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American Meteorological Society, Journal of the Atmospheric Sciences, 4(66), p. 1033-1040, 2009

DOI: 10.1175/2008jas2816.1

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Aerosol Radiative Forcing and Forcing Efficiency in the UVB for Regions Affected by Saharan and Asian Mineral Dust

Journal article published in 2009 by O. E. García, A. M. Díaz, F. J. Expósito, J. P. Díaz, A. Redondas ORCID, T. Sasaki
This paper is available in a repository.
This paper is available in a repository.

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Abstract

Abstract The influence of mineral dust on ultraviolet energy transfer is studied for two different mineralogical origins. The aerosol radiative forcing ΔF and the forcing efficiency at the surface ΔFeff in the range 290–325 nm were estimated in ground-based stations affected by the Saharan and Asian deserts during the dusty seasons. UVB solar measurements were taken from the World Ozone and Ultraviolet Data Center (WOUDC) for four Asian stations (2000–04) and from the Santa Cruz Observatory, Canary Islands (2002–03), under Gobi and Sahara Desert influences, respectively. The Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol optical depth at 550 nm was used to characterize the aerosol load τ, whereas the aerosol index provided by the Total Ozone Mapping Spectrometer (TOMS) sensor was employed to identify the mineral dust events. The ΔF is strongly affected by the aerosol load, the values found being comparable in both regions during the dusty seasons. Under those conditions, ΔF values as large as −1.29 ± 0.53 W m−2 (τ550 = 0.48 ± 0.24) and −1.43 ± 0.38 W m−2 (τ550 = 0.54 ± 0.26) were reached under Saharan and Asian dust conditions, respectively. Nevertheless, significant differences have been observed in the aerosol radiative forcing per unit of aerosol optical depth in the slant path, τS. The maximum ΔFeff values associated with dust influences were −1.55 ± 0.20 W m−2 τS550−1 for the Saharan region and −0.95 ± 0.11 W m−2 τS550−1 in the Asian area. These results may be used as a benchmark database for establishing aerosol corrections in UV satellite products or in global climate model estimations.