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Establish a dataset of co-located in-situ and satellite data for sea ice in the Southern Ocean

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2017
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Abstract (EN)

Sea ice is simply frozen seawater. Remote sensing of sea ice properties has always been a challenging task. This thesis is part of HORIZON 2020 SPICES "Space-borne observations for detecting and forecasting sea ice cover extremes" project as of to establish a dataset of co-located in-situ and satellite data for sea ice in the Southern Ocean. In order to response needs of increase polar activities, SPICES is focusing on detection of sea ice extremes and in particular, it aims for detection of heavily ridged ice regions from SAR, detection of MYI floes in a area composed mostly FY from SAR, detection of most thickest ice from RA thickness profiles, detection of regionally anomalous thick or thin ice via SMOS data, detection of sea ice areas vulnerable for the wave action, detection of early/late melting season and improving capabilities to forecast seasonal sea ice extremes. Remote sensing products traditionally provide overall information on sea ice conditions such as ice extent and concentration. However, this information stays limited for ice charting, tactical navigation and management of offshore activities since the sea ice hazards are related to sea ice thickness. Therefore, the thesis provided the basis to obtain sea ice thickness information by establishing the datasets. For the purpose of this thesis, Chapter 1 included the introduction of sea ice related satellite technology and the main purpose of the thesis. Chapter 2 provided the information on "Study Area: Antarctic Sea Ice" and "Data description: Satellite Remote Sensing Detecting Sea Ice". Chapter 3 followed with methodology. Chapter 4 included the results and discussion, for the overall purpose of this thesis, to construct a dataset of in-situ reference snow/ice data co-located with all relevant satellite data. Chapter 5 suggested the conclusion with necessary steps to have more elaborating the idea of the Space-borne Observations for Detecting and Forecasting Sea Ice Cover Extremes.

Author

Özgün Oktar

How to Cite

Özgün Oktar (Master Thesis). Establish a dataset of co-located in-situ and satellite data for sea ice in the Southern Ocean, 2017, İstanbul Technical University.

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