Modal Ice Thickness Research Articles

Sea ice and snow characteristics from year-long transects at the MOSAiC Central Observatory

Repeated transects have become the backbone of spatially distributed ice and snow thickness measurements crucial for understanding of ice mass balance. Here we detail the transects at the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) 2019–2020, which represent the first such measurements collected across an entire season. Compared with similar historical transects, the snow at MOSAiC was thin (mean depths of approximately 0.1–0.3 m), while the sea ice was relatively thick first-year ice (FYI) and second-year ice (SYI). SYI was of two distinct types: relatively thin level ice formed from surfaces with extensive melt pond cover, and relatively thick deformed ice. On level SYI, spatial signatures of refrozen melt ponds remained detectable in January. At the beginning of winter the thinnest ice also had the thinnest snow, with winter growth rates of thin ice (0.33 m month−1 for FYI, 0.24 m month−1 for previously ponded SYI) exceeding that of thick ice (0.2 m month−1). By January, FYI already had a greater modal ice thickness (1.1 m) than previously ponded SYI (0.9 m). By February, modal thickness of all SYI and FYI became indistinguishable at about 1.4 m. The largest modal thicknesses were measured in May at 1.7 m. Transects included deformed ice, where largest volumes of snow accumulated by April. The remaining snow on level ice exhibited typical spatial heterogeneity in the form of snow dunes. Spatial correlation length scales for snow and sea ice ranged from 20 to 40 m or 60 to 90 m, depending on the sampling direction, which suggests that the known anisotropy of snow dunes also manifests in spatial patterns in sea ice thickness. The diverse snow and ice thickness data obtained from the MOSAiC transects represent an invaluable resource for model and remote sensing product development.

Interannual variability in Transpolar Drift summer sea ice thickness and potential impact of Atlantification

Abstract. Changes in Arctic sea ice thickness are the result of complex interactions of the dynamic and variable ice cover with atmosphere and ocean. Most of the sea ice exiting the Arctic Ocean does so through Fram Strait, which is why long-term measurements of ice thickness at the end of the Transpolar Drift provide insight into the integrated signals of thermodynamic and dynamic influences along the pathways of Arctic sea ice. We present an updated summer (July–August) time series of extensive ice thickness surveys carried out at the end of the Transpolar Drift between 2001 and 2020. Overall, we see a more than 20 % thinning of modal ice thickness since 2001. A comparison of this time series with first preliminary results from the international Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) shows that the modal summer thickness of the MOSAiC floe and its wider vicinity are consistent with measurements from previous years at the end of the Transpolar Drift. By combining this unique time series with the Lagrangian sea ice tracking tool, ICETrack, and a simple thermodynamic sea ice growth model, we link the observed interannual ice thickness variability north of Fram Strait to increased drift speeds along the Transpolar Drift and the consequential variations in sea ice age. We also show that the increased influence of upward-directed ocean heat flux in the eastern marginal ice zones, termed Atlantification, is not only responsible for sea ice thinning in and around the Laptev Sea but also that the induced thickness anomalies persist beyond the Russian shelves and are potentially still measurable at the end of the Transpolar Drift after more than a year. With a tendency towards an even faster Transpolar Drift, winter sea ice growth will have less time to compensate for the impact processes, such as Atlantification, have on sea ice thickness in the eastern marginal ice zone, which will increasingly be felt in other parts of the sea-ice-covered Arctic.

Sea-ice thickness in the coastal northeastern Chukchi Sea from moored ice-profiling sonar

ABSTRACTTime series ice-draft data were obtained from moored ice-profiling sonar (IPS), in the coastal northeastern Chukchi Sea during 2009/10. Time series data show seasonal growth of sea-ice draft, occasionally interrupted by coastal polynya. The sea-ice draft distribution indicates a slightly lower abundance of thick, deformed ice compared with the eastern Beaufort Sea. In January, a rapid increase in the abundance of thick ice coincided with a period of minimal drift indicating compaction again the coast and dynamical thickening. The overall mean draft and corresponding derived thickness are 1.27 and 1.38 m, respectively. The evolution of modal ice thickness observed can be explained mostly by thermodynamic growth. The derived ice thicknesses are used to estimate heat losses based on ERA-interim data. Heat losses from the raw, 1 s IPS data are ~50 and 100% greater than those calculated using IPS data averaged over spatial scales of ~20 and 100 km, respectively. This finding demonstrates the importance of subgrid-scale ice-thickness distribution for heat-loss calculation. The heat-loss estimate based on thin ice data derived from AMSR-E data corresponds well with that from the 1 s observed ice-thickness data, validating heat-loss estimates from the AMSR-E thin ice-thickness algorithm.

