Thermal simulation of a lake with winter ice cover1

Patterson, John C.; Hamblin, P. F.

doi:10.4319/lo.1988.33.3.0323

Cited by 119 publications

(108 citation statements)

References 23 publications

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“…Lemke 1987;Riedlinger and Warn-Varnas 1990;Manabe et al 199 l), and similar thermodynamic lake-ice models have been used by others (e.g. Patterson and Hamblin 1988;Cu and Stefan 1990;Hamblin and Carmack 1990;Hostetler and Bartlein 1990).…”

Section: Model Descriptionmentioning

confidence: 99%

“…Our model, LIMNOS (lake ice model-numerical operational simulation), has similar algorithms to these other models. However, previous studies have primarily concentrated on either model development and validation (Patterson and Hamblin 1988;Gu and Stefan 1990;Croley and Assel 1994) or linkage to atmospheric models (Hostetler et al 1993). Our current effort is a detailed sensitivity analysis of the relative importance of meteorological and limnological parameters in the thermodynamics of lake ice.…”

Section: Acknowledgmentsmentioning

confidence: 99%

“…Small lakes can be adequately simulated by vertical models, such as the dynamic reservoir simulation model (DYRESM; Imberger 822 and Patterson 198 1; Patterson and Hamblin 1988), Minnesota lake model (MINLAKE; Gu and Stefan 1990), and the model developed by Hostetler and colleagues (e.g. Hostetler and Bartlein 1990).…”

Section: Acknowledgmentsmentioning

confidence: 99%

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Measuring the sensitivity of southern Wisconsin lake ice to climate variations and lake depth using a numerical model

Vavrus

Wynne

Foley

1996

Limnology & Oceanography

145

121

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The sensitivity of lake ice phenology to climatic variations is tested using a numerical lake-ice model (LIMNOS). The model simulates the evolution of ice and snow cover by time-integrating equations of vertical heat conduction through ice and snow. The required input variables are mean lake depth, air temperature and moisture, wind speed, solar radiation, snowfall, and cloudiness.The model simulates the ice-on and ice-off dates of three southern Wisconsin lakes to within 1 week of their historical averages, despite large differences in mean depth. Using hourly meteorological data from 196 l-l 990 as inputs, LIMNOS simulates the annual ice-on and ice-off dates of Lake Mendota with a median absolute error of only 2 d and 4 d, respectively.The atmospheric variables are altered to determine the sensitivity of Lake Mendota ice phenology to climate change. The simulated ice-off date shows stronger sensitivity than the ice-on date to air temperature changes, and the sensitivity of both dates is greater for climatic warmings than toolings. Increased snowfall causes a monotonic delay in the breakup date, whereas decreased snowfall nonlinearly hastens ice decay.Interest in lake ice has been spurred by both basic and applied considerations, including its role in the heat budget 0.f lakes (e.g. Birge 19 15;Juday 1940;Scott 1964;Hamblin and Carmack 1990), importance to aquatic ecosystems (e.g. Blumberg and DiToro 1990; Magnuson et al. 1990), structural engineering and navigational implications (e.g. Wortley 1992), and use as a climate indicator (e.g. Scott 1964; Schindler et al. 1990;Hanson et al. 1992;Assel and Robertson 1995).Although the complex relationships between lake ice and climate are central to all of these concerns, increased use of lake ice as a climate proxy has led to the recent work in this area. Atmospheric general circulation models Special thanks to Brad Franklin, Pam Knox, John J. Magnuson, John E. Kutzbach, and Thomas M. Lillesand for help and cooperation throughout this project. We are also grateful to Steve Hostetler and an anonymous reviewer for insightful comments in reviewing this manuscript.

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Section: Model Descriptionmentioning

confidence: 99%

Section: Acknowledgmentsmentioning

confidence: 99%

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Measuring the sensitivity of southern Wisconsin lake ice to climate variations and lake depth using a numerical model

Vavrus

Wynne

Foley

1996

Limnology & Oceanography

145

121

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“…During ice-free conditions, the sum of the energy fluxes at the lake surface (Qo) dictates the time rate of changes ofwater temperature Tw, according to Patterson and Hamblin [ 1988]. When a thick snow cover causes hydrostatic sinking of the ice-snow boundary below the surface of the lake, the model converts some of the snow into grey ice, following Ledley [1985].…”

Section: Limnos: Model Descriptionmentioning

confidence: 99%

Global patterns of lake ice phenology and climate: Model simulations and observations

