An Alternative Heat-Budget Model Relevant to Heat Transfer in Fishes and Its Practical Use for Detecting Their Physiological Thermoregulation

2006 ◽  
Vol 23 (12) ◽  
pp. 1065-1071 ◽  
Author(s):  
Takashi Kitagawa ◽  
Shingo Kimura
Keyword(s):  
Heat Transfer ◽  
Heat Budget ◽  
Budget Model

scholarly journals Thermal Inertia Approach Using a Heat Budget Model to Estimate the Spatial Distribution of Surface Soil Moisture over a Semiarid Grassland in Central Mongolia

2018 ◽  
Vol 19 (1) ◽  
pp. 245-265 ◽  
Author(s):  
Dai Matsushima ◽  
Jun Asanuma ◽  
Ichirow Kaihotsu
Keyword(s):  
Time Series ◽  
Soil Moisture ◽  
Surface Soil ◽  
Heat Budget ◽  
Atmospheric Stability ◽  
Thermal Inertia ◽  
In Situ Observation ◽  
Surface Soil Moisture ◽  
Budget Model

Abstract Thermal inertia is a physical parameter that evaluates soil thermal properties with an emphasis on the stability of the temperature when the soil is affected by heating/cooling. Thermal inertia can be retrieved from a heat budget formulation as a parameter when the time series of Earth surface temperature and forcing variables, such as insolation and air temperature, are given. In this study, a two-layer, linearized heat budget model was employed for the retrieval of thermal inertia over a grassland in a semiarid region. Application of different formulations to the aerodynamic conductance with respect to atmospheric stability significantly improved the accuracy of the thermal inertia retrieval. The retrieved values of thermal inertia were well correlated with in situ surface soil moisture at multiple ground stations. The daily time series of thermal inertia–derived soil moisture qualitatively agreed well with in situ soil moisture after antecedent rainfalls, which was found after fitting the time series to an exponentially decaying function. On the contrary, AMSR2 soil moisture mostly did not agree with in situ soil moisture. The results of the estimation showed high accuracy: the root-mean-square error was 0.038 m3 m−3 compared to the in situ data and was applied to an area of 2° × 2° in which the in situ observation locations were included. The spatiotemporal distribution of surface soil moisture was mapped at a 0.03° × 0.03° spatial resolution in the study area as 10- or 11-day averages over a vegetation growth period of 2012.

scholarly journals Interannual and seasonal asymmetries in Gulf Stream Ring Formations from 1980 to 2019

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Adrienne Silver ◽  
Avijit Gangopadhyay ◽  
Glen Gawarkiewicz ◽  
E. Nishchitha S. Silva ◽  
Jenifer Clark
Keyword(s):  
Heat Transfer ◽  
Gulf Stream ◽  
Heat Budget ◽  
Formation Rate ◽  
Ring Formation ◽  
The North ◽  
Warm Core ◽  
Formation Behavior ◽  
The Difference ◽  
Cold Core

AbstractAs the Gulf Stream separates from the coast, it sheds both Warm and Cold Core Rings between $$75^\circ$$ 75 ∘ and $$55^\circ \,\hbox {W}$$ 55 ∘ W . We present evidence that this ring formation behavior has been asymmetric over both interannual and seasonal time-scales. After a previously reported regime-shift in 2000, 15 more Warm Core Rings have been forming yearly compared to 1980–1999. In contrast, there have been no changes in the annual formation rate of the Cold Core Rings. This increase in Warm Core Ring production leads to an excess heat transfer of 0.10 PW to the Slope Sea, amounting to 7.7–12.4% of the total Gulf Stream heat transport, or 5.4–7.3% of the global oceanic heat budget at $$30^\circ \,\hbox {N}$$ 30 ∘ N . Seasonally, more Cold Core Rings are produced in the winter and spring and more Warm Core Rings are produced in the summer and fall leading to more summertime heat transfer to the north of the Stream. The seasonal cycle of relative ring formation numbers is strongly correlated (r = 0.82) with that of the difference in upper layer temperatures between the Sargasso and Slope seas. This quantification motivates future efforts to understand the recent increasing influence of the Gulf Stream on the circulation and ecosystem in the western North Atlantic.

scholarly journals Daytime Heat Transfer Processes over Mountainous Terrain

2013 ◽  
Vol 70 (12) ◽  
pp. 4041-4066 ◽  
Author(s):  
Juerg Schmidli
Keyword(s):  
Heat Transfer ◽  
Land Surface ◽  
Heat Budget ◽  
Surface Fluxes ◽  
Turbulent Heat ◽  
Mountainous Terrain ◽  
Dynamic Feedback ◽  
Mean Flow ◽  
Valley Wind ◽  
Transfer Processes

Abstract The daytime heat transfer mechanisms over mountainous terrain are investigated by means of large-eddy simulations over idealized valleys. Two- and three-dimensional topographies, corresponding to infinite and finite valleys, are used in order to evaluate the influence of the along-valley wind and the valley surroundings on the heat transfer processes. The atmosphere is coupled to an interactive land surface, allowing for dynamic feedback on the surface fluxes. The valley heat budget is analyzed both from a local and bulk perspective, and the flow is Reynolds decomposed into its mean and turbulent component. The analysis clarifies recent issues of contention regarding the heating of the valley atmosphere. The flow decomposition allows one to clearly distinguish between the different heating processes: those associated with the mean flow, such as advection-induced cooling by the upslope flows and the warming induced by the compensating subsidence, and those associated with the turbulent motions. The latter include the warming of the mixed layer due to the convergence of the turbulent heat flux and cooling in the capping inversion due to overshooting thermals. The analysis from the bulk perspective confirms that the net effect of the thermally induced cross-valley circulation is to export heat out of the valley and away from the mountain ridge. The valley-volume effect is confirmed as the primary cause of enhanced diurnal temperature amplitudes in valleys. The results are robust with regard to the different topographies studied.

Regional distribution of perceived temperatures estimated by the human heat budget model (the Klima-Michel model) in South Korea

2009 ◽  
Vol 26 (2) ◽  
pp. 275-282 ◽  
Author(s):  
Jiyoung Kim ◽  
Kyu Rang Kim ◽  
Byoung-Cheol Choi ◽  
Dae-Geun Lee ◽  
Jeong-Sik Kim
Keyword(s):  
South Korea ◽  
Heat Budget ◽  
Regional Distribution ◽  
Budget Model
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