https://doi.org/10.1029/2025WR040216

The Canadian Lake Ice Model has been adapted and distributed at a high spatial resolution (∼50 m) to simulate Lake Ice Thickness (LIT) and phenology across small to medium-sized lakes in this study. The model was applied to simulate the spatial variability of LIT, Ice Cover Duration (ICD), and Lake Ice Phenology across 500 predominantly small to medium-sized lakes in the North Slave Region (NSR) of the Northwest Territories (NWT), Canada, from 1984 to 2022. The model utilizes a 30 m grid lake surface temperature (LST) data set derived from the North Slave LST data set, along with climate inputs from the European Center for Medium-Range Weather Forecasts Reanalysis v5 (ERA5), including wind speed, relative humidity, snowfall, and cloud cover. These inputs provide surface fluxes to the model, driving its unsteady heat equation to produce daily LIT, annual ICD, and annual freeze-up and break-up dates on a ∼50 m grid resolution. Validation against in situ measurements shows a root mean square deviation of 2.7–7 cm for LIT. Trend analysis revealed a significant decline in LIT (−0.26 cm/year to −0.10 cm/year) and ICD (−0.40 days/year to −0.15 days/year). The highest rates of LIT decline are observed in the early and later months of ice formation. Freeze-up timings are primarily influenced by depth, while geographic factors such as latitude and elevation affect break-up timing in the NSR. This distributed modeling approach provides a robust assessment of lake ice variability and trends under changing climate and weather conditions.

https://doi.org/10.1029/2025WR040216