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Lake ice thickness (LIT) is important for regional hydroclimate systems, lake ecosystems, and human activities on the ice, and is thought to be highly susceptible to global warming. However, the spatiotemporal variability in LIT is largely unknown due to the difficulty in deriving in situ measurements and the lack of an effective remote sensing platform. Despite intensive development and applications of lake ice models driven by general circulation model output, evaluation of the global LIT is mostly based on assumed “ideal” lakes in each grid cell of the climate forcing data. A method for calculating the actual global LIT is therefore urgently needed. Here we use satellite altimetry to retrieve ice thickness for 16 large lakes in the Northern Hemisphere (Lake Baikal, Great Slave Lake, and others) with an accuracy of ∼0.2 m for almost three decades. We then develop a 1-D lake ice model driven primarily by remotely sensed data and cross-validated with the altimetric LIT to provide a robust means of estimating LIT for lakes larger than 50 km2 across the Northern Hemisphere. Mean LIT (annual maximum ice thickness) for 1313 simulated lakes and reservoirs covering ∼840,000 km2 for 2003–2018 is 0.63 ± 0.02 m, corresponding to ∼485 Gt of water. LIT changes are projected for 2071–2099 under RCPs 2.6, 6.0, and 8.5, showing that the mean LIT could decrease by ∼0.35 m under the worst concentration pathway and the associated lower ice road availability could have a significant impact on socio-economic activities.

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.

Lake ice phenology is regarded as a good proxy for the past and present climates. Long time series passive microwave radiometry data are used to estimate lake ice phenology variations in the Qinghai–Tibet Plateau (QTP), and a contrasting pattern of phenology change trend is found that the time series trend of lake ice freeze-up or break-up time is obviously reversed for lakes in the QTP. The reason for this contrasting trend of lake ice phenology is discussed based on factors such as salinity, water volume change, and air temperature change. Lake ice phenology data are separated based on lake salinity for the climate study: lake ice phenology of lakes with low salinity can be used as air temperature and climate change indicator, whereas lake ice phenology of lakes with high salinity and a low water volume can be used as an indicator of water volume variation under climate change. Correlation analysis of air temperature and the lake ice phenology show that air temperature is the main driving factor behind lake ice phenology variations. The lake ice phenology results suggest overall rising air temperatures during the period 1987–2017 in all regions of the QTP.

Timely information on lake ice cover conditions is critical in support of commercial shipping, winter-road transportation, and winter leisure activities such as snowmobiling and ice fishing. Monito...

Despite long‐term analyses of lake ice phenology globally, comparatively little is known about high‐elevation lakes, for which climate shifts are thought to be occurring faster than at lower elevations. Using a 36‐yr dataset (1983–2018) on alpine lakes (> 3000 m ASL) from the Green Lakes Valley, Colorado (GLV), we found that ice‐cover duration decreased by an average of ~ 24 d, due to both earlier ice‐off (9 d) and especially later ice‐on (15 d). Spring ice thickness also decreased by 0.88 cm yr−1. By comparison, ice‐cover duration in the GLV is decreasing ~ 50% faster than for Northern Hemisphere lakes (n = 215), which translates to an increase in open water duration ~ 2.5 times more in the GLV than the average of the Northern Hemisphere. Our analytical comparison demonstrated more rapid trends in this alpine region compared to lakes more broadly, and especially emphasized the influence of elevation on lake ice phenology.

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.

A key aspect of ice impacts on ship hulls and other structures is the shape of the impacted surface, particularly when there is plastic deformation due to the impact force/pressure and potential for increased confinement. To study this issue, some relatively simple ice-crushing tests have been performed in the lab using four different acrylic crushing platens: one that was flat, a second that had a shallow spherical-cap hollow, a third with a spherical-cap hollow with a greater radius of curvature, and a fourth with a cylindrical-cap hollow. The influences of the ‘degree of hollow’ and ‘shape of hollow’, i.e. the amount of confinement, were investigated by crushing identically-shaped granular freshwater ice specimens against the four platens, where the penetration rate was 16 mm/s and the ambient temperature was -10 °C. In addition to load/displacement measurements, high-speed imaging data of the platen-ice interface (to view hard-zone / soft-zone ice contact evolution during crushing) were acquired through the transparent acrylic platens. The shape and loading characteristics of the ice at the contact interface are discussed in the context of the four differing crushing-platen surface shapes. The average load data throughout the penetration range for the four crushing platens can be explained by three effects: the differing degrees of lateral confinement generated by the various platens; the flow and constriction behavior of the crushed ice (i.e. shattered-spall debris) generated by spallation events at the hard zones; the increasing bulk-ice confinement with penetration as the platens get closer to the ice-holder at the base of the ice samples., 26th IAHR International Symposium on Ice, June 19-23, 2022, Montréal, Québec, Canada

