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NYC Tech
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/-73.96098328,40.81799698,13,0,0/550x200?access_token=pk.eyJ1IjoiZ2FyeXNndWlkZSIsImEiOiJjamtobmRiYmgwb3gwM3F1a2o2Mmd0YWw3In0.DinA62CR3-OKtf3axa5O7Q)
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The rise of machine learning in weather forecasting
Speaker: Mariana Clare
Date: December 7, 2023
Time: 3:30 p.m.
Format: Hybrid (the speaker will be presenting virtually, but LEAP will host an in-person event followed by a short reception).
Virtual: Zoom link provided upon registration
In-person: Columbia Innovation Hub, 2276 12th Avenue, Second Floor, Room 202, New York, NY 10027
*Please note that in-person space is limited.*
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Abstract: Over the last year, there has been a rise in machine learning methods being used to create highly accurate weather predictions. These methods have been applied by some of the world's leading tech companies with impressive results being shown for many applications. Some works have even made claims that these machine learning methods are more accurate than the existing state-of-the-art numerical weather models. But is this claim justified? In particular, how do machine learning methods cope with extreme weather events, which are some of the most difficult & most important events to forecast. In this talk I will present an evaluation of the current state of machine learning in weather forecasting & reflect on the opportunities & challenges for the future.
Bio: Mariana Clare is a researcher at the European Centre for Medium Range Weather Forecasts (ECMWF), where she works on building a machine learning model for weather forecasting. She is particularly interested on how to capture the model uncertainty in these data-driven approaches.
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