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Arctic lakes are sensitive to climate change, and the timing and duration of ice presence and absence (i.e., ice phenology) on the lake surface can be used as a climate indicator. In this study of Linnévatnet, one of the largest lakes on Svalbard, we compare inferences of lake ice duration from satellite data with continuously monitored lake water temperature and photographs from automatic cameras. Visible surface reflectance data from the moderate-resolution imaging spectroradiometer (MODIS) were used to observe the change in the lake-wide mean surface reflectance of Linnévatnet from 2003–2019, and smoothing splines were applied to the to determine the date of summer ice-off (also called "break-up end"—BUE). Similarly, BUE and fall ice-on (or "freeze-up end"—FUE) were determined from lake-wide mean time series of Sentinel-1 microwave backscatter from 2014–2019. Overall, the ice timing dates identified from the satellite observations agree well with the in-situ observations (RMSE values of approximately 2–7 days for BUE and FUE, depending on the method and in-situ dataset), lending confidence to the accuracy of remote sensing of lake ice phenology in remote Arctic regions. Our observations of Linnévatnet indicate that BUE dates do not have a significant trend, while FUE dates have been occurring approximately 1.5 days later per year during the study period. These results support an overall decrease in annual duration of lake ice cover in this part of Svalbard. [ABSTRACT FROM AUTHOR]

In most of Environment and Climate Change Canada's (ECCC) current operational systems, inland water physical processes are simulated using a simple water scheme. Water surface temperatures and ice cover fractions are updated daily using analyses. However, ECCC recognizes the need for interactive lakes in its weather and environmental prediction systems, such as those used to forecast surface conditions and floods. As a first step toward this goal, the current study evaluates the impact of the Canadian Small Lake Model (CSLM) in an offline context on surface water temperature, ice phenology and near‐surface atmospheric conditions. The use of CSLM increases lake surface temperatures and decreases its RMSE during ice‐free months, which has a direct impact on the 2‐m air temperature by reducing the cold bias observed in the simulation without CSLM, particularly over larger lakes. CSLM improves ice cover in subgrid lakes, while having a neutral impact on intermediate lakes. On large lakes, CSLM tends to degrade ice cover simulation in southernmost lakes, while improving ice cover in northernmost lakes. The increased lake ice cover in CSLM, particularly over subgrid lakes and in the northern latitudes, has a strong impact on humidity fluxes at the surface during wintertime with a near‐interruption of evapotranspiration over lakes. In summertime, increased water temperature with CSLM leads to a 38% increase in evapotranspiration. With these results, it is expected that the synergy of CSLM and lake‐related observations will improve the simulation and initialization of lake conditions in ECCC's systems. Plain Language Summary: Compared to most surrounding land, lakes are a higher source of humidity. Their slower response to atmospheric temperature changes induces a warming of the lower atmosphere in winter and a cooling in summer. Lakes can thus have a strong impact on the local climate. Their inclusion in Earth System Models allows for simulated lakes to exchange interactively with the atmosphere and the rest of the water cycle, which is particularly important in Canada since it is home to 62% of all lakes around the world. At Environment and Climate Change Canada (ECCC), the Canadian Small Lake Model (CSLM) has recently been developed to respond to this need. The current study evaluates the impact of lakes simulated by CSLM on lake surface (ice cover, water temperature) and near‐surface atmospheric conditions (temperature, humidity) compared to the current setup in ECCC's systems, in which lakes are not interactive. CSLM outperforms non‐interactive lakes, especially on small lakes: it improves summertime lake water surface temperature and wintertime ice coverage, which leads to an improvement of near‐surface temperatures. However, since CSLM was developed specifically to simulate small lakes, it struggles for very large lakes. This limitation could be resolved through the use of observations. Key Points: Environment and Climate Change Canada recognizes the need for interactive lakes in its weather and environmental prediction systemsThe Canadian Small Lake Model (CSLM) outperforms the current setup on most lakes, particularly on subgrid lakes, in offline modeIt is expected that the synergy of CSLM and lake‐related observations will improve the simulation and initialization of lake conditions [ABSTRACT FROM AUTHOR]

Ice plays key roles in regulating hydrological, ecological, biogeochemical, and socioeconomic functions of lakes. Long-term in situ lake ice phenological records indicate that lake ice is trending toward later freeze-up, earlier breakup, and a shorter ice duration. Parallel to study of lake ice using in situ records and process-based models, satellite remote sensing can expand our understanding of lake ice change over large spatial scales. However, most remote sensing studies have focused on large lakes or short periods of time, which may not robustly represent changes over multidecadal time periods or in the much more numerous small lakes. Here, we present a random forest model, Sensitive Lake Ice Detection (SLIDE), to accurately extract ice conditions from Landsat TM, ETM+, and OLI images. We trained the model using a manually labeled lake ice dataset (1089 labeled areas over 995 lakes globally). Our results show that our model achieves accurate classification between ice/snow and water (accuracy: 97.8%, kappa coefficient: 95.5%). Comparing Landsat-derived ice cover with in situ ice conditions, we show that our model produces less bias, lower RMSE, and higher kappa than does the Landsat snow/ice flag from the quality assessment band. This is especially true during the transitional period surrounding the ice on and off dates reported from in situ (mean bias −7.3% from our model, −17.3% from the Landsat quality band). Our results demonstrate the feasibility of mining the rich Landsat archive to study lake ice dynamics and of better flagging ice-affected lake observations. [ABSTRACT FROM AUTHOR]

Snow and ice were monitored by thermistor-string-based Snow and Ice Mass Balance Array (SIMBA) in Lake Orajärvi in northern Finland. An existing automatic SIMBA-algorithm was further developed to derive air/snow, snow/ice and ice/water interfaces based on the SIMBA environment temperature (ET) profiles. The identified interfaces agreed with in situ observations made in 2011/12 winter season. The method was capable to identify upward-moving snow/ice interface that was also visible from SIMBA heating temperature (HT) profiles, which responds to differences in the thermal diffusivities of air, snow, ice and water. The SIMBA data obtained in winters 2017/18 and 2018/19 were used to investigate snow and ice mass balance. An upward-moving snow/ice interface was detected as a result of meteoric ice (snow ice and superimposed ice) formation. Snow contributed to granular lake ice formation up to 40–55% of the total ice thickness on the seasonal mean. Heavy snowfalls and low air temperature in early winter are favourable for granular ice formation. The seasonal mean snow depth on nearby land was 2.7–2.9 times of that on the lake. The estimation of freeboard from snow and ice mass-balance measurement is sensitive to the snow density. Accurate ice freeboard calculation is still a challenge.

Antarctic lakes with perennial ice covers provide the opportunity to investigate in-lake processes without direct atmospheric interaction, and to study their ice-cover sensitivity to climate conditions. In this study, a numerical model – driven by radiative, atmospheric and turbulent heat fluxes from the water body beneath the ice cover – was implemented to investigate the impact of climate change on the ice covers from two Antarctic lakes: west lobe of Lake Bonney (WLB) and Crooked Lake. Model results agreed well with measured ice thicknesses of both lakes (WLB – RMSE= 0.11 m over 16 years of data; Crooked Lake – RMSE= 0.07 m over 1 year of data), and had acceptable results with measured ablation data at WLB (RMSE= 0.28 m over 6 years). The differences between measured and modeled ablation occurred because the model does not consider interannual variability of the ice optical properties and seasonal changes of the lake's thermal structure. Results indicate that projected summer air temperatures will increase the ice-cover annual melting in WLB by 2050, but that the ice cover will remain perennial through the end of this century. Contrarily, at Crooked Lake the ice cover becomes ephemeral most likely due to the increase in air temperatures.

