Abstract: Machine learning approaches for inferring large-scale sea ice rheology from Lagrangian and Eulerian data (Ocean Sciences Meeting 2020)

Machine learning approaches for inferring large-scale sea ice rheology from Lagrangian and Eulerian data

Dimitrios Giannakis¹, Georgy E Manucharyan², Joanna Slawinska³ and Suddhasattwa Das¹, (1)New York University, Courant Institute of Mathematical Sciences, New York, NY, United States, (2)University of Washington Seattle Campus, School of Oceanography, Seattle, United States, (3)University of Wisconsin-Milwaukee, Department of Physics, Milwaukee, WI, United States

Abstract:

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