Tropospheric Ozone Assessment Report: Assessment of global-scale model performance for global and regional ozone distributions, variability, and trends

Abstract

The goal of the Tropospheric Ozone Assessment Report (TOAR) is to provide the research community with an up-to-date scientific assessment of tropospheric ozone, from the surface to the tropopause. While a suite of observations provides significant information on the spatial and temporal distribution of tropospheric ozone, observational gaps make it necessary to use global atmospheric chemistry models to synthesize our understanding of the processes and variables that control tropospheric ozone abundance and its variability. Models facilitate the interpretation of the observations and allow us to make projections of future tropospheric ozone and trace gas distributions for different anthropogenic or natural perturbations. This paper assesses the skill of current-generation global atmospheric chemistry models in simulating the observed present-day tropospheric ozone distribution, variability, and trends. Drawing upon the results of recent international multi-model intercomparisons and using a range of model evaluation techniques, we demonstrate that global chemistry models are broadly skillful in capturing the spatio-temporal variations of tropospheric ozone over the seasonal cycle, for extreme pollution episodes, and changes over interannual to decadal periods. However, models are consistently biased high in the northern hemisphere and biased low in the southern hemisphere, throughout the depth of the troposphere, and are unable to replicate particular metrics that define the longer term trends in tropospheric ozone as derived from some background sites. When the models compare unfavorably against observations, we discuss the potential causes of model biases and propose directions for future developments, including improved evaluations that may be able to better diagnose the root cause of the model-observation disparity. Overall, model results should be approached critically, including determining whether the model performance is acceptable for the problem being addressed, whether biases can be tolerated or corrected, whether the model is appropriately constituted, and whether there is a way to satisfactorily quantify the uncertainty.

Key drivers of ozone change and its radiative forcing over the 21st century

“…However, there are systematic biases: RE is overestimated in the NH and underestimated in the SH, with significant biases in the subtropics. These RE biases are mostly consistent with the biases in tropospheric ozone in current climate models (Young et al, 2017), although the simulated annual global present-day tropospheric 10 column ozone (28.9 ± 1.5 DU) is within observed interannual variability of 28.1-34.1 DU . The fact that the biases are apparent in many climate models suggests a common deficiency, and emissions data have been proposed as a likely candidate Young et al, 2017).…”

“…The tropospheric ozone budget (production, loss, dry deposition, stratospheric input), 15 burden and lifetime for the CNTRL simulation (see Table 2 and Fig. S1) are within previous multi-model activities estimates Young et al, 2017). peak is found at high latitudes in the NH, driven by transport of relatively rich tropospheric ozone air from mid-latitudes coupled with only moderate ozone depletion in the NH stratosphere.…”

Sensitivity of Ozone Dry Deposition to Ecosystem‐Atmosphere Interactions: A Critical Appraisal of Observations and Simulations

“…We note that summertime surface O 3 in the AM4_LM4dd simulations are still biased high over populated regions of the eastern United States, western Europe, and eastern China, as in many other global models (Young et al, 2018). Since LM4.0 does not have systematic biases in V d,O3 over these regions during the growing season, we suggest that these surface O 3 biases may reflect some other uncertainties, such as in isoprene chemistry, chemical O 3 loss, regional O 3 precursor emissions, and difficulty in resolving O 3 vertical gradients (Fiore et al, 2014;Lin et al, 2017;Travis et al, 2016).…”

HTAP2 multi-model estimates of premature human mortality due to intercontinental transport of air pollution and emission sectors

“…We evaluate model performance for the 2010 baseline simulation for 11 TF HTAP2 models for O 3 and eight models for PM 2.5 (Table S1). For O 3 , we use ground level measurements from 2010 at 4655 sites globally, collected by the Tropospheric Ozone Assessment Report (TOAR) (Schultz et al, 2017;Young et al, 2018). The TOAR dataset identifies stations as urban, rural, and unclassified sites (Schultz et al, 2017).…”