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<span style="font-family: "Times New Roman", serif;">Dear all, <o:p></o:p></span></p>
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<span style="font-family: "Times New Roman", serif;"> </span></p>
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<span style="font-family: "Times New Roman", serif;">Please join us for a MET seminar, which will be at 3:00PM on Jan. 20 (Tuesday) in EOAS 1044, given by Dr. Samuel Fung from University of Miami. His seminar is entitled “</span><span style="font-family: "Times New Roman", serif;">Enhancing
Tropical Cyclone Research and Forecast at High Resolution </span><span style="font-family: "Times New Roman", serif;">”<i><span style="background: white;"> </span></i><span style="background: white;">(abstract below)</span></span><span style="font-family: "Times New Roman", serif;"><o:p></o:p></span></p>
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<span style="font-family: "Times New Roman", serif;">DATE: Tuesday, January 20 <o:p></o:p></span></p>
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<span style="font-family: "Times New Roman", serif;">TIME: 3-4 PM<o:p></o:p></span></p>
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<span style="font-family: "Times New Roman", serif;">LOCATION: EOA 1044 <o:p></o:p></span></p>
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<span style="font-family: "Times New Roman", serif;">SPEAKER: Dr. Samuel Fung<o:p></o:p></span></p>
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<span style="font-family: "Times New Roman", serif;"> </span></p>
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<span style="font-size: 9pt; font-family: Helvetica;">Join Zoom Meeting</span><br>
<a href="https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Ffsu.zoom.us%2Fj%2F94406633431&data=05%7C02%7Ceoas-seminar%40lists.fsu.edu%7C1ad3b450e27f45d3b38308de531981cc%7Ca36450ebdb0642a78d1b026719f701e3%7C0%7C0%7C639039566160691277%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&sdata=BIDIVtgtXNp6jAkh%2Fr5meMqriaZ7kAcj%2FE7IPuW8sZA%3D&reserved=0" originalsrc="https://fsu.zoom.us/j/94406633431" style="color: rgb(150, 96, 125);"><span style="font-size: 9pt; font-family: Helvetica;">https://nam04.safelinks.protection.outlook.com/?url=https%3A%2F%2Ffsu.zoom.us%2Fj%2F94406633431&data=05%7C02%7Cmcai%40fsu.edu%7Ced08db9f5c874c01a0d108de530f8bae%7Ca36450ebdb0642a78d1b026719f701e3%7C0%7C0%7C639039523382703658%7CUnknown%7CTWFpbGZsb3d8eyJFbXB0eU1hcGkiOnRydWUsIlYiOiIwLjAuMDAwMCIsIlAiOiJXaW4zMiIsIkFOIjoiTWFpbCIsIldUIjoyfQ%3D%3D%7C0%7C%7C%7C&sdata=t5Ab36UoBsbBkVfqnSdCQUeh2dC3GcKXXgLsOxk7PNE%3D&reserved=0</span></a><span style="font-size: 9pt; font-family: Helvetica;"><br>
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Meeting ID: 944 0663 3431</span><span style="font-family: "Times New Roman", serif;"><o:p></o:p></span></p>
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<span style="font-family: "Times New Roman", serif;">Title: Enhancing Tropical Cyclone Research and Forecast at High Resolution <o:p></o:p></span></p>
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<span style="font-family: "Times New Roman", serif;">Abstract: <o:p></o:p></span></p>
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<span style="font-family: "Times New Roman", serif;">As computational power enables kilometer‑scale weather modeling, model inputs and physics must evolve to capture subgrid variability. This seminar presents two advances: (1) capture urban heterogeneity to
enhance tropical cyclone (TC) landfall simulation, and (2) develop a scale‑aware turbulent mixing scheme to enhance TC tracks and intensity forecast.<o:p></o:p></span></p>
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<span style="font-family: "Times New Roman", serif;">The first section introduces the Local Climate Zones (LCZs), that utilize satellite imageries and machine learning methods to subcategorize urban land use into 10 classes for capturing intraurban variability.
High‑resolution simulations of landfalling TCs show that incorporating LCZs can enhance near‑surface winds, temperature, and rainfall compared to default land use land cover dataset.<o:p></o:p></span></p>
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<span style="font-family: "Times New Roman", serif;">This second section introduces a scale-aware turbulent mixing scheme to improve operational TC forecast that blends Large Eddy Simulation (LES) physics with mesoscale parameterizations. The scheme can create
better predictions of TC tracks and intensity in the operational framework. The mechanisms are also discussed.<o:p></o:p></span></p>
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<span style="font-family: "Times New Roman", serif;">These results show the need to revisit model inputs and model physics for more accurate high‑resolution extreme weather prediction.</span><o:p></o:p></p>
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