Record low sea-ice concentration in the central Arctic during summer 2010

Zhao, Jinping; Barber, David G.; Zhang, Shugang; Yang, Qinghua; Wang, Xiaoyu; Xie, Hongjie

doi:10.1007/s00376-017-7066-6

Cited by 23 publications

(6 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The model sea ice extent during the summer of 2010, and more generally the distribution of the sea ice concentration, compares reasonably well with satellite observations (not shown. Note that this period includes a drop in sea ice concentration in the Central Arctic, found both in model results and in satellite observations, that has already been documented by Zhao et al (2018) and attributed to an enhancement of ice divergence in this region this particular year. This specific period has also been chosen as some storms occurred during it, so that extreme waves conditions can be investigated.…”

Section: Pan-arctic Configurationsupporting

confidence: 71%

See 1 more Smart Citation

Toward a coupled model to investigate wave-sea ice interactions in the Arctic marginal ice zone

Boutin¹,

Lique²,

Ardhuin³

et al. 2019

Preprint

View full text Add to dashboard Cite

Abstract. The Arctic Marginal Ice Zone (MIZ), where strong interactions between sea ice, ocean and atmosphere are taking place, is expanding as the result of the on-going sea ice retreat. Yet, state-of-art models are not capturing the complexity of the varied processes occurring in the MIZ, and in particular the processes involved in the ocean-sea ice interactions. In the present study, a coupled sea ice - wave model is developed, in order to improve our understanding and model representation of those interactions. The coupling allows us to account for the wave radiative stress resulting from the wave attenuation by sea ice, and the sea ice lateral melt resulting from the wave-induced sea ice break-up. We found that, locally in the MIZ, the waves can affect the sea ice drift and melt, resulting in significant changes in sea ice concentration and thickness as well as sea surface temperature and salinity. Our results highlight the need to include the wave-sea ice processes in models aiming at forecasting sea ice conditions on short time scale, although the coupling between waves and sea ice would probably required to be investigated in a more complex system, allowing for interactions with the ocean and the atmosphere.

show abstract

Section: Pan-arctic Configurationsupporting

confidence: 71%

“…where the value of lateral melt in the NOT_CPL run are small but positive. This is due to the drop in sea ice concentration that happens in the region in August 2010 (Zhao et al, 2018) (Fig. 6b).…”

Section: Thermodynamical Effect Of the Couplingmentioning

confidence: 98%

Toward a coupled model to investigate wave-sea ice interactions in the Arctic marginal ice zone

Boutin¹,

Lique²,

Ardhuin³

et al. 2019

Preprint

View full text Add to dashboard Cite

show abstract

“…The maximum (higher) values of sea ice concentration was reducing, while the minimum (lower) values of concentration were found to be increasing (Vázquez et al, 2016). The highest decreasing rates are mainly focused on the Beaufort, Chukchi, and East Siberian Seas (Chen & Zhao, 2017;Zhao et al, 2017). In the summer of 2010, there was a very low sea ice concentration (30%) that appeared at high Arctic latitudes, even lower than that of the surrounding pack of ice at lower latitudes (Cavalieri & Parkinson, 2012).…”

Section: Introductionmentioning

confidence: 95%

Analysis of sea ice concentration and thickness over Barents Sea using standard logistic curve model

Panicker

Vachharajani

Srivastava

et al. 2023

Journal of Geomatics

View full text Add to dashboard Cite

As marginal, the Barents Sea plays a major role in the process of Atlantification, and large seasonal variability in sea ice is observed over the region. Current sea ice concentration and thickness obtained from satellite help one understand the variation in sea ice is seasonal. During summer, the concentration and thickness of sea ice are seen to fall, and during winters, it is seen to rise. In order to understand the difference in these variabilities and to analyse the future state of sea ice, a standard logistic curve model is considered. The standard logistic curve model is applied to sea ice parameters during summer and winter to quantify the sea ice growth and decay processes over the Barents Sea.The model yields predicted values based on the adjustment parameter (b) used.Results show that the predicted sea ice concentration performs well with the satellite sea ice concentration values. The model is run on the timeframe grouped into two, with each set having an average of ten years from 2000-2020. For the decay process, the fitted sea ice concentration decay curves derived from the standard logistic curve model are in good agreement with the observed data for the two timelines, with r2 = 0.88 and 0.87, respectively. Similarly, for the growth process, the relevant fitted decay curves derived from the standard logistic curve model are also in good agreement with the observed data during the above different time periods withr2= 0.80 and 0.78, respectively. Further, the model is implied to sea ice thickness, and the result obtained by the logistic curve model is found to be consistent with the satellite sea ice thickness with r2 = 0.75 for the years 2011–2020. Particularly, both the rapid sea ice increase pattern during the growth process and the remarkable decrease pattern during the decay process are successfully characterized by the corresponding fitted curves. The introduction of calculated adjustment parameters into the model helps in accurately determining the sea ice variables, which brings us closer to conservation tools that mitigate therisks associated with rapid sea ice loss.

show abstract

“…The SIE declined significantly in the summer, followed by that in autumn, winter, and spring during the 1979-2013 period [16]. In the summer of 2010, there was a very low sea-ice concentration that appeared at high Arctic latitudes-even lower than that of surrounding pack of ice at lower latitudes [17].…”

Section: Introductionmentioning

confidence: 95%

Variability of Arctic Sea Ice (1979–2016)

Wang

2018

Water

View full text Add to dashboard Cite

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.

show abstract

Record low sea-ice concentration in the central Arctic during summer 2010

Cited by 23 publications

References 31 publications

Toward a coupled model to investigate wave-sea ice interactions in the Arctic marginal ice zone

Toward a coupled model to investigate wave-sea ice interactions in the Arctic marginal ice zone

Analysis of sea ice concentration and thickness over Barents Sea using standard logistic curve model

Variability of Arctic Sea Ice (1979–2016)

Contact Info

Product

Resources

About