scholarly journals Pan-Arctic sea ice-algal chl a biomass and suitable habitat are largely underestimated for multiyear ice

2017 ◽  
Vol 23 (11) ◽  
pp. 4581-4597 ◽  
Author(s):  
Benjamin A. Lange ◽  
Hauke Flores ◽  
Christine Michel ◽  
Justin F. Beckers ◽  
Anne Bublitz ◽  
...  
Keyword(s):  
Sea Ice ◽  
Arctic Sea Ice ◽  
Suitable Habitat ◽  
Chl A ◽  
Arctic Sea ◽  
Multiyear Ice

scholarly journals Snow Depth Retrieval on Arctic Sea Ice From Passive Microwave Radiometers—Improvements and Extensions to Multiyear Ice Using Lower Frequencies

2018 ◽  
Vol 123 (10) ◽  
pp. 7120-7138 ◽  
Author(s):  
Philip Rostosky ◽  
Gunnar Spreen ◽  
Sinead L. Farrell ◽  
Torben Frost ◽  
Georg Heygster ◽  
...  
Keyword(s):  
Sea Ice ◽  
Snow Depth ◽  
Arctic Sea Ice ◽  
Passive Microwave ◽  
Arctic Sea ◽  
Microwave Radiometers ◽  
Multiyear Ice ◽  
Lower Frequencies

Controls on Arctic Sea Ice from First-Year and Multiyear Ice Survivability

2011 ◽  
Vol 24 (9) ◽  
pp. 2378-2390 ◽  
Author(s):  
Kyle C. Armour ◽  
Cecilia M. Bitz ◽  
LuAnne Thompson ◽  
Elizabeth C. Hunke
Keyword(s):  
Sea Ice ◽  
Ice Cover ◽  
Arctic Sea Ice ◽  
Global Climate Models ◽  
Climate Forcing ◽  
Reduced Model ◽  
First Year ◽  
Arctic Sea ◽  
Multiyear Ice ◽  
Area And Volume

Abstract Recent observations of Arctic sea ice show that the decrease in summer ice cover over the last few decades has occurred in conjunction with a significant loss of multiyear ice. The transition to an Arctic that is populated by thinner, first-year sea ice has important implications for future trends in area and volume. Here, a reduced model for Arctic sea ice is developed. This model is used to investigate how the survivability of first-year and multiyear ice controls the mean state, variability, and trends in ice area and volume. A hindcast with a global dynamic–thermodynamic sea ice model that traces first-year and multiyear ice is used to estimate the survivability of each ice type. These estimates of survivability, in concert with the reduced model, yield persistence time scales of September area and volume anomalies and the characteristics of the sensitivity of sea ice to climate forcing that compare well with a fully coupled climate model. The September area is found to be nearly in equilibrium with climate forcing at all times, and therefore the observed decline in summer sea ice cover is a clear indication of a changing climate. Keeping an account of first-year and multiyear ice area within global climate models offers a powerful way to evaluate those models with observations, and could help to constrain projections of sea ice decline in a warming climate.

scholarly journals On the 2011 record low Arctic sea ice thickness: a combination of dynamic and thermodynamic anomalies

2021 ◽  
Author(s):  
Xuewei Li ◽  
Qinghua Yang ◽  
Lejiang Yu ◽  
Paul R. Holland ◽  
Chao Min ◽  
...  
Keyword(s):  
Surface Energy ◽  
Sea Ice ◽  
Reanalysis Data ◽  
Arctic Sea Ice ◽  
Ice Thickness ◽  
Sea Ice Thickness ◽  
Ice Melt ◽  
Arctic Sea ◽  
Arctic Sea Ice Thickness ◽  
Multiyear Ice