Abstract In most of Environment and Climate Change Canada's (ECCC) current operational systems, inland water physical processes are simulated using a simple water scheme. Water surface temperatures and ice cover fractions are updated daily using analyses. However, ECCC recognizes the need for interactive lakes in its weather and environmental prediction systems, such as those used to forecast surface conditions and floods. As a first step toward this goal, the current study evaluates the impact of the Canadian Small Lake Model (CSLM) in an offline context on surface water temperature, ice phenology and near‐surface atmospheric conditions. The use of CSLM increases lake surface temperatures and decreases its RMSE during ice‐free months, which has a direct impact on the 2‐m air temperature by reducing the cold bias observed in the simulation without CSLM, particularly over larger lakes. CSLM improves ice cover in subgrid lakes, while having a neutral impact on intermediate lakes. On large lakes, CSLM tends to degrade ice cover simulation in southernmost lakes, while improving ice cover in northernmost lakes. The increased lake ice cover in CSLM, particularly over subgrid lakes and in the northern latitudes, has a strong impact on humidity fluxes at the surface during wintertime with a near‐interruption of evapotranspiration over lakes. In summertime, increased water temperature with CSLM leads to a 38% increase in evapotranspiration. With these results, it is expected that the synergy of CSLM and lake‐related observations will improve the simulation and initialization of lake conditions in ECCC's systems.

Synthetic aperture radar (SAR) is a valuable tool for lake ice monitoring. The recently proposed SAR configuration for Earth observation called compact polarimetric (CP) SAR could be a good compromised choice between conventional (single or dual) and fully polarimetric (FP) SAR for operational ice applications, including lake ice. Given its enhanced radar target information compared with conventional SAR systems over wider swath coverage compared with FP SAR, CP systems could play important role in the new generation of Earth observation systems. Herein, we study the evolution of CP SAR parameters from simulated CP SAR data in relation to early ice growth. Focus of the study is on four lakes located in Cornwallis Island, Canadian Central Arctic. We adopt parameters extracted from dual circular polarimetric and right circular transmit, linear (horizontal and vertical) receive configurations. In this study, we consider the ice thickness calculated from an established empirical model. Meteorological and ice climatological data were used to support the analysis. Results demonstrated a potential connection between a number of CP parameters and lake ice growth. Furthermore, we were able to highlight the relationship between the density of air bubbles in ice layer and the intensity of volume scattering mechanism, leading to the identification of lakes with increased gas production activities. Thus, differences between lakes in terms of density of air bubbles were detected and statistically evaluated. [ABSTRACT FROM AUTHOR]

Within Arctic deltas, surficial hydrologic connectivity of lakes to nearby river channels influences physical processes like sediment transport and ice phenology as well as biogeochemical processes such as photochemistry. As the Arctic hydrologic cycle is impacted by climate change, it is important to quantify temporal variability in connectivity. However, current connectivity detection methods are either spatially limited due to data availability constraints or have been applied at only a single time. Additionally, the relationship between connectivity and lake ice is still poorly quantified. In this study, we present a multitemporal classification of functional lake connectivity in the Colville River Delta, Alaska. We introduce a connectivity detection algorithm based on remote sensing of high sediment river water recharge that is expandable to other high sediment Arctic deltas. We compare results to three existing data sets, producing 64.4%, 75.8%, and 85.2% lake classification accuracy. Mismatches between the data sets are often due to inconsistencies in methodology or definition of connectivity. Connectivity varies temporally in about 10% of studied lakes and correlates strongly with discharge and lake elevation, supporting the idea that future changes in discharge will be a driver of changes in connectivity. Highly connected lakes start and end ice break up an average of 26 and 17 days earlier, respectively, compared to lakes that are poorly connected. Because spring and summer ice conditions drive Arctic lake photochemistry processes, our research suggests that surface connectivity is an important parameter to consider when studying biogeochemistry of Arctic delta lakes. Plain Language Summary: Arctic deltas contain a complex tapestry of channels and lakes. Lakes can be isolated from channels or connected to channels—either by feeder channels, other lakes, or by water movement over land during flooding. This connectivity is important because it impacts the movement of sediment, light penetration through water, and when lake ice forms and disappears. While we anticipate future changes in connectivity due to climate change, our ability to monitor connectivity is limited to individual deltas or single instances in time. Additionally, the relationship between lake ice and connectivity is poorly understood. In this study, we used a method based on satellite observations of sediment in water to examine lake connectivity variations within the Colville River Delta, Alaska. We found that most lakes stay connected or disconnected, but that about 10% of lakes have variable connectivity. These lakes are more likely to be connected when river discharge is high. Additionally, lake ice tends to break up earlier and last for a shorter period of time in connected lakes. Because lake ice conditions drive chemical interaction between sunlight and organic compounds in the water, connectivity is important to consider when studying the biology and chemistry of Arctic delta lakes. Key Points: We have developed an algorithm using optical properties of lakes and channels to detect lake‐to‐channel connectivity in an Arctic deltaWe show that this algorithm can be used to detect lakes where functional connectivity varies based on maximum summer dischargeDifferences in functional connectivity drive lake ice phenology, which is likely important for photochemical processes [ABSTRACT FROM AUTHOR]

Long‐term lake ice phenological records from around the Northern Hemisphere provide unique sensitive indicators of climatic variations, even prior to the existence of physical meteorological measurement stations. Here, we updated ice phenology records for 60 lakes with time‐series ranging from 107–204 years to provide the first re‐assessment of Northern Hemispheric ice trends since 2004 by adding 15 additional years of ice phenology records and 40 lakes to our study. We found that, on average, ice‐on was 11.0 days later, ice‐off was 6.8 days earlier, and ice duration was 17.0 days shorter per century over the entire record for each lake. Trends in ice‐on and ice duration were six times faster in the last 25‐year period (1992–2016) than previous quarter centuries. More extreme events in recent decades, including late ice‐on, early ice‐off, shorter periods of ice cover, or no ice cover at all, contribute to the increasing rate of lake ice loss. Reductions in greenhouse gas emissions could limit increases in air temperature and abate losses in lake ice cover that would subsequently limit ecological, cultural, and socioeconomic consequences, such as increased evaporation rates, warmer water temperatures, degraded water quality, and the formation of toxic algal blooms. Plain Language Summary: The timing of lake ice‐on and ice‐off has been observed for decades to centuries because of its importance to refrigeration, transportation, recreation, and cultural traditions. Further, the timing of lake ice is a sensitive indicator of climate as freshwater freezes at 0°C. In our study, we found that ice duration was more than two weeks shorter per century in 60 lakes distributed across the Northern Hemisphere. In the last 25‐year period, trends in ice‐on and duration were over six times faster than in previous quarter centuries. More extremely late ice‐on and early ice‐off years, in addition to years in which a lake did not freeze at all, contributed to this alarming rate of lake ice loss. Mitigation of greenhouse gas emissions is necessary to preserve the existence of annual lake ice cover within this century. Key Points: Lake ice‐on was 11 days later, ice‐off was 7 days earlier, and ice duration was 17 days shorter per century for each lakeTrends in ice‐on and ice duration were six times faster in the last 25‐year period (1992–2016) than previous quarter centuriesIncreased frequency of extreme events, including ice‐free years and short ice durations, were found in larger lakes and warmer regions [ABSTRACT FROM AUTHOR]

Seasonal lake ice is sensitive to temperature fluctuations and long-term temperature trends. It is therefore a good indicator of climate warming, which will likely have dramatic impacts on lake ice phenology in northern latitudes. Beside the climate change aspect, lake ice data are important regarding transport and safety issues. In addition, changes in ice cover affect the ecology of the lake and water quality.A new method for accessing lake ice extent (LIE) using optical satellite data was developed at the Finnish Environment Institute. The resulting ICEmod method is based on multidimensional Gaussian distributions calculated for training data using several reflectance and thermal bands and their-related indices. Three alternative classes are provided for a lake ice pixel: (i) open water, (ii) ice cover, and (iii) cloud. The main advantages of ICEmod are the utilization of several spectral bands, inclusion of simultaneous cloud detection, definition of statistical probability for each pixel, the simplicity of processing and easy transition between different satellite sensors. This novel method is applied in the provision of the Sentinel-3 Sea and Land Surface Temperature Radiometer (SLSTR) -based 0.005° Lake Ice Extent product (LIE-NH) for the Northern Hemisphere under the Global Land Service, a component of the Copernicus Land Service.The 0.005° resolution LIE products based on ICEmod applied to SLSTR (an extensive subset corresponding to LIE-NH) were validated against high-resolution Sentinel-2 Multispectral Instrument -images covering lakes in the different parts of the Northern Hemisphere, most of them representing both open water and ice pixels. The gained overall classification accuracy is 96%. The resulting omission error for ice is 6% and omission mainly occurs in lakes where the ice is very dark and fragmented. The ICEmod method is not always able to separate dark ice from open water if there is water on the top of the dark ice, while misclassifications do not occur if the water layer is on white ice. The commission error for ice is 2.5% and is mostly related to the ambiguity in the definition of a ice-pixel: i.e. whether a 0.005° LIE pixel should be classified as ice or open water when the area within the pixel is partially ice-covered. When the lake is completely ice-covered or ice-free, the overall accuracy is 100%. According to the tentative qualitative comparison with European Space Agency Climate Change Initiative Lake Ice Cover (LIC) product, LIE-NH may provide more accurate lake ice information, and it also provides lake ice data for more than 13 000 lakes while LIC operates for 250 lakes only.

