BEGIN:VCALENDAR
VERSION:2.0
METHOD:PUBLISH
CALSCALE:GREGORIAN
PRODID:-//WordPress - MECv7.34.2//EN
X-ORIGINAL-URL:https://essic.umd.edu/
X-WR-CALNAME:ESSIC
X-WR-CALDESC:UMD - Earth System Science Interdisciplinary Center
X-WR-TIMEZONE:America/New_York
BEGIN:VTIMEZONE
TZID:America/New_York
X-LIC-LOCATION:America/New_York
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20260308T030000
RRULE:FREQ=YEARLY;BYMONTH=03;BYDAY=2SU
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20261101T010000
RRULE:FREQ=YEARLY;BYMONTH=11;BYDAY=1SU
END:STANDARD
END:VTIMEZONE
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-PUBLISHED-TTL:PT1H
X-MS-OLK-FORCEINSPECTOROPEN:TRUE
BEGIN:VEVENT
CLASS:PUBLIC
UID:MEC-c752a2fef40ec94d00999635f7599f25@essic.umd.edu
DTSTART;TZID=America/New_York:20211012T140000
DTEND;TZID=America/New_York:20211012T150000
DTSTAMP:20230905T131446Z
CREATED:20230905
LAST-MODIFIED:20230905
PRIORITY:5
SEQUENCE:0
TRANSP:OPAQUE
SUMMARY:Changing Precipitation and the Potential for Machine Learning To Improve Climate Predictions
DESCRIPTION:This event has passed. See the seminar recording here:\n\n \n\n\nProf. Paul O’Gorman\nProfessor of Atmospheric Science\nMassachusetts Institute of Technology\nTuesday October 12, 2021, 2 PM ET\n \nAbstract:\nChanges in precipitation due to greenhouse gas emissions can have a major impact on society and ecosystems. The response of both mean and extreme precipitation varies strongly by region and season in ways that are not well understood. Climate models struggle to accurately simulate precipitation and associated circulations in the current climate, making it difficult to predict the climate-change response. In this talk, I will discuss efforts to develop new machine-learning parameterizations for climate models to improve the simulation of precipitation patterns and winds. I will focus on approaches that are physically consistent, stable and robust, and which can be applied over a range of spatial resolutions.\n \nBiosketch:\nPaul O’Gorman is a Professor of Atmospheric Science at MIT. His research is motivated by the need to understand how the hydrological cycle and atmospheric circulations respond to climate change. Particular areas of interest include the extratropical storm tracks, moist convection, and extreme precipitation. In addition to developing theory and analyzing simulations and observations, his research group is working to improve climate models through machine learning.\n \nWebinar:\nWebinar: https://go.umd.edu/ogormanwebinar ( https://go.umd.edu/ogormanwebinar )\nEvent site: https://go.umd.edu/ogorman ( https://go.umd.edu/ogorman )\nWebinar number: 2622 839 2890\nWebinar password: essic\nTo join the audio conference only:\nUS Toll: +1-415-655-0002\nGlobal call-in numbers ( https://umd.webex.com/umd/globalcallin.php?MTID=e492bfe8c2d628cca31b7c1f3b7185bcf )\n \nFor IT assistance:\nCazzy Medley: cazzy@umd.edu ( mailto:cazzy@umd.edu )\nResources:\nSeminar schedule & archive: https://go.umd.edu/essicseminar ( https://go.umd.edu/essicseminar )\nSeminar Google calendar: https://go.umd.edu/essicseminarcalendar ( https://go.umd.edu/essicseminarcalendar )\nSeminar recordings on Youtube: https://www.youtube.com/user/ESSICUMD ( https://www.youtube.com/user/ESSICUMD )\n
URL:https://essic.umd.edu/events/changing-precipitation-and-the-potential-for-machine-learning-to-improve-climate-predictions/
ORGANIZER;CN=John Xun Yang:MAILTO:jxyang@umd.edu
CATEGORIES:Fall 2021
ATTACH;FMTTYPE=image/jpeg:https://essic.umd.edu/wp-content/uploads/2023/09/headshot_Paul.OGorman-scaled.jpg
END:VEVENT
END:VCALENDAR