Retrievals of Lake Ice Thickness From Great Slave Lake and Great Bear Lake Using CryoSat-2


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Christian.Haas [ at ] awi.de

Abstract

Satellite observations have revealed decreases in the duration of the seasonal snow and ice coverage of Great Slave Lake (GSL) and Great Bear Lake (GBL), large freshwater lakes in Northern Canada. However, limited information is available about ice thickness changes. Here, we present and validate a method to retrieve lake ice thickness using the CryoSat-2 (CS2) radar altimeter. These are the first satellite altimeter retrievals of lake ice thickness. Under optimal conditions, the CS2 signal is scattered from both the snow-ice and the ice-water interfaces, with returns from each interface being of sufficient power to be identified in the radar waveform. The distance between the scattering horizons is used to determine the ice thickness, similar to traditional ground penetrating radar measurements. The seasonal evolution of ice thickness of GBL and GSL is compared with in situ measurements, modeled ice thicknesses, and previous studies. The impact of ice and snow properties on signal penetration and the thickness retrieval are examined with synthetic aperture radar imagery. The CS2 ice thickness retrievals are able to observe the seasonal thickening of the lake ice and closely match the in situ measurements over both lakes (R > 0.65, RMSE < 0.33 m). Thickness retrievals of thin ice are limited by a minimum waveform peak separation of 2 range bins, approximately 0.26 m in ice. Although not designed for lake ice studies, CS2 and future SAR satellite altimeter missions offer new possibilities to monitor the ice and water levels of climatically sensitive and influential lakes.



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Eprint ID
51882
DOI https://www.doi.org/10.1109/tgrs.2017.2677583

Cite as
Beckers, J. F. , Alec Casey, J. and Haas, C. (2017): Retrievals of Lake Ice Thickness From Great Slave Lake and Great Bear Lake Using CryoSat-2 , IEEE Transactions on Geoscience and Remote Sensing, 55 (7), pp. 3708-3720 . doi: https://www.doi.org/10.1109/tgrs.2017.2677583


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