More than 50% of global lakes periodically freeze, and their lake ice phenology is sensitive to climate change. However, spatially detailed quantification of the changes in lake ice at the global scale is not available. Here, we map ice cover in >33,000 lakes throughout the North Temperate Zone (23.5°–66.5°N) using 0.55 million Landsat images from 1985 to 2020. Over this period, we found a remarkable reduction in median ice cover occurrence (ICO) (61% to 43%), which was strongly related to warming terrestrial mean surface temperatures (R2 = 0.94, p < 0.05). Lakes in Europe showed the most pronounced ice loss (median ICO decreased from 50% to 24%), and extensive lake ice losses were also detected in the northern US, and central and eastern Asia. An overall increase in ice cover was identified from P2 (1999–2006) to P3 (2007–2014) due to regional decreased temperatures associated with the "global warming hiatus." Thehigh‐resolution mapping of lake ice here provides essentialbaseline information whichcan be used to elucidate ice loss‐induced environmental and societal impacts. Plain Language Summary: Widespread reductions in lake ice have been detected recently worldwide, yet spatially detailed characterization of global lake ice is currently unavailable. Using 0.55 million Landsat satellite images from 1985 to 2020, we provide the first long‐term wall‐to‐wall mapping of lake ice cover over the entire Northern Temperate Zone, comprising >33,000 lakes representing 48% of the global lake area in total. We track spatially detailed changes in lake ice across the entire Northern Temperate Zone, and examine how ice change patterns have differed geographically and temporally in response to climate change. Key Points: We provide the first long‐term wall‐to‐wall mapping of lake ice cover over the entire Northern Temperate ZoneWe found a remarkable reduction in median ice cover occurrence (61‐43%)Extensive lake ice retreats were found in central and southern Europe, the northern US, and central and southeastern Asia [ABSTRACT FROM AUTHOR]

The Qinghai‐Tibet Plateau possesses the largest alpine lake system, which plays a crucial role in the land‐atmosphere interaction. We report first observations on the thermal and radiation regime under ice of the largest freshwater lake of the Plateau. The results reveal that freshwater lakes on the Tibetan Plateau fully mix under ice. Due to strong solar heating, water temperatures increase above the maximum density value 1–2 months before the ice break, forming stable thermal stratification with subsurface temperatures >6°C. The resulting heat flow from water to ice makes a crucial contribution to ice cover melt. After the ice breakup, the accumulated heat is released into the atmosphere during 1–2 days, increasing lake‐atmosphere heat fluxes up to 500 W m−2. The direct biogeochemical consequences of the deep convective mixing are aeration of the deep lake waters and upward supply of nutrients to the upper photic layer. Plain Language Summary: The Qinghai‐Tibet Plateau possesses the largest alpine lake system, which plays a crucial role in the land‐atmosphere interaction. Data on thermal properties of Tibetan lakes during the ice‐covered season are extremely scarce. The first observations on the thermal and radiation regime under ice of the largest freshwater lake of the Plateau reveal that freshwater (and apparently the majority of brackish) lakes gain an extremely large amount of solar radiation penetrating the highly transparent ice cover. As a result, lakes fully mix under ice and get heated up to >6°C. The accumulated heat makes a crucial contribution to ice cover melt. The quick release of the heat to the atmosphere during 1–2 days after the ice breakup strongly increases lake‐atmosphere heat fluxes, potentially affecting regional weather conditions. Warm and well‐mixed conditions are favorable for aquatic life in the extreme environment of Tibet. Key Points: An abnormal thermal regime under the ice cover of Tibetan lakes is revealedThe lakes get heated above their maximum density temperature by extremely high level of solar radiation penetrating the ice coverThe stored heat shortens the ice‐covered period and is quickly released into the atmosphere after ice‐off, affecting local climate [ABSTRACT FROM AUTHOR]

Lake ice phenology has been recorded for decades, providing us with long‐term records to investigate the impact of climate change in lakes since the Industrial Revolution. Here, we examine the trends and drivers of 18 lakes across the Northern Hemisphere, with 156–204 years of data, starting in the 1810s. We show that: (a) trends in ice phenology are faster than found by previous studies. Ice‐on is 11 days later per century, ice‐off is 9 days earlier per century, and ice cover duration is 19 days shorter per century; (b) there are significant breakpoints in the 1850s, 1870s, mid‐1890s, and mid‐1990s, after which trends in ice phenology are even faster, and associated with changing weather and climate; and (c) local air temperatures explain the most variation in ice phenology, on average 36.5%, followed by progressive climate change explaining around 17.5% on average, with teleconnection patterns explaining the least variation. Our findings support the assertion that broad‐scale climatic changes have led to more rapid lake ice loss in lakes distributed across the Northern Hemisphere, with potential widespread impacts on critical ecosystem services that lake ice provides. Plain Language Summary: Lake ice cover has been recorded for decades and has been shown to be sensitive to climatic change. Hence, we can use lake ice cover to investigate how climate change has affected lakes over the past ∼200 years. In this study, we explore 18 lakes across the Northern Hemisphere, with ice cover data starting in the 1810s. We find that ice‐on is increasingly later, ice‐off is earlier, and ice duration is shorter, with all these changes occurring at faster rates than previous studies showed. We discovered breakpoints in lake ice cover, after which the trends in lake ice phenology become faster than the trends before the breakpoints, and these breakpoints are related to changing local air temperatures and teleconnection patterns. Finally, we show that local air temperature influences the timing of ice‐on and ice‐off the most, followed by long‐term climate change and teleconnection patterns. Hence, we provide support for the statement that climate change has contributed to faster trends in ice phenology, with likely negative impacts on the important ecosystem services provided by lakes. Key Points: Trends in lake ice phenology are faster than shown in previous studies when including most recent dataSignificant breakpoints in ice phenology are associated with changing weather and climateWarmer air temperature explains most of the variation in later ice‐on and earlier ice‐off dates, in addition to shorter ice duration [ABSTRACT FROM AUTHOR]

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There are few studies where the evolution of grain orientations and crystal misorientations of neighboring grains in a polycrystalline ice sample during grain growth are analyzed. In this work, crystal orientations and misorientations were studied in two ice cylinders obtained from bidistilled water using the techniques of plastic replicas and chemical etching pits. The cylinders were grown, one through fast freezing and the other through slow freezing. It was observed that the initial crystal orientations of the grains varied from one cylinder to the other, but this did not result in significant differences in the final crystal misorientations between neighboring grains. Such crystal misorientations could be special because they are related to a coincidence sites lattice (CSL), which could be associated with low-energy grain boundaries. Therefore, the decrease in grain boundary energy during grain growth could be influenced by these special crystal misorientations. [ABSTRACT FROM AUTHOR]

As an important part of the cryosphere, lake ice is a sensitive indicator of climate change. Remote sensing technology can quickly and accurately monitor the process of its formation and decay, among which Moderate Resolution Imaging Spectroradiometer (MODIS) images are the most widely used data in the remote sensing monitoring of lake ice. The reasonable selection of monitoring methods is of great significance to grasp the dynamic process and response to climate change of lake ice. In this study, five commonly used remote sensing monitoring methods of lake ice based on MODIS MOD09GA data, including the single band threshold method (SBT), reflectance difference threshold method (RDT), normalized difference snow index method (NDSI), modified normalized difference snow index method (MNDSI) and lake ice index method (LII), were selected to compare their accuracies in extracting lake ice extent by combining them with four evaluation metrics of accuracy, precision, recall and mean intersection over union (MIoU). In addition, the ability of the high-precision LII method for extracting long time series lake ice phenology and its applicability to multiple types of lakes were verified. The results showed that compared with the NDSI method, the other four methods more easily distinguished between lake ice and lake water by setting thresholds. The SBT method and the RDT method had better extraction effects in the freezing process and the melting process, respectively. Compared with the NDSI and MNDSI methods, the LII method showed a significant improvement in lake ice extraction over the entire freeze–thaw cycle, with the smallest mean monitoring error of 1.53% for the percentage of lake ice area in different periods. Meanwhile, the LII method can be used to determine long term lake ice phenology dates and had good performance in extracting lake ice for different types of lakes on the Qinghai–Tibet Plateau with the optimal threshold interval of 0.05~0.07, which can be used for lake ice monitoring and long-term phenological studies in this region.

