Hourly estimation of soil heat flux density at the soil surface with three models and two field methods

Venegas, Pablo; Grandón, A.; Jara, Jorge; Paredes, Jerónimo

doi:10.1007/s00704-012-0705-z

Cited by 11 publications

(18 citation statements)

References 24 publications

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“…Santanello and Friedl (2003) developed a universal approach to estimate G 0 from net radiation using two parameters based on the amplitude of the soil surface temperature. This approach could well produce the daytime G 0 (Liebethal and Foken 2007;Venegas et al 2013). Cellier et al (1996) presented a method to determine G 0 as a fraction of sensitive heat flux, which yielded a better result in bare soils with very low soil water content.…”

Section: Introductionmentioning

confidence: 98%

“…Another simple estimation was considering G 0 as the fraction of net radiation (Choudhury et al 1987;Kustas and Daughtry 1990). However, it had been pointed out by Venegas et al (2013) that it was rather poor with the varied or constant percentage during 1 day, especially during the daytime (Liebethal and Foken 2007). Santanello and Friedl (2003) developed a universal approach to estimate G 0 from net radiation using two parameters based on the amplitude of the soil surface temperature.…”

Section: Introductionmentioning

confidence: 99%

“…In fact, Liebethal and Foken (2007) evaluated six approaches to estimate G 0 , but only two approaches were chosen to estimate the whole daily G 0 , and the data was collected without considering different weather conditions. Venegas et al (2013) compared three models and two methods to estimate G 0 on clear days and cloudy days, but only daylight (from 8:00 to 18:00) estimation was discussed. Overall, the application of these models and methods to estimate daily G 0 lacks systematic validation under different weather conditions, including rainfall events.…”

Section: Introductionmentioning

confidence: 99%

“…The gradient calorimetric method was regarded as the reference due to its well performance of estimating G 0 (Liebethal et al 2005;Evett et al 2012;Venegas et al 2013). The objectives of this study are (1) to evaluate the estimation accuracy of G 0 by the three models and one method on the day under different weather conditions, (2) to determine the optimal measurement depth of the heat flux plate under different weather conditions for plate calorimetric, and (3) to find out which model/method is priority to estimate G 0 under different weather conditions.…”

Section: Introductionmentioning

confidence: 99%

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Estimation of ground heat flux from soil temperature over a bare soil

Wang

et al. 2016

Theor Appl Climatol

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Ground soil heat flux, G 0 , is a difficult-to-measure but important component of the surface energy budget. Over the past years, many methods were proposed to estimate G 0 ; however, the application of these methods was seldom validated and assessed under different weather conditions. In this study, three popular models (force-restore, conduction-convection, and harmonic) and one widely used method (plate calorimetric), which had well performance in publications, were investigated using field data to estimate daily G 0 on clear, cloudy, and rainy days, while the gradient calorimetric method was regarded as the reference for assessing the accuracy. The results showed that harmonic model was well reproducing the G 0 curve for clear days, but it yielded large errors on cloudy and rainy days. The force-restore model worked well only under rainfall condition, but it was poor to estimate G 0 under rain-free conditions. On the contrary, the conduction-convection model was acceptable to determine G 0 under rain-free conditions, but it generated large errors on rainfall days. More importantly, the plate calorimetric method was the best to estimate G 0 under different weather conditions compared with the three models, but the performance of this method is affected by the placement depth of the heat flux plate. As a result, the heat flux plate was recommended to be buried as close as possible to the surface under clear condition. But under cloudy and rainy conditions, the plate placed at depth of around 0.075 m yielded G 0 well. Overall, the findings of this paper provide guidelines to acquire more accurate estimation of G 0 under different weather conditions, which could improve the surface energy balance in field.

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Section: Introductionmentioning

confidence: 98%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Estimation of ground heat flux from soil temperature over a bare soil

Wang

et al. 2016

Theor Appl Climatol

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“…4690 V. R. N. Pauwels and E. Daly: Ground heat flux parameterization flux parameterization schemes can be found in Liebethal and Foken (2007) and Venegas et al (2013).…”

Section: Introductionmentioning

confidence: 99%

Advantages of analytically computing the ground heat flux in land surface models

Pauwels

Daly

2016

Hydrol. Earth Syst. Sci.

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Abstract. It is generally accepted that the ground heat flux accounts for a significant fraction of the surface energy balance. In land surface models, the ground heat flux is typically estimated through a numerical solution of the heat conduction equation. Recent research has shown that this approach introduces errors in the estimation of the energy balance. In this paper, we calibrate a land surface model using a numerical solution of the heat conduction equation with four different vertical spatial resolutions. It is found that the thermal conductivity is the most sensitive parameter to the spatial resolution. More importantly, the thermal conductivity values are directly related to the spatial resolution, thus rendering any physical interpretation of this value irrelevant. The numerical solution is then replaced by an analytical solution. The results of the numerical and analytical solutions are identical when fine spatial and temporal resolutions are used. However, when using resolutions that are typical of land surface models, significant differences are found. When using the analytical solution, the ground heat flux is directly calculated without calculating the soil temperature profile. The calculation of the temperature at each node in the soil profile is thus no longer required, unless the model contains parameters that depend on the soil temperature, which in this study is not the case. The calibration is repeated, and thermal conductivity values independent of the vertical spatial resolution are obtained. The main conclusion of this study is that care must be taken when interpreting land surface model results that have been obtained using numerical ground heat flux estimates. The use of exact analytical solutions, when available, is recommended.

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Impacts of soil heat flux calculation methods on the surface energy balance closure

Russell

Gao

et al. 2015

Agricultural and Forest Meteorology

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Hourly estimation of soil heat flux density at the soil surface with three models and two field methods

Cited by 11 publications

References 24 publications

Estimation of ground heat flux from soil temperature over a bare soil

Estimation of ground heat flux from soil temperature over a bare soil

Advantages of analytically computing the ground heat flux in land surface models

Impacts of soil heat flux calculation methods on the surface energy balance closure

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