scholarly journals Sea-ice production and air/ice/ocean/biogeochemistry interactions in the Ross Sea during the PIPERS 2017 autumn field campaign

2020 ◽  
Vol 61 (82) ◽  
pp. 181-195 ◽  
Author(s):  
S. F. Ackley ◽  
S. Stammerjohn ◽  
T. Maksym ◽  
M. Smith ◽  
J. Cassano ◽  
...  
Keyword(s):  
Heat Flux ◽  
Sea Ice ◽  
Multidisciplinary Approach ◽  
Ross Sea ◽  
Ice Thickness ◽  
Biogeochemical Processes ◽  
Sea Ice Thickness ◽  
Ocean Biogeochemistry ◽  
Ice Edge ◽  
Ice Production

AbstractThe Ross Sea is known for showing the greatest sea-ice increase, as observed globally, particularly from 1979 to 2015. However, corresponding changes in sea-ice thickness and production in the Ross Sea are not known, nor how these changes have impacted water masses, carbon fluxes, biogeochemical processes and availability of micronutrients. The PIPERS project sought to address these questions during an autumn ship campaign in 2017 and two spring airborne campaigns in 2016 and 2017. PIPERS used a multidisciplinary approach of manned and autonomous platforms to study the coupled air/ice/ocean/biogeochemical interactions during autumn and related those to spring conditions. Unexpectedly, the Ross Sea experienced record low sea ice in spring 2016 and autumn 2017. The delayed ice advance in 2017 contributed to (1) increased ice production and export in coastal polynyas, (2) thinner snow and ice cover in the central pack, (3) lower sea-ice Chl-a burdens and differences in sympagic communities, (4) sustained ocean heat flux delaying ice thickening and (5) a melting, anomalously southward ice edge persisting into winter. Despite these impacts, airborne observations in spring 2017 suggest that winter ice production over the continental shelf was likely not anomalous.

scholarly journals Autumn sea ice thickness, ridging and heat flux variability in and adjacent to Terra Nova Bay, Ross Sea, Antarctica

2001 ◽  
Vol 106 (C3) ◽  
pp. 4437-4448 ◽  
Author(s):  
Martin O. Jeffries ◽  
Kim Morris ◽  
Ted Maksym ◽  
Nickolai Kozlenko ◽  
Tina Tin
Keyword(s):  
Heat Flux ◽  
Sea Ice ◽  
Ross Sea ◽  
Ice Thickness ◽  
Sea Ice Thickness ◽  
Terra Nova Bay ◽  
Flux Variability ◽  
Terra Nova

Sea ice deformation and thickness in the Western Ross Sea

2021 ◽  
Author(s):  
Wolfgang Rack ◽  
Daniel Price ◽  
Christian Haas ◽  
Patricia J. Langhorne ◽  
Greg H. Leonard
Keyword(s):  
Sea Ice ◽  
Satellite Images ◽  
Ross Sea ◽  
Thickness Distribution ◽  
Ice Thickness ◽  
Ice Dynamics ◽  
Sea Ice Thickness ◽  
Ice Volume ◽  
Terra Nova Bay ◽  
Western Ross Sea

<p>Sea ice cover is arguably the longest and best observed climate variable from space, with over four decades of highly reliable daily records of extent in both hemispheres. In Antarctica, a slight positive decadal trend in sea ice cover is driven by changes in the western Ross Sea, where a variation in weather patterns over the wider region forced a change in meridional winds. The distinguishing wind driven sea ice process in the western Ross Sea is the regular occurrence of the Ross Sea, McMurdo Sound, and Terra Nova Bay polynyas. Trends in sea ice volume and mass in this area unknown, because ice thickness and dynamics are particularly hard to measure.</p><p>Here we present the first comprehensive and direct assessment of large-scale sea-ice thickness distribution in the western Ross Sea. Using an airborne electromagnetic induction (AEM) ice thickness sensor towed by a fixed wing aircraft (Basler BT-67), we observed in November 2017 over a distance of 800 km significantly thicker ice than expected from thermodynamic growth alone. By means of time series of satellite images and wind data we relate the observed thickness distribution to satellite derived ice dynamics and wind data. Strong southerly winds with speeds of up to 25 ms<sup>-1</sup> in early October deformed the pack ice, which was surveyed more than a month later.</p><p>We found strongly deformed ice with a mean and maximum thickness of 2.0 and 15.6 m, respectively. Sea-ice thickness gradients are highest within 100-200 km of polynyas, where the mean thickness of the thickest 10% of ice is 7.6 m. From comparison with aerial photographs and satellite images we conclude that ice preferentially grows in deformational ridges; about 43% of the sea ice volume in the area between McMurdo Sound and Terra Nova Bay is concentrated in more than 3 m thick ridges which cover about 15% of the surveyed area. Overall, 80% of the ice was found to be heavily deformed and concentrated in ridges up to 11.8 m thick.</p><p>Our observations hold a link between wind driven ice dynamics and the ice mass exported from the western Ross Sea. The sea ice statistics highlighted in this contribution forms a basis for improved satellite derived mass balance assessments and the evaluation of sea ice simulations.</p>

