Sea ice remote sensing using AMSR‐E 89‐GHz channels

Spreen, Gunnar; Kaleschke, Lars; Heygster, Georg

doi:10.1029/2005jc003384

Cited by 1,233 publications

(1,196 citation statements)

References 33 publications

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“…The product is based on 85ĠHz SSM/I brightness temperatures, using the ARTIST Sea Ice (ASI) algorithm developed at the University of Bremen (Spreen et al, 2008b). The use of the 85 GHz channel data enables a sea ice concentration at 12.5 km × 12.5 km pixel resolution.…”

Section: Sea Ice Concentrationmentioning

confidence: 99%

Variability and trends in Laptev Sea ice outflow between 1992–2011

et al. 2013

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Abstract. Variability and trends in seasonal and interannual ice area export out of the Laptev Sea between 1992 and 2011 are investigated using satellite-based sea ice drift and concentration data. We found an average total winter (October to May) ice area transport across the northern and eastern Laptev Sea boundaries (NB and EB) of 3.48 × 10 5 km 2 . The average transport across the NB (2.87 × 10 5 km 2 ) is thereby higher than across the EB (0.61 × 10 5 km 2 ), with a less pronounced seasonal cycle. The total Laptev Sea ice area flux significantly increased over the last decades (0.85 × 10 5 km 2 decade −1 , p > 0.95), dominated by increasing export through the EB (0.55 × 10 5 km 2 decade −1 , p > 0.90), while the increase in export across the NB is smaller (0.3 × 10 5 km 2 decade −1 ) and statistically not significant. The strong coupling between across-boundary SLP gradient and ice drift velocity indicates that monthly variations in ice area flux are primarily controlled by changes in geostrophic wind velocities, although the Laptev Sea ice circulation shows no clear relationship with large-scale atmospheric indices. Also there is no evidence of increasing wind velocities that could explain the overall positive trends in ice export. The increased transport rates are rather the consequence of a changing ice cover such as thinning and/or a decrease in concentration. The use of a back-propagation method revealed that most of the ice that is incorporated into the Transpolar Drift is formed during freeze-up and originates from the central and western part of the Laptev Sea, while the exchange with the East Siberian Sea is dominated by ice coming from the central and southeastern Laptev Sea. Furthermore, our results imply that years of high ice export in late winter (February to May) have a thinning effect on the ice cover, which in turn preconditions the occurence of negative sea ice extent anomalies in summer.

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Section: Sea Ice Concentrationmentioning

confidence: 99%

Variability and trends in Laptev Sea ice outflow between 1992–2011

et al. 2013

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“…Each data point of the cetacean survey was annotated with water depth (from IBCSO, Arndt et al 2013) and derived bathymetric slope and local ice concentration (from daily 6.25-km-resolution satellite remote sensing data; Daily AMSR2 Sea Ice Maps, http://www.meer eisportal.de; Spreen et al 2008).…”

Section: Cetaceansmentioning

confidence: 99%

Horizontal niche partitioning of humpback and fin whales around the West Antarctic Peninsula: evidence from a concurrent whale and krill survey

et al. 2016

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A dedicated aerial cetacean survey was conducted concurrently to a standardised net trawl survey for krill in order to investigate distribution patterns of large whales and different krill species and to investigate relationships of these. Distance sampling data were used to produce density surface models for humpback (Megaptera novaeangliae) and fin whales (Balaenoptera physalus) around the West Antarctic Peninsula (WAP). Abundance for both species was estimated over two strata in the Bransfield Strait and Drake Passage. Distinct distribution patterns suggest horizontal niche partitioning of the two whale species around the WAP, with fin whales aggregating at the shelf edge of the South Shetland Islands in the Drake Passage and humpback whales in the Bransfield Strait. Krill biomass estimated from the concurrent krill survey was used along with CTD data from the same expedition, bathymetric parameters and satellite data on chlorophyll-a and ice concentration to model krill distribution. Comparisons of the predicted distributions of both whale species with the predicted distributions of Euphausia superba, Euphausia crystallorophias and Thysanoessa macrura suggest a complex relationship rather than a straightforward correlation between krill and whales. However, results indicate that fin whales were feeding in an area dominated by T. macrura, while humpback whales were found in areas of higher E. superba biomass. Our results provide abundance estimates for humpback whales and, for the first time, fin whales in the WAP and contribute important information on feeding ecology and habitat use of these two species in the Southern Ocean.

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“…The model is initialized with the ice concentration derived from the AMSR-E passive microwave sensor (Kaleschke et al, 2001;Spreen et al, 2008, data obtained from the Integrated Climate Date Center, University of Hamburg, Germany, http://icdc.zmaw.de) and the TOPAZ reanalysis ice thickness, within the area covered with ice. As the modeled ice volume of the TOPAZ reanalysis is known to be too low (Sakov et al, 2015), we increased the initial thickness uniformly so that the total volume is the same as that given by the PIOMAS model (Zhang and Rothrock, 2003) on 15 The neXtSIM model is able to simulate correctly the observed evolution of the sea-ice volume, extent and area for the freezing season (from September to May) but simulates a too-rapid melt from May onwards .…”

Section: Nextsim Trajectories Datasetmentioning

confidence: 99%

Arctic sea-ice diffusion from observed and simulated Lagrangian trajectories

et al. 2016

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Abstract. We characterize sea-ice drift by applying a Lagrangian diffusion analysis to buoy trajectories from the International Arctic Buoy Programme (IABP) dataset and from two different models: the standalone Lagrangian sea-ice model neXtSIM and the Eulerian coupled ice-ocean model used for the TOPAZ reanalysis. By applying the diffusion analysis to the IABP buoy trajectories over the period 1979-2011, we confirm that sea-ice diffusion follows two distinct regimes (ballistic and Brownian) and we provide accurate values for the diffusivity and integral timescale that could be used in Eulerian or Lagrangian passive tracers models to simulate the transport and diffusion of particles moving with the ice. We discuss how these values are linked to the evolution of the fluctuating displacements variance and how this information could be used to define the size of the search area around the position predicted by the mean drift. By comparing observed and simulated sea-ice trajectories for three consecutive winter seasons (2007)(2008)(2009)(2010)(2011), we show how the characteristics of the simulated motion may differ from or agree well with observations. This comparison illustrates the usefulness of first applying a diffusion analysis to evaluate the output of modeling systems that include a sea-ice model before using these in, e.g., oil spill trajectory models or, more generally, to simulate the transport of passive tracers in sea ice.

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Sea ice remote sensing using AMSR‐E 89‐GHz channels

Cited by 1,233 publications

References 33 publications

Variability and trends in Laptev Sea ice outflow between 1992–2011

Variability and trends in Laptev Sea ice outflow between 1992–2011

Horizontal niche partitioning of humpback and fin whales around the West Antarctic Peninsula: evidence from a concurrent whale and krill survey

Arctic sea-ice diffusion from observed and simulated Lagrangian trajectories

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