The goal of the Tropospheric Ozone Assessment Report (TOAR) is to provide the research community ... more 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.
US background ozone (O3) includes O3 produced from anthropogenic O3 precursors emitted outside of... more US background ozone (O3) includes O3 produced from anthropogenic O3 precursors emitted outside of the USA, from global methane, and from any natural sources. Using a suite of sensitivity simulations in the GEOS-Chem global chemistry transport model, we estimate the influence from individual background sources versus US anthropogenic sources on total surface O3 over 10 continental US regions from 2004 to 2012. Evaluation with observations reveals model biases of +0–19 ppb in seasonal mean maximum daily 8 h average (MDA8) O3, highest in summer over the eastern USA. Simulated high-O3 events cluster too late in the season. We link these model biases to excessive regional O3 production (e.g., US anthropogenic, biogenic volatile organic compounds (BVOCs), and soil NOx emissions), or coincident missing sinks. On the 10 highest observed O3 days during summer (O3_top10obs_JJA), US anthropogenic emissions enhance O3 by 5–11 ppb and by less than 2 ppb in the eastern versus western USA. The O3 enhancement from BVOC emissions during summer is 1–7 ppb higher on O3_top10obs_JJA days than on average days, while intercontinental pollution is up to 2 ppb higher on average versus on O3_top10obs_JJA days. During the summers of 2004–2012, monthly regional mean US background O3 MDA8 levels vary by up to 15 ppb from year to year. Observed and simulated summertime total surface O3 levels on O3_top10obs_JJA days decline by 3 ppb (averaged over all regions) from 2004–2006 to 2010–2012, reflecting rising US background (+2 ppb) and declining US anthropogenic O3 emissions (−6 ppb) in the model. The model attributes interannual variability in US background O3 on O3_top10obs days to natural sources, not international pollution transport. We find that a 3-year averaging period is not long enough to eliminate interannual variability in background O3 on the highest observed O3 days.
The goal of the Tropospheric Ozone Assessment Report (TOAR) is to provide the research community ... more 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.
US background ozone (O3) includes O3 produced from anthropogenic O3 precursors emitted outside of... more US background ozone (O3) includes O3 produced from anthropogenic O3 precursors emitted outside of the USA, from global methane, and from any natural sources. Using a suite of sensitivity simulations in the GEOS-Chem global chemistry transport model, we estimate the influence from individual background sources versus US anthropogenic sources on total surface O3 over 10 continental US regions from 2004 to 2012. Evaluation with observations reveals model biases of +0–19 ppb in seasonal mean maximum daily 8 h average (MDA8) O3, highest in summer over the eastern USA. Simulated high-O3 events cluster too late in the season. We link these model biases to excessive regional O3 production (e.g., US anthropogenic, biogenic volatile organic compounds (BVOCs), and soil NOx emissions), or coincident missing sinks. On the 10 highest observed O3 days during summer (O3_top10obs_JJA), US anthropogenic emissions enhance O3 by 5–11 ppb and by less than 2 ppb in the eastern versus western USA. The O3 enhancement from BVOC emissions during summer is 1–7 ppb higher on O3_top10obs_JJA days than on average days, while intercontinental pollution is up to 2 ppb higher on average versus on O3_top10obs_JJA days. During the summers of 2004–2012, monthly regional mean US background O3 MDA8 levels vary by up to 15 ppb from year to year. Observed and simulated summertime total surface O3 levels on O3_top10obs_JJA days decline by 3 ppb (averaged over all regions) from 2004–2006 to 2010–2012, reflecting rising US background (+2 ppb) and declining US anthropogenic O3 emissions (−6 ppb) in the model. The model attributes interannual variability in US background O3 on O3_top10obs days to natural sources, not international pollution transport. We find that a 3-year averaging period is not long enough to eliminate interannual variability in background O3 on the highest observed O3 days.
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Papers by Jean Guo
global chemistry transport model, we estimate the influence from individual background sources versus US anthropogenic sources on total surface O3 over 10 continental US regions from 2004 to 2012. Evaluation with observations reveals model biases of +0–19 ppb in seasonal mean
maximum daily 8 h average (MDA8) O3, highest in summer over the eastern USA. Simulated high-O3 events cluster too late in the season. We link these model biases to excessive regional O3 production (e.g., US anthropogenic, biogenic volatile organic compounds (BVOCs), and soil NOx emissions), or coincident missing sinks. On the 10 highest observed O3 days during summer (O3_top10obs_JJA), US anthropogenic emissions enhance O3 by 5–11 ppb and by less than 2 ppb in the eastern versus western USA. The O3 enhancement from BVOC emissions during summer is 1–7 ppb higher on O3_top10obs_JJA days than on average
days, while intercontinental pollution is up to 2 ppb higher on average versus on O3_top10obs_JJA days. During the summers of 2004–2012, monthly regional mean US background O3 MDA8 levels vary by up to 15 ppb from year to year. Observed and simulated summertime total surface O3 levels on O3_top10obs_JJA days decline by 3 ppb (averaged over all
regions) from 2004–2006 to 2010–2012, reflecting rising US background (+2 ppb) and declining US anthropogenic O3 emissions (−6 ppb) in the model. The model attributes interannual variability in US background O3 on O3_top10obs days to natural sources, not international pollution transport. We find that a 3-year averaging period is not long enough
to eliminate interannual variability in background O3 on the highest observed O3 days.
global chemistry transport model, we estimate the influence from individual background sources versus US anthropogenic sources on total surface O3 over 10 continental US regions from 2004 to 2012. Evaluation with observations reveals model biases of +0–19 ppb in seasonal mean
maximum daily 8 h average (MDA8) O3, highest in summer over the eastern USA. Simulated high-O3 events cluster too late in the season. We link these model biases to excessive regional O3 production (e.g., US anthropogenic, biogenic volatile organic compounds (BVOCs), and soil NOx emissions), or coincident missing sinks. On the 10 highest observed O3 days during summer (O3_top10obs_JJA), US anthropogenic emissions enhance O3 by 5–11 ppb and by less than 2 ppb in the eastern versus western USA. The O3 enhancement from BVOC emissions during summer is 1–7 ppb higher on O3_top10obs_JJA days than on average
days, while intercontinental pollution is up to 2 ppb higher on average versus on O3_top10obs_JJA days. During the summers of 2004–2012, monthly regional mean US background O3 MDA8 levels vary by up to 15 ppb from year to year. Observed and simulated summertime total surface O3 levels on O3_top10obs_JJA days decline by 3 ppb (averaged over all
regions) from 2004–2006 to 2010–2012, reflecting rising US background (+2 ppb) and declining US anthropogenic O3 emissions (−6 ppb) in the model. The model attributes interannual variability in US background O3 on O3_top10obs days to natural sources, not international pollution transport. We find that a 3-year averaging period is not long enough
to eliminate interannual variability in background O3 on the highest observed O3 days.