Estimating the thickness of ridged sea ice from ship observations in the Ross Sea

2003 ◽  
Vol 15 (1) ◽  
pp. 47-54 ◽  
Author(s):  
TINA TIN ◽  
MARTIN O. JEFFRIES ◽  
MIKKO LENSU ◽  
JUKKA TUHKURI
Keyword(s):  
Sea Ice ◽  
Ross Sea ◽  
Low Cost ◽  
Thickness Distribution ◽  
Ice Thickness ◽  
Equivalent Thickness ◽  
Sea Ice Thickness ◽  
Antarctic Sea Ice ◽  
Using Data ◽  
Original Formula

Ship-based observations of sea ice thickness using the Antarctic Sea Ice Processes and Climate (ASPeCt) protocol provide information on ice thickness distribution at relatively low cost. This protocol uses a simple formula to calculate the mass of ice in ridges based on surface observations. We present two new formulae and compare these with results from the “Original” formula using data obtained in the Ross Sea in autumn and winter. The new “r-star” formula uses a more realistic ratio of sail and keel areas to transform dimensions of sails to estimates of mean keel areas. As a result, estimates of “equivalent thickness” (i.e. mean thickness of ice in ridged areas) increased by over 200%. The new “Probability” formula goes one step further, by incorporating the probability that a sail is associated with a keel underwater, and the probability that keels may be found under level surfaces. This resulted in estimates of equivalent thickness comparable with the Original formula. Estimates of equivalent thickness at one or two degree latitude resolution are sufficiently accurate for validating sea ice models. Although ridges are small features in the Ross Sea, we have shown that they constitute a significant fraction of the total ice mass.

Early winter ice and snow thickness distribution, ice structure and development of the western Ross Sea pack ice between the ice edge and the Ross Ice Shelf

1997 ◽  
Vol 9 (2) ◽  
pp. 188-200 ◽  
Author(s):  
Martin O. Jeffries ◽  
Ute Adolphs
Keyword(s):  
Sea Ice ◽  
Layer Thickness ◽  
Ross Sea ◽  
Ice Thickness ◽  
First Year ◽  
Ross Ice Shelf ◽  
Antarctic Sea Ice ◽  
Pack Ice ◽  
Ice Edge ◽  
Snow And Ice