Landfast ice plays an important role in the nearshore hydrodynamics of large lakes, such as the dampening of surface waves and currents. In this study, previously developed landfast ice basal stress parameterizations were added to an unstructured grid hydrodynamic ice model to represent the effects of grounded ice keels and tensile strength of ice cover. Numerical experiments using this model were conducted to evaluate the development of coastal landfast ice in Lake Superior. A sensitivity study of the free parameters was conducted from December 2018 to May 2021 to cover both high and low ice cover winters in Lake Superior and was compared against observations from the United States National Ice Center. The model reproduces the annual variation in coastal landfast ice in Lake Superior, particularly in shallow nearshore areas and the semi-enclosed bays in the northern regions of the lake. Experiments also show that the growth of landfast ice is mainly controlled by the free parameter that controls the critical ice thickness for the activation of basal stress. Overall, the model tends to underestimate the extent of coastal landfast against observations.

Ice‐off dates on lakes are some of the longest phenological records in the field of ecology, and some of the best evidence of long‐term climatic change. However, there has been little investigation as to whether the date of ice‐off on a lake impacts spring and summer ecosystem dynamics. Here, I analyzed 274 years of long‐term data from eight north temperate lakes in two climate zones to address whether lakes have ecological memory of ice‐off in the subsequent summer. Five metrics were investigated: epilimnion temperatures, hypolimnion temperatures, hypolimnetic oxygen drawdown, water clarity, and spring primary productivity. The response of the metrics to ice‐off date were variable across latitude and lake type. The northern set of lakes stratified quickly following ice‐off, and early ice‐off years resulted in significantly warmer hypolimnetic temperatures. Oxygen depletion in the hypolimnion was not impacted by ice‐off date, likely because in late ice‐off years the lakes did not fully mix. In the southern lakes, ice‐off date was not correlated to the onset of stratification, with the latter being a more dominant control on hypolimnetic temperature and oxygen. The implications of these findings is that as ice‐off date trends earlier in many parts of the world, the lakes that will likely experience the largest changes in spring and summer ecosystem properties are the lakes that currently have the longest duration of lake ice. In considering a future with warmer winters, these results provide a starting point for predicting how lake ecosystem properties will change with earlier ice‐off. Plain Language Summary: Lake ice is disappearing around the world. This slow loss of winter is a clear sign of climate change, but does the date of ice‐off impact spring and summer lake processes? Untangling a memory effect of ice‐off from other factors, such as spring and summer weather, requires decades of monitoring data. Here, 274 years of lake records from eight lakes in two climate zones were analyzed to investigate whether lakes have ecological memory of ice‐off. The response of lake temperature, oxygen concentrations, and water clarity to ice‐off date were variable across latitude and lake size and type. It was found that when lakes stratify immediately following ice‐off, bottom water conditions have ecological memory of the timing of ice‐off. However, in lakes with a short duration of lake ice, this memory effect fades. The implication of this finding is that as ice‐off date trends earlier in many parts of the world, the lakes that will likely experience the largest changes in spring and summer lake ecosystem properties are the lakes that currently have the longest duration of lake ice. Key Points: Ice‐off date has variable impacts on ecosystem properties across lake type and climatic zoneLakes with a short duration of ice have little ecological memory of ice‐off dateWhen lakes stratify immediately following ice‐off, ice‐off date impacts summer ecosystem properties [ABSTRACT FROM AUTHOR]

We quantified the relationships between seasonal air temperatures and ice phenology for a 0.54 km2 boreal lake in Northwestern Ontario, Canada using a 50‐year time series (1970–2019). Significant temporal trends in the duration of ice cover (−4.0 days decade−1) occurred over the study period and both ice‐on and ice‐off dates were highly predictable from seasonal air temperatures. While temporal trends in ice‐off dates were not significant, ice‐on dates trended later by 2.2 days decade−1, and both ice‐off dates and the duration of ice‐cover became increasingly variable over the study period. For three consecutive winter seasons, we also evaluated regional variations of ice‐phenology and snow and ice‐thickness from 9 to 30 boreal lakes across a lake size gradient (0.02–26 km2) using ground based and satellite observations. Regional variation of ice‐on dates (30–45 days), ice‐off dates (10–21 days), and total duration of ice‐cover (22–38 days) between lakes displayed significant nonlinear relationships to lake size across all years. Regional variation of ice‐off dates was structured according to lake size, and appeared driven by relationships between lake size, snow thickness, and ice thickness. Multiple linear regression and generalized additive modeling approaches to predict ice‐on and ice‐off dates at the regional scale by integrating the effects of air temperature and lake size had similar performance, explaining >90% of the variance of observed. Plain Language Summary: In this study, we used a continuous 50‐year data set of air temperature and ice phenology for a single boreal lake, and a combination of ground‐based and satellite observations to examine regional variation and drivers of ice phenology across 9–30 lakes near the IISD Experimental Lakes Area, Canada. Results indicated that ice‐cover duration declined by approximately 4 days per decade, and ice‐on and ice‐off dates were highly predictable based on seasonal air temperatures. Our regional analysis indicated that the duration of ice‐cover varied by approximately 1 month even for lakes in close proximity to one another and experienced similar weather conditions. This spatial variation of ice phenology was structured along a gradient of lake size. These results provide strong evidence of regional changes in climate since the 1970s and quantify the importance of air temperature and lake size in driving the duration of ice cover at a regional scale and can be incorporated with climate projections to estimate future ice‐conditions across lakes of varying sizes. Key Points: Long‐term declines in ice‐cover duration (4 days/decade) were highly predictable from seasonal air temperaturesRegional variation of ice‐cover duration was approximately 1 month and structured by factors associated with lake sizeLake‐size effects on ice‐off dates appeared driven by variations in snow and ice thickness [ABSTRACT FROM AUTHOR]

Using the psychometric paradigm of risk in conjunction with surveys of the Michigan public (n = 638) and a regional planning organization (n = 65), we examine the perceived risk and concerns associated with underwater oil pipelines, the Enbridge Line 5 pipeline in particular, and oil spills under ice. The fate of Line 5 is heavily debated in Michigan, specifically the portion that traverses the Straits of Mackinac, which can be ice-covered for months. Scant literature examines how individuals perceive the risk associated with Line 5, its alternatives, or potential spills in open water or under ice. Here we identify considerable concern regarding both the pipeline and the potential for spills under ice on behalf of the public, and increased concern about spills under ice on behalf of the planning organization. Organization members' concerns are significantly predicted by beliefs about the difficulty in remediating spills, however not by beliefs about spills' likelihood, difficulty in detection, noticeability, or consequences. Our results identify the need to better examine and communicate the risks associated with underwater pipelines and spills, both in open water and under ice, as well as options for remediating oil captured under ice. Furthermore, we recommend the adoption of decision-making and risk governance processes that explicitly expand analysis of the social, economic and environmental tradeoffs of underwater pipelines such as Line 5. [ABSTRACT FROM AUTHOR]

