Abstract
This study explores the direct and semi-direct radiative effect of North African dust in the present and future climate using the regional climate model RegCM4. The simulations cover a historical decade extending from December 1999 to November 2009 and a future decade that spans from December 2089 to November 2099 under the Representative Concentration Pathway 4.5 (RCP4.5), without considering land-cover/land-use changes. For each time-slice a set of two experiments was conducted, namely the “Control”, in which dust is radiatively inactive and the “Feedback”, in which dust interacts with shortwave and longwave radiation. The impact of North African dust on the regional radiative balance is assessed by comparing the “Feedback” and the “Control” experiments during the historical period. The results indicate that the combined effect of dust Direct + Semi-direct Radiative Effect (DSRE) on the shortwave is − 13.8 W m−2 and − 10.7 W m−2 over the Sahel and the Sahara, respectively. The Direct Radiative Effect (DRE) dominates over the Semi-direct Radiative Effect (SRE) in both winter and summer, although during summer over some parts of the desert the SRE in the longwave spectrum accounts for almost 50% of the DSRE. Part of this is due to a noteworthy statistically significant increase of clouds that reaches values up to 3% and stretches across the eastern and western Sahara desert. Dust DSRE intensifies moderately in the future period (− 15.8 W m−2 and − 11.0 W m−2), while its spatial distribution remains the same, suggesting that the effect of climate change in the atmosphere will not alter the radiative effect of dust over North Africa considerably. When taking into account the dust radiative feedback in regional climate simulations the maximum temperature is altered by − 0.2/− 0.2 °C and − 0.3/− 0.6 °C over the Sahel and Sahara regions, respectively, during the summer/winter period, mainly as a result of changes in the shortwave radiative balance. On the contrary, the minimum temperature increases, since it is mostly controlled by the longwave radiation emitted from the Earth’s surface. In the future period the near surface air temperature increases by 1.5–2.5 °C and the fine dust column burden increases by + 4% to + 8% in comparison to the historical period, mainly due to the RCP4.5 forcing. When the dust feedback on climate is active in future simulations it can decrease the summer daily maximum temperature by 0.3 °C over Sahel, and decrease or increase it locally in Sahara by up to 0.2 °C. Prior to the Feedback-Control analysis an extensive evaluation has been conducted for dust optical depth, dust extinction, near surface air temperature and cloud fraction cover using the LIVAS, CRU and CM SAF datasets.
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Acknowledgements
Results presented in this work have been produced using the AUTH Scientific Computing Centre Infrastructure and technical support. This work was also supported by computational time granted from the Greek Research & Technology Network (GRNET) in the National High Performance Computing facility ARIS under the projects “Direct Climate Feedback of Dust (DCFD)” and “Dataset for dUst effect on Climate, Health, Economy and Society Studies (DUCHESS)”. The authors would like also to acknowledge the use of data from the LIVAS (http://lidar.space.noa.gr:8080/livas), CM SAF (http://www.cmsaf.eu) and CRU (https://crudata.uea.ac.uk/cru/data/hrg) databases.
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Appendix
Modified Normalized Mean Bias (MNMB): \(MNMB = \frac{2}{N}\mathop \sum \limits_{i}^{{}} \frac{{{\text{sim}}_{i} - obs_{i} }}{{{\text{sim}}_{i} + obs_{i} }}\)
Fractional Gross Error (FGE): \(FGE = \frac{2}{N}\mathop \sum \limits_{i}^{{}} \left| {\frac{{sim_{i} - obs_{i} }}{{sim_{i} + obs_{i} }}} \right|\)
Percent Bias (P.Bias): \(P.Bias = \frac{{100 \times \left[ {\sum \left( {{\text{sim}} - obs} \right)} \right]}}{{\sum \left( {obs} \right)}}\) where obs and sim is the observed and model quantities, respectively. N is the population.
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Tsikerdekis, A., Zanis, P., Georgoulias, A.K. et al. Direct and semi-direct radiative effect of North African dust in present and future regional climate simulations. Clim Dyn 53, 4311–4336 (2019). https://doi.org/10.1007/s00382-019-04788-z
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DOI: https://doi.org/10.1007/s00382-019-04788-z