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The Cryosphere An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/tc-2019-261
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/tc-2019-261
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 09 Dec 2019

Submitted as: research article | 09 Dec 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal The Cryosphere (TC).

A linear model to derive melt pond depth from hyperspectral data

Marcel König and Natascha Oppelt Marcel König and Natascha Oppelt
  • Department of Geography, Kiel University, Kiel, 24118, Germany

Abstract. Melt ponds are key elements in the energy balance of Arctic sea ice. Observing their temporal evolution is crucial for understanding melt processes and predicting sea ice evolution. Remote sensing is the only technique that enables large-scale observations of Arctic sea ice. However, monitoring vertical melt pond evolution in this way is challenging because most of the optical signal reflected by a pond is defined by the scattering characteristics of the underlying ice. Without knowing the influence of melt water on the reflected signal, the water depth cannot be determined. To solve the problem, we simulated the way melt water changes the reflected spectra of bare ice. We developed a model based on the slope of the log-scaled remote sensing reflectance at 710 nm. We validated the model using 49 in situ melt pond spectra and corresponding depths from ponds on dark and bright ice. Retrieved pond depths are precise (RMSE = 2.81 cm) and highly correlated with in situ measurements (r = 0.89; p = 4.34e−17). The model further explains a large portion of the variation in pond depth (R2 = 0.74). Our results indicate that pond depth is retrievable from optical data under clear sky conditions. This technique is potentially transferrable to hyperspectral remote sensors on UAVs, aircraft and satellites.

Marcel König and Natascha Oppelt
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Status: open (until 22 Feb 2020)
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Marcel König and Natascha Oppelt
Data sets

Optical measurements of bare ice and melt ponds on Arctic sea ice acquired during POLARSTERN cruise PS106 M. König and N. Oppelt https://doi.pangaea.de/10.1594/PANGAEA.908075

Reflectance measurements (Ocean Optics STS-VIS) of bare ice and melt ponds on Arctic sea ice acquired during POLARSTERN cruise PS106/1 P. Gege, M. König, and N. Oppelt https://doi.pangaea.de/10.1594/PANGAEA.908074

HCRF measurements (Ibsen Freedom VIS FSV-305) of bare Arctic sea ice acquired during POLARSTERN cruise PS106/2 P. Gege and M. König https://doi.pangaea.de/10.1594/PANGAEA.908073

Marcel König and Natascha Oppelt
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Short summary
We used data that we collected on RV Polarstern cruise PS106 in summer 2017 to develop a model for the derivation of melt pond depth from reflectance measurements. We simulated reflectances of melt ponds of varying color and water depth and use the sun zenith angle and the slope of the log-scaled reflectance at 710 nm to derive pond depth. We validated the model on the in situ melt pond data and found it to derive pond depth very accurately.
We used data that we collected on RV Polarstern cruise PS106 in summer 2017 to develop a model...
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