The Tibetan Plateau (TP) lakes are sensitive to climate change due to its seasonal ice cover, but few studies have paid attention to the freeze-thaw process of TP lakes and its key control parameters. By combining 216 simulation experiments using the LAKE2.0 model with the observations, we evaluated the effects of ice and snow albedo, ice (Kdi) and water (Kdw) extinction coefficients on the lake ice phenology, water temperature, sensible and latent heat fluxes. The reference experiment performs well in simulating the lake temperature, with a small positive bias increasing with depth, but it underestimates the ice thickness. The increase of ice albedo, snow albedo and Kdi induce a significant decrease in water temperature. Compared with the latent heat, the sensible heat flux is more sensitive to these three parameters. The ice thickness increases almost linearly with the increase of ice albedo but decreases with the increase of Kdi. The ice thickness and frozen days vary little with Kdw, but increasing Kdw can decrease the water temperature. Compared with the ice albedo, the Kdi and snow albedo have a large effect on the number of frozen days. This study brings to light the necessity to improve the parameterizations of the TP lakes freeze-thaw process. [ABSTRACT FROM AUTHOR]

Further to systematic experiments on the flexural strength of laboratory-grown, fresh water ice loaded cyclically, this paper describes results from new experiments of the same kind on lake ice harvested in Svalbard. The experiments were conducted at −12 °C, 0.1 Hz frequency and outer-fiber stress in the range from ~ 0.1 to ~ 0.7 MPa. The results suggest that the flexural strength increases linearly with stress amplitude, similar to the behavior of laboratory-grown ice. [ABSTRACT FROM AUTHOR]

We found that a winter of abnormally low snowfall and numerous dust storms from eolian processes acting on exposed landscapes (including a major 4-day dust storm while onsite in May 2014) caused a cascade of impacts on the physical, chemical, and ecological functioning of the largest lake by volume in the High Arctic (Lake Hazen; Nunavut, Canada). MODIS imagery revealed that dust deposited in snowpacks on the lake's ice acted as light-absorbing impurities (LAIs), reducing surface reflectance and increasing surface temperatures relative to normal snowpack years, causing early snowmelt and drainage of meltwaters into the lake. LAIs remaining on the ice surface melted into the ice, causing premature candling and one of the earliest ice-offs and longest ice-free seasons on record for Lake Hazen. Meltwater inputs from snowpacks resulted in dilution of dissolved, and increased concentration of particulate bound, chemical species in Lake Hazen's upper water column. Spring inputs of nutrients increased both heterotrophy and algal productivity under the surface ice following snowmelt, with a net consumption of dissolved oxygen. As climate change continues to alter High Arctic temperatures and precipitation patterns, we can expect further changes in dust storm frequency and severity with corresponding impacts for freshwater ecosystems.

Arctic lakes are sensitive to climate change, and the timing and duration of ice presence and absence (i.e., ice phenology) on the lake surface can be used as a climate indicator. In this study of Linnévatnet, one of the largest lakes on Svalbard, we compare inferences of lake ice duration from satellite data with continuously monitored lake water temperature and photographs from automatic cameras. Visible surface reflectance data from the moderate-resolution imaging spectroradiometer (MODIS) were used to observe the change in the lake-wide mean surface reflectance of Linnévatnet from 2003–2019, and smoothing splines were applied to the to determine the date of summer ice-off (also called “break-up end”—BUE). Similarly, BUE and fall ice-on (or “freeze-up end”—FUE) were determined from lake-wide mean time series of Sentinel-1 microwave backscatter from 2014–2019. Overall, the ice timing dates identified from the satellite observations agree well with the in-situ observations (RMSE values of approximately 2–7 days for BUE and FUE, depending on the method and in-situ dataset), lending confidence to the accuracy of remote sensing of lake ice phenology in remote Arctic regions. Our observations of Linnévatnet indicate that BUE dates do not have a significant trend, while FUE dates have been occurring approximately 1.5 days later per year during the study period. These results support an overall decrease in annual duration of lake ice cover in this part of Svalbard.

Autonomous temperature data loggers were used to measure the temperature profile within a growing ice cover and in the water below. The ice formed under natural conditions over the pond. We observed the presence of distinct layers of gas bubbles throughout the ice thickness. Temperature measurements allowed us to determine growth rates (μm s−1) and cooling rates (°C s−1) of the ice and demonstrated that these bubble layers formed during the peak ice growth rates from 0.58 to 0.92 µm s−1. The growth rates, leading to the formation of layers of bubbles, were more than an order of magnitude lower than for bubbles produced in controlled laboratory conditions (from 3 to 80 µm s−1). This observation introduces the possibility that solid impurities play a role in natural waters and that they must lower the limit of growth rates required for bubble occurrence. Data revealed a decrease in ice growth rates while cooling rates increased. We interpret this observation as an effect of the heat flux from the water to the ice (8.34–34.11 W m−2), and of gas concentration changes in the water below. Calculations of the ice thickness using traditional methods showed the necessity to include the heat flux from the water to the ice and the effect of gas bubbles within the ice and near the ice–water interface.

This article is an attempt to analyse and compare several selected parameters regarding ice phenomena using the correlation analysis of two lakes, which are benchmark lakes located in the central part of the Kashubian Lakeland. These lakes are: Raduńskie Górne, a larger one (387.2 hm2) and Ostrzyckie, a smaller one covering an area of 308.0 hm2. The analysis covered measurement sequences for the period 1971–2010. The material for analysis regarding data on ice phenomena on Lake Raduńskie Górne was obtained from the University of Gdańsk Limnological Station in Borucino while the data for Lake Ostrzyckie was obtained from the Institute of Meteorology and Water Management (IMGW). Relations between the following parameters of the ice regime were analysed: duration of the ice phenomena, duration of the ice cover, average and maximum thickness of the ice cover. The analysis and data comparisons have revealed that there are strong and very strong relations between the analysed parameters, which made it possible to develop proper statistical models. Hence, should there be a lack of data on the ice-cover pattern for one of these lakes it is possible to recreate them using the elaborated empirical models and data for the other.

The Tibetan Plateau (TP) lakes are sensitive to climate change due to ice-albedo feedback, but almost no study has paid attention to the ice albedo of TP lakes and its potential impacts. Here we present a recent field experiment for observing the lake ice albedo in the TP, and evaluate the applicability of the Moderate Resolution Imaging Spectroradiometer (MODIS) products as well as ice-albedo parameterizations. Most of the observed lake ice albedos on TP are

Snow and ice were monitored by thermistor-string-based Snow and Ice Mass Balance Array (SIMBA) in Lake Orajärvi in northern Finland. An existing automatic SIMBA-algorithm was further developed to derive air/snow, snow/ice and ice/water interfaces based on the SIMBA environment temperature (ET) profiles. The identified interfaces agreed with in situ observations made in 2011/12 winter season. The method was capable to identify upward-moving snow/ice interface that was also visible from SIMBA heating temperature (HT) profiles, which responds to differences in the thermal diffusivities of air, snow, ice and water. The SIMBA data obtained in winters 2017/18 and 2018/19 were used to investigate snow and ice mass balance. An upward-moving snow/ice interface was detected as a result of meteoric ice (snow ice and superimposed ice) formation. Snow contributed to granular lake ice formation up to 40–55% of the total ice thickness on the seasonal mean. Heavy snowfalls and low air temperature in early winter are favourable for granular ice formation. The seasonal mean snow depth on nearby land was 2.7–2.9 times of that on the lake. The estimation of freeboard from snow and ice mass-balance measurement is sensitive to the snow density. Accurate ice freeboard calculation is still a challenge. [ABSTRACT FROM AUTHOR]

