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BEGIN:VEVENT
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UID:MEC-c22abfa379f38b5b0411bc11fa9bf92f@phervietnam.org
DTSTART:20230328T020000Z
DTEND:20230328T040000Z
DTSTAMP:20230328T074500Z
CREATED:20230328
LAST-MODIFIED:20240113
PRIORITY:5
SEQUENCE:8
TRANSP:OPAQUE
SUMMARY:Webinar: Weather forecast using Predictive Recurrent Neural Networks
DESCRIPTION:Speaker\nDr. Hoang Viet Tran\nPacific Northwest National Laboratory\nAbstract:\nNumerical Weather Prediction (NWP) models provide reliable global forecasts but require high computational cost. Deep Learning (DL) emulators trained on NWP outputs offer cost-effective and reliable forecasts. However, current DL models oversimplify the temporal component leading to prediction errors accumulated quickly as the lead time increase.\nWe propose a DL architecture with more focus on weather variables’ dynamics through time. Our Predictive Recurrent Neural Network (PredRNN), previously used for modeling video dynamics, was trained on outputs of the European Centre for Medium-Range Weather Forecasts (ECMWF). Preliminary results show that the PredRNN outperformed the operational ECMWF and two latest DL emulators in forecasting wind speed, precipitation and sea surface pressure for hurricane Sandy. Our findings suggest that incorporating temporal dynamics in DL weather forecasting models can improve their accuracy.\n
URL:https://phervietnam.org/events/webinar-weather-forecast-using-predictive-recurrent-neural-networks/
CATEGORIES:Research & Innovation,VIAN Webinar and Training Courses
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