scholarly journals Potential of temperature- and salinity-driven shifts in diatom compatible solute concentrations to impact biogeochemical cycling within sea ice

Elem Sci Anth ◽  
2020 ◽  
Vol 8 ◽  
Author(s):  
Hannah M. Dawson ◽  
Katherine R. Heal ◽  
Angela K. Boysen ◽  
Laura T. Carlson ◽  
Anitra E. Ingalls ◽  
...  
Keyword(s):  
Sea Ice ◽  
Compatible Solutes ◽  
Biogeochemical Cycling ◽  
Compatible Solute ◽  
Arctic Sea Ice ◽  
Polar Regions ◽  
Antarctic Sea Ice ◽  
Metabolite Profiles ◽  
Metabolite Pool ◽  
Cellular Metabolite

Sea-ice algae are an important source of primary production in polar regions, yet we have limited understanding of their responses to the seasonal cycling of temperature and salinity. Using a targeted liquid chromatography-mass spectrometry-based metabolomics approach, we found that axenic cultures of the Antarctic sea-ice diatom, Nitzschia lecointei, displayed large differences in their metabolomes when grown in a matrix of conditions that included temperatures of –1 and 4°C, and salinities of 32 and 41, despite relatively small changes in growth rate. Temperature exerted a greater effect than salinity on cellular metabolite pool sizes, though the N- or S-containing compatible solutes, 2, 3-dihydroxypropane-1-sulfonate (DHPS), glycine betaine (GBT), dimethylsulfoniopropionate (DMSP), and proline responded strongly to both temperature and salinity, suggesting complexity in their control. We saw the largest (> 4-fold) response to salinity for proline. DHPS, a rarely studied but potential compatible solute, had the highest intracellular concentrations among all compatible solutes of ~85 mM. When comparing the culture findings to natural Arctic sea-ice diatom communities, we found extensive overlap in metabolite profiles, highlighting the relevance of culture-based studies to probe environmental questions. Large changes in sea-ice diatom metabolomes and compatible solutes over a seasonal cycle could be significant components of biogeochemical cycling within sea ice.

scholarly journals Using CALIOP to constrain blowing snow emissions of sea salt aerosols over Arctic and Antarctic sea ice

2018 ◽  
Author(s):  
Jiayue Huang ◽  
Lyatt Jaeglé ◽  
Viral Shah
Keyword(s):  
Sea Ice ◽  
Lower Troposphere ◽  
Arctic Sea Ice ◽  
Sea Salt ◽  
Polar Regions ◽  
Blowing Snow ◽  
Sea Salt Aerosols ◽  
Antarctic Sea Ice ◽  
Surface Snow ◽  
Frost Flowers

Abstract. Sea salt aerosols (SSA) produced on sea ice surfaces by blowing snow events or lifting of frost flower crystals have been suggested as important sources of SSA during winter over polar regions. The magnitude and relative contribution of blowing snow and frost flower SSA sources, however, remain uncertain. In this study, we use 2007–2009 aerosol extinction coefficients from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) instrument onboard the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite and the GEOS-Chem global chemical transport model to constrain sources of SSA over Arctic and Antarctic sea ice. CALIOP retrievals show elevated levels of aerosol extinctions (10–20 Mm−1) in the lower troposphere (0–2 km) over polar regions during cold months. The standard GEOS-Chem model underestimates the CALIOP aerosol extinctions by 50–70 %. Adding frost flower emissions of SSA fails to explain the CALIOP observations. With blowing snow SSA emissions, the model captures the overall spatial and seasonal variation of CALIOP aerosol extinctions over the polar regions, but overestimates springtime aerosol extinctions over Arctic sea ice and winter-spring extinctions over Antarctic sea ice. We reduce the surface snow salinity over multi-year sea ice and infer the monthly FYI snow salinity required to minimize the discrepancy between CALIOP extinctions and the GEOS-Chem simulation. The empirically-derived snow salinity shows a decreasing trend in between fall and spring. The optimized blowing snow model with inferred snow salinities generally agrees with CALIOP extinction observations to within 10 % over sea ice, but underestimates aerosol extinctions over the regions where frost flowers are expected to have a large influence. Frost flowers could thus contribute indirectly to SSA production by increasing the local surface snow salinity and, therefore, the SSA production from blowing snow. We carry out a case study of an Arctic blowing snow SSA feature predicted by GEOS-Chem and sampled by CALIOP. Using backtrajectories, we link this feature to a blowing snow event which occurred 2 days earlier over first-year sea ice and was also detected by CALIOP.

