Retrieval of Aerosol Optical Properties via an All-Sky Imager and Machine Learning: Uncertainty in Direct Normal Irradiance Estimations

Retrieval of Aerosol Optical Properties via an All-Sky Imager and Machine Learning: Uncertainty in Direct Normal Irradiance Estimations

Quality-assured aerosol optical properties (AOP) with high spatiotemporal resolution are vital for the accurate estimation of direct aerosol radiative forcing and solar irradiance under clear skies. In this study, the sky information from an all-sky imager (ASI) is used with machine learning (ML) sy...

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Bibliographic Details
Main Authors: Stavros-Andreas Logothetis, Christos-Panagiotis Giannaklis, Vasileios Salamalikis, Panagiotis Tzoumanikas, Panagiotis-Ioannis Raptis, Vassilis Amiridis, Kostas Eleftheratos, Andreas Kazantzidis
Format: Article
Language:English
Published: MDPI AG 2023-08-01
Series:Environmental Sciences Proceedings
Subjects:
all-sky imager
aerosol optical properties
machine learning
aerosol retrieval
AERONET
DNI estimations
Online Access:https://www.mdpi.com/2673-4931/26/1/133

Internet

https://www.mdpi.com/2673-4931/26/1/133

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