scholarly journals The impact of variable sea ice roughness on changes in A rctic O cean surface stress: A model study

2016 ◽  
Vol 121 (3) ◽  
pp. 1931-1952 ◽  
Author(s):  
Torge Martin ◽  
Michel Tsamados ◽  
David Schroeder ◽  
Daniel L. Feltham
1997 ◽  
Vol 25 ◽  
pp. 111-115 ◽  
Author(s):  
Achim Stössel

This paper investigates the long-term impact of sea ice on global climate using a global sea-ice–ocean general circulation model (OGCM). The sea-ice component involves state-of-the-art dynamics; the ocean component consists of a 3.5° × 3.5° × 11 layer primitive-equation model. Depending on the physical description of sea ice, significant changes are detected in the convective activity, in the hydrographic properties and in the thermohaline circulation of the ocean model. Most of these changes originate in the Southern Ocean, emphasizing the crucial role of sea ice in this marginally stably stratified region of the world's oceans. Specifically, if the effect of brine release is neglected, the deep layers of the Southern Ocean warm up considerably; this is associated with a weakening of the Southern Hemisphere overturning cell. The removal of the commonly used “salinity enhancement” leads to a similar effect. The deep-ocean salinity is almost unaffected in both experiments. Introducing explicit new-ice thickness growth in partially ice-covered gridcells leads to a substantial increase in convective activity, especially in the Southern Ocean, with a concomitant significant cooling and salinification of the deep ocean. Possible mechanisms for the resulting interactions between sea-ice processes and deep-ocean characteristics are suggested.


2021 ◽  
Author(s):  
Zhaomin Ding ◽  
Renguang Wu

AbstractThis study investigates the impact of sea ice and snow changes on surface air temperature (SAT) trends on the multidecadal time scale over the mid- and high-latitudes of Eurasia during boreal autumn, winter and spring based on a 30-member ensemble simulations of the Community Earth System Model (CESM). A dynamical adjustment method is used to remove the internal component of circulation-induced SAT trends. The leading mode of dynamically adjusted SAT trends is featured by same-sign anomalies extending from northern Europe to central Siberia and to the Russian Far East, respectively, during boreal spring and autumn, and confined to western Siberia during winter. The internally generated component of sea ice concentration trends over the Barents-Kara Seas contributes to the differences in the thermodynamic component of internal SAT trends across the ensemble over adjacent northern Siberia during all the three seasons. The sea ice effect is largest in autumn and smallest in winter. Eurasian snow changes contribute to the spread in dynamically adjusted SAT trends as well around the periphery of snow covered region by modulating surface heat flux changes. The snow effect is identified over northeast Europe-western Siberia in autumn, north of the Caspian Sea in winter, and over eastern Europe-northern Siberia in spring. The effects of sea ice and snow on the SAT trends are realized mainly by modulating upward shortwave and longwave radiation fluxes.


2010 ◽  
Vol 7 (12) ◽  
pp. 3941-3959 ◽  
Author(s):  
I. Marinov ◽  
S. C. Doney ◽  
I. D. Lima

Abstract. The response of ocean phytoplankton community structure to climate change depends, among other factors, upon species competition for nutrients and light, as well as the increase in surface ocean temperature. We propose an analytical framework linking changes in nutrients, temperature and light with changes in phytoplankton growth rates, and we assess our theoretical considerations against model projections (1980–2100) from a global Earth System model. Our proposed "critical nutrient hypothesis" stipulates the existence of a critical nutrient threshold below (above) which a nutrient change will affect small phytoplankton biomass more (less) than diatom biomass, i.e. the phytoplankton with lower half-saturation coefficient K are influenced more strongly in low nutrient environments. This nutrient threshold broadly corresponds to 45° S and 45° N, poleward of which high vertical mixing and inefficient biology maintain higher surface nutrient concentrations and equatorward of which reduced vertical mixing and more efficient biology maintain lower surface nutrients. In the 45° S–45° N low nutrient region, decreases in limiting nutrients – associated with increased stratification under climate change – are predicted analytically to decrease more strongly the specific growth of small phytoplankton than the growth of diatoms. In high latitudes, the impact of nutrient decrease on phytoplankton biomass is more significant for diatoms than small phytoplankton, and contributes to diatom declines in the northern marginal sea ice and subpolar biomes. In the context of our model, climate driven increases in surface temperature and changes in light are predicted to have a stronger impact on small phytoplankton than on diatom biomass in all ocean domains. Our analytical predictions explain reasonably well the shifts in community structure under a modeled climate-warming scenario. Climate driven changes in nutrients, temperature and light have regionally varying and sometimes counterbalancing impacts on phytoplankton biomass and structure, with nutrients and temperature dominant in the 45° S–45° N band and light-temperature effects dominant in the marginal sea-ice and subpolar regions. As predicted, decreases in nutrients inside the 45° S–45° N "critical nutrient" band result in diatom biomass decreasing more than small phytoplankton biomass. Further stratification from global warming could result in geographical shifts in the "critical nutrient" threshold and additional changes in ecology.


