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Measurements of carbon-14-containing carbon monoxide (14CO) in glacial ice are useful for studies of the past oxidative capacity of the atmosphere as well as for reconstructing the past cosmic ray flux. The 14CO abundance in glacial ice represents the combination of trapped atmospheric 14CO and in situ cosmogenic 14CO. The systematics of in situ cosmogenic 14CO production and retention in ice are not fully quantified, posing an obstacle to interpretation of ice core 14CO measurements. Here we provide the first comprehensive characterization of 14CO at an ice accumulation site (Summit, Greenland), including measurements in the ice grains of the firn matrix, firn air and bubbly ice below the firn zone. The results are interpreted with the aid of a firn gas transport model into which we implemented in situ cosmogenic 14C. We find that almost all (≈ 99.5 %) of in situ 14CO that is produced in the ice grains in firn is very rapidly (in <1 year) lost to the open porosity and from there mostly vented to the atmosphere. The timescale of this rapid loss is consistent with what is expected from gas diffusion through ice. The small fraction of in situ 14CO that initially stays in the ice grains continues to slowly leak out to the open porosity at a rate of ≈ 0.6 % yr−1. Below the firn zone we observe an increase in 14CO content with depth that is due to in situ 14CO production by deep-penetrating muons, confirming recent estimates of 14CO production rates in ice via the muon mechanisms and allowing for narrowing constraints on these production rates.

Despite significant precursor emission reductions in the US over recent decades, atmospheric nitrate deposition remains an important terrestrial stressor. Here, we utilized statistical air mass back trajectory analysis and nitrogen stable isotope deltas (δ(15N)) to investigate atmospheric nitrate spatiotemporal trends in the northeastern US from samples collected at three US EPA Clean Air Status and Trends Network (CASTNET) sites from December 2016–2018. For the considered sites, similar seasonal patterns in nitric acid (HNO3) and particulate nitrate (pNO3) concentrations were observed with spatial differences attributed to nitrogen oxide (NOx) emission densities in source contributing regions that were typically ≤ 1000 km. Significant spatiotemporal δ(15N) variabilities in HNO3 and pNO3 were observed with higher values during winter relative to summer, like previous reports from CASTNET samples collected in the early 2000s for our study region. In the early 2000s, δ(15N) of atmospheric nitrate in the northeast US had been suggested to be driven by NOx emissions; however, we did not find significant spatiotemporal changes in the modeled NOx emissions by sector and fuel type or δ(15N, NOx) for the source regions of the CASTNET sites. Instead, the seasonal and spatial differences in the observed δ(15N) of atmospheric nitrate were driven by nitrate formation pathways (i.e., homogeneous reactions of NO2 oxidation via hydroxyl radical or heterogeneous reactions of dinitrogen pentoxide on wetted aerosol surfaces) and their associated δ(15N) fractionation. Under the field conditions of low NOx relative to O3 concentrations and when δ(15N, NOx) emission sources do not have significant variability, we demonstrate that δ(15N) of atmospheric nitrate can be a robust tracer for diagnosing nitrate formation.

The northeastern US represents a mostly urban corridor impacted by high population and fossil fuel combustion emission density. This has led to historically degraded air quality and acid rain that has been a focus of regulatory-driven emissions reductions. Detailing the chemistry of atmospheric nitrate formation is critical for improving the model representation of atmospheric chemistry and air quality. The oxygen isotopic compositions of atmospheric nitrate are useful indicators in tracking nitrate formation pathways. Here, we measured oxygen isotope deltas (Δ(17O) and δ(18O)) for nitric acid (HNO3) and particulate nitrate (pNO3) from three US EPA Clean Air Status and Trends Network (CASTNET) sites in the northeastern US from December 2016 to 2018. The Δ(17O, HNO3) and δ(18O, HNO3) values ranged from 12.9 ‰ to 30.9 ‰ and from 46.9 ‰ to 82.1 ‰, and the Δ(17O, pNO3) and δ(18O, pNO3) ranged from 16.6 ‰ to 33.7 ‰ and from 43.6 ‰ to 85.3 ‰, respectively. There was distinct seasonality of δ(18O) and Δ(17O), with higher values observed during winter compared to during summer, suggesting a shift in O3 to HOx radical chemistry, as expected. Unexpectedly, there was a statistical difference in Δ(17O) between HNO3 and pNO3, with higher values observed for pNO3 (27.1 ± 3.8) ‰ relative to HNO3 (22.7 ± 3.6) ‰, and significant differences in the relationship between δ(18O) and Δ(17O). This difference suggests atmospheric nitrate phase-dependent oxidation chemistry that is not predicted in models. Based on the output from GEOS-Chem and both the δ(18O) and Δ(17O) observations, we quantify the production pathways of atmospheric nitrate. The model significantly overestimated the heterogeneous N2O5 hydrolysis production for both HNO3 and pNO3, a finding consistent with observed seasonal changes in δ(18O) and Δ(17O) of HNO3 and pNO3, though large uncertainties remain in the quantitative transfer of δ(18O) from major atmospheric oxidants. This comparison provides important insight into the role of oxidation chemistry in reconciling a commonly observed positive bias for modeled atmospheric nitrate concentrations in the northeastern US.

