Canopy Energy Balance Research Articles

Analyzing the impact of various factors on leaf surface temperature based on a new tree-scale canopy energy balance model

Trees are one of the effective ways to regulate the microclimate, while the environmental parameters influence their transpiration rate. These complex processes manifest at the macro scale through leaf surface temperature (LST). Therefore, the key to studying the influence of trees on the microclimate is to calculate the LST. In this paper, we propose a new tree-scale canopy energy balance (CEB) model related to tree canopy height based on the big-leaf model to calculate the LST and analyze the influence of various factors on both LST and each sub-term of CEB. The results indicate that air temperature and solar radiation have a greater effect on LST than relative humidity on it. When the total solar radiation flux remains constant, air parameters primarily affect the latent heat flux of trees through the vapor pressure deficit between leaves and the air. The transpiration rate of trees is influenced not only by air parameters, but also by stomatal resistance. Solar radiation can directly determine the magnitude of the net radiation flux in the CEB, while its influence on latent heat flux is insignificant. Under high solar radiation flux conditions, an increase in wind speed can mitigate the rise of LST.

CFD simulations of the tree effect on the outdoor microclimate by coupling the canopy energy balance model

Trees can effectively regulate the urban microclimate, while the change of microclimate conditions in turn affect the physiological state of trees. In this paper, CFD simulations are performed by coupling canopy energy balance (CEB) model to study the effects of trees on outdoor microclimate. The results show that the tree has different effects on outdoor microclimate under different wind speeds, air conditions, solar radiation and stomatal resistance. Increasing the wind speed will weaken the cooling effect of the tree. This weakening effect can extend to a distance of about 3.2 times of the tree canopy width behind the tree when the inflow air temperature is 30 °C. However, the influence range at high wind speeds is greater than that at low wind speeds. Air temperature and relative humidity have opposite effects on the sensible and latent heat fluxes of the tree, while they both have negligible effects on the net radiation flux. The humidification effect of the tree will be weakened as the relative humidity increases. Solar radiation has a greater effect on leaf surface temperature (LST) than on air temperature. The net radiation flux is high at the top and bottom of the tree and comparatively low at the central section, which is related to the vertical distribution of leaf area density (LAD). Trees can mitigate the effects of environmental changes on the LST by regulating stomatal resistance, and the reduction of stomatal resistance leads to a greater cooling effect.

Decoupling between ecosystem photosynthesis and transpiration: a last resort against overheating

Ecosystems are projected to face extreme high temperatures more frequently in the near future. Various biotic coping strategies exist to prevent heat stress. Controlled experiments have recently provided evidence for continued transpiration in woody plants during high air temperatures, even when photosynthesis is inhibited. Such a decoupling of photosynthesis and transpiration would represent an effective strategy (‘known as leaf or canopy cooling’) to prevent lethal leaf temperatures. At the ecosystem scale, continued transpiration might dampen the development and propagation of heat extremes despite further desiccating soils. However, at the ecosystem scale, evidence for the occurrence of this decoupling is still limited. Here, we aim to investigate this mechanism using eddy-covariance data of thirteen woody ecosystems located in Australia and a causal graph discovery algorithm. Working at half-hourly time resolution, we find evidence for a decoupling of photosynthesis and transpiration in four ecosystems which can be classified as Mediterranean woodlands. The decoupling occurred at air temperatures above 35 ∘C. At the nine other investigated woody sites, we found that vegetation CO2 exchange remained coupled to transpiration at the observed high air temperatures. Ecosystem characteristics suggest that the canopy energy balance plays a crucial role in determining the occurrence of a decoupling. Our results highlight the value of causal-inference approaches for the analysis of complex physiological processes. With regard to projected increasing temperatures and especially extreme events in future climates, further vegetation types might be pushed to threatening canopy temperatures. Our findings suggest that the coupling of leaf-level photosynthesis and stomatal conductance, common in land surface schemes, may need be re-examined when applied to high-temperature events.

