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Changing Arctic climate may alter freshwater ecosystems as a result of warmer surface waters, longer open-water periods, reduced wintertime lake ice growth, and altered hydrologic connectivity. This study aims to characterize zooplankton community composition and size structure in the context of hydrologic connectivity and ice regimes in Arctic lakes. Between 2011 and 2016, we sampled the phytoplankton, zooplankton, and fish communities from a set of representative lakes on the Arctic Coastal Plain (ACP) of northern Alaska to determine potential food web responses to changing Arctic ecosystems. Multivariate analyses showed that time from ice-out had a strong influence on zooplankton community structure and that seasonal succession of zooplankton differed between lakes with varying hydrologic connectivity. Trends were observed suggesting that large-bodied zooplankton (Daphnia, calanoid copepods) may be more prevalent in poorly connected lakes with low fish diversity. Large-bodied zooplankton displayed higher biomass in lakes with high occurrences of bedfast ice, while small-bodied zooplankton (Bosmina, rotifers) displayed highest biomass in deeper lakes with low occurrences of bedfast ice. Our results contribute to limited knowledge of zooplankton in remote lakes of the ACP and suggest that the anticipated changes to aquatic ecosystems in the Arctic may include energetically less efficient plankton food webs.

New renewable electricity is nowadays often generated by photovoltaics and wind. Yet, their intermittent nature calls for energy storage, which is today still provided to ~95% by pumped-storage (PS) hydropower plants. However, PS is known to affect abiotic and biotic characteristics of the two connected water bodies. Thus, a two-dimensional laterally-averaged hydrodynamic and water quality model was set up to assess the impacts on water quality and temperature in a first step. Then, this analysis was extended to evaluate the additional effect of climate change, which also modifies abiotic and biotic characteristics. For this purpose, 150-years long synthetic time series of meteorological conditions for current (1998-2012) and future climate (2078-2092) were generated with a weather generator. To assess the robustness of projected impacts on the ice cover of the upper reservoir (Sihlsee) three one-dimensional, vertical hydrodynamic models were additionally set up. To attribute effects to either the PS flows or to water withdrawal from the hypolimnion, two reference scenarios were defined: one with deep-water withdrawal (NoPS) and another one with surface outflow (QNat). While the hypolimnetic temperature differs by

The timing of lake ice breakup and freezeup are important indicators of climate change in Arctic and boreal regions because they respond rapidly and directly to variations in climate conditions. Despite its importance, lake ice phenology remains poorly documented in most lakes of Alaska. To fill this data gap, we constructed a remote sensing-derived lake ice phenology database covering all lakes in Alaska larger than 1 km2 (n = 4241) over the period 2000–2019. This dataset, which includes lake ice on/off dates and lake ice duration, was based on an automatic method using daily moderate resolution imaging spectroradiomenter (MODIS) imagery to measure lake ice fraction. This method extracts lake ice pixels from MODIS images using a dynamic threshold that was calibrated against Landsat Fmask. Different filters that account for clouds, polar night, and other sources of error were applied to increase the accuracy of lake ice phenology estimation. Trend analysis shows earlier breakup (−5.5 d decade−1) for 440 lakes and later breakup (7.5 d decade−1) for four lakes (p < 0.05). A total of 289 lakes had significant trends toward later freezeup (2.9 d decade−1) and 11 lakes towards earlier freezeup (−3.3 d decade−1). Most lakes with significant trends are north of the Brooks Range. This dataset can contribute to increased understanding of interactions between lake processes and climate change, and it supports the study of biogeochemical, limnological and ecological regimes in Alaska and pan-Arctic regions.

