An Improved Method of Extremal Value Analysis of Arctic Sea Ice Thickness Derived From Upward Looking Sonar Ice Data

Abstract

Abstract In the Beaufort Sea, observations of extreme draft sea ice features havebeen identified from upward looking sonar (ULS) datasets spanning severalyears. Using analysis methods from extreme value theory, the estimated 100-yearreturn values of the maximum ice draft have been derived. In addition, theapplicability of these statistical techniques to the Northeast Greenland iceregime is examined using one year of ULS data at two locations from 2008 to2009. The methods have been developed for the Beaufort Sea region andsubsequently, further refined for use in estimating extreme ice hazards offNortheast Greenland. These estimates provide inputs to the design of offshoreplatforms and ships in support of oil and gas activities in these ice-infestedwaters. Previous studies in the Canadian Beaufort Sea derived an empirical upperlimit on the maximum sea ice thickness resulting from deformation processesbased on the relationship of maximum ice thickness as a function ofsimultaneous values of undeformed ice thickness. Using the more extensive ULSice keel data sets now available, these methods were re-evaluated and updated. Similar analyses were carried out on ice thickness measurements obtained offNortheast Greenland which reveal distinct differences in the ice regime ofthese two geographical areas. Improvements to extremal value statistical analysis methods for longrecurrence intervals of 100 years for ice draft (D100) are based on the threeparameter Weibull distribution which has been optimized for application to verylarge sea ice keels using a peak over threshold selection approach. Theseresults were compared to the maximum draft limit and undeformed ice thicknessrelationship. We developed techniques to refine at a high resolution the lowerthreshold on maximum draft and examine the implications of this filtering onD100. This is an important consideration as selecting the lower maximum draftthreshold is a balance between retaining enough observations to ensurestatistical robustness and sampling only the extreme tail of the maximum draftdistribution. Methods for performing these statistical analyses arepresented.