Energy partitioning between plant canopy and soil, performance of the two-source energy balance model in a vineyard

Partitioning of evapotranspiration (ET) into soil water evaporation and transpiration allows separate assessment of soil and plant water, energy, and carbon exchange. Remote sensing-based models are ideally suited to monitor ET over large areas, but ET partitioning estimates vary widely. The objective of this study was to evaluate the two-source energy balance (TSEB) model for seasonal ET partitioning using total, soil, and vine canopy energy balance fluxes measured over a vineyard in the Negev desert in Israel. Energy fluxes were evaluated with the original TSEB and three adapted versions using (1) measured soil heat flux, (2) optimized plant transpiration parameterization, and (3) measured soil and vine temperatures instead of composite surface temperature as model inputs. Optimization of plant transpiration parameters revealed a model tendency to underestimate transpiration due to underestimation of available energy and potential transpiration. Adaptations included, among others, accounting for higher leaf radiation absorption expected in dense clumped canopies, which increases available energy, and increasing the Priestley-Taylor coefficient from 1.26 to 2, which increases potential transpiration. While the original TSEB gave reasonable total energy fluxes, the vine energy fluxes were greatly underestimated. Both soil heat flux and plant transpiration adaptations improved modeled vine energy fluxes throughout the season under both well-watered and water-stressed conditions. However, the performance of the TSEB version using measured soil and vine temperatures was inferior to applying the standard TSEB with composite temperature. While daily energy fluxes could be estimated with reasonable accuracy, sub-daily fluxes proved to be more challenging and merit further research. Finally, changes in ET partitioning with canopy development and in response to water stress could be detected quite well albeit it with an underestimation of the transpiration fraction of ET, which, on average, amounted to 39% using standard TSEB and 6% with optimized plant transpiration parameters.

Tree model with drag, transpiration, shading and deposition: Identification of cooling regimes and large-eddy simulation

Trees play an important role in the urban heat island effect and urban air quality due to their impact on the transfer of radiation, momentum, heat, moisture and pollution. However, the effects of trees are hard to quantify due to their complex interactions with urban surfaces and the turbulent atmosphere overhead. We present a complete tree model for large-eddy simulations (LES) that represents the effects of trees on drag, transpiration, shading and deposition at resolutions of O(1 m, 0.1 s) whilst minimising the number of model parameters. The tree model avoids the necessity to resolve the leaf temperature via a derivation of the Penman-Monteith equation and distinguishes between cooling via transpiration and shading. The latent heat flux is further broken down into radiative and advective components in order to better understand the mechanism behind transpirational cooling (e.g. the ‘oasis’ effect).The new tree model is investigated analytically to provide insight into tree cooling regimes, and is applied to field studies to contextualise the analysis. The combined cooling effect of trees due to transpiration and shading processes can be reduced to a four-dimensional parameter space. The net tree cooling (NTC) and tree cooling ratio (TCR) parameters are defined to enable a systematic categorisation of the thermal effect of a tree into five regimes: net heating, net reduction (shading dominated), net reduction (transpiration dominated), net cooling (shading dominated) and net cooling (transpiration dominated). Existing parameterisations for tree cooling are reviewed, illustrating their limitations and highlighting the need for complete models to determine tree cooling.The tree model is implemented into the LES model uDALES. The drag and canopy energy balance models are validated, and results are presented for domains that are 1) fully covered by trees; 2) partially covered by trees; and 3) have a single line of trees. These simulations provide physical insight into the effect of trees on the microclimate and provide evaluation data for future studies.

