[Eoas-seminar] Meteorology PhD Defense for Ruikai Yan, Wednesday, May 1, 2019, 10:30 PM, LOV353

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Tue Apr 23 15:02:48 EDT 2019

Meteorology Seminar

Ruikai Yan

PhD Meteorology Candidate


Major Professor:  Dr. Ming Cai

Date: Wednesday, May 1st                   Time: 10:30 AM

Location: Werner A. Baum Seminar Room (353 Love Building)
(Please join us for refreshments served outside room 353 Love @ 10:00 AM)


The ability to construct radial wind profiles of tropical cyclones (TC) from limited observations is crucial to the initialization of TC simulations and predictions. A minimum requirement for constructing a reasonable radial wind profile is a high skill in estimating one of the four TC characteristic parameters, namely maximum wind speed (Vmax), radius of maximum wind speed (rmax), 17 ms−1 wind speed (V17), and radius of 17 ms−1 wind (r17) from the other three. In this study, we put froth an absolute angular momentum (AAM) based analytical model for inferring the radial profile beyond the rmax. An AAM loss function L, defined as the ratio of the AAM at r17 to that at rmax, is introduced to represent the AAM loss during radially inward motions in a TC by utilizing observations of the four TC characteristic parameters. We parameterize the AAM loss function L as a function of these four parameters and environmental factors. The parameterized AAM loss function L, combined with mathematical expressions of AAM at r17 and at rmax, gives us the newly developed analytical model. This observation-physics based model allows us to construct radial profiles of TCs under four different configurations from observations of these four parameters. Specifically, we can use Vmax and rmax as inputs for solving (a) the tangential velocity profile of a TC from rmax to r17 or (b) the TC’s radius for a given tangential velocity from Vmax to V17. Alternatively, we can use V17 and r17 as inputs for solving (c) the tangential velocity profile of a TC from r17 to rmax or (d) the TC’s radius for a given tangential velocity from V17 to Vmax. This enables us to acquire radial wind profiles when one of the four parameters is not available in observations.  The degree of consistency of (a) versus (c) and (b) versus (c) is an indicator of the robustness of the model. We evaluate the skill of our model using 4491 records of 197 named TCs derived from the Extended Best Track Dataset for the period of 1998-2016, and find that the mean errors in estimating Vmax, rmax, V17, and r17 are, respectively, 5.95 m/s, 25.37 km, 3.33 m/s, and 57.67 km.
The newly developed analytical model has several advantages over widely recognized existing TC wind profile models. Most empirical models, for example, are designed to construct radial wind profiles in only one of the four configurations. While other physics-based models have mean errors in Vmax, rmax, and r17 that are larger by several factors. Furthermore, our model can yield physically realistic radial wind profiles and solutions of TC characteristic parameters (meaning that for radial wind profiles, wind velocity decreases monotonically from rmax to r17, and for solutions, Vmax > V17 > 0 and  r17 > rmax > 0) for all 4491 TC records, regardless of which of the four con- figurations is chosen. For more than 10% of the TC records, however, other physics-based models have radial wind profiles that are discrete or increases from the inside to outside, and have solutions that either do not exist or are not physical under certain configurations.

Shel McGuire
Florida State University
Academic Program Specialist
Department of Earth, Ocean, & Atmospheric Science
1017 Academic Way, 410 Love Building (Meteorology)
Tallahassee, FL 32306

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