Bruce C. Elder

A First Assessment of IceBridge Snow and Ice Thickness Data Over Arctic Sea Ice

We present a first assessment of airborne laser and radar altimeter data over snow-covered sea ice, gathered during the National Aeronautics and Space Administration Operation IceBridge Mission. We describe a new technique designed to process radar echograms from the University of Kansas snow radar to estimate snow depth. We combine IceBridge laser altimetry with radar-derived snow depths to determine sea ice thickness. Results are validated through comparison with direct measurements of snow and ice thickness collected in situ at the Danish GreenArc 2009 sea ice camp located on fast ice north of Greenland. The IceBridge instrument suite provides accurate measurements of snow and ice thickness, particularly over level ice. Mean IceBridge snow and ice thickness agree with in situ measurements to within ~ 0.01 and ~ 0.05 m, respectively, while modal snow and ice thickness estimates agree to within 0.02 and 0.10 m, respectively. IceBridge snow depths were correlated with in situ measurements (R = 0.7, for an averaging length of 55 m). The uncertainty associated with the derived IceBridge sea ice thickness estimates is 0.40 m. The results demonstrate the retrieval of both first-year and multiyear ice thickness from IceBridge data. The airborne data were however compromised in heavily ridged ice where snow depth, and hence ice thickness, could not be measured. Techniques developed as part of this study will be used for routine processing of IceBridge retrievals over Arctic sea ice. The limitations of the GreenArc study are discussed, and recommendations for future validation of airborne measurements via field activities are provided.

Arctic sea-ice melt in 2008 and the role of solar heating

Abstract There has been a marked decline in the summer extent of Arctic sea ice over the past few decades. Data from autonomous ice mass-balance buoys can enhance our understanding of this decline. These buoys monitor changes in snow deposition and ablation, ice growth, and ice surface and bottom melt. Results from the summer of 2008 showed considerable large-scale spatial variability in the amount of surface and bottom melt. Small amounts of melting were observed north of Greenland, while melting in the southern Beaufort Sea was quite large. Comparison of net solar heat input to the ice and heat required for surface ablation showed only modest correlation. However, there was a strong correlation between solar heat input to the ocean and bottom melting. As the ice concentration in the Beaufort Sea region decreased, there was an increase in solar heat to the ocean and an increase in bottom melting.

Sea ice mass balance observations from the North Pole Environmental Observatory

In recent years the periphery of the Arctic sea ice cover has undergone significant changes, with a reduction in summer ice extent, a thinning of the ice, and a shift from multiyear to first year ice. Here we examine sea ice conditions during nine summers between 2000 and 2013 in the interior of the ice pack, using autonomous measurements of sea ice mass balance deployed near the North Pole. Results exhibit no definitive trends. There is large interannual variability, with surface melt ranging from 0.02 m to 0.50 m and bottom melt from 0.10 m to 0.57 m. The largest amounts of bottom melt have occurred in the past few years. For all 9 years the ice at the end of the melt season was at least 1.2 m thick.

Temporal evolution of Arctic sea-ice temperature

Abstract Vertical profiles of temperature from the air through the snow and ice and into the upper ocean were measured over an annual cycle, from October 1997 to October 1998, as part of a study of the Surface Heat Budget of the Arctic Ocean (SHEBA). These observations were made at nine locations, including young ice, ponded ice, undeformed ice, a hummock, a consolidated ridge and a new blocky ridge. All of the sites had similar environmental forcing, with air temperatures at the different sites typically within 1°C. In general, the seasonal evolution of ice temperature followed a pattern of (1) a cold front propagating down through the ice in the fall, (2) cold ice temperatures and ice growth in late fall, winter and early spring, and (3) warming to the freezing point in the summer. Within this general pattern, there was considerable spatial variability in the temperature profiles, particularly during winter. For example, snow/ice interface temperatures varied by as much as 30°C between sites. The coldest ice temperatures were observed in a consolidated ridge with a thin snow cover, while the warmest were in ponded ice. The warm pond temperatures were a result of two factors: the initial cooling in the fall was retarded by freezing of pond water, and the depressed surface of the pond was quickly covered by a deep layer of snow (0.6 m). In an 8 m thick unconsolidated ridge, the cold front did not penetrate to the ice bottom during winter, and a portion of the interior remained below freezing during the summer. The spatial variability in snow depth and ice conditions can result in situations where there is significant horizontal transport of heat.

