Surface ablation model evaluation on a drifting ice island in the Canadian Arctic

• Published in: Cold Regions Science and Technology
• Main Authors: Crawford, Anna J., Mueller, Derek, Humphreys, Ellen, Carrieres, Tom, Tran, Hai
• Format: Article in Journal/Newspaper
• Language: English
• Published: 2015
• Subjects: Ice hazards; Ice islands; Surface ablation; Melting modeling; Deterioration modeling; Energy-balance; Arctic; Bylot Island; Canada; Lancaster Sound; Nunavut; Iceberg*
• Online Access: https://research-portal.st-andrews.ac.uk/en/researchoutput/surface-ablation-model-evaluation-on-a-drifting-ice-island-in-the-canadian-arctic(0ba58470-eacf-4694-82b8-a4d33c64f61b).html; https://doi.org/10.1016/j.coldregions.2014.11.011

A 4-week micro-meteorological dataset was collected by an automatic weather station on a small ice island (0.13 km 2 ) adrift off Bylot Island (Lancaster Sound, Nunavut, Canada) during the 2011 melt season. This dataset provided an opportunity to identify the environmental variables and energy fluxes that contribute most to surface ablation during the melt season, as well as test previously developed surface melt (ablation) models. Surface ablation was estimated using energy fluxes calculated using the bulk aerodynamic approach (EB AWS ) and three existing surface ablation models. These models included a simple solar radiation model developed for iceberg use (CIS-IB), a more sophisticated energy-balance model developed for ice island use (CIS-II), and a temperature index melt (TIM) model based on an assumed relationship between air temperature, time, and surface ablation. The models were driven by our measured micro-meteorological data (optimal forcing) or regional environmental forecast data from the Global Environmental Multiscale (GEM) Model, which is used for operational iceberg modeling. The sensible heat flux contributed most to the ice surface's available melt energy (47%), followed by net radiation (38%) and the latent heat flux (30%), while the subsurface heat flux removed 15% of available energy. When cumulative surface ablation was predicted with these calculated energy fluxes (EB AWS ), observed surface ablation was under-predicted by 38%. Results illustrate the decreased performance of the melt models when run with GEM data versus in-situ micro-meteorological data, which is optimal for model input but not available for operational modeling. The CIS-II model under-predicted cumulative surface ablation by 5.7% (RMSE = 1.2 cm) with observed micro-meteorological data and over-predicted cumulative surface ablation by 35% when run with GEM model data. This is likely a result of the GEM model wind speed being 57% greater than that recorded on the ice island. Since surface ablation plays a greater relative ...