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Just a correction, that the MET seminar given by Dr. Zane Martin is this Thursday, March
<b class="">25</b> at 3:30 PM. I know that there was a lot of interest in machine learning following one of our colloquia last year, so I hope to see a good turnout this week for Zane’s talk!
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<div class="">Graduate students, please stick around after the seminar for a student-only Q&A with the speaker. Zane is a postdoc at Colorado State who I’ve known since he started graduate school and he is super friendly and fun to talk to. In addition to his
work in modeling of tropical dynamics, Zane has participated in a couple of field campaigns.</div>
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<div class="">Cheers, </div>
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<div class="">Allison</div>
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Allison Wing, Ph.D.</div>
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Assistant Professor</div>
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Earth, Ocean and Atmospheric Science</div>
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Florida State University</div>
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<a href="mailto:awing@fsu.edu" class="">awing@fsu.edu</a></div>
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<div class="">On Mar 22, 2021, at 9:32 AM, eoas-seminar--- via Eoas-seminar <<a href="mailto:eoas-seminar@lists.fsu.edu" class="">eoas-seminar@lists.fsu.edu</a>> wrote:</div>
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<span style="margin: 0px; font-size: 12pt; background-color: white;" class="">Hi all,</span><span style="background-color: rgb(255, 255, 255); display: inline !important;" class=""></span></div>
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<div style="margin: 0px;" class="">Here is an announcement that we have a MET seminar at 3:30 PM on Thursday, Mar.
<b class="">25</b>, 2021. The related information can be found in the following and the attached flyer. </div>
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<div style="font-weight: normal; margin: 0px;" class=""><b class="">Speaker</b>: Dr. Zane K. Martin, Department of Atmospheric Sciences, Colorado State University</div>
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<div style="font-weight: normal; margin: 0px;" class=""><b class="">Title</b>: Predicting the Madden-Julian oscillation using interpretable machine learning</div>
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<div style="font-weight: normal; margin: 0px;" class=""><b class="">Abstract</b>: The Madden-Julian oscillation (MJO) is among the most important modes of tropical variability on the planet, and a dominant driver of subseasonal-to-seasonal prediction skill
and predictability globally. The past decade has seen substantial advances in MJO prediction using dynamical forecast models, which now show higher skill than statistical MJO forecasts. Also in recent years, an increasing body of literature has demonstrated
that machine learning methods represent a new frontier in Earth science with a wide range of applications. After a brief overview of the current state of MJO prediction, we discuss how state-of-the-art machine learning can be used to make real-time MJO forecasts.
We introduce a particular type of machine learning model called a neural network, and then demonstrate how it can be used to predict MJO. We show that machine learning models have high skill relative to statistical models overall, but still underperform the
very best dynamical MJO models. We close by discussing the strengths of these models and how they might be used and improved going forward, including their potential to lead to insights about the MJO. We also discuss cutting-edge techniques from the field
of interpretable AI that allow us to visualize how these neural network makes predictions.</div>
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<div style="font-weight: normal; margin: 0px;" class=""><b class="">Time</b>: 3:30 PM, Thursday, Mar. 25, 2021</div>
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<span style="font-weight: normal; margin: 0px;" class=""><b class="">Zoom Meeting</b>:<span style="margin: 0px;" class=""> <a href="https://fsu.zoom.us/j/97840279436?pwd=YzlkdnNqZG1GaDhVMnJzSmZIb2VwQT09" id="LPlnk490772" class="">https://fsu.zoom.us/j/97840279436?pwd=YzlkdnNqZG1GaDhVMnJzSmZIb2VwQT09</a></span><br class="">
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We will start the zoom meeting site to meet the speaker at 3:00 PM. It is also noted a post-seminar student-speaker session will start immediately after the seminar.</div>
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Cheers,</div>
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Zhaohua</div>
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<span id="cid:2D1713B6-4EAF-41CE-A261-F227244AB316@hsd1.fl.comcast.net."><MET_Seminar_Flyer_Martin.pdf></span><span style="caret-color: rgb(0, 0, 0); font-family: Helvetica; font-size: 12px; font-style: normal; font-variant-caps: normal; font-weight: normal; letter-spacing: normal; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; word-spacing: 0px; -webkit-text-stroke-width: 0px; text-decoration: none; float: none; display: inline !important;" class="">_______________________________________________</span><br style="caret-color: rgb(0, 0, 0); font-family: Helvetica; font-size: 12px; font-style: normal; font-variant-caps: normal; font-weight: normal; letter-spacing: normal; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; word-spacing: 0px; -webkit-text-stroke-width: 0px; text-decoration: none;" class="">
<span style="caret-color: rgb(0, 0, 0); font-family: Helvetica; font-size: 12px; font-style: normal; font-variant-caps: normal; font-weight: normal; letter-spacing: normal; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; word-spacing: 0px; -webkit-text-stroke-width: 0px; text-decoration: none; float: none; display: inline !important;" class="">Eoas-seminar
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<a href="mailto:Eoas-seminar@lists.fsu.edu" style="font-family: Helvetica; font-size: 12px; font-style: normal; font-variant-caps: normal; font-weight: normal; letter-spacing: normal; orphans: auto; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; widows: auto; word-spacing: 0px; -webkit-text-size-adjust: auto; -webkit-text-stroke-width: 0px;" class="">Eoas-seminar@lists.fsu.edu</a><br style="caret-color: rgb(0, 0, 0); font-family: Helvetica; font-size: 12px; font-style: normal; font-variant-caps: normal; font-weight: normal; letter-spacing: normal; text-align: start; text-indent: 0px; text-transform: none; white-space: normal; word-spacing: 0px; -webkit-text-stroke-width: 0px; text-decoration: none;" class="">
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