[Eoas-seminar] COAPS Short Seminar Series

[eoas-seminar at lists.fsu.edu]

COAPS Short Seminar Series
11:00 AM October 2nd
Attend F2F (in 255 Research A) or Virtually (via Zoom)
https://fsu.zoom.us/j/92268262553

Meeting ID: 922 6826 2553
Talks are 12 minutes long with an additional 8 minutes for questions.

The wavelet approach to wavenumber spectral analyses on inhomogeneous and non-periodic flows
By Takaya Uchida
Description: While Fourier methods have provided us with immense benefits in extracting the spatiotemporal scales of turbulent flows, they come with its shortcomings of requiring the data to be periodic and homogenous. Such requirements skew the data and introduce artifacts stemming from the windowing/tapering applied to make the data periodic. Here, a wavelet-based method is re-introduced in an oceanographic and spectral context to estimate localized wavenumber spectrum and spectral flux of kinetic energy and enstrophy. We apply this to a numerical simulation of idealized, doubly-periodic quasi-geostrophic flows, i.e. the flow is constrained by the Coriolis force and vertical stratification. The double periodicity allows for a straightforward Fourier analysis as the baseline method. Our wavelet spectra agree well with the canonical Fourier approach but with the additional strengths of negating the necessity for the data to be periodic and being able to extract local anisotropies in the flow. Caution is warranted, however, when computing higher-order quantities, such as spectral flux.

Ocean sound speed profile clustering in the Gulf Stream separation region
By Ethan Wright
Description: Vertical profiles of sound speed in the ocean are critical to sonar applications, such as automated target localization and optimal navigation routing for underwater vehicles. For these applications, vertical profiles of sound speed are used to estimate transmission loss. Calculating representative sound speed profiles in areas where contrasting water masses are present is a challenging task. In these areas, averaging a set of sound speed profiles over time can lead to an erroneous profile that is not associated with a particular water mass. One such region with strongly fluctuating sound speed conditions is the separation region of the Gulf Stream from the North American continent. The goal of this study is to analyze the different techniques for clustering that lead to the best representation of the range of conditions most important to sound transmission in this region. To capture the variability of the dominant sound speed conditions, a machine learning approach is introduced where vertical sound speed profiles calculated from ARGO float data are clustered using k-means and hierarchical agglomerative clustering.
NOTE: Please feel free to forward/share this invitation with other groups/disciplines that might be interested in this talk/topic. All are welcome to attend.

-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://lists.fsu.edu/pipermail/eoas-seminar/attachments/20230929/fa7cb04d/attachment.html>
-------------- next part --------------
A non-text attachment was scrubbed...
Name: not available
Type: text/calendar
Size: 4792 bytes
Desc: not available
URL: <http://lists.fsu.edu/pipermail/eoas-seminar/attachments/20230929/fa7cb04d/attachment.ics>