ICEWEAR is a five-year research program, seeking to improve knowledge of surface wear and surface friction influences on the ice-induced wear of concrete structures in polar marine environments. Through the program, a variety of research lines have examined these influences, through ice-concrete interaction laboratory testing, investigations of ice-concrete contact physics, wear reduction strategies and modelling and analysis. The ICEWEAR research program adds to previous research programs over the past five decades that have examined ice-concrete contact phenomena. It also goes further by investigating the hybridization of ASTM and other standardized testing procedures/equipment in order to design new, meaningful, robust ice-concrete tests that can be standardized to better-enable the comparison of results across research programs. This paper will present some of the outputs from the first of these lines of research, with examples of the construction, testing and optimization of new equipment for adhesion, friction, wear and impact ice-concrete contact studies. The paper considers the effects of experimental design, and in particular, the influence of time and pressure on the experimental results., 26th IAHR International Symposium on Ice, June 19-23, 2022, Montréal, Québec, Canada

International audience; Zooplankton can spend winter actively under the ice cover of lakes. However, dietary resources under lake ice are both quantitatively and qualitatively limited, and feeding might not be energetically rewarding for most zooplankton species. Many zooplankters are expected to fast throughout the winter, exhausting their previously accumulated fat storage. We hypothesised that only a fraction of the actively overwintering zooplankton contributes to an active food web under lake ice, leading to few trophic linkages within the planktonic community.2. Zooplankton habitats and feeding were investigated under the ice of Lake Onego. Zooplankton habitats and migrations were studied by coupling zooplankton sam-pling around the clock to measurements of particle movement using an acoustic Doppler current profiler. Secondly, fatty acid-specific stable isotope compositions were used to determine whether and which zooplankton fatty acids ultimately came from the assimilation of under-ice seston.3. The algal biomass was low under ice and mostly dominated by large diatoms. Copepods dominated the zooplankton community. Species present as late cope-podite and adult instars were confined to the deeper layers, while nauplii occupied the surface layer. Diel vertical migration by Cyclops was the most tangible ob-servation of persistent feeding under the ice. Previously accumulated fat storage represented most of zooplankton fatty acids, with few, yet detectable, fatty acids recently acquired by feeding under the ice.4. Although some zooplankton taxa maintained feeding activity under the ice of Lake Onego, the food source available beneath the ice was not sufficiently rewarding to leave an isotopic imprint upon the dominant fatty acids of bulk zooplankton. The seston fatty acids that were passed on to zooplankton from feeding under ice were not provided by diatoms, although they made up most of the phytoplank-ton biovolume. Instead, the zooplankton food web was supported by mixotrophic phytoplankton (i.e. cryptophytes and chrysophytes) that represented

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.

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.

Spectral albedo and light transmittance through snow, ice, and water were measured in Lake Wuliangsuhai (40 degrees 36 '-41 degrees 30 ' N, 108 degrees 43 '-108 degrees 70 ' E), Inner Mongolia, China, during winter 2016. Data on the weather, structure of lake ice, and geochemistry of water were also collected during the 60-day field program. The study lake is shallow (mean depth 1.0-1.5 m) with a large wetland area. Compared with polar lakes, solar elevation is higher, snow accumulation is much lower, and the ice has more sediment. The ice was all congelation ice with a mean thickness of 36.6 cm, corresponding to a mean air temperature of -9.6 degrees C. The mean daily broadband albedo and photosynthetically active radiation (PAR) band transmittance were 0.54 and 0.08 (bare ice), 0.74 and 0.04 (new snow), and 0.30 and 0.12 (melting period), respectively. The level of light allowed photosynthesis to occur to the bottom of the lake. The ice acted as a grey filter for the sunlight with a mean attenuation coefficient of 2.1 m(-1). These results expand our knowledge of the evolution of light transfer through ice and snow cover and its role in the ecology of lakes in temperate and arid areas.