A study of early winter first-year sea ice conditions and development in the western Ross Sea in May and June 1995 included measurements of snow and ice thickness, freeboard, ice core structure and stable isotopic composition. These variables showed strong spatial variability between the Ross Ice Shelf and the ice edge 1400 km to the north, and indicate that the development of the Ross Sea pack ice is quite different from that observed in other Antarctic sea ice zones. The thinnest snow and ice occurred in a 200 km wide coastal zone. The thickest snow and ice were observed in a continental shelf zone 200–600 km from the coast where the average ice thickness (0.8 m) determined by drilling is as thick as first-year sea ice later in winter elsewhere in Antarctica. A zone of moderate snow and ice thickness occurred on the deep ocean from 600 km to the ice edge at 1400 km. Thermodynamic thickening of the ice in the inner pack ice, <800 km from the coast, was dominated by congelation ice growth, which occurred in a greater amount (65%) and in thicker layers (mean: 20 cm) than was observed in the outer pack ice >800 km from the coast (amount: 22%; mean layer thickness: 12 cm) and elsewhere in the Antarctic pack ice. The preponderance of congelation ice in the inner pack ice might be due to a low oceanic heat flux on the Ross Sea continental shelf, and a colder, less stormy environment which favours the more frequent and prolonged calm conditions necessary for significant congelation ice growth. In the outer pack ice, thermodynamic thickening occurred mainly by snow ice formation (mean layer thickness: 20 cm) while dynamic processes, i.e., rafting and ridging, caused the thickening of frazil ice and columnar ice (mean layer thickness: 14 cm and 12 cm respectively). A greater amount of snow ice (37%) occurred in the outer pack ice than in the inner pack ice (15%), and both values indicate that in the Ross Sea, unlike other Antarctic sea ice zones, there can be significant seawater flooding of the snow/ice interface and snow ice formation before midwinter.

scholarly journals Benefits of assimilating thin sea ice thickness from SMOS into the TOPAZ system

2016 ◽  
Vol 10 (6) ◽  
pp. 2745-2761 ◽  
Author(s):  
Jiping Xie ◽  
François Counillon ◽  
Laurent Bertino ◽  
Xiangshan Tian-Kunze ◽  
Lars Kaleschke
Keyword(s):  
Sea Ice ◽  
Cold Season ◽  
The Arctic ◽  
Ice Thickness ◽  
Data Set ◽  
Sea Ice Thickness ◽  
Ice Concentration ◽  
Ice Edge ◽  
Anomaly Analysis ◽  
The Impact

Abstract. An observation product for thin sea ice thickness (SMOS-Ice) is derived from the brightness temperature data of the European Space Agency's (ESA) Soil Moisture and Ocean Salinity (SMOS) mission. This product is available in near-real time, at daily frequency, during the cold season. In this study, we investigate the benefit of assimilating SMOS-Ice into the TOPAZ coupled ocean and sea ice forecasting system, which is the Arctic component of the Copernicus marine environment monitoring services. The TOPAZ system assimilates sea surface temperature (SST), altimetry data, temperature and salinity profiles, ice concentration, and ice drift with the ensemble Kalman filter (EnKF). The conditions for assimilation of sea ice thickness thinner than 0.4 m are favorable, as observations are reliable below this threshold and their probability distribution is comparable to that of the model. Two parallel Observing System Experiments (OSE) have been performed in March and November 2014, in which the thicknesses from SMOS-Ice (thinner than 0.4 m) are assimilated in addition to the standard observational data sets. It is found that the root mean square difference (RMSD) of thin sea ice thickness is reduced by 11 % in March and 22 % in November compared to the daily thin ice thicknesses of SMOS-Ice, which suggests that SMOS-Ice has a larger impact during the beginning of the cold season. Validation against independent observations of ice thickness from buoys and ice draft from moorings indicates that there are no degradations in the pack ice but there are some improvements near the ice edge close to where the SMOS-Ice has been assimilated. Assimilation of SMOS-Ice yields a slight improvement for ice concentration and degrades neither SST nor sea level anomaly. Analysis of the degrees of freedom for signal (DFS) indicates that the SMOS-Ice has a comparatively small impact but it has a significant contribution in constraining the system (> 20 % of the impact of all ice and ocean observations) near the ice edge. The areas of largest impact are the Kara Sea, Canadian Archipelago, Baffin Bay, Beaufort Sea and Greenland Sea. This study suggests that the SMOS-Ice is a good complementary data set that can be safely included in the TOPAZ system.

scholarly journals Estimation of Thin Ice Thickness and Detection of Fast Ice from SSM/I Data in the Antarctic Ocean

2007 ◽  
Vol 24 (10) ◽  
pp. 1757-1772 ◽  
Author(s):  
Takeshi Tamura ◽  
Kay I. Ohshima ◽  
Thorsten Markus ◽  
Donald J. Cavalieri ◽  
Sohey Nihashi ◽  
...  
Keyword(s):  
Sea Ice ◽  
Ross Sea ◽  
Weddell Sea ◽  
Ice Thickness ◽  
Coastal Current ◽  
Antarctic Ocean ◽  
Coastal Polynya ◽  
Fast Ice ◽  
Ice Production ◽  
The Antarctic

