Preprints
https://doi.org/10.5194/egusphere-2022-1156
https://doi.org/10.5194/egusphere-2022-1156
 
16 Jan 2023
16 Jan 2023
Status: this preprint is open for discussion.

The importance of detection thresholds for the quantification of source and timing of high-latitude dust emission using remote sensing

Rosemary Alice Huck1, Robert G. Bryant2, and James King3 Rosemary Alice Huck et al.
  • 1School of Geography and the Environment, Oxford University Centre for the Environment, University of Oxford, Oxford OX1 3QY, UK
  • 2Department of Geography, University of Sheffield, Sheffield S10 2TN, UK
  • 3Laboratoire d’Érosion Éolienne, Département de Géographie, Université de Montréal, Montréal, H2V 0B3, Canada

Abstract. The observation and quantification of mineral dust fluxes from high-latitude sources remains difficult due to a known paucity of year-round in situ observations and known limitations of satellite remote sensing data (e.g., cloud cover and dust detection). Here we explore the chronology of dust emissions at a known and instrumented high latitude dust source: Lhù’ààn Mân (Kluane Lake) in Yukon, Canada. At this location we combine ground instrumentation, space-based remote sensing platforms, ground-based AERONET data, and oblique camera images to (i) investigate the daily to annual chronology of dust emissions recorded by these instrumental and remote sensing methods (at timescales ranging from minutes to years), and (ii) use data intercomparisons to comment on the principal factors that control the detection of dust in each case. Dust emissions were observed using oblique time-lapse (RC) cameras installed at Lhù’ààn Mân for up to 23 hours a day. These were used as a baseline for analysis of aerosol retrievals from in situ metrological data, AERONET, and co-incident MODIS MAIAC.

Use of high-cadence remote camera (RC) data collected during dust events allowed us to optimise the use of combination of date quality (DQ) 1 (aerosol optical depth - AOD) and DQ2 (single scattering albedo and Angstöm exponent) to best represent AOD dust retrievals from AERONET. Nevertheless, when compared with time series of RC data, optimised AERONET data only manage an overall 26 % detection rate for events (sub day) but 100 % detection rate for dust event days (DED) when dust was within the field of view. Here, in this instance, RC and remote sensing data were able to suggest that the low event detection rate was attributed to fundamental variations in dust advection trajectory, dust plume height, and inherent restrictions in sun angle at high latitudes. Working with a time series of optimised AOD data (covering 2018/2019), we were able to investigate the gross impacts of DQ choice on DED detection at the month/year scale. Relative to ground observations, AERONET’s DQ2.0 cloud screening algorithm may remove as much as 97 % of known dust events (3 % detection). Finally, when undertaking an AOD comparison for DED and non-DED retrievals, we find that cloud screening of MODIS/AERONET lead to a combined low sample of co-incident dust events, and weak correlations between retrievals. Our results quantify and explain the extent of under-representation of dust in both ground and space remote sensing method; a factor which impacts on the effective calibration and validation of global climate and dust models.

Rosemary Alice Huck et al.

Status: open (until 27 Feb 2023)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse

Rosemary Alice Huck et al.

Data sets

Meterological data Rosemary Huck, James King https://doi.org/10.5281/zenodo.7249227

Remote camera images James King, Rosemary Huck https://doi.org/10.5281/zenodo.7249227

Rosemary Alice Huck et al.

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Short summary
This study shows that mineral aerosols (dust) emission events in high-latitude areas are under-represented in both ground and space detecting methods. This is done through a suite of ground-based data to prove that dust emissions from the proglacial area, Lhù’ààn Mân occur almost daily but are not always recorded at different timescales. Dust has multiple effects on atmospheric process, therefore accurate quantification is important in the calibration and validation of climate models.