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Temperate lakes worldwide are losing ice cover but the implications for under‐ice thermal dynamics are poorly constrained. Using a 92‐year record of ice phenology from a temperate and historically dimictic lake, we examined trends, variability, and drivers of ice phenology and under‐ice temperatures. The onset of ice formation decreased by 23 days century−1, which can be largely attributed to warming air temperatures. Ice‐off date has become substantially more variable with spring air temperatures and cumulative February through April snowfall explaining over 80% of the variation in timing. As a result of changing ice phenology, total ice duration contracted by a month and more than doubled in interannual variability. Using weekly under‐ice temperature profiles for the most recent 36 years, we found that shorter ice duration decreased winter inverse stratification and was associated with an extended spring mixing period. We illustrate the limitations of relying on discrete ice clearance dates in our assumptions around under‐ice thermal dynamics by presenting high‐frequency under‐ice observations in two recent winters: one with intermittent ice cover and a year with slow spring ice clearance. Plain Language Summary: Lakes worldwide are losing ice cover in response to climate change. We used a rare and nearly century‐long data set of ice formation and ice clearance records to examine trends, variability, and drivers. We found that ice cover is getting substantially shorter and more variable with winter ice duration about a month shorter now than it was a century ago. Using under‐ice temperature measurements from the most recent three decades, we found differences in under‐ice temperatures affected by lake ice duration. Key Points: Ice duration and ice formation are getting shorter or occurring later, and both are increasing in interannual variabilityIce break up is not trending earlier, but interannual variability is increasingThis dimictic lake is at risk of transitioning toward monomixis in the near future [ABSTRACT FROM AUTHOR]

Real‐time forecasted ice information for large lakes, such as the Great Lakes, is critical for essential operations, such as ice breaking, commercial navigation, search and rescue, and oil spill response. Existing forecast products for large lake ice conditions are not available for medium‐range time horizons (5–16 days out), yet they could provide important information for decision making, particularly for ice breaking and spill responses. In addition, ice forecasts for Earth's largest lakes at these timescales could be important for Medium‐Range Weather (MRW) forecasting. However, the skill of existing operational products in predicting ice conditions at MRW timescales has not been studied. This work aims to determine how well ice forecasts from a coupled large lake hydrodynamic‐ice model perform for MRW forecast horizons. Simulations were carried out for the 2022 Great Lakes ice season, using 8 different 16‐day forecast periods. Forecast results were compared to observations of meteorology and ice conditions from the U.S. National Ice Center. Results show the MRW ice forecasts in the Great Lakes outperform persistence‐based forecasts. These findings could inform the development or extension of lake operational ice forecasting and the potential of coupling between atmospheric and large lake models at medium‐range forecast time scales. Plain Language Summary: Ice information for large lakes is critical for essential operations, such as ice breaking, commercial navigation, search and rescue, and oil spill response. Ice forecasts are currently not available in the medium‐range (5–16 days out) time scale, yet they could provide valuable information for decision making. This information could also be important for medium‐range weather forecasts. The skill of existing Great Lakes ice forecast products at medium‐range time scales is currently unknown. Our work aims to determine how well ice forecasts from an atmosphere‐lake model perform for medium‐range time scales. Simulations were carried out for the 2022 Great Lakes ice season, using 8 different 16‐day forecast periods. The modeled forecasts were compared to observations from the National Ice Center and observed meteorological conditions. Results show that the modeled forecasts outperform persistence forecasts. These findings could inform the development or extension of ice forecasting and the potential of an atmosphere‐lake model at medium‐range time scales. Key Points: Medium‐range (5‐ to 16‐day) ice forecasts show utility in the Great LakesModel ice forecasts outperform ice persistence forecastsAir temperature bias in medium‐range weather forecasts is the likely greatest contributor to ice error [ABSTRACT FROM AUTHOR]

Lakes in Southwest Alaska are a critical habitat to many species and provide livelihoods to many communities through subsistence fishing, transportation, and recreation. Consistent and reliable data are rarely available for even the largest lakes in this sparsely populated region, so data-intensive methods utilizing long-term observations and physical data are not possible. To address this, we used optical remote sensing (MODIS 2002–2016) to establish a phenology record for key lakes in the region, and we modeled lake-ice formation and breakup for the years 1982–2022 using readily available temperature and solar radiation-based predictors in a survival modeling framework that accounted for years when lakes did not freeze. Results were validated with observations recorded at two lakes, and stratification measured by temperature arrays in three others. Our model provided good predictions (mean absolute error, freeze-over = 11 days, breakup = 16 days). Cumulative freeze-degree days and cumulative thaw-degree days were the strongest predictors of freeze-over and breakup, respectively. Lake volume appeared to mediate lake-ice phenology, as ice-cover duration tended to be longer and less variable in lower-volume lakes. Furthermore, most lakes < 10 km3 showed a trend toward shorter ice seasons of −1 to −6 days/decade, while most higher-volume lakes showed undiscernible or positive trends of up to 2 days/decade. Lakes > 20 km3 also showed a greater number of years when freeze-over was neither predicted by our model (37 times, n = 200) nor observed in the MODIS record (19 times, n = 60). While three lakes in our study did not commonly freeze throughout our study period, four additional high-volume lakes began experiencing years in which they did not freeze, starting in the late 1990s. Our study provides a novel approach to lake-ice prediction and an insight into the future of lake ice in the Boreal region. [ABSTRACT FROM AUTHOR]