Abstract Antarctic coastal polynyas are important areas of high sea ice production and dense water formation, and thus their detection including an estimate of thin ice thickness is essential. In this paper, the authors propose an algorithm that estimates thin ice thickness and detects fast ice using Defense Meteorological Satellite Program (DMSP) Special Sensor Microwave Imager (SSM/I) data in the Antarctic Ocean. Detection and estimation of sea ice thicknesses of &lt;0.2 m are based on the SSM/I 85- and 37-GHz polarization ratios (PR85 and PR37) through a comparison with sea ice thicknesses estimated from the Advanced Very High Resolution Radiometer (AVHRR) data. The exclusion of data affected by atmospheric water vapor is discussed. Because thin ice and fast ice (specifically ice shelves, glacier tongues, icebergs, and landfast ice) have similar PR signatures, a scheme was developed to separate these two surface types before the application of the thin ice algorithm to coastal polynyas. The probability that the algorithm correctly distinguishes thin ice from thick ice and from fast ice is ∼95%, relative to the ice thicknesses estimated from AVHRR. Although the standard deviation of the difference between the thin ice thicknesses estimated from the SSM/I algorithm and AVHRR is ∼0.05 m and thus not small, the estimated ice thicknesses from the microwave algorithm appear to have small biases and the accuracies are independent of region and season. A distribution map of thin ice occurrences derived from the SSM/I algorithm represents the Ross Sea coastal polynya being by far the largest among the Antarctic coastal polynyas; the Weddell Sea coastal polynyas are much smaller. Along the coast of East Antarctica, coastal polynyas frequently form on the western side of peninsulas and glacier tongues, downstream of the Antarctic Coastal Current.

scholarly journals Sea-ice thickness and roughness in the Ross Sea, Antarctica

2001 ◽  
Vol 33 ◽  
pp. 187-193 ◽  
Author(s):  
Tina Tin ◽  
Martin O. Jeffries
Keyword(s):  
Surface Roughness ◽  
Sea Ice ◽  
Ross Sea ◽  
Geographical Location ◽  
Ice Thickness ◽  
Snow Surface ◽  
Sea Ice Thickness ◽  
Antarctic Sea Ice ◽  
Ice Roughness ◽  
Ice Floes

AbstractSea-ice thickness and roughness data collected on three cruises in the Ross Sea, Antarctica, showed interseasonal, regional and interannual variability. Variability was reduced to season, or age of ice floe, when sea-ice roughness values from around Antarctica were compared. There were statistically significant correlations between mean snow elevation and mean ice thickness; snow surface roughness and mean ice thickness; and snow surface roughness and ice bottom roughness, which appeared to be independent of season, geographical location and deformation history of ice floes. Our field data indicate that ice thickness can be predicted from snow elevation measurements with higher accuracy in summer. The feasibility of using snow surface roughness to infer ice thickness and ice bottom roughness is promising, and can provide us with a means to study the thickness and underside of Antarctic sea ice at good spatial and temporal resolution.

Estimating the annual cycle of sea-ice thickness and volume in the Ross Sea

2011 ◽  
Vol 58 (9-10) ◽  
pp. 1250-1260 ◽  
Author(s):  
Tracy L. DeLiberty ◽  
Cathleen A. Geiger ◽  
Stephen F. Ackley ◽  
Anthony P. Worby ◽  
Michael L. Van Woert
Keyword(s):  
Sea Ice ◽  
Annual Cycle ◽  
Ross Sea ◽  
Ice Thickness ◽  
Sea Ice Thickness

scholarly journals Estimation of thin Sea-ice thickness from NOAA AVHRR data in a polynya off the Wilkes Land coast, East Antarctica

