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  • 1
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    PANGAEA
    In:  Supplement to: Weller, Rolf; Wagenbach, Dietmar; Legrand, Michel R; Elsässer, Christoph; Tian-Kunze, Xiangshan; König-Langlo, Gert (2011): Continuous 25-yr aerosol records at coastal Antarctica – I: inter-annual variability of ionic compounds and links to climate indices. Tellus Series B-Chemical and Physical Meteorology, 63(5), 901-919, https://doi.org/10.1111/j.1600-0889.2011.00542.x
    Publication Date: 2023-10-28
    Description: The aerosol climatology at the coastal Antarctic Neumayer Station (NM) was investigated based on continuous, 25-yr long observations of biogenic sulphur components (methanesulfonate and non-sea salt sulphate), sea salt and nitrate. Although significant long-term trends could only be detected for nitrate (-3.6 ± 2.5% per year between 1983 and 1993 and +4.0 ± 3.2% per year from 1993-2007), non-harmonic periodicities between 2 and 5 yr were typical for all species. Dedicated time series analyses revealed that relations to sea ice extent and various circulation indices are weak at best or not significant. In particular, no consistent link between sea ice extent and sea salt loadings was evident suggesting only a rather local relevance of the NM sea salt record. Nevertheless, a higher Southern Annular Mode index tended to entail a lower biogenic sulphur signal. In examining the spatial uniformity of the NM findings we contrasted them to respective 17 yr records from the coastal Dumont d'Urville Station. We found similar long-term trends for nitrate, indicating an Antarctic-wide but not identifiable atmospheric signal, although any significant impact of solar activity or pollution could be ruled out. No inter-site variability on the multiannual scale was evident for the other ionic compounds.
    Keywords: Air chemistry observatory; Air temperature at 2 m height; Anemometer; Atmospheric Chemistry @ AWI; AWI_AC; BARO; Barometer; Chloride; DATE/TIME; Date/time end; Dronning Maud Land, Antarctica; Duration, number of days; HEIGHT above ground; Ion chromatography; Methane sulfonic acid; Neumayer_based; Neumayer_SPUSO; NEUMAYER III; Nitrate; Priority Programme 1158 Antarctic Research with Comparable Investigations in Arctic Sea Ice Areas; Sodium; SPP1158; SPUSO; Station pressure; Sulfate, non-sea-salt; Thermometer; Wind speed at 2 m height
    Type: Dataset
    Format: text/tab-separated-values, 2980 data points
    Location Call Number Limitation Availability
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  • 2
    Publication Date: 2015-03-13
    Description: Following the launch of ESA's Soil Moisture and Ocean Salinity (SMOS) mission, it has been shown that brightness temperatures at a low microwave frequency of 1.4 GHz (L-band) are sensitive to sea ice properties. In the first demonstration study, sea ice thickness up to 50 cm has been derived using a semi-empirical algorithm with constant tie-points. Here, we introduce a novel iterative retrieval algorithm that is based on a thermodynamic sea ice model and a three-layer radiative transfer model, which explicitly takes variations of ice temperature and ice salinity into account. In addition, ice thickness variations within the SMOS spatial resolution are considered through a statistical thickness distribution function derived from high-resolution ice thickness measurements from NASA's Operation IceBridge campaign. This new algorithm has been used for the continuous operational production of a SMOS-based sea ice thickness data set from 2010 on. The data set is compared to and validated with estimates from assimilation systems, remote sensing data, and airborne electromagnetic sounding data. The comparisons show that the new retrieval algorithm has a considerably better agreement with the validation data and delivers a more realistic Arctic-wide ice thickness distribution than the algorithm used in the previous study (Kaleschke et al., 2012).
    Type: Article , PeerReviewed
    Format: text
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  • 3
    Publication Date: 2019-07-17
    Description: The impact of assimilating sea ice thickness data derived from ESA's Soil Moisture and Ocean Salinity (SMOS) satellite together with Special Sensor Microwave Imager/Sounder (SSMIS) sea ice concentration data of the National Snow and Ice Data Center (NSIDC) in a coupled sea ice-ocean model is examined. A period of 3 months from 1 November 2011 to 31 January 2012 is selected to assess the forecast skill of the assimilation system. The 24 h forecasts and longer forecasts are based on the Massachusetts Institute of Technology general circulation model (MITgcm), and the assimilation is performed by a localized Singular Evolutive Interpolated Kalman (LSEIK) filter. For comparison, the assimilation is repeated only with the SSMIS sea ice concentrations. By running two different assimilation experiments, and comparing with the unassimilated model, independent satellite-derived data, and in situ observation, it is shown that the SMOS ice thickness assimilation leads to improved thickness forecasts. With SMOS thickness data, the sea ice concentration forecasts also agree better with observations, although this improvement is smaller.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
    Format: application/pdf
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  • 4
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    In:  EPIC3International Symposium on Sea Ice in a Changing Environment, Hobart, Australia, 2014-03-10-2014-03-14
    Publication Date: 2019-07-17
    Description: Appropriate initial conditions are essential for accurate forecasts of sea ice conditions in the Arctic. We present a prototype of an assimilation and forecast system, where a new sea ice thickness data set based on the Soil Moisture and Ocean Salinity (SMOS) satellite data and sea ice concentration data (SSMIS) are assimilated with a local Singular Evolutive Interoplated Kalman (SEIK) [3] filter. The system is run for 3 months in the transition between autumn and winter 2011/2012. Forecasts of different length are evaluated and compared to independent in-situ data.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Conference , notRev
    Format: application/pdf
    Location Call Number Limitation Availability
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  • 5
    Publication Date: 2014-06-02
    Description: Following the launch of ESA's Soil Moisture and Ocean Salinity (SMOS) mission, it has been shown that brightness temperatures at a low microwave frequency of 1.4 GHz (L-band) are sensitive to sea ice properties. In the first demonstration study, sea ice thickness up to 50 cm has been derived using a semi-empirical algorithm with constant tie-points. Here, we introduce a novel iterative retrieval algorithm that is based on a thermodynamic sea ice model and a three-layer radiative transfer model, which explicitly takes variations of ice temperature and ice salinity into account. In addition, ice thickness variations within the SMOS spatial resolution are considered through a statistical thickness distribution function derived from high-resolution ice thickness measurements from NASA's Operation IceBridge campaign. This new algorithm has been used for the continuous operational production of a SMOS-based sea ice thickness data set from 2010 on. The data set is compared to and validated with estimates from assimilation systems, remote sensing data, and airborne electromagnetic sounding data. The comparisons show that the new retrieval algorithm has a considerably better agreement with the validation data and delivers a more realistic Arctic-wide ice thickness distribution than the algorithm used in the previous study (Kaleschke et al., 2012).
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , isiRev
    Format: application/pdf
    Location Call Number Limitation Availability
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