Validation of SMOS sea ice thickness retrieval in the northern Baltic Sea

The Soil Moisture and Ocean Salinity (SMOS) mission observes brightness temperatures at a low microwave frequency of 1.4 GHz (L-band) with a daily coverage of the polar regions. L-band radiometry has been shown to provide information on the thickness of thin sea ice. Here, we apply a new emission model that has previously been used to investigate the impact of snow on thick Arctic sea ice. The model has not yet been used to retrieve ice thickness. In contrast to previous SMOS ice thickness retrievals, the new model allows us to include a snow layer in the brightness temperature simulations. Using ice thickness estimations from satellite thermal imagery, we simulate brightness temperatures during the ice growth season 2011 in the northern Baltic Sea. In both the simulations and the SMOS observations, brightness temperatures increase by more than 20 K, most likely due to an increase of ice thickness. Only if we include the snow in the model, the absolute values of the simulations and the observations agree well (mean deviations below 3.5 K). In a second comparison, we use high-resolution measurements of total ice thickness (sum of ice and snow thickness) from an electromagnetic (EM) sounding system to simulate brightness temperatures for 12 circular areas. While the SMOS observations and the simulations that use the EM modal ice thickness are highly correlated (r2=0.95), the simulated brightness temperatures are on average 12 K higher than observed by SMOS. This would correspond to an 8-cm overestimation of the modal ice thickness by the SMOS retrieval. In contrast, if the simulations take into account the shape of the EM ice thickness distributions (r2=0.87), the mean deviation between simulated and observed brightness temperatures is below 0.1 K.

Large-scale ice thickness distribution of first-year sea ice in spring and summer north of Svalbard

AbstractThe large-scale thickness distribution of sea ice was measured during several campaigns in the European Arctic north of Svalbard from 2007 using an airborne electromagnetic induction device. In August 2010 and April-May 2011, this was complemented by extensive on-ice work including measurements of snow thickness and freeboard. Ice thicknesses show a clear difference between the seasons, with thicker ice during spring than in summer. In spring 2011, negative freeboard and flooding were observed as a result of the extensive snow cover. We find that the characteristics of the first-year sea ice allow combining observations from different years. The ice thickness in the marginal ice zone increases with increasing latitude and increasing distance to the ice edge; however, in the inner ice pack from ∼100 km from the ice edge the thickness remains almost constant. Modal ice thickness in spring reaches 2.4 m whereas in summer it is 1.0–1.4 m. Our study provides new insight into ice thickness distributions of a typical ice cover consisting of mainly first- and second-year ice, which may become the dominant ice type in the Arctic in the future.

Thickness and surface‐properties of different sea‐ice regimes within the Arctic Trans Polar Drift: Data from summers 2001, 2004 and 2007

Large‐scale sea‐ice thickness and surface property data were obtained in three summers and in three different sea‐ice regimes in the Arctic Trans‐Polar Drift (TPD) by means of helicopter electromagnetic sounding. Distribution functions P of sea‐ice thickness and of the height, spacing, and density of sails were analyzed to characterize ice regimes of different ages and deformations. Results suggest that modal ice thickness is affected by the age of a sea‐ice regime and that the degree of deformation is represented by the shape of P. Mean thickness changes with both age and deformation. Standard error calculations showed that representative mean and modal thickness could be obtained with transect lengths of 15 km and 50 km, respectively, in less deformed ice regimes such as those around the North Pole. In heavier deformed ice regimes closer to Greenland, 100 km transects were necessary for mean thickness determination and a representative modal thickness could not be obtained at all. Mean sail height did not differ between ice regimes, whereas sail density increased with the degree of deformation. Furthermore, the fraction of level ice, open melt ponds, and open water along the transects were determined. Although overall ice thickness in the central TPD was 50% thinner in 2007 than in 2001, first‐year ice (FYI) was not significantly thinner in 2007 than FYI in 2001, with a decrease of only 0.3 m. Thinner FYI in 2007 only occurred close to the sea‐ice edge, where open water covered more than 10% of the surface. Melt pond coverage retrieved from laser measurements was 15% in both the 2004 MYI regime and the 2007 FYI regime.

