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  • Author or Editor: Wei Zhao x
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Qin Xu
,
Li Wei
,
Yi Jin
,
Qingyun Zhao
, and
Jie Cao

Abstract

This paper proposes a new method to properly define and accurately determine the vortex center of a model-predicted tropical cyclone (TC) from a dynamic perspective. Ideally, a dynamically determined TC vortex center should maximize the gradient wind balance or, equivalently, minimize the gradient wind imbalance measured by an energy norm over the TC vortex. In practice, however, such an energy norm cannot be used to easily and unambiguously determine the TC vortex center. An alternative yet practical approach is developed to dynamically and unambiguously define the TC vortex center. In this approach, the TC vortex core of near-solid-body rotation is modeled by a simple parametric vortex constrained by the gradient wind balance. Therefore, the modeled vortex can fit simultaneously the perturbation pressure and streamfunction of the TC vortex part (extracted from the model-predicted fields) over the TC vortex core area (within the radius of maximum tangential wind), while the misfit is measured by a properly defined cost function. Minimizing this cost function yields the desired dynamic optimality condition that can uniquely define the TC vortex center. Using this dynamic optimality condition, a new method is developed in the form of iterative least squares fit to accurately determine the TC vortex center. The new method is shown to be efficient and effective for finding the TC vortex center that accurately satisfies the dynamic optimality condition.

Full access
Shuyi S. Chen
,
Wei Zhao
,
Mark A. Donelan
, and
Hendrik L. Tolman

Abstract

The extreme high winds, intense rainfall, large ocean waves, and copious sea spray in hurricanes push the surface-exchange parameters for temperature, water vapor, and momentum into untested regimes. The Coupled Boundary Layer Air–Sea Transfer (CBLAST)-Hurricane program is aimed at developing improved coupling parameterizations (using the observations collected during the CBLAST-Hurricane field program) for the next-generation hurricane research prediction models. Hurricane-induced surface waves that determine the surface stress are highly asymmetric, which can affect storm structure and intensity significantly. Much of the stress is supported by waves in the wavelength range of 0.1–10 m, which is the unresolved “spectral tail” in present wave models. A directional wind–wave coupling method is developed to include effects of directionality of the wind and waves in hurricanes. The surface stress vector is calculated using the two-dimensional wave spectra from a wave model with an added short-wave spectral tail. The wind and waves are coupled in a vector form rather than through the traditional roughness scalar. This new wind–wave coupling parameterization has been implemented in a fully coupled atmosphere–wave–ocean model with 1.67-km grid resolution in the atmospheric model, which can resolve finescale features in the extreme high-wind region of the hurricane eyewall. It has been tested in a number of storms including Hurricane Frances (2004), which is one of the best-observed storms during the CBLAST-Hurricane 2004 field program. This paper describes the new wind–wave coupling parameterization and examines the characteristics of the coupled model simulations of Hurricane Frances (2004). Observations of surface waves and winds are used to evaluate the coupled model results.

Full access
Yi-Hung Kuo
,
J. David Neelin
,
Chih-Chieh Chen
,
Wei-Ting Chen
,
Leo J. Donner
,
Andrew Gettelman
,
Xianan Jiang
,
Kuan-Ting Kuo
,
Eric Maloney
,
Carlos R. Mechoso
,
Yi Ming
,
Kathleen A. Schiro
,
Charles J. Seman
,
Chien-Ming Wu
, and
Ming Zhao

Abstract

To assess deep convective parameterizations in a variety of GCMs and examine the fast-time-scale convective transition, a set of statistics characterizing the pickup of precipitation as a function of column water vapor (CWV), PDFs and joint PDFs of CWV and precipitation, and the dependence of the moisture–precipitation relation on tropospheric temperature is evaluated using the hourly output of two versions of the GFDL Atmospheric Model, version 4 (AM4), NCAR CAM5 and superparameterized CAM (SPCAM). The 6-hourly output from the MJO Task Force (MJOTF)/GEWEX Atmospheric System Study (GASS) project is also analyzed. Contrasting statistics produced from individual models that primarily differ in representations of moist convection suggest that convective transition statistics can substantially distinguish differences in convective representation and its interaction with the large-scale flow, while models that differ only in spatial–temporal resolution, microphysics, or ocean–atmosphere coupling result in similar statistics. Most of the models simulate some version of the observed sharp increase in precipitation as CWV exceeds a critical value, as well as that convective onset occurs at higher CWV but at lower column RH as temperature increases. While some models quantitatively capture these observed features and associated probability distributions, considerable intermodel spread and departures from observations in various aspects of the precipitation–CWV relationship are noted. For instance, in many of the models, the transition from the low-CWV, nonprecipitating regime to the moist regime for CWV around and above critical is less abrupt than in observations. Additionally, some models overproduce drizzle at low CWV, and some require CWV higher than observed for strong precipitation. For many of the models, it is particularly challenging to simulate the probability distributions of CWV at high temperature.

Open access