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

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

A tessellation-based methodology for interactively analyzing the spatio-temporal evolution of a dynamic phenomenon – ice coverage and its characteristics – using a spatial online analytical processing (OLAP) approach is proposed. The feasibility of the method was tested through a prototype developed in the context of the CanICE project using Canadian Ice Service data and the Egg Code, an international standard for characterizing sea and lake ice. By transforming the standard spatial OLAP vector-based point of view – aggregating data from instances of evolving features – into a tessellation-based point of view – aggregating data from constant spaces with evolving properties – the proposed solution makes it possible to meet the criteria of interactive multidimensional analysis for dynamic phenomena. The second innovative aspect of the methodology relates to the management of data quality with a spatial OLAP approach. Resume: Cet article propose une methodologie basee sur la reduction en mosaique (ou tessellation) pour effectuer une analyse spatiotemporelle d’un phenomene dynamique – la couverture de glace et ses caracteristiques – incorporee a une approche SOLAP (spatial online analytical processing). Nous avons teste cette methode dans le cadre du projet CanICE a l’aide d’un prototype qui s’appuie sur des donnees du Service canadien des glaces et sur le code de l’œuf, une norme internationale de description des glaces. Ainsi, la transformation de l’approche SOLAP standard – basee sur les vecteurs – en une approche basee sur la reduction en mosaique permet l’analyse multidimensionnelle d’un phenomene dynamique. Un autre aspect innovant de notre methodologie repose sur la gestion de la qualite des donnees avec une approche SOLAP.

The primary drivers of the recent accelerated warming of the Laurentian Great Lakes from 1982 to 2012 are explored through observations, remote sensing, and regional climate model experiments. The study focuses on the abrupt warming from 1997 to 1998 as a proxy for the long-term warming trend. The lake surface warming has been heterogeneous in both space and time, ranging from moderate warming in late spring over the southern lakes and shallow areas of the northern lakes to strong warming in mid-summer over the northern, deep lake areas. The greatest lake warming between 1997 and 1998 occurs over the deepest areas of Lake Superior during mid-summer, primarily arising from enhanced heat accumulation during the mild winter of 1997/1998 and amplified by greater incoming surface solar radiation and air temperature during the spring of 1998, according to model experiments. The mild winter condition, together with the increased solar radiation and air temperature during spring, causes an earlier onset of springtime stratification, resulting in enhanced heat absorption by surface water and thereby contributing to lake surface warming during the subsequent summer in 1998 compared with 1997. In contrast, the modest peak warming over southern lakes and shallow areas of northern lakes from 1997 to 1998 is a rapid response to synchronous increases in solar radiation and air temperature during May between the 2 yr. Changes in antecedent wintertime lake ice cover are found to have played only a minor role in the accelerated warming trend of the Laurentian Great Lakes.

Lake-ice properties at Lake Abashiri, Hokkaido, Japan, were examined using field observations and a 1-D thermodynamic model to clarify formation processes at mid-latitudes subject to significant snowfall as well as moderate air temperature. At all lake sites examined, the ice comprised two distinct layers: a snow ice (SI) layer on top and a congelation ice (CI) layer below. The SI layer occupied as much as 29–73% of the total ice thickness, a much greater fraction than that reported for lakes at Arctic high latitudes. In the model, the CI growth rate was estimated using the traditional heat budget method, while the SI growth rate was calculated assuming the excessive snowfall from the isostatic balance is converted to SI by a snow compression rate (β) with the surface melting rate added when the surface heat budget becomes positive. By tuning the value of β to the observational results of SI thickness, the model outcome successfully reproduced the observational thicknesses of CI and SI, and the break-up date of the lake. Essentially, the model findings show how snow and its formation into SI reduce, by about half, the seasonal variability of total ice thickness.

Several lake ice phenology studies from satellite data have been undertaken. However, the availability of long-term lake freeze-thaw-cycles, required to understand this proxy for climate variability and change, is scarce for European lakes. Long time series from space observations are limited to few satellite sensors. Data of the Advanced Very High Resolution Radiometer (AVHRR) are used in account of their unique potential as they offer each day global coverage from the early 1980s expectedly until 2022. An automatic two-step extraction was developed, which makes use of near-infrared reflectance values and thermal infrared derived lake surface water temperatures to extract lake ice phenology dates. In contrast to other studies utilizing thermal infrared, the thresholds are derived from the data itself, making it unnecessary to define arbitrary or lake specific thresholds. Two lakes in the Baltic region and a steppe lake on the Austrian–Hungarian border were selected. The later one was used to test the applicability of the approach to another climatic region for the time period 1990 to 2012. A comparison of the extracted event dates with in situ data provided good agreements of about 10 d mean absolute error. The two-step extraction was found to be applicable for European lakes in different climate regions and could fill existing data gaps in future applications. The extension of the time series to the full AVHRR record length (early 1980 until today) with adequate length for trend estimations would be of interest to assess climate variability and change. Furthermore, the two-step extraction itself is not sensor-specific and could be applied to other sensors with equivalent near- and thermal infrared spectral bands.