2015 ◽  
Vol 56 (69) ◽  
pp. 383-393 ◽  
Author(s):  
E. Rachel Bernstein ◽  
Cathleen A. Geiger ◽  
Tracy L. Deliberty ◽  
Mary D. Lemcke-Stampone

AbstractThis work evaluates two distinct calculations of central tendency for sea-ice thickness and quantifies the impact such calculations have on ice volume for the Southern Ocean. The first calculation, area-weighted average thickness, is computed from polygonal ice features and then upscaled to regions. The second calculation, integrated thickness, is a measure of the central value of thickness categories tracked across different scales and subsequently summed to chosen regions. Both methods yield the same result from one scale to the next, but subsequent scales develop diverging solutions when distributions are strongly non-Gaussian. Data for this evaluation are sea-ice stage-of-development records from US National Ice Center ice charts from 1995 to 1998, as proxy records of ice thickness. Results show regionally integrated thickness exceeds area-weighted average thickness by as much as 60% in summer with as few as five bins in thickness distribution. Year-round, the difference between the two calculations yields volume differences consistently >10%. The largest discrepancies arise due to bimodal distributions which are common in ice charts based on current subjective-analysis protocols. We recommend that integrated distribution be used for regional-scale sea-ice thickness and volume estimates from ice charts and encourage similar testing of other large-scale thickness data archives.


2016 ◽  
Vol 141 ◽  
pp. 153-167 ◽  
Author(s):  
J. Zhou ◽  
M. Kotovitch ◽  
H. Kaartokallio ◽  
S. Moreau ◽  
J.-L. Tison ◽  
...  

2021 ◽  
Author(s):  
Isolde Glissenaar ◽  
Jack Landy ◽  
Alek Petty ◽  
Nathan Kurtz ◽  
Julienne Stroeve

<p>The ice cover of the Arctic Ocean is increasingly becoming dominated by seasonal sea ice. It is important to focus on the processing of altimetry ice thickness data in thinner seasonal ice regions to understand seasonal sea ice behaviour better. This study focusses on Baffin Bay as a region of interest to study seasonal ice behaviour.</p><p>We aim to reconcile the spring sea ice thickness derived from multiple satellite altimetry sensors and sea ice charts in Baffin Bay and produce a robust long-term record (2003-2020) for analysing trends in sea ice thickness. We investigate the impact of choosing different snow depth products (the Warren climatology, a passive microwave snow depth product and modelled snow depth from reanalysis data) and snow redistribution methods (a sigmoidal function and an empirical piecewise function) to retrieve sea ice thickness from satellite altimetry sea ice freeboard data.</p><p>The choice of snow depth product and redistribution method results in an uncertainty envelope around the March mean sea ice thickness in Baffin Bay of 10%. Moreover, the sea ice thickness trend ranges from -15 cm/dec to 20 cm/dec depending on the applied snow depth product and redistribution method. Previous studies have shown a possible long-term asymmetrical trend in sea ice thinning in Baffin Bay. The present study shows that whether a significant long-term asymmetrical trend was found depends on the choice of snow depth product and redistribution method. The satellite altimetry sea ice thickness results with different snow depth products and snow redistribution methods show that different processing techniques can lead to different results and can influence conclusions on total and spatial sea ice thickness trends. Further processing work on the historic radar altimetry record is needed to create reliable sea ice thickness products in the marginal ice zone.</p>


2021 ◽  
Author(s):  
Dorsa Nasrollahi Shirazi ◽  
Michel Tsamados ◽  
Isobel Lawrence ◽  
Sanggyun Lee ◽  
Thomas Johnson ◽  
...  

