Cross-validation of polynya monitoring methods from multisensor satellite and airborne data: a case study for the Laptev Sea

Willmes, Sascha; Krumpen, Thomas; Adams, Susanne; Rabenstein, Lasse; Haas, Christian; Hoelemann, Jens A.; Hendricks, Stefan; Heinemann, Günther

doi:10.5589/m10-012

Cited by 40 publications

(55 citation statements)

References 30 publications

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“…The core of this approach is a one-dimensional energy balance model, in which IST and the thin-ice thickness are related to atmospheric radiation fluxes and turbulent heat fluxes. The original method of Yu and Rothrock (1996) was first improved and modified by Willmes et al (2010) and Adams et al (2013). More recently, the latest modifications of the algorithm are described in detail in Preußer et al (2015a, b) and Paul et al (2015b), together with comprehensive information on applied parametrization schemes that are used to calculate atmospheric radiation fluxes and turbulent heat fluxes.…”

Section: Methodsmentioning

confidence: 99%

“…The derivation of polynya area needs to be addressed with spatial and temporal resolutions that are sufficient for capturing the seasonal and regional dynamics of polynya events (Winsor and Björk, 2000;Morales-Maqueda et al, 2004;Tamura et al, 2008;Willmes et al, 2010). Furthermore, the heat loss over the polynya has to be calculated, which requires detailed information about the fraction of open water, the ice thickness and its distribution within the polynya.…”

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confidence: 99%

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Circumpolar polynya regions and ice production in the Arctic: results from MODIS thermal infrared imagery from 2002/2003 to 2014/2015 with a regional focus on the Laptev Sea

et al. 2016

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Abstract. High-resolution MODIS thermal infrared satellite data are used to infer spatial and temporal characteristics of 17 prominent coastal polynya regions over the entire Arctic basin. Thin-ice thickness (TIT) distributions ( ≤ 20 cm) are calculated from MODIS ice-surface temperatures, combined with ECMWF ERA-Interim atmospheric reanalysis data in an energy balance model for 13 winter seasons (2002/2003to 2014/2015 November to March). From all available MODIS swath data, daily thin-ice thickness composites are computed in order to derive quantities such as polynya area and total thermodynamic (i.e., potential) ice production. A gap-filling approach is applied to account for cloud and data gaps in the MODIS composites. All polynya regions combined cover an average thin-ice area of 226.6 ± 36.1 × 10 3 km 2 in winter. This allows for an average total winter-accumulated ice production of about 1811 ± 293 km 3 , whereby the Kara Sea region, the North Water polynya (both 15 %), polynyas on the western side of Novaya Zemlya (20 %), as well as scattered smaller polynyas in the Canadian Arctic Archipelago (all combined 12 %) are the main contributors. Other wellknown sites of polynya formation (Laptev Sea, Chukchi Sea) show smaller contributions and range between 2 and 5 %. We notice distinct differences to earlier studies on pan-Arctic polynya characteristics, originating in some part from the use of high-resolution MODIS data, as the capability to resolve small-scale (> 2 km) polynyas and also large leads are increased. Despite the short record of 13 winter seasons, positive trends in ice production are detected for several regions of the eastern Arctic (most significantly in the Laptev Sea region with an increase of 6.8 km 3 yr −1 ) and the North Water polynya, while other polynyas in the western Arctic show a more pronounced variability with varying trends. We emphasize the role of the Laptev Sea polynyas as being a major influence on Transpolar Drift characteristics through a distinct relation between increasing ice production and ice area export. Overall, our study presents a spatially highly accurate characterization of circumpolar polynya dynamics and ice production, which should be valuable for future modeling efforts of atmosphere-ice-ocean interactions in the Arctic.

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Section: Methodsmentioning

confidence: 99%

mentioning

confidence: 99%

Circumpolar polynya regions and ice production in the Arctic: results from MODIS thermal infrared imagery from 2002/2003 to 2014/2015 with a regional focus on the Laptev Sea

et al. 2016

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“…Due to this strong surface heat loss within coastal polynyas frazil ice forms, which is subsequently transported toward the downwind edge of the polynyas (Smith et al, 1990;Morales Maqueda et al, 2004;Krumpen et al, 2011;Willmes et al, 2010). This process creates a spatial gradient of thin-ice thickness (TIT) increasing from open-water conditions at the windward polynya edge to thicker ice at the downwind side.…”

Section: O Gutjahr Et Al: Quantification Of Ice Production In Laptementioning

confidence: 99%

“…However, assumptions have to be made for the subgrid-scale thin-ice thickness, since particularly in winter leads and polynyas are rarely ice free (Willmes et al, 2010(Willmes et al, , 2011aAdams et al, 2013).…”