Making informed use of observations and climate models to advance understanding of past and future sea ice changes

2021 ◽  
Author(s):  
Francois Massonnet
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Arctic Sea Ice ◽  
Satellite Observations ◽  
Polar Regions ◽  
Antarctic Sea Ice ◽  
Arctic Sea ◽  
Big Picture ◽  
Assimilation Model

<p>Polar Regions are viewed by many as "observational deserts", as in-situ measurements there are indeed scarce relative to other regions. The increasing availability of satellite observations does not entirely solve the problem, due to persistent uncertainties in the derived products. Climate models have been instrumental in completing the big picture, but they are themselves subject to errors, some of which are systematic. How to take advantage of the respective strengths of observations and models, while minimizing their respective weaknesses?  To illustrate this point, I will discuss how recent advances in data assimilation, model evaluation, and numerical modeling have enabled progress on addressing important questions in polar research, such as: what are the causes of the recent Antarctic sea ice variability? What might the future of Arctic sea ice look like? How to improve the skill of seasonal sea ice predictions? How should the existing observational network be improved at high latitudes? What are the priorities in terms of modeling? By running through these cases, I will provide support for the emerging hypothesis that "the whole is greater than the sum of its parts": treating observations and climate models as two noisy instances of the same, unknown truth, gives access to answers that would not have been possible using each source separately.</p>

scholarly journals Comparing and contrasting the behaviour of Arctic and Antarctic sea ice over the 35 year period 1979-2013

2015 ◽  
Vol 56 (69) ◽  
pp. 18-28 ◽  
Author(s):  
Ian Simmonds
Keyword(s):  
Sea Ice ◽  
Coupled Model ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Positive Trend ◽  
Polar Regions ◽  
Sea Ice Extent ◽  
Antarctic Sea Ice ◽  
Arctic Sea ◽  
The Antarctic

AbstractWe examine the evolution of sea-ice extent (SIE) over both polar regions for 35 years from November 1978 to December 2013, as well as for the global total ice (Arctic plus Antarctic). Our examination confirms the ongoing loss of Arctic sea ice, and we find significant (p˂ 0.001) negative trends in all months, seasons and in the annual mean. The greatest rate of decrease occurs in September, and corresponds to a loss of 3 x 106 km2 over 35 years. The Antarctic shows positive trends in all seasons and for the annual mean (p˂0.01), with summer attaining a reduced significance (p˂0.10). Based on our longer record (which includes the remarkable year 2013) the positive Antarctic ice trends can no longer be considered ‘small’, and the positive trend in the annual mean of (15.29 ± 3.85) x 103 km2 a–1 is almost one-third of the magnitude of the Arctic annual mean decrease. The global annual mean SIE series exhibits a trend of (–35.29 ± 5.75) x 103 km2 a-1 (p<0.01). Finally we offer some thoughts as to why the SIE trends in the Coupled Model Intercomparison Phase 5 (CMIP5) simulations differ from the observed Antarctic increases.

Making an informed use of observations and climate models to advance understanding of past and future sea ice changes

2020 ◽  
Author(s):  
François Massonnet
Keyword(s):  
Sea Ice ◽  
Climate Models ◽  
Arctic Sea Ice ◽  
Polar Regions ◽  
Antarctic Sea Ice ◽  
Arctic Sea ◽  
Big Picture ◽  
Assimilation Model ◽  
Major Progress

&lt;p&gt;Polar Regions are viewed by many as &quot;observational deserts&quot;, as in-situ measurements there are indeed scarce relative to other regions. The increasing availability of satellite observations is salutary but does not entirely solve the problem due to persistent uncertainties in the derived products. Climate models have been instrumental in completing the big picture. However, models are themselves subject to errors, some of which are systematic. How to take advantage of the respective strengths of observations and models, while minimizing their respective weaknesses? To illustrate this point, I will discuss how recent advances in data assimilation, model evaluation, and numerical modeling have enabled major progress in tackling important questions in polar research, such as: What are the causes of the recent Antarctic sea ice variability? What might the future of Arctic sea ice look like? How to improve the skill of seasonal sea ice predictions? How should the existing observational network be improved at high latitudes? What are the priorities in terms of sea ice modeling for climate change studies? By running through these cases, I will provide evidence for the emerging hypothesis that &quot;the whole is greater than the sum of its parts&quot;: treating observations and climate models as two noisy instances of the same, but unknown truth, gives insights that would not be possible if each source was used separately.&lt;/p&gt;

scholarly journals Ice Concentration Retrieval from the Analysis of Microwaves: A New Methodology Designed for the Copernicus Imaging Microwave Radiometer

2020 ◽  
Vol 12 (7) ◽  
pp. 1060 ◽  
Author(s):  
Lise Kilic ◽  
Catherine Prigent ◽  
Filipe Aires ◽  
Georg Heygster ◽  
Victor Pellet ◽  
...  
Keyword(s):  
Sea Ice ◽  
Spatial Resolution ◽  
Microwave Radiometer ◽  
Optimal Estimation ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Special Focus ◽  
Polar Regions ◽  
Sea Ice Concentration ◽  
Ice Concentration