Canopy wetness in the Eastern Amazon

Canopy wetness is a common condition that influences photosynthesis, the leaching or uptake of solutes, the water status and energy balance of canopies, and the interpretation of eddy covariance and remote sensing data. While often treated as a binary variable, ‘wet’ or ‘dry’, forest canopies are often partially wet, requiring the use of a continuous description of wetness. Minor precipitation events such as dew, that wet a fraction of the canopy, have been found to contribute to dry season foliar water uptake in the Eastern Amazon, and are fundamentally important to the canopy energy balance. However, few studies have reported the spatial and temporal distribution of canopy wetness, or the relative contribution of dew to leaf wetness, for forest ecosystems.In this study, we use two canopy profiles of leaf wetness sensors, coupled with meteorological data, to address fundamental questions about spatial and temporal variation of leaf wetness in an Eastern Amazonian rainforest. We also investigate how well meteorological tower data can predict canopy wetness using two models, one empirical and one that is physically-based.The results show that the canopy is 100% dry only for 34% of the time, otherwise being between 5% and 100% wet. Dew accounts for 20% or 43% of total annual leaf wetness, and 36% or 50% of canopy wetness in dry season, excluding or including dew events that co-occur with rain, respectively. Wetness duration was higher at the top than bottom of the canopy, mainly because of rain events, whilst dew formation was strongly dependent on the local canopy structure and varied horizontally through the canopy. The best empirical model accounted for 55% of the variance in canopy wetness, while the physical model accounted for 48% of the variance. We discuss future modelling improvements of the physical model to increase its predictive capacity.

Tree transpiration in a multi-species Mediterranean garden

Urban trees provide benefits and services, like improving environmental quality and mitigating impacts of climate change on human health, e.g. through the reduction of greenhouse gases effects, the removal of pollutants from the atmosphere and the improvement of water quality through interception of pollution. Tree transpiration in a multi-species urban garden in southern Italy was investigated for one year, on hourly, daily, seasonal and annual time scale. Water status of trees was determined by means of the Crop Water Stress Index (CWSI). The difference between canopy and air temperature was calculated using transpiration measurements and the canopy energy balance. Transpiration was measured by heat dissipation method (HDM) in more than 14 tree species, grouped in four classes (Olea, Citrus and Eriobotrya, Conifers and Broadleaves) according to number of specimens in the garden and similarity in plant functional category. At single tree scale, the radial trend of sap flux density was modeled considering the sapwood area, while the upscaling to the garden level was performed using the quantile method integrated by trunk diameter classification. Complete daytime time series of sap flux density were obtained by gap filling algorithms, based on multivariate models based on environmental drivers of transpiration. Tree transpiration showed that Olea and Citrus and Eriobotrya had a good adaptation to Mediterranean climates. CWSI values indicated that Conifers suffered a moderate water shortage, while the other species were subjected to higher water shortage. Conifers showed the maximum efficacy in lowering air temperature, followed by Broadleaves, Olea and Citrus and Eriobotrya. The uncertainties were evaluated by error analysis.

The Impact of Biomass Heat Storage on the Canopy Energy Balance and Atmospheric Stability in the Community Land Model

AbstractAtmospheric models used for weather prediction and future climate projections rely on land models to calculate surface boundary conditions. Observations of near‐surface states and fluxes made at flux measurement sites provide valuable data with which to assess the quality of simulated lower boundary conditions. A previous assessment of the Community Land Model version 4.5 using data from the Niwot Ridge Subalpine Forest AmeriFlux tower showed that simulated latent heat fluxes could be improved by adjusting a parameter describing the maximum leaf wetted area, but biases in midday sensible heat flux and nighttime momentum flux were generally not reduced by model parameter perturbations. These biases are related to the model's lack of heat storage in vegetation biomass. A biomass heat capacity is parameterized in Community Land Model version 5 with measurable quantities such as canopy height, diameter at breast height, and tree number density. After implementing a parameterization describing the heat transfer between the forest biomass and the canopy air space, the biases in the mean midday sensible heat and mean nighttime momentum fluxes at Niwot Ridge are reduced from 47 to 13 W/m2 and from 0.12 to −0.03 m/s, respectively. The bias in the mean nighttime canopy air temperature was reduced from −5.9 to 0.4 °C. Additional simulations at other flux tower sites demonstrate a consistent reduction in midday sensible heat flux, a lower ratio of the sum of sensible and latent heat flux to net radiation, and an increase in nighttime canopy temperatures.