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.

To understand the variations in surface water associated with changes in air temperature, precipitation, and permafrost in the Headwater Area of the Yellow River (HAYR), we studied the dynamics of alpine lakes larger than 0.01 km2 during 1986–2019 using Google Earth Engine (GEE) platform. The surface areas of water bodies in the HAYR were processed using mass remote sensing images consisting of Landsat TM/ETM+/OLI, Sentinel-2A, and MODIS based on automatic extraction of water indices under GEE. Besides, the lake ice phenology of the Sister Lakes (the Gyaring Lake and the Ngoring Lake) was derived by threshold segmenting of water/ice area ratio. Results demonstrate that the change of surface areas experienced four stages: decreasing during 1986–2004, increasing during 2004–2012, decreasing again during 2012–2017, and increasing again during 2017–2019. Correspondingly, the number of small lakes decreased (−26.5 per year), increased (139.5 per year), again decreased (−109.0 per year), and again increased (433.0 per year). Eight lakes larger than 1 km2 disappeared in 2004 but restored afterward. The overall trends in the area of small lakes (0.01–1 km2), large lakes (>1 km2), and all lakes during 1986–2019 were 0.4, 3.1, and 3.4 km2 per year, respectively. Although the onsets of freezing, freeze-up, breaking and the break-up of the Sister Lakes varied from year to year, there is no obvious trend regarding the lake ice phenology. Tendencies of lake variations in the HAYR are primarily related to the increased net precipitation and the declined aridity, followed by the construction of hydropower station around the outlet of the Ngoring Lake, as well as permafrost degradation.

The lake ice phenology response to climate change has been receiving growing concern in recent years. However, most studies have put emphasis on the spatial and temporal variability of lake ice phenology, and relatively few studies have been devoted to investigating the physical mechanisms of changes in lake ice phenology from the perspective of climatic dynamics. This study investigates the possible impact of the Antarctic Oscillation (AAO) on the variations in lake ice phenology over the Tibetan Plateau (TP). The results show that there is an intimate relationship between the AAO and the variations in break-up/ice duration during the period 2003–15. Further analysis indicates that the preceding boreal spring AAO-induced atmospheric circulation anomalies are favorable for generating tropical South Atlantic Ocean SST anomalies through air–sea interaction. Then the tropical SST anomalies strengthen the anomalous local-scale meridional–vertical circulation that projects into the Azores high and further induce the extratropical portion of the North Atlantic SST tripole. The anomalous warm core in the North Atlantic serves as the source of wave activity flux and stimulates a stationary wave train along the Eurasian continent to change the downstream atmospheric circulation. As a response, an abnormal cyclone and enhanced updraft are triggered over the TP, which are favorable for the formation of snowfall and then lower the surface air temperature according to the snow-albedo feedback mechanism, and thus result in the prolonged lake ice duration events. This study provides a new insight to link the AAO influence and climate over the TP and is helpful to understand the changes in lake ice phenology in response to climate change in recent years.

Lake ice phenology is a sensitive indicator reflecting global warming. In this article, the long-term changes in lake ice phenology of the second-largest lake at Tibetan Plateau (i.e., the Nam Co) in response to climate change are investigated based on mathematical modeling. The model has been testified capable of reproducing daily surface temperature of the lake in both frozen and unfrozen seasons. The lake ice phenology determined according to the simulated lake surface temperature is found consistent with that derived from satellite observations. For the Nam Co during the period 1978–2017, the freezing date has been delayed (reached up to 0.57 days/year), whereas the thawing date became earlier (−0.23 days/year). The trend of lake ice phenology is significantly correlated to the annual minimal lake surface and air temperature. Modeling experiment suggests that lake ice phenology of the Nam Co is very sensitive to a warmer climate. Under warmer future, much later freezing date and earlier thawing date are expected; hence the ice-covering duration would be significantly shortened.