Lake ice phenology, i.e. the timing of freeze-up and break-up and the duration of the ice cover, is regarded as an important indicator of changes in regional climate. Based on the boundary data of lakes, some moderate-high resolution remote sensing datasets including MODIS and Landsat TM/ETM+ images and the meteorological data, the spatial-temporal variations of lake ice phenology in the Hoh Xil region during the period 2000–2011 were analyzed by using RS and GIS technology. And the factors affecting the lake ice phenology were also identified. Some conclusions can be drawn as follows. (1) The time of freeze-up start (FUS) and freeze-up end (FUE) of lake ice appeared in the late October–early November, mid-November–early December, respectively. The duration of lake ice freeze-up was about half a month. The time of break-up start (BUS) and break-up end (BUE) of lake ice were relatively dispersed, and appeared in the early February–early June, early May–early June, respectively. The average ice duration (ID) and the complete ice duration (CID) of lakes were 196 days and 181 days, respectively. (2) The phenology of lake ice in the Hoh Xil region changed dramatically in the last 10 years. Specifically, the FUS and FUE time of lake ice showed an increasingly delaying trend. In contrast, the BUS and BUE time of lake ice presented an advance. This led to the reduction of the ID and CID of lake. The average rates of ID and CID were–2.21 d/a and–1.91 d/a, respectively. (3) The variations of phenology and evolution of lake ice were a result of local and climatic factors. The temperature, lake area, salinity and shape of the shoreline were the main factors affecting the phenology of lake ice. However, the other factors such as the thermal capacity and the geological structure of lake should not be ignored as well. (4) The spatial process of lake ice freeze-up was contrary to its break-up process. The type of lake ice extending from one side of lakeshore to the opposite side was the most in the Hoh Xil region.

Ground-penetrating radar (GPR) is not commonly used to study lake ice, and in general, the ground-based use of radar frequencies greater than 500 MHz in cryosphere geophysics is rare, due to a general interest in deeper stratigraphy and the difficulty of extensive profiling over rough snow surfaces. Our goal was to find further information on the origin of the deposition and formation of intra-ice layers, bottom topography, and subbottom deposits using GPR with pulses centered near 850 MHz on two permanently ice-covered lakes in the McMurdo Dry Valleys, Antarctica. The profiles were obtained using a one-person sled operation over Lake Bonney, which is typical of lakes in the region, having an ice thickness that ranges between 3 and 5 m, and Lake Vida, where the maximum ice depth is at least 27 m. Lake Bonney exhibits a semicontinuous sediment horizon at approximately a 2-m depth and several minor horizons. In contrast, Lake Vida contains unconformably eroded and folded continuous reflection horizons, packages of minor horizons between major horizons, evidence of incised fluvial deposition along the bottom, and subbottom penetration of at least 4.5 m in some areas. Where the ice thickness is less than 20 m, the lake is frozen to the bottom. Most horizon waveform phase attributes indicate relatively lower permittivity than in the surrounding matrix. Consequently, we interpreted these strata to be caused by layers of pure ice embedded within a salty and dirty ice matrix, which were formed during minor flooding. These findings supported previous conclusions that Lake Vida ice formed from surface runoff in combination with periods of ablation.