Observations of sea ice thickness, surface roughness and ice motion in Amundsen Gulf

Ice thickness and surface roughness measurements of first‐year (FY) sea ice were collected with a fix‐mounted helicopter‐borne electromagnetic (HEM) ‐laser system in Amundsen Gulf in April to May 2004. The modal ice thickness values are in good qualitative agreement with different ice types identified in synthetic aperture radar (SAR) imagery and shown on ice charts produced by the Canadian Ice Service. Modal ice thickness values which generally represent level ice thicknesses were about 2.0 m over landfast ice. A large range of modal ice thicknesses was observed in the mobile ice region, with values of about 0.2 m (young ice) in leads (where there was high radar backscatter), 0.6 m (thin FY ice) in the polynya (where there was medium to high backscatter), and about 1.1–1.9 m (thick FY ice) elsewhere. High surface roughnesses are strongly associated with high radar backscatter in SAR imagery, and are observed in areas of large shear. The ratio of the standard deviations of ice draft and averaged roughness in an area of landfast ice is in good agreement with the ratio of the standard deviations of ice draft and ice‐equivalent roughness expected from isostasy, with constant level ice and snow thickness. However, the standard deviation of ice‐equivalent roughness may be significantly underestimated, due to differences in snow thickness between level and deformed ice, and limitations of the laser processing method. Modal ice (plus snow) thicknesses measured with the HEM system are within the range of historical values measured at Cape Parry.

Monitoring ice thickness in Fram Strait

Time series of ice thickness in Fram Strait are evaluated together with ice drift for estimation of the ice flux from the Arctic Ocean. Ice draft was measured from moored sonars every 4 min, suggesting a nominal sampling interval of 30 m. On the basis of these data the annual cycle of many statistics can be resolved. The modal ice thickness shows a maximum of 3.15 m in May and a minimum in September of 2.43 m, indicating an annual variation range of 0.72 m. This compares with model results, comprehensive drillings, and most of the submarine observations during the last 2–3 decades, indicating no significant long‐term ice thickness change. This is also concurrent with the lack of significant temperature changes in the Arctic Ocean during the same period. The mean ice thickness in the central core of the ice stream shows an annual amplitude of 1 m with a minimum in September of 2.25 m and a maximum in April‐May of 3.25 m. The mean thickness of ice only (open water excluded) is 3.27 m and compares with 3.29 m which is the mean thickness of ice only from 17 submarine tracks in the Arctic Ocean 1960–1982. The mean annual ice export, which is equal to the mean annual net production of ice in the Arctic Ocean, is ∼2850 km3 yr−1 for the period 1990–1996. This efflux shows significant variations from year to year with a minimum in 1990–1991 of ∼2050 km yr−1 and a maximum in 1994–1995 of ∼4700 km3 yr−1. This significant variation of nearly 130% is mainly caused by an increased atmospheric forcing and to a lesser degree by an increase in the annual mean ice thickness of ∼20% over the same period.

Evaluation of ship-based electromagnetic-inductive thickness measurements of summer sea-ice in the Bellingshausen and Amundsen Seas, Antarctica

The accuracy of electromagnetic-inductive (EM) sea-ice thickness measurements performed from a moving icebreaker is evaluated. Ice thickness distributions and ridge statistics are derived. In the Bellingshausen Sea the ice was moderately deformed with mean and modal ice thicknesses of 1.3 and 0.9 m, respectively. In contrast, the heavily deformed ice in the Amundsen Sea had mean thicknesses between 2.3 and 3.1 m, with modes between 1.6 and 2.7 m. By means of the measured apparent electrical conductivity on ice of known thickness, the conductivity of the perennial summer ice was found to be significant and could not be neglected in the calibration of EM measurements. The high conductivity is mainly due to the widespread occurrence of seawater-filled gaps close to the ice surface. The system, consisting of commercially available instruments, yielded reliable mean thickness estimates. This is shown by comparison with drill-hole measurements and visual observations. However, the thickness profiles appear highly low-pass filtered compared to their surface height profile determined with a laser altimeter. Thus the system possesses a limited lateral resolution such that the thickness of single pressure ridges cannot be resolved. This is only in part attributed to the trade-off between increasing instrument height and decreasing lateral resolution of EM measurements. The low resolution is mainly due to the particular EM instrument, as its sensitivity is highly reduced if used far above the water surface, and it has a comparatively long time constant of 1 s. Additionally, the water-filled gap in the ice generally reduces the sensitivity of the measured apparent conductivity to ice thickness changes.

