The decline in arctic sea‐ice thickness: Separating the spatial, annual, and interannual variability in a quarter century of submarine data

Rothrock, D. A.; Percival, Donald B.; Wensnahan, Mark

doi:10.1029/2007jc004252

Cited by 267 publications

(296 citation statements)

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“…These changes coincide with coherent reports on decreasing Arctic sea ice volume and general thinning of the ice cover (Kurtz et al, 2011;Kwok, 2011;Rothrock et al, 2008). The great loss of Arctic sea ice during the ice minimum in 2007 seem to have had a particular strong impact on the ice drift patterns, and especially the loss of large amounts of perennial sea ice in the Western Arctic seems to have changed the sea ice characteristics there (Maslanik et al, 2011).…”

Section: Sea Ice Drift and Deformationsupporting

confidence: 60%

Remote sensing of sea ice: advances during the DAMOCLES project

et al. 2012

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Abstract. In the Arctic, global warming is particularly pronounced so that we need to monitor its development continuously. On the other hand, the vast and hostile conditions make in situ observation difficult, so that available satellite observations should be exploited in the best possible way to extract geophysical information. Here, we give a résumé of the sea ice remote sensing efforts of the European Union's (EU) project DAMOCLES (Developing Arctic Modeling and Observing Capabilities for Long-term Environmental Studies). In order to better understand the seasonal variation of the microwave emission of sea ice observed from space, the monthly variations of the microwave emissivity of first-year and multi-year sea ice have been derived for the frequencies of the microwave imagers like AMSR-E (Advanced Microwave Scanning Radiometer on EOS) and sounding frequencies of AMSU (Advanced Microwave Sounding Unit), and have been used to develop an optimal estimation method to retrieve sea ice and atmospheric parameters simultaneously. In addition, a sea ice microwave emissivity model has been used together with a thermodynamic model to establish relations between the emissivities from 6 GHz to 50 GHz. At the latter frequency, the emissivity is needed for assimilation into atmospheric circulation models, but is more difficult to observe directly. The size of the snow grains on top of the sea ice influences both its albedo and the microwave emission. A method to determine the effective size of the snow grains from observations in the visible range (MODIS) is developed and demonstrated in an application on the Ross ice shelf. The bidirectional reflectivity distribution function (BRDF) of snow, which is an essential input parameter to the retrieval, has been measured in situ on Svalbard during the DAMO-CLES campaign, and a BRDF model assuming aspherical particles is developed. Sea ice drift and deformation is derived from satellite observations with the scatterometer AS-CAT (62.5 km grid spacing), with visible AVHRR observations (20 km), with the synthetic aperture radar sensor ASAR (10 km), and a multi-sensor product (62.5 km) with improved angular resolution (Continuous Maximum Cross Correlation, CMCC method) is presented. CMCC is also used to derive the sea ice deformation, important for formation of sea ice leads (diverging deformation) and pressure ridges (converging). The indirect determination of sea ice thickness from altimeter freeboard data requires knowledge of the ice density and snow load on sea ice. The relation between freeboard and ice thickness is investigated based on the airborne Sever expeditions conducted between 1928 and 1993.

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Section: Sea Ice Drift and Deformationsupporting

confidence: 60%

Remote sensing of sea ice: advances during the DAMOCLES project

et al. 2012

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“…Abbot, C.C. Walker, E. Tziperman, unpublished manuscript), the dependence of sea ice surface albedo on snow and melt pond coverage (24,25), ocean heat flux convergence feedbacks (6,26), changes in wind-driven ice dynamics (7), and changes in ice rheology (27) in a thinning ice cover (28) could potentially lead to other bifurcation thresholds or smooth out the threshold investigated here, akin to the smoothing of a first order phase transition because of statistical fluctuations (29). We are emboldened in our approach, however, because behavior consistent with the mechanism proposed here can be found in the published results of models with a broad range of complexities.…”

Section: Discussionmentioning

confidence: 99%

Nonlinear threshold behavior during the loss of Arctic sea ice

Eisenman

Wettlaufer

2009

Proc. Natl. Acad. Sci. U.S.A.