Lake ice thickness (LIT) is a sensitive indicator of climate change, identified as a thematic variable of Lakes as an Essential Climate Variable (ECV) by the Global Climate Observing System (GCOS). Here, we present a novel and efficient analytically based retracking approach for estimating LIT from high-resolution Ku-band (13.6 GHz) synthetic-aperture radar (SAR) altimetry data. The retracker method is based on the analytical modeling of the SAR radar echoes over ice-covered lakes that show a characteristic double-peak feature attributed to the reflection of the Ku-band radar waves at the snow–ice and ice–water interfaces. The method is applied to Sentinel-6 Unfocused SAR (UFSAR) and Fully Focused SAR (FFSAR) data, with their corresponding tailored waveform model, referred to as the SAR_LIT and FFSAR_LIT retracker, respectively. We found that LIT retrievals from Sentinel-6 high-resolution SAR data at different posting rates are fully consistent with the LIT estimations obtained from thermodynamic lake ice model simulations and from low-resolution mode (LRM) Sentinel-6 and Jason-3 data over two ice seasons during the tandem phase of the two satellites, demonstrating the continuity between LRM and SAR LIT retrievals. By comparing the Sentinel-6 SAR LIT estimates to optical/radar images, we found that the Sentinel-6 LIT measurements are fully consistent with the evolution of the lake surface conditions, accurately capturing the seasonal transitions of ice formation and melt. The uncertainty in the LIT estimates obtained with Sentinel-6 UFSAR data at 20 Hz is in the order of 5 cm, meeting the GCOS requirements for LIT measurements. This uncertainty is significantly smaller, by a factor of 2 to 3 times, than the uncertainty obtained with LRM data. The FFSAR processing at 140 Hz provides even better LIT estimates, with 20% smaller uncertainties. The LIT retracker analysis performed on data at the higher posting rate (140 Hz) shows increased performance in comparison to the 20 Hz data, especially during the melt transition period, due to the increased statistics. The LIT analysis has been performed over two representative lakes, Great Slave Lake and Baker Lake (Canada), demonstrating that the results are robust and hold for lake targets that differ in terms of size, bathymetry, snow/ice properties, and seasonal evolution of LIT. The SAR LIT retrackers presented are promising tools for monitoring the inter-annual variability and trends in LIT from current and future SAR altimetry missions. [ABSTRACT FROM AUTHOR]

The perennially ice-covered lakes of the McMurdo Dry Valleys (MDVs), Antarctica, are an important reservoir of liquid water in an arid and largely frozen environment. During the austral summer, the margins of these ice covers melt, forming a “moat” of liquid water and thin ice, allowing exchange between lake waters and the atmosphere to occur and serving as an interface between lake, soil, and stream ecosystems. The size of these moats varies from year to year. Here, we have established the first published record of moat area changes at MDVs’ Lake Fryxell through time using manual traces of the moat as observed via satellite imagery. We have also tested a semi-automated approach for measuring moat area and found that it consistently underestimated the manual record, which we suspect may be due to the lower spatial resolution of images used in this versus the manual approach. Finally, we developed a predictive model based on readily available climate data, allowing moat area to be predicted beyond the limits of the satellite-based records. We found that functional moat area varies annually, potentially influencing ecosystem processes in the moats.

Arctic landscapes are characterized by diverse water bodies, which are covered with ice for most of the year. Ice controls surface albedo, hydrological properties, gas exchange, and ecosystem services, but freezing processes differ between water bodies. We studied the influence of geomorphology and meteorology on winter ice of water bodies in the Lena Delta, Siberia. Electrical conductivity (EC) and stable water isotopes of ice cores from four winters and six water bodies were measured at unprecedented resolution down to 2-cm increments, revealing differences in freezing systems. Open-system freezing shows near-constant isotopic and EC gradients in ice, whereas closed-system freezing shows decreasing isotopic composition with depth. Lena River ice displays three zones of isotopic composition within the ice, reflecting open-system freezing that records changing water sources over the winter. The isotope composition of ice covers in landscape units of different ages also reflects the individual water reservoir settings (i.e., Pleistocene vs. Holocene ground ice thaw). Ice growth models indicate that snow properties are a dominant determinant of ice growth over winter. Our findings provide novel insights into the winter hydrochemistry of Arctic ice covers, including the influences of meteorology and water body geomorphology on freezing rates and processes.

Lakes on the Qinghai Tibet Plateau (QTP) are widely distributed spatially, and they are mostly seasonally frozen. Due to global warming, the thickness and phenology of the lake ice has been changing, which profoundly affects the regional climate evolution. There are a few studies about lake ice in alpine regions, but the understanding of climatological characteristics of lake ice on the QTP is still limited. Based on a field experiment in the winter of 2022, the thermal conductivity of Qinghai Lake ice was determined as 1.64 W·m−1·°C−1. Airborne radar ice thickness data, meteorological observations, and remote sensing images were used to evaluate a quasi-steady ice model (Leppäranta model) performance of the lake. This is an analytic model of lake ice thickness and phenology. The long-term (1979–2017) ice history of the lake was simulated. The results showed that the modeled mean ice thickness was 0.35 m with a trend of −0.002 m·a−1, and the average freeze-up start (FUS) and break-up end (BUE) were 30 December and 5 April, respectively, which are close to the field and satellite observations. The simulated trend of the maximum ice thickness from 1979 to 2017 (0.004 m·a−1) was slightly higher than the observed result (0.003 m·a−1). The simulated trend was 0.20 d·a−1 for the FUS, −0.34 d·a−1 for the BUE, and −0.54 d·a−1 for the ice duration (ID). Correlation and detrending analysis were adopted for the contribution of meteorological factors. In the winters of 1979–2017, downward longwave radiation and air temperature were the two main factors that had the best correlation with lake ice thickness. In a detrending analysis, air temperature, downward longwave radiation, and solar radiation contributed the most to the average thickness variability, with contributions of 42%, 49%, and −48%, respectively, and to the maximum thickness variability, with contributions of 41%, 45%, and −48%, respectively. If the six meteorological factors (air temperature, downward longwave radiation, solar radiation, wind speed, pressure, and specific humidity) are detrending, ice thickness variability will increase 83% on average and 87% at maximum. Specific humidity, wind, and air pressure had a poor correlation with ice thickness. The findings in this study give insights into the long-term evolutionary trajectory of Qinghai Lake ice cover and serve as a point of reference for investigating other lakes in the QTP during cold seasons. [ABSTRACT FROM AUTHOR]

