scholarly journals Elevated mercury measured in snow and frost flowers near Arctic sea ice leads

2005 ◽  
Vol 32 (4) ◽  
pp. n/a-n/a ◽  
Author(s):  
T. A. Douglas ◽  
M. Sturm ◽  
W. R. Simpson ◽  
S. Brooks ◽  
S. E. Lindberg ◽  
...  
2018 ◽  
Vol 12 (12) ◽  
pp. 3747-3757 ◽  
Author(s):  
Yuanyuan Zhang ◽  
Xiao Cheng ◽  
Jiping Liu ◽  
Fengming Hui

Abstract. The Arctic sea ice extent throughout the melt season is closely associated with initial sea ice state in winter and spring. Sea ice leads are important sites of energy fluxes in the Arctic Ocean, which may play an important role in the evolution of Arctic sea ice. In this study, we examine the potential of sea ice leads as a predictor for summer Arctic sea ice extent forecast using a recently developed daily sea ice lead product retrieved from the Moderate-Resolution Imaging Spectroradiometer (MODIS). Our results show that July pan-Arctic sea ice extent can be predicted from the area of sea ice leads integrated from midwinter to late spring, with a prediction error of 0.28 million km2 that is smaller than the standard deviation of the observed interannual variability. However, the predictive skills for August and September pan-Arctic sea ice extent are very low. When the area of sea ice leads integrated in the Atlantic and central and west Siberian sector of the Arctic is used, it has a significantly strong relationship (high predictability) with both July and August sea ice extent in the Atlantic and central and west Siberian sector of the Arctic. Thus, the realistic representation of sea ice leads (e.g., the areal coverage) in numerical prediction systems might improve the skill of forecast in the Arctic region.


2018 ◽  
Author(s):  
Yuanyuan Zhang ◽  
Xiao Cheng ◽  
Jiping Liu ◽  
Fengming Hui

Abstract. The Arctic sea ice extent throughout the melt season is closely associated with initial sea ice state in winter and spring. Sea ice leads are important sites of energy fluxes in the Arctic Ocean, which may play an important role in the evolution of Arctic sea ice. In this study, we examine the potential of sea ice leads as a predictor for seasonal Arctic sea ice extent forecast using a recently developed daily sea ice leads product retrieved from Moderate-Resolution Imaging Spectroradiometer. Our results show that July pan-Arctic sea ice extent can be accurately predicted from the area of sea ice leads integrated from mid-winter to late spring. However, the predictive skills for August and September pan-Arctic sea ice extent are very low. When the area of sea ice leads integrated in the Atlantic and central and west Siberian sector of the Arctic is used, it has a significantly strong relationship (high predictability) with both July and August sea ice extent in the Atlantic and central and west Siberian sector of the Arctic. Thus, the realistic representation of sea ice leads (e.g., the areal coverage) in numerical prediction systems might improve the skill of forecast in the Arctic region.


2019 ◽  
Author(s):  
Damiano Della Lunga ◽  
Hörhold Maria ◽  
Birthe Twarloh ◽  
Behrens Melanie ◽  
Dallmayr Remi ◽  
...  

Abstract. Sea ice is a key component of the climate system, since it modifies the surface albedo, the radiation balance, as well as the exchange of heat, moisture and gases between the ocean and the overlying atmosphere. Hence, the reconstruction of sea ice cover before the instrumental era and the industrial times is crucial to understand the evolution of Arctic climate in the last millennium and better predict its future evolution. However, identifying relevant paleo proxies in climate archives related to sea ice cover is not straightforward. Ice cores from polar regions offer great potential to provide high-resolution records of Arctic sea ice variability from chemical impurities such as Bromine species, which were recently proposed as indicators of sea ice extent, although their variability might be modulated by regional influences. We here use Bromine and Bromine enrichment of two ice cores form North Greenland (B17 & B26) and investigate its potential as proxy to reconstruct sea ice extent over the period 1363–1993 AD. Across the instrumental period, a good correlation is observed with the Baffin Bay and the Greenland Sea for B26 and B17 respectively, with both record showing minima corresponding to known Artic warming events such as the 1420 AD (for B17) and 1920–1940 (Early century warming, B17 & B26), together with a strong decline starting in the late 19th century. We simultaneously derived a chemical classification of sea ice-related contributors of ionic species (i.e. blowing snow, frost flowers, open water) utilizing the depletion of SO42− compare to Ca2+, K+ and Mg2+ characterizing sea ice brines and blowing snow as well the excess of Br− and Cl−, characterizing frost flowers, to elucidate the evolution of the different sources. In both B17 and B26 records we observe a strong contribution of blowing snow in the earliest part of the datasets, gradually declining in recent years in favour of open water sources.


2019 ◽  
Vol 11 (5) ◽  
pp. 521 ◽  
Author(s):  
Jay Hoffman ◽  
Steven Ackerman ◽  
Yinghui Liu ◽  
Jeffrey Key

Sea ice leads (fractures) play a critical role in the exchange of mass and energy between the ocean and atmosphere in the polar regions. The thinning of Arctic sea ice over the last few decades will likely result in changes in lead distributions, so monitoring their characteristics is increasingly important. Here we present a methodology to detect and characterize sea ice leads using satellite imager thermal infrared window channels. A thermal contrast method is first used to identify possible sea ice lead pixels, then a number of geometric and image analysis tests are applied to build a subset of positively identified leads. Finally, characteristics such as width, length and orientation are derived. This methodology is applied to Moderate Resolution Imaging Spectroradiometer (MODIS) observations for the months of January through April over the period of 2003 to 2018. The algorithm results are compared to other satellite estimates of lead distribution. Lead coverage maps and statistics over the Arctic illustrate spatial and temporal lead patterns.


2014 ◽  
Vol 119 (20) ◽  
pp. 11,593-11,612 ◽  
Author(s):  
D. G. Barber ◽  
J. K. Ehn ◽  
M. Pućko ◽  
S. Rysgaard ◽  
J. W. Deming ◽  
...  

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