PT Journal
AU König, M
   Oppelt, N
TI A linear model to derive melt pond depth on Arctic sea ice from hyperspectral data
SO The Cryosphere : TC ; an interactive open access journal of the European Geosciences Union
PY 2020
VL 14
IS 8
PU Copernicus GmbH
DI 10.5194/tc-14-2567-2020
WP https://macau.uni-kiel.de/receive/macau_mods_00002757
LA en
DE arctic sea; ice; pond depth; meltwater; hyperspectral remote sensors
SN 1994-0424
AB 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 melt pond deepening 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 meltwater on the reflected signal, the water depth cannot be determined. To solve the problem, we simulated the way meltwater 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 as a function of depth that is widely independent from the bottom albedo and accounts for the influence of varying solar zenith angles. We validated the model using 49 in situ melt pond spectra and corresponding depths from shallow ponds on dark and bright ice. Retrieved pond depths are accurate (root mean square error, RMSE=2.81 cm; nRMSE=16 %) and highly correlated with in situ measurements (r=0.89; p=4.34×10−17)
PI Katlenburg-Lindau
ER