Modelling SAR Backscatter from Lake Ice under Wet Conditions using the Snow Microwave Radiative Transfer (SMRT) model
- 1University of Waterloo, Geography and Environmental Management, Canada (jmurfitt@uwaterloo.ca)
- 2H2O Geomatics
- 3Institut des Géosciences de l’Environnement, Université Grenoble Alpes
- 4Finnish Meteorological Institute
Lake ice plays a critical role in local energy balances and provides crucial socio-economic services such as travel between communities and transportation of goods during winter months. However, over the past 40 years, the number of in situ observations has declined. Additionally, increasing temperatures lead to an increasing number of melt events throughout the season, resulting in the formation of more snow ice and slush layers. The increase in wet ice conditions poses a challenge in monitoring lake ice using active microwave technologies (e.g., synthetic aperture radar) and can be a risk to those who use ice cover as an essential travel route. This study focuses on Lake Oulujärvi in Finland during the 2020-2021 ice season. Using the snow microwave radiative transfer (SMRT) model, backscatter was modelled using observations of dry and wet conditions from the field. Snow density, snow depth, microstructure data, and ice thickness data collected during the field campaign helped parameterize the Snow Microwave Radiative Transfer (SMRT) model. Simulations under dry conditions showed that increasing roughness at the ice-water interface had the largest increase in backscatter. However, when the water content of the overlying snow layers increased, the roughness of the interface with the highest moisture content became the dominant interface impacting backscatter. Melt-freeze events throughout the ice season had a prolonged impact on backscatter resulting in increases of >3.69 dB. Larger increases in backscatter due to higher moisture were a result of larger dielectric contrasts created between overlying dry snow on slush layers. Improved understanding of the impact of wet conditions on backscatter can help to improve the monitoring of hazardous lake ice conditions and aid in the further development of inversion models for lake ice properties.
How to cite: Murfitt, J., Duguay, C., Picard, G., and juha.lemmetyinen@fmi.fi, J.: Modelling SAR Backscatter from Lake Ice under Wet Conditions using the Snow Microwave Radiative Transfer (SMRT) model, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-10182, https://doi.org/10.5194/egusphere-egu23-10182, 2023.