Sources, sinks, and transatlantic transport of North African dust aerosol: A multimodel analysis and comparison with remote sensing data

• Published in: Journal of Geophysical Research: Atmospheres
• Main Authors: Kim, D., Chin, M., Yu, H., Diehl, T., Tan, Q., Kahn, R.A., Tsigaridis, K., Bauer, S.E., Takemura, T., Pozzoli, L., Bellouin, N., Schulz, M, Peyridieu, Sophie, Chédin, A., Koffi, B.
• Other Authors: Universities Space Research Association Washington (USRA), GSFC Earth Sciences Division, NASA Goddard Space Flight Center (GSFC), Earth System Sciences Interdisciplinary Center College Park, University of Maryland College Park, University of Maryland System-University of Maryland System, Center for Climate Systems Research New York (CCSR), Columbia University New York, NASA Goddard Institute for Space Studies (GISS), Research Institute for Applied Mechanics, Kyushu University, Fukuoka, Japan, Avrasya Yer Bilimleri Enstitüsü = Eurasia Institute of Earth Sciences Istanbul (AYBE), Istanbul Technical University (ITÜ), Met Office Hadley Centre (MOHC), United Kingdom Met Office Exeter, Norwegian Meteorological Institute Oslo (MET), Laboratoire de Météorologie Dynamique (UMR 8539) (LMD), Université Pierre et Marie Curie - Paris 6 (UPMC)-Institut national des sciences de l'Univers (INSU - CNRS)-École polytechnique (X)-École des Ponts ParisTech (ENPC)-Centre National de la Recherche Scientifique (CNRS)-Département des Géosciences - ENS Paris, École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Air and Climate Unit Ispra, JRC Institute for Environment and Sustainability (IES), European Commission - Joint Research Centre Ispra (JRC)-European Commission - Joint Research Centre Ispra (JRC)
• Format: Article in Journal/Newspaper
• Language: English
• Published: HAL CCSD 2014
• Subjects: [SDU.STU.GP]Sciences of the Universe [physics]/Earth Sciences/Geophysics [physics.geo-ph]; Aerosol Robotic Network; North Atlantic
• Online Access: https://hal.science/hal-01087728; https://hal.science/hal-01087728/document; https://hal.science/hal-01087728/file/2013JD021099.pdf; https://doi.org/10.1002/2013JD021099

International audience This study evaluates model-simulated dust aerosols over North Africa and the North Atlantic from five global models that participated in the Aerosol Comparison between Observations and Models phase II model experiments. The model results are compared with satellite aerosol optical depth (AOD) data from Moderate Resolution Imaging Spectroradiometer (MODIS), Multiangle Imaging Spectroradiometer (MISR), and Sea-viewing Wide Field-of-view Sensor, dust optical depth (DOD) derived from MODIS and MISR, AOD and coarse-mode AOD (as a proxy of DOD) from ground-based Aerosol Robotic Network Sun photometer measurements, and dust vertical distributions/centroid height from Cloud Aerosol Lidar with Orthogonal Polarization and Atmospheric Infrared Sounder satellite AOD retrievals. We examine the following quantities of AOD and DOD: (1) the magnitudes over land and over ocean in our study domain, (2) the longitudinal gradient from the dust source region over North Africa to the western North Atlantic, (3) seasonal variations at different locations, and (4) the dust vertical profile shape and the AOD centroid height (altitude above or below which half of the AOD is located). The different satellite data show consistent features in most of these aspects; however, the models display large diversity in all of them, with significant differences among the models and between models and observations. By examining dust emission, removal, and mass extinction efficiency in the five models, we also find remarkable differences among the models that all contribute to the discrepancies of model-simulated dust amount and distribution. This study highlights the challenges in simulating the dust physical and optical processes, even in the best known dust environment, and stresses the need for observable quantities to constrain the model processes. Key Points North African dust is studied using observations and models Observations agree in the magnitude, distribution, and seasonality of dust Models show large differences ...