A Lagrangian Time-Series Machine Learning Framework for Predicting Concentrations and Exploring Drivers of Atmospheric Aerosols: Model Development and Application to Cloud Condensation Nuclei in Marine Boundary Layer
Zhou, Shengqian; Qi, Dong; Liu, Hanyang; Vorobeychik, Yevgeniy; Wang, Jian;
A Lagrangian Time-Series Machine Learning Framework for Predicting Concentrations and Exploring Drivers of Atmospheric Aerosols: Model Development and Application to Cloud Condensation Nuclei in Marine Boundary Layer
This preprint presents a Lagrangian time-series machine learning framework for predicting atmospheric aerosol concentrations and investigating their environmental drivers. We demonstrate the advantages of this approach through an application to marine boundary layer cloud condensation nuclei.
Machine Learning, Cloud Condensation Nuclei, FOS: Earth and related environmental sciences, Aerosol-Cloud Interactions, Atmospheric Sciences
Machine Learning, Cloud Condensation Nuclei, FOS: Earth and related environmental sciences, Aerosol-Cloud Interactions, Atmospheric Sciences
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