Climate warming causes shorter winters and changes in ice and snow cover in subarctic lakes, highlighting the need to better understand under-ice ecosystem functioning. The plankton community in a subarctic, oligotrophic lake was studied throughout the ice-covered season, focusing on lipid dynamics and life history traits in two actively overwintering copepods, Cyclops scutifer and Eudiaptomus graciloides. Whereas C. scutifer was overwintering in C-IV to C-V stage, E. graciloides reproduced under ice cover. Both species had accumulated lipids prior to ice-on and showed a substantial decrease in total lipid content throughout the ice-covered period: E. graciloides (60%–38% dw) and C. scutifer (73%–33% dw). Polyunsaturated fatty acids of algal origin were highest in E. graciloides and declined strongly in both species. Stearidonic acid (18:4n-3) content in E. graciloides was particularly high and decreased rapidly during the study period by 50%, probably due to reproduction. The copepods differed in feeding behavior, with the omnivore C. scutifer continuing to accumulate lipids until January, whereas the herbivorous E. graciloides accumulated lipids from under-ice primary production during the last months of ice-cover. Our findings emphasize the importance of lipid accumulation and utilization for actively overwintering copepods irrespective of the timing of their reproduction. [ABSTRACT FROM AUTHOR]

This article introduces the first use of global navigation satellite system (GNSS) reflectometry for monitoring lake ice phenology. This is demonstrated using Qinghai Lake, Tibetan Plateau, as a case study. Signal-to-noise ratio (SNR) values obtained from the cyclone GNSS (CYGNSS) constellation over four ice seasons (2018 to 2022) were used to examine the impact of lake surface conditions on reflected GNSS signals during open water and ice cover seasons. A moving t-test algorithm was applied to time-varying SNR values allowing for the detection of lake ice at daily temporal resolution. Good agreement was achieved between ice phenology records derived from CYGNSS data and Moderate Resolution Imaging Spectroradiometer (MODIS) imagery. The CYGNSS timings for freeze-up, i.e., the period starting with the first appearance of ice on the lake (freeze-up start; FUS) until the lake becomes fully ice covered (freeze-up end; FUE), as well as those for breakup, i.e., the period beginning with the first pixel of open water (breakup start; BUS) and ending when the whole lake becomes ice-free (breakup end; BUE), were validated against the phenology dates derived from MODIS images. Mean absolute errors are 7, 5, 10, 4, and 5 days for FUS, FUE, BUS, BUE, and ice cover duration, respectively. Observations revealed the sensitivity of GNSS reflected signals to surface melt prior to the appearance of open water conditions as determined from MODIS, which explains the larger difference of 10 days for BUS.

The ice phenology of alpine lakes on the Tibetan Plateau (TP) is a rapid and direct responder to climate changes, and the variations in lake ice exhibit high temporal frequency characteristics. MODIS and passive microwave data are widely used to monitor lake ice changes with high temporal resolution. However, the low spatial resolutions make it difficult to effectively quantify the freeze-melt dynamics of lakes. This work used Sentinel-1 synthetic aperture radar (SAR) data to derive highresolution ice maps (about 6 days), then with the aid of Sentinel-2 optical images to quantify freeze-melt processes in three typical lakes on the TP (e.g. Selin Co, Ayakekumu Lake, and Nam Co). The results showed that three lakes had an average annual ice period of 125–157 days and a complete ice cover period of 72–115 days, from 2018 to 2022. They exhibit different ice phenology patterns. Nam Co is characterized by repeated episodes of freezing, melting, and refreezing, resulting in a prolonged freeze-up period. Meanwhile, the break-up period of Nam Co lasts for a longer duration (about 19 days), and the break-up exhibits a smooth process. Similarly, Ayakekumu Lake showed more significant inter-annual fluctuations in the freeze-up period, with deviations of up to 28 days observed among different years. Compared to the other two lakes, Selin Co experienced a relatively short freeze-up and break-up period. In short, Sentinel-1 SAR data can effectively monitor the weekly and seasonal variations in lake ice on the TP. Particularly, this data facilitates quantification of the freeze-melt dynamics. [ABSTRACT FROM AUTHOR]

Lake ice thickness (LIT) is one of the key climate variables in the lake ice domain, but there are currently large uncertainties in the retrieval of LIT. We present and validate a new LIT retrieval method that utilizes ICESat-2 data to assist CryoSat-2 echo peak selection, aiming to improve the accuracy of LIT retrieval and enable data acquisition without on-site measurements. The method involves screening out similar ICESat-2 and CryoSat-2 tracks based on time and space constraints. It also involves dynamically adjusting the range constraint window of CryoSat-2 waveforms based on the high-precision lake ice surface ellipsoid height obtained from ICESat-2/ATL06 data. Within this range constraint window, the peak selection strategy is used to determine the scattering interfaces between snow-ice and ice-water. By utilizing the distance between the scattering horizons, the thickness of the lake ice can be determined. We performed the ice thickness retrieval experiment for Baker Lake in winter and verified it against the on-site measurement data. The results showed that the accuracy was about 0.143 m. At the same time, we performed the ice thickness retrieval experiment for Great Bear Lake (GBL), which does not have on-site measurement data, and compared it with the climate change trend of GBL. The results showed that the retrieval results were consistent with the climate change trend of GBL, confirming the validity of the proposed method. [ABSTRACT FROM AUTHOR]

