scholarly journals Transient thermal modeling of permafrost conditions in Southern Norway

2012 ◽  
Vol 6 (6) ◽  
pp. 5345-5403
Author(s):  
S. Westermann ◽  
T. V. Schuler ◽  
K. Gisnås ◽  
B. Etzelmüller
Keyword(s):  
Snow Depth ◽  
Thermal Modeling ◽  
Conductive Heat ◽  
Snow Pack ◽  
Bottom Temperature ◽  
Ground Temperatures ◽  
Borehole Temperatures ◽  
The 1960S ◽  
Southern Norway ◽  
Transient Thermal

Abstract. Thermal modeling is a powerful tool to infer the temperature regime of the ground in permafrost areas. We present a transient permafrost model, CryoGrid 2, that calculates ground temperatures according to conductive heat transfer in the soil and in the snow pack. CryoGrid 2 is forced by operational air temperature and snow depth products for potential permafrost areas in Southern Norway for the period 1958 to 2009 at 1 km spatial resolution. In total, an area of about 80 000 km2 is covered. The model results are validated against borehole temperatures, permafrost probability maps from "Bottom Temperature of Snow" measurements and inventories of landforms indicative of permafrost occurrence. The validation demonstrates that CryoGrid 2 can reproduce the observed lower permafrost limit to within 100 m at all validation sites, while the agreement between simulated and measured borehole temperatures is within 1 K for most sites. The number of grid cells with simulated permafrost does not change significantly between the 1960s the 1990s. In the 2000s, a significant reduction of about 40% of the area with average 2 m ground temperatures below 0 °C is found which mostly corresponds to degrading permafrost with still negative temperatures in deeper ground layers. The thermal conductivity of the snow is the largest source of uncertainty in CryoGrid 2 strongly affecting the simulated permafrost area. Finally, the prospects of employing CryoGrid 2 for an operational soil temperature product for Norway are discussed.

scholarly journals Transient thermal modeling of permafrost conditions in Southern Norway

2013 ◽  
Vol 7 (2) ◽  
pp. 719-739 ◽  
Author(s):  
S. Westermann ◽  
T. V. Schuler ◽  
K. Gisnås ◽  
B. Etzelmüller
Keyword(s):  
Snow Depth ◽  
Thermal Modeling ◽  
Conductive Heat ◽  
Bottom Temperature ◽  
Ground Temperatures ◽  
Negative Temperatures ◽  
Borehole Temperatures ◽  
The 1960S ◽  
Southern Norway ◽  
Transient Thermal

Abstract. Thermal modeling is a powerful tool to infer the temperature regime of the ground in permafrost areas. We present a transient permafrost model, CryoGrid 2, that calculates ground temperatures according to conductive heat transfer in the soil and in the snowpack. CryoGrid 2 is forced by operational air temperature and snow-depth products for potential permafrost areas in Southern Norway for the period 1958 to 2009 at 1 km2 spatial resolution. In total, an area of about 80 000 km2 is covered. The model results are validated against borehole temperatures, permafrost probability maps from "bottom temperature of snow" measurements and inventories of landforms indicative of permafrost occurrence. The validation demonstrates that CryoGrid 2 can reproduce the observed lower permafrost limit to within 100 m at all validation sites, while the agreement between simulated and measured borehole temperatures is within 1 K for most sites. The number of grid cells with simulated permafrost does not change significantly between the 1960s and 1990s. In the 2000s, a significant reduction of about 40% of the area with average 2 m ground temperatures below 0 °C is found, which mostly corresponds to degrading permafrost with still negative temperatures in deeper ground layers. The thermal conductivity of the snow is the largest source of uncertainty in CryoGrid 2, strongly affecting the simulated permafrost area. Finally, the prospects of employing CryoGrid 2 as an operational soil-temperature product for Norway are discussed.

