Dust aerosol emission over the Sahara during summertime from Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) observations

作者：Todd Martin C^*; Cavazos Guerra Carolina

来源：Atmospheric Environment, 2016, 128: 147-157.

DOI：10.1016/j.atmosenv.2015.12.037

• Sahara
• Dust
• Aerosol
• Preferential sources
• CALIOP
• Lidar

Dust aerosols are an important component of the climate system and a challenge to incorporate into weather and climate models. Information on the location and magnitude of dust emission remains a key information gap to inform model development. Inadequate surface observations ensure that satellite data remain the primary source of this information over extensive and remote desert regions. Here, we develop estimates of the relative magnitude of active dust emission over the Sahara desert based on data from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP). Utilising the unique vertical profile of aerosol characteristics provided by CALIOP our algorithm identifies emission from aerosol extinction and lidar backscatter in the near surface layers. From the long-term CALIOP archive of day and night-time orbits over 2006-13 we construct coarse resolution maps of a new dust emission index (DEI) for the Sahara desert during the peak summer dust season (June to September). The spatial structure of DEI indicates highest emission over a broad zone focused on the border regions of Southern Algeria, Northern Mali and northwest Niger, displaced substantially (similar to 7 degrees) to the east of the mean maximum in satellite-derived aerosol optical depth. In this region night-time emission exceeds that during the day. The DEI maps substantially corroborate recently derived dust source frequency count maps based on back-tracking plumes in high temporal resolution SEVIRI imagery. As such, a convergence of evidence from multiple satellite data sources using independent methods provides an increasingly robust picture of Saharan dust emission sources. Various caveats are considered. As such, quantitative estimates of dust emission may require a synergistic combined multi-sensor analysis.

• 出版日期2016-3