Surface ozone (O3) pollution poses significant threats to crop production and food security worldwide, but an assessment of present-day and future crop yield losses due to exposure to O3 still abides with great uncertainties, mostly due: (1) to the large spatiotemporal variability and uncertain future projections of O3 concentration itself; (2) different methodological approaches to quantify O3 exposure and impacts; (3) difficulty in accounting for co-varying factors such as CO2 concentration and climatic conditions. In this paper, we explore these issues using a common framework: a consistent set of simulated present-day O3 fields from one chemical transport model, coupled with a terrestrial ecosystem-crop model to derive various O3 exposure metrics and impacts on relative crop yields worldwide, and examine the potential effects of elevated CO2 on O3-induced crop yield losses. Throughout, we review and explain the differences in formulation and parameterization in the various approaches, including the concentration-based metrics, flux-based metrics, and mechanistic biophysical crop modeling. We find that while the spatial pattern of yield losses for a given crop is generally consistent across metrics, the magnitudes can differ substantially. Pooling the concentration-based and flux-based metrics together, we estimate the present-day globally aggregated yield losses to be: 3.6 ± 1.1% for maize, 2.6 ± 0.8% for rice, 6.7 ± 4.1% for soybean, and 7.2 ± 7.3% for wheat; these estimates are generally consistent with previous studies but on the lower end of the uncertainty range covered. We attribute the large combined uncertainty mostly to the differences among methodological approaches, and secondarily to differences in O3 and meteorological inputs. Based on a biophysical crop model that mechanistically simulates photosynthetic and yield responses of crops to stomatal O3 uptake, we further estimate that increasing CO2 concentration from 390 to 600 ppm reduces the globally aggregated O3-induced yield loss by 21–52% for maize and by 27–38% for soybean, reflecting a CO2-induced reduction in stomatal conductance that in turn alleviates stomatal O3 uptake and thus crop damage. Rising CO2 may therefore render the currently used exposure-yield relationships less applicable in a future atmosphere, and we suggest approaches to address such issues.

Abstract. Dry deposition is a key process for surface ozone (O3) removal. Stomatal uptake is a major component of O3 dry deposition, which is parameterized differently in current land surface models and chemical transport models. We developed and used a standalone terrestrial biosphere model, driven by a unified set of prescribed meteorology, to evaluate two widely used dry deposition modeling frameworks, Wesely (1989) and Zhang et al. (2003), with different configurations of stomatal resistance: (1) the default multiplicative method in the Wesely scheme (W89) and Zhang et al. (2003) scheme (Z03), (2) the traditional photosynthesis-based Farquhar–Ball–Berry (FBB) stomatal algorithm, and (3) the Medlyn stomatal algorithm (MED) based on optimization theory. We found that using the FBB stomatal approach that captures ecophysiological responses to environmental factors, especially to water stress, can generally improve the simulated dry deposition velocities compared with multiplicative schemes. The MED stomatal approach produces higher stomatal conductance than FBB and is likely to overestimate dry deposition velocities for major vegetation types, but its performance is greatly improved when spatially varying slope parameters based on annual mean precipitation are used. Large discrepancies were also found in stomatal responses to rising CO2 levels from 390 to 550 ppm: the multiplicative stomatal method with an empirical CO2 response function produces reduction (−35 %) in global stomatal conductance on average much larger than that with the photosynthesis-based stomatal method (−14 %–19 %). Our results show the potential biases in O3 sink caused by errors in model structure especially in the Wesely dry deposition scheme and the importance of using photosynthesis-based representation of stomatal resistance in dry deposition schemes under a changing climate and rising CO2 concentration.