Over the last 25 years, the Arctic sea ice has seen its extent decline dramatically. Passive microwave observations, with their ability to penetrate clouds and their independency to sunlight, have been used to provide sea ice concentration (SIC) measurements since the 1970s. The Copernicus Imaging Microwave Radiometer (CIMR) is a high priority candidate mission within the European Copernicus Expansion program, with a special focus on the observation of the polar regions. It will observe at 6.9 and 10.65 GHz with 15 km spatial resolution, and at 18.7 and 36.5 GHz with 5 km spatial resolution. SIC algorithms are based on empirical methods, using the difference in radiometric signatures between the ocean and sea ice. Up to now, the existing algorithms have been limited in the number of channels they use. In this study, we proposed a new SIC algorithm called Ice Concentration REtrieval from the Analysis of Microwaves (IceCREAM). It can accommodate a large range of channels, and it is based on the optimal estimation. Linear relationships between the satellite measurements and the SIC are derived from the Round Robin Data Package of the sea ice Climate Change Initiative. The 6 and 10 GHz channels are very sensitive to the sea ice presence, whereas the 18 and 36 GHz channels have a better spatial resolution. A data fusion method is proposed to combine these two estimations. Therefore, IceCREAM will provide SIC estimates with the good accuracy of the 6+10GHz combination, and the high spatial resolution of the 18+36GHz combination.

scholarly journals Brief communication: lack of agreement in remote sensing detection of cyclonic drift caused by Atlantic weather in Antarctic sea ice

2021 ◽  
Author(s):  
Wayne de Jager ◽  
Marcello Vichi
Keyword(s):  
Remote Sensing ◽  
Sea Ice ◽  
Alternative Methods ◽  
Polar Regions ◽  
Sea Ice Concentration ◽  
Sea Ice Extent ◽  
Ice Dynamics ◽  
Antarctic Sea Ice ◽  
Ice Drift ◽  
The Impact

Abstract. Sea-ice extent variability, a measure based on satellite-derived sea ice concentration measurements, has traditionally been used as an essential climate variable to evaluate the impact of climate change on polar regions. However, concentration- based measurements of ice variability do not allow to discriminate the relative contributions made by thermodynamic and dynamic processes, prompting the need to use sea-ice drift products and develop alternative methods to quantify changes in sea ice dynamics that would indicate trends in Antarctic ice characteristics. Here, we present a new method to automate the detection of rotational drift features in Antarctic sea ice at daily timescales using currently available remote sensing ice motion products from EUMETSAT OSI SAF. Results show that there is a large discrepancy in the detection of cyclonic drift features between products, both in terms of intensity and year-to-year distributions, thus diminishing the confidence at which ice drift variability can be further analysed. Product comparisons showed that there was good agreement in detecting anticyclonic drift, and cyclonic drift features were measured to be 1.5–2.2 times more intense than anticyclonic features. The most intense features were detected by the merged product, suggesting that the processing chain used for this product could be injecting additional rotational momentum into the resultant drift vectors. We conclude that it is therefore necessary to better understand why the products lack agreement before further trend analysis of these drift features and their climatic significance can be assessed.

scholarly journals The importance of diurnal processes for the Seasonal cycle of Sea-ice microwave brightness temperatures during early Summer in the Weddell Sea, Antarctica

2006 ◽  
Vol 44 ◽  
pp. 297-302 ◽  
Author(s):  
Sascha Willmes ◽  
Jörg Bareiss ◽  
Christian Haas ◽  
Marcel Nicolaus
Keyword(s):  
Sea Ice ◽  
Seasonal Cycle ◽  
Meteorological Data ◽  
Austral Summer ◽  
Early Summer ◽  
Arctic Sea Ice ◽  
Weddell Sea ◽  
Brightness Temperatures ◽  
Antarctic Sea Ice ◽  
Dominant Feature

AbstractOver the perennial Sea ice in the western and central Weddell Sea, Antarctica, the onset of Summer is accompanied by a Significant decrease of Sea-ice brightness temperatures (Tb) as observed by passive-microwave radiometers Such as the Special Sensor Microwave/Imager (SSM/I). The Summer-specific Tb drop is the dominant feature in the seasonal cycle of Tb data and represents a conspicuous difference to most Arctic Sea-ice regions, where the onset of Summer is mostly marked by a rise in Tb. Data from a 5 week drift Station through the western Weddell Sea in the 2004/05 austral Summer, Ice Station POLarstern (IsPOL), helped with identifying the characteristic processes for Antarctic Sea ice. In Situ glaciological and meteorological data, in combination with SSM/I Swath Satellite data, indicate that the cycle of repeated diurnal thawing and refreezing of Snow (‘freeze–thaw cycles’) is the dominant process in the Summer Season, with the absence of complete Snow wetting. The resulting metamorphous Snow with increased grain Size, as well as the formation of ice layers, leads to decreasing emissivity, enhanced volume Scattering and increased backscatter. This causes the Summer Tb drop.

