Physical characteristics of melt ponds

Abstract

Improving the predictive capabilities for the development of Arctic sea ice cover strongly depends on a better understanding of the ice-albedo feedback mechanism. Using a combination of multi- and hyperspectral airborne imagery, field spectroscopy and bio-optical modelling we aim to quantify melt pond fraction, melt pond depth, thickness of underlying ice, pond water constituents (chlorophyll, suspended organic and inorganic matter) and surface albedo in different ice regimes. The main goal is to develop a semi-automated application for melt pond analysis for airborne hyperspectral instruments. A further goal is to employ the collected data to validate and improve parameterizations of melt pond properties used in regional and global climate models. The ground based measurements are essential for the parameterization of bio-optical models as well as for the validation of results derived from airborne measurements, which is crucial for accuracy assessment.