Publication

Abstract : The presence of melt ponds can dramatically change the thermal and radiative properties of sea ice. The albedo of melt ponds is much lower than that of snow or ice, and thus affects the surface radiation balance through higher shortwave absorption. This process tends to accelerate melting of adjacent snow cover and the ice beneath. This `snow/ice albedo feedback mechanism has been examined extensively and is thought to be a vital feedback mechanism operating within the ocean-sea ice-atmosphere interface. Understanding these processes and mechanisms associated with the detection and timing of melt pond formation has become a subject of interest for observational and modeling communities, in the context of changing Arctic climate and sea ice regime shift. This study aims to develop a reliable method to detect sea ice melt pond onset (PO) from C- band Synthetic Aperture Radar (SAR) backscatter using Sentinel-1A/B (S1) and space-borne scatterometer data from ASCAT, in conjunction with station and ERA5-derived meteorological data. We showcase daily, dual-sensor, co-polarised (co-pol) backscatter ratio (VV/HH) for the north of Canadian Arctic Archipelago from 2017 and 2018using daily-coincident ASCAT VV and S1 HH data. PO is detected separately as a function of first year ice (FYI) and multi-year ice (MYI) and is found to vary spatially. The 2017 and 2018 seasonal progression from late winter to PO is investigated and time series of the co-pol ratio are analyzed. Wind speed, precipitation, and air temperature data support the detection method. PO is observed when the co-pol ratio exceeds ~2.5 to 3.0 dB. PO observations are validated with available cloud free Sentinel-2A optical imagery during the transition from melt onset to ponding. The results demonstrate the novelty and efficacy of using inter-platform dual-sensor C-band co-pol microwave backscatter for detecting pond onset over large spatial scales.