Daytime sensible heat flux estimation over heterogeneous surfaces using multitemporal land‐surface temperature observations

Actual evapotranspiration is assessed via surface energy balance at an hourly rate. However, a robust estimation of daily evapotranspiration from hourly values is required. Outcomes of surface energy balance are frequently determined via measures of eddy covariance latent heat flux. Surface energy balance can be applied on images acquired at different times and spatial resolutions. In addition, hourly actual evapotranspiration needs to be integrated at a daily rate for operational uses. Questions arise whether the validation of surface energy balance models can benefit from complementary in situ measures of latent heat flux and sap flow transpiration. Here, validation was driven by image acquisition time, spatial resolution, and temporal integration. Thermal and optical images were collected with a proximity-sensing platform on an olive orchard at different acquisition times. Actual latent heat fluxes from canopy and sap flux at tree trunks were measured with a flux tower and heat dissipation probes. The latent heat fluxes were then further analyzed. A surface energy balance was applied over proximity sensing images re-sampled at different spatial resolutions with resulting latent heat fluxes compared to in situ ones. A time lag was observed and quantified between actual latent heat fluxes from canopy and sap flux at the tree trunk. Results also indicate that a pixel resolution comparable to the average canopy size was suitable for estimating the actual evapotranspiration via a single source surface energy balance model. Images should not be acquired at the beginning or the end of the diurnal period. Findings imply that sap flow transpiration can be used to measure surface energy balance at a daily rate or when images are found at an hourly rate near noon, and the existing time lag between the latent heat flux at the canopy and the sap flow at the trunk does not need to be taken into account.

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“…Other measurements are based on scintillometry, lisimetry, and surface renewal (e.g., [12][13][14]). …”

Section: Methodsmentioning

confidence: 99%

On the Use of the Eddy Covariance Latent Heat Flux and Sap Flow Transpiration for the Validation of a Surface Energy Balance Model

et al. 2018

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“…Approaching the shear at the canopy top by u*/hc (hc is the canopy height), the semi-empirical Equation ( 6) was proven reliable for a variety of canopies. Assuming that the maximum temperature to be reached by the parcel of air is LST, Equation (7) proposes a linear relationship between quantities (LST-T) and A where T is the potential temperature of the air measured at a reference height above the canopy [21,22]. In Equation (7), b is a coefficient (hereafter referred to as offset) that corrects for the fact that (LST-T) may not necessarily follow the adiabatic lapse rate at neutral conditions (i.e., case where A = 0 K) and z0m is the roughness length for momentum.…”

Section: Sensible Heat Fluxmentioning

confidence: 99%

“…Thus, ε0 was set to 0.97. The offset in Equation ( 7) was determined as in Castellví et al(2016) [22]. Thus, the coefficient b at sunrise and sunset was determined setting A = 0 K, at noon the offset was set to zero and for the rest of the day it was calculated using a linear relationship from sunrise to noon and from noon to sunset.…”

Section: Solving the Sensible And Latent Heat Fluxesmentioning

confidence: 99%

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Sensible Heat and Latent Heat Flux Estimates in a Tall and Dense Forest Canopy under Unstable Conditions

Castellvı́

Buttar

et al. 2022

Atmosphere

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A method to estimate the sensible heat flux (H) for unstable atmospheric condition requiring measurements taken in half-hourly basis as input and involving the land surface temperature (LST), HLST, was tested over a tall and dense aspen stand. The method avoids the need to estimate the zero-plane displacement and the roughness length for momentum. The net radiation (Rn) and the latent heat flux (λE) dominated the surface energy balance (SEB). Therefore, λE was estimated applying the residual method using HLST as input, λER-LST. The sum of H and λE determined with the eddy covariance (EC) method led to a surface energy imbalance of 20% Rn. Thus, the reference taken for the comparisons were determined forcing the SEB using the EC Bowen ratio (BREB method). For clear sky days, HLST performed close to HBREB. Therefore, it showed potential in the framework of remote sensing because the input requirements are similar to current methods widely used. For cloudy days, HLST scattered HBREB and nearly matched the accumulated sensible hear flux. Regardless of the time basis and cloudiness, λER-LST was close to λEBREB. For all the data, both HLST and λER-LST were not biased and showed, respectively, a mean absolute relative error of 24.5% and 12.5% and an index of agreement of 68.5% and 80%.

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“…The interaction of surface turbulent structures with surface temperature fluctuations has been draw attention gradually. The turbulent structures sweep the interface and give rise to surface temperature fluctuations [16] [17]. Recent studies have revealed that the characteristic of the near-surface airflow can be indirectly deduced based on surface high frequency temperature fluctuations.…”

Section: Introductionmentioning

confidence: 99%

Research of near-wall thermodynamic state for indoor airflow over the vertical heating unit using TIV/PIV/RTD

Luo

Liu

2019

Building and Environment

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Up to now, few studies focus on thermodynamic state including the velocity and temperature of the air near heating unit. The thermodynamic state of the airflow over an indoor heating unit has a significant influence on indoor thermal comfort and energy consumption. This study analyzed the thermal and dynamic state of the near-wall airflow over the heating unit. The thermal state was measured using resistance thermal detectors (RTDs). The near-wall airflow field were measured by particle image velocimetry (PIV) and TIV. The performance of TIV in natural and mixed convection were evaluated by comparing the TIV and PIV measurement results. Under natural convection, the velocity shows vertical variation and the spatial difference changes more pronounced with the increase of heating temperature. Under mixed convection, the near-wall temperature changes uniform and the velocity exhibits a decreasing trend with the increase of height. Through the spectrum analysis of the temperature, it is found that the velocity measured by TIV is close to the velocity near the boundary layer to some content. The positions of the near-surface velocity measured by TIV are not fixed in all cases and change with the change of the boundary layer. The findings in this study can provide a convenient and feasible flow field measurement method suitable for actual space scale. This method can predict the effect of heating terminal units on indoor airflow and thermal environment, so as to optimize the form and arrangement of the heating terminal units, and improve heating efficiency and occupants' thermal comfort.

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Daytime sensible heat flux estimation over heterogeneous surfaces using multitemporal land‐surface temperature observations

Cited by 14 publications

References 83 publications

On the Use of the Eddy Covariance Latent Heat Flux and Sap Flow Transpiration for the Validation of a Surface Energy Balance Model

On the Use of the Eddy Covariance Latent Heat Flux and Sap Flow Transpiration for the Validation of a Surface Energy Balance Model

Sensible Heat and Latent Heat Flux Estimates in a Tall and Dense Forest Canopy under Unstable Conditions

Research of near-wall thermodynamic state for indoor airflow over the vertical heating unit using TIV/PIV/RTD

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