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

Huttunen, Jani; Kokkola, Harri; Mielonen, Tero; Mononen, Mika Esa Juhani; Lipponen, Antti; Reunanen, Juha; Lindfors, Anders Vilhelm; Mikkonen, Santtu; Lehtinen, Kari Erkki Juhani; Kouremeti, Natalia; Bais, Alkiviadis; Niska, Harri; Arola, Antti

doi:https://doi.org/10.5194/acp-16-8181-2016

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.

https://doi.org/10.5194/acp-16-8181-2016

© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 16, issue 13

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, Harri Kokkola, Tero Mielonen, Mika Esa Juhani Mononen, Antti Lipponen, Juha Reunanen, Anders Vilhelm Lindfors, Santtu Mikkonen, Kari Erkki Juhani Lehtinen, Natalia Kouremeti, Alkiviadis Bais, Harri Niska, and Antti Arola

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Final revised paper (published on 07 Jul 2016)
Preprint (discussion started on 25 Jan 2016)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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RC1: 'Evaluation of methods to estimate AOD', Anonymous Referee #1, 22 Feb 2016
- AC1: 'The author's response for the referee 1', Jani Huttunen, 02 May 2016
RC2: 'Some minor considerations', Michael Taylor, 01 Mar 2016
- AC2: 'The author's response for the referee 2', Jani Huttunen, 02 May 2016

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

AR by Jani Huttunen on behalf of the Authors (02 May 2016) Author's response Manuscript

ED: Referee Nomination & Report Request started (19 May 2016) by Bernhard Mayer

RR by Anonymous Referee #1 (20 May 2016)

ED: Reconsider after minor revisions (Editor review) (01 Jun 2016) by Bernhard Mayer

AR by Jani Huttunen on behalf of the Authors (09 Jun 2016) Author's response Manuscript

ED: Publish as is (14 Jun 2016) by Bernhard Mayer

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.