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COAPS Short Seminar Series
<div class="ContentPasted0">11:00 AM Feb. 5th</div>
<div class="ContentPasted0">Attend F2F (in 255 Research A) or Virtually (via Zoom)</div>
<div class="ContentPasted0">https://fsu.zoom.us/j/92268262553</div>
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<div class="ContentPasted0">Meeting ID: 922 6826 2553</div>
<div class="ContentPasted0">Talks are 12 minutes long with an additional 8 minutes for questions.
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<div class="ContentPasted0">The influence of vertical resolution on internal tide energetics and its effects on underwater acoustics propagation</div>
<div class="ContentPasted0">By Luna Hiron</div>
<div class="ContentPasted0">Description: Internal tide generation and breaking play a primary role in the vertical transport and mixing of heat and other properties in the ocean interior, thereby influencing climate regulation. Additionally, internal tides
increase sound speed variability in the ocean, consequently impacting underwater acoustic propagation. With advancements in large-scale ocean modeling capabilities, it is essential to assess the impact of higher model resolutions (horizontal and vertical)
in representing internal tides. This study investigates the influence of vertical resolution on internal tide energetics and its subsequent effects on underwater acoustic propagation in the HYbrid Coordinate Ocean Model (HYCOM). An idealized configuration
only forced with semidiurnal tides with 1 km horizontal grid-spacing and a ridge is used to test two different vertical-grid discretization and seven distinct numbers of layers, ranging from 8 to 128 isopycnal layers. Isopycnal layers are either defined by
the zero-crossings of the horizontal velocity eigenfunctions or starting by the zero-crossings of the 128th mode horizontal velocity eigenfunction and removing intermediate layers. The analyses reveal that increasing the number of layers up to 48 layers increased
the domain-integrated barotropic-to-baroclinic tidal conversion, available potential energy, and vertical kinetic energy, maintaining consistency in simulations with higher layer counts. Vertical shear exhibits a similar pattern but peaking at 96 layers. Simulations
with at least 48 layers better resolved the available potential energy contained in modes higher than the 3rd baroclinic mode. Finally, acoustic analyses show an increase in sound speed variability, and subsequent changes in underwater acoustic propagation,
with the addition of layers until 48 layers. Therefore, the study concludes that a minimum vertical resolution (48 layers in this case) is required to minimize the impact on internal tide properties and associated underwater acoustic propagation.</div>
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<div class="ContentPasted0">The 2023/2024 El Niño - Evolution and Impacts</div>
<div class="ContentPasted0">By David Zierden</div>
<div class="ContentPasted0">Description: The current El Niño has been described as “historically strong” by NOAA with Nino 3.4 values approaching +2.0 C above normal. The evolution of this event was out of the normal, with the greatest SST departures beginning
in the eastern Pacific and spreading westward. Impacts from this El Niño event include Atlantic hurricane activity, frequent winter rain and storminess, and the threat of severe weather and coastal flooding.</div>
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<div class="ContentPasted0">Introduction to Graphcast</div>
<div class="ContentPasted0">By Olmo Zavala</div>
<div class="ContentPasted0">Description: The GraphCast model is a machine learning-based method designed for global medium-range weather forecasting. It was trained directly from reanalysis data and is capable of predicting hundreds of weather variables over
10 days at a 0.25-degree resolution globally in under one minute. The model outperforms traditional numerical weather prediction systems and supports better severe event prediction, including tropical cyclones, atmospheric rivers, and extreme temperatures.
It is a significant advancement in accurate and efficient weather forecasting. In this talk, I'll introduce its training process, the variables it predicts, its performance compared to traditional systems, and its impact on severe weather event prediction.</div>
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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.<br>
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