Abstract. The sea ice thickness is recognized as an early indicator of climate changes. The mean Arctic sea ice thickness has been declining for the past four decades, and a sea ice thickness record minimum is confirmed occurring in autumn 2011. We used a daily sea ice thickness reanalysis data covering the melting season to investigate the dynamic and thermodynamic processes leading to the minimum thickness. Ice thickness budget analysis demonstrates that the ice thickness loss is associated with an extraordinarily large amount of multiyear ice volume export through the Fram Strait during the season of sea ice advance. Due to the loss of multiyear ice, the Arctic ice thickness becomes more sensitive to atmospheric anomalies. The positive net surface energy flux anomalies melt roughly 0.22 m of ice more than usual from June to August. An analysis of clouds and radiative fluxes from ERA5 reanalysis data reveals that the increased net surface energy absorption supports the enhanced sea ice melt. The enhanced cloudiness led to positive anomalies of net long-wave radiation. Furthermore, the enhanced sea ice melt reduces the surface albedo, triggering an ice–albedo amplifying feedback and contributing to the accelerating loss of multiyear ice. The results demonstrate that the dynamic transport of multiyear ice and the subsequent surface energy budget response is a critical mechanism actively contributing to the evolution of Arctic sea ice thickness.

scholarly journals Sub-kilometre scale distribution of snow depth on Arctic sea ice from Soviet drifting stations

2021 ◽  
Author(s):  
Robbie Mallett ◽  
Julienne Stroeve ◽  
Michel Tsamados ◽  
Rosemary Willatt ◽  
Thomas Newman ◽  
...  
Keyword(s):  
Sea Ice ◽  
Snow Depth ◽  
Arctic Sea Ice ◽  
First Year ◽  
Sea Ice Thickness ◽  
Arctic Sea ◽  
Ice Field ◽  
The Mean ◽  
Ice Impacts ◽  
Multiyear Ice

The sub-kilometre scale distribution of snow depth on Arctic sea ice impacts atmosphere-ice fluxes of heat and light, and is of importance for satellite estimates of sea ice thickness from both radar and lidar altimeters. While information about the mean of this distribution is increasingly available from modelling and remote sensing, the full distribution cannot yet be resolved. We analyse 33539 snow depth measurements from 499 transects taken at Soviet drifting stations between 1955 and 1991 and derive a simple statistical distribution for snow depth over multi-year ice as a function of only the mean snow depth. We then evaluate this snow depth distribution against snow depth transects that span first-year ice to multiyear ice from the MOSAiC, SHEBA and AMSR-Ice field campaigns. Because the distribution can be generated using only the mean snow depth, it can be used in the downscaling of several existing snow depth products for use in flux modelling and altimetry studies.

scholarly journals Observations of Sea Ice Melt from Operation IceBridge Imagery

2019 ◽  
Author(s):  
Nicholas C. Wright ◽  
Chris M. Polashenski ◽  
Scott T. McMichael ◽  
Ross A. Beyer
Keyword(s):  
Sea Ice ◽  
Arctic Sea Ice ◽  
First Year ◽  
Ice Melt ◽  
Melt Pond ◽  
Ice Surface ◽  
Optical Images ◽  
Arctic Sea ◽  
Ice Floes ◽  
Multiyear Ice

Abstract. The summer albedo of Arctic sea ice is heavily dependent on the fraction and color of melt ponds that form on the ice surface. This work presents a new dataset of sea ice surface fractions along Operation IceBridge (OIB) flight tracks derived from the Digital Mapping System optical imagery set. This dataset was created by deploying version 2 of the Open Source Sea-ice Processing (OSSP) algorithm to NASA’s Advanced Supercomputing Pleiades System. These new surface fraction results are then analyzed to investigate the behavior of meltwater on first-year ice in comparison to multiyear ice. Observations herein show that first-year ice does not ubiquitously have a higher melt pond fraction than multiyear ice under the same forcing conditions, contrary to established knowledge in the sea ice community. We discover and document a larger possible spread of pond fractions on first year ice leading to both high and low pond coverage, in contrast to the uniform melt evolution that has been previously observed on multiyear ice floes. We also present a selection of optical images that captures both the typical and atypical ice types, as observed from the OIB dataset. We hope to demonstrate the power of this new dataset and to encourage future collaborative efforts to utilize the OIB data to explore the behavior of melt pond formation Arctic sea ice.

