scholarly journals On the Brutsaert temperature roughness length model for sensible heat flux estimation

1997 ◽  
Vol 33 (10) ◽  
pp. 2315-2324 ◽  
Author(s):  
Anthony T. Cahill ◽  
Marc B. Parlange ◽  
John D. Albertson
Keyword(s):  
Heat Flux ◽  
Roughness Length ◽  
Sensible Heat Flux ◽  
Sensible Heat ◽  
Heat Flux Estimation ◽  
Flux Estimation

An improved model for sensible heat flux estimation based on landcover classification

2014 ◽  
Author(s):  
Ti Zhou ◽  
Xiaozhou Xin ◽  
Jingjun Jiao ◽  
Zhiqing Peng
Keyword(s):  
Heat Flux ◽  
Sensible Heat Flux ◽  
Sensible Heat ◽  
Heat Flux Estimation ◽  
Landcover Classification ◽  
Flux Estimation ◽  
Improved Model

scholarly journals Sensible Heat Flux Estimation over the FIFE Site by Neural Networks

1998 ◽  
Vol 55 (7) ◽  
pp. 1185-1197 ◽  
Author(s):  
Behzad Abareshi ◽  
Peter H. Schuepp
Keyword(s):  
Neural Networks ◽  
Heat Flux ◽  
Sensible Heat Flux ◽  
Sensible Heat ◽  
Heat Flux Estimation ◽  
Flux Estimation

scholarly journals Sensible heat flux estimation by flux variance and half-order time derivative methods

2001 ◽  
Vol 37 (9) ◽  
pp. 2333-2343 ◽  
Author(s):  
Karen H. Wesson ◽  
Gabriel Katul ◽  
Chun-Ta Lai
Keyword(s):  
Heat Flux ◽  
Time Derivative ◽  
Sensible Heat Flux ◽  
Sensible Heat ◽  
Heat Flux Estimation ◽  
Flux Estimation

scholarly journals Daytime sensible heat flux estimation over heterogeneous surfaces using multitemporal land-surface temperature observations

2016 ◽  
Vol 52 (5) ◽  
pp. 3457-3476 ◽  
Author(s):  
F. Castellví ◽  
C. Cammalleri ◽  
G. Ciraolo ◽  
A. Maltese ◽  
F. Rossi
Keyword(s):  
Heat Flux ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Sensible Heat Flux ◽  
Sensible Heat ◽  
Heterogeneous Surfaces ◽  
Heat Flux Estimation ◽  
Flux Estimation ◽  
Temperature Observations

scholarly journals A Bayesian analysis of sensible heat flux estimation: Quantifying uncertainty in meteorological forcing to improve model prediction

2013 ◽  
Vol 49 (5) ◽  
pp. 2343-2358 ◽  
Author(s):  
Ali Ershadi ◽  
Matthew F. McCabe ◽  
Jason P. Evans ◽  
Gregoire Mariethoz ◽  
Dmitri Kavetski
Keyword(s):  
Heat Flux ◽  
Bayesian Analysis ◽  
Model Prediction ◽  
Sensible Heat Flux ◽  
Sensible Heat ◽  
Meteorological Forcing ◽  
Heat Flux Estimation ◽  
Improve Model ◽  
Flux Estimation ◽  
Quantifying Uncertainty

scholarly journals Significant Decrease of Uncertainties in Sensible Heat Flux Simulation Using Temporally Variable Aerodynamic Roughness in Two Typical Forest Ecosystems of China

2012 ◽  
Vol 51 (6) ◽  
pp. 1099-1110 ◽  
Author(s):  
Yanlian Zhou ◽  
Weimin Ju ◽  
Xiaomin Sun ◽  
Xuefa Wen ◽  
Dexin Guan
Keyword(s):  
Heat Flux ◽  
Roughness Length ◽  
Aerodynamic Resistance ◽  
Sensible Heat Flux ◽  
Surface Fluxes ◽  
Sensible Heat ◽  
Atmospheric Stratification ◽  
Thermal Roughness Length ◽  
Aerodynamic Roughness ◽  
Simulation Errors

AbstractAerodynamic roughness length zom is an important parameter for reliably simulating surface fluxes. It varies with wind speed, atmospheric stratification, terrain, and other factors. However, it is usually considered a constant. It is known that uncertainties in zom result in latent heat flux (LE) simulation errors, since zom links LE with aerodynamic resistance. The effects of zom on sensible heat flux (SH) simulation are usually neglected because there is no direct link between the two. By comparing SH simulations with three types of zom inputs, it is found that allowing zom temporal variation in an SH simulation model significantly improves agreement between simulated and measured SH and also decreases the sensitivity of the SH model to the heat transfer coefficient Ct, which in turn determines the linkage between zom and thermal roughness length zoh.

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