2006 ◽  
Vol 44 ◽  
pp. 269-274 ◽  
Author(s):  
Takeshi Tamura ◽  
Kay I. Ohshima ◽  
Hiroyuki Enomoto ◽  
Kazutaka Tateyama ◽  
Atsuhiro Muto ◽  
...  
Keyword(s):  
Heat Flux ◽  
Sea Ice ◽  
Meteorological Data ◽  
Ice Thickness ◽  
Sea Ice Thickness ◽  
Flux Calculation ◽  
Ice Surface ◽  
Wilkes Land ◽  
Ice Surface Temperature

AbstractAntarctic coastal polynyas are major areas of intense ocean–atmosphere heat and moisture flux, and associated high Sea-ice production and dense-water formation. Their accurate detection, including an estimate of thin ice thickness, is therefore very important. In this paper, we apply a technique originally developed in the Arctic to an estimation of Sea-ice thickness using Us National Oceanic and Atmospheric Administration (NOAA) Advanced Very High Resolution Radiometer (AVHRR) data and meteorological data in the Vincennes Bay polynya off Wilkes Land, East Antarctica. The method is based upon the heat-flux calculation using Sea-ice Surface temperature estimates from the Satellite thermal-infrared data combined with global objective analysis (European Centre for Medium-Range Weather Forecasts (ECMWF)) data. The validity of this method is assessed by comparing results with independent ice-surface temperature and ice-thickness data obtained during an Australian-led research cruise to the region in 2003. In thin-ice (polynya) regions, ice thicknesses estimated by the heat-flux calculation using AVHRR and ECMWF data Show reasonable agreement with those estimated by (a) applying the heat-flux calculation to in Situ radiation thermometer and meteorological data and (b) in Situ observations. The Standard deviation of the difference between the AVHRR-derived and in Situ data is ∽0.02 m. Comparison of the AVHRR ice-thickness retrievals with coincident Satellite passive-microwave polarization ratio data confirms the potential of the latter as a means of deriving maps of thin Sea-ice thickness on the wider Scale, uninterrupted by darkness and cloud cover.

scholarly journals Sensitivity of Northern Hemisphere climate to ice–ocean interface heat flux parameterizations

2021 ◽  
Vol 14 (8) ◽  
pp. 4891-4908
Author(s):  
Xiaoxu Shi ◽  
Dirk Notz ◽  
Jiping Liu ◽  
Hu Yang ◽  
Gerrit Lohmann
Keyword(s):  
Heat Flux ◽  
Heat Exchange ◽  
Sea Ice ◽  
Temperature Difference ◽  
Climate Model ◽  
Turbulent Heat Flux ◽  
The Arctic ◽  
Ice Thickness ◽  
Turbulent Heat ◽  
Sea Ice Thickness

Abstract. We investigate the impact of three different parameterizations of ice–ocean heat exchange on modeled sea ice thickness, sea ice concentration, and water masses. These three parameterizations are (1) an ice bath assumption with the ocean temperature fixed at the freezing temperature; (2) a two-equation turbulent heat flux parameterization with ice–ocean heat exchange depending linearly on the temperature difference between the underlying ocean and the ice–ocean interface, whose temperature is kept at the freezing point of the seawater; and (3) a three-equation turbulent heat flux approach in which the ice–ocean heat flux depends on the temperature difference between the underlying ocean and the ice–ocean interface, whose temperature is calculated based on the local salinity set by the ice ablation rate. Based on model simulations with the stand-alone sea ice model CICE, the ice–ocean model MPIOM, and the climate model COSMOS, we find that compared to the most complex parameterization (3), the approaches (1) and (2) result in thinner Arctic sea ice, cooler water beneath high-concentration ice and warmer water towards the ice edge, and a lower salinity in the Arctic Ocean mixed layer. In particular, parameterization (1) results in the smallest sea ice thickness among the three parameterizations, as in this parameterization all potential heat in the underlying ocean is used for the melting of the sea ice above. For the same reason, the upper ocean layer of the central Arctic is cooler when using parameterization (1) compared to (2) and (3). Finally, in the fully coupled climate model COSMOS, parameterizations (1) and (2) result in a fairly similar oceanic or atmospheric circulation. In contrast, the most realistic parameterization (3) leads to an enhanced Atlantic meridional overturning circulation (AMOC), a more positive North Atlantic Oscillation (NAO) mode and a weakened Aleutian Low.

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