Analysis of Lhù’ààn Mân’ (Kluane Lake) dust plumes using passive and active ground-based remote sensing supported by physical surface measurements

• Main Authors: Sayedain, Seyed Ali, O’Neill, Norman T., King, James, Hayes, Patrick L., Bellamy, Daniel, Washington, Richard, Engelstaedter, Sebastian, Vicente-Luis, Andy, Bachelder, Jill, Bernhard, Malo
• Format: Text
• Language: English
• Published: 2023
• Subjects: Arctic; Kluane Lake; Yukon
• Online Access: https://doi.org/10.5194/amt-2023-67; https://amt.copernicus.org/preprints/amt-2023-67/

There is growing recognition that high latitude dust (HLD), originating from local, drainage-basin flows, is the dominant source for certain important phenomena such as particle deposition on snow / ice. The analysis of such local plumes (including a better exploitation of remote sensing data) has been targeted as a key aerosol issue by the HLD community. The sub-Arctic Lhù’ààn Mân’ (Kluane Lake) region in the Canadian Yukon is subject to regular drainage, wind-induced dust plumes. This dust emission site is one of many current and potential proglacial dust sources in the Canadian North. In situ ground-based measurements are, due to constraints in accessing these types of regions, rare. Ground- and satellite-based remote sensing accordingly play an important role in helping characterize local dust sources in the Arctic and sub-Arctic. We compared ground-based, passive and active remote sensing springtime (May 2019) retrievals with microphysical surface-based measurements in the Lhù’ààn Mân’ region in order to better understand the potential for ground- and satellite-based remote sensing of HLD plumes. This included correlation analyzes between ground-based coarse mode (CM) aerosol optical depth (AOD) retrievals from AERONET AOD spectra, CM AODs derived from co-located Doppler lidar profiles and OPS (Optical Particle Sizer) surface measurements of CM particle-volume concentration ( v c (0)). An automated dust classification scheme was developed to objectively identify local dust events. The classification process helped distinguish lidar-derived CM AODs which co-varied with v dust (0) (during recognized dust events) and those that varied at the same columnar scale as AERONET-derived CM AOD (and thus could be remotely sensed). False positive cloud events for which dust-induced, high frequency variations in lidar-derived CM AODs in cloudless atmospheres indicated that the AERONET cloud-screening process was rejecting CM dust AODs. The persistence of a positive lidar ratio bias in comparing the CIMEL/lidar-derived ...