Detecting Melt Pond Onset on Landfast Arctic Sea Ice Using a Dual C-Band Satellite Approach

The presence of melt ponds on the surface of Arctic sea ice affects its albedo, thermal properties, and overall melting rate, and thus, the detection of melt pond onset is of significant importance for understanding the Arctic's changing climate. This study investigates the utility of a novel m...

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Bibliographic Details
Main Author: Maknun, Syeda Shahida
Other Authors: Yackel, John James, Nandan, Vishnu, Hugenholtz, Christopher Herman, Rangelova, Elena Veselinova
Format: Master Thesis
Language:English
Published: Graduate Studies 2024
Subjects:
Canadian Arctic Archipelago
Sea ice
Melt ponds
Pond onset
Co-polarized ratio
Sentinel-1
ASCAT
Dual-sensor C-band
Snow
Remote Sensing
Physical Geography
albedo
Arctic
Arctic Archipelago
Online Access:https://hdl.handle.net/1880/118967
https://doi.org/10.11575/PRISM/46563
Description
Summary:The presence of melt ponds on the surface of Arctic sea ice affects its albedo, thermal properties, and overall melting rate, and thus, the detection of melt pond onset is of significant importance for understanding the Arctic's changing climate. This study investigates the utility of a novel method for detecting the onset of melt ponds on sea ice using a satellite-based, dual-sensor C-band approach, whereby Sentinel-1 provides horizontally polarized (HH) data and Advanced SCATterometer (ASCAT) provides vertically polarized (VV) data. The co-polarized ratio (VV/HH) is used to detect the presence of melt ponds on landfast sea ice in the Canadian Arctic Archipelago in 2017 and 2018. ERA-5 air temperature, and wind speed reanalysis datasets are used to establish the VV/HH threshold for pond onset detection which have been further validated by Landsat-8 reflectance. Co-polarized ratio threshold of 3 standard deviations from late winter season (April) acquisitions is used for assessing pond onset detection associated with the air temperature and wind speed data along with visual observation from Sentinel-1 and cloud-free Sentinel-2 imagery. In 2017, the pond onset detection rate percentages were 70.59% for FYI and 92.3% for MYI. Results suggest that this method, because of its dual-platform application, has potential for providing large-area coverage estimation of sea ice melt pond onset timing using different earth observation satellites.

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