Anomalous areas of varying shape and location characterized by low backscatter in Synthetic Aperture Radar (SAR) imagery of lake ice on lake Neyto on the Yamal Peninsula in Russia have been described qualitatively in the literature for many years. Possible suggested causes are the formation of eddies or the release of gas through the lake sediments, which could both lead to local thinning of the ice layer and alter radar backscatter. To date, the phenomenon, its cause, and its spatial and temporal dynamics are poorly understood, and studies from other geographic regions are completely absent. In order to perform first steps towards a better understanding of the phenomenon, we developed a workflow to quantitatively assess the spatial variability of the anomalies in the years 2015 to 2019 for lake Neyto. We introduce a binary image classification algorithm developed with state-of-the-art open-source image processing tools and employ metrics commonly used for describing spatial relationships of vector and raster data. This includes polygon distances, polygon intersections and cumulative pixel counts deduced from the classification results in order to quantify, for the very first time, the dynamics over a number of years. The geospatial analysis reveals large spatial variations, but also some overlap between different years. Locations of anomalies do not seem more similar between consecutive years than when they are compared over the longer period. Some of the spatial properties of the clusters of low backscatter may support the explanation of gas release as the primary cause of the observed patterns.

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.

The quality of lake ice is of uppermost importance for ice safety and under-ice ecology, but its temporal and spatial variability is largely unknown. Here we conducted a coordinated lake ice quality sampling campaign across the Northern Hemisphere during one of the warmest winters since 1880 and show that lake ice during 2020/2021 commonly consisted of unstable white ice, at times contributing up to 100% to the total ice thickness. We observed that white ice increased over the winter season, becoming thickest and constituting the largest proportion of the ice layer towards the end of the ice cover season when fatal winter drownings occur most often and light limits the growth and reproduction of primary producers. We attribute the dominance of white ice before ice-off to air temperatures varying around the freezing point, a condition which occurs more frequently during warmer winters. Thus, under continued global warming, the prevalence of white ice is likely to substantially increase during the critical period before ice-off, for which we adjusted commonly used equations for human ice safety and light transmittance through ice. Under continued global warming, lakes will increasingly be covered by white ice, in particular towards the end of the ice cover season when fatal winter drownings occur most often and light limits the growth and reproduction of primary producers.

Paper cite as :Zhang, G., and S. Duan (2021), Lakes as sentinels of climate change on the Tibetan Plateau, All Earth, doi: 10.1080/27669645.2021.2015870 Data available: Air temperature (T) at Gangcha station from 1958 to 2019 Lake surface water temperature (LSWT) at Xiashe station from 1967 to 2020 Lake ice depth and lake ice duration at Xiashe station from 1994 to 2020 Precipitation (P) at Gangcha station from 1958 to 2019 Runoff at Buha station from 1956 to 2020 Lake level at Xiashe station from 1956 to 2020 Lake area from 1956 to 2020 estimated from the correlation constructed between lake area derived from Landsat images and lake level from gauge measurements in 2001−2020

Ice Engineering is associated with how to solve challenges from different kinds of ice, such as, sea ice, river ice, lake ice, icing, and snow in cold regions. The aim is to design special structures which could resist structural and global impact from drifting ice and freezing ice.

As the global climate warms, lakes are expected and have been observed to experience changes in seasonal ice cover. Previous research has observed decreasing freeze durations, but relatively few studies have investigated the impact of climate change on lake ice intermittency - the tendency of lakes to freeze over in some years but not others. Here we conduct an analysis of a lake dataset that includes nineteen intermittent ice-covered lakes in the northern hemisphere. We use logistic and binomial regression to model the relationship between historical climate changes and freeze events, with log CO2 concentration and mean winter temperature as covariates. Across the lakes, we observe a decrease in freeze probability and years with freeze events, with nine out of nineteen lakes showing a significant relationship between freeze years and log CO2 concentration. Additionally, we find that mean winter temperature can be a simple, readily accessible predictor for intermittent lake freeze. We also examine Lake Carnegie in Princeton, NJ as a case study, taking into account both quantitative data and anecdotal evidence, and find that the probability of ice skating has decreased from nearly 1 to 0.2 over the past century. Accordingly, local newspaper archives semantically suggest that local expectations for lake freezing have reversed over the last century as a societal response to climate change.

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. (Less)

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 u...

Studies of lake ice phenology have historically relied on limited in situ data. Satellite-derived temperature data provide an opportunity to better understand the climatological factors and trends behind ice phenology. Here we developed a model that uses daytime and nighttime surface temperature observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard Aqua to approximate ice in for 13 lakes and ice out for 58 lakes in Maine from 2002–2018. Ice-in and ice-out approximations were signaled by a moving average of the data crossing the 0°C threshold. The comparison of in situ and satellite-derived ice-out and ice-in dates were both highly correlated, but the amount of bias in those estimates was influenced by the number of days in a moving average of temperature. Systematic biases in the approximation model toward predicting ice in too early and ice out too late point to the importance of in-lake dynamics in modifying the timing of stabilization or melting of ice.

