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Glacier ice surface properties in South-West Greenland Ice Sheet: first estimates from PRISMA imaging spectroscopy data

Urheber*innen
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Bohn,  Niklas
1.4 Remote Sensing, 1.0 Geodesy, Departments, GFZ Publication Database, Deutsches GeoForschungsZentrum;

Di Mauro,  B.
External Organizations;

Colombo,  R.
External Organizations;

Thompson,  D. R.
External Organizations;

Susiluoto,  J.
External Organizations;

Carmon,  N.
External Organizations;

Turmon,  M. J.
External Organizations;

Guanter,  L.
External Organizations;

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5010018.pdf
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Zitation

Bohn, N., Di Mauro, B., Colombo, R., Thompson, D. R., Susiluoto, J., Carmon, N., Turmon, M. J., Guanter, L. (2022): Glacier ice surface properties in South-West Greenland Ice Sheet: first estimates from PRISMA imaging spectroscopy data. - Journal of Geophysical Research: Biogeosciences, 127, 3, e2021JG006718.
https://doi.org/10.1029/2021JG006718


Zitierlink: https://gfzpublic.gfz-potsdam.de/pubman/item/item_5010018
Zusammenfassung
Snow and ice melt processes on the Greenland Ice Sheet are a key in Earth’s energy balance and are acutely sensitive to climate change. Melting dynamics are directly related to a decrease in surface albedo, amongst others caused by the accumulation of light-absorbing particles (LAPs). Featuring unique spectral patterns, these accumulations can be mapped and quantified by imaging spectroscopy. We present first results for the retrieval of glacier ice properties from the spaceborne PRISMA imaging spectrometer by applying a recently developed simultaneous inversion of atmospheric and surface state using optimal estimation. The image analyzed in this study was acquired over the South-West margin of the Greenland Ice Sheet in late August 2020. The area is characterized by patterns of both clean and dark ice associated with a high amount of LAPs deposited on the surface. We present retrieval maps and uncertainties for grain size, liquid water, and algae concentration, as well as estimated reflectance spectra for different surface properties. We then show the feasibility of using imaging spectroscopy to interpret multiband sensor data to achieve high accuracy, frequently repeated observations of changing snow and ice conditions. For example, the impurity index calculated from multiband Sentinel-3 OLCI measurements is dependent on dust particles, but we show that algae concentration alone can be predicted from this data with less than 20 % uncertainty. Our study evidence that present and upcoming orbital imaging spectroscopy missions such as PRISMA, EnMAP, CHIME, and the SBG designated observable, can significantly support research of melting ice sheets.