no code implementations • 22 Feb 2024 • Reed River Chen, Christopher Ribaudo, Jennifer Sleeman, Chace Ashcraft, Collin Kofroth, Marisa Hughes, Ivanka Stajner, Kevin Viner, Kai Wang
Due to a recent increase in extreme air quality events, both globally and locally in the United States, finer resolution air quality forecasting guidance is needed to effectively adapt to these events.
no code implementations • 23 Mar 2023 • Sophia Hamer, Jennifer Sleeman, Ivanka Stajner
In this work we describe a method that combines unsupervised learning and a forecast-aware bi-directional LSTM network to perform bias correction for operational air quality forecasting using AirNow station data for ozone and PM2. 5 in the continental US.
