Understanding snow and sea ice properties at microwave frequencies for remote sensing applications during MOSAiC (MOSAiCmicrowaveRS)

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Over the past few decades dramatic changes in Arctic sea ice conditions have been observed. These changes include rapid declines in sea ice extent, age, and thickness coupled with extended melt seasons. In parallel the amount of shipping and offshore activities in the Arctic are increasing and demand for improved sea ice monitoring. Passive and active microwave satellite remote sensing offer retrieval of several sea ice parameters such as sea ice type, thickness, drift and extent. However, retrieval algorithms for these parameters are, to some degree, relying on empirical relationships obtained from a limited set of scenarios. They mostly lack snow information, incidence angle dependencies and seasonal variation aspects. In the framework of the year-round MOSAiC expedition we will improve some of these retrieval algorithms with the aid of in-situ and air-borne observations with high spatio-temporal variability. In short, this project covers the following aspects:– Satellite observations of sea ice at microwave frequencies are widely available today and are used both for operational applications and climate studies.– A wide range of resolutions and frequencies from Synthetic Aperture Radar (SAR), microwave radiometers and scatterometers are available on a daily basis.– Here we will develop new and improve current methods to derive sea ice properties from microwave observations, in particular ice type and lead distribution from SAR and snow properties and ice type from microwave radiometers.– The one-year long MOSAiC expedition in the central Arctic Ocean in 2019/2020 will provide necessary in-situ and airborne observations.– Airborne laser scanner, electromagnetic ice thickness sounding, and optical images will allow evaluation of satellite results for a complete seasonal cycle. – In-situ microwave radar and radiometer measurements in conjunction with detailed snow and ice measurements will aid the development of improved radiative transfer, emission, and scattering models for snow and sea ice remote sensing applications.