Spring Meltwater Mixing in Small Arctic Lakes

1985 ◽  
Vol 42 (11) ◽  
pp. 1789-1798 ◽  
Author(s):  
Martin A. Bergmann ◽  
Harold E. Welch
Keyword(s):  
Tritiated Water ◽  
Temporal Distribution ◽  
Early Spring ◽  
Arctic Lakes ◽  
Ice Thickness ◽  
Unfrozen Water ◽  
Temperature Profiles ◽  
Lake Ice ◽  
Flushing Rate ◽  
Meltwater Chemistry

Meltwater mixing in small arctic lakes at Saqvaqjuac (63°68′N, 90°40′W) was studied in 1980 and 1981 to evaluate the applicability of theoretical lake water renewal times to the modeling of ice-covered lakes. Two 370-GBq tritium additions were made to 7.09-ha P&N Lake. One was mixed with the unfrozen water at the time of maximum lake-ice thickness (May 1980) and the other was mixed with the lake immediately after freezing (October 1980). Dye experiments were also performed at four lakes to define the spatial and temporal distribution of the inflow and icemelt layers. Results from the tritiated water and dye addition experiments, as well as conductance and temperature profiles, showed that during ice-on, the cold low-density meltwater floated in a thin layer 0–100 cm beneath the ice, extended over the entire subice-surface area, and left the lake without mixing with the heavier subice water. These results imply that (1) lake models incorporating a lake flushing rate term need to be reevaluated to accommodate the lack of meltwater mixing beneath spring ice and (2) more attention should be given to the early spring meltwater chemistry and its distribution within the upper lake strata.

scholarly journals The influence of albedo parameterization for improved lake ice simulation

2020 ◽  
Author(s):  
Alexis L. Robinson ◽  
Sarah S. Ariano ◽  
Laura C. Brown
Keyword(s):  
Field Measurements ◽  
Time Lapse ◽  
Ice Cover ◽  
High Arctic ◽  
Arctic Lakes ◽  
Ice Thickness ◽  
Lake Ice ◽  
Temperate Region ◽  
Climate Conditions ◽  
Arctic Lake

Abstract. Lake ice models can be used to study the latitudinal differences of current and projected changes in ice covered lakes under a changing climate. 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 composition between northern and temperate 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 the High Arctic 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 both an underestimation in ice thickness (~ 4 to 18 cm) and ice-off timing (~ 25 to 30 days). Field measurements were used to adjust the albedo parameterization used in CLIMo, which resulted in improvements to both simulated ice thickness, within 0.1 cm to 10 cm of manual measurements, and ice-off timing, within 1 to 7 days of observations. These findings suggest regionally specific measurements of albedo can improve the accuracy of lake ice simulations. These results further our knowledge regarding of the response of temperate and High Arctic lake ice regimes to climate conditions.

scholarly journals The Influence of Snow and Ice Albedo towards Improved Lake Ice Simulations

Hydrology ◽  
2021 ◽  
Vol 8 (1) ◽  
pp. 11
Author(s):  
Alexis L. Robinson ◽  
Sarah S. Ariano ◽  
Laura C. Brown
Keyword(s):  
Field Measurements ◽  
Ice Cover ◽  
High Arctic ◽  
Arctic Lakes ◽  
Ice Thickness ◽  
Lake Ice ◽  
Temperate Region ◽  
Climate Conditions ◽  
Arctic Lake ◽  
Lake Ice Cover

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.

scholarly journals Ice processes and growth history on Arctic and sub-Arctic lakes using ERS-1 SAR data

Polar Record ◽  
1995 ◽  
Vol 31 (177) ◽  
pp. 115-128 ◽  
Author(s):  
K. Morris ◽  
M. O. Jeffries ◽  
W. F. Weeks
Keyword(s):  
Arctic Lakes ◽  
Polar Regions ◽  
Lake Ice ◽  
Sar Images ◽  
The North ◽  
Growth History ◽  
North Slope Of Alaska ◽  
Term Monitoring ◽  
Selection Of

AbstractA survey of ice growth and decay processes on a selection of shallow and deep sub-Arctic and Arctic lakes was conducted using radiometrically calibrated ERS-1 SAR images. Time series of radar backscatter data were compiled for selected sites on the lakes during the period of ice cover (September to June) for the years 1991–92 and 1992–93. A variety of lake-ice processes could be observed, and significant changes in backscatter occurred from the time of initial ice formation in autumn until the onset of the spring thaw. Backscatter also varied according to the location and depth of the lakes. The spatial and temporal changes in backscatter were most constant and predictable at the shallow lakes on the North Slope of Alaska. As a consequence, they represent the most promising sites for long-term monitoring and the detection of changes related to global warming and its effects on the polar regions.