Assessing the interplay between canopy energy balance and photosynthesis with cellulose δ18O: large-scale patterns and independent ground-truthing

There are few whole-canopy or ecosystem scale assessments of the interplay between canopy temperature and photosynthesis across both spatial and temporal scales. The stable oxygen isotope ratio (δ18O) of plant cellulose can be used to resolve a photosynthesis-weighted estimate of canopy temperature, but the method requires independent confirmation. We compare isotope-resolved canopy temperatures derived from multi-year homogenization of tree cellulose δ18O to canopy-air temperatures weighted by gross primary productivity (GPP) at multiple sites, ranging from warm temperate to boreal and subalpine forests. We also perform a sensitivity analysis for isotope-resolved canopy temperatures that showed errors in plant source water δ18O lead to the largest errors in canopy temperature estimation. The relationship between isotope-resolved canopy temperatures and GPP-weighted air temperatures was highly significant across sites (p < 0.0001, R2 = 0.82), thus offering confirmation of the isotope approach. The previously observed temperature invariance from temperate to boreal biomes was confirmed, but the greater elevation of canopy temperature above air temperature in the boreal forest was not. Based on the current analysis, we conclude that canopy temperatures in the boreal forest are as warm as those in temperate systems because day-time-growing-season air temperatures are similarly warm.

Glacial Amazonia at the canopy-scale: Using a biophysical model to understand forest robustness

A canopy-scale model (CANOAK) was used to simulate lowland Amazonia during the Last Glacial Maximum. Modeled values of Net Ecosystem Exchange driven by glacial environmental conditions were roughly half the magnitude of modern fluxes. Factorial experiments reveal lowered [CO2] to be the primary cause of reduced carbon fluxes while lowered air temperatures enhance net carbon uptake. LGM temperatures are suggested to be closer to optimal for carbon uptake than modern temperatures, explained through the canopy energy balance. Further analysis of the canopy energy balance and resultant leaf temperature regime provide viable mechanisms to explain enhanced carbon-water relations at lowered temperatures and forest robustness over glaciations. An ecophysiological phenomena known as the ‘cross-over’ point, wherein leaf temperatures sink below air temperature, was reproduced and found to demarcate critical changes in energy balance partitioning.

Intensifying drought eliminates the expected benefits of elevated carbon dioxide for soybean.

Stimulation of C3 crop yield by rising concentrations of atmospheric carbon dioxide ([CO2]) is widely expected to counteract crop losses that are due to greater drought this century. But these expectations come from sparse field trials that have been biased towards mesic growth conditions. This eight-year study used precipitation manipulation and year-to-year variation in weather conditions at a unique open-air field facility to show that the stimulation of soybean yield by elevated [CO2] diminished to zero as drought intensified. Contrary to the prevalent expectation in the literature, rising [CO2] did not counteract the effect of strong drought on photosynthesis and yield because elevated [CO2] interacted with drought to modify stomatal function and canopy energy balance. This new insight from field experimentation under hot and dry conditions, which will become increasingly prevalent in the coming decades, highlights the likelihood of negative impacts from interacting global change factors on a key global commodity crop in its primary region of production.