Travel time changes in a tomography array caused by a sea ice cover

In September 1988 an acoustic tomography array was deployed in the Greenland Sea in the region 74–76°N, 1°E-5°W. We have modelled travel time changes which may be produced in this array by the presence, or growth, of a sea ice cover. Three types of icefield are considered: a typical East Greenland marginal ice zone (MIZ) thickness distribution, using as input data a sonar profile from a British submarine; a field of discrete floes without pressure ridging; and a pancake-frazils mix growing on the open sea. Firstly we calculated travel time changes caused by an ice sheet uniform thickness. The travel time decreases with increasing ice thickness, by 2–10 ms for 3 m thickness at a frequency of 250 Hz and a range of 200 km, but the magnitude depends on grazing angle and (strongly) on compressional and shear velocities in ice. With some values for velocity the relationship is no longer monotonic. In a real icefield we surmised that the modal ice thickness is responsible for the coherent reflected ray which is detected. Secondly we calculated the progressive travel time decrease resulting from the increase in mixed layer salinity caused by salt rejection from a growing ice cover. We conclude that this is negligible for MIZ-type ice covers, but is detectable for rapidly growing pancake fields and in the case of shallow rays may reach 3.5 ms per day. Finally we calculated the scattering loss associated with ice bottom roughness in MIZ-type icefields, finding that for steep rays it is about 15 dB on average at 200 km range, so that signal-to-noise ratios in such arrays need to be raised to ensure adequate timing precision. If this is achieved, we conclude that acoustic tomography can be used as a means of monitoring modal ice thickness in the Greenland Sea.

Relation between transparency and currents in the north-eastern Pacific : K ozlyaninov, M. V., 1961. Trud. Inst. Okeanol., Akad. Nauk SSSR, 45: 102–112.

The accuracy of electromagnetic-inductive (EM) sea-ice thickness measurements performed from a moving icebreaker is evaluated. Ice thickness distributions and ridge statistics are derived. In the Bellingshausen Sea the ice was moderately deformed with mean and modal ice thicknesses of 1.3 and 0.9 m, respectively. In contrast, the heavily deformed ice in the Amundsen Sea had mean thicknesses between 2.3 and 3.1 m, with modes between 1.6 and 2.7 m. By means of the measured apparent electrical conductivity on ice of known thickness, the conductivity of the perennial summer ice was found to be significant and could not be neglected in the calibration of EM measurements. The high conductivity is mainly due to the widespread occurrence of seawater-filled gaps close to the ice surface. The system, consisting of commercially available instruments, yielded reliable mean thickness estimates. This is shown by comparison with drill-hole measurements and visual observations. However, the thickness profiles appear highly low-pass filtered compared to their surface height profile determined with a laser altimeter. Thus the system possesses a limited lateral resolution such that the thickness of single pressure ridges cannot be resolved. This is only in part attributed to the trade-off between increasing instrument height and decreasing lateral resolution of EM measurements. The low resolution is mainly due to the particular EM instrument, as its sensitivity is highly reduced if used far above the water surface, and it has a comparatively long time constant of 1 s. Additionally, the water-filled gap in the ice generally reduces the sensitivity of the measured apparent conductivity to ice thickness changes.

Vegetable pigments in the suspended material and in bottom sediments of the Indian Ocean : K outyurin, V. M. and A. P. L isitsin, 1961. Mezhd. Kom. Mezhd. Geofiz. Goda, Presidiume Akad. Nauk, SSSR, Okeanol. Issled. (3): 90–116.

The accuracy of electromagnetic-inductive (EM) sea-ice thickness measurements performed from a moving icebreaker is evaluated. Ice thickness distributions and ridge statistics are derived. In the Bellingshausen Sea the ice was moderately deformed with mean and modal ice thicknesses of 1.3 and 0.9 m, respectively. In contrast, the heavily deformed ice in the Amundsen Sea had mean thicknesses between 2.3 and 3.1 m, with modes between 1.6 and 2.7 m. By means of the measured apparent electrical conductivity on ice of known thickness, the conductivity of the perennial summer ice was found to be significant and could not be neglected in the calibration of EM measurements. The high conductivity is mainly due to the widespread occurrence of seawater-filled gaps close to the ice surface. The system, consisting of commercially available instruments, yielded reliable mean thickness estimates. This is shown by comparison with drill-hole measurements and visual observations. However, the thickness profiles appear highly low-pass filtered compared to their surface height profile determined with a laser altimeter. Thus the system possesses a limited lateral resolution such that the thickness of single pressure ridges cannot be resolved. This is only in part attributed to the trade-off between increasing instrument height and decreasing lateral resolution of EM measurements. The low resolution is mainly due to the particular EM instrument, as its sensitivity is highly reduced if used far above the water surface, and it has a comparatively long time constant of 1 s. Additionally, the water-filled gap in the ice generally reduces the sensitivity of the measured apparent conductivity to ice thickness changes.