Field observations were performed in Lake Nanhai, a shallow Chinese lake, to investigate the impact of variations in snow thickness (0–7.0 cm) on solar radiation transfer. As the snow thickness increases from 0 to 7.0 cm, the albedo increases from 0.27 to 0.96. The bulk extinction coefficients of snow, snow-ice, and congelation ice are 9.47, 9.69, and 2.18 m−1, respectively. The peak of the transmission spectrum shifts from the blue to green light waveband compared to the solar radiation spectrum. The proportion of incident radiation at surface penetrating to the under-ice water ranges from 0.5% to 19.7% associated with snow depth from 7 cm to 0 cm. Fresh snow influences the under-ice light condition crucially, and therefore the seasonal evolution of the lake phytoplankton community is affected. [ABSTRACT FROM AUTHOR]

The rapid formation of glacial lakes is one of the most conspicuous landscape changes caused by atmospheric warming in glacierised regions. However, relatively little is known about the history and current state of glacial lakes in the High Arctic. This study aims to address this issue by providing the first inventory of glacial lakes in Svalbard, focusing in particular on the post-Little Ice Age evolution of glacial lakes and their typology. To do so, we used aerial photographs and satellite imagery together with archival topographic data from 1936 to 2020. The inventory comprises the development of 566 glacial lakes (146 km2) that were still in direct contact with glaciers during the period 2008–2012. The results show a consistent increase in the total area of glacial lakes from the 1930s to 2020 and suggest an apparent link between climatic and geological factors, and the formation of specific lake dam types: moraine, ice, or bedrock. We also detected 134 glacial lake drainage events that have occurred since the 1930s. This study shows that Svalbard has one of the highest rates of glacial lake development in the world, which is an indicator of the overall dynamics of landscape change in the archipelago in response to climate change.

We present a Simple Lake Ice Model to calculate the growth rate of lake ice in a cold and relatively dry climate. The focus is on Lake St. Moritz, Switzerland, which has an area of 0.78 km2 and is about 45 m deep. In winter the lake is extensively used for recreational purposes, including horse racing with thousands of spectators. Safety on the ice cover is essential, and there is a great need to have a simple tool with which the growth rate of the ice layer can be calculated for given meteorological conditions. The approach is based on a simple formulation of the upper temperature of the ice layer, which depends on air temperature and snow cover. Input data are the date on which the lake freezes over, daily mean air temperatures and snow depth. For the winter 2021/22 calculated ice growth compares well with ice thickness measurements. We demonstrate that grooming of the snow has a significant positive effect on the ice thickening rate. We also evaluate the sensitivity of the simulated ice thickness to increasing mean temperature.

Lake ice changes in winter under the influence of global climate change, but how lake ice changes will regulate water gross primary productivity (GPP) and carbon sequestration capacity is still unclear. Here, we evaluated and analyzed the geographic spatial pattern and dynamic changes of lake ice and GPP on the Qinghai-Tibetan Plateau (QTP) in the past 20 years. Results show that lake ice duration on the QTP is 123.36±2.43 d on average, although longer for lakes at higher altitudes, of moderate size, and with shallower depths. Lake ice thickness is between 55–66 cm on average, and its GPP on the QTP is between 0.17–3.35 g C m−2 d−1. In the context of global climate change, reductions in lake ice cover duration and changes in ice thickness on the QTP increased phytoplankton GPP during the winter freeze period while decreasing Carbon dioxide (CO2) emissions during the melting period.

Lake ice phenology (LIP), hiding information about lake energy and material exchange, serves as an important indicator of climate change. Utilizing an efficient technique to swiftly extract lake ice information is crucial in the field of lake ice research. The Bayesian ensemble change detection (BECD) algorithm stands out as a powerful tool, requiring no threshold compared to other algorithms and, instead, utilizing the probability of abrupt changes to detect positions. This method is predominantly employed by automatically extracting change points from time series data, showcasing its efficiency and accuracy, especially in revealing phenological and seasonal characteristics. This paper focuses on Bosten Lake (BL) and employs PMRS data in conjunction with the Bayesian change detection algorithm. It introduces an automated method for extracting LIP information based on the Bayesian change detection algorithm. In this study, the BECD algorithm was employed to extract lake ice phenology information from passive microwave remote sensing data on Bosten Lake. The reliability of the passive microwave remote sensing data was further investigated through cross-validation with MOD10A1 data. Additionally, the Mann–Kendall non-parametric test was applied to analyze the trends in lake ice phenology changes in Bosten Lake. Spatial variations were examined using MOD09GQ data. The results indicate: (1) The Bayesian change detection algorithm (BCDA), in conjunction with PMRS data, offers a high level of accuracy and reliability in extracting the lake ice freezing and thawing processes. It accurately captures the phenological parameters of BL's ice. (2) The average start date of lake ice freezing is in mid-December, lasting for about three months, and the start date of ice thawing is usually in mid-March. The freezing duration (FD) of lake ice is relatively short, shortening each year, while the thawing speed is faster. The stability of the lake ice complete ice cover duration is poor, averaging 84 days. (3) The dynamic evolution of BL ice is rapid and regionally distinct, with the lake center, southwest, and southeast regions being the earliest areas for ice formation and thawing, while the northwest coastal and Huang Shui Gou areas experience later ice formation. (4) Since 1978, BL's ice has exhibited noticeable trends: the onset of freezing, the commencement of thawing, complete thawing, and full freezing have progressively advanced in regard to dates. The periods of full ice coverage, ice presence, thawing, and freezing have all shown a tendency toward shorter durations. This study introduces an innovative method for LIP extraction, opening up new prospects for the study of lake ecosystem and strategy formulation, which is worthy of further exploration and application in other lakes and regions. [ABSTRACT FROM AUTHOR]