PLSS Transient Thermal Modeling for Control

1996 ◽  
Author(s):  
Anthony B. Campbell ◽  
Satish S. Nair ◽  
John B. Miles ◽  
Bruce W. Webbon
Keyword(s):  
Thermal Modeling ◽  
Transient Thermal

scholarly journals Forcing the SURFEX/Crocus snow model with combined hourly meteorological forecasts and gridded observations in southern Norway

2017 ◽  
Author(s):  
Hanneke Luijting ◽  
Dagrun Vikhamar-Schuler ◽  
Trygve Aspelien ◽  
Mariken Homleid
Keyword(s):  
Land Surface ◽  
Snow Depth ◽  
Water Resource Management ◽  
Snow Accumulation ◽  
Surface Model ◽  
Snow Melt ◽  
Grid Spacing ◽  
Snow Covered Area ◽  
Covered Area ◽  
Southern Norway

Abstract. In Norway, thirty percent of the annual precipitation falls as snow. Knowledge of the snow reservoir is therefore important for energy production and water resource management. The land surface model SURFEX with the detailed snowpack scheme Crocus (SURFEX/Crocus) has been run with a grid spacing of approximately 1 km over an area in southern Norway for two years (01 September 2014–31 August 2016), using two different forcing data sets: 1) hourly meteorological forecasts from the operational weather forecast model AROME MetCoOp (2.5 km grid spacing), and 2) gridded hourly observations of temperature and precipitation (1 km grid spacing) in combination with the meteorological forecasts from AROME MetCoOp. We present an evaluation of the modeled snow depth and snow cover, as compared to point observations of snow depth and to MODIS satellite images of the snow-covered area. The evaluation focuses on snow accumulation and snow melt. The results are promising. Both experiments are capable of simulating the snow pack over the two winter seasons, but there is an overestimation of snow depth when using only meteorological forecasts from AROME MetCoOp, although the snow-covered area throughout the melt season is better represented by this experiment. The errors, when using AROME MetCoOp as forcing, accumulate over the snow season, showing that assimilation of snow depth observations into SURFEX/Crocus might be necessary when using only meteorological forecasts as forcing. When using gridded observations, the simulation of snow depth is significantly improved, which shows that using a combination of gridded observations and meteorological forecasts to force a snowpack model is very useful and can give better results than only using meteorological forecasts. There is however an underestimation of snow ablation in both experiments. This is mainly due to the absence of wind-induced erosion of snow in the SURFEX/Crocus model, underestimated snow melt and biases in the forcing data.

Thermal Modeling Using Two-Port Network Impedance Fractional-Order Approximations

2021 ◽  
Author(s):  
Jean-François Duhé ◽  
Stéphane Victor ◽  
Pierre Melchior ◽  
Youssef Abdelmounen ◽  
François Roubertie
Keyword(s):  
Heat Transfer ◽  
Frequency Domain ◽  
Fractional Order ◽  
Heat Dissipation ◽  
Thermal Modeling ◽  
Building Design ◽  
Frequency Domain Analysis ◽  
Conductive Heat ◽  
Frequency Behavior ◽  
Thermal Phenomena

Abstract Sufficiently accurate thermal modeling is necessary for many applications such as heat dissipation, melting processes, building design or even bio-heat transfers in surgery. Circuit models help modeling heat transfer dynamics: this method is simple and is often used to model thermal phenomena. However, such models well approximates low and high frequency behavior but they are not accurate enough in the middle band of interest, thus lacking of precision in dynamical terms. A more complete and accurate description of conductive heat transfer can be obtained by using a two-port network. The resulting analytical expressions are complex and nonlinear in the frequency ω. This complexity in the frequency domain is difficult to handle when it comes to control applications and more specifically in real-time applications such as surgery. Consequently, an analysis of this thermal two-port network in the frequency domain directly leads to fractional-order systems. A frequency domain analysis of the series and shunt impedances will be presented and different approximations will be explored in order to obtain simple but sufficiently precise linear fractional transfer function models. The series impedances are approximated by using asymptotic and pole-zero approximations and the shunt impedance is approximated by using a capacitance approximation and two fractional model approximations.

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