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- Author or Editor: Branislava Lalić x
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Abstract
The spatial distribution of the leaf-area density is a key parameter in describing the forest canopy characteristics, which has a strong impact on its radiation balance and the mass and energy exchange with the atmosphere as well. The objective of this short study is to define an empirical relation describing the vertical distribution of leaf-area density that can be used for an improved estimation of the turbulent transfer coefficient inside the forest as well as above it. To check the validity of the method proposed, the calculated values are compared with the observations using datasets from eight observational sites located in four different types of forest, covering a broad range of mean values of leaf-area indices between 2 and 18.
Abstract
The spatial distribution of the leaf-area density is a key parameter in describing the forest canopy characteristics, which has a strong impact on its radiation balance and the mass and energy exchange with the atmosphere as well. The objective of this short study is to define an empirical relation describing the vertical distribution of leaf-area density that can be used for an improved estimation of the turbulent transfer coefficient inside the forest as well as above it. To check the validity of the method proposed, the calculated values are compared with the observations using datasets from eight observational sites located in four different types of forest, covering a broad range of mean values of leaf-area indices between 2 and 18.
Abstract
The correct simulation of the sensible and latent heat fluxes from a non-plant-covered surface is very important in designing the surface scheme for modeling the processes in the land–air exchange. However, using different bare soil evaporation schemes in land surface parameterization, an error in partitioning the surface fluxes can be introduced.
In parameterization of evaporation from a non-plant-covered surface in resistance representation, the α and β approaches are commonly used in corresponding formulas where the α and β are functions of soil water content. The performance of different schemes within these approaches is briefly discussed. For that purpose six schemes, based on different dependence α or β on volumetric soil moisture content and its saturated value, are used.
The latent and sensible heat fluxes and the ground temperature outputs were obtained from the numerical tests using the foregoing schemes. The tests were based on time integrations by the bare soil parameterization scheme using real data. The datasets obtained over the experimental site in Rimski Šančevi, Yugoslavia, on chernozem soil were used.
The obtained values of the latent and sensible heat fluxes and the ground temperature were compared with the observed values. Finally, their variability was considered using a simple root-mean-square analysis.
Abstract
The correct simulation of the sensible and latent heat fluxes from a non-plant-covered surface is very important in designing the surface scheme for modeling the processes in the land–air exchange. However, using different bare soil evaporation schemes in land surface parameterization, an error in partitioning the surface fluxes can be introduced.
In parameterization of evaporation from a non-plant-covered surface in resistance representation, the α and β approaches are commonly used in corresponding formulas where the α and β are functions of soil water content. The performance of different schemes within these approaches is briefly discussed. For that purpose six schemes, based on different dependence α or β on volumetric soil moisture content and its saturated value, are used.
The latent and sensible heat fluxes and the ground temperature outputs were obtained from the numerical tests using the foregoing schemes. The tests were based on time integrations by the bare soil parameterization scheme using real data. The datasets obtained over the experimental site in Rimski Šančevi, Yugoslavia, on chernozem soil were used.
The obtained values of the latent and sensible heat fluxes and the ground temperature were compared with the observed values. Finally, their variability was considered using a simple root-mean-square analysis.
