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  • 1
    Publication Date: 2017-01-01
    Description: Storfjorden, which hosts a latent heat polynya, is a well known region of dense water formation. This Brine-enriched Shelf Water (BSW) displays substantial year to year variability in its properties, which is partly linked to interannual variations in ice production. Here we have developed a model based on high-resolution AMSR-E satellite sea-ice concentration data, available between 2002 and 2011, and atmospheric forcing to estimate the ice production in the polynya and associated salt release. The average modeled ice production for the epoch 2002–2011 is 47 km3 per year, corresponding to a salt release of 1200 × 109 kg. The two most anomalous winters were 2004–2005 (salt deficit of −367 × 109 kg) and 2007–2008 (salt excess of 398 × 109 kg). Available observations of BSW properties are relatively scarce during this period and are here augmented with data collected in March 2007 from an ice-tethered mooring to the northwest of the fjord. BSW was found up to the surface, with maximum salinity and density of 35.27 and 28.4 kg m−3, respectively, at 55 m. In addition, supercooled water was found down to 10 m under relatively mild atmospheric conditions. It is shown to have formed a week before, during an intense frazil ice formation episode, exceeding 2 km3 of frazil ice according to the model. Although observations remain too few to robustly assess the relation between ice production and BSW properties, there is suggestion of a direct impact for most anomalous years. The exceptional ice production in 2007–2008 is most likely the cause of the very saline BSW in 2008 and strong plume of dense water toward Fram Strait reported by other authors. Anomalous ice production appears predominantly driven by the duration of the freezing season and anomalous opening of the polynya.
    Type: Article , PeerReviewed
    Format: text
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  • 2
    Publication Date: 2022-03-08
    Description: Precise knowledge of wintertime sea ice production in Arctic polynyas is not only required to enhance our understanding of atmosphere‐sea ice‐ocean interactions but also to verify frequently utilized climate and ocean models. Here, a high‐resolution (2‐km) Moderate Resolution Imaging Spectroradiometer (MODIS) thermal infrared satellite data set featuring spatial and temporal characteristics of 17 Arctic polynya regions for the winter seasons 2002/2003 to 2017/2018 is directly compared to an akin low‐resolution Advanced Microwave Scanning Radiometer‐EOS (AMSR‐E) passive microwave data set for 2002/2003 to 2010/2011. The MODIS data set is purely based on a 1‐D energy‐balance model, where thin‐ice thicknesses (≤ 20 cm) are directly derived from ice‐surface temperature swath data and European Centre for Medium‐Range Weather Forecasts Re‐Analysis‐Interim atmospheric reanalysis data on a quasi‐daily basis. Thin‐ice thicknesses in the AMSR‐E data set are derived empirically. Important polynya properties such as areal extent and potential thermodynamic ice production can be estimated from both pan‐Arctic data sets. Although independently derived, our results show that both data sets feature quite similar spatial and temporal variations of polynya area (POLA) and ice production (IP), which suggests a high reliability. The average POLA (average accumulated IP) for all Arctic polynyas combined derived from both MODIS and AMSR‐E are 1.99×105 km2 (1.34×103 km3) and 2.29×105 km2 (1.31×103 km3), respectively. Narrow polynyas in areas such as the Canadian Arctic Archipelago are notably better resolved by MODIS. Analysis of 16 winter seasons provides an evaluation of long‐term trends in POLA and IP, revealing the significant increase of ice formation in polynyas along the Siberian coast.
    Type: Article , PeerReviewed
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  • 3
    Publication Date: 2022-12-01
    Description: Author Posting. © American Meteorological Society, 2022. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Bulletin of the American Meteorological Society 103(6), (2022): E1502-E1521, https://doi.org/10.1175/bams-d-21-0227.1.
    Description: Climate observations inform about the past and present state of the climate system. They underpin climate science, feed into policies for adaptation and mitigation, and increase awareness of the impacts of climate change. The Global Climate Observing System (GCOS), a body of the World Meteorological Organization (WMO), assesses the maturity of the required observing system and gives guidance for its development. The Essential Climate Variables (ECVs) are central to GCOS, and the global community must monitor them with the highest standards in the form of Climate Data Records (CDR). Today, a single ECV—the sea ice ECV—encapsulates all aspects of the sea ice environment. In the early 1990s it was a single variable (sea ice concentration) but is today an umbrella for four variables (adding thickness, edge/extent, and drift). In this contribution, we argue that GCOS should from now on consider a set of seven ECVs (sea ice concentration, thickness, snow depth, surface temperature, surface albedo, age, and drift). These seven ECVs are critical and cost effective to monitor with existing satellite Earth observation capability. We advise against placing these new variables under the umbrella of the single sea ice ECV. To start a set of distinct ECVs is indeed critical to avoid adding to the suboptimal situation we experience today and to reconcile the sea ice variables with the practice in other ECV domains.
    Description: PH’s contribution was funded under the Australian Government’s Antarctic Science Collaboration Initiative program, and contributes to Project 6 of the Australian Antarctic Program Partnership (ASCI000002). PH acknowledges support through the Australian Antarctic Science Projects 4496 and 4506, and the International Space Science Institute (Bern, Switzerland) project #405.
    Description: 2022-12-01
    Keywords: Sea ice ; Climate change ; Climatology ; Climate records
    Repository Name: Woods Hole Open Access Server
    Type: Article
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