scholarly journals The Arctic and Antarctic Sea-Ice Area Index Records versus Measured and Modeled Temperature Data

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Nicola Scafetta ◽  
Adriano Mazzarella
Keyword(s):  
Sea Ice ◽  
General Circulation ◽  
General Circulation Models ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Climate Indices ◽  
Area Index ◽  
Antarctic Sea Ice ◽  
Arctic Sea ◽  
The Antarctic

Here we study the Arctic and Antarctic sea-ice area records provided by the National Snow and Ice Data Center (NSIDC). These records reveal an opposite climatic behavior: since 1978 the Arctic sea-ice area index decreased, that is, the region has warmed, while the Antarctic sea-ice area index increased, that is, the region has cooled. During the last 7 years the Arctic sea-ice area has stabilized while the Antarctic sea-ice area has increased at a rate significantly higher than during the previous decades; that is, the sea-ice area of both regions has experienced a positive acceleration. This result is quite robust because it is confirmed by alternative temperature climate indices of the same regions. We also found that a significant 4-5-year natural oscillation characterizes the climate of these sea-ice polar areas. On the contrary, we found that the CMIP5 general circulation models have predicted significant warming in both polar sea regions and failed to reproduce the strong 4-5-year oscillation. Because the CMIP5 GCM simulations are inconsistent with the observations, we suggest that important natural mechanisms of climate change are missing in the models.

scholarly journals Sterol identification in floating Arctic sea ice algal aggregates and the Antarctic sea ice diatom Berkeleya adeliensis

2018 ◽  
Vol 118 ◽  
pp. 1-3 ◽  
Author(s):  
Simon T. Belt ◽  
Thomas A. Brown ◽  
Lukas Smik ◽  
Philipp Assmy ◽  
C.J. Mundy
Keyword(s):  
Sea Ice ◽  
Arctic Sea Ice ◽  
Antarctic Sea Ice ◽  
Arctic Sea ◽  
The Antarctic

scholarly journals Impact of sea ice on the marine iron cycle and phytoplankton productivity

2014 ◽  
Vol 11 (17) ◽  
pp. 4713-4731 ◽  
Author(s):  
S. Wang ◽  
D. Bailey ◽  
K. Lindsay ◽  
J. K. Moore ◽  
M. Holland
Keyword(s):  
Southern Ocean ◽  
Sea Ice ◽  
Ice Cover ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Phytoplankton Production ◽  
Iron Cycle ◽  
Surface Ocean ◽  
Antarctic Sea Ice ◽  
Iron Concentrations

Abstract. Iron is a key nutrient for phytoplankton growth in the surface ocean. At high latitudes, the iron cycle is closely related to the dynamics of sea ice. In recent decades, Arctic sea ice cover has been declining rapidly and Antarctic sea ice has exhibited large regional trends. A significant reduction of sea ice in both hemispheres is projected in future climate scenarios. In order to adequately study the effect of sea ice on the polar iron cycle, sea ice bearing iron was incorporated in the Community Earth System Model (CESM). Sea ice acts as a reservoir for iron during winter and releases the trace metal to the surface ocean in spring and summer. Simulated iron concentrations in sea ice generally agree with observations in regions where iron concentrations are relatively low. The maximum iron concentrations simulated in Arctic and Antarctic sea ice are much lower than observed, which is likely due to underestimation of iron inputs to sea ice or missing mechanisms. The largest iron source to sea ice is suspended sediments, contributing fluxes of iron of 2.2 × 108 mol Fe month−1 in the Arctic and 4.1 × 106 mol Fe month−1 in the Southern Ocean during summer. As a result of the iron flux from ice, iron concentrations increase significantly in the Arctic. Iron released from melting ice increases phytoplankton production in spring and summer and shifts phytoplankton community composition in the Southern Ocean. Results for the period of 1998 to 2007 indicate that a reduction of sea ice in the Southern Ocean will have a negative influence on phytoplankton production. Iron transport by sea ice appears to be an important process bringing iron to the central Arctic. The impact of ice to ocean iron fluxes on marine ecosystems is negligible in the current Arctic Ocean, as iron is not typically the growth-limiting nutrient. However, it may become a more important factor in the future, particularly in the central Arctic, as iron concentrations will decrease with declining sea ice cover and transport.

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