Assessment of radar‐derived snow depth over Arctic sea ice

Knowledge of contemporaneous snow depth on Arctic sea ice is important both to constrain the regional climatology and to improve the accuracy of satellite altimeter estimates of sea ice thickness. We assess new data available from the NASA Operation IceBridge snow radar instrument and derive snow depth estimates across the western Arctic ice pack using a novel methodology based on wavelet techniques that define the primary reflecting surfaces within the snow pack. We assign uncertainty to the snow depth estimates based upon both the radar system parameters and sea ice topographic variability. The accuracy of the airborne snow depth estimates are examined via comparison with coincident measurements gathered in situ across a range of ice types in the Beaufort Sea. We discuss the effect of surface morphology on the derivation, and consequently the accuracy, of airborne snow depth estimates. We find that snow depths derived from the airborne snow radar using the wavelet-based technique are accurate to 1 cm over level ice. Over rougher surfaces including multiyear and ridged ice, the radar system is impacted by ice surface morphology. Across basin scales, we find the snow-radar-derived snow depth on first-year ice is at least ∼60% of the value reported in the snow climatology for the Beaufort Sea, Canada Basin, and parts of the central Arctic, since these regions were previously dominated by multiyear ice during the measurement period of the climatology. Snow on multiyear ice is more consistent with the climatology.

Observations of the annual cycle of sea ice temperature and mass balance

A vertical array of thermistors coupled with an autonomous data-logging system was used to obtain a 15-month record of ice temperature profiles in a multiyear floe in the Beaufort Sea. This record was used to monitor atmosphere, ice and ocean temperatures, determine changes in the ice mass balance, and infer estimates of the ocean heat flux and the snow thermal conductivity. Ablation during the summer melt season consisted of approximately 0.3 m of snow melt, 0.67 m of ice surface ablation and 0.25 m of bottom ablation. There was 0.45 m of bottom accretion during the growth season. The annually averaged ocean heat flux was 4 W m−2, with a summertime value of 9 W m−2. Comparing these results to earlier studies conducted in the same region showed considerable interannual variability in summer melting. The thermal conductivity of snow cover was approximately 0.3 W m−1 K−1 during winter.

Seasonal ice mass-balance buoys: adapting tools to the changing Arctic

Abstract Monitoring the local mass balance of Arctic sea ice provides opportunities to attribute the observed changes in a particular floe’s mass balance to specific forcing phenomena. A shift from multi-year to seasonal ice in large portions of the Arctic presents a challenge for the existing Lagrangian array of autonomous ice mass-balance buoys, which were designed with a perennial ice cover in mind. This work identifies the anticipated challenges of operation in seasonal ice and presents a new autonomous buoy designed to monitor ice mass balance in the seasonal ice zone. the new design presented incorporates features which allow the buoy to operate in thin ice and open water, and reduce its vulnerability to ice dynamics and wildlife damage, while enhancing ease of deployment. A test deployment undertaken from April to June 2009 is discussed and results are presented with analysis to illustrate both the features and limitations of the buoy’s abilities.

Investigations of skeletal layer microstructure in the context of remote sensing of oil in sea ice

ABSTRACT (2017-159) The Arctic Oil Spill Response Technology – Joint Industry Program (JIP) funded a controlled basin experiment in November 2014 to assess the relative capabilities of a variety of...

Detection of oil in and under ice

ABSTRACT (2017-147) In 2014, researchers from ten organizations came to the U.S. Army Corps of Engineers, Cold Regions Research and Engineering Laboratory (CRREL) in New Hampshire to conduct a firs...

Comparison of ice stress records in terms of extreme value analysis

Abstract Dynamic ice models use stress tensor to describe the forces arising from internal ice friction. The model stress values are typically one to two magnitudes smaller than values measured by stressmeters deployed on ice floes. The synthesis of the pack-ice stress state from the measurements has been complicated by the peaky character of stress records, and the means to connect them with spatial stress distribution of the floe system have been lacking. Here a reanalysis of Arctic Sea Ice Mechanics Initiative (SIMI) data is made in terms of extreme value statistics. The basic quantity is the maximum stress observed during a time period. The records exhibit self-affine scaling. The statistics are then determined by two parameters, the Hurst exponent H and a reference stress level. Similar analysis is possible for the kinematic data. This establishes the comparability of stress records with each other and with kinematic records. The results suggest that the exponent is related to the stress state of the regional floe system, while the stress level is determined by local floe characteristics. Based on this a characterization of spatial distribution of pack-ice stresses is given.