The reconstruction of a 73-year time series of AOD at 500 nm by using artificial neural networks.

The reconstruction of a 73-year time series of AOD at 500 nm at IZO has been achieved by using artificial neural networks (ANNs) from 1941 to 2001 and AOD measurements directly obtained with a Precision Filter Radiometer (PFR) between 2003 and 2013. The ANN AOD time series has been comprehensively validated against  coincident  AOD  measurements  performed  with  a  solar  spectrometer  Mark-I  (1984–2009)  and AERONET  CIMEL photometers (2004–2009) at IZO, obtaining a rather good agreement on a daily basis (Pearson R=0.97 between AERONET and ANN AOD, and 0.93 between Mark -I and ANN AOD estimates). The ANN method has proved to be a very useful tool for the reconstruction of daily AOD values at 500 nm from meteorological input data, such as the horizontal visibility, fraction of clear sky, and relative humidity, recorded at IZO. This methodology might be extrapolated to other sites, especially those affected by high
dust loads. See García et al. (2016).

foto_serie_ANN_AODFigure.-  (a) Time series of the number of days grouped into ANN AOD intervals (AOD≥  0.05; AOD≥0.10; AOD≥0.20) on the left axis, while on the right axis, the bars indicate the number of days with SYNOP data reporting dust in suspension (05–06 SYNOP codes) for the period 1941–2009. The 5-year running mean is shown in black. (b) Scatterplot of number of days with ANN AOD≥0.20 and number of days with 05–06 SYNOP codes. The least-square fit parameters are shown in the legend.