Determining soil moisture and soil properties in vegetated areas by assimilating soil temperatures

AbstractThis study addresses two critical barriers to the use of Passive Distributed Temperature Sensing (DTS) for large‐scale, high‐resolution monitoring of soil moisture. In recent research, a particle batch smoother (PBS) was developed to assimilate sequences of temperature data at two depths into Hydrus‐1D to estimate soil moisture as well as soil thermal and hydraulic properties. However, this approach was limited to bare soil and assumed that the cable depths were perfectly known. In order for Passive DTS to be more broadly applicable as a soil hydrology research and remote sensing soil moisture product validation tool, it must be applicable in vegetated areas. To address this first limitation, the forward model (Hydrus‐1D) was improved through the inclusion of a canopy energy balance scheme. Synthetic tests were used to demonstrate that without the canopy energy balance scheme, the PBS estimated soil moisture could be even worse than the open loop case (no assimilation). When the improved Hydrus‐1D model was used as the forward model in the PBS, vegetation impacts on the soil heat and water transfer were well accounted for. This led to accurate and robust estimates of soil moisture and soil properties. The second limitation is that, cable depths can be highly uncertain in DTS installations. As Passive DTS uses the downward propagation of heat to extract moisture‐related variations in thermal properties, accurate estimates of cable depths are essential. Here synthetic tests were used to demonstrate that observation depths can be jointly estimated with other model states and parameters. The state and parameter results were only slightly poorer than those obtained when the cable depths were perfectly known. Finally, in situ temperature data from four soil profiles with different, but known, soil textures were used to test the proposed approach. Results show good agreement between the observed and estimated soil moisture, hydraulic properties, thermal properties, and observation depths at all locations. The proposed method resulted in soil moisture estimates in the top 10 cm with RMSE values typically &lt;0.04 . This demonstrates the potential of detecting the spatial variability of soil moisture and properties in vegetated areas from Passive DTS data.

Energy and evapotranspiration partitioning in a desert vineyard

The challenge of partitioning energy and evapotranspiration (ET) components was addressed over a season (bud break till harvest) in a wine grape vineyard located in an extreme arid region. A below canopy energy balance approach was applied to continuously estimate evaporation from the soil (E) while system ET was measured using eddy covariance. Below canopy energy balance was assessed at the dry midrow position as well as the wet irrigated position directly underneath the vine row, with E calculated as the residual of measured net radiation, soil heat flux, and computed sensible heat flux. The variables used to compute sensible heat flux included soil surface temperature measured using infrared thermometers and below-canopy wind speed in a soil resistance formulation that required a modified wind factor. The E derived from below canopy energy balance was reasonable at daily intervals although it underestimated micro-lysimeter E measurements, suggesting there may have been advected energy from the midrow to the below-vine position. Seasonal partitioning indicated that total E amounted to 9–11% of ET. In addition, empirical functions from the literature relating crop coefficients (Kcb) to plant size, appeared to give reasonable results under full canopy, albeit with some day to day variation, but underestimated Kcb during the growing period.

Development of an urban canopy model for the evaluation of urban thermal climate with snow cover in severe cold regions

Snow plays an important role in determining heat and moisture exchanges between the underlying surface and atmosphere in winter. However, the effect of snow cover is not considered or assumed to be negligible in existing urban canopy energy balance models. In this paper, a one-dimensional snow model that accounts for heat transfer within snow cover is developed, and the model is implemented into an urban canopy energy balance model to simulate energy and moisture exchanges in cold urban areas with stable snow cover. The numerical methods of the snow model and the urban canopy model are demonstrated first, and the urban canopy model is subsequently used to simulate the thermal climate of a residential area dynamically in Yichun, China during winter. The results indicate that the existence of snow cover decreases the outdoor air temperature by 0.15 °C on average and 1.16 °C at maximum. In addition, the outdoor mean SET* increases 0.43 °C with the removal of snow cover, indicating that the thermal comfort of people outside decreases due to the presence of snow cover.

