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  • English  (12)
  • 11
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    In:  XXVIII General Assembly of the International Union of Geodesy and Geophysics (IUGG)
    Publication Date: 2023-05-09
    Description: The extraordinary Hunga Tonga-Hunga Ha'apai volcano eruption occurred on 15 January 2022 had quite a global influence through ejecting volcanic ashes and unleashing a variety of strong waves that rippled through oceans and the atmosphere. Here we use remote sensing data to show that a tsunami triggered by the violent explosion resulted in calving from a remote Antarctic ice tongue. The volcano-triggered tsunami travelled over 6,000 km before impinging on the Drygalski Ice Tongue, resulting in the calving of a 10 km × 4.5 km iceberg from the ice front. Our study provides the most detailed observational evidence to date and confirms the linkages between the tsunami and the iceberg calving. Furthermore, it implies the stability of ice shelves in Antarctica may be influenced by extreme events outside the polar regions.
    Language: English
    Type: info:eu-repo/semantics/conferenceObject
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  • 12
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    In:  XXVIII General Assembly of the International Union of Geodesy and Geophysics (IUGG)
    Publication Date: 2023-07-13
    Description: With the declining Arctic sea ice extent, it is increasingly demanded for high resolution sea ice concentration (SIC) monitoring. This paper introduces a new thermal infrared ice concentration algorithm (TIRIA), which directly uses thermal infrared (TIR) brightness temperatures thus does not rely on surface temperature products as traditional algorithms. Factors such as sea water salinity and observation angle and their impacts on ice/water brightness temperature are accounted. TIRIA and a traditional algorithm, namely MPA, were applied to FY-3D MERSI-II TIR imagery. Results were inter-compared with passive microwave (PM) SICs and validated with near-infrared (NIR) SICs. Overall speaking, both TIRIA and MPA tend to underestimate SIC in ice-covered area, while overestimate in open water area. Compared to MPA, the overestimation of SIC is largely mitigated in TIRIA. This consequently leads to an overall better performance of TIRIA. Although the bias tends towards slightly negative value, the higher correlation meanwhile smaller MAE and RMSE indicates good potentials of the new algorithm. TIRIA can be theoretically applied to any TIR data. However, factors such as cloud mask and data accuracy play important roles in the TIR SIC retrieval thus should be taken with caution.
    Language: English
    Type: info:eu-repo/semantics/conferenceObject
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