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Abstract. The newly developed offline land ecosystem model Terrestrial Ecosystem Model in R (TEMIR) version 1.0 is described here. This version of the model simulates plant ecophysiological (e.g., photosynthetic, stomatal) responses to varying meteorological conditions and concentrations of CO2 and ground-level ozone (O3) based on prescribed meteorological and atmospheric chemical inputs from various sources. Driven by the same meteorological data used in the GEOS-Chem chemical transport model, this allows asynchronously coupled experiments with GEOS-Chem simulations with unique coherency for investigating biosphere-atmosphere chemical interactions. TEMIR agrees well with FLUXNET site-level gross primary productivity (GPP) in terms of both the diurnal and monthly cycles (correlation coefficients R2 > 0.85 and R2 > 0.8, respectively) for most plant functional types (PFTs). Grass and shrub PFTs have larger biases due to generic model representations. The model performs best when driven by local site-level meteorology rather than reanalyzed gridded meteorology. Simulation using gridded meteorology agrees well for annual GPP in seasonality and spatial distribution with a global average of 134 Pg C yr–1. Application of Monin-Obukhov similarity theory to infer canopy conditions from gridded meteorology does not improve model performance, predicting a uniform increase of +21 % for global GPP. Present-day O3 concentrations simulated by GEOS-Chem and an O3 damage scheme at high sensitivity show a 2 % reduction in global GPP with prominent reductions by up to 15 % in eastern China and the eastern US. Regional correlations are generally unchanged when O3 is present, and biases are reduced especially for regions with high O3 damages. An increase in atmospheric CO2 concentration by 20 ppmv from year-2000 to year-2010 level modestly decreases O3 damage due to reduced stomatal uptake, consistent with ecophysiological understanding. Our work showcases the utility of this version of TEMIR for evaluating biogeophysical responses of vegetation to changes in atmospheric composition and meteorological conditions.

Abstract. Dry deposition is a key process for surface ozone (O3) removal. Stomatal resistance is a major component of O3 dry deposition, which is parameterized differently in current land surface models and chemical transport models. We developed and used a standalone terrestrial biosphere model, driven by a unified set of prescribed meteorology, to evaluate two widely used dry deposition modeling frameworks, Wesely (1989) and Zhang et al. (2003), with different configurations of stomatal resistance: 1) the default multiplicative method in each deposition scheme; 2) the traditional photosynthesis-based Farquhar-Ball-Berry (FBB) stomatal algorithm; 3) the Medlyn stomatal algorithm based on an optimization theory. We found that using the FBB stomatal approach that captures ecophysiological responses to environmental factors, especially to water stress, can generally improve the simulated dry deposition velocities compared with multiplicative schemes. The Medlyn stomatal approach produces higher stomatal conductance (reverse of stomatal resistance) than FBB and is likely to overestimate dry deposition velocities for major vegetation types, but its performance is greatly improved when spatially varying slope parameters based on annual mean precipitation are used. Large discrepancies were also found in simulated stomatal responses to rising CO2 levels, and that multiplicative stomatal method with an empirical CO2 response function produces reduction (−35 %) in global stomatal conductance, which is much larger than that with photosynthesis-based stomatal method (−14–19 %) when atmospheric CO2 level increases from 390 ppm to 550 ppm. Our results show the potential biases in O3 sink caused by errors in model structure especially in the Wesely dry deposition scheme, and the importance of using photosynthesis-based representation of stomatal resistance in dry deposition schemes under a changing climate and rising CO2 concentration.

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In this study, we use four long-term measurement sites with hourly observations:(1) The Harvard Forest Environmental Measurement Site (referred to as Harvard Forest) located in central Massachusetts.We use a O3 EC flux dataset together with ambient O3 concentrations (Munger and Wofsy, 1999) from year 1992 to 2006 to derive vd. Observed ozone flux data was measured at a height of 29m at the EMS site since 1991 (dataset id: HF004). We use air density at 25ºC and 1010hPa to compute vd when temperature measurements are missing. Observed hourly vd values are removed if they are: (a) from days with more than 30% of missing hourly measurements are removed; (b) not fall within mean ± 3 standard deviations.(2) The Borden Forest Research Station (referred to as Borden Forest) is located in southern Ontario, Canada. We use a database of hourly vd from year 2008 to 2013 (Wu et al., 2016). Gs was computed using flux data from FLUXNET-Canada Dataset (TEAM, 2016). vd values were derived with a modified gradient method (MGM) which have been proved to agree well with eddy covariance measurements. Negative vd values and the same portion of positive vd values with highest ranking were removed.(3) The Blodgett Ameriflux site (referred to as Blodgett Forest) is located near Georgetown, California, US. The site is dominated by ponderosa pine, characterized by a Mediterranean climate. We use the dataset from Fare et al. ( 2010), which includes observed vd and Gs from year 2001 to 2007.(4) The SMEAR II field measurement station (System for Measuring Forest Ecosystem-Atmosphere Relationships II) is located in Hyytiälä Forest, southern Finland. We use quality-checked hourly O3 flux and concentrations for Hyytiälä Forest from year 2007 to 2010. The height of trees near measurement tower was about 14-18m from 2000 to 2010. We use O3 concentrations averaged from measurements at height 33.6m and 16.8m.

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