Articles | Volume 10, issue 7
Atmos. Meas. Tech., 10, 2435–2453, 2017

Special issue: SKYNET – the international network for aerosol, clouds,...

Atmos. Meas. Tech., 10, 2435–2453, 2017
Research article
11 Jul 2017
Research article | 11 Jul 2017

Dust impact on surface solar irradiance assessed with model simulations, satellite observations and ground-based measurements

Panagiotis G. Kosmopoulos et al.

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Subject: Aerosols | Technique: Remote Sensing | Topic: Validation and Intercomparisons
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Cited articles

Allen, R. J., Norris, J. R., and Wild, M.: Evaluation of multidecadal variability in CMIP5 surface solar radiation and inferred underestimation of aerosol direct effects over Europe, China, Japan, and India, J. Geophys. Res.-Atmos., 118, 6311–6336,, 2013.
Amiridis, V., Kafatos, M., Perez, C., Kazadzis, S., Gerasopoulos, E., Mamouri, R. E., and Zerefos, C.: The potential of the synergistic use of passive and active remote sensing measurements for the validation of a regional dust model, Ann. Geophys., 27, 3155–3164, 2009.
Amiridis, V., Marinou, E., Tsekeri, A., Wandinger, U., Schwarz, A., Giannakaki, E., and Ansmann, A.: LIVAS: a 3-D multi-wavelength aerosol/cloud database based on CALIPSO and EARLINET, Atmos. Chem. Phys., 15, 7127–7153,, 2015.
Athanasopoulou, E., Rieger, D., Walter, C., Vogel., H., Karali, A., Hatzaki, M., and Roussos, A.: Fire risk, atmospheric chemistry and radiative forcing assessment of wildfires in eastern Mediterranean, Atmos. Environ., 95, 113–125, 2014.
Athanasopoulou, E., Protonotariou, A., Papangelis, G., Tombrou, M., Mihalopoulos, N., and Gerasopoulos, E.: Long-range transport of Saharan dust and chemical transformations over the Eastern Mediterranean, Atmos. Environ., 140, 592–604, 2016.
Short summary
We study the impact of dust on solar energy using remote sensing data in conjunction with synergistic modelling and forecasting techniques. Under high aerosol loads, we found great solar energy losses of the order of 80 and 50% for concentrated solar power and photovoltaic installations, respectively. The 1-day forecast presented an overall accuracy within 10% in direct comparison to the real conditions under high energy potential, optimising the efficient energy planning and policies.