Abstract. Lake surface temperature (LST) is an important attribute that highlights regional weather and climate variability and trends. The spatial resolution and thermal sensors on Landsat platforms provide the capability of monitoring the temporal and spatial distribution of lake surface temperature on small- to medium-sized lakes. In this study, a retrieval algorithm was applied to the thermal bands of Landsat archives to generate a LST dataset (North Slave LST dataset) for 535 lakes in the North Slave Region (NSR) of the Northwest Territories (NWT), Canada, for the period of 1984 to 2021. North Slave LST was retrieved from Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), and Landsat 8 Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS); however, most of the dataset was created from the thermal bands of Landsat 5 (43 %) due to its longevity (1984–2013). Cloud masks were applied to Landsat images to eliminate cloud cover. In addition, a 100 m inward buffer was applied to lakes to prevent pixel mixing with shorelines. To evaluate the algorithm applied, retrieved LST was compared with in situ data and Moderate Resolution Imaging Spectroradiometer (MODIS) LST observations. A good agreement was observed between in situ observations and North Slave LST, with a mean bias of 0.12 ∘C and a root mean squared deviation (RMSD) of 1.7 ∘C. The North Slave LST dataset contains more available data for warmer months (May to September; 57.3 %) compared to colder months (October to April). The average number of images per year for each lake across the NSR ranged from 20 to 45. The North Slave LST dataset, available at https://doi.org/10.5683/SP3/J4GMC2 (Attiah et al., 2022), will provide communities, scientists, and stakeholders with spatial and temporal changing temperature trends on lakes for the past 38 years.

Abstract. Lake surface temperature (LST) is an important attribute that highlights regional weather and climate variability and trends. The spatial resolution and thermal sensors on Landsat platforms provide the capability of monitoring the temporal and spatial distribution of lake surface temperature on small- to medium-sized lakes. In this study, a retrieval algorithm was applied to the thermal bands of Landsat archives to generate a LST dataset (North Slave LST dataset) for 535 lakes in the North Slave Region (NSR) of the Northwest Territories (NWT), Canada, for the period of 1984 to 2021. North Slave LST was retrieved from Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper Plus (ETM+), and Landsat 8 Operational Land Imager (OLI) and the Thermal Infrared Sensor (TIRS); however, most of the dataset was created from the thermal bands of Landsat 5 (43 %) due to its longevity (1984–2013). Cloud masks were applied to Landsat images to eliminate cloud cover. In addition, a 100 m inward buffer was applied to lakes to prevent pixel mixing with shorelines. To evaluate the algorithm applied, retrieved LST was compared with in situ data and Moderate Resolution Imaging Spectroradiometer (MODIS) LST observations. A good agreement was observed between in situ observations and North Slave LST, with a mean bias of 0.12 ∘C and a root mean squared deviation (RMSD) of 1.7 ∘C. The North Slave LST dataset contains more available data for warmer months (May to September; 57.3 %) compared to colder months (October to April). The average number of images per year for each lake across the NSR ranged from 20 to 45. The North Slave LST dataset, available at https://doi.org/10.5683/SP3/J4GMC2 (Attiah et al., 2022), will provide communities, scientists, and stakeholders with spatial and temporal changing temperature trends on lakes for the past 38 years.

This study analyzed lake surface temperature (LST) trends and spatial distribution across 535 predominantly small to medium lakes across the North Slave Region (NSR) of the Northwest Territories (NWT), Canada. The NWT is characterized by a vast number of lakes covering a significant portion of its spatial extent. However, there is limited knowledge of how LST responds to climate warming in this region. To address this, LST was analyzed in four distinct periods: open water season (OW), ice cover season (IC), and the transitional months of May (TM) and October (TO). LSTs from 1984 to 2021 were retrieved from a lake-specific satellite-derived LST dataset (North Slave LST). LST trend distribution and relationships were analyzed using the Mann-Kendall test and a multilinear regression model. The analysis revealed an overall increase in LST, with average rates (max) of 0.03 °C/year (0.05 °C/year), 0.03 °C/year (0.06 °C/year), and 0.13 °C/year (0.27 °C/year) for OW, TM, and TO, respectively accross study lakes. A faster rate of change was observed in October compared to other periods. Results indicated significant increases in LST for 411 lakes (77%) during OW, 418 lakes (78%) during TO, and 490 lakes (92%) during TM. The spatial distribution and magnitude of LST change were primarily influenced by geographical than morphometric properties. The analysis demonstrated later freeze-up (0.20 day/year) and earlier break-up (−0.17 day/year) of lake ice across the NSR.