The role of stomata in regulating photosynthesis and transpiration, and hence governing global biogeochemical cycles and climate, is well-known. Less well-understood, however, is the importance of stomatal control to the exchange of other trace gases between terrestrial vegetation and the atmosphere. Yet these gases determine atmospheric composition, and hence air quality and climate, on scales ranging from local to global, and seconds to decades. Vegetation is a major sink for ground-level ozone via the process of dry deposition and the primary source of many biogenic volatile organic compounds (BVOCs). The rate of dry deposition is largely controlled by the rate of diffusion of a gas through the stomata, and this also governs the emission rate of some key BVOCs. It is critical therefore that canopy-atmosphere exchange models capture the physiological processes controlling stomatal conductance and the transfer of trace gases other than carbon dioxide and water vapor. We incorporate three of the most widely used coupled stomatal conductance-photosynthesis models into the one-dimensional multi-layer FORest Canopy-Atmosphere Transfer (FORCAsT1.0) model to assess the importance of choice of parameterization on simulated ozone deposition rates. Modeled GPP and stomatal conductance across a broad range of ecosystems differ by up to a factor of two between the best and worst performing model configurations. This leads to divergences in seasonal and diel profiles of ozone deposition velocity of up to 30% and deposition rate of up to 13%, demonstrating that the choice of stomatal conductance parameterization is critical in accurate quantification of ozone deposition.

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FORCAST-gs：气孔导度参数化对估计臭氧沉积速度的重要性

众所周知，气孔在调节光合作用和蒸腾作用，从而控制全球生物地球化学循环和气候方面的作用。然而，不太清楚的是气孔控制对于陆地植被和大气之间其他痕量气体交换的重要性。然而，这些气体决定了大气成分，从而决定了空气质量和气候，范围从局部到全球，从几秒钟到几十年不等。植被是通过干沉降过程吸收地面臭氧的主要汇，也是许多生物挥发性有机化合物 (BVOC) 的主要来源。干沉积速率主要由气体通过气孔的扩散速率控制，这也控制着一些关键 BVOC 的排放速率。因此，冠层-大气交换模型捕获控制气孔导度和除二氧化碳和水蒸气以外的痕量气体转移的生理过程至关重要。我们将三个最广泛使用的耦合气孔导度-光合作用模型合并到一维多层森林冠层-大气转移 (FORCAsT1.0) 模型中，以评估参数化选择对模拟臭氧沉积率的重要性。跨广泛生态系统的建模 GPP 和气孔导度在性能最佳和最差的模型配置之间差异高达两倍。这导致臭氧沉积速度高达 30% 和沉积率高达 13% 的季节性和昼夜剖面差异，