Evidence of Arctic sea ice thinning from direct observations

Renner, Angelika; Gerland, Sebastian; Haas, Christian; Spreen, Gunnar; Beckers, Justin; Hansen, Edmond; Nicolaus, Marcel; Goodwin, Harvey

doi:10.1002/2014gl060369

Cited by 115 publications

(123 citation statements)

References 27 publications

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“…From 2006 to 2014, the central Arctic is governed by shear; since 2011 FTLE ridges in this region have been governed by both shear and divergence, in a manner consistent with faster drift and loss of MYI in the TDS (Kwok et al 2013) and a continued decline in TDS sea-ice thickness, as described in Renner et al (2014). Smallerscale, divergence-dominated FTLE ridges throughout the Arctic (Figs.…”

Section: Spatial Variability Of Shear and Divergencementioning

confidence: 63%

“…The absence of hyperbolic features may be due to the fact that at minimum a continuous two-year integration time frame is required to capture recirculation of sea ice in the BG, as demonstrated in recent back-trajectory analyses in observational sea-ice thickness studies by Renner et al (2014). Since summer data are not provided for the OSI SAF data set, only a six-month integration interval is available.…”

Section: Lad Shear and Hyperbolic Structuresmentioning

confidence: 99%

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Lagrangian analysis of sea-ice dynamics in the Arctic Ocean

2016

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Section: Spatial Variability Of Shear and Divergencementioning

confidence: 63%

Section: Lad Shear and Hyperbolic Structuresmentioning

confidence: 99%

Lagrangian analysis of sea-ice dynamics in the Arctic Ocean

2016

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“…However, the sea-ice age becomes younger by 0.6 years per decade (Krumpen et al, 2015), which goes along with a decrease in the sea-ice thickness (Renner et al, 2014;Krumpen et al, 2015). 20…”

Section: Study Area and Sample Preparationmentioning

confidence: 99%

Deep-sea benthic communities and oxygen fluxes in the Arctic Fram Strait controlled by sea-ice cover and water depth

Hoffmann¹,

Braeckman²,

Hasemann³

et al. 2018

Preprint

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Arctic Ocean surface sea-ice conditions are linked with the deep sea benthic oxygen fluxes via a cascade of dependencies across ecosystem components like primary production, food supply, the activity of the benthic community, and their functions. Additionally, each of the ecosystem components is influenced by abiotic factors like light availability, temperature, water depth or grain size structure. In this study, we investigated the coupling between surface sea-ice 5 conditions and deep-sea benthic remineralization processes through a cascade of dependencies in the Fram Strait. We measured sea-ice concentrations, nutrient profiles, different sediment compounds, benthic community parameters, and oxygen fluxes at 12 stations in the HAUSGARTEN area of the Fram Strait in water depth between 275-2500 m. Our investigations reveal that the Fram Strait is bisected in a permanently and highly sea-ice covered area and a seasonally and low sea-ice covered area, which both are long-lasting and stable. Within the Fram Strait ecosystem, sea-ice concentration 10 and water depth are two independent abiotic factors, controlling the deep-sea benthos. Sea-ice concentration correlates well with the available food, water depth with the oxygen flux, and both abiotic factors correlate with the macrofauna biomass.However, in water depths >1500 m the influence of the surface sea-ice cover fades out and water depth effect becomes more dominant. Remineralisation across the Fram Strait is ~ 1 mmol C m -²d -1 . Owing to the contrasting primary production pattern, our data indicate that the portion of newly produced carbon that is remineralised by the benthos is ~2.6 % in the 15 seasonally low sea-ice covered Fram Strait but can be >15 % in the permanently high sea-ice covered Fram Strait.Furthermore, by comparing a permanently sea-ice covered area with a seasonally sea-ice covered area, we discuss a potential scenario for the deep-sea benthic ecosystem in the future Arctic Ocean, in which an increased surface primary production can lead to increasing benthic remineralisation in water depths <1500 m. 20Biogeosciences Discuss., https://doi

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“…Kwok, 2009; Renner et al, 2014). The sea ice cover is therefore highly variable with both FYI and MYI and contains a large fraction of deformed ice.…”

Section: Study Sitementioning

confidence: 99%

“…Measurements of total snow plus sea ice thickness (from now on referred to as sea ice thickness) were performed with an electromagnetic induction sounder (EM-bird), which was towed underneath the helicopter and flown at a height of about 15 m above the surface. More details about the EMbird can be found in Haas et al (2009) and Renner et al (2013Renner et al ( , 2014. From this device, the difference in conductivity between sea ice and water is used to find the height of the EM-bird above the ice/water interface, and a laser altimeter integrated in the EM-bird detects the distance between the EM-bird and the snow/ice surface.…”

Section: Airborne Measurementsmentioning

confidence: 99%

Late-summer sea ice segmentation with multi-polarisation SAR features in C and X band

Fors¹,

Brekke²,

Doulgeris³

et al. 2016

The Cryosphere

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Abstract. In this study, we investigate the potential of sea ice segmentation by C-and X-band multi-polarisation synthetic aperture radar (SAR) features during late summer. Five highresolution satellite SAR scenes were recorded in the Fram Strait covering iceberg-fast first-year and old sea ice during a week with air temperatures varying around 0 • C. Sea ice thickness, surface roughness and aerial photographs were collected during a helicopter flight at the site. Six polarimetric SAR features were extracted for each of the scenes. The ability of the individual SAR features to discriminate between sea ice types and their temporal consistency were examined. All SAR features were found to add value to sea ice type discrimination. Relative kurtosis, geometric brightness, cross-polarisation ratio and co-polarisation correlation angle were found to be temporally consistent in the investigated period, while co-polarisation ratio and co-polarisation correlation magnitude were found to be temporally inconsistent. An automatic feature-based segmentation algorithm was tested both for a full SAR feature set and for a reduced SAR feature set limited to temporally consistent features. In C band, the algorithm produced a good late-summer sea ice segmentation, separating the scenes into segments that could be associated with different sea ice types in the next step. The X-band performance was slightly poorer. Excluding temporally inconsistent SAR features improved the segmentation in one of the X-band scenes.

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Evidence of Arctic sea ice thinning from direct observations

Cited by 115 publications

References 27 publications

Lagrangian analysis of sea-ice dynamics in the Arctic Ocean

Lagrangian analysis of sea-ice dynamics in the Arctic Ocean

Deep-sea benthic communities and oxygen fluxes in the Arctic Fram Strait controlled by sea-ice cover and water depth

Late-summer sea ice segmentation with multi-polarisation SAR features in C and X band

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