Satellite altimetry has been proven to measure water levels in lakes and rivers effectively. The Sentinel-3A satellite is equipped with a dual-frequency synthetic aperture radar altimeter (SRAL), which allows for inland water levels to be measured with higher precision and improved spatial resolution. However, in regions at middle and high latitudes, where many lakes are covered by ice during the winter, the non-uniformity of the altimeter footprint can substantially impact the accuracy of water level estimates, resulting in abnormal readings when applying standard SRAL synthetic aperture radar (SAR) waveform retracking algorithms (retrackers). In this study, a modified method is proposed to determine the current surface type of lakes, analyzing changes in backscattering coefficients and brightness temperature. This method aligns with ground station observations and ensures consistent surface type classification. Additionally, a dual-threshold algorithm that addresses the limitations of the original bimodal algorithm by identifying multiple peaks without needing elevation correction is introduced. This innovative approach significantly enhances the precision of equivalent water level measurements for ice-covered lakes. The study retrieves and compares the water level data of nine North American lakes covered by ice from 2016–2019 using the dual-threshold and the SAMOSA-3 algorithm with in situ data. For Lake Athabasca, Cedar Lake, Great Slave Lake, Lake Winnipeg, and Lake Erie, the root mean square error (RMSE) of SAMOSA-3 is 39.58 cm, 46.18 cm, 45.75 cm, 42.64 cm, and 6.89 cm, respectively. However, the dual-threshold algorithm achieves an RMSE of 6.75 cm, 9.47 cm, 5.90 cm, 7.67 cm, and 5.01 cm, respectively, representing a decrease of 75%, 79%, 87%, 82%, and 27%, respectively, compared to SAMOSA-3. The dual-threshold algorithm can accurately estimate water levels in ice-covered lakes during winter. It offers a promising prospect for achieving long-term, continuous, and high-precision water level measurements for middle- and high-latitude lakes. [ABSTRACT FROM AUTHOR]

The rapid formation of glacial lakes is one of the most conspicuous landscape changes caused by atmospheric warming in glacierised regions. However, relatively little is known about the history and current state of glacial lakes in the High Arctic. This study aims to address this issue by providing the first inventory of glacial lakes in Svalbard, focusing in particular on the post-Little Ice Age evolution of glacial lakes and their typology. To do so, we used aerial photographs and satellite imagery together with archival topographic data from 1936 to 2020. The inventory comprises the development of 566 glacial lakes (146 km2) that were still in direct contact with glaciers during the period 2008–2012. The results show a consistent increase in the total area of glacial lakes from the 1930s to 2020 and suggest an apparent link between climatic and geological factors, and the formation of specific lake dam types: moraine, ice, or bedrock. We also detected 134 glacial lake drainage events that have occurred since the 1930s. This study shows that Svalbard has one of the highest rates of glacial lake development in the world, which is an indicator of the overall dynamics of landscape change in the archipelago in response to climate change. [ABSTRACT FROM AUTHOR]

Lakes on the Qinghai Tibet Plateau (QTP) are widely distributed spatially, and they are mostly seasonally frozen. Due to global warming, the thickness and phenology of the lake ice has been changing, which profoundly affects the regional climate evolution. There are a few studies about lake ice in alpine regions, but the understanding of climatological characteristics of lake ice on the QTP is still limited. Based on a field experiment in the winter of 2022, the thermal conductivity of Qinghai Lake ice was determined as 1.64 W·m−1·°C−1. Airborne radar ice thickness data, meteorological observations, and remote sensing images were used to evaluate a quasi-steady ice model (Leppäranta model) performance of the lake. This is an analytic model of lake ice thickness and phenology. The long-term (1979–2017) ice history of the lake was simulated. The results showed that the modeled mean ice thickness was 0.35 m with a trend of −0.002 m·a−1, and the average freeze-up start (FUS) and break-up end (BUE) were 30 December and 5 April, respectively, which are close to the field and satellite observations. The simulated trend of the maximum ice thickness from 1979 to 2017 (0.004 m·a−1) was slightly higher than the observed result (0.003 m·a−1). The simulated trend was 0.20 d·a−1 for the FUS, −0.34 d·a−1 for the BUE, and −0.54 d·a−1 for the ice duration (ID). Correlation and detrending analysis were adopted for the contribution of meteorological factors. In the winters of 1979–2017, downward longwave radiation and air temperature were the two main factors that had the best correlation with lake ice thickness. In a detrending analysis, air temperature, downward longwave radiation, and solar radiation contributed the most to the average thickness variability, with contributions of 42%, 49%, and −48%, respectively, and to the maximum thickness variability, with contributions of 41%, 45%, and −48%, respectively. If the six meteorological factors (air temperature, downward longwave radiation, solar radiation, wind speed, pressure, and specific humidity) are detrending, ice thickness variability will increase 83% on average and 87% at maximum. Specific humidity, wind, and air pressure had a poor correlation with ice thickness. The findings in this study give insights into the long-term evolutionary trajectory of Qinghai Lake ice cover and serve as a point of reference for investigating other lakes in the QTP during cold seasons.

Study region: 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. Study focus: 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. New hydrological insights: 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.

Great Slave Lake (GSL), one of the world's largest and deepest lakes, has undergone an aquatic ecosystem transformation in response to twenty-first-century accelerated Arctic warming that is unparalleled in at least the past two centuries. Algal remains from four high-resolution palaeolimnological records retrieved from the West Basin provide baseline limnological data that we compared with historical phycological surveys undertaken on GSL between the 1940s and 1990s. We document the rapid restructuring of algal community composition ca 2000 CE that is consistent with recent increases in regional air temperature and declines in ice cover and wind speed, that collectively altered habitats for aquatic biota. This new limnological regime initiated the first observation of scaled chrysophytes and favoured the rapid proliferation of small planktonic cyclotelloid diatoms which replaced the long-established dominance of large filamentous Aulacoseira islandica in West Basin sedimentary records. Such abrupt transformations in the primary producers of this socioecologically valuable 'northern Great Lake' may have widespread implications for the entire food web with unknown consequences for aquatic ecosystem functioning and fisheries, which First Nations, Métis and other northern communities depend upon, pointing to the need for new studies. [ABSTRACT FROM AUTHOR]

