Air Quality Estimation and Forecasting via Data Fusion With Uncertainty Quantification: Theoretical Framework and Preliminary Results

Integrating air quality information from models, satellites, and in situ monitors allows for both better estimation of air quality and better quantification of uncertainties in this estimation. Uncertainty quantification is important to appropriately convey confidence in these estimates and forecast...

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Veröffentlicht in:	Journal of geophysical research. Machine learning and computation 2024-12, Vol.1 (4), p.n/a
Hauptverfasser:	Malings, Carl, Knowland, K. Emma, Pavlovic, Nathan, Coughlin, Justin G., King, Daniel, Keller, Christoph, Cohn, Stephen, Martin, Randall V.
Format:	Artikel
Sprache:	eng
Schlagworte:	air quality data fusion forecasting uncertainty quantification
Online-Zugang:	Volltext
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