Ice phenomena are construed as the occurrence of ice in water irrespective of its structure, form, and duration. One of the most frequently discussed research problems is the possibility of using long-term ice phenology as an indicator of changes of the thermal conditions of ambient air. The study used correlation analysis and regression models in order to determine changes in the parameters studied over time. In order to compare the ice regime of the study reservoir and other lakes in the region, discriminant function analysis, principal components analysis (PCA), and canonical redundancy analysis (RDA) were applied. During the 52 winter seasons studied (1964&ndash, 2015), there were weak but still statistically significant trends concerning the increase in air temperature in the region (by 0.3 &deg, C per decade), the reduction in the number of days with ice cover (by 8.6 days per decade) and the decline in the maximum and average thicknesses of lake ice (by 2.0 cm and 1.2 cm per decade). The low average depth and volume capacity are reflected in the rapid freezing rate of the reservoir, and its location results in a longer duration of ice cover, greater ice thickness, and later dates of its melting.

Nearly half of the world’s lakes freeze periodically. In the past few decades, lakes in the northern hemisphere are increasingly recording unusually short or no annual ice season due to climate variability and change. This is raising concerns about the potential impact of short annual ice cover season on lake ecosystem structure, stability, and function. Here we develop a tentative framework that delineates the connection between winter climate variability, shorter lake ice season, and related environmental and social impacts with focus on winter thermal thresholds in lake ice. This framework organizes existing knowledge on this topic and presents a systems-scale view. The integrative system’s scale view presented in this study seeks to inform: (a) usability of seasonal climatic information to understand timing of ice out and thresholds therein, and (b) efforts seeking to develop adaptive lake related management and planning policies in a changing climate.

Lake-ice phenology is one of the key cryosphere indicators. Based on changes in time series of daily lake ice coverage and the microwave brightness temperature, two machine-learning methods were selected for estimating the phenology of lake ice. Using MODIS lake ice coverage time series, a convolutional neural network (CNN) was used to automatically classify lakes as either having or not having regular freezing signatures. The classification results were compared to the test samples and classification accuracies of 91% and 100% were found for lakes that do and do not freeze annually, respectively. In order to extract the lake ice phenology from passive microwave brightness temperature data, support vector regression (SVR) was used: the freeze-up start (FUS) and break-up end (BUE) were extracted using time series of estimated emissivity. The lake ice phenology results obtained using SVR were compared with the reference results. The values of R2 for FUS and BUE were 0.8928 and 0.8899, respectively. These results show that it is possible to use AI methods for the fast extraction of the phenology of lake ice and that these methods can be applied to lakes globally.

Lake ice is a sensitive factor for the Earth’s environment and climate change research. In the comparative study on climate change to the Earth three-pole (Antarctic, Arctic, and Tibetan Plateau), the lake ice phenology can be used to represent seasonal climate changes. In this paper, the lake ice phenology and the corresponding daily temperature for 48 lakes in Northern Europe, Tibetan Plateau and Mongolia Plateau were used as the typical case for comparative research. Based on passive microwave remote sensing data. The results showed that the average lake ice cover duration experienced a consistent decreasing for the three regions from 1978-2018. However, in the northern Tibetan Plateau, though the lake ice cover duration showed a shortening trend from 1978 to 2000, it displayed a prolonged trend from 2000 to 2018. Moreover, the air temperature changes of the lake area had a significant correlation with the changes of ice cover duration in each region, and the change of 0 °C isotherm in the Northern Europe lakes are more sensitive than the Mongolian Plateau and the Tibetan Plateau. The air temperature played a major role in the change of lake ice phenology, but there were still other factors that affected the lake ice phenology changes, especially in northern Tibetan Plateau. By comparing the analysis of the ice cover duration in the three regions and the effect of air temperature on the lake ice cover duration change, it provides more evidences for the study on climate change research in different regions.

