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Enhanced winter snowmelt in the Antarctic Peninsula: Automatic snowmelt identification from radar scatterometer

  • Lei Zheng
  • , Chunxia Zhou*
  • , Kang Wang
  • *Corresponding author for this work
  • Sun Yat-Sen University
  • Wuhan University
  • Southern Marine Science and Engineering Guangdong Laboratory - Guanzhou

Research output: Contribution to journalArticlepeer-review

Abstract

Surface snowmelt affects the energy balance through melt-albedo feedback and may endanger the ice shelves in the Antarctic Peninsula (AP) through hydrofracture. Here, we introduce an automatic snowmelt identification algorithm based on Quick Scatterometer and Advanced Scatterometer. The proposed method can provide self-adaptive thresholds for snowmelt detection based on Rosin thresholding, and is able to detect weak melt signals with a wavelet denoising procedure. Results suggest the AP surface snowmelt has slightly declined during 1999–2018 in the context of recent cooling. However, winter melt index (i.e., melt days times the area of melting) has significantly increased (above the 99% confidence level) with a rate of 83% decade−1. Unprecedented winter snowmelt was found in 2015/2016 when about one-third of the AP experienced snowmelt in late May. This may be attributed to the intrusions of marine air and the enhanced föhn-driven warming resulted from the abnormal northwesterly flow driven by a significant deepening of the Amundsen Sea Low.

Original languageEnglish
Article number111835
JournalRemote Sensing of Environment
Volume246
DOIs
StatePublished - 1 Sep 2020

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 14 - Life Below Water
    SDG 14 Life Below Water

Keywords

  • Antarctic Peninsula
  • Rosin thresholding
  • Scatterometer
  • Wavelet denoising
  • Winter snowmelt

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