Section: O Gutjahr Et Al: Quantification Of Ice Production In Laptementioning

confidence: 99%

Quantification of ice production in Laptev Sea polynyas and its sensitivity to thin-ice parameterizations in a regional climate model

et al. 2016

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Abstract. The quantification of sea-ice production in the Laptev Sea polynyas is important for the Arctic sea-ice budget and the heat loss to the atmosphere. We estimated the ice production for the winter season 2007/2008 (NovemberApril) based on simulations with the regional climate model COSMO-CLM at a horizontal resolution of 5 km and compared it to remote sensing estimates. A reference and five sensitivity simulations were performed with different assumptions on grid-scale and subgrid-scale ice thickness considered within polynyas, using a tile approach for fractional sea ice. In addition, the impact of heat loss on the atmospheric boundary layer was investigated.About 29.1 km 3 of total winter ice production was estimated for the reference simulation, which varies by up to +124 % depending on the thin-ice assumptions. For the most realistic assumptions based on remote sensing of ice thickness the ice production increases by +39 %. The use of the tile approach enlarges the area and enhances the magnitude of the heat loss from polynyas up to +110 % if subgrid-scale open water is assumed and by +20 % for realistic assumptions. This enhanced heat loss causes in turn higher ice production rates and stronger impact on the atmospheric boundary layer structure over the polynyas. The study shows that ice production is highly sensitive to the thin-ice parameterizations for fractional sea-ice cover. In summary, realistic ice production estimates could be retrieved from our simulations. Neglecting subgrid-scale energy fluxes might considerably underestimate the ice production in coastal polynyas, such as in the Laptev Sea, with possible consequences on the Arctic sea-ice budget.

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“…Their importance for the maintenance of the Arctic sea-ice volume and their impact on stratification in the Arctic Ocean is not completely understood. The Laptev Sea polynyas have been discussed in terms of ice production and the generation of higher saline water by several authors (Zakharov, 1966;Cavalieri and Martin, 1994;Dethleff et al, 1998;Dmitrenko et al, 2005Dmitrenko et al, , 2009Willmes et al, 2010). Dmitrenko et al (2009) have estimated the mean annual net sea-ice production in the entire Laptev Sea to be between 750 km 3 and 1450 km 3 on the basis of salinity observations within the upper 50 m of the water column.…”

Section: Introductionmentioning

confidence: 99%

A combined approach of remote sensing and airborne electromagnetics to determine the volume of polynya sea ice in the Laptev Sea

et al. 2013

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Abstract.A combined interpretation of synthetic aperture radar (SAR) satellite images and helicopter electromagnetic (HEM) sea-ice thickness data has provided an estimate of sea-ice volume formed in Laptev Sea polynyas during the winter of 2007/08. The evolution of the surveyed sea-ice areas, which were formed between late December 2007 and middle April 2008, was tracked using a series of SAR images with a sampling interval of 2-3 days. Approximately 160 km of HEM data recorded in April 2008 provided seaice thicknesses along profiles that transected sea ice varying in age from 1 to 116 days. For the volume estimates, thickness information along the HEM profiles was extrapolated to zones of the same age. The error of areal mean thickness information was estimated to be between 0.2 m for younger ice and up to 1.55 m for older ice, with the primary error source being the spatially limited HEM coverage. Our results have demonstrated that the modal thicknesses and mean thicknesses of level ice correlated with the sea-ice age, but that varying dynamic and thermodynamic sea-ice growth conditions resulted in a rather heterogeneous sea-ice thickness distribution on scales of tens of kilometers. Taking all uncertainties into account, total sea-ice area and volume produced within the entire surveyed area were 52 650 km 2 and 93.6 ± 26.6 km 3 . The surveyed polynya contributed 2.0 ± 0.5 % of the sea-ice produced throughout the Arctic during the 2007/08 winter. The SAR-HEM volume estimate compares well with the 112 km 3 ice production calculated with a high-resolution ocean sea-ice model. Measured modal and mean-level ice thicknesses correlate with calculated freezing-degree-day thicknesses with a factor of 0.87-0.89, which was too low to justify the assumption of homogeneous thermodynamic growth conditions in the area, or indicates a strong dynamic thickening of level ice by rafting of even thicker ice.

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Cross-validation of polynya monitoring methods from multisensor satellite and airborne data: a case study for the Laptev Sea

Cited by 40 publications

References 30 publications

Circumpolar polynya regions and ice production in the Arctic: results from MODIS thermal infrared imagery from 2002/2003 to 2014/2015 with a regional focus on the Laptev Sea

Circumpolar polynya regions and ice production in the Arctic: results from MODIS thermal infrared imagery from 2002/2003 to 2014/2015 with a regional focus on the Laptev Sea

Quantification of ice production in Laptev Sea polynyas and its sensitivity to thin-ice parameterizations in a regional climate model

A combined approach of remote sensing and airborne electromagnetics to determine the volume of polynya sea ice in the Laptev Sea

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