Monitoring the Sensible Heat Flux over Urban Areas using Large Aperture Scintillometry: Case Study of Marseille City During the Escompte Experiment

2005 ◽  
Vol 118 (3) ◽  
pp. 449-476 ◽  
Author(s):  
J. -P. Lagouarde ◽  
M. Irvine ◽  
J. -M. Bonnefond ◽  
C. S. B. Grimmond ◽  
N. Long ◽  
...  
Keyword(s):  
Heat Flux ◽  
Urban Areas ◽  
Sensible Heat Flux ◽  
Sensible Heat ◽  
Large Aperture

Heat island mitigation using water retentive pavement sprinkled with reclaimed wastewater

2008 ◽  
Vol 57 (5) ◽  
pp. 763-771 ◽  
Author(s):  
H. Yamagata ◽  
M. Nasu ◽  
M. Yoshizawa ◽  
A. Miyamoto ◽  
M. Minamiyama
Keyword(s):  
Heat Flux ◽  
Urban Areas ◽  
Sensible Heat Flux ◽  
Heat Island ◽  
Temperature Decrease ◽  
Sensible Heat ◽  
Reclaimed Wastewater ◽  
Wet Bulb Globe Temperature ◽  
The Road ◽  
Globe Temperature

In Japan, reclaimed wastewater has been recycled widely for non-potable urban applications and it is to be used for sprinkling roads to mitigate heat island in urban areas. To assess the heat island mitigation effects of the sprinkling reclaimed wastewater on water retentive pavement, we carried out a survey at Shiodome-District, Tokyo. The temperatures of air and roads, humidity, and WBGT (Wet-bulb globe temperature) were measured and heat flux was estimated to compare the condition of the areas with/without sprinkling. The following results were obtained. 1) Sprinkling reclaimed wastewater decreased the road surface temperature by 8 degrees during the daytime and by 3 degrees at night: temperatures equal to those on planting zones. Nevertheless sprinkling was done only in the daytime, the temperature decrease effect was not only obtained during the daytime: it continued through the night, due to the water retentive pavement. 2) Sprinkling reclaimed wastewater reduced the amount of sensible heat flux and increased that of latent heat flux. These results suggest that sprinkling reclaimed wastewater on water retentive pavement can effectively mitigate the heat island phenomenon.

scholarly journals Intercomparison of Sensible Heat Flux from Large Aperture Scintillometer and Eddy Covariance Methods: Field Experiment over a Homogeneous Semi-arid Region

2009 ◽  
Vol 135 (1) ◽  
pp. 151-159 ◽  
Author(s):  
Dawit A. Zeweldi ◽  
Mekonnen Gebremichael ◽  
Junming Wang ◽  
Theodore Sammis ◽  
Jan Kleissl ◽  
...  
Keyword(s):  
Heat Flux ◽  
Field Experiment ◽  
Eddy Covariance ◽  
Arid Region ◽  
Sensible Heat Flux ◽  
Sensible Heat ◽  
Large Aperture ◽  
Large Aperture Scintillometer ◽  
Semi Arid Region ◽  
Semi Arid

Estimating urban sensible heat flux using satellite-based data

2021 ◽  
Author(s):  
Gabriel Rios ◽  
Prathap Ramamurthy
Keyword(s):  
Heat Flux ◽  
Land Cover ◽  
Model Validation ◽  
Satellite Data ◽  
Urban Areas ◽  
Sensible Heat Flux ◽  
Cost Effective ◽  
Surface Energy Budget ◽  
High Temporal Resolution ◽  
Sensible Heat

<p>A model for calculating sensible heat flux (Q<sub>H</sub>) – a primary component of the urban surface energy budget - is presented here. Remote sensing data from the NOAA GOES-16 satellite and a high-resolution land cover dataset are used as inputs to calculate the spatio-temporal variability in urban sensible heat flux. The primary motivation for this model is to present a cost-effective approach to calculate Q<sub>H</sub> independent of traditional flux observations and computational methods. The GOES-16 satellite data, which has a moderate spatial and high temporal resolution (2 km square at 5 minute intervals) enables the estimation of Q<sub>H</sub> over highly heterogeneous urban areas. The model is constructed using an iterative algorithm that uses surface layer turbulence parameterization to solve for Q<sub>H</sub> as a function of the enterprise GOES-16 Land Surface Temperature product, an urban air temperature model, publicly-accessible ground observations, and the National Land Cover Database (NLCD). Preliminary model validation was performed over a five-month period in 2019. Three (3) ground flux stations in the New York City metro area with varying degrees of urbanization were used for model validation. Statistics from validation found an RMSE of 42.9 W-m<sup>-</sup><sup>2</sup>, a mean bias of 12.9 W-m<sup>-2</sup>, and an R<sup>2</sup> of 0.80. Validation results demonstrate that the algorithm shows good correlation with observed values, suggesting that satellite data can be used as an accessible and cost-effective option to estimate Q<sub>H</sub> in urban areas.</p>

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