Articles | Volume 18, issue 16
Atmos. Chem. Phys., 18, 12491–12510, 2018
https://doi.org/10.5194/acp-18-12491-2018
Atmos. Chem. Phys., 18, 12491–12510, 2018
https://doi.org/10.5194/acp-18-12491-2018
Research article
29 Aug 2018
Research article | 29 Aug 2018

How reliable are CMIP5 models in simulating dust optical depth?

Bing Pu and Paul Ginoux

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Cited articles

Abudu, S., Cui, C. L., King, J. P., Moreno, J., and Bawazir, A. S.: Modeling of daily pan evaporation using partial least squares regression, Sci. China Technol. Sc., 54, 163–174, https://doi.org/10.1007/s11431-010-4205-z, 2011. 
Arora, V. K., Scinocca, J. F., Boer, G. J., Christian, J. R., Denman, K. L., Flato, G. M., Kharin, V. V., Lee, W. G., and Merryfield, W. J.: Carbon emission limits required to satisfy future representative concentration pathways of greenhouse gases, Geophys. Res. Lett., 38, L05805, https://doi.org/10.1029/2010gl046270, 2011. 
Ashpole, I. and Washington, R.: A new high-resolution central and western Saharan summertime dust source map from automated satellite dust plume tracking, J. Geophys. Res.-Atmos., 118, 6981–6995, https://doi.org/10.1002/jgrd.50554, 2013. 
Baddock, M. C., Ginoux, P., Bullard, J. E., and Gill, T. E.: Do MODIS-defined dust sources have a geomorphological signature?, Geophys. Res. Lett., 43, 2606–2613, https://doi.org/10.1002/2015gl067327, 2016. 
Bangert, M., Nenes, A., Vogel, B., Vogel, H., Barahona, D., Karydis, V. A., Kumar, P., Kottmeier, C., and Blahak, U.: Saharan dust event impacts on cloud formation and radiation over Western Europe, Atmos. Chem. Phys., 12, 4045–4063, https://doi.org/10.5194/acp-12-4045-2012, 2012. 
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Short summary
Biases in dust modeling may result in biases in simulating energy budget and regional climate. Output of seven Coupled Model Intercomparison Project Phase 5 (CMIP5) models is examined. Seasonal cycle and spatial pattern of dust optical depth (DOD) in very dusty regions are largely captured by multi-model mean. But observed connections between DOD and local controlling factors such as bareness are not well represented. Future projections by CMIP5 models and a regression model are also analyzed.
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