Lake Ice and Climate Perturbation: Numerical Experiments on a Small Boreal Lake

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.

Lake ice is a sensitive indicator for the environment and climate change. In the comparative study of climate change from the three poles (Antarctic, Arctic, and the Tibetan Plateau), the lake ice phenology which is mirrored the seasonal changes of lake ice, and it is an important index for assessing the synchronization and difference of climate change. Based on passive microwave, lake ice phenology of 48 lakes from 1978 to 2017 were extracted for northern Europe, Tibetan Plateau and Mongolia Plateau. A comparative analysis of the temporal variation for the lake ice phenology shows that from 1978 to 2017, the average ice cover duration showed a shortening trend of all regions, and the Northern Europe with the most dramatic shortening. The year of 2000 may be a turning of the lake ice cover duration in three regions. Especially in the northern Tibetan Plateau where is a trend of prolonged ice cover duration after 2000, and the delay of the break-up end date plays a more important role than the advance of the freeze-up start date. For the spatial changes, the variation of lake ice cover duration in the Tibetan Plateau shows a spatially aggregate phenomenon, and both the Northern Europe and Mongolian Plateau show changes with latitude. The comparison of lake ice phenology changes of three regions can provide more basis for climate characteristics analysis or climate change research. In the future work, various remote sensing data will be comprehensively used to obtain more information on lake ice phenology in High Mountain and cold regions. Meanwhile, it will combine other reanalysis data to find the reasons that affect the lake ice phenology, and provide support for the comparative study of the three-pole environment.

Abstract. The one-dimensional hydrodynamic ice model, DYRESM-WQ-I, was modified to simulate ice cover and thermal structure of dimictic Lake Mendota, Wisconsin, USA, over a continuous 104-year period (1911–2014). The model results were then used to examine the drivers of changes in ice cover and water temperature, focusing on the responses to shifts in air temperature, wind speed, and water clarity at multiyear timescales. Observations of the drivers include a change in the trend of warming air temperatures from 0.081 °C per decade before 1981 to 0.334 °C per decade thereafter, as well as a shift in mean wind speed from 4.44 m s−1 before 1994 to 3.74 m s−1 thereafter. Observations show that Lake Mendota has experienced significant changes in ice cover: later ice-on date(9.0 days later per century), earlier ice-off date (12.3 days per century), decreasing ice cover duration (21.3 days per century), while model simulations indicate a change in maximum ice thickness (12.7 cm decrease per century). Model simulations also show changes in the lake thermal regime of earlier stratification onset (12.3 days per century), later fall turnover (14.6 days per century), longer stratification duration (26.8 days per century), and decreasing summer hypolimnetic temperatures (−1.4 °C per century). Correlation analysis of lake variables and driving variables revealed ice cover variables, stratification onset, epilimnetic temperature, and hypolimnetic temperature were most closely correlated with air temperature, whereas freeze-over water temperature, hypolimnetic heating, and fall turnover date were more closely correlated with wind speed. Each lake variable (i.e., ice-on and ice-off dates, ice cover duration, maximum ice thickness, freeze-over water temperature, stratification onset, fall turnover date, stratification duration, epilimnion temperature, hypolimnion temperature, and hypolimnetic heating) was averaged for the three periods (1911–1980, 1981–1993, and 1994–2014) delineated by abrupt changes in air temperature and wind speed. Average summer hypolimnetic temperature and fall turnover date exhibit significant differences between the third period and the first two periods. Changes in ice cover (ice-on and ice-off dates, ice cover duration, and maximum ice thickness) exhibit an abrupt change after 1994, which was related in part to the warm El Niño winter of 1997–1998. Under-ice water temperature, freeze-over water temperature, hypolimnetic temperature, fall turnover date, and stratification duration demonstrate a significant difference in the third period (1994–2014), when air temperature was warmest and wind speeds decreased rather abruptly. The trends in ice cover and water temperature demonstrate responses to both long-term and abrupt changes in meteorological conditions that can be complemented with numerical modeling to better understand how these variables will respond in a future climate.

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

Lake ice phenology directly reflects local climate changes, serving as a key indicator of climate change. In today’s rapidly evolving climate, utilizing advanced remote sensing techniques to quickly extract long-term lake ice phenology features and studying their correlation with other climate factors is crucial. This study focuses on lakes in Xinjiang, China, with a mountainous area greater than 100 km2, including Sayram Lake, Ayahkum Lake, Achihkul Lake, Jingyu Lake, and Ahsaykan Lake. The Bayesian ensemble change detection algorithm was employed to extract lake ice phenology information, and the Mann–Kendall (MK) non-parametric test was used to analyze trends. The visual interpretation method was used to interpret the spatial evolution characteristics of lake ice, and the Pearson correlation coefficient was used to explore the driving factors of lake ice phenology. Results indicate the following: (1) Jingyu Lake exhibited the most significant delay in both freezing and complete freezing days, while Ayahkum Lake showed the most stable pattern. Ahsaykan Lake demonstrated the least delay in both starting and complete melting days. (2) Sayram Lake’s ice evolution was unstable, with wind causing variability in the locations where freezing begins and melting spreading from the west shore. Ayahkum Lake, Ahsaykan Lake, and Jingyu Lake exhibited similar seasonal variations, while Achihkul Lake’s ice spatial changes spread from the east to the center during freezing and from the center to the shore during melting. (3) The study found that the freeze–thaw process is influenced by a combination of factors including lake area, precipitation, wind speed, and temperature.

