precipitation symmetry, vortex tilt, moisture, and other aspects of Michael’s evolution are compared through composites of stronger and weaker members. The 850–200-hPa vertical shear is 22 kt (11 m s−1) in the mean of both strong and weak members during the early stage. Tilt and moisture are two distinguishing factors between strong and weak members. The relationship between vortex tilt and humidification is complex, and other studies have shown both are important for sheared intensification. Here, it is shown that tilt reduction leads to upshear humidification and is thus a driving factor for intensification. A stronger initial vortex and early evolution of the vortex also appear to be the key to members that are able to resist the sheared environment.

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Sundararaman G. Gopalakrishnan
,
Frank Marks Jr.
,
Xuejin Zhang
,
Jian-Wen Bao
,
Kao-San Yeh
, and
Robert Atlas

Abstract

Forecasting intensity changes in tropical cyclones (TCs) is a complex and challenging multiscale problem. While cloud-resolving numerical models using a horizontal grid resolution of 1–3 km are starting to show some skill in predicting the intensity changes in individual cases, it is not clear at this time what may be a reasonable horizontal resolution for forecasting TC intensity changes on a day-to-day-basis. The Experimental Hurricane Weather Research and Forecasting System (HWRFX) was used within an idealized framework to gain a fundamental understanding of the influence of horizontal grid resolution on the dynamics of TC vortex intensification in three dimensions. HWFRX is a version of the National Centers for Environmental Prediction (NCEP) Hurricane Weather Research and Forecasting (HWRF) model specifically adopted and developed jointly at NOAA’s Atlantic Oceanographic and Meteorological Laboratory (AOML) and Earth System Research Laboratory (ESRL) for studying the intensity change problem at a model grid resolution of about 3 km. Based on a series of numerical experiments at the current operating resolution of about 9 km and at a finer resolution of about 3 km, it was found that improved resolution had very little impact on the initial spinup of the vortex. An initial axisymmetric vortex with a maximum wind speed of 20 m s−1 rapidly intensified to 50 m s−1 within about 24 h in either case. During the spinup process, buoyancy appears to have had a pivotal influence on the formation of the warm core and the subsequent rapid intensification of the modeled vortex. The high-resolution simulation at 3 km produced updrafts as large as 48 m s−1. However, these extreme events were rare, and this study indicated that these events may not contribute significantly to rapid deepening. Additionally, although the structure of the buoyant plumes may differ at 9- and 3-km resolution, interestingly, the axisymmetric structure of the simulated TCs exhibited major similarities. Specifically, the similarities included a deep inflow layer extending up to about 2 km in height with a tangentially averaged maximum inflow velocity of about 12–15 m s−1, vertical updrafts with an average velocity of about 2 m s−1, and a very strong outflow produced at both resolutions for a mature storm. It was also found in either case that the spinup of the primary circulation occurred not only due to the weak inflow above the boundary layer but also due to the convergence of vorticity within the boundary layer. Nevertheless, the mature phase of the storm’s evolution exhibited significantly different patterns of behavior at 9 and 3 km. While the minimum pressure at the end of 96 h was 934 hPa for the 9-km simulation, it was about 910 hPa for the 3-km run. The maximum tangential wind at that time showed a difference of about 10 m s−1. Several sensitivity experiments related to the initial vortex intensity, initial radius of the maximum wind, and physics were performed. Based on ensembles of simulations, it appears that radial advection of the tangential wind and, consequently, radial flux of vorticity become important forcing terms in the momentum budget of the mature storm. Stronger convergence in the boundary layer leads to a larger transport of moisture fluxes and, subsequently, a stronger storm at higher resolution.

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Altuğ Aksoy
,
Sim D. Aberson
,
Tomislava Vukicevic
,
Kathryn J. Sellwood
,
Sylvie Lorsolo
, and
Xuejin Zhang

Abstract

The Hurricane Weather Research and Forecasting (HWRF) Ensemble Data Assimilation System (HEDAS) is developed to assimilate tropical cyclone inner-core observations for high-resolution vortex initialization. It is based on a serial implementation of the square root ensemble Kalman filter (EnKF). In this study, HWRF is used in an experimental configuration with horizontal grid spacing of 9 (3) km on the outer (inner) domain. HEDAS is applied to 83 cases from years 2008 to 2011. With the exception of two Hurricane Hilary (2011) cases in the eastern North Pacific basin, all cases are observed in the Atlantic basin. Observed storm intensity for these cases ranges from tropical depression to category-4 hurricane.

