A gridded air quality forecast through fusing site-available machine learning predictions from RFSML v1.0 and chemical transport model results from GEOS-Chem v13.1.0 using the ensemble Kalman filter
<p>Statistical methods, particularly machine learning models, have gained significant popularity in air quality predictions. These prediction models are commonly trained using the historical measurement datasets independently collected at the environmental monitoring stations and their operati...
| Published in: | Geoscientific Model Development |
|---|---|
| Main Authors: | , , , , , , , , |
| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2023-08-01
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| Online Access: | https://gmd.copernicus.org/articles/16/4867/2023/gmd-16-4867-2023.pdf |