An investigation of the effect of environmental factors on the budgets of heat, water vapor, and carbon dioxide within a tree

Modeling the balances of heat, water, vapor, and carbon dioxide within three-dimensional vegetation was tried. This model consists of three submodels: a model for turbulent flow within vegetation, a model for radiation transfer within vegetation, and a stomatal conductance model. This model was applied to a single tree. The numerical experiment resulted in the following : 1) A great deal of short wave radiation absorbed by leaves was released through transpiration. 2) The influence of long wave radiation on the energy balance within the tree was not negligible. 3) The sensible heat transfer due to water vapor flux from leaves hardly affected the energy balance within the tree. The fact indicates that the results from the turbulence model for dry air are almost equal to those of the turbulence model for moist air.

In the previous paper, we proposed a model for simulating the budgets of heat, water vapor, and carbon dioxide within three-dimensional vegetation. And we applied the model to a single tree and investigated the detail of heat balance within the foliage. Then we investigated the effect of the environmental factors on the heat budget within the foliage, by varying the environmental factors. In this paper, we examined the validity of our model. We compared the results from the model with the measured data. Our model accurately estimated the measured data.

A radiative transfer model for surface radiation budget studies

[1] A large-eddy simulation (LES) code is coupled with a land surface model to investigate the diurnal variation of the atmospheric boundary layer (ABL). The diurnal evolution of the ABL is driven by a time-varying incoming solar radiation. The results show that the domain average surface fluxes of sensible heat, water vapor, and carbon dioxide are smooth functions of time but the fluxes at any given surface grid point show random variations, especially the sensible heat flux. At the ABL top, the LES-resolved entrainment fluxes of these scalars also evolve with time and are not fixed fractions of their respective surface fluxes. Entrainment efficiency (the ratio of entrainment flux at zi to weδϕ, where zi is the ABL height, we is entrainment velocity, and δϕ is the jump of scalar across the entrainment zone) is highest for CO2 and lowest for sensible heat. The first-order jump condition model is very good approximation to simulated entrainment fluxes which are largely controlled by the vertical gradients of the scalars across the capping inversion. Our results suggest that over the range of geostrophic winds considered (0–5 m s−1), neither the surface nor the entrainment flux reveals sensitivity to the geostrophic wind speed variations.

A coupled model of leaf photosynthesis, stomatal conductance, and leaf energy balance for chrysanthemum (Dendranthema grandiflora)

Stomata play a central role in regulating the exchange of carbon and water vapor between ecosystems and the atmosphere. Their function is represented by land surface models (LSMs) by conductance models. The Functionally Assembled Terrestrial Ecosystem Simulator (FATES) is a dynamic vegetation demography model that can simulate both detailed plant demographic and ecophysiological dynamics. To evaluate the effect of stomatal conductance model representation on forest water and carbon fluxes in FATES, we implemented an optimality-based stomatal conductance model—the Medlyn (MED) model, that simulates the relationship between photosynthesis (A) and stomatal conductance to water vapor (gsw) as an alternative to the FATES default Ball-Woodrow-Berry (BWB) model. To evaluate how the behavior of FATES is affected by stomatal model choice, we conducted a model sensitivity analysis to explore the response of gsw to synthetic climate forcing variables including atmospheric CO2 concentration, air temperature, radiation, and vapor pressure deficit (VPD). We found that modeled gsw values varied greatly between the BWB and MED formulations due to the different default stomatal slope parameters (g1). After harmonizing g1 and holding the same stomatal intercept parameter (g0) for both model formulations, we found that the divergence in modeled gsw was limited to conditions when the VPD exceeded 1.5 kPa. We then evaluated model simulation results against measurements from a wet evergreen forest in Panama. Results showed that both the MED and BWB model formulations were able to capture the magnitude and diurnal change of measured gsw and A but underestimated both by about 30 % when the soil was predicted to be very dry. Our study suggests that the parameterization of stomatal conductance models and current model response to drought are the critical areas for improving model simulation of CO2 and water fluxes in tropical forests.