Analytic methods are useful for lake ice climatology investigations that account for ice phenology, thickness, and extent. Ice climatology depends on the local climate and lake characteristics, which can be compressed into a few forcing factors for analytic modelling. The internal factors are lake depth, size, and water quality, while the external factors are solar radiation, air–lake interaction, and heat flux from bottom sediment. A two-layer temperature structure with a sharp thermocline in-between is employed for the water body and a non-inert conduction law for the ice cover. A thermal equilibrium approach results in temperature and ice thickness solutions, and a time scale analysis provides the applicability of the equilibrium method for lake ice climatology. A non-steady solution is needed for ice melting. [ABSTRACT FROM AUTHOR]

We present a Simple Lake Ice Model to calculate the growth rate of lake ice in a cold and relatively dry climate. The focus is on Lake St. Moritz, Switzerland, which has an area of 0.78 km2 and is about 45 m deep. In winter the lake is extensively used for recreational purposes, including horse racing with thousands of spectators. Safety on the ice cover is essential, and there is a great need to have a simple tool with which the growth rate of the ice layer can be calculated for given meteorological conditions. The approach is based on a simple formulation of the upper temperature of the ice layer, which depends on air temperature and snow cover. Input data are the date on which the lake freezes over, daily mean air temperatures and snow depth. For the winter 2021/22 calculated ice growth compares well with ice thickness measurements. We demonstrate that grooming of the snow has a significant positive effect on the ice thickening rate. We also evaluate the sensitivity of the simulated ice thickness to increasing mean temperature. [ABSTRACT FROM AUTHOR]

Khovsgol Lake, a seasonal ice-covered lake located in boreal Siberia, plays important economic, transportation and agricultural roles for local residents. On 11 January 2021, an Mw 6.7 earthquake struck the center of this lake, providing a unique opportunity to better understand lake ice movement, ridge distribution, and hydraulic and hydrodynamic processes, as a result of the mainshock. We use a pixel-tracking method on both Sentinel-1 synthetic aperture radar and Sentinel-2 optical remote-sensing data covering this lake before, during and after the mainshock to obtain lake-ice displacement. Combining these measurements with different viewing geometries, we determine the locations of pressure ridges in each period and derive their relative 3D displacement maps with a precision of

Global surface freshwater primarily resides in lakes, with the overwhelming majority found in Earth’s largest lakes, thus understanding potential climate change effects in these large lakes is critical. In dimictic lakes, climate change has extended the duration of summer thermal stratification and reduced the length of the ice season. These changes are relatively straightforward to evaluate in smaller, inland lakes. However, in large lakes, such as the North American Great Lakes, temporally intermittent and spatially heterogeneous ice cover, and spatial thermal heterogeneity limit the utility of simple ice on–off or mixing classifications; therefore, assessing how climate change is impacting winter conditions in large lakes is challenging. Here, we use in-situ and satellite-derived surface water temperature observations from the North American Great Lakes to overcome these limitations and show that warming air temperatures are driving reductions in the number of winter days, collectively those with either ice cover or inverse thermal stratification, in favor of increases in isothermal conditions for the period 1995–2023. We find that on average the Great Lakes are experiencing a loss of 14 winter days per decade. Our results demonstrate how climate change has yielded disproportionate changes in the annual thermal cycle and mixing conditions of Earth’s largest freshwater system and signals the potential for fundamental ecosystem shifts due to a loss of winter.

Lake ice thickness (LIT) is one of the key climate variables in the lake ice domain, but there are currently large uncertainties in the retrieval of LIT. We present and validate a new LIT retrieval method that utilizes ICESat-2 data to assist CryoSat-2 echo peak selection, aiming to improve the accuracy of LIT retrieval and enable data acquisition without on-site measurements. The method involves screening out similar ICESat-2 and CryoSat-2 tracks based on time and space constraints. It also involves dynamically adjusting the range constraint window of CryoSat-2 waveforms based on the high-precision lake ice surface ellipsoid height obtained from ICESat-2/ATL06 data. Within this range constraint window, the peak selection strategy is used to determine the scattering interfaces between snow-ice and ice-water. By utilizing the distance between the scattering horizons, the thickness of the lake ice can be determined. We performed the ice thickness retrieval experiment for Baker Lake in winter and verified it against the on-site measurement data. The results showed that the accuracy was about 0.143 m. At the same time, we performed the ice thickness retrieval experiment for Great Bear Lake (GBL), which does not have on-site measurement data, and compared it with the climate change trend of GBL. The results showed that the retrieval results were consistent with the climate change trend of GBL, confirming the validity of the proposed method.

Satellite altimetry has been proven to measure water levels in lakes and rivers effectively. The Sentinel-3A satellite is equipped with a dual-frequency synthetic aperture radar altimeter (SRAL), which allows for inland water levels to be measured with higher precision and improved spatial resolution. However, in regions at middle and high latitudes, where many lakes are covered by ice during the winter, the non-uniformity of the altimeter footprint can substantially impact the accuracy of water level estimates, resulting in abnormal readings when applying standard SRAL synthetic aperture radar (SAR) waveform retracking algorithms (retrackers). In this study, a modified method is proposed to determine the current surface type of lakes, analyzing changes in backscattering coefficients and brightness temperature. This method aligns with ground station observations and ensures consistent surface type classification. Additionally, a dual-threshold algorithm that addresses the limitations of the original bimodal algorithm by identifying multiple peaks without needing elevation correction is introduced. This innovative approach significantly enhances the precision of equivalent water level measurements for ice-covered lakes. The study retrieves and compares the water level data of nine North American lakes covered by ice from 2016–2019 using the dual-threshold and the SAMOSA-3 algorithm with in situ data. For Lake Athabasca, Cedar Lake, Great Slave Lake, Lake Winnipeg, and Lake Erie, the root mean square error (RMSE) of SAMOSA-3 is 39.58 cm, 46.18 cm, 45.75 cm, 42.64 cm, and 6.89 cm, respectively. However, the dual-threshold algorithm achieves an RMSE of 6.75 cm, 9.47 cm, 5.90 cm, 7.67 cm, and 5.01 cm, respectively, representing a decrease of 75%, 79%, 87%, 82%, and 27%, respectively, compared to SAMOSA-3. The dual-threshold algorithm can accurately estimate water levels in ice-covered lakes during winter. It offers a promising prospect for achieving long-term, continuous, and high-precision water level measurements for middle- and high-latitude lakes.