The potential of using Sentinel-1 and ALOS PALSAR-2 data for characterizing West Siberian lake ice backscatter anomalies

2021 ◽  
Author(s):  
Georg Pointner ◽  
Annett Bartsch
Keyword(s):  
Thick Layer ◽  
Arctic Lakes ◽  
The Arctic ◽  
Late Winter ◽  
Alos Palsar ◽  
Lake Ice ◽  
In Situ Data ◽  
L Band ◽  
Ice Regime ◽  
Sar Imagery

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

scholarly journals Arctic sea-ice albedo derived from RGPS-based ice-thickness estimates

2001 ◽  
Vol 33 ◽  
pp. 225-229 ◽  
Author(s):  
R.W. Lindsay
Keyword(s):  
Sea Ice ◽  
Empirical Relationship ◽  
Early Spring ◽  
Snow Accumulation ◽  
Arctic Sea Ice ◽  
Ice Thickness ◽  
First Year ◽  
Large Set ◽  
Radar Images ◽  
Arctic Sea

AbstractThe RADARSAT geophysical processor system (RGPS) uses sequential synthetic aperture radar images of Arctic sea ice taken every 3 days to track a large set of Lagrangian points over the winter and spring seasons. The points are the vertices of cells, which are initially square and 10 km on a side, and the changes in the area of these cells due to opening and closing of the ice are used to estimate the fractional area of a set of first-year ice categories. The thickness of each category is estimated by the RGPS from an empirical relationship between ice thickness and the freezing degree-days since the formation of the ice. With a parameterization of the albedo based on the ice thickness, the albedo may be estimated from the first-year ice distribution. We compute the albedo for the first spring processed by the RGPS, the early spring of 1997. The data include most of the Beaufort and Chukchi Seas. We find that the mean albedo is 0.79 with a standard deviation of 0.04, with lower albedo values near the edge of the perennial ice zone. The biggest source of error is likely the assumed rate of snow accumulation on new ice.

scholarly journals Low Cost and Compact FMCW 24 GHz Radar Applications for Snowpack and Ice Thickness Measurements

Sensors ◽  
2020 ◽  
Vol 20 (14) ◽  
pp. 3909
Author(s):  
Patrick Pomerleau ◽  
Alain Royer ◽  
Alexandre Langlois ◽  
Patrick Cliche ◽  
Bruno Courtemanche ◽  
...  
Keyword(s):  
Snow Depth ◽  
Continuous Wave ◽  
Snow Water Equivalent ◽  
Low Cost ◽  
Ice Thickness ◽  
Lake Ice ◽  
Wide Range ◽  
Thickness Measurements ◽  
24 Ghz

Monitoring the evolution of snow on the ground and lake ice—two of the most important components of the changing northern environment—is essential. In this paper, we describe a lightweight, compact and autonomous 24 GHz frequency-modulated continuous-wave (FMCW) radar system for freshwater ice thickness and snow mass (snow water equivalent, SWE) measurements. Although FMCW radars have a long-established history, the novelty of this research lies in that we take advantage the availability of a new generation of low cost and low power requirement units that facilitates the monitoring of snow and ice at remote locations. Test performance (accuracy and limitations) is presented for five different applications, all using an automatic operating mode with improved signal processing: (1) In situ lake ice thickness measurements giving 2 cm accuracy up to ≈1 m ice thickness and a radar resolution of 4 cm; (2) remotely piloted aircraft-based lake ice thickness from low-altitude flight at 5 m; (3) in situ dry SWE measurements based on known snow depth, giving 13% accuracy (RMSE 20%) over boreal forest, subarctic taiga and Arctic tundra, with a measurement capability of up to 3 m in snowpack thickness; (4) continuous monitoring of surface snow density under particular Antarctic conditions; (5) continuous SWE monitoring through the winter with a synchronized and collocated snow depth sensor (ultrasonic or LiDAR sensor), giving 13.5% bias and 25 mm root mean square difference (RMSD) (10%) for dry snow. The need for detection processing for wet snow, which strongly absorbs radar signals, is discussed. An appendix provides 24 GHz simulated effective refractive index and penetration depth as a function of a wide range of density, temperature and wetness for ice and snow.

