Editorial Type:
Article
Article Type:
Research Article

Comparison of Four Different Stomatal Resistance Schemes Using FIFE Data. Part II: Analysis of Terrestrial Biospheric–Atmospheric Interactions

Devdutta S. Niyogi State Climate Office of North Carolina and Department of Marine, Earth, and Atmospheric Sciences, North Carolina State University, Raleigh, North Carolina

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Sethu Raman State Climate Office of North Carolina and Department of Marine, Earth, and Atmospheric Sciences, North Carolina State University, Raleigh, North Carolina

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Kiran Alapaty State Climate Office of North Carolina and Department of Marine, Earth, and Atmospheric Sciences, North Carolina State University, Raleigh, North Carolina

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Print Publication:
01 Oct 1998
DOI:
https://doi.org/10.1175/1520-0450(1998)037<1301:COFDSR>2.0.CO;2
Page(s):
1301–1320
Restricted access

Abstract

Stomatal resistance (Rs) forms a pivotal component of the surface energy budget and of the terrestrial biosphere–atmosphere interactions. Using a statistical–graphical technique, the Rs-related interactions between different atmospheric and physiological variables are resolved explicitly from observations made during the First ISLSCP (International Satellite Land Surface Climatology Project) Field Experiment (FIFE). A similar analysis was undertaken for the Rs parameterization schemes, as used in the present models. Three physiological schemes (the Ball–Woodrow–Berry, Kim and Verma, and Jacobs) and one operational Jarvis-type scheme were evaluated in terms of their ability to replicate the terrestrial biosphere–atmosphere interactions.

It was found that all of the Rs parameterization schemes have similar qualitative behavior for routine meteorological applications (without carbon assimilation). Compared to the observations, there was no significant difference found in employing either the relative humidity or the vapor pressure deficit as the humidity descriptor in the analysis. Overall, the relative humidity–based interactions were more linear than the vapor pressure deficit and hence could be considered more convenient in the scaling exercises. It was found that with high photosynthesis rates, all of the schemes had similar behavior. It was found with low assimilation rates, however, that the discrepancies and nonlinearity in the interactions, as well as the uncertainties, were exaggerated.

Introduction of CO2 into the analysis created a different dimension to the problem. It was found that for CO2-based studies, the outcome had high uncertainty, as the interactions were nonlinear and the schemes could not converge onto a single interpretive scenario. This study highlights the secondary or indirect effects, and the interactions are crucial prior to evaluation of the climate and terrestrial biosphere–related changes even in the boundary layer perspective. Overall, it was found that direct and indirect effects could lead the system convergence toward different scenarios and have to be explicitly considered for atmospheric applications at all scales.

Corresponding author address: Dr. Sethu Raman, Dept. of Marine, Earth, and Atmospheric Sciences, North Carolina State University, Box 8208, Raleigh, NC 27695-8208.

Abstract

Stomatal resistance (Rs) forms a pivotal component of the surface energy budget and of the terrestrial biosphere–atmosphere interactions. Using a statistical–graphical technique, the Rs-related interactions between different atmospheric and physiological variables are resolved explicitly from observations made during the First ISLSCP (International Satellite Land Surface Climatology Project) Field Experiment (FIFE). A similar analysis was undertaken for the Rs parameterization schemes, as used in the present models. Three physiological schemes (the Ball–Woodrow–Berry, Kim and Verma, and Jacobs) and one operational Jarvis-type scheme were evaluated in terms of their ability to replicate the terrestrial biosphere–atmosphere interactions.

It was found that all of the Rs parameterization schemes have similar qualitative behavior for routine meteorological applications (without carbon assimilation). Compared to the observations, there was no significant difference found in employing either the relative humidity or the vapor pressure deficit as the humidity descriptor in the analysis. Overall, the relative humidity–based interactions were more linear than the vapor pressure deficit and hence could be considered more convenient in the scaling exercises. It was found that with high photosynthesis rates, all of the schemes had similar behavior. It was found with low assimilation rates, however, that the discrepancies and nonlinearity in the interactions, as well as the uncertainties, were exaggerated.

Introduction of CO2 into the analysis created a different dimension to the problem. It was found that for CO2-based studies, the outcome had high uncertainty, as the interactions were nonlinear and the schemes could not converge onto a single interpretive scenario. This study highlights the secondary or indirect effects, and the interactions are crucial prior to evaluation of the climate and terrestrial biosphere–related changes even in the boundary layer perspective. Overall, it was found that direct and indirect effects could lead the system convergence toward different scenarios and have to be explicitly considered for atmospheric applications at all scales.

Corresponding author address: Dr. Sethu Raman, Dept. of Marine, Earth, and Atmospheric Sciences, North Carolina State University, Box 8208, Raleigh, NC 27695-8208.

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Journal of Applied Meteorology and Climatology

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