Lake ice phenology (LIP), hiding information about lake energy and material exchange, serves as an important indicator of climate change. Utilizing an efficient technique to swiftly extract lake ice information is crucial in the field of lake ice research. The Bayesian ensemble change detection (BECD) algorithm stands out as a powerful tool, requiring no threshold compared to other algorithms and, instead, utilizing the probability of abrupt changes to detect positions. This method is predominantly employed by automatically extracting change points from time series data, showcasing its efficiency and accuracy, especially in revealing phenological and seasonal characteristics. This paper focuses on Bosten Lake (BL) and employs PMRS data in conjunction with the Bayesian change detection algorithm. It introduces an automated method for extracting LIP information based on the Bayesian change detection algorithm. In this study, the BECD algorithm was employed to extract lake ice phenology information from passive microwave remote sensing data on Bosten Lake. The reliability of the passive microwave remote sensing data was further investigated through cross-validation with MOD10A1 data. Additionally, the Mann–Kendall non-parametric test was applied to analyze the trends in lake ice phenology changes in Bosten Lake. Spatial variations were examined using MOD09GQ data. The results indicate: (1) The Bayesian change detection algorithm (BCDA), in conjunction with PMRS data, offers a high level of accuracy and reliability in extracting the lake ice freezing and thawing processes. It accurately captures the phenological parameters of BL’s ice. (2) The average start date of lake ice freezing is in mid-December, lasting for about three months, and the start date of ice thawing is usually in mid-March. The freezing duration (FD) of lake ice is relatively short, shortening each year, while the thawing speed is faster. The stability of the lake ice complete ice cover duration is poor, averaging 84 days. (3) The dynamic evolution of BL ice is rapid and regionally distinct, with the lake center, southwest, and southeast regions being the earliest areas for ice formation and thawing, while the northwest coastal and Huang Shui Gou areas experience later ice formation. (4) Since 1978, BL’s ice has exhibited noticeable trends: the onset of freezing, the commencement of thawing, complete thawing, and full freezing have progressively advanced in regard to dates. The periods of full ice coverage, ice presence, thawing, and freezing have all shown a tendency toward shorter durations. This study introduces an innovative method for LIP extraction, opening up new prospects for the study of lake ecosystem and strategy formulation, which is worthy of further exploration and application in other lakes and regions.

Small bodies of water in densely populated areas have not yet been thoroughly studied in terms of their ice cover. Filling the existing research gap related to ice cover occurrence is therefore important for identifying natural processes (e.g., response to climate warming and water oxygenation in winter), and also has socio-economic significance (e.g., reducing the risk of loss of health and life for potential ice cover users). This paper addresses the issue of determining the utility of two simple empirical models based on the accumulated freezing degree-days (AFDD) formula for predicting maximum ice thickness in water bodies. The study covered 11 small anthropogenic water bodies located in the Katowice Upland and consisted of comparing the values obtained from modelling with actual ice thicknesses observed during three winter seasons (2009/2010, 2010/2011, and 2011/2012). The best fit was obtained between the values observed and those calculated using Stefan's formula with an empirical coefficient of 0.014. A poorer fit was obtained for Zubov's formula (with the exception of the 2011/2012 season), which is primarily due to the fact that this model does not account for the thickness of the snow accumulated on the ice cover. Bengst'cise forecasting of the state of the ice cover and the provision of the relevant information to interested users will increase the safety of using such water bodies in climate warming conditions, reducing the number of accidents. [ABSTRACT FROM AUTHOR]

Khovsgol Lake, a seasonal ice-covered lake located in boreal Siberia, plays important economic, transportation and agricultural roles for local residents. On 11 January 2021, an Mw 6.7 earthquake struck the center of this lake, providing a unique opportunity to better understand lake ice movement, ridge distribution, and hydraulic and hydrodynamic processes, as a result of the mainshock. We use a pixel-tracking method on both Sentinel-1 synthetic aperture radar and Sentinel-2 optical remote-sensing data covering this lake before, during and after the mainshock to obtain lake-ice displacement. Combining these measurements with different viewing geometries, we determine the locations of pressure ridges in each period and derive their relative 3D displacement maps with a precision of <2.2 m. Our results indicate a large E-W displacement of up to 10.3 m and a vertical displacement of up to 4.6 m during the coseismic period, which has a distinctly different magnitude and pattern of displacement compared to the pre- and post-event periods. Given the ice motion pattern and magnitude, we speculate that the unique ice displacement of Khovsgol Lake may have been caused by a rare seismic seiche after the mainshock. [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. [ABSTRACT FROM AUTHOR]

The surface morphology of lake ice undergoes remarkable changes under the combined influence of thermal and mechanical forces, which has been rarely observed by remote sensing. A large-scale linear structure has repeatedly appeared on satellite images of Chagan Lake in recent years. We prosed a method to extract linear structure on the lake ice surface. We applied it to high spatial-temporal images merged by the Landsat and GOCI images using an enhanced spatial and temporal adaptive reflectance fusion model (ESTARFM). We monitored the changes in surface morphology in Chagan Lake from November 2018 to March 2019, which were further verified as ice ridges during the field investigation. The average length of the ice ridges during the completely frozen period was 21141.57 ± 68.36 m. The average azimuth angle was 335.48° ± 0.23°, perpendicular to the wind domain. Besides, we discovered spherical ice balls along the southwestern coast. The deformation of surface morphology is closed related to wind direction, snowfall, and air temperature. [ABSTRACT FROM AUTHOR]