Changes to ice cover on lakes throughout the northern landscape has been established as an indicator of climate change and variability, expected to have implications for both human and environmental systems. Monitoring lake ice cover is also required to enable more reliable weather forecasting across lake-rich northern latitudes. Currently, the Canadian Ice Service (CIS) monitors lakes using synthetic aperture radar (SAR) and optical imagery through visual interpretation, with total lake ice cover reported weekly as a fraction out of ten. An automated method of classification would allow for more detailed records to be delivered operationally. In this research, we present an automatic ice-mapping approach which integrates unsupervised segmentation from the Iterative Region Growing using Semantics (IRGS) algorithm with supervised random forest (RF) labeling. IRGS first locally segments homogeneous regions in an image, then merges similar regions into classes across the entire scene. Recently, these output regions were manually labeled by the user to generate ice maps, or were labeled using a Support Vector Machine (SVM) classifier. Here, three labeling methods (Manual, SVM, and RF) are applied after IRGS segmentation to perform ice-water classification on 36 RADARSAT-2 scenes of Great Bear Lake (Canada). SVM and RF classifiers are also tested without integration with IRGS. An accuracy assessment has been performed on the results, comparing outcomes with author-generated reference data, as well as the reported ice fraction from CIS. The IRGS-RF average classification accuracy for this dataset is 95.8%, demonstrating the potential of this automated method to provide detailed and reliable lake ice cover information operationally.

High Resolution Limited Area Model (HIRLAM), used for operational numerical weather prediction in the Finnish Meteorological Institute (FMI), includes prognostic treatment of lake surface state since 2012. Forecast is based on the Freshwater Lake (FLake) model integrated to HIRLAM. Additionally, an independent objective analysis of lake surface water temperature (LSWT) combines the short forecast of FLake to observations from the Finnish Environment Institute (SYKE). The resulting description of lake surface state – forecast FLake variables and analysed LSWT – was compared to SYKE observations of lake water temperature, freezing and melting dates as well as the ice and snow thickness for 2012–2018 over 45 lakes in Finland. During the ice-free period, the predicted LSWT corresponded to the observations with a slight overestimation, with a systematic error of +0.91 K. The colder temperatures were underrepresented and the maximum temperatures were too high. The objective analysis of LSWT was able to reduce the bias to +0.35 K. The predicted freezing dates corresponded well the observed dates, mostly within the accuracy of a week. The forecast melting dates were far too early, typically several weeks ahead of the observed dates. The growth of ice thickness after freezing was generally overestimated. However, practically no predicted snow appeared on lake ice. The absence of snow, found to be due to a technical error in HIRLAM, is suggested to be also the reason of the inaccurate simulation of the ice melt in spring.

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

Thermokarst lakes are important emitters of methane, a potent greenhouse gas. However, accurate estimation of methane flux from thermokarst lakes is difficult due to their remoteness and observational challenges associated with the heterogeneous nature of ebullition. We used high-resolution (9–11 cm) snow-free aerial images of an interior Alaskan thermokarst lake acquired 2 and 4 days following freeze-up in 2011 and 2012, respectively, to detect and characterize methane ebullition seeps and to estimate whole-lake ebullition. Bubbles impeded by the lake ice sheet form distinct white patches as a function of bubbling when lake ice grows downward and around them, trapping the gas in the ice. Our aerial imagery thus captured a snapshot of bubbles trapped in lake ice during the ebullition events that occurred before the image acquisition. Image analysis showed that low-flux A- and B-type seeps are associated with low brightness patches and are statistically distinct from high-flux C-type and hotspot seeps associated with high brightness patches. Mean whole-lake ebullition based on optical image analysis in combination with bubble-trap flux measurements was estimated to be 174 ± 28 and 216 ± 33 mL gas m−2 d−1 for the years 2011 and 2012, respectively. A large number of seeps demonstrated spatiotemporal stability over our 2-year study period. A strong inverse exponential relationship (R2 > = 0.79) was found between the percent of the surface area of lake ice covered with bubble patches and distance from the active thermokarst lake margin. Even though the narrow timing of optical image acquisition is a critical factor, with respect to both atmospheric pressure changes and snow/no-snow conditions during early lake freeze-up, our study shows that optical remote sensing is a powerful tool to map ebullition seeps on lake ice, to identify their relative strength of ebullition, and to assess their spatiotemporal variability.