High-resolution lake ice/water observations retrieved from satellite imagery through efficient, automated methods can provide critical information to lake ice forecasting systems. Synthetic aperture radar (SAR) data is well-suited to this purpose due to its high spatial resolution (approximately 50 m). With recent increases in the volume of SAR data available, the development of automated retrieval methods for these data is a priority for operational centres. However, automated retrieval of ice/water data from SAR imagery is difficult, due to ambiguity in ice and open water signatures, both in terms of image tone and in terms of parameterized texture features extracted from these images. Convolutional neural networks (CNNs) can learn features from imagery in an automated manner, and have been found effective in previous studies on sea ice concentration estimation from SAR. In this study the use of CNNs to retrieve ice/water observations from dual-polarized SAR imagery of two of the Laurentian Great Lakes, Lake Erie and Lake Ontario, is investigated. For data assimilation, it is crucial that the retrieved observations are of high quality. To this end, quality control measures based on the uncertainty of the CNN output to eliminate incorrect retrievals are discussed and demonstrated. The quality control measures are found to be effective in both dual-polarized and single-polarized retrievals. The ability of the CNN to downscale the coarse resolution training labels is demonstrated qualitatively. [ABSTRACT FROM AUTHOR]

Extreme climate events can have significant consequences on ecosystems and by extension human populations. Over 50 million of the world's lakes typically freeze each winter, and the absence of winter ice cover, in lakes where ice has historically been present, can be characterized as an extreme event. We quantified the effects of extreme climate events on lake ice cover using 78‐year ice records from 122 lakes to show that (1) extreme ice‐free years are becoming more frequent and severe, (2) winter air temperature is a significant predictor of ice cover that was driven by large‐scale climate oscillations, (3) extremes in temperature are closely related to extremes in ice cover, and (4) ice‐free years are forecasted to result in significant loss of ice‐cover in the future. Without drastic reductions in carbon emissions, we can expect the widespread loss of lake ice cover could have significant socioeconomic and biological implications. Plain Language Summary: Climate change is expected to have a large impact on humans and our natural systems. Freshwater lakes are an important resource and each year, millions around the world freeze during the winter months. However, climate change is expected to threaten the freezing of some of these lakes. We explored 122 lakes that typically freeze over winter and that had records of freeze/thaw since 1939. We asked, do extremes in winter air temperature affect extremes in lake ice cover and what would that mean for the future? Winter air temperature was found to closely predict ice‐free years for lakes. Years with abnormally hot winters were also years where many lakes remained ice‐free. Projecting into the future, we predicted that lakes will continue to experience more ice‐free years. With a reduction in carbon emissions, there will be a modest increase in ice‐free years, but if carbon emissions continue as they are currently, there could be a large increase in ice‐free lakes. This study highlights lake ice as another victim of climate change. The loss of lake ice will have impacts to natural systems and also socioeconomic implications for human populations that are dependent on it. Key Points: Observed recent increases in ice‐free years for 122 lakes since 1939Extremes in winter air temperature were observed to closely relate to extremes in ice‐free cover for lakesUsing climate change scenarios, ice‐free years for lakes are predicted to increase significantly in the next decades [ABSTRACT FROM AUTHOR]

Ice cover plays a critical role in physical, biogeochemical, and ecological processes in lakes. Despite its importance, winter limnology remains relatively understudied. Here, we provide a primer on the predominant drivers of freshwater lake ice cover and the current methodologies used to study lake ice, including in situ and remote sensing observations, physical based models, and experiments. We highlight opportunities for future research by integrating these four disciplines to address key knowledge gaps in our understanding of lake ice dynamics in changing winters. Advances in technology, data integration, and interdisciplinary collaboration will allow the field to move toward developing global forecasts of lake ice cover for small to large lakes across broad spatial and temporal scales, quantifying ice quality and ice thickness, moving from binary to continuous ice records, and determining how winter ice conditions and quality impact ecosystem processes in lakes over winter. Ultimately, integrating disciplines will improve our ability to understand the impacts of changing winters on lake ice. Plain Language Summary: Lakes are experiencing accelerated rates of warming, including shorter seasonal duration of ice cover, later ice‐on, earlier ice‐off, and in some years no ice cover at all. Lake ice has been historically studied independently by four subdisciplines: observations by in situ and remote sensing scientists, controlled mesocosm experiments by limnologists, and process‐based models by physical modelers. Here, we highlight opportunities for collaboration between disciplines and provide guidelines to successfully integrate the disciplines to tackle the most urgent questions surrounding lake ice loss in warming climates. Key Points: Ripe opportunity to merge disciplines and harmonize data streams to further understand lake ice dynamics in changing wintersDevelop integrated plans for future data collection by moving from ice cover and phenology to multifaceted descriptions of ice conditionsOperationalize development of skill sets to work in multidisciplinary teams by constructing a workforce and developing a common language [ABSTRACT FROM AUTHOR]

Lake Hazen, the High Arctic's largest lake, has received an approximately 10-fold increase in glacial meltwater since its catchment glaciers shifted from net mass gain to net mass loss in 2007 common era (CE), concurrent with recent warming. Increased glacial meltwater can alter the ecological functioning of recipient aquatic ecosystems via changes to nutrient budgets, turbidity and thermal regimes. Here, we examine a rare set of five high-resolution sediment cores collected in Lake Hazen between 1990 and 2017 CE to investigate the influence of increased glacial meltwater versus alterations to lake ice phenology on ecological change. Subfossil diatom assemblages in all cores show two major shifts over the past approximately 200 years including: (i) a proliferation of pioneering, benthic taxa at approximately 1900 CE from previously depauperate populations; and (ii) a rise in planktonic taxa beginning at approximately 1980 CE to present-day dominance. The topmost intervals from each sequentially collected core provide exact dates and demonstrate that diatom regime shifts occurred decades prior to accelerated glacial inputs. These data show that diatom assemblages in Lake Hazen are responding primarily to intrinsic lake factors linked to decreasing duration of lake ice and snow cover rather than to limnological impacts associated with increased glacial runoff. [ABSTRACT FROM AUTHOR]

Antarctic lakes with perennial ice covers provide the opportunity to investigate in-lake processes without direct atmospheric interaction, and to study their ice-cover sensitivity to climate conditions. In this study, a numerical model – driven by radiative, atmospheric and turbulent heat fluxes from the water body beneath the ice cover – was implemented to investigate the impact of climate change on the ice covers from two Antarctic lakes: west lobe of Lake Bonney (WLB) and Crooked Lake. Model results agreed well with measured ice thicknesses of both lakes (WLB – RMSE= 0.11 m over 16 years of data; Crooked Lake – RMSE= 0.07 m over 1 year of data), and had acceptable results with measured ablation data at WLB (RMSE= 0.28 m over 6 years). The differences between measured and modeled ablation occurred because the model does not consider interannual variability of the ice optical properties and seasonal changes of the lake's thermal structure. Results indicate that projected summer air temperatures will increase the ice-cover annual melting in WLB by 2050, but that the ice cover will remain perennial through the end of this century. Contrarily, at Crooked Lake the ice cover becomes ephemeral most likely due to the increase in air temperatures. [ABSTRACT FROM AUTHOR]

Ice surface albedo is an important factor in various optical remote sensing technologies used to determine the distribution of snow or melt water on the ice, and to judge the formation or melting of lake ice in winter, especially in cold and arid areas. In this study, field measurements were conducted at Wuliangsuhai Lake, a typical lake in the semi-arid cold area of China, to investigate the diurnal variation of the ice surface albedo. Observations showed that the diurnal variations of the ice surface albedo exhibit bimodal characteristics with peaks occurring after sunrise and before sunset. The curve of ice surface albedo with time is affected by weather conditions. The first peak occurs later on cloudy days compared with sunny days, whereas the second peak appears earlier on cloudy days. Four probability density distribution functions—Laplace, Gauss, Gumbel, and Cauchy—were combined linearly to model the daily variation of the lake ice albedo on a sunny day. The simulations of diurnal variation in the albedo during the period from sunrise to sunset with a solar altitude angle higher than 5° indicate that the Laplace combination is the optimal statistical model. The Laplace combination can not only describe the bimodal characteristic of the diurnal albedo cycle when the solar altitude angle is higher than 5°, but also reflect the U-shaped distribution of the diurnal albedo as the solar altitude angle exceeds 15°. The scale of the model is about half the length of the day, and the position of the two peaks is closely related to the moment of sunrise, which reflects the asymmetry of the two peaks of the ice surface albedo. This study provides a basis for the development of parameterization schemes of diurnal variation of lake ice albedo in semi-arid cold regions.

