Modelling on seasonal lake ice evolution in central Asian arid climate zone: a case study

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 andmelting 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.

Thermodynamic processes of lake ice and landfast ice around Zhongshan Station, Antarctica

Thermodynamic processes of ice in three lakes and landfast ice around Zhongshan Station, Antarctica, were observed in 2006. The mass balance of lake ice was compared with that of landfast ice. The responses of lake ice and sea ice temperatures to the local surface air temperature are explored. Vertical conductive heat fluxes at varying depths of lake ice and sea ice were derived from vertical temperature profiles. The freeze up of lake ice and landfast ice occurred from late February to early March. Maximum lake ice thicknesses occurred from late September to early October, with values of 156-177 cm. The maximum sea ice thicknesses of 167-174 cm occurred relatively later, from late October to late November. Temporal variations of lake ice and landfast ice internal temperatures lagged those of air temperatures. High-frequency variations of air temperature were evidently attenuated by ice cover. The temporal lag and the high-frequency attenuation were greater for sea ice than for lake ice, and more distinct for the deeper ice layer than for the upper ice layer. This induced a smaller conductive heat flux through sea ice than lake ice, at the same depth and under the same atmospheric forcing, and a smoother fluctuation in the conductive heat flux for the deeper ice layer than for the upper ice layer. Enhanced desalination during the melt season increased the melting point temperature within sea ice, making it different from fresh lake ice.

Quantifying freeze-melt dynamics of lakes on the Tibetan Plateau using Sentinel-1 synthetic aperture radar imagery

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

MODIS-based Daily Lake Ice Extent and Coverage dataset for Tibetan Plateau

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.

A lake ice phenology dataset for the Northern Hemisphere based on passive microwave remote sensing

Lake ice phenology(LIP)is an essential indicator of climate change and helps with understanding of the regional characteristics of climate change impacts.Ground observation records and remote sensing retrieval products of lake ice phenology are abundant for Europe,North America,and the Tibetan Plateau,but there is a lack of data for inner Eurasia.In this work,enhanced-resolution passive microwave satellite data(PMW)were used to investigate the Northern Hemisphere Lake Ice Phenology(PMW LIP).The Freeze Onset(FO),Complete Ice Cover(CIC),Melt Onset(MO),and Complete Ice Free(CIF)dates were derived for 753 lakes,including 409 lakes for which ice phenology retrievals were available for the period 1978 to 2020 and 344 lakes for which these were available for 2002 to 2020.Verification of the PMW LIP using ground records gave correlation coefficients of 0.93 and 0.84 for CIC and CIF,respectively,and the corresponding values of the RMSE were 11.84 and 10.07 days.The lake ice phenology in this dataset was significantly correlated(P<0.001)with that obtained from Moderate Resolution Imaging Spectroradiometer(MODIS)data-the average correlation coefficient was 0.90 and the average RMSE was 7.87 days.The minimum RMSE was 4.39 days for CIF.The PMW is not affected by the weather or the amount of sunlight and thus provides more reliable data about the freezing and thawing process information than MODIS observations.The PMW LIP dataset pro-vides the basic freeze-thaw data that is required for research into lake ice and the impact of climate change in the cold regions of the Northern Hemisphere.The dataset is available at http://www.doi.org/10.11922/sciencedb.j00076.00081.

The role of lake heat flux in the growth and melting of ice

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 inInner 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,theice cover winter seasonal mean lake heat flux were 14 W·m^(−2) and 4 W·m^(−2) in Lake Wuliangsuhai and Lake Orajärvi,respectively.

Ice bottom evolution derived from thermistor string-based ice mass balance buoy observations

Digital information on sea ice extent,thickness,volume,and distribution is crucial for understanding Earth's climate system.The Snow and Ice Mass Balance Apparatus(SIMBA)is used to determine snow and ice temperatures in Arctic,Antarctic,ice-covered seas,and boreal lakes.Snow depth and ice thickness are derived from SIMBA temperature regimes(SIMBA_ET and SIMBA_HT).In warm conditions,SiMBA_ET temperature-based ice thickness may have errors due to the isothermal vertical profile.SIMBA_HT provides a visible ice-bottom interface for manual quantification.We propose an unmanned approach,combining neural networks,wavelet analysis,and Kalman filtering(NWK),to mathematically establish NwK and retrieve ice bottoms from various SIMBA_HT datasets.In the Arctic,NWK-derived total thickness showed a bias range of-5.64 cm to 4.01 cm and a correlation coefficient of 95%-99%.For Baltic Sea ice,values ranged from 1.31 cm to 2.41 cm(88%-98%correlation),and for boreal lake ice,-0.7 cm to 2.6 cm(75%-83%correlation).During ice growth,thermal equilibrium,and melting,the bias varied from-3.93 cm to 2.37 cm,-1.92 cm to 0.04 cm,and-4.90 cm to 3.96 cm,with correlation coefficients of 76%-99%.These results demonstrate NWK's robustness in retrieving ice bottom evolution in different water environments.

Variation of alpine lakes from 1986 to 2019 in the Headwater Area of the Yellow River,Tibetan Plateau using Google Earth Engine

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

2000-2011年可可西里地区主要湖泊冰情时空变化（英文）

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 pre- sented 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.