Lakes sensitively respond to global and regional climate change, especially in arid areas. Using Moderate Resolution Imaging Spectroradiometer (MODIS) daily snow products, the lake ice phenology of 23 lakes in the Xinjiang Uygur Autonomous Region of China from 2001 to 2018 was extracted based on thresholds of ice/water pixel numbers, and their change trends over 18 years were calculated. The results of MODIS-derived lake ice phenology showed consistent variations with existing ice phenology data sets derived from passive microwave data. Generally, lakes in Xinjiang begin to freeze from October to December every year, and their ice cover periods end from March to June. The average ice cover duration for the 23 lakes is 167 days, of which 16 lakes have an average shortening rate of − 1.08 days/year and seven lakes have an average extending rate of 1.18 days/year. The majority of lakes experienced later freeze-up (17 lakes) and earlier break-up (18 lakes) from 2001 to 2018. Lake ice phenology is affected by both climatic factors and lake physicochemical characteristics, in which freeze-up dates are more easily affected by lake-specific factors such as lake area (r = 0.535), while climatic factors especially water surface temperature have greater impacts on lake break-up dates (r = − 0.874). Compared to air temperature, water surface temperature changes have a more direct influence on the variations in lake ice phenology, 1° increase in water surface temperature may cause the ice cover duration to decrease by 12 days, while precipitation changes have almost no effect on the lakes in Xinjiang. In some cases, lake changes such as changes to the area and mineralization may also have dominant impacts on lake ice phenology.

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

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.

Changes in climate, warming temperatures and increased precipitation are impacting surface water resources in the Northwest Territories, Canada. Satellite remote sensing is an important tool to mon...

The article presents the ice phenology of Lake Ostrzyckie, which is a water body covering an area of 308 ha located in the central part of the Kashubian Lakeland, northern Poland. The analysis presented in the article is based on data from daily ice phenomena monitoring for the period of 1971–2010. Data including forms of lake ice, as well as the thickness of the ice cover were obtained from the Institute of Meteorology and Water. In order to present relations between the ice phenomena and air temperature the meteorological data from the Gdańsk University Limnological Station in Borucino were used. The article presents changes in the duration time of the ice seasons and changes in the ice cover duration time in relation to winter season (November–April) temperatures. The structure of the ice phenomena duration period observed on Lake Ostrzyckie consists of three different stages of ice cover formation. 94% of this time the lake is covered by permanent ice cover, the freezing period takes about 5%, and the break-up takes only 1% of the ice phenomena duration period. In general the ice phenomena in the lake can occur only in the years when the average air temperature in the winter is lower than 5.0°C, whereas the permanent ice cover is created when the average air temperature of the winter season is lower than 4.8°C. The maximum thickness of the ice cover is usually 23 cm, and the average is 14 cm.

In this study, we coupled the two-layer one-dimensional Freshwater lake (FLake) model into the Climate Forecast System (CFS) version 2 to improve simulations of the effects of the Great Lakes on winter climate forecasts in that region. We first incorporated global lake fraction and depth data into the coupled CFS-FLake through a subgridding system. An interface between the CFS and FLake was then developed to link the two models for energy and water flux exchanges. The lake scheme was triggered only if the lake fraction was more than 10% in one CFS grid cell. We conducted ensemble retrospective forecasts with CFS-FLake for the period of 1997 through 2016 with 9 monthly leads. These forecasts were assessed to obtain a better understanding of the role of the Great Lakes in the climate system for winter, when significant lake-effect precipitation often occurs. Our results indicate that forecasts of lake surface temperature (LST), lake ice coverage (LIC), and precipitation with CFS-FLake were consistently better than those with CFS. The major improvements resulted from changes in land use type for the Great Lakes, from ocean and land in CFS to lakes in CFS-FLake. With the change from ocean to lake, LST mostly decreased with increasing LIC, resulting in lower surface heat and water fluxes to the atmosphere during the winter. However, with the change from land to lake, LST increased, leading to higher heat and water fluxes. In the meantime, precipitation predicted by CFS-FLake was reduced quite significantly over the Great Lakes compared to that by CFS. This reduction was caused by suppressed rising motion due to increased stability in the lower atmosphere as a result of lowered surface heat and water fluxes. The results from this study indicate that local and mesoscale surface and atmospheric processes significantly affect regional climate forecasts, and the coupled CFS-FLake model will have a broader impact on climate and hydrology research and forecasts.