Walsh¹,

Vavrus²,

Foley³

et al. 1998

J. Geophys. Res.

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Abstract. Lake ice phenology parameters (dates of ice onset and thaw) provide an integrative climatic description of autumn to springtime conditions. Interannual variations in lake ice duration and thickness allow estimates of local climatic variability. In addition, long-term changes in lake ice phenology may provide a robust indication of climatic change. The relationship between lake ice and climate enables the use of process-based models for predicting the dates of freeze-up and thaw. LIMNOS (Lake Ice Model Numerical Operational Simulator) is one such model, which was originally designed to simulate the ice phenology of several lakes in southern Wisconsin. In this study, LIMNOS is modified to run globally on a 0.5 ø by 0.5 ø latitude-longitude grid using average monthly climate data. We initially simulate the ice phenology for lakes of 5-and 20-m mean depths across the northern hemisphere to demonstrate the effects of lake depth, latitude, and elevation on ice phenology. To evaluate the results of LIMNOS we also simulate the ice phenology of 30 lakes across the northern hemisphere which have long-term ice records. LIMNOS reproduces the general geographic patterns of ice-on and ice-off dates, although ice-off dates tend to occur later in the model. Lakes with extreme depths, surface areas, or precipitation are simulated less accurately than small, shallow lakes. This study reveals strengths and weaknesses of LIMNOS and suggests aspects which need improving. Future investigations should focus on the use of geographically extensive lake ice observations and modeling to elucidate patterns of climatic variability and/or climate change. In this study, we attempt to describe the global-scale patterns of lake ice phenology in relation to climate. First, we use a numerical model of lake ice physics (Lake Ice Model Numerical Operational Simulator (LIMNOS)) to simulate the phenology of lake ice for lakes across the entire globe. Second, the model is applied to a 0.5 ø by 0.5 ø latitude-longitude grid and is driven by long-term average (30-year; 1931-1960) climatic data. Third, in each 0.5 ø by 0.5 ø grid cell we simulate lake ice development over hypothetical lakes of 5-and 20-m mean depths to help quantify the role of lake morphometry. Fourth, we compare model simulations against a compilation of 30 long-term lake ice phenology records spanning the northern hemisphere. By comparing the model simulations against these observations we evaluate the potential skill of using computer models to describe the physical relationships between lake ice and climate across continental and global scales. 28,825

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“…Therefore, during the ice cover period, water temperatures are simulated by solving (4) together with additional equations for snow depth and ice thickness [Patterson and Hamblin, 1988;Gu and Stefan, 1990]. Snow thickness is determined from snow accumulation (precipitation), followed by compaction and melting of snow by surface heat input (convection, rainfall, and solar radiation), and melting within the snow layer due to internal absorption of short wave radiation.…”

Section: Year-round Lake Water Temperature Modelmentioning

confidence: 99%

Temperature variability in lake sediments

Fang¹,

Stefan²

1998

Water Resources Research

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Abstract. Sediment temperatures were simulated from the sediment-water interface down to 10 rn for circular lakes with surface areas of 0.2-10 km 2 and maximum lake depths of 4-24 m. The calculations were made using daily weather conditions measured over 19 years (1961)(1962)(1963)(1964)(1965)(1966)(1967)(1968)(1969)(1970)(1971)(1972)(1973)(1974)(1975)(1976)(1977)(1978)(1979) at three geographic locations, representing climate conditions from north to south latitudes in the central United States. A one-dimensional sediment temperature model coupled with a year-round lake water temperature model (MINLAKE96) was used. The models were tested against extensive water temperature and some sediment temperature data. Lake sediment equilibrium temperatures at 10 rn below the water-sediment interface were found almost equal to the annual mean temperature of the overlaying water and hence dependent on the lake temperature regime, which in turn depends on the local climate and a lake's physical characteristics (e.g., surface area As, maximum depth H•oc, and water transparency as measured by Secchi depth). The lake geometry ratio A 0'25//-/ (m -ø'5) gives a good indicationwhether a lake will permanently stratify in summer or not, and that makes a large difference for the sediment temperature regime. Sediment temperatures at 10 rn below the littoral waters of a lake are almost equal to subsurface ground (terrestrial) temperatures, regardless of the type of lake, whereas sediment temperatures at 10 rn below the deepest portion of a stratified lake have a strong linear relationship with the logarithm of the lake geometry ratio. Two generalized 10-m sediment temperature profiles were developed, one for ice-covered lakes and the other for year-round open water lakes. Sediment temperatures at 10 rn below the sediment-water interface at different depths of a lake can be reconstructed from the generalized profiles using Secchi depth, surface area, maximum depth, and annual mean air temperature as input. Sediment temperature at several meters depth (e.g., 10 m) below a lake bed is a useful and necessary initial condition to predict water temperature dynamics in lakes of the temperate zone and hence other water quality parameters whose kinetics are linked to water temperature. In this paper, we address a very similar physical situation: sediment temperatures below lakes. In our discussion, the sediment at the bottom of a lake is analogous to soil below the ground surface, and the water-sediment interface in the lake is analogous to a soil (ground) surface. The heat flux into or out of the lake sediments is assumed to be driven solely by the water temperature at the lake bottom (groundwater flow is ignored in this study). Since lake water temperatures are largely determined by heat exchange with the atmosphere, one can say that, in principle, lake sediment temperatures are also driven by atmospheric inputs. However, the modulation ex-717

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Thermal simulation of a lake with winter ice cover1

Cited by 119 publications

References 23 publications

Measuring the sensitivity of southern Wisconsin lake ice to climate variations and lake depth using a numerical model

Measuring the sensitivity of southern Wisconsin lake ice to climate variations and lake depth using a numerical model

Global patterns of lake ice phenology and climate: Model simulations and observations

Temperature variability in lake sediments

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