Detailed observations of thermal structure over an entire winter in a large lake reveal the presence of large (10–20 m) overturns under the ice, driven by diurnal solar heating. Convection can occur in the early winter, but the most vigorous convection occurred near the end of winter. Both periods are when our lake ice model suggest thinner ice that would have been transparent. This under‐ice convection led to a deepening of the mixed layer over time, consistent with previous short‐term studies. During periods of vigorous convection under the ice at the end of winter, the dissolved oxygen had become supersaturated from the surface to 23 m below the surface, suggesting abundant algal growth. Analysis of our high‐frequency observations over the entire winter of 2015 using the Thorpe‐scale method quantified the scale of mixing. Furthermore, it revealed that changes in oxygen concentrations are closely related to the intensity of mixing.

Shallow lakes, with depths less than ca. 3.5–4 m, are a ubiquitous feature of the Arctic Alaskan Coastal Plain, covering up to 40% of the land surface. With such an extended areal coverage, lakes and their ice regimes represent an important component of the cryosphere. The duration of the ice season has major implications for the regional and local climate, as well as for the physical and biogeochemical processes of the lakes. With day and night observations in all weather conditions, synthetic aperture radar (SAR) sensors provide year-round acquisitions. Monitoring the evolution of radar backscatter (σ°) is useful for detecting the timing of the beginning and end of the ice season. Analysis of the temporal evolution of C-band σ° from Advanced Synthetic Aperture Radar (ASAR) Wide Swath and RADARSAT-2 ScanSAR, with a combined frequency of acquisitions from two to five days, was employed to evaluate the potential of SAR to detect the timing of key lake-ice events. SAR observations from 2005 to 2011 were compared to outputs of the Canadian Lake Ice Model (CLIMo). Model simulations fall within similar ranges with those of the SAR observations, with a mean difference between SAR observations and model simulations of only one day for water-clear-of-ice (WCI) from 2006 to 2010. For freeze onset (FO), larger mean differences were observed. SAR analysis shows that the mean FO date for these shallow coastal lakes is 30 September and the mean WCI date is 5 July. Results reveal that greater variability existed in the mean FO date (up to 26 days) than in that of melt onset (MO) (up to 12 days) and in that of WCI (6 days). Additionally, this study also identifies limitations and provides recommendations for future work using C-band SAR for monitoring the lake- ice phenology of shallow Arctic lakes.

Lake ice is an important component in understanding the local climate as changes in temperature have an impact on the timing of key ice phenology events. In recent years, there has been a decline in the in-situ monitoring of lake ice events in Canada and microwave remote sensing imagery from synthetic aperture radar (SAR) is more widely used due to the high spatial resolution and response of backscatter to the freezing and melting of the ice surface. RADARSAT-2 imagery was used to develop a threshold-based method for determining lake ice events for mid-latitude lakes in Central Ontario from 2008 to 2017. Estimated lake ice phenology events are validated with ground-based observations and are compared against the Moderate Resolution Imaging Spectroradiometer (MODIS band 2). The threshold-based method was found to accurately identify 12 out of 17 freeze events and 13 out of 17 melt events from 2015–2017 when compared to ground-based observations. Mean absolute errors for freeze events ranged from 2.5 to 10.0 days when compared to MODIS imagery while the mean absolute error for water clear of ice (WCI) ranged from 1.5 to 7.1 days. The method is important for the study of mid-latitude lake ice due to its unique success in detecting multiple freeze and melting events throughout the ice season.

Arctic snow and ice cover are vital indicators of climate variability and change, yet while the Arctic shows overall warming and dramatic changes in snow and ice cover, the response of these high-latitude regions to recent climatic change varies regionally. Although previous studies have examined changing snow and ice separately, examining phenology changes across multiple components of the cryosphere together is important for understanding how these components and their response to climate forcing are interconnected. In this work, we examine recent changes in sea ice, lake ice, and snow together at the pan-Arctic scale using the Interactive Multisensor Snow and Ice Mapping System 24 km product from 1997–2019, with a more detailed regional examination from 2004–2019 using the 4 km product. We show overall that for sea ice, trends toward earlier open water (−7.7 d per decade, p<0.05) and later final freeze (10.6 d per decade, p<0.05) are evident. Trends toward earlier first snow-off (−4.9 d per decade, p<0.05), combined with trends toward earlier first snow-on (−2.8 d per decade, p<0.05), lead to almost no change in the length of the snow-free season, despite shifting earlier in the year. Sea ice-off, lake ice-off, and snow-off parameters were significantly correlated, with stronger correlations during the snow-off and ice-off season compared to the snow-on and ice-on season. Regionally, the Bering and Chukchi seas show the most pronounced response to warming, with the strongest trends identified toward earlier ice-off and later ice-on. This is consistent with earlier snow-off and lake ice-off and later snow-on and lake ice-on in west and southwest Alaska. In contrast to this, significant clustering between sea ice, lake ice, and snow-on trends in the eastern portion of the North American Arctic shows an earlier return of snow and ice. The marked regional variability in snow and ice phenology across the pan-Arctic highlights the complex relationships between snow and ice, as well as their response to climatic change, and warrants detailed monitoring to understand how different regions of the Arctic are responding to ongoing changes.

Lake ice models are a vital tool for studying the response of ice-covered lakes to changing climates throughout the world. The Canadian Lake Ice Model (CLIMo) is a one-dimensional freshwater ice cover model that simulates Arctic and sub-Arctic lake ice cover well. Modelling ice cover in temperate regions has presented challenges due to the differences in ice composition between northern and temperate region lake ice. This study presents a comparison of measured and modelled ice regimes, with a focus on refining CLIMo for temperate regions. The study sites include two temperate region lakes (MacDonald Lake and Clear Lake, Central Ontario) and two High Arctic lakes (Resolute Lake and Small Lake, Nunavut) where climate and ice cover information have been recorded over three seasons. The ice cover simulations were validated with a combination of time lapse imagery, field measurements of snow depth, snow density, ice thickness and albedo data, and historical ice records from the Canadian Ice Database (for Resolute Lake). Simulations of High Arctic lake ice cover show good agreement with previous studies for ice-on and ice-off dates (MAE 6 to 8 days). Unadjusted simulations for the temperate region lakes show good ice-on timing, but an under-representation of ice thickness, and earlier complete ice-off timing (~3 to 5 weeks). Field measurements were used to adjust the albedo values used in CLIMo, which resulted in improvements to both simulated ice thickness (~3 cm MAE compared to manual measurements), and ice-off timing, within 0 to 7 days (2 days MAE) of observations. These findings suggest regionally specific measurements of albedo can improve the accuracy of lake ice simulations, which further our knowledge of the response of temperate and High Arctic lake ice regimes to climate conditions.