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Section 1: Publication
Publication Type
Journal Article
Authorship
Attiah, G., Scott, A., and Pour, H. K.
Title
Spatially Distributed Modelling of Lake Ice Trends and Distribution in the North Slave Region, NWT, Canada
Year
2025
Publication Outlet
Water Resources Research
DOI
ISBN
ISSN
Citation
Abstract
The Canadian Lake Ice Model has been distributed and adapted to run at a fine spatial resolution ( ̃50 m) for simulating lake
ice thickness and phenology on small to medium-sized lakes for this study. The model’s capabilities are extended to simulate the
spatial variability of Lake ice thickness (LIT), Ice Cover Duration (ICD), and Lake Ice Phenology (LIP) 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 30 m grid lake surface temperature (LST) data derived from the North Slave LST dataset, along with climate
inputs from the European Centre for Medium-Range Weather Forecasts Reanalysis v5 and ECMWF (ERA5), including wind
speed, mean air temperature, relative humidity, snow depth, 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. Validation against in-situ measurements showed a root mean square deviation of 2.7 cm to 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 day/year to -0.15 day/year) over the
study period. The findings highlight the sensitivity of LIT and freeze-up dates to lake morphometry. In contrast, ice break-up
dates are primarily influenced by geographic factors such as latitude and elevation. The distributed model comprehensively
assesses lake ice variability and trends across 500 lakes under changing climate and weather conditions.
Plain Language Summary
Section 2: Additional Information
Program Affiliations
Project Affiliations
Submitters
Publication Stage
Preprint
Theme
Presentation Format
Additional Information
This is a preprint and has not been peer reviewed. Data may be preliminary.