Recent investigations using polarimetric decomposition and numerical models have helped to improve the understanding of how radar signals interact with lake ice. However, further research is needed on how radar signals are impacted by varying lake ice properties. Radiative transfer (RT) models provide one method of improving this understanding. These are the first published experiments using the snow microwave RT (SMRT) model to investigate the response of different frequencies (L-, C-, and X-band) at horizontal-horizontal (HH) and vertical-vertical (VV) polarizations using various incidence angles (20°, 30°, and 40°) to changes in ice thickness, porosity, bubble radius, and ice–water interface roughness. This is also the first use of SMRT in combination with a thermodynamic lake ice model. Experiments were for a lake with tubular bubbles and one without tubular bubbles under difference scenarios. An analysis of the backscatter response to different properties indicates that increasing ice thickness and layer porosity have little impact on backscatter from lake ice. X-band backscatter shows increased response to surface ice layer bubble radius; however, this was limited to other frequencies except at shallower incidence angles (40°). All three frequencies display the largest response to increasing root mean square (rms) height at the ice–water interface, which supports surface scattering at the ice–water interface as being the dominant scattering mechanism. These results demonstrate that the SMRT is a valuable tool for understanding the response of backscatter to changes in freshwater lake ice properties and could be used in the development of inversion models. [ABSTRACT FROM AUTHOR]

Lake ice thickness (LIT), a thematic product of lakes as an essential climate variable (ECV), is sensitive to changes in air temperature and on-ice snow mass. Here, a novel and efficient analytic method (retracking approach) is presented for the estimation of LIT from Ku-band (13.6 GHz) radar altimetry data. The new retracker, referred to as ${{\mathtt {LRM}}\_{}{\mathtt {LIT}}}$ , is based on the physical modeling of the conventional radar echoes (also called low-resolution mode or LRM) over ice-covered lakes that show a characteristic step-like feature in their leading edge attributed to the reflection of radar waves at the snow–ice and ice–water interfaces. The method is applied to Jason-2 and Jason-3 data acquired over Great Slave Lake, Canada, over three ice seasons (2013–2016). As expected, the agreement between the Jason-2 and Jason-3 LIT estimates over their overlapping period (2016 ice season) is excellent with a mean bias error of 0.013 m and root mean square error (RMSE) of 0.024 m. LIT estimates from ${{\mathtt {LRM}}\_{}{\mathtt {LIT}}}$ are in good agreement with simulations from a thermodynamic lake ice model and in situ measurements with RMSE values of the order of a few centimeters for the three winter seasons. The retracker also provides a robust way to assess the accuracy of LIT estimates which is in the order of 0.10 m when the ice cover is well established and prior to melt onset. In addition, ${{\mathtt {LRM}}\_{}{\mathtt {LIT}}}$ captures the seasonal transitions during the freeze-up and breakup periods and ice growth over different winter seasons, making it a promising method for monitoring inter-annual variability and trends in LIT from past and current conventional radar altimetry missions. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The occurrence of harmful algal blooms (HABs) in coastal and inland waters has a significant impact on societies. This complex biogeophysical phenomenon becomes further complicated due to the impact of climate change. This review summarizes the research performed in recent years in the direction of climate change on three lake parameters, viz. lake temperature, precipitation, runoff, and lake ice, which impacts the lake ecology and, in turn, impacts the HABs. The present paper also reviews the research work related to the relationship between climate change and HABs. The purpose of this study is to provide the researchers with the opportunity to understand the current research in the direction of climate change and HABs so they can contribute effectively to one of the most important phenomena that will severely impact water quality in the future warmer climate, in coastal as well as inland water bodies. Furthermore, this work aims to discuss how HABs will change in the future warmer climate. [ABSTRACT FROM AUTHOR]

In ice-covered polar lakes, a narrow ice-free moat opens up in spring or early summer, and then persists at the edge of the lake until complete ice loss or refreezing. In this study, we analyzed the horizontal gradients in Ward Hunt Lake, located in the Canadian High Arctic, and addressed the hypothesis that the transition from its nearshore open-water moat to offshore ice-covered waters is marked by discontinuous shifts in limnological properties. Consistent with this hypothesis, we observed an abrupt increase in below-ice concentrations of chlorophyll a beyond the ice margin, along with a sharp decrease in temperature and light availability and pronounced changes in benthic algal pigments and fatty acids. There were higher concentrations of rotifers and lower concentrations of viruses at the ice-free sampling sites, and contrasts in zooplankton fatty acid profiles that implied a greater importance of benthic phototrophs in their inshore diet. The observed patterns underscore the structuring role of ice cover in polar lakes. These ecosystems do not conform to the traditional definitions of littoral versus pelagic zones but instead may have distinct moat, ice-margin, and ice-covered zones. This zonation is likely to weaken with ongoing climate change.

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.

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.

Lakes are rapidly losing ice under global warming, but little is known about ice structure changes. Ice structure is a key regulator of ice stability and thus safety, affecting activities on ice. Here, we analysed spatial and temporal variations in ice structure across 21 Swedish lakes, spanning from 55 to 69 °N, and over five decades. We found regional differences in ice structure, with fastest changes occurring in southern Sweden. The stable clear ice layer was particularly sensitive to warming, showing a rapid decline. The number of days when temperatures exceeded the freezing point during the ice cover period was identified as a strong driver for how ice was structured. Since there is a high risk for increased occurrences of unsafe ice conditions under predicted air temperature changes, we recommend re-establishing ice structure monitoring programmes, informing society on the increased risks of being on ice and including ice structure to safety guidelines., (© 2024. The Author(s).)

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]