Overall, it is found that high-resolution tropical cyclone observations, when assimilated with an advanced data assimilation technique such as the EnKF, result in analyses of the primary circulation that are realistic in terms of intensity, wavenumber-0 radial structure, as well as wavenumber-1 azimuthal structure. Representing the secondary circulation in the analyses is found to be more challenging with systematic errors in the magnitude and depth of the low-level radial inflow. This is believed to result from a model bias in the experimental HWRF caused by the overdiffusive nature of the planetary boundary layer parameterization utilized. Thermodynamic deviations from the observed structure are believed to be caused by both an imbalance between the number of the kinematic and thermodynamic observations in general and the suboptimal ensemble covariances between kinematic and thermodynamic fields. Future plans are discussed to address these challenges.

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Sim D. Aberson
,
Altuğ Aksoy
,
Kathryn J. Sellwood
,
Tomislava Vukicevic
, and
Xuejin Zhang

Abstract

NOAA has been gathering high-resolution, flight-level dropwindsonde and airborne Doppler radar data in tropical cyclones for almost three decades; the U.S. Air Force routinely obtained the same type and quality of data, excepting Doppler radar, for most of that time. The data have been used for operational diagnosis and for research, and, starting in 2013, have been assimilated into operational regional tropical cyclone models. This study is an effort to quantify the impact of assimilating these data into a version of the operational Hurricane Weather Research and Forecasting model using an ensemble Kalman filter. A total of 83 cases during 2008–11 were investigated. The aircraft whose data were used in the study all provide high-density flight-level wind and thermodynamic observations as well as surface wind speed data. Forecasts initialized with these data assimilated are compared to those using the model standard initialization. Since only NOAA aircraft provide airborne Doppler radar data, these data are also tested to see their impact above the standard aircraft data. The aircraft data alone are shown to provide some statistically significant improvement to track and intensity forecasts during the critical watch and warning period before projected landfall (through 60 h), with the Doppler radar data providing some further improvement. This study shows the potential for improved forecasts with regular tropical cyclone aircraft reconnaissance and the assimilation of data obtained from them, especially airborne Doppler radar data, into the numerical guidance.

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Ghassan J. Alaka Jr.
,
Xuejin Zhang
,
Sundararaman G. Gopalakrishnan
,
Stanley B. Goldenberg
, and
Frank D. Marks

Abstract

The Hurricane Weather Research and Forecasting (HWRF) Model is a dynamical model that has shown annual improvements in its tropical cyclone (TC) track forecasts as a result of various modifications. This study focuses on an experimental version of HWRF, called the basin-scale HWRF (HWRF-B), configured with 1) a large, static outer domain to cover multiple TC basins and 2) multiple sets of high-resolution movable nests to produce forecasts for several TCs simultaneously. Although HWRF-B and the operational HWRF produced comparable average track errors for the 2011–14 Atlantic hurricane seasons, strengths of HWRF-B are identified and linked to its configuration differences. HWRF-B track forecasts were generally more accurate compared with the operational HWRF when at least one additional TC was simultaneously active in the Atlantic or east Pacific basins and, in particular, when additional TCs were greater than 3500 km away. In addition, at long lead times, HWRF-B average track errors were lower than for the operational HWRF for TCs initialized north of 25°N or west of 60°W, highlighting the sensitivity of TC track forecasts to the location of the operational HWRF’s outermost domain. A case study, performed on Hurricane Michael, corroborated these HWRF-B strengths. HWRF-B shows the potential to serve as an effective bridge between regional modeling systems and next-generational global efforts.

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Jun A. Zhang
,
Frank D. Marks
,
Jason A. Sippel
,
Robert F. Rogers
,
Xuejin Zhang
,
Sundararaman G. Gopalakrishnan
,
Zhan Zhang
, and
Vijay Tallapragada

Abstract

Improving physical parameterizations in forecast models is essential for hurricane prediction. This study documents the upgrade of horizontal diffusion parameterization in the Hurricane Weather Research and Forecasting (HWRF) Model and evaluates the impact of this upgrade on hurricane forecasts. The horizontal mixing length L h was modified based on aircraft observations and extensive idealized and real-case numerical experiments. Following an earlier work by the first two authors, who focused on understanding how the horizontal diffusion parameterization worked in HWRF and its dynamical influence on hurricane intensification using idealized simulations, a series of sensitivity experiments was conducted to simulate Hurricane Earl (2010) in which only L h was varied. Results from the Earl forecasts confirmed the findings from previous theoretical and idealized numerical studies, in that both the simulated maximum intensity and intensity change rate are dependent on L h . Comparisons between the modeled and observed structure of Hurricane Earl, such as storm size, boundary layer heights, warm-core height and temperature anomaly, and eyewall slope, suggested that the L h used in the HWRF Model should be decreased. Lowering L h in HWRF has a positive impact on hurricane prediction based on over 200 retrospective forecasts of 10 Atlantic storms. Biases in both storm intensity and storm size are significantly reduced with the modified L h .

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