The goal of this research was to evaluate the effect of Arctic climate change on the surrounding land area. In this research, we developed a method to monitor the freezing and thawing of shallow lakes in the Arctic region using C-band synthetic aperture radar (SAR) data and provide a strategy to evaluate the effect of climate change on the Arctic land area. A method to monitor the ice condition of these lakes was investigated using the SAR data acquired by Sentinel-1 from 2014 to 2017. We confirmed that the C-band SAR data from Sentinel-1 could monitor the freezing and thawing ice condition of shallow lakes in northern Alaska. The backscattering threshold between floating and grounded ice was −14 dB, which was approximately 2 dB less than that of ers-1/2. We envision continuing to monitor lake ice over a long period of time using future available Sentinel-1 data.

We have conducted a multiyear (2011–2014) airborne microwave radiometer measurement program of snow on lake ice, regularly using our HUTRAD instrument (6.9 to 36.5 GHz, vertical and horizontal polarization). Occasionally, we have also used our interferometric 1.4 GHz HUT-2D radiometer. Our data consist of observations along a 4-km test line over two lakes in southern Finland, and include data also for adjacent land areas, whose land-cover types range from forest to short vegetation. A wide variety of snow and ice conditions were encountered, covering early winter, mid-winter and late winter conditions, and the melting season. In this paper we focus on the comparison of brightness temperatures observed for snow on lake ice and snow on terrain.

The thawing time and lake ice completely covered time can directly reflect the climate change in the region, and the duration of the lake ice can also reflect the local climate change. The traditional field monitoring of lake ice requires a lot of manpower and material resources, and the timeliness is poor, so it is not suitable for long-term ice condition monitoring. Since 1960s, remote sensing image has been used because of its wide range, fast speed, low cost and so on. More and more widely used in all kinds of research, the long-term monitoring of lake ice can also use remote sensing monitoring. Based on the Landsat series of remote sensing data, the Neural Network Algorithm was used to study the remote sensing image of Namco lake in the lake ice segmentation. The lake ice condition of Namco lake was monitored from 1988 to 2016.

Participatory sensing (PS) and citizen science hold promises for a genuinely interactive and inclusive citizen engagement in meaningful and sustained collection of data about social and environmental phenomena. Yet the underlying motivations for public engagement in PS remain still unclear particularly regarding the role of gamification, for which HCI research findings are often inconclusive. This paper reports the findings of an experimental study specifically designed to further understand the effects of gamification on citizen engagement. Our study involved the development and implementation of two versions (gamified and non-gamified) of a mobile application designed to capture lake ice coverage data in the sub-arctic region. Emerging findings indicate a statistically significant effect of gamification on participants' engagement levels in PS. The motivation, approach and results of our study are outlined and implications of the findings for future PS design are reflected. Post-print / Final draft

To address the contribution of long-term wind wave changes on diminishing ice period in Northern European lakes, an in situ observation of wind waves was conducted to calibrate a wind-wave numerical model for Lake Pyhajarvi, which is the largest lake in southwest Finland. Using station-measured hydrometeorological data from 1963 to 2013 and model-simulated wind waves, correlation and regression analyses were conducted to assess the changing trend and main influences on ice period. Ice period in Lake Pyhajarvi decreased significantly over 51 years (r = 0.47, P

Most high-altitude lakes are more sensitive to global warming than the regional atmosphere. However, most existing climate models produce unrealistic surface temperatures on the Tibetan Plateau (TP) lakes, and few studies have focused on the influence of ice surface albedo on high-altitude lakes. Based on field albedo measurements, moderate resolution imaging spectrometer (MODIS) albedo products and numerical simulation, this study evaluates the ice albedo parameterization schemes in existing lake models and investigates the characteristics of the ice surface albedo in six typical TP lakes, as well as the influence of ice albedo error in the FLake model. Compared with observations, several ice albedo schemes all clearly overestimate the lake ice albedo by 0.26 to 0.66, while the average bias of MODIS albedo products is only 0.07. The MODIS-observed albedo of a snow-covered lake varies with the snow proportion, and the lake surface albedo in a snow-free state is approximately 0.15 during the frozen period. The MODIS-observed ice surface (snow-free) albedos are concentrated within the ranges of 0.14–0.16, 0.08–0.10 and 0.10–0.12 in Aksai Chin Lake, Nam Co Lake and Ngoring Lake, respectively. The simulated lake surface temperature is sensitive to variations in lake ice albedo especially in the spring and winter.