scholarly journals The Spatial and Temporal Distribution of Process Gases within the Biowaste Compost

Data ◽  
2019 ◽  
Vol 4 (1) ◽  
pp. 37 ◽  
Author(s):  
Sylwia Stegenta ◽  
Karolina Sobieraj ◽  
Grzegorz Pilarski ◽  
Jacek Koziel ◽  
Andrzej Białowiec
Keyword(s):  
Cross Sections ◽  
Temporal Distribution ◽  
Volume Ratio ◽  
Early Spring ◽  
Spatial And Temporal Distribution ◽  
Plant Operator ◽  
Ambient Temperatures ◽  
Worker Exposure ◽  
Subsequent Measurement ◽  
Process Gases

Composting is generally accepted as the sustainable recycling of biowaste into a useful and beneficial product for soil. However, composting processes can produce gases that are considered air pollutants. In this dataset, we summarized the spatial and temporal distribution of process gases (including rarely reported carbon monoxide, CO) generated inside full-scale composting piles. In total 1375 cross-sections were made and presented in 230 figures. The research aimed to investigate the phenomenon of gas evolution during the composting of biowaste depending on the pile turning regime (no turning, turning once a week, and turning twice a week) and pile location (outdoors, and indoors in a composting hall). The analyzed biowaste (a mixture of tree leaves and branches, grass clippings, and sewage sludge) were composted in six piles with passive aeration including additional turning at a municipal composting plant. The chemical composition and temperature of process gases within each pile were analyzed weekly for ~49–56 days. The variations in the degree of pile aeration (O2 content), temperature, and the spatial distribution of CO, CO2 and NO concentration during the subsequent measurement cycles were summarized and visualized. The lowest O2 concentrations were associated with the central (core) part of the pile. Similarly, an increase in CO content in the pile core sections was found, which may indicate that CO is oxidized in the upper layer of composting piles. Higher CO and CO2 concentrations and temperature were also observed in the summer season, especially on the south side of piles located outdoors. The most varied results were for the NO concentrations that occurred in all conditions. The dataset was used by the composting plant operator for more sustainable management. Specifically, the dataset allowed us to make recommendations to minimize the environmental impact of composting operations and to lower the risk of worker exposure to CO. The new procedure is as follows: turning of biowaste twice a week for the first two weeks, followed by turning once a week for the next two weeks. Turning is not necessary after four weeks of the process. The recommended surface-to-volume ratio of a compost pile should not exceed 2.5. Compost piles should be constructed with a surface-to-volume ratio of less than 2 in autumn and early spring when low ambient temperatures are common.

The hydrologic regime of Mackenzie River and connection of "no-closure" lakes to distributary channels in the Mackenzie Delta, Northwest Territories

1995 ◽  
Vol 32 (7) ◽  
pp. 926-937 ◽  
Author(s):  
C. R. Burn
Keyword(s):  
Water Level ◽  
Drainage Basin ◽  
Late Summer ◽  
River System ◽  
Water Levels ◽  
Ice Thickness ◽  
Mackenzie Delta ◽  
Lake Ice ◽  
Discharge System ◽  
Mackenzie River

Mackenzie Delta lakes have been classified by the seasonal duration of their connection to Mackenzie River. "No-closure" lakes are determined on the basis of minimum summer water level. Such lakes may become disconnected from the Mackenzie in autumn or winter, as water level falls or if the sills between lakes and distributary channels are frozen through and so sealed. Water level in the central delta rises continuously after late November–early December, at first because discharge into the delta increases once the Mackenzie drainage basin has frozen over, and then as sea and channel ice thickens in the outer delta, impounding discharge. Since 1973 this seasonal increase in stage from its minimum in early December to the level on 1 April has been between 29 and 95 cm. Between 1987 and 1994, the rise in stage near Inuvik has been slightly greater than increases in lake-ice thickness (30–68 cm). Channels and lakes that are connected to the Mackenzie discharge system in December may remain connected throughout winter. A critical sill elevation for connection of such lakes to the river system is the minimum stage minus mid-December ice thickness. Recently, these elevations have been from 1.0 to 1.6 m lower than late summer water levels. Lakes with sill elevations still lower may remain connected to the Mackenzie throughout the year. In 1993-1994, only 3 of 16 "no-closure" lakes surveyed near Inuvik remained open to the Mackenzie discharge throughout winter, representing 2% of the lakes in this portion of the delta.

