TY - JOUR
T1 - Surface ablation model evaluation on a drifting ice island in the Canadian Arctic
AU - Crawford, Anna J.
AU - Mueller, Derek
AU - Humphreys, Ellen
AU - Carrieres, Tom
AU - Tran, Hai
N1 - Funding and in-kind support (equipment, travel) were granted by Environment Canada, ArcticNet and NSERC.
PY - 2015/2
Y1 - 2015/2
N2 - A 4-week micro-meteorological dataset was collected by an automatic weather station on a small ice island (0.13 km2)
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 (EBAWS) 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 (EBAWS),
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 role
in overall deterioration of ice islands than traditional icebergs due to
morphological differences (size, surface structure), it must be
accurately represented in operational ice island deterioration models.
The costs and benefits between parsimonious TIM models and skilled
energy-balance models are weighed here for operational modelers to
consider, along with the complications caused by the use of the regional
environmental data input provided by the GEM model for operational modeling efforts.
AB - A 4-week micro-meteorological dataset was collected by an automatic weather station on a small ice island (0.13 km2)
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 (EBAWS) 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 (EBAWS),
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 role
in overall deterioration of ice islands than traditional icebergs due to
morphological differences (size, surface structure), it must be
accurately represented in operational ice island deterioration models.
The costs and benefits between parsimonious TIM models and skilled
energy-balance models are weighed here for operational modelers to
consider, along with the complications caused by the use of the regional
environmental data input provided by the GEM model for operational modeling efforts.
KW - Ice hazards
KW - Ice islands
KW - Surface ablation
KW - Melting modeling
KW - Deterioration modeling
KW - Energy-balance
U2 - 10.1016/j.coldregions.2014.11.011
DO - 10.1016/j.coldregions.2014.11.011
M3 - Article
SN - 0165-232X
VL - 110
SP - 170
EP - 182
JO - Cold Regions Science and Technology
JF - Cold Regions Science and Technology
ER -