Estimation of urban energy heat flux and anthropogenic heat discharge using aster image and meteorological data: case study in Beijing metropolitan area

In order to analyze the mechanism of the urban heat island, it is paramount and meaningful to estimate the anthropogenic heat flux in cities. A case study was carried out to study the energy balance process in Beijing, China, based on a canopy energy balance equation and to estimate the urban energy fluxes and anthropogenic heat discharge and their seasonal and spatial variations. Two ASTER images and meteorological observation data from the winter and summer seasons were used for the study. The results showed that: (1) in Beijing, the anthropogenic heat discharge flux reached a maximum of 163.76 W m −2 in winter and 288.26 W m −2 in summer. Spatially, the magnitude of the flux was significantly affected by urban land cover types. In winter, the highest value occurred at an urban commercial district with an average value of 47.60 W m −2 . In summer, the highest value occurred at the airport and the industrial areas with the regional average reaching 47.29 W m −2 ; the spatial pattern of the heat discharge appears to be clustered, with some, localized high-accumulation centers such as in industrial areas and commercial districts. (2) The anthropogenic discharge was one of the important contributors to the surface-atmosphere energy exchange in cities. The heat discharge had a positive effect on elevating the surface temperature and formation of the urban heat island, especially in the summer. The study confirms the importance to account for the impact of the anthropogenic heat flux on urban energy budget.

Modeling energy and carbon fluxes in a heterogeneous oak woodland: A three-dimensional approach

Most land surface and ecosystem models assume that a vegetated canopy can be abstracted as a turbid medium when such models compute mass, energy, and carbon exchange. However, those models fail to simulate radiation environments in heterogeneous landscapes. This study aims to couple a spatially explicit three-dimensional (3D) shortwave and longwave radiative transfer model with a soil and canopy energy balance and canopy physiology model (CANOAK-FLiES), to investigate how well the 3D model performs in a heterogeneous landscape compared to a 1D model. The canopy structural parameters were extracted using airborne-based Light Detection and Ranging (LiDAR) data and digital cover photographs. The developed model was compared with a wide variety of field and remote sensing data (e.g., hyper-spectral remote sensing images, overstory and understory radiation, and tower-based energy and CO 2 fluxes) in a woody oak savanna in CA, USA. Overall, the simulated spatial and diurnal patterns of the radiation environment were consistent with the measurements of shortwave and longwave wavebands. The 3D approach worked better than the 1D approach from the wet mild spring to the dry hot summer while the relative importance of using the 3D approach depends on climate and canopy physiological conditions as well as the canopy structure. With low leaf area index in the oak woodland, the woody elements absorbed 12%–39% of the PAR and 20%–52% of the NIR radiation. Consequently, 12% of the daytime energy flux was used as woody heat storage at our study site. This novel 3D model has the potential to serve as a useful tool for analyzing the spatio-temporal variability of radiation and energy fluxes in evaluating footprints of radiation sensors and eddy covariance fluxes, and serve as a standard in evaluating the performance of a hierarchy of simpler land surface models to compute mass and energy exchange of heterogeneous landscapes.

The community Noah land surface model with multiparameterization options (Noah-MP): 1. Model description and evaluation with local-scale measurements

[1] This first paper of the two‐part series describes the objectives of the community efforts in improving the Noah land surface model (LSM), documents, through mathematical formulations, the augmented conceptual realism in biophysical and hydrological processes, and introduces a framework for multiple options to parameterize selected processes (Noah‐MP). The Noah‐MP’s performance is evaluated at various local sites using high temporal frequency data sets, and results show the advantages of using multiple optional schemes to interpret the differences in modeling simulations. The second paper focuses on ensemble evaluations with long‐term regional (basin) and global scale data sets. The enhanced conceptual realism includes (1) the vegetation canopy energy balance, (2) the layered snowpack, (3) frozen soil and infiltration, (4) soil moisture‐groundwater interaction and related runoff production, and (5) vegetation phenology. Sample local‐scale validations are conducted over the First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE) site, the W3 catchment of Sleepers River, Vermont, and a French snow observation site. Noah‐MP shows apparent improvements in reproducing surface fluxes, skin temperature over dry periods, snow water equivalent (SWE), snow depth, and runoff over Noah LSM version 3.0. Noah‐MP improves the SWE simulations due to more accurate simulations of the diurnal variations of the snow skin temperature, which is critical for computing available energy for melting. Noah‐MP also improves the simulation of runoff peaks and timing by introducing a more permeable frozen soil and more accurate simulation of snowmelt. We also demonstrate that Noah‐MP is an effective research tool by which modeling results for a given process can be interpreted through multiple optional parameterization schemes in the same model framework.