Co-Occurrence Probability Analysis of Sea Ice at Yingkou and Huludao Observation Stations of China

2017 ◽  
Author(s):  
Shanshan Tao ◽  
Zhifeng Wang ◽  
Ri Zhang ◽  
Sheng Dong
Keyword(s):  
Sea Ice ◽  
Probability Distributions ◽  
Joint Probability ◽  
Offshore Structures ◽  
Early Spring ◽  
Probability Analysis ◽  
Ice Thickness ◽  
Occurrence Probability ◽  
Sea Ice Thickness ◽  
Ice Conditions

Co-occurrence probability analysis of sea ice between adjacent areas is very helpful for the hazard prevention and protection strategy making of coastal and offshore engineering. Yingkou and Huludao with similar latitudes are located on the opposite sides of Liaodong Bay of China. Their sea ice conditions are both apparent in winter and early spring, so it is useful to study on the co-occurrence situations of sea ice conditions between these two areas. Based on the annual maximum sea ice thickness of Yingkou and Huludao observation stations, the co-occurrence probability analysis of sea ice thickness is conducted. The joint probability distributions of sea ice thickness between these adjacent areas are constructed by using univariate maximum entropy distributions and four bivariate copulas. Both marginal curve fittings are very well, and the model determined by Gumbel-Hougaard copula describes the bivariate sea ice thickness data best. Then different cases of co-occurrence probabilities of sea ice thickness between Yingkou and Huludao are presented, and they can provide references to the hazard protection of the coastal and offshore structures between these two areas.

scholarly journals Response of ice cover on shallow lakes of the North Slope of Alaska to contemporary climate conditions (1950–2011): radar remote sensing and numerical modeling data analysis

2013 ◽  
Vol 7 (4) ◽  
pp. 3783-3821 ◽  
Author(s):  
C. M. Surdu ◽  
C. R. Duguay ◽  
L. C. Brown ◽  
D. Fernández Prieto
Keyword(s):  
Shallow Lakes ◽  
Ice Cover ◽  
Arctic Lakes ◽  
North Slope ◽  
Lake Ice ◽  
Climate Conditions ◽  
The North ◽  
North Slope Of Alaska ◽  
Sar Data ◽  
Ice Model

Abstract. Air temperature and winter precipitation changes over the last five decades have impacted the timing, duration, and thickness of the ice cover on Arctic lakes as shown by recent studies. In the case of shallow tundra lakes, many of which are less than 3 m deep, warmer climate conditions could result in thinner ice covers and consequently, to a smaller fraction of lakes freezing to their bed in winter. However, these changes have not yet been comprehensively documented. The analysis of a 20 yr time series of ERS-1/2 synthetic aperture radar (SAR) data and a numerical lake ice model were employed to determine the response of ice cover (thickness, freezing to the bed, and phenology) on shallow lakes of the North Slope of Alaska (NSA) to climate conditions over the last six decades. Analysis of available SAR data from 1991–2011, from a sub-region of the NSA near Barrow, shows a reduction in the fraction of lakes that freeze to the bed in late winter. This finding is in good agreement with the decrease in ice thickness simulated with the Canadian Lake Ice Model (CLIMo), a lower fraction of lakes frozen to the bed corresponding to a thinner ice cover. Observed changes of the ice cover show a trend toward increasing floating ice fractions from 1991 to 2011, with the greatest change occurring in April, when the grounded ice fraction declined by 22% (α = 0.01). Model results indicate a trend toward thinner ice covers by 18–22 cm (no-snow and 53% snow depth scenarios, α = 0.01) during the 1991–2011 period and by 21–38 cm (α = 0.001) from 1950–2011. The longer trend analysis (1950–2011) also shows a decrease in the ice cover duration by ∼24 days consequent to later freeze-up dates by 5.9 days (α = 0.1) and earlier break-up dates by 17.7–18.6 days (α = 0.001).

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