Ground temperature estimations using simplified analytical and semi-empirical approaches

Droulia, Fotoula; Lykoudis, S.; Tsiros, Ioannis X.; Alvertos, N.; Akylas, Evangelos; Garofalakis, I.

doi:10.1016/j.solener.2008.07.013

Cited by 68 publications

(37 citation statements)

References 22 publications

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“…Indeed, we observed such longer time-scale changes in subsurface temperatures and chose relatively similar days in order to test our methodology. However, using FT, all signals can be modeled using a series of superimposed sine waves and superimposing annual and daily surface temperature sinusoids achieves more accuracy in predicting heat flux in soil (Hu et al, 2002;Elias et al, 2004;Droulia et al, 2009). The method for applying a sine wave soil heat conduction model to each of the harmonic components of a FT decomposition has long been recognized to improve accuracy of predicting subsurface temperatures (Van Wijk and de Vries, 1966;Ballard, 1972).…”

Section: Discussionmentioning

confidence: 99%

“…Sinusoidal soil temperature models that assume periodic temperature fluctuations and are parameterized with simple meteorological measurements are particularly attractive due to their ease of calculation and minimal data requirements (Paul et al, 2004;Droulia et al, 2009). However, such models can provide unsatisfactory results because they assume soil homogeneity and ignore the spatiotemporal temperature variations caused by overstory shading (Hardy et al, 2004;Bond-Lamberty et al, 2005).…”

Section: Introductionmentioning

confidence: 99%

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Forest understory soil temperatures and heat flux calculated using a Fourier model and scaled using a digital camera

Graham

Lam

Yuen

2010

Agricultural and Forest Meteorology

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a b s t r a c tThe characterization of the solar radiation environment under a forest canopy is important for both understanding temperature-dependent biological processes and validating energy balance models. A modified sinusoidal model of soil heat conductivity was used to estimate subsurface temperature and heat flux from the uneven but periodic solar heating of the soil surface due to sun flecks from a forest canopy. Using a mobile sensor platform with an infrared thermometer along an 11 m transect, a sunfleck model of soil surface temperature was tested using soil surface temperature maxima, air temperatures, and photodiodes placed on the soil surface to measure sunflecks. A pan-tilt-zoom digital camera on a 10 m tower above the site was then used to capture a time series of panoramic images of sunflecks reflected from the soil surface and to scale the sunfleck temperature model to a wide area. Finally, this image-based model of surface temperatures was combined with the modified sinusoidal model for heat conduction to estimate soil subsurface temperatures and heat flux over a wide area due to sunflecks from a forest canopy.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Forest understory soil temperatures and heat flux calculated using a Fourier model and scaled using a digital camera

Graham

Lam

Yuen

2010

Agricultural and Forest Meteorology

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“…This is not an accurate representation when the surface forcing is applied for some finite time, where the different depths exhibit a transient and more complex behaviour. However, for many systems the quasi-steady state approximation is reasonable, as exemplified by the analysis of Droulia et al [2009]. This model was extended by Droulia et al [2009] to account for both the daily and annual heat waves, which involves the superposition of two waves.…”

Section: Iii24 Initial and Boundary Conditionsmentioning

confidence: 99%

“…However, for many systems the quasi-steady state approximation is reasonable, as exemplified by the analysis of Droulia et al [2009]. This model was extended by Droulia et al [2009] to account for both the daily and annual heat waves, which involves the superposition of two waves. The final solution is essentially a sum of terms of the form of Eq.…”

Section: Iii24 Initial and Boundary Conditionsmentioning

confidence: 99%

Interactions Between Downslope Flows and a Developing Cold-Air Pool

Burns

Chemel

2014

Boundary-Layer Meteorol

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I would like to dedicate this thesis to my family.i Abstract Downslope flows and regions of enhanced cooling have important impacts on society and the environment. Parameterisation of these often subgrid-scale phenomena in numerical models requires a sound understanding of the underlying physical processes, which has been the overarching aim of this work. A numerical model has been used to characterise the development of a region of enhanced cooling in an idealised alpine valley with width and depth of order 10 and 1 km, respectively, under stable, decoupled, poorly-drained conditions. A focus of this work has been to remove the uncertainty surrounding the forcing mechanisms behind the development of regions of enhanced cooling. The average valley-atmosphere cooling has been found to be almost equally partitioned between radiative and dynamics effects. Complex interactions between the downslope flows and the region of enhanced cooling have been quantified for the first time. For example, relatively large variations in the downslope flows are generally restricted to the region of enhanced cooling and cannot solely be attributed to the analytical model of [McNider, 1982a]. These flow variations generally coincide with return flows above the downslope flows, where a thin region of unstable air occurs, as well as coinciding with elongated downslope flow structures. The impact of these interactions on the dispersion of passive pollutants has been investigated. For example, pollutants are generally trapped within the region of enhanced cooling. The concentration of pollutants within the region of enhanced cooling, emitted over the lower half of the slopes, increase as the emission source moves away from the ground-based inversion that expands from the bottom of the valley. The concentration of pollutants within the region of enhanced cooling is very similar when varying the location of the emission source over the top half of the valley slopes. This work includes a test of the effects of varying the horizontal numerical grid resolution on average valley-atmosphere temperature changes.iii

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“…Most of these factors change irregularly and as a result, the prediction and estimation of vertical air temperature is multifaceted. In previous studies, many analytical models (Smerdon et al 2006), semi-analytical models (Droulia et al 2009;Yuan et al 2008), empirical models (Al-Ajmi et al 2006), numerical methods (Janssen et al 2004;Rees et al 2000), Fourier models (Graham et al 2010) and neural network methods (dos Santos Coelho et al 2009) have been used to solve various heat transfer problems (Rees et al 2000). Most of these methods require many measured parameters, some of which are hard to obtain under real field conditions.…”

Section: Introductionmentioning

confidence: 99%

Numerical simulation of urban heat island intensity under urban–suburban surface and reference site in Kolkata, India

Khan

Chatterjee

2016

Model. Earth Syst. Environ.

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Urban heat island intensity (UHII) in Kolkata has been assessed using simplified numerical model for vertical temperature measurement in tropical monsoon summer month (June, 2015) during pre-onset of monsoon season. The data of 25 field observation sites show that the surface temperature curves are likely to mathematical trapeziums, and surface temperatures are related to vertical air temperatures. Therefore, approximated temperature trapeziums that are determined by high and lower air temperatures can be used to numerical simulation the vertical surface temperature fluctuation or variation. Two different field observation sites respectively in the urban and suburban areas were taken as model purpose. Distinct and good agreement was obtained between numerical simulation and observed temperature. Observed temperatures indicate the mean temperature under urban concrete surface environment is about 3.54°C greater than that of adjacent suburban open surface. The deviation from normal is due to the heat wave environmental effect and different surface thermal effect, which are about 2.08°C and 2.92°C, respectively. Combined with air relative humidity (RH), 'Heat' islands associated with 'Dry' island, which means urban air relative humidity is lower than suburban air relative humidity (79.52 %,). According to the variation of RH and temperature deviation graphs, urban heat island, vertical surface types and rainfall are important factors that influence the air humidity and temperature.

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Ground temperature estimations using simplified analytical and semi-empirical approaches

Cited by 68 publications

References 22 publications

Forest understory soil temperatures and heat flux calculated using a Fourier model and scaled using a digital camera

Forest understory soil temperatures and heat flux calculated using a Fourier model and scaled using a digital camera

Interactions Between Downslope Flows and a Developing Cold-Air Pool

Numerical simulation of urban heat island intensity under urban–suburban surface and reference site in Kolkata, India

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