As the largest landmass on Earth, Asia’s climatic history is of paramount importance. However, with the exception of China, research on the historical climatology of the continent remains in its infancy. Climate reconstructions using Islamic sources have been undertaken for Arabia and West Asia, particularly for the first millennium ce. For the Indian subcontinent, reconstruction has primarily used colonial sources, so information about past climatic variability exists mainly for the last three centuries. For Indonesia, colonial records have substantial potential, having been used previously only to compile disaster chronologies. Documentary reconstruction in Russia is minimal, with the exception of a review produced by Borisenkov in 1992. Climate reconstruction is far more advanced in Japan, including highly robust long-term temperature reconstructions from the dates of spring flowering and lake ice records.

This bibliography includes 294 books and articles published mostly in 2010. Annotated books and articles relate to ten thematic sections of glaciology: 1. General problems of glaciology 2. Physics and chemistry of ice 3. Ice in atmosphere 4. Snow cover 5. Snow avalanches and glacial mudflows 6. Sea ice 7. River and lake ice 8. Icings and ground ice 9. Glaciers and ice sheets 10. Paleoglaciology

Canada's RADARSAT Constellation Mission (RCM) will have the capacity to acquire C-band compact polarimetry (CP) data in all imaging modes over swaths up to 500 km wide. Our study aimed to assess and develop the utility of RCM CP data for the purpose of lake ice breakup monitoring. The breaking ice and open water information content of RADARSAT-2 (R2) polarimetric data and simulated RCM CP data was compared. Despite relative losses in terms of polarization diversity and radiometric sensitivity, RCM-type CP data were concluded to make a good source of information in support lake ice breakup monitoring. For that reason, a CP-based approach, called CP_LakeIceBC, to classify breaking ice and open water for the purpose of lake ice breakup monitoring was developed. CP_LakeIceBC is driven by incidence angle information, uses five CP backscatter variables (RH, RR, RV/RH, RR/RL, and conformity), and is compatible with high- and medium-resolution RCM-type CP products. Application of CP_LakeIceBC to represe...

This paper presents a series of uniaxial compressive experiments on natural lake ice under moderate strain-rate in the range of 10−1 to 102 s−1 at −0.1 °C. Natural lake ice samples of 8 cm by 8 cm in cross section and 20 cm high were used to investigate strain-rate dependence of uniaxial compressive strength and flaw effects on ice strength under moderate strain rates. The fracture modes of ice at moderate strain rates were also systematically investigated by using high-speed camera. It is found uniaxial compressive strength of natural lake ice increases with increasing strain-rate in the employed moderate strain-rate range. And natural flaws such as air bubble have a significant effect on uniaxial compressive strength of ice under moderate strain-rate, higher air content ice possesses lower compressive strength. Ice fracture mode depends on strain-rate (or compressive velocity) of ice specimen, varying from splitting at strain rates lower than 10 s−1 to crushing at strain rates higher than 10 s−1. Ice specimen crushes into fine fragments may due to insufficient time for micro cracks to propagate, thus results in higher strength. In addition, dependence of compressive strength on strain-rate in a wide strain-rate range is also discussed.

Experiments on waves at the surface of a floating elastic sheet are presented, with implications for ocean and lake ice sheets. The growth of a daughter wave from the interaction between two mother waves at different scales is observed and is well described by weakly nonlinear resonant interaction.

On the basis of data from the period 1971–2007, and by applying trend analysis, a study on formation, disappearance and duration of lake ice cover on the Morskie Oko Lake in the Tatra Mountains in southern Poland was carried out. The results show decreasing trends in the maximum thickness of winter lake ice cover and in duration of lake ice phenomena, while air temperature recorded at the same period at the foot of the Tatra Mountains shows increasing trend. There are strong relationships between the course of lake ice phenomena and air temperature. Citation Choinski, A., L. Kolendowicz, J. Pociask-Karteczka, et al., 2010: Changes in lake ice cover on the Morskie Oko Lake in Poland (1971–2007). Adv. Clim. Change Res., 1 , doi: 10.3724/SP.J.1248.2010.00071.

