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<span style="color: black; font-size: 12pt;">Hi all,</span><br>
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<div style="margin:0px">Here is reminder that we have a MET seminar at 3:30 PM Today, Mar. 25, 2021. The related information can be found in the following and the attached flyer. </div>
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<div style="margin:0px"><b>Speaker</b>: Dr. Zane K. Martin, Department of Atmospheric Sciences, Colorado State University</div>
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<div style="margin:0px"><b>Title</b>: Predicting the Madden-Julian oscillation using interpretable machine learning</div>
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<div style="margin:0px"><b>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="margin:0px"><b>Time</b>: 3:30 PM, Thursday, Mar. 25, 2021</div>
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<span style="margin:0px"><b>Zoom Meeting</b>:<span style="margin:0px"> <a href="https://fsu.zoom.us/j/97840279436?pwd=YzlkdnNqZG1GaDhVMnJzSmZIb2VwQT09" id="LPlnk490772">https://fsu.zoom.us/j/97840279436?pwd=YzlkdnNqZG1GaDhVMnJzSmZIb2VwQT09</a></span><br>
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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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