Improved mapping of sea ice production in the Arctic Ocean using AMSR‐E thin ice thickness algorithm

Iwamoto, Katsushi; Ohshima, Κay I.; Tamura, Takeshi

doi:10.1002/2013jc009749

Cited by 66 publications

(197 citation statements)

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“…Following the work of Martin (1981), Tamura and Ohshima (2011) argued that frazil ice consists of freshwater ice crystals enclosed within a thin saline layer and that frazil ice production rates are of similar magnitudes to freshwater ice production rates. Consequently, we also use fixed values for ρ ice and L f in order to ensure comparability with earlier studies focusing on sea-ice production in (Arctic) polynyas (e.g., Willmes et al, 2011;Tamura and Ohshima, 2011;Iwamoto et al, 2014). However, this simplification may introduce an additional error source in our estimates due to spatially and temporally varying conditions for ice formation.…”

Section: Derivation Of Ice Production and Polynya Areamentioning

confidence: 99%

“…According to the surface energy balance, the heat fluxQ ice is equal to the total atmospheric heat loss (sum of net radiation, turbulent latent and sensible heat flux). We do not consider an ocean heat flux, although it might potentially reduce thermodynamic ice growth in certain areas of the Chukchi Sea (Hirano et al, 2016), the Canadian Arctic Archipelago (Hannah et al, 2009;Melling et al, 2015) and northern Baffin Bay (e.g., Steffen, 1985;Yao and Tang, 2003) by as much as 23-27 % in case of the NOW polynya (Tamura and Ohshima, 2011;Iwamoto et al, 2014). The volume ice production rate ∂V ∂t (IP) is calculated by multiplying ∂h ∂t with the areal extent of each pixel in the regarded region.…”

Section: Derivation Of Ice Production and Polynya Areamentioning

confidence: 99%

“…For those regions, this implies that the characteristics derived here may contain periods with extensive ice-free conditions, first and foremost in early winter. Pan-Arctic estimations of daily thin-ice thickness (TIT) and ice production in polynyas were previously published by Tamura and Ohshima (2011) and Iwamoto et al (2014), who both presented newly developed empirical thin-ice algorithms. Therein, commonly used passive microwave remote sensing data from the Special Sensor Microwave/Imager (SSM/I) and Advanced Microwave Scanning Radiometer-EOS (AMSR-E) satellite sensors are related to reference thin-ice thicknesses from Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) thermal infrared data, based on a characteristic inverse relationship between the surface brine volume fraction and the thickness of sea ice (Iwamoto et al, 2014).…”

mentioning

confidence: 99%

“…Pan-Arctic estimations of daily thin-ice thickness (TIT) and ice production in polynyas were previously published by Tamura and Ohshima (2011) and Iwamoto et al (2014), who both presented newly developed empirical thin-ice algorithms. Therein, commonly used passive microwave remote sensing data from the Special Sensor Microwave/Imager (SSM/I) and Advanced Microwave Scanning Radiometer-EOS (AMSR-E) satellite sensors are related to reference thin-ice thicknesses from Advanced Very High Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) thermal infrared data, based on a characteristic inverse relationship between the surface brine volume fraction and the thickness of sea ice (Iwamoto et al, 2014). In both studies, the advantages of passive microwave systems (complete daily coverage in the Arctic with almost no influence of clouds) come at the cost of quite coarse spatial resolutions (6.25-25 km), which strongly limit the ability to resolve small and/or narrow thin-ice areas in close proximity to coastlines or along fast-ice edges .…”

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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: Derivation Of Ice Production and Polynya Areamentioning

confidence: 99%

Section: Derivation Of Ice Production and Polynya Areamentioning

confidence: 99%

mentioning

confidence: 99%

mentioning

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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“…It is one of the most significant regions where a considerable amount of the total Arctic sea ice is produced (Aagard et al, 1981;Dmitrenko et al, 2009;Dethleff et al, 1998;Willmes et al, 2011a;Tamura and Ohshima, 2011;Iwamoto et al, 2014). The newly formed sea ice is subsequently transported by the Transpolar Drift Stream and accounts for about 20 % of the total ice export through Fram Strait (Rigor and Colony, 1997).…”

Section: Introductionmentioning

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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A wind‐driven, hybrid latent and sensible heat coastal polynya off Barrow, Alaska

et al. 2016

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The nature of the Barrow Coastal Polynya (BCP), which forms episodically off the Alaska coast in winter, is examined using mooring data, atmospheric reanalysis data, and satellite‐derived sea‐ice concentration and production data. We focus on oceanographic conditions such as water mass distribution and ocean current structure beneath the BCP. Two moorings were deployed off Barrow, Alaska in the northeastern Chukchi Sea from August 2009 to July 2010. For sea‐ice season from December to May, a characteristic sequence of five events associated with the BCP has been identified; (1) dominant northeasterly wind parallel to the Barrow Canyon, with an offshore component off Barrow, (2) high sea‐ice production, (3) upwelling of warm and saline Atlantic Water beneath the BCP, (4) strong up‐canyon shear flow associated with displaced density surfaces due to the upwelling, and (5) sudden suppression of ice growth. A baroclinic current structure, established after the upwelling, caused enhanced vertical shear and corresponding vertical mixing. The mixing event and open water formation occurred simultaneously, once sea‐ice production had stopped. Thus, mixing events accompanied by ocean heat flux from the upwelled warm water into the surface layer played an important role in formation/maintenance of the open water area (i.e., sensible heat polynya). The transition from a latent to a sensible heat polynya is well reproduced by a high‐resolution pan‐Arctic ice‐ocean model. We propose that the BCP, previously considered to be a latent heat polynya, is a wind‐driven hybrid latent and sensible heat polynya, with both features caused by the same northeasterly wind.

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Improved mapping of sea ice production in the Arctic Ocean using AMSR‐E thin ice thickness algorithm

Abstract: New and improved estimates of sea ice production in the Arctic Ocean are derived from AMSR-

Cited by 66 publications

References 64 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 wind‐driven, hybrid latent and sensible heat coastal polynya off Barrow, Alaska

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