Stomata play a central role in regulating the exchange of carbon and water vapor between ecosystems and the atmosphere. Their function is represented by land surface models (LSMs) by conductance models. The Functionally Assembled Terrestrial Ecosystem Simulator (FATES) is a dynamic vegetation demography model that can simulate both detailed plant demographic and ecophysiological dynamics. To evaluate the effect of stomatal conductance model representation on forest water and carbon fluxes in FATES, we implemented an optimality-based stomatal conductance model—the Medlyn (MED) model, that simulates the relationship between photosynthesis (A) and stomatal conductance to water vapor (gsw) as an alternative to the FATES default Ball-Woodrow-Berry (BWB) model. To evaluate how the behavior of FATES is affected by stomatal model choice, we conducted a model sensitivity analysis to explore the response of gsw to synthetic climate forcing variables including atmospheric CO2 concentration, air temperature, radiation, and vapor pressure deficit (VPD). We found that modeled gsw values varied greatly between the BWB and MED formulations due to the different default stomatal slope parameters (g1). After harmonizing g1 and holding the same stomatal intercept parameter (g0) for both model formulations, we found that the divergence in modeled gsw was limited to conditions when the VPD exceeded 1.5 kPa. We then evaluated model simulation results against measurements from a wet evergreen forest in Panama. Results showed that both the MED and BWB model formulations were able to capture the magnitude and diurnal change of measured gsw and A but underestimated both by about 30 % when the soil was predicted to be very dry. Our study suggests that the parameterization of stomatal conductance models and current model response to drought are the critical areas for improving model simulation of CO2 and water fluxes in tropical forests.

Stomata play a central role in regulating the exchange of carbon and water vapor between ecosystems and the atmosphere. Their function is represented by land surface models (LSMs) by conductance models. The Functionally Assembled Terrestrial Ecosystem Simulator (FATES) is a dynamic vegetation demography model that can simulate both detailed plant demographic and ecophysiological dynamics. To evaluate the effect of stomatal conductance model representation on forest water and carbon fluxes in FATES, we implemented an optimality-based stomatal conductance model—the Medlyn (MED) model, that simulates the relationship between photosynthesis (A) and stomatal conductance to water vapor (gsw) as an alternative to the FATES default Ball-Woodrow-Berry (BWB) model. To evaluate how the behavior of FATES is affected by stomatal model choice, we conducted a model sensitivity analysis to explore the response of gsw to synthetic climate forcing variables including atmospheric CO2 concentration, air temperature, radiation, and vapor pressure deficit (VPD). We found that modeled gsw values varied greatly between the BWB and MED formulations due to the different default stomatal slope parameters (g1). After harmonizing g1 and holding the same stomatal intercept parameter (g0) for both model formulations, we found that the divergence in modeled gsw was limited to conditions when the VPD exceeded 1.5 kPa. We then evaluated model simulation results against measurements from a wet evergreen forest in Panama. Results showed that both the MED and BWB model formulations were able to capture the magnitude and diurnal change of measured gsw and A but underestimated both by about 30 % when the soil was predicted to be very dry. Our study suggests that the parameterization of stomatal conductance models and current model response to drought are the critical areas for improving model simulation of CO2 and water fluxes in tropical forests.

Stomata play a central role in regulating the exchange of carbon and water vapor between ecosystems and the atmosphere. Their function is represented by land surface models (LSMs) by conductance models. The Functionally Assembled Terrestrial Ecosystem Simulator (FATES) is a dynamic vegetation demography model that can simulate both detailed plant demographic and ecophysiological dynamics. To evaluate the effect of stomatal conductance model representation on forest water and carbon fluxes in FATES, we implemented an optimality-based stomatal conductance model—the Medlyn (MED) model, that simulates the relationship between photosynthesis (A) and stomatal conductance to water vapor (gsw) as an alternative to the FATES default Ball-Woodrow-Berry (BWB) model. To evaluate how the behavior of FATES is affected by stomatal model choice, we conducted a model sensitivity analysis to explore the response of gsw to synthetic climate forcing variables including atmospheric CO2 concentration, air temperature, radiation, and vapor pressure deficit (VPD). We found that modeled gsw values varied greatly between the BWB and MED formulations due to the different default stomatal slope parameters (g1). After harmonizing g1 and holding the same stomatal intercept parameter (g0) for both model formulations, we found that the divergence in modeled gsw was limited to conditions when the VPD exceeded 1.5 kPa. We then evaluated model simulation results against measurements from a wet evergreen forest in Panama. Results showed that both the MED and BWB model formulations were able to capture the magnitude and diurnal change of measured gsw and A but underestimated both by about 30 % when the soil was predicted to be very dry. Our study suggests that the parameterization of stomatal conductance models and current model response to drought are the critical areas for improving model simulation of CO2 and water fluxes in tropical forests.

