skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.

Attention:

The NSF Public Access Repository (PAR) system and access will be unavailable from 10:00 PM to 12:00 AM ET on Tuesday, March 25 due to maintenance. We apologize for the inconvenience.


Title: Sea ice thickness and false bottom measurements along drill lines during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition, Leg 4
This dataset contains measurements of sea ice thickness along drill lines. These measurements were taken in the Central Arctic during Leg 4 of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition, July 14-29, 2020. Thickness measurements include observations of rafted ice, false bottoms, and sea ice freeboard. Measurements were made through holes in the ice made with a 2-inch sea ice drill, with thickness and features observations made using a combination of thickness tape and a snow stick adapted for the purpose. The primary aim of these observations was to capture the presence and distribution of false bottom features under the ice during the melt season.  more » « less
Award ID(s):
1724467
PAR ID:
10389913
Author(s) / Creator(s):
; ; ; ;
Publisher / Repository:
NSF Arctic Data Center
Date Published:
Subject(s) / Keyword(s):
sea ice thickness MOSAiC
Format(s):
Medium: X Other: text/xml
Sponsoring Org:
National Science Foundation
More Like this
  1. Precise measurements of Arctic sea ice mass balance are necessary to understand the rapidly changing sea ice cover and its representation in climate models. During the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition, we made repeat point measurements of snow and ice thickness on primarily level first- and second-year ice (FYI, SYI) using ablation stakes and ice thickness gauges. This technique enabled us to distinguish surface and bottom (basal) melt and characterize the importance of oceanic versus atmospheric forcing. We also evaluated the time series of ice growth and melt in the context of other MOSAiC observations and historical mass balance observations from the Surface Heat Budget of the Arctic (SHEBA) campaign and the North Pole Environmental Observatory (NPEO). Despite similar freezing degree days, average ice growth at MOSAiC was greater on FYI (1.67 m) and SYI (1.23 m) than at SHEBA (1.45 m, 0.53 m), due in part to initially thinner ice and snow conditions on MOSAiC. Our estimates of effective snow thermal conductivity, which agree with SHEBA results and other MOSAiC observations, are unlikely to explain the difference. On MOSAiC, FYI grew more and faster than SYI, demonstrating a feedback loop that acts to increase ice production after multi-year ice loss. Surface melt on MOSAiC (mean of 0.50 m) was greater than at NPEO (0.18 m), with considerable spatial variability that correlated with surface albedo variability. Basal melt was relatively small (mean of 0.12 m), and higher than NPEO observations (0.07 m). Finally, we present observations showing that false bottoms reduced basal melt rates in some FYI cases, in agreement with other observations at MOSAiC. These detailed mass balance observations will allow further investigation into connections between the carefully observed surface energy budget, ocean heat fluxes, sea ice, and ecosystem at MOSAiC and during other campaigns. 
    more » « less
  2. The rapid melt of snow and sea ice during the Arctic summer provides a significant source of low-salinity meltwater to the surface ocean on the local scale. The accumulation of this meltwater on, under, and around sea ice floes can result in relatively thin meltwater layers in the upper ocean. Due to the small-scale nature of these upper-ocean features, typically on the order of 1 m thick or less, they are rarely detected by standard methods, but are nevertheless pervasive and critically important in Arctic summer. Observations during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition in summer 2020 focused on the evolution of such layers and made significant advancements in understanding their role in the coupled Arctic system. Here we provide a review of thin meltwater layers in the Arctic, with emphasis on the new findings from MOSAiC. Both prior and recent observational datasets indicate an intermittent yet long-lasting (weeks to months) meltwater layer in the upper ocean on the order of 0.1 m to 1.0 m in thickness, with a large spatial range. The presence of meltwater layers impacts the physical system by reducing bottom ice melt and allowing new ice formation via false bottom growth. Collectively, the meltwater layer and false bottoms reduce atmosphere-ocean exchanges of momentum, energy, and material. The impacts on the coupled Arctic system are far-reaching, including acting as a barrier for nutrient and gas exchange and impacting ecosystem diversity and productivity. 
    more » « less