Lake ice phenology is a climate-sensitive indicator. However, ground-based monitoring suffers from the limitations of human vision and the difficulty of its implementation in harsh environments. Remote sensing provides great potential to detect lake ice phenology. In this study, a new automated method was developed to extract lake ice phenology parameters by capturing the temporal pattern of the transitional water/ice phase using a parameterized time function. The method is based on Moderate-Resolution Imaging Spectroradiometer (MODIS) daily temperature products, which have unique potential for monitoring lake ice cover as a result of providing four observations per day at 1 km spatial resolution from 2002 to 2016. Three seasonally ice-covered lakes with different characteristics in different climate regions were selected to test the method during the period of 2002–2016. The temporal pattern of water/ice transition phase was determined on the basis of unfrozen water cover fraction extracted from the MODIS daily temperature data, and was compared with the MODIS snow and reflectance products and Landsat images. A good agreement with an R2 of above 0.8 was found when compared with the MODIS snow product. The annual variation of extracted ice phenology dates showed good consistency with the MODIS reflectance and AMSR-E/2 products. The approach was then applied to nine seasonally ice-covered lakes in northern China from 2002 to 2016. The strongest tendency towards a later freeze-up start date was revealed in Lake Qinghai (6.31 days/10 yr) among the lakes in Tibetan plateau, and the break-up start and end dates rapidly shifted towards earlier dates in Lake Hulun (−3.73 days/10 yr; −5.02 days/10 yr). The method is suitable for estimating and monitoring ice phenology on different types of lakes over large scales and has a strong potential to provide valuable information on the responses of ice processes to climate change.

The aim of this study was to determine the dynamics of the process of a course of ice creation phenomena in two small water bodies located in the Silesian Upland. The studies and observations of ice formation on the water bodies were conducted during the period 10th November 2011 to 23rd March 2012. The following parameters were determined each day: degree of ice coverage on each water body, thickness and ice structure and thickness of snow cover on each water body. From the studies it results that a course of the ice formation of both water bodies was almost identical. The same maximum ice thickness was recorded in both cases. It was 36 cm in that season, with slight differences in average thickness. The course of particular phases of ice formation in different water regions was also very similar. The number of days with the ice phenomena and the number of days from the beginning to the end of the ice phenomena were identical in both cases, being 96 and 131 days, respectively. The slight differences over several days were recorded in the case of: number of days with shore ice (lb), number of days with partial ice cover (lcz), number of days with an incomplete ice cover (lnp), number of breaks in the ice cover (B). Additionally, with daily measurements of ice cover thickness the relationships between the course of the average daily air temperature from the meteorological station of Faculty of Earth Sciences of University of Silesia and the daily changes in the ice thickness in the water regions in question were determined by using Spearman’s correlation coefficient. In both cases the relationships were strong and they were r= −0,84(p

To gain more understanding of lake ice melting process, field research was carried out in an arctic tundra lake, Kilpisjärvi (surface area 37.1 km2, maximum depth 57 m) in the melting periods of 2013 and 2014. The heat budget of the ice cover was dominated by the radiation balance; turbulent heat fluxes were large in 2013 due to warm air advection but small in 2014. Transmittance of solar radiation through ice was 0.25 in 2013 and 0.10 in 2014, snow-ice was absent in 2013 but in 2014 accounted for 50% of the ice cover. The melting rate was 4.4 cm d-1 in 2013, 1.9 cm d-1 in 2014. The portions of surface, bottom and internal melting were, respectively, 2.9, 1.0 and 0.5 cm d-1 in 2013 and 0.8, 1.0 and 0.1 cm d-1 in 2014. Internal melting was realized in increase of ice porosity. In 2013 a rapid ice breakage event completed the ice breakup in short time when ice porosity had reached 40-50%. A lake ice melting model should include the thickness and porosity of ice, with porosity connected to an ice strength criterion.

Seepage of geological methane through sediments of Arctic lakes might contribute conceivably to the atmospheric methane budget. However, the abundance and precise locations of such seeps are poorly quantified. For Lake Neyto, one of the largest lakes on the Yamal Peninsula in Northwestern Siberia, temporally expanding regions of anomalously low backscatter in C-band SAR imagery acquired in late winter and spring have been suggested to be related to seepage of methane from hydrocarbon reservoirs. However, this hypothesis has not been verified using in-situ observations so far. Similar anomalies have also been identified for other lakes on Yamal, but it is still uncertain whether or how many of them are related to methane seepage. This study aimed to document similar lake ice backscatter anomalies on a regional scale over four study regions (the Yamal Peninsula and Tazovskiy Peninsulas; the Lena Delta in Russia; the National Petroleum Reserve Alaska) during different years using a time series based approach on Google Earth Engine (GEE) that quantifies changes of σ0 from the Sentinel-1 C-band SAR sensor over time. An algorithm for assessing the coverage that takes the number of acquisitions and maximum time between acquisitions into account is presented, and differences between the main operating modes of Sentinel-1 are evaluated. Results show that better coverage can be achieved in extra wide swath (EW) mode, but interferometric wide swath (IW) mode data could be useful for smaller study areas and to substantiate EW results. A classification of anomalies on Lake Neyto from EW Δσ0 images derived from GEE showed good agreement with the classification presented in a previous study. Automatic threshold-based per-lake counting of years where anomalies occurred was tested, but a number of issues related to this approach were identified. For example, effects of late grounding of the ice and anomalies potentially related to methane emissions could not be separated efficiently. Visualizations of Δσ0 images likely reflect the temporal expansions of anomalies and are expected to be particularly useful for identifying target areas for future field-based research. Characteristic anomalies that clearly resemble the ones observed for Lake Neyto could be identified solely visually in the Yamal and Tazovskiy study regions. All data and algorithms produced in the framework of this study are openly provided to the scientific community for future studies and might potentially aid our understanding of geological lake seepage upon the progression of related field-based studies and corresponding evaluations of formation hypotheses.

Lake Ontario ice conditions are statistically linked to regional temperatures recorded in Toronto, during the most recent climate normal (1980/81–2009/10). A metric was developed to capture the net melting effect of average winter temperatures to characterize lake ice conditions, referred to as Net Melting-Degree Days (NMDD). This metric was able to account for 78% of lake ice interannual variability (R2 = 0.783, P < 0.001). Based on NMDD parameters, current lake ice conditions were characterized in four ways: heavy, moderate, light and very light. Lake Ontario ice conditions were reconstructed to create a hindcast for the span of the instrumental temperature record (1840/41–1979/80). Based on a decadal analysis, heavy ice seasons decreased significantly (R2 = 0.658, P < 0.001) from the 1840s to the 2000s, declining from an average of 6 heavy ice seasons per decade during the most distant climate normal (1840s to 1960s) to an average of only 1 heavy ice season per decade during the most recent climate normal (1980s to 2000s). Finally, lake ice conditions are projected to the end of the 21st century, using an optimal ensemble of Global Climate Model outputs for two different climate change scenarios (RCP4.5, RCP8.5). Heavy ice seasons no longer occur as early as the 2050s under both RCP4.5 and RCP8.5. Whereas, very light ice seasons go from being an extreme in the baseline period (10%), to the dominant characterization of Lake Ontario ice conditions by the 2080s, for both RCP4.5 (73%) and RCP8.5 (100%). [ABSTRACT FROM AUTHOR]