The Tibetan Plateau houses numerous lakes, the phenology and duration of lake ice in this region are sensitive to regional and global climate change, and as such are used as key indicators in climate change research, particularly in environment change comparison studies for the Earth three poles. However, due to its harsh natural environment and sparse population, there is a lack of conventional in situ measurement on lake ice phenology. The Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Snow Index (NDSI) data, which can be traced back 20 years with a 500 m spatial resolution, were used to monitor lake ice for filling the observation gaps. Daily lake ice extent and coverage under clear-sky conditions was examined by employing the conventional SNOWMAP algorithm, and those under cloud cover conditions were re-determined using the temporal and spatial continuity of lake surface conditions through a series of steps. Through time series analysis of every single lake with size greater than 3 km2 in size, 308 lakes within the Tibetan Plateau were identified as the effective records of lake ice extent and coverage to form the Daily Lake Ice Extent and Coverage dataset, including 216 lakes that can be further retrieved with four determinable lake ice parameters: Freeze-up Start (FUS), Freeze-up End (FUE), Break-up Start (BUS), and Break-up End (BUE), and 92 lakes with two parameters, FUS and BUE. Six lakes of different sizes and locations were selected for verification against the published datasets by passive microwave remote sensing. The lake ice phenology information obtained in this paper was highly consistent with that from passive microwave data at an average correlation coefficient of 0.91 and an RMSE value varying from 0.07 to 0.13. The present dataset is more effective at detecting lake ice parameters for smaller lakes than the coarse resolution passive microwave remote sensing observations. The published data are available in https://data.4tu.nl/repository/uuid:fdfd8c76-6b7c-4bbf-aec8-98ab199d9093 and http://www.sciencedb.cn/dataSet/handle/744.

Climate change is expected to decrease ice coverage and thickness globally while increasing the variability of ice coverage and thickness on midlatitude lakes. Ice thickness affects physical, biological, and chemical processes as well as safety conditions for scientists and the general public. Measurements of ice thickness that are both temporally frequent and spatially extensive remain a technical challenge. Here new observational methods using repurposed soil moisture sensors that facilitate high spatial–temporal sampling of ice thickness are field tested on Lake Mendota in Wisconsin during the winter 2015/16 season. Spatial variability in ice thickness was high, with differences of 10 cm of ice column thickness over 1.05 km of horizontal distance. When observational data were compared with manual measurements and model output from both the Freshwater Lake (FLake) model and General Lake Model (GLM), ice thickness from sensors matches manual measurements, whereas GLM and FLake results showed a thinner and thicker ice layer, respectively. The FLake-modeled ice column temperature effectively remained at 0°C, not matching observations. We also show that daily ice dynamics follows the expected linear function of ice thickness growth/melt, improving confidence in sensor accuracy under field conditions. We have demonstrated a new method that allows low-cost and high-frequency measurements of ice thickness, which will be needed both to advance winter limnology and to improve on-ice safety.

Trend analysis of spring ice-out on eight lakes within the state of Maine of the northeastern USA reveals a change to earlier occurrence by 1 to 2 weeks over the period 1956–2015. Much of the trend occurred from the late 1970s through the 1980s, but a secondary trend toward earlier ice-out appears to have begun in the late 1990s. Synoptic climate data support local and hemispheric climate evidence of increasingly earlier ice-out, particularly during the earlier period of pronounced change. Local spring and winter maximum daily air temperatures increased while winter precipitation decreased; synoptic weather types of moderate temperature character increased in frequency, while polar types became less frequent; synoptic weather types became warmer in spring and winter, and in spring, warmer weather types became wetter, while cooler weather types became drier; and two key climate teleconnections, the Pacific-North American pattern and the El Nino/La Nina pattern, changed significantly toward a phase historically associated with earlier ice-out. While the results underscore the value in monitoring and study of lake ice as a climate proxy, they also demonstrate the value of synoptic climate data for filling the spatial gap between local and large-scale climate data in studies of lake ice phenology.