  3. During the Arctic melt season, relatively fresh meltwater layers can accumulate under sea ice as a result of snow and ice melt, far from terrestrial freshwater inputs. Such under-ice meltwater layers, sometimes referred to as under-ice melt ponds, have been suggested to play a role in the summer sea ice mass balance both by isolating the sea ice from saltier water below, and by driving formation of ‘false bottoms’ below the sea ice. Such layers form at the interface of the fresher under-ice layer and the colder, saltier seawater below. During the Multidisciplinary drifting Observatory for the Study of the Arctic Climate (MOSAiC) expedition in the Central Arctic, we observed the presence of under-ice meltwater layers and false bottoms throughout July 2020 at primarily first-year ice locations. Here, we examine the distribution, prevalence, and drivers of under-ice ponds and the resulting false bottoms during this period. The average thickness of observed false bottoms and freshwater equivalent of under-ice meltwater layers was 0.08 m, with false bottom ice comprised of 74–87% FYI melt and 13–26% snow melt. Additionally, we explore these results using a 1D model to understand the role of dynamic influences on decoupling the ice from the seawater below. The model comparison suggests that the ice-ocean friction velocity was likely exceptionally low, with implications for air-ice-ocean momentum transfer. Overall, the prevalence of false bottoms was similar to or higher than noted during other observational campaigns, indicating that these features may in fact be common in the Arctic during the melt season. These results have implications for the broader ice-ocean system, as under-ice meltwater layers and false bottoms provide a source of ice growth during the melt season, potentially reduce fluxes between the ice and the ocean, isolate sea ice primary producers from pelagic nutrient sources, and may alter light transmission to the ocean below. 
    more » « less
  4. Sea ice thickness is a key parameter in the polar climate and ecosystem. Thermodynamic and dynamic processes alter the sea ice thickness. The Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition provided a unique opportunity to study seasonal sea ice thickness changes of the same sea ice. We analyzed 11 large-scale (∼50 km) airborne electromagnetic sea thickness and surface roughness surveys from October 2019 to September 2020. Data from ice mass balance and position buoys provided additional information. We found that thermodynamic growth and decay dominated the seasonal cycle with a total mean sea ice thickness increase of 1.4 m (October 2019 to June 2020) and decay of 1.2 m (June 2020 to September 2020). Ice dynamics and deformation-related processes, such as thin ice formation in leads and subsequent ridging, broadened the ice thickness distribution and contributed 30% to the increase in mean thickness. These processes caused a 1-month delay between maximum thermodynamic sea ice thickness and maximum mean ice thickness. The airborne EM measurements bridged the scales from local floe-scale measurements to Arctic-wide satellite observations and model grid cells. The spatial differences in mean sea ice thickness between the Central Observatory (<10 km) of MOSAiC and the Distributed Network (<50 km) were negligible in fall and only 0.2 m in late winter, but the relative abundance of thin and thick ice varied. One unexpected outcome was the large dynamic thickening in a regime where divergence prevailed on average in the western Nansen Basin in spring. We suggest that the large dynamic thickening was due to the mobile, unconsolidated sea ice pack and periodic, sub-daily motion. We demonstrate that this Lagrangian sea ice thickness data set is well suited for validating the existing redistribution theory in sea ice models. Our comprehensive description of seasonal changes of the sea ice thickness distribution is valuable for interpreting MOSAiC time series across disciplines and can be used as a reference to advance sea ice thickness modeling. 
    more » « less
  5. This dataset contains broadband albedo measurements made on the sea ice surface from approximately 1-meter (m) elevation during April – September 2020 as part of the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition in the Central Arctic Ocean. Measurements were made in three modes: (i) along ‘albedo lines’, between 60-200 meters (m) in length, with measurements every 5 meters (or 10 meters on leg 3), (ii) at specific ‘library sites,’ or (iii) ‘experiments’. Albedo lines were chosen with the aim of crossing representative surface conditions during the summer sea ice evolution, including snow-covered ridges, bare ice, and ponded ice. Included in the dataset are classification of the surface cover and depth for most measurements. Broadband albedo data was collected using a Kipp and Zonen albedometer. This dataset is collocated with the spectral albedo dataset (doi.org/10.18739/A2FT8DK8Z) and albedo photo dataset (doi.org/10.18739/A2B27PS3N). 
    more » « less