04 May 2023
 | 04 May 2023
Status: this preprint is currently under review for the journal AMT.

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

Seyed Ali Sayedain, Norman T. O’Neill, James King, Patrick L. Hayes, Daniel Bellamy, Richard Washington, Sebastian Engelstaedter, Andy Vicente-Luis, Jill Bachelder, and Malo Bernhard

Abstract. 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 (vc (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 vdust (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 value with a prescribed value obtained from OPS-derived particle sizes coupled with dust-speciation-derived refractive indices led to the suggestion that the prescribed value could be increased to optically-derived values of 20 sr by the presence of optically significant dust particles at an effective radius of 11–12 µm. Bimodal CM PSDs from full-fledged AERONET inversions (the combination of AOD spectra and almucantar radiances) also showed CM peaks at ~ 1.3 µm and 5–6.6 µm radius: this, we argued, was associated with springtime Asian dust and Lhù’ààn Mân’ dust, respectively. Correlations between the CIMEL-derived fine mode (FM) AOD and FM OPS-derived particle-volume concentration suggest that remote sensing techniques can be employed to monitor FM dust (which is arguably a better indicator of the long-distance transport of HLD).

Seyed Ali Sayedain et al.

Status: open (until 24 Jun 2023)

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  • RC1: 'Comment on amt-2023-67', Anonymous Referee #1, 27 May 2023 reply

Seyed Ali Sayedain et al.

Seyed Ali Sayedain et al.


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Short summary
We used (columnar) ground-based remote sensing (RS) tools and surface measurements to characterize local (drainage-basin) dust plumes at a site in the Yukon. Plume height, particle size, and column to surface ratios enabled insight into how satellite RS could be used to analyze Arctic-wide dust transport. This helps modellers refine dust impacts in their climate change simulations. It is an important step since local dust is a key source of dust deposition on snow in the sensitive Arctic region.