Evaluation of ozone deposition models over a subalpine forest in Niwot Ridge, Colorado

In this study, we evaluated three conceptually similar ozone gas deposition models. These dry deposition models are frequently used with chemical transport models for calculations over large spatial domains. However, large scale applications of surface-atmosphere exchange of reactive gases require modeling results as accurate as possible to avoid nonlinear accumulation of errors in the spatially representative results. In this paper, model evaluation and comparison against measured data over a coniferous forest at Niwot Ridge AmeriFlux site (Colorado, USA) is carried out. At this site, no previous model calibration took place for any of the models, therefore, we can test and compare their performances under similar conditions as they would perform in a spatial application. Our results show systematic model errors in all the three cases, model performance varies with time of the day, and the errors show a pronounced seasonal pattern as well. The introduction of soil moisture content stress in the model improved model performance regarding the magnitude of fluxes, but the correlation between measured and modeled ozone deposition values remains low. Our results suggest that ozone dry deposition model results should be interpreted carefully in large scale applications, where the accuracy can vary with land cover sometimes are biased

Climate controls over ecosystem metabolism: insights from a fifteen-year inductive artificial neural network synthesis for a subalpine forest

Eddy covariance (EC) datasets have provided insight into climate determinants of net ecosystem productivity (NEP) and evapotranspiration (ET) in natural ecosystems for decades, but most EC studies were published in serial fashion such that one study's result became the following study's hypothesis. This approach reflects the hypothetico-deductive process by focusing on previously derived hypotheses. A synthesis of this type of sequential inference reiterates subjective biases and may amplify past assumptions about the role, and relative importance, of controls over ecosystem metabolism. Long-term EC datasets facilitate an alternative approach to synthesis: the use of inductive data-based analyses to re-examine past deductive studies of the same ecosystem. Here we examined the seasonal climate determinants of NEP and ET by analyzing a 15-year EC time-series from a subalpine forest using an ensemble of Artificial Neural Networks (ANNs) at the half-day (daytime/nighttime) time-step. We extracted relative rankings of climate drivers and driver-response relationships directly from the dataset with minimal a priori assumptions. The ANN analysis revealed temperature variables as primary climate drivers of NEP and daytime ET, when all seasons are considered, consistent with the assembly of past studies. New relations uncovered by the ANN approach include the role of soil moisture in driving daytime NEP during the snowmelt period, the nonlinear response of NEP to temperature across seasons, and the low relevance of summer rainfall for NEP or ET at the same daytime/nighttime time step. These new results offer a more complete perspective of climate-ecosystem interactions at this site than traditional deductive analyses alone

Evaluation of ozone deposition models over a subalpine forest in Niwot Ridge, Colorado

In this study, we evaluated three conceptually similar ozone gas deposition models. These dry deposition models are frequently used with chemical transport models for calculations over large spatial domains. However, large scale applications of surface-atmosphere exchange of reactive gases require modeling results as accurate as possible to avoid nonlinear accumulation of errors in the spatially representative results. In this paper, model evaluation and comparison against measured data over a coniferous forest at Niwot Ridge AmeriFlux site (Colorado, USA) is carried out. At this site, no previous model calibration took place for any of the models, therefore, we can test and compare their performances under similar conditions as they would perform in a spatial application. Our results show systematic model errors in all the three cases, model performance varies with time of the day, and the errors show a pronounced seasonal pattern as well. The introduction of soil moisture content stress in the model improved model performance regarding the magnitude of fluxes, but the correlation between measured and modeled ozone deposition values remains low. Our results suggest that ozone dry deposition model results should be interpreted carefully in large scale applications, where the accuracy can vary with land cover sometimes are biased

Controls over ozone deposition to a high elevation subalpine forest

Ecosystem level ozone (O3) fluxes during four different years were examined at a subalpine forest site in the Colorado Rocky Mountains. The local mountain-valley wind system and the proximity of the Denver Metropolitan area leads to high summertime ozone episodes on many afternoons. The timing between these episodes and the ecosystem processes controlling photosynthesis during the growing season plays a critical role in determining the amount of ozone deposition. Light and vapor pressure deficit (VPD) were the most dominant environmental drivers controlling the deposition of O3 at this site through their influence on stomatal conductance. 81% of the daytime O3 uptake was predicted to occur through the stomata. Stomatal uptake decreased at high VPD and temperatures leading to an overall decrease in O3 flux; however, we did observe a non-stomatal conductance for O3 that increased slightly with temperature before leveling off at higher values. During the growing season, O3 deposition fluxes were enhanced after midday precipitation events and continued at elevated levels throughout the following night, implying a role for surface wetness. From nighttime data, evidence for both the presence of water films on the needles and non-closure of the plant stomata were observed. During the winter (non-growing) season, the ozone deposition velocity showed a consistent dependency on the latent heat flux. Although the mechanism is unclear, it is apparent that precipitation events play a role here through their influence on latent heat flux. © 2009 Elsevier B.V. All rights reserved