Modeling stomatal conductance is a key element in predicting tree growth and water use at the stand scale. We compared three commonly used models of stomatal conductance, the Jarvis-Loustau, Ball-Berry and Leuning models, for their suitability for incorporating soil water stress into their formulation, and for their performance in modeling forest ecosystem fluxes. We optimized the parameters of each of the three models with sap flow and soil water content data. The optimized Ball-Berry model showed clear relationships with air temperature and soil water content, whereas the optimized Leuning and Jarvis-Loustau models only showed a relationship with soil water content. We conclude that use of relative humidity instead of vapor pressure deficit, as in the Ball-Berry model, is not suitable for modeling daily gas exchange in Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) in the Speulderbos forest near the village of Garderen, The Netherlands. Based on the calculated responses to soil water content, we linked a model of forest growth, FORGRO, with a model of soil water, SWIF, to obtain a forest water-balance model that satisfactorily simulated carbon and water (transpiration) fluxes and soil water contents in the Douglas-fir forest for 1995.

Towards operational atmospheric correction of airborne hyperspectral imaging spectroscopy: Algorithm evaluation, key parameter analysis, and machine learning emulators

Impact of leaf physiological characteristics on seasonal variation in CO 2, latent and sensible heat exchanges over a tree plantation

Computational fluid dynamics (CFD) models of a HighRiseTM hog building (HRHB) were developed to simulateair velocity and ammonia distribution within the building under minimum ventilation conditions. Because bothlaminar/transient and turbulent flow conditions exist in the building, two different flow simulations were used. Air velocityprofiles from both turbulent and laminar flow models indicated that some air moves from the lower to the upper level, whichaffects the distribution of ammonia in the pig space. The simulation results were compared to air velocities and ammoniaconcentrations measured within an experimental HRHB. The turbulent flow model more closely matched measured ammoniavalues at locations in the HRHB than the laminar flow model. Using the turbulent flow model, ammonia concentration in thepig space would be below 25 ppm, and the NH3 emission factor for the HRHB during winter (low ventilation) conditions wouldbe 4.6 kg pig1 yr1. Although limited by the representation of real building geometry and processes, the twodimensional CFDmodels allowed rapid simulation of airflow and species gradients in the HRHB.

The measurements from satellite microwave imaging and sounding channels are simultaneously utilized through a one-dimensional (1-D) variation method (1D-var) to retrieve the profiles of atmospheric temperature, water vapor and cloud water. Since the radiative transfer model in this 1D-var procedure includes scattering and emission from the earth's atmosphere, the retrieval can perform well under all weather conditions. The iterative procedure is optimized to minimize computational demands and to achieve better accuracy. At first, the profiles of temperature, water vapor, and cloud liquid water are derived using only the AMSU-A measurements at frequencies less than 60 GHz. The second step is to retrieve rain and ice water using the AMSU-B measurements at 89 and 150 GHz. Finally, all AMSU-A/B sounding channels at 50-60 and 183 GHz are utilized to further refine the profiles of temperature and water vapor while the profiles of cloud, rain, and ice water contents are constrained to those previously derived. It is shown that the radiative transfer model including multiple scattering from clouds and precipitation can significantly improve the accuracy for retrieving temperature, moisture and cloud water. In hurricane conditions, an emission-based radiative transfer model tends to produce unrealistic temperature anomalies throughout the atmosphere. With a scattering-based radiative transfer model, the derived temperature profiles agree well with those observed from aircraft dropsondes.

The Liebe and Rosenkranz atmospheric absorption models for dry air and water vapor below 100 GHz are refined based on an analysis of antenna temperature (TA) measurements taken by the Global Precipitation Measurement Microwave Imager (GMI) in the frequency range 10.7 to 89.0 GHz. The GMI TA measurements are compared to the TA predicted by a radiative transfer model (RTM), which incorporates both the atmospheric absorption model and a model for the emission and reflection from a rough‐ocean surface. The inputs for the RTM are the geophysical retrievals of wind speed, columnar water vapor, and columnar cloud liquid water obtained from the satellite radiometer WindSat. The Liebe and Rosenkranz absorption models are adjusted to achieve consistency with the RTM. The vapor continuum is decreased by 3% to 10%, depending on vapor. To accomplish this, the foreign‐broadening part is increased by 10%, and the self‐broadening part is decreased by about 40% at the higher frequencies. In addition, the strength of the water vapor line is increased by 1%, and the shape of the line at low frequencies is modified. The dry air absorption is increased, with the increase being a maximum of 20% at the 89 GHz, the highest frequency considered here. The nonresonant oxygen absorption is increased by about 6%. In addition to the RTM comparisons, our results are supported by a comparison between columnar water vapor retrievals from 12 satellite microwave radiometers and GPS‐retrieved water vapor values.