<p>The Copernicus operational Sentinel-3A since February 2016 and Sentinel-3B since April 2018 build on the CryoSat-2 legacy in terms of their synthetic aperture radar (SAR) mode altimetry providing high-resolution radar freeboard elevation data over the polar regions up to 81N. This technology combined with the Ocean and Land Colour Instrument (OLCI) imaging spectrometer offers the first space-time collocated optical imagery and radar altimetry dataset. We use these joint datasets for validation of several existing surface classification algorithms based on Sentinel-3 altimeter echo shapes. We also explore the potential for novel AI techniques such as convolutional neural networks (CNN) for winter and summer sea ice surface classification (i.e. melt pond fraction, lead fraction, sea ice roughness). For lead surface classification we analyse the winters of 2018/19 and 2019/20 and for summer sea ice feature classification we focus on the Sentinel-3A &3B tandem phase of the summer 2018. We compare our CNN models with other existing surface classification algorithms.</p>


2021 ◽  
Vol 34 (10) ◽  
pp. 3799-3819
Author(s):  
Hyung-Gyu Lim ◽  
Jong-Yeon Park ◽  
John P. Dunne ◽  
Charles A. Stock ◽  
Sung-Ho Kang ◽  
...  

AbstractHuman activities such as fossil fuel combustion, land-use change, nitrogen (N) fertilizer use, emission of livestock, and waste excretion accelerate the transformation of reactive N and its impact on the marine environment. This study elucidates that anthropogenic N fluxes (ANFs) from atmospheric and river deposition exacerbate Arctic warming and sea ice loss via physical–biological feedback. The impact of physical–biological feedback is quantified through a suite of experiments using a coupled climate–ocean–biogeochemical model (GFDL-CM2.1-TOPAZ) by prescribing the preindustrial and contemporary amounts of riverine and atmospheric N fluxes into the Arctic Ocean. The experiment forced by ANFs represents the increase in ocean N inventory and chlorophyll concentrations in present and projected future Arctic Ocean relative to the experiment forced by preindustrial N flux inputs. The enhanced chlorophyll concentrations by ANFs reinforce shortwave attenuation in the upper ocean, generating additional warming in the Arctic Ocean. The strongest responses are simulated in the Eurasian shelf seas (Kara, Barents, and Laptev Seas; 65°–90°N, 20°–160°E) due to increased N fluxes, where the annual mean surface temperature increase by 12% and the annual mean sea ice concentration decrease by 17% relative to the future projection, forced by preindustrial N inputs.


2016 ◽  
Author(s):  
Johannes Bieser ◽  
Franz Slemr ◽  
Jesse Ambrose ◽  
Carl Brenninkmeijer ◽  
Steve Brooks ◽  
...  

Abstract. Atmospheric chemistry and transport of mercury play a key role in the global mercury cycle. However, there are still considerable knowledge gaps concerning the fate of mercury in the atmosphere. This is the second part of a model inter-comparison study investigating the impact of atmospheric chemistry and emissions on mercury in the atmosphere. While the first study focused on ground based observations of mercury concentration and deposition, here we investigate the vertical distribution and speciation of mercury from the planetary boundary layer to the lower stratosphere. So far, there have been few model studies investigating the vertical distribution of mercury, mostly focusing on single aircraft campaigns. Here, we present a first comprehensive analysis based on various aircraft observations in Europe, North America, and on inter-continental flights. The investigated models proved to be able to reproduce the distribution of total and elemental mercury concentrations in the troposphere including inter-hemispheric trends. One key aspect of the study is the investigation of mercury oxidation in the troposphere. We found that different chemistry schemes were better at reproducing observed oxidized mercury (RM) patterns depending on altitude. High RM concentrations in the upper troposphere could be reproduced with oxidation by bromine while elevated concentrations in the lower troposphere were better reproduced by OH and ozone chemistry. However, the results were not always conclusive as the physical and chemical parametrizations in the chemistry transport models also proved to have a substantial impact on model results.


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