scholarly journals Variability of Arctic Sea Ice (1979–2016)

Water ◽  
2018 ◽  
Vol 11 (1) ◽  
pp. 23 ◽  
Author(s):  
Zhankai Wu ◽  
Xingdong Wang
Keyword(s):  
Sea Ice ◽  
Data Center ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
First Year ◽  
Concentration Data ◽  
Sea Ice Concentration ◽  
Arctic Sea ◽  
Ice Concentration ◽  
Multiyear Ice

This study is based on the daily sea ice concentration data from the National Snow and Ice Data Center (NSIDC; Cooperative Institute for Research in Environmental Sciences (CIRES), Boulder, CO, USA) from 1979 to 2016. The Arctic sea ice is analyzed from the total sea ice area, first year ice extent, multiyear ice area, and the variability of sea ice concentration in different ranges. The results show that the total sea ice area decreased by 0.0453 × 106 km2·year−1 (−0.55%/year) between 1979 and 2016, and the variability of the sea ice area from 1997 to 2016 is significantly larger than that from 1979 to 1996. The first-year ice extent increased by 0.0199 × 106 km2·year−1 (0.36%/year) from 1997 to 2016. The multiyear ice area decreased by 0.0711 × 106 km2·year−1 (−0.66%/year) from 1979 to 2016, of which in the last 20 years is about 30.8% less than in 1979–1996. In terms of concentration, we have focused on comparing 1979–1996 and 1997–2016 in different ranges. Sea ice concentration between 0.9–1 accounted for about 39.57% from 1979 to 1996, while from 1997–2016, it accounted for only 27.75%. However, the sea ice of concentration between 0.15–0.4 exhibits no significant trend changes.

scholarly journals Observations of sea ice melt from Operation IceBridge imagery

2020 ◽  
Vol 14 (10) ◽  
pp. 3523-3536
Author(s):  
Nicholas C. Wright ◽  
Chris M. Polashenski ◽  
Scott T. McMichael ◽  
Ross A. Beyer
Keyword(s):  
Sea Ice ◽  
Arctic Sea Ice ◽  
First Year ◽  
Ice Melt ◽  
Melt Pond ◽  
Ice Surface ◽  
Optical Images ◽  
Arctic Sea ◽  
Ice Floes ◽  
Multiyear Ice

Abstract. The summer albedo of Arctic sea ice is heavily dependent on the fraction and color of melt ponds that form on the ice surface. This work presents a new dataset of sea ice surface fractions along Operation IceBridge (OIB) flight tracks derived from the Digital Mapping System optical imagery set. This dataset was created by deploying version 2 of the Open Source Sea-ice Processing (OSSP) algorithm to NASA's Advanced Supercomputing Pleiades System. These new surface fraction results are then analyzed to investigate the behavior of meltwater on first-year ice in comparison to multiyear ice. Observations herein show that first-year ice does not ubiquitously have a higher melt pond fraction than multiyear ice under the same forcing conditions, contrary to established knowledge in the sea ice community. We discover and document a larger possible spread of pond fractions on first-year ice leading to both high and low pond coverage, in contrast to the uniform melt evolution that has been previously observed on multiyear ice floes. We also present a selection of optical images that capture both the typical and atypical ice types, as observed from the OIB dataset. The derived OIB data presented here will be key to explore the behavior of melt pond formation Arctic sea ice.

scholarly journals Phytoplankton and dimethylsulfide dynamics at two contrasting Arctic ice edges

2020 ◽  
Vol 17 (6) ◽  
pp. 1557-1581 ◽  
Author(s):  
Martine Lizotte ◽  
Maurice Levasseur ◽  
Virginie Galindo ◽  
Margaux Gourdal ◽  
Michel Gosselin ◽  
...  
Keyword(s):  
Sea Ice ◽  
Surface Waters ◽  
Arctic Sea Ice ◽  
The Arctic ◽  
Chl A ◽  
Melt Pond ◽  
Nares Strait ◽  
Arctic Sea ◽  
Ice Edge ◽  
Methylated Sulfur Compounds

