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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.

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.

Millions of lakes and ponds occupy large areas of the Arctic discontinuous and continuous permafrost zones. During most of the year, the surfaces of these lakes remain covered by a thick layer of ice. Synthetic Aperture Radar (SAR) data have shown to be useful for studying the ice on Arctic lakes, especially for monitoring lake ice phenology and the grounding state of the ice (ice frozen to the lakebed versus floating lake ice). Significant backscatter is often observed from the floating ice regime in C-band due to scattering on a rough ice-water interface.Recent research has revealed features of anomalously low backscatter in Sentinel-1 C-band SAR imagery on some of the West Siberian lakes that likely belong to the floating ice regime. These anomalies are characterized by prominent shapes and sizes and seem to expand throughout late winter and/or spring. It is currently assumed that some of these features are related to strong emissions of natural gas (methane from hydrocarbon reservoirs), making it important to assess their origin in detail and understand the associated mechanisms. However, in-situ data are still missing.Here, we assess the potential of the combined use of C-band Sentinel-1 (freely available) and L-band ALOS PALSAR-2 data (available through JAXA PI agreement #3068002) to study the backscatter anomalies. We highlight the differences between observed backscatter from the two sensors with respect to different surface types (ground-fast lake ice, floating lake ice and anomalies) and investigate backscatter differences between frozen and melting conditions. Further, polarimetric classification is performed on L-band PALSAR-2 imagery, which reveals differences in scattering mechanisms between anomalies and floating lake ice.

Lake ice cover is essential to conserving the global freshwater supply for the 50 million lakesthat freeze each winter. Here, we ask when lakes across the Northern Hemisphere may permanently loseice cover. A K-means cluster analysis from 31 lakes identified four clusters of lakes vulnerable to losing icecover, including shallow and deep lakes in regions where winter air temperatures hover ∼0 °C and largerand deeper lakes in colder regions. By the end of this century, we estimate that up to 5,679 lakes of 1.35million HydroLAKES may permanently lose ice cover if greenhouse gas emissions (GHG) continue tobe emitted at current levels. In the Northern Hemisphere, lakes in southern and coastal regions, some ofwhich are among the largest lakes in the world and in close proximity to large human populations, are themost vulnerable to permanently losing ice.

The seasonal cycle of ice thickness and temperature in Lake Wuliangsuhai, a typical shallow lake in the central Asian arid climate zone, was simulated using the HIGHTSI model and the MERRA-2 data as the meteorological forcing. The average ice growth rate was 0.64 cm·d−1 and −1.65 cm·d−1 for the growth and melting stage of the ice cover, respectively. The ice thickness agreed well with the field observations conducted in winter 2017, with a correlation coefficient of 0.97. The ice temperature field also agreed with observations in both daily variations and the vertical profile, and a better agreement in the daily amplitude and profile shape of ice temperature could be achieved if field data on physical properties of snow cover and melting ice were available. This study proved the feasibility of both the HIGHTSI model and the MERRA-2 data for modeling the ice cover evolution in Lake Wuliangsuhai, providing a basis for a deep insight into the difference of lake ice evolution between central Asian arid climate zone and polar/sub-polar regions.

For shallow lakes, ice mass balance is largely dominated by thermodynamic processes. The heat flux from lake water plays a critical role for ice growth and melting. In this study, we applied a numerical thermodynamic lake model to investigate the sensitivity of the lake ice mass balance to the lake heat flux during the growth and melting periods. Several groups of modelling experiments forced by simplified climatological weather data have been carried out. Two sites, Lake Wuliangsuhai in Inner Mongolia, China’s arid region and Lake Orajärvi in snowy Finnish Lapland, were investigated. Lake heat flux affects inversely proportional maximum ice thickness followed by ice break-up date. The solar radiation and surface albedo complicate the effect of lake heat flux on lake ice mass balance during melting season. With heavy snowfall, the increase of lake heat flux adds on the formation of granular ice but reduces the formation of columnar ice. Under climatological weather conditions, the ice cover winter seasonal mean lake heat flux were 14 W·m−2 and 4 W·m−2 in Lake Wuliangsuhai and Lake Orajärvi, respectively.

Ecologists involved in long-term research created the metaphors of the “Invisible Present” and the “Invisible Place” to communicate the purposes of Long-Term Ecological Research to the National Science Foundation, other scientists, and the wider public. This chapter discusses using lake ice cover to tackle the joint problems of the Invisible Present and the Invisible Place, by expanding the time and space scales not only at the North Temperate Lakes Long-Term Ecological Research site, but across Wisconsin, North America, and the Northern Hemisphere. LTER formed an international Lake Ice Analysis Group in the mid-1990s, to create and make publicly available a common lake ice phenology database. By 2000, analyses of ice cover provided strong evidence for warming winters in the Northern Hemisphere, and for the impact of the Second Industrial Revolution on climate. Importantly, for ice freeze time series, 20 and 50 years of data were insufficient to detect climate change while longer records did; large-scale climate drivers like El Nino, the North Atlantic Oscillation, as well as local weather influenced inter-year dynamics of lake ice seasonality; inter-year dynamics between lakes were coherent locally and persisted regionally at lower values; extreme ice dates changed in the direction of a warming climate; and changes in lake ice already have affected people negatively. Research on inland water ice and winter limnology continues today and has depended on successes in continuing leadership and participation within and beyond the LTER program.