Aerosol optical depth retrievals at the Izaña Atmospheric Observatory from 1941 to 2013 by using artificial neural networks

This paper presents the reconstruction of a 73-year time series of the aerosol optical depth (AOD) at 500 nm at the subtropical high-mountain Izaña Atmospheric Observatory (IZO) located in Tenerife (Canary Islands, Spain). For this purpose, we have combined AOD estimates from artificial neural netwo...

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Published in:Atmospheric Measurement Techniques
Main Authors: García, R. D., García, O. E., Cuevas, E., Cachorro, V. E., Barreto, A., Guirado-Fuentes, C., Kouremeti, N., Bustos, J. J., Romero-Campos, P. M., Frutos, A. M.
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Language:English
Published: 2018
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Online Access:https://doi.org/10.5194/amt-9-53-2016
https://amt.copernicus.org/articles/9/53/2016/
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spelling ftcopernicus:oai:publications.copernicus.org:amt31569 2023-05-15T13:06:26+02:00 Aerosol optical depth retrievals at the Izaña Atmospheric Observatory from 1941 to 2013 by using artificial neural networks García, R. D. García, O. E. Cuevas, E. Cachorro, V. E. Barreto, A. Guirado-Fuentes, C. Kouremeti, N. Bustos, J. J. Romero-Campos, P. M. Frutos, A. M. 2018-10-11 application/pdf https://doi.org/10.5194/amt-9-53-2016 https://amt.copernicus.org/articles/9/53/2016/ eng eng doi:10.5194/amt-9-53-2016 https://amt.copernicus.org/articles/9/53/2016/ eISSN: 1867-8548 Text 2018 ftcopernicus https://doi.org/10.5194/amt-9-53-2016 2020-07-20T16:24:19Z This paper presents the reconstruction of a 73-year time series of the aerosol optical depth (AOD) at 500 nm at the subtropical high-mountain Izaña Atmospheric Observatory (IZO) located in Tenerife (Canary Islands, Spain). For this purpose, we have combined AOD estimates from artificial neural networks (ANNs) from 1941 to 2001 and AOD measurements directly obtained with a Precision Filter Radiometer (PFR) between 2003 and 2013. The analysis is limited to summer months (July–August–September), when the largest aerosol load is observed at IZO (Saharan mineral dust particles). The ANN AOD time series has been comprehensively validated against coincident AOD measurements performed with a solar spectrometer Mark-I (1984–2009) and AERONET (AErosol RObotic NETwork) CIMEL photometers (2004–2009) at IZO, obtaining a rather good agreement on a daily basis: Pearson coefficient, R , of 0.97 between AERONET and ANN AOD, and 0.93 between Mark-I and ANN AOD estimates. In addition, we have analysed the long-term consistency between ANN AOD time series and long-term meteorological records identifying Saharan mineral dust events at IZO (synoptical observations and local wind records). Both analyses provide consistent results, with correlations > 85 %. Therefore, we can conclude that the reconstructed AOD time series captures well the AOD variations and dust-laden Saharan air mass outbreaks on short-term and long-term timescales and, thus, it is suitable to be used in climate analysis. Text Aerosol Robotic Network Copernicus Publications: E-Journals Atmospheric Measurement Techniques 9 1 53 62
institution Open Polar
collection Copernicus Publications: E-Journals
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language English
description This paper presents the reconstruction of a 73-year time series of the aerosol optical depth (AOD) at 500 nm at the subtropical high-mountain Izaña Atmospheric Observatory (IZO) located in Tenerife (Canary Islands, Spain). For this purpose, we have combined AOD estimates from artificial neural networks (ANNs) from 1941 to 2001 and AOD measurements directly obtained with a Precision Filter Radiometer (PFR) between 2003 and 2013. The analysis is limited to summer months (July–August–September), when the largest aerosol load is observed at IZO (Saharan mineral dust particles). The ANN AOD time series has been comprehensively validated against coincident AOD measurements performed with a solar spectrometer Mark-I (1984–2009) and AERONET (AErosol RObotic NETwork) CIMEL photometers (2004–2009) at IZO, obtaining a rather good agreement on a daily basis: Pearson coefficient, R , of 0.97 between AERONET and ANN AOD, and 0.93 between Mark-I and ANN AOD estimates. In addition, we have analysed the long-term consistency between ANN AOD time series and long-term meteorological records identifying Saharan mineral dust events at IZO (synoptical observations and local wind records). Both analyses provide consistent results, with correlations > 85 %. Therefore, we can conclude that the reconstructed AOD time series captures well the AOD variations and dust-laden Saharan air mass outbreaks on short-term and long-term timescales and, thus, it is suitable to be used in climate analysis.
format Text
author García, R. D.
García, O. E.
Cuevas, E.
Cachorro, V. E.
Barreto, A.
Guirado-Fuentes, C.
Kouremeti, N.
Bustos, J. J.
Romero-Campos, P. M.
Frutos, A. M.
spellingShingle García, R. D.
García, O. E.
Cuevas, E.
Cachorro, V. E.
Barreto, A.
Guirado-Fuentes, C.
Kouremeti, N.
Bustos, J. J.
Romero-Campos, P. M.
Frutos, A. M.
Aerosol optical depth retrievals at the Izaña Atmospheric Observatory from 1941 to 2013 by using artificial neural networks
author_facet García, R. D.
García, O. E.
Cuevas, E.
Cachorro, V. E.
Barreto, A.
Guirado-Fuentes, C.
Kouremeti, N.
Bustos, J. J.
Romero-Campos, P. M.
Frutos, A. M.
author_sort García, R. D.
title Aerosol optical depth retrievals at the Izaña Atmospheric Observatory from 1941 to 2013 by using artificial neural networks
title_short Aerosol optical depth retrievals at the Izaña Atmospheric Observatory from 1941 to 2013 by using artificial neural networks
title_full Aerosol optical depth retrievals at the Izaña Atmospheric Observatory from 1941 to 2013 by using artificial neural networks
title_fullStr Aerosol optical depth retrievals at the Izaña Atmospheric Observatory from 1941 to 2013 by using artificial neural networks
title_full_unstemmed Aerosol optical depth retrievals at the Izaña Atmospheric Observatory from 1941 to 2013 by using artificial neural networks
title_sort aerosol optical depth retrievals at the izaña atmospheric observatory from 1941 to 2013 by using artificial neural networks
publishDate 2018
url https://doi.org/10.5194/amt-9-53-2016
https://amt.copernicus.org/articles/9/53/2016/
genre Aerosol Robotic Network
genre_facet Aerosol Robotic Network
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https://amt.copernicus.org/articles/9/53/2016/
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container_title Atmospheric Measurement Techniques
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