202

295

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In light of the rapid recent retreat of Arctic sea ice, a number of studies have discussed the possibility of a critical threshold (or ''tipping point'') beyond which the ice-albedo feedback causes the ice cover to melt away in an irreversible process. The focus has typically been centered on the annual minimum (September) ice cover, which is often seen as particularly susceptible to destabilization by the ice-albedo feedback. Here, we examine the central physical processes associated with the transition from ice-covered to ice-free Arctic Ocean conditions. We show that although the ice-albedo feedback promotes the existence of multiple ice-cover states, the stabilizing thermodynamic effects of sea ice mitigate this when the Arctic Ocean is ice covered during a sufficiently large fraction of the year. These results suggest that critical threshold behavior is unlikely during the approach from current perennial sea-ice conditions to seasonally ice-free conditions. In a further warmed climate, however, we find that a critical threshold associated with the sudden loss of the remaining wintertime-only sea ice cover may be likely.Arctic climate ͉ bifurcation ͉ climate change ͉ tipping point T he retreat of Arctic sea ice during recent decades (1) is believed to be augmented by the difference in albedo (i.e., reflectivity) between sea ice and exposed ocean waters (2). Because bare or snow-covered sea ice is highly reflective to solar radiation, the increasing area of open water that is exposed as sea ice recedes leads to an increase in absorbed solar radiation, thereby contributing to further ice retreat. A number of recent studies have discussed the possibility that this positive ice-albedo feedback will cause the rapidly declining annual minimum (September) sea-ice cover to cross a critical threshold, after which the sea ice will melt back on an irreversible trajectory to a seasonally ice-free state (3-9).Heuristically, one might expect in a simple annual mean picture of the Arctic Ocean that completely ice-covered and ice-free stable states could coexist under the same climate forcing. The ice-free state would remain warm because of the absorption of most incident solar radiation, whereas the icecovered state would reflect most solar radiation and remain below the freezing temperature. In such a picture, these two stable states would be separated by an unstable intermediate state in which the Arctic Ocean is partially covered by ice and absorbs just enough solar radiation such that it remains at the freezing temperature: Adding a small amount of additional sea ice to this unstable state would lead to less solar absorption, cooling, and a further extended sea-ice cover. If the background climate warmed, the unstable state would require an increased ice extent to reflect sufficient solar radiation to remain at the freezing temperature. Beyond a critical threshold, the background climate would become so warm that the ice-covered state would reach the freezing temperature. At this point the stable ice-covered state and ...

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“…Over the last 3 decades, sea-ice extent (SIE) in the Arctic has decreased and submarine ice draft measurements indicate that also sea-ice volume is declining (Rothrock et al, 1999(Rothrock et al, , 2008Lindsay and Schweiger, 2015). In the Antarctic, in contrast, SIE is increasing, but little is known about the changes in sea-ice volume.…”

Section: Introductionmentioning

confidence: 99%

About the consistency between Envisat and CryoSat-2 radar freeboard retrieval over Antarctic sea ice

et al. 2016

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Abstract. Knowledge about Antarctic sea-ice volume and its changes over the past decades has been sparse due to the lack of systematic sea-ice thickness measurements in this remote area. Recently, first attempts have been made to develop a sea-ice thickness product over the Southern Ocean from space-borne radar altimetry and results look promising. Today, more than 20 years of radar altimeter data are potentially available for such products. However, the characteristics of individual radar types differ for the available altimeter missions. Hence, it is important and our goal to study the consistency between single sensors in order to develop long and consistent time series. Here, the consistency between freeboard measurements of the Radar Altimeter 2 on board Envisat and freeboard measurements from the SyntheticAperture Interferometric Radar Altimeter on board CryoSat-2 is tested for their overlap period in 2011. Results indicate that mean and modal values are in reasonable agreement over the sea-ice growth season (May-October) and partly also beyond. In general, Envisat data show higher freeboards in the first-year ice zone while CryoSat-2 freeboards are higher in the multiyear ice zone and near the coasts. This has consequences for the agreement in individual sectors of the Southern Ocean, where one or the other ice class may dominate. Nevertheless, over the growth season, mean freeboard for the entire (regionally separated) Southern Ocean differs generally by not more than 3 cm (8 cm, with few exceptions) between Envisat and CryoSat-2, and the differences between modal freeboards lie generally within ±10 cm and often even below.

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The decline in arctic sea‐ice thickness: Separating the spatial, annual, and interannual variability in a quarter century of submarine data

Cited by 267 publications

References 23 publications

Remote sensing of sea ice: advances during the DAMOCLES project

Remote sensing of sea ice: advances during the DAMOCLES project

Nonlinear threshold behavior during the loss of Arctic sea ice

About the consistency between Envisat and CryoSat-2 radar freeboard retrieval over Antarctic sea ice

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