Department of Urban and Environmental Engineering (Environmental Science and Engineering)Launching CryoSat-2, which is a current radar altimeter mission for the monitoring of polar region
enables to produce monthly based sea ice thickness since April 2010. The Sea ice thickness cannot be
measured directly by satellite. Sea ice freeboard that is an elevation above sea level can be converted in to
sea ice thickness by assuming hydrostatic equilibrium. Sea ice leads (e.g., linear cracks in sea ices) are
regarded as sea surface tie points for the estimation of sea ice freeboard. Identifying the sea ice leads is
one of the core factors to retrieve sea ice thickness. The surface elevation is estimated by the use of
Threshold First maxima Retracker Algorithm (TFMRA) for a 40% threshold using CryoSat-2 L1b data
and the leads are detected by machine learning approaches such as decision trees and random forest. The
machine learning produces better accuracy for the sea ice thickness than previous simple thresholding
approach, validating EM-31, airborne sea ice thickness observations. A novel method to overcome
previous threshold based lead detection methods for identifying leads is developed, which is waveform
mixture algorithm that linear mixture analysis is applied in terms of waveforms. The waveform mixture
algorithm can distinguish leads without beam behavior parameters and backscatter sigma-0 but just use
waveforms, which is less affected by updating baseline for CryoSat-2. In addition to the development of
the algorithms, a scientific research is carried out. Causes for sea ice anomaly phenomenon in November
2016 is investigated. Eventually, sea ice the volume derived by thickness is used for the analysis of sea ice
extent minimum in November 2016 and suggest a new insight of sea ice minimum phenomenon. Unlike
sea ice extent, the sea ice volume is not a minimum in November 2016. However, since the base period
for sea ice volume is short, it is hard to mention climatology of sea ice volume.ope