Modeling Runoff Generation in a Small Snow‐Dominated Mountainous Catchment

Snowmelt in mountainous areas is an important contributor to river water flows in the western United States. We developed a distributed model that calculates solar radiation, canopy energy balance, surface energy balance, snow pack dynamics, soil water flow, snow–soil–bedrock heat exchange, soil water freezing, and lateral surface and subsurface water flow. The model was applied to describe runoff generation in a subcatchment of the Dry Creek Experimental Watershed near Boise, ID. Calibration was achieved by optimizing the soil water field capacity (a trigger for lateral subsurface flow), lateral saturated soil hydraulic conductivity, and vertical saturated hydraulic conductivity of the bedrock. Validation results show that the model can successfully calculate snow dynamics, soil water content, and soil temperature. Modeled streamflow for the validation period was underestimated by 53%. The timing of the streamflow was captured reasonably well (modeling efficiency was 0.48 for the validation period). The model calculations suggest that 50 to 53% of the yearly incoming precipitation in the subcatchment is consumed by evapotranspiration. The model results further suggest that 34 to 36% of the incoming precipitation is transformed into deep percolation into the bedrock, while only 11 to 16% is transformed into streamflow.

Field experiments using CO2 enrichment: a comparison of two main methods

The dramatic increase in global atmospheric carbon dioxide over the past century is hypothesized to have significant impacts on the earth system. To understand the effects of elevated CO2 on terrestrial ecosystems, two main methods have been used to simulate an increase of CO2 in a semi-controlled field setting: 1) Open Top Chambers (OTC); and 2) Free Air CO2 Enrichment (FACE). The OTC method has been applied to study the components of forest ecosystems at small scale by manipulating seedlings or isolated juvenile trees, but is not able to address ecosystem processes as a whole. For technical reasons, OTC cannot be used to consider scaling issues, interaction with the boundary layer, and competition among species. To address these issues FACE technology was developed. FACE enables longer-term studies in larger plots, and allows studies of plant processes such as leaf area and canopy development, canopy energy balance and canopy gas exchange. In this review, I synthesize results from literature, in particular from meta-analysis techniques applied either to OTC or FACE. The results are qualitatively similar: CO2 enrichment leads to reduced stomatal conductance and leaf nitrogen, and enhanced photosynthesis and production. However, photosynthesis and crop yield were lower in FACE experiments than OTC, while starch content was higher. These results provide support for ecosystem model simulations, and help fill the gap between individual plants, forest and regional ecosystem. Neither OTC nor FACE can provide a clear indication of the regional-scale feedbacks between atmosphere and vegetation that might be expected under elevated CO2. To address this issue, further research is needed.

Modeling the Water and Energy Balance of Vegetated Areas with Snow Accumulation

The ability to quantify soil–atmosphere water and energy exchange is important in understanding agricultural and natural ecosystems, as well as the earth's climate. We developed a one‐dimensional vertical model that calculates solar radiation, canopy energy balance, surface energy balance, snowpack dynamics, soil water flow, and snow–soil–bedrock heat exchange, including soil water freezing. The processes are loosely coupled (solved sequentially) to limit the computational burden. The model was applied to describe water and energy dynamics for a northeast‐facing mountain slope in the Dry Creek Experimental Watershed near Boise, ID. Calibration was achieved by optimizing the saturated soil hydraulic conductivity. Validation results showed that the model can successfully calculate seasonal dynamics in snow height, soil water content, and soil temperature. Both the calibration and validation years confirmed earlier results that evapotranspiration on the northeast‐facing slope consumes approximately 60% of yearly precipitation, while deep percolation from the soil profile constitutes about 40% of yearly precipitation.