Articles | Volume 16, issue 13
https://doi.org/10.5194/acp-16-8181-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/acp-16-8181-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
07 Jul 2016
Research article |
| 07 Jul 2016
Retrieval of aerosol optical depth from surface solar radiation measurements using machine learning algorithms, non-linear regression and a radiative transfer-based look-up table
Jani Huttunen
Finnish Meteorological Institute (FMI), Atmospheric
Research Centre of Eastern Finland, Kuopio, Finland
Department of Applied Physics, University of Eastern
Finland, Kuopio, Finland
Harri Kokkola
Finnish Meteorological Institute (FMI), Atmospheric
Research Centre of Eastern Finland, Kuopio, Finland
Tero Mielonen
Finnish Meteorological Institute (FMI), Atmospheric
Research Centre of Eastern Finland, Kuopio, Finland
Mika Esa Juhani Mononen
Independent researcher, Kuopio, Finland
Antti Lipponen
Finnish Meteorological Institute (FMI), Atmospheric
Research Centre of Eastern Finland, Kuopio, Finland
Department of Applied Physics, University of Eastern
Finland, Kuopio, Finland
Juha Reunanen
Tomaattinen Oy, Helsinki, Finland
Anders Vilhelm Lindfors
Finnish Meteorological Institute (FMI), Atmospheric
Research Centre of Eastern Finland, Kuopio, Finland
Santtu Mikkonen
Department of Applied Physics, University of Eastern
Finland, Kuopio, Finland
Kari Erkki Juhani Lehtinen
Finnish Meteorological Institute (FMI), Atmospheric
Research Centre of Eastern Finland, Kuopio, Finland
Department of Applied Physics, University of Eastern
Finland, Kuopio, Finland
Natalia Kouremeti
Physikalisch-Meteorologisches Observatorium Davos,
Dorfstrasse 33, 7260 Davos Dorf, Switzerland
Aristotle University of Thessaloniki, Laboratory of
Atmospheric Physics, Thessaloniki, 54124, Greece
Alkiviadis Bais
Aristotle University of Thessaloniki, Laboratory of
Atmospheric Physics, Thessaloniki, 54124, Greece
Harri Niska
Department of Environmental and Biological Sciences,
University of Eastern Finland, Kuopio, Finland
Finnish Meteorological Institute (FMI), Atmospheric
Research Centre of Eastern Finland, Kuopio, Finland
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Latest update: 18 Nov 2025
Short summary
For a good estimate of the current forcing by anthropogenic aerosols, knowledge in past is needed. One option to lengthen time series is to retrieve aerosol optical depth from solar radiation measurements. We have evaluated several methods for this task. Most of the methods produce aerosol optical depth estimates with a good accuracy. However, machine learning methods seem to be the most applicable not to produce any systematic biases, since they do not need constrain the aerosol properties.
For a good estimate of the current forcing by anthropogenic aerosols, knowledge in past is...
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