Abstract. Arctic sea ice is retreating and thinning and its rate of decline has steepened in the last decades. While phytoplankton blooms are known to seasonally propagate along the ice edge as it recedes from spring to summer, the substitution of thick multiyear ice (MYI) with thinner, ponded first-year ice (FYI) represents an unequal exchange when considering the roles sea ice plays in the ecology and climate of the Arctic. Consequences of this shifting sea ice on the phenology of phytoplankton and the associated cycling of the climate-relevant gas dimethylsulfide (DMS) and its precursor dimethylsulfoniopropionate (DMSP) remain ill constrained. In July–August 2014, two contrasting ice edges in the Canadian High Arctic were explored: a FYI-dominated ice edge in Barrow Strait and a MYI-dominated ice edge in Nares Strait. Our results reveal two distinct planktonic systems and associated DMS dynamics in connection to these diverging ice types. The surface waters exiting the ponded FYI in Barrow Strait were characterized by moderate chlorophyll a (Chl a, <2.1 µg L−1) as well as high DMSP (115 nmol L−1) and DMS (12 nmol L−1), suggesting that a bloom had already started to develop under the markedly melt-pond-covered (ca. 40 %) FYI. Heightened DMS concentrations at the FYI edge were strongly related to ice-associated seeding of DMS in surface waters and haline-driven stratification linked to ice melt (Spearman's rank correlation between DMS and salinity, rs=-0.91, p<0.001, n=20). However, surface waters exiting the MYI edge at the head of Nares Strait were characterized by low concentrations of Chl a (<0.5 µg L−1), DMSP (<16 nmol L−1), and DMS (<0.4 nmol L−1), despite the nutrient-replete conditions characterizing the surface waters. The increase in autotrophic biomass and methylated sulfur compounds took place several kilometers (ca. 100 km) away from the MYI edge, suggesting the requisite for ice-free, light-sufficient conditions for a phytoplankton bloom to fully develop and for sulfur compound dynamics to follow and expand. In light of the ongoing and projected climate-driven changes to Arctic sea ice, results from this study suggest that the early onset of autotrophic blooms under thinner, melt-pond-covered ice may have vast implications for the timing and magnitude of DMS pulses in the Arctic.

scholarly journals Effects of Stochastic Ice Strength Perturbation on Arctic Finite Element Sea Ice Modeling

2013 ◽  
Vol 26 (11) ◽  
pp. 3785-3802 ◽  
Author(s):  
Stephan Juricke ◽  
Peter Lemke ◽  
Ralph Timmermann ◽  
Thomas Rackow
Keyword(s):  
Finite Element ◽  
Markov Chain ◽  
Sea Ice ◽  
Spatial Correlation ◽  
Time Correlation ◽  
Arctic Sea Ice ◽  
Ice Volume ◽  
Arctic Sea ◽  
Ice Strength ◽  
Multiyear Ice

Abstract The ice strength parameter P* is a key parameter in dynamic/thermodynamic sea ice models that cannot be measured directly. Stochastically perturbing P* in the Finite Element Sea Ice–Ocean Model (FESOM) of the Alfred Wegener Institute aims at investigating the effect of uncertainty pertaining to this parameterization. Three different approaches using symmetric perturbations have been applied: 1) reassignment of uncorrelated noise fields to perturb P* at every grid point, 2) a Markov chain time correlation, and 3) a Markov chain time correlation with some spatial correlation between nodes. Despite symmetric perturbations, results show an increase of Arctic sea ice volume and a decrease of Arctic sea ice area for all three approaches. In particular, the introduction of spatial correlation leads to a substantial increase in sea ice volume and mean thickness. The strongest response can be seen for multiyear ice north of the Greenland coast. An ensemble of eight perturbed simulations generates a spread in the multiyear ice comparable to the interannual variability of the model. Results cannot be reproduced by a simple constant global modification of P*.

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