Applicant

Dr. Nina Maaß 
Universität Hamburg 
Institut für Meereskunde

Project Description

Antarctic sea ice is generally covered with snow, and thus the snow properties determine the surface characteristics of the ice and influence the interaction between atmosphere and ocean.Snow-ice formation is much more common in the Antarctic than in the Arctic and contributes significantly to the sea ice mass balance. Additionally, information on snow depth and density are required to derive ice thickness from altimeter measurements. However, so far knowledge on Antarctic snow on sea ice mainly originates from individual field measurements and ship observations. On larger scales, snow depth can also be retrieved from passive microwave satellites measuring at 19 and 37GHz frequency, but validation of the method and investigation of error sources are ongoing work. In the Snow Covers impact on Antarctic Sea Ice (SCASI) project, we aim for quantifying the amount and distribution of snow on sea ice, as well as the physical properties of snow and their temporal evolution. The overall goal is to develop a new and consistent snow data product for Antarctic sea ice that represents various length scales and different seasons. In order to achieve this and to bridge the scales from point measurements to satellite footprints, we synthesize field observations, satellite remote sensing and numerical modeling. A widely-used snow cover model that has been successfully applied for modeling snow in alpine regions is the one-dimensional SNOWPACK model. In the SCASI project, we bring together Swiss and German partners to further develop a sea ice version of SNOWPACK and to combine it with in-situ and buoy measurements as well as passive microwave satellite observations. The SCASI-Remote Sensing (SCASI-RS) project deals with the satellite remote sensing part of SCASI. In SCASI-RS, we compare SNOWPACK simulations with in-situ measurements to identify suitable cases for validation of satellite retrievals. By combining SNOWPACK with emission models we can simulate microwave radiation and investigate the impact of snow properties on the retrieval methods. This will not only be done for the microwave frequencies at 19 and 37GHz, used for snow depth retrievals so far, but also for a lower frequency of 1.4 GHz. Global satellite observations at 1.4GHz have been available since 2009, and we investigate whether snow depth in the Antarctic can also be derived from this very low microwave frequency, as it has been suggested for the Arctic recently. Due to the distinct differences of the ice and snow conditions, however, the results may not be transferred directly to Antarctic regions.The resulting product will be useful for sea ice and radiation models, altimetry-based ice thickness retrievals and other research that depends on information on snow on sea ice, for example regarding biological production or geo-chemical cycles.

DFG Programme: Infrastructure Priority Programmes

International Connection: Switzerland

Co-Applicants: Professor Dr. Lars Kaleschke; Dr. Marcel Nicolaus

Cooperation partners: Professor Dr. Michael Lehning; Dr. Nander Wever

Term since 2018