Optical remote sensing images with high temporal resolution can be used to monitor lake ice phenology, a periodic freezing and thawing cycle of ice resulting from seasonal and inter-annual climate ...

Ice provides a range of ecosystem services—including fish harvest1, cultural traditions2, transportation3, recreation4 and regulation of the hydrological cycle5—to more than half of the world’s 117 million lakes. One of the earliest observed impacts of climatic warming has been the loss of freshwater ice6, with corresponding climatic and ecological consequences7. However, while trends in ice cover phenology have been widely documented2,6,8,9, a comprehensive large-scale assessment of lake ice loss is absent. Here, using observations from 513 lakes around the Northern Hemisphere, we identify lakes vulnerable to ice-free winters. Our analyses reveal the importance of air temperature, lake depth, elevation and shoreline complexity in governing ice cover. We estimate that 14,800 lakes currently experience intermittent winter ice cover, increasing to 35,300 and 230,400 at 2 and 8 °C, respectively, and impacting up to 394 and 656 million people. Our study illustrates that an extensive loss of lake ice will occur within the next generation, stressing the importance of climate mitigation strategies to preserve ecosystem structure and function, as well as local winter cultural heritage. Up to 35,000 lakes in the Northern Hemisphere may be at risk of intermittent winter ice cover at 2 °C warming, reveals an observation-based study. This would affect 394 million people reliant on lake ice for ecosystem services.

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.

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.

The lake ice phenology variations are vital for the land–surface–water cycle. Qinghai Lake is experiencing amplified warming under climate change. Based on the MODIS imagery, the spatio-temporal dynamics of the ice phenology of Qinghai Lake were analyzed using machine learning during the 2000/2001 to 2019/2020 ice season, and cloud gap-filling procedures were applied to reconstruct the result. The results showed that the overall accuracy of the water–ice classification by random forest and cloud gap-filling procedures was 98.36% and 92.56%, respectively. The annual spatial distribution of the freeze-up and break-up dates ranged primarily from DOY 330 to 397 and from DOY 70 to 116. Meanwhile, the decrease rates of freeze-up duration (DFU), full ice cover duration (DFI), and ice cover duration (DI) were 0.37, 0.34, and 0.13 days/yr., respectively, and the duration was shortened by 7.4, 6.8, and 2.6 days over the past 20 years. The increased rate of break-up duration (DBU) was 0.58 days/yr. and the duration was lengthened by 11.6 days. Furthermore, the increase in temperature resulted in an increase in precipitation after two years, the increase in precipitation resulted in the increase in DBU and decrease in DFU in corresponding years, and decreased DI and DFI after one year.

Lake-ice phenology is an essential indicator of climate change impact for different regions (Livingstone, 1997; Duguay, 2010), which helps understand the regional characters of synchrony and asynchrony. The observation of lake ice phenology includes ground observation and remote sensing inversion. Although some lakes have been observed for hundreds of years, due to the limitations of the observation station and the experience of the observers, ground observations cannot obtain the lake ice phenology of the entire lake. Remote sensing has been used for the past 40 years, in particular, has provided data covering the high mountain and high latitude regions, where the environment is harsh and ground observations are lacking. Remote sensing also provides a unified data source and monitoring standard, and the possibility of monitoring changes in lake ice in different regions and making comparisons between them. The existing remote sensing retrieval products mainly cover North America and Europe, and data for Eurasia is lacking (Crétaux et al., 2020).Based on the passive microwave, the lake ice phenology of 522 lakes in the northern hemisphere during 1978-2020 was obtained, including Freeze-Up Start (FUS), Freeze-Up End (FUE), Break-Up Start (BUS), Break-Up End (BUE), and Ice Cover Duration (ICD). The ICD is the duration from the FUS to the BUE, which can directly reflect the ice cover condition. At latitudes north of 60°N, the average of ICD is approximately 8-9 months in North America and 5-6 months in Eurasia. Limited by the spatial resolution of the passive microwave, lake ice monitoring is mainly in Northern Europe. Therefore, the average of ICD over Eurasia is shorter, while the ICD is more than 6 months for most lakes in Russia. After 2000, the ICD has shown a shrinking trend, except northeastern North America (southeast of the Hudson Bay) and the northern Tibetan Plateau. The reasons for the extension of ice cover duration need to be analyzed with parameters, such as temperature, the lake area, and lake depth, in the two regions.