Estimation of urban sensible heat flux using a dense wireless network of observations

Nadeau, Daniel F.; Brutsaert, Wilfried; Parlange, Marc B.; Bou‐Zeid, Elie; Barrenetxea, Guillermo; Couach, O.; Boldi, Marc Olivier; Selker, John S.; Vetterli, Martin

doi:10.1007/s10652-009-9150-7

Cited by 56 publications

(38 citation statements)

References 53 publications

(65 reference statements)

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“…To determine the input parameters for r a , the approach of [10] is modified to the satellite data. Both, roughness length (for heat and momentum) and displacement height are needed in r a calculation.…”

Section: A Flux Calculationmentioning

confidence: 99%

Spatial Distribution of Sensible and Latent Heat Flux in the City of Basel (Switzerland)

Feigenwinter

Vogt

Parlow

et al. 2018

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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Abstract-Urban surfaces are a complex mixture of different land covers and surface materials; the relative magnitudes of the surface energy balance components therefore vary widely across a city. Eddy covariance (EC) measurements provide the best estimates of turbulent heat fluxes but are restricted to the source area. Land surface modeling with earth observation (EO) data is beneficial for extrapolation of a larger area since citywide information is possible. Turbulent sensible and latent heat fluxes are calculated by a combination of micrometeorological approaches (the aerodynamic resistance method, ARM), EO data, and GIS techniques. Input data such as land cover fractions and surface temperatures are derived from Landsat 8 OLI and TIRS, urban morphology was calculated from high-resolution digital building models and GIS data layers, and meteorological data were provided by flux tower measurements. Twenty-two Landsat scenes covering all seasons and different meteorological conditions were analyzed. Sensible heat fluxes were highest for industrial areas, railway stations, and areas with high building density, mainly corresponding to the pixels with highest surface-to-air temperature differences. The spatial distribution of latent heat flux is strongly related to the saturation deficit of vapor and the (minimum) stomatal resistance of vegetation types. Seasonal variations are highly dependent on meteorological conditions, i.e., air temperature, water vapor saturation deficit, and wind speed. Comparison of measured fluxes with modeled fluxes in the weighted source area of the flux towers is moderately accurate due to known drawbacks in the modeling approach and uncertainties inherent to EC measurements, particularly in urban areas.

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Section: A Flux Calculationmentioning

confidence: 99%

Spatial Distribution of Sensible and Latent Heat Flux in the City of Basel (Switzerland)

Feigenwinter

Vogt

Parlow

et al. 2018

IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing

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“…However, radio soundings are usually only taken at specific times, wherefore these data do not allow studying the short term evolution of the atmosphere. A continuous monitoring of the atmosphere is possible with remote sensing systems such as lidars (Eichinger et al, 1993;Pahlow et al, 2005) and RASSsodars (Nadeau et al, 2009). Unfortunately, these systems can be limited in vertical resolution which makes it difficult to accurately detect very low MH, or they have other limitations due to eye safety or noise pollution (e.g.…”

Section: Introductionmentioning

confidence: 99%

Fiber optic distributed temperature sensing for the determination of the nocturnal atmospheric boundary layer height

et al. 2011

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Abstract.A new method for measuring air temperature profiles in the atmospheric boundary layer at high spatial and temporal resolution is presented. The measurements are based on Raman scattering distributed temperature sensing (DTS) with a fiber optic cable attached to a tethered balloon. These data were used to estimate the height of the stable nocturnal boundary layer. The experiment was successfully deployed during a two-day campaign in September 2009, providing evidence that DTS is well suited for this atmospheric application. Observed stable temperature profiles exhibit an exponential shape confirming similarity concepts of the temperature inversion close to the surface. The atmospheric mixing height (MH) was estimated to vary between 5 m and 50 m as a result of the nocturnal boundary layer evolution. This value is in good agreement with the MH derived from concurrent Radon-222 ( 222 Rn) measurements and in previous studies.

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“…2. For further technical details on measuring devices used, refer to the work of Nadeau et al [44] and Simoni et al [64].…”

Section: Distribute D Point and Catchment Analysismentioning

confidence: 99%

Improving the degree-day method for sub-daily melt simulations with physically-based diurnal variations

Tobin

Schaefli

Nicótina

et al. 2013

Advances in Water Resources

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Estimation of urban sensible heat flux using a dense wireless network of observations

Cited by 56 publications

References 53 publications

Spatial Distribution of Sensible and Latent Heat Flux in the City of Basel (Switzerland)

Spatial Distribution of Sensible and Latent Heat Flux in the City of Basel (Switzerland)

Fiber optic distributed temperature sensing for the determination of the nocturnal atmospheric boundary layer height

Improving the degree-day method for sub-daily melt simulations with physically-based diurnal variations

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