Sensible heat and latent heat flux estimates in a tall and dense forest canopy under unstable conditions

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 di...

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Bibliographic Details
Authors: Castellví Sentís, Francesc, Ali Buttar, Noman, Hu, Yongguang, Ikram, Kamran
Format: article
Status:Published version
Publication Date:2022
Country:España
Institution:Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Repository:Recercat. Dipósit de la Recerca de Catalunya
OAI Identifier:oai:recercat.cat:10459.1/83173
Online Access:https://doi.org/10.3390/atmos13020264
http://hdl.handle.net/10459.1/83173
Access Level:Open access
Keyword:Sensible heat flux
Latent heat flux
In situ sensing
Aspen forest
Boscos i silvicultura
Àlbers
Description
Summary: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%.