Two experimental brightness temperature data sets are revisited: A ground-based campaign of terrestrial snow in 1985 and an airborne research program of snow on lake ice in 2007–2014. Both data sets were obtained in southern Finland using multi-frequency microwave radiometers. In this paper both the overall behavior of the brightness temperature during the ground-based campaign and results from the intensive data collection period on April 12–13 (melt/freeze cycle) are discussed. Additionally, selected results from the airborne snow/lake ice program are compared with theoretical values. Two theoretical models are used for simulation.

International audience; The radar backscatter response of snow covered lake and fjord ice is investigated using a ground based multifrequency synthetic aperture radar system operated in a tomographic configuration. Direct imaging of the snow and ice layering is achieved by focusing the signal from a two-dimensional (2-D) synthetic array in the 3-D space. A mathematical derivation describing the propagation of electromagnetic waves across a dense and multilayered complex medium with arbitrary but finite number of layers is presented. It is used to estimate the depth and refractive indices of the snow and ice layers from the tomograms employing a simple least-square optimization scheme. The lake and fjord ice datasets are compared with respect to their vertical stratification and estimated refractive indices. The vertical structure of the reflectivity of the snow-covered lake ice is investigated and compared at two different frequencies, X-, and C-band. It is found that snow and ice volume responses at C-band are very low compared to the corresponding responses at X-band. At both frequencies, backscattering from surface and interface structures dominate volume contributions.

In December 1913 Sir Ernest Shackleton released a prospectus and announced The Imperial Trans-Antarctic Expedition. His goal was to undertake the first crossing of Antarctica from the Weddell Sea via the polar plateau to McMurdo Sound on the Ross Sea. The journey had already been attempted by Wilhelm Filchner whose shipDeutschland, had become beset in the Weddell Sea ice for nine months in 1912. Shackleton aimed ‘to make all possible scientific observations on [the Trans-Antarctic] journey; to carry on similar work by parties operating from the two bases on the Weddell and Ross Seas [and] to carry on scientific work, and travel unknown portions of the coastline, by the two ships of the expedition’(Shackleton 1913: 3). WithEndurancea continental crossing party of six led by Shackleton would begin from the Weddell Sea and a supporting depot laying party led byNimrodveteran Lieutenant Aeneas L.A. Mackintosh RNR, with the auxiliary barquentineAurorabased in McMurdo Sound. Unbeknown to each party, both experienced problems beyond their control.Endurancewas holed and sank in the Weddell Sea andAuroralocked in ice, although damaged, reached New Zealand. Here the ship was repaired and then undertook a relief expedition with Shackleton as a passenger, to McMurdo Sound. In spite of these major setbacks each party conducted valuable scientific observations.When Shackleton published his bookSouth(Shackleton 1919) on the expedition, compiled with New Zealand journalist and friend Edward Saunders, with exception of accounts on the Ross Sea party sledging and drift of the shipAurora, no recognition was given to work undertaken by the four Ross Sea party scientists and an assistant. Later publications have focused on the depot-laying, while books on Antarctic science have largely overlooked the science undertaken.The purpose of this paper is to make this better known, and to give credit to the four scientists involved. The science conducted although primarily concerned with meteorological observations, also covers limited glaciological observations including the ablation of lake ice, solution of glacier ice in salt water, tidal recordings, collection of zoological and other specimens, along with the use of improvised equipment to undertake observations. The science achieved was secondary to the field work. The Ross Sea party science was done however, under conditions not normally conducive for such field work with health issues a major contributing factor. A lack of funding, equipment, personality problems, concern forAuroraand crew, uncertainty of Shackleton's Antarctic crossing and their own relief, led to depression, sleeplessness and insomnia.