Lake ice supports a range of socio‐economic and cultural activities including transportation and winter recreational actives. The influence of weather patterns on ice‐cover dynamics of temperate lakes requires further understanding for determining how changes in ice composition will impact ice safety and the range of ecosystem services provided by seasonal ice cover. An investigation of lake ice formation and decay for three lakes in Central Ontario, Canada, took place over the course of two winters, 2015–2016 and 2016–2017, through the use of outdoor digital cameras, a Shallow Water Ice Profiler (upward‐looking sonar), and weekly field measurements. Temperature fluctuations across 0°C promoted substantial early season white ice growth, with lesser amounts of black ice forming later in the season. Ice thickening processes observed were mainly through meltwater, or midwinter rain, refreezing on the ice surface. Snow redistribution was limited, with frequent melt events limiting the duration of fresh snow on the ice, leading to a fairly uniform distribution of white ice across the lakes in 2015–2016 (standard deviations week to week ranging from 3 to 5 cm), but with slightly more variability in 2016–2017 when more snow accumulated over the season (5 to 11 cm). White ice dominated the end‐of‐season ice composition for both seasons representing more than 70% of the total ice thickness, which is a stark contrast to Arctic lake ice that is composed mainly of black ice. This research has provided the first detailed lake ice processes and conditions from medium‐sized north‐temperate lakes and provided important information on temperate region lake ice characteristics that will enhance the understanding of the response of temperate lake ice to climate and provide insight on potential changes to more northern ice regimes under continued climate warming. [ABSTRACT FROM AUTHOR]

To gain more understanding of lake ice melting process, field research was carried out in an arctic tundra lake, Kilpisjärvi (surface area 37.1 km², maximum depth 57 m) in the melting periods of 2013 and 2014. The heat budget of the ice cover was dominated by the radiation balance; turbulent heat fluxes were large in 2013 due to warm air advection but small in 2014. Transmittance of solar radiation through ice was 0.25 in 2013 and 0.10 in 2014, snow-ice was absent in 2013 but in 2014 accounted for 50% of the ice cover. The melting rate was 4.4 cm d-1 in 2013, 1.9 cm d-1 in 2014. The portions of surface, bottom and internal melting were, respectively, 2.9, 1.0 and 0.5 cm d-1 in 2013 and 0.8, 1.0 and 0.1 cm d-1 in 2014. internal melting was realized in increase of ice porosity. in 2013 a rapid ice breakage event completed the ice breakup in short time when ice porosity had reached 40-50%. A lake ice melting model should include the thickness and porosity of ice, with porosity connected to an ice strength criterion. [ABSTRACT FROM AUTHOR]

Although perennially ice‐covered Antarctic lakes have experienced variable ice thicknesses over the past several decades, future ice thickness trends and associated aquatic biological responses under projected global warming remain unknown. Heat stored in the water column in chemically stratified Antarctic lakes that have middepth temperature maxima can significantly influence the ice thickness trends via upward heat flux to the ice/water interface. We modeled the ice thickness of the west lobe of Lake Bonney, Antarctica, based on possible future climate scenarios utilizing a 1D thermodynamic model that accounts for surface radiative fluxes as well as the heat flux associated with the temperature evolution of the water column. Model results predict that the ice cover of Lake Bonney will shift from perennial to seasonal within one to four decades, a change that will drastically influence ecosystem processes within the lake. Key Point: Future loss of permanent ice cover is predicted [ABSTRACT FROM AUTHOR]

Lake ice phenology is considered a sensitive indicator of regional climate change. We utilized time series information of this kind extracted from a series of multi-source remote sensing (RS) datasets including the MOD09GQ surface reflectance product, Landsat TM/ETM+ images, and meteorological records to analyze spatiotemporal variations of ice phenology of Qinghai Lake between 2000 and 2016 applying both RS and GIS technology. We also identified the climatic factors that have influenced lake ice phenology over time and draw a number of conclusions. First, data show that freeze-up start (FUS), freeze-up end (FUE), break-up start (BUS), and break-up end (BUE) on Qinghai Lake usually occurred in mid-December, early January, mid-to-late March, and early April, respectively. The average freezing duration (FD, between FUE and BUE), complete freezing duration (CFD, between FUE and BUS), ice coverage duration (ICD, between FUS and BUE), and ablation duration (AD, between BUS and BUE) were 88 days, 77 days, 108 days and 10 days, respectively. Second, while the results of this analysis reveal considerable differences in ice phenology on Qinghai Lake between 2000 and 2016, there has been relatively little variation in FUS times. Data show that FUE dates had also tended to fluctuate over time, initially advancing and then being delayed, while the opposite was the case for BUS dates as these advanced between 2012 and 2016. Overall, there was a shortening trend of Qinghai Lake's FD in two periods, 2000-2005 and 2010-2016, which was shorter than those seen on other lakes within the hinterland of the Tibetan Plateau. Third, Qinghai Lake can be characterized by similar spatial patterns in both freeze-up (FU) and break-up (BU) processes, as parts of the surface which freeze earlier also start to melt first, distinctly different from some other lakes on the Tibetan Plateau. A further feature of Qinghai Lake ice phenology is that FU duration (between 18 days and 31 days) is about 10 days longer than BU duration (between 7 days and 20 days). Fourth, data show that negative temperature accumulated during the winter half year (between October and the following April) also plays a dominant role in ice phenology variations of Qinghai Lake. Precipitation and wind speed both also exert direct influences on the formation and melting of lake ice cover and also cannot be neglected. [ABSTRACT FROM AUTHOR]

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.

The aim of the study was to evaluate, for the first time, the capability of different machine learning (ML) algorithms in classifying along-track lake surface conditions (open water and ice types) across ice seasons (freeze-up, ice growth and break-up periods) from Sentinel-3 A/B synthetic aperture radar altimeter (SRAL) data. To achieve this goal, over 107,500 radar waveforms extracted from 11 large lakes across the Northern Hemisphere and three ice seasons (2018–2021) were manually labelled using complementary satellite data (Sentinel-1 imaging Synthetic Aperture Radar (SAR), Sentinel-2 Multispectral Instrument (MSI) Level 1C, and MODIS Aqua/Terra data) for the training and testing of the ML algorithms in discriminating between open water, young (thin) ice, growing ice and melting ice. The four ML algorithms tested include Random Forest (RF), Gradient Boosting Trees (GBT), K Nearest Neighbor (KNN) and Support Vector Machine (SVM). To characterize the waveforms, seven waveform parameters were derived: Leading Edge Width (LEW), Offset Center of Gravity (OCOG) Width, Pulse Peakiness (PP), backscatter coefficient (Sigma0), late tail to peak power (LTPP), early tail to peak power (ETPP) and the maximum value of the echo power (Max). Accuracies >95% were achieved across all classifiers using a 4-parameter combination (Sigma0, PP, OCOG Width, and LEW). Among all waveform parameters, Sigma0, OCOG width and PP were found to be the most important parameters for discriminating between lake ice types and open water. Despite showing comparable classification performances in the overall classification, RF and KNN are found to be a better fit for global lake ice mapping as both are less sensitive to their internal hyperparameters. Additionally, consistent results (>93.7% accuracy in all classifiers) achieved on the accuracy assessment carried out for each lake (out-of-sample testing) revealed the strength of the classifiers for spatial transferability. Implementation of RF and KNN could be valuable in a pre-or post-processing step for identifying lake surface conditions under which the retrieval of water level and ice thickness may be limited or not possible and, therefore, inform algorithms currently used for the generation of operational or research products. While the research focused on 11 of the largest lakes of the Northern Hemisphere, the classification approach presented herein has potential for application on smaller lakes too since data in SAR mode (∼300 m along-track resolution) are used. • This is the first study using Sentinel-3 SAR altimetry for lake ice classification. • Four different machine learning classifiers (SVM, KNN, RF and GBT) were assessed. • RF and KNN are recommended for classification of ice types along altimeter tracks. • Sigma0, OCOG Width, PP are the best parameters to differentiate lake ice and water. • Over 93.7% accuracy in spatial cross-validation shows broad-scale applicability. [ABSTRACT FROM AUTHOR]

A 1-D ice cover model was developed to predict and constrain drivers of long-term ice thickness trends in chemically stratified lakes of Taylor Valley, Antarctica. The model is driven by surface radiative heat fluxes and heat fluxes from the underlying water column. The model successfully reproduced 16 a (between 1996 and 2012) of ice thickness changes for the west lobe of Lake Bonney (average ice thickness = 3.53 m) and Lake Fryxell (average ice thickness = 4.22 m). Long-term ice thickness trends require coupling with the thermal structure of the water column. The heat stored within the temperature maximum of lakes exceeding a liquid water column depth of 20 m can either impede or facilitate ice thickness change depending on the predominant climatic trend (cooling or warming). As such, shallow (