<p>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).</p><p>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.</p>

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.

Lake Ice phenology of small lakes: Impacts of climate variability in the Great Lakes region

Lake ice phenology is an indicator of past and present climate, it is sensitive to regional and global climate change. In the past few decades, the climate of Central Asia has changed significantly due to global warming and anthropogenic activities. However, there are few studies on the lake ice phenology in Central Asia. In this study, the lake ice phenology of 53 lakes in Central Asia were extracted using MODIS daily LST products from 2002 to 2020. The results show that MODIS-extracted lake ice phenology is generally consistent with Landsat-extracted and AVHRR-extracted lake ice phenology. Generally, lakes in Central Asia start to freeze from October to December. The trends in the lake ice phenology show strong regional differences. Lakes distributed along the Kunlun Mountains show overall delayed trends in all lake ice phenology variables, while lakes located in southwestern Central Asia show clear advancing trends in the freeze-up start dates (7.06 days) and breakup end dates (6.81 days). Correlations between the phenology of lake ice and local and climatic factors suggest that the ice breakup process and the duration of its complete coverage depend more on heat, while precipitation mainly affects the freezing time of the ice. Wind speed mainly affects the time of completely frozen of ice. In general, the breakup process is more susceptible to climatic factors, while local factors have strong influences on the freeze-up process.

Lake ice phenology serves as a sensitive indicator of climate change in the lake-rich Northeast China. In this study, the freeze-up date (FUD), break-up date (BUD), and ice cover duration (ICD) of 31 lakes were extracted from a time series of the land water surface temperature (LWST) derived from the combined MOD11A1 and MYD11A1 products for the hydrological years 2001 to 2021. Our analysis showed a high correlation between the ice phenology measures derived by our study and those provided by hydrological records (R2 of 0.89) and public datasets (R2 > 0.7). There was a notable coherence in lake ice phenology in Northeast China, with a trend in later freeze-up (0.21 days/year) and earlier break-up (0.19 days/year) dates, resulting in shorter ice cover duration (0.50 days/year). The lake ice phenology of freshwater lakes exhibited a faster rate of change compared to saltwater lakes during the period from HY2001 to HY2020. We used redundancy analysis and correlation analysis to study the relationships between the LWST and lake ice phenology with various influencing factors, including lake properties, local climate factors, and atmospheric circulation. Solar radiation, latitude, and air temperature were found to be the primary factors. The FUD was more closely related to lake characteristics, while the BUD was linked to local climate factors. The large-scale oscillations were found to influence the changes in lake ice phenology via the coupled influence of air temperature and precipitation. The Antarctic Oscillation and North Atlantic Oscillation correlate more with LWST in winter, and the Arctic Oscillation correlates more with the ICD.

Ice phenology interactions with water and air temperatures in high mountain lakes

Climatic sensitivity of seasonal ice-cover, water temperature and biogeochemical cycling in Lake 239 of the Experimental Lakes Area (ELA), Ontario, Canada

Lake ice phenology of Nam Co, Central Tibetan Plateau, China, derived from multiple MODIS data products

Abstract. A new automated method enabling consistent satellite assessment of seasonal lake ice phenology at 5 km resolution was developed for all lake pixels (water coverage ≥ 90 %) in the Northern Hemisphere using 36.5 GHz H-polarized brightness temperature (Tb) observations from the Advanced Microwave Scanning Radiometer for EOS and Advanced Microwave Scanning Radiometer 2 (AMSR-E/2) sensors. The lake phenology metrics include seasonal timing and duration of annual ice cover. A moving t test (MTT) algorithm allows for automated lake ice retrievals with daily temporal fidelity and 5 km resolution gridding. The resulting ice phenology record shows strong agreement with available ground-based observations from the Global Lake and River Ice Phenology Database (95.4 % temporal agreement) and favorable correlations (R) with alternative ice phenology records from the Interactive Multisensor Snow and Ice Mapping System (R = 0.84 for water clear of ice (WCI) dates; R = 0.41 for complete freeze over (CFO) dates) and Canadian Ice Service (R = 0.86 for WCI dates; R = 0.69 for CFO dates). Analysis of the resulting 12-year (2002–2015) AMSR-E/2 ice record indicates increasingly shorter ice cover duration for 43 out of 71 (60.6 %) Northern Hemisphere lakes examined, with significant (p < 0.05) regional trends toward earlier ice melting for only five lakes. Higher-latitude lakes reveal more widespread and larger trends toward shorter ice cover duration than lower-latitude lakes, consistent with enhanced polar warming. This study documents a new satellite-based approach for rapid assessment and regional monitoring of seasonal ice cover changes over large lakes, with resulting accuracy suitable for global change studies.

Assessment of wind resources in two parts of Northeast Brazil with the use of numerical models