Methane (CH4) is a strong greenhouse gas that has become the focus of climate mitigation policies in recent years. Ethane/methane ratios can be used to identify and partition the different sources of methane, especially in areas with natural gas mixed with biogenic methane emissions, such as cities. We assessed the precision, accuracy, and selectivity of three commercially available laser-based analyzers that have been marketed as measuring instantaneous dry-mole fractions of methane and ethane in ambient air. The Aerodyne SuperDUAL instrument performed the best out of the three instruments, but it is large and requires expertise to operate. The Aeris Mira Ultra LDS analyzer also performed well for the price point and small size, but it required characterization of the water vapor dependence of reported concentrations and careful set-up for use. The Picarro G2210-i precisely measured methane, but it did not detect the 10 ppbv (part-per-billion by volume) increases in ambient ethane detected by the other two instruments when sampling a plume of incompletely combusted natural gas. For long-term tower deployments or those with large mobile laboratories, the Aerodyne SuperDUAL provides the best precision for methane and ethane. The more compact Aeris MIRA can, with careful use, quantify thermogenic methane sources to sufficient precision for mobile and short-term deployments in urban or oil and gas areas. We weighed the advantages of each instrument, including size, power requirement, ease of use on mobile platforms, and expertise needed to operate the instrument. We recommend the Aerodyne SuperDUAL or the Aeris MIRA Ultra LDS depending on the situation.

The NASA Atmospheric Tomography (ATom) mission built a photochemical climatology of air parcels based on in situ measurements with the NASA DC-8 aircraft along objectively planned profiling transects through the middle of the Pacific and Atlantic oceans. In this paper we present and analyze a data set of 10 s (2 km) merged and gap-filled observations of the key reactive species driving the chemical budgets of O3 and CH4 (O3, CH4, CO, H2O, HCHO, H2O2, CH3OOH, C2H6, higher alkanes, alkenes, aromatics, NOx, HNO3, HNO4, peroxyacetyl nitrate, and other organic nitrates), consisting of 146 494 distinct air parcels from ATom deployments 1 through 4. Six models calculated the O3 and CH4 photochemical tendencies from this modeling data stream for ATom 1. We find that 80 %–90 % of the total reactivity lies in the top 50 % of the parcels and 25 %–35 % in the top 10 %, supporting previous model-only studies that tropospheric chemistry is driven by a fraction of all the air. Surprisingly, the probability densities of species and reactivities averaged on a model scale (100 km) differ only slightly from the 2 km ATom 10 s data, indicating that much of the heterogeneity in tropospheric chemistry can be captured with current global chemistry models. Comparing the ATom reactivities over the tropical oceans with climatological statistics from six global chemistry models, we find generally good agreement with the reactivity rates for O3 and CH4. Models distinctly underestimate O3 production below 2 km relative to the mid-troposphere, and this can be traced to lower NOx levels than observed. Attaching photochemical reactivities to measurements of chemical species allows for a richer, yet more constrained-to-what-matters, set of metrics for model evaluation. This paper presents a corrected version of the paper published under the same authors and title (sans “corrected”) as https://doi.org/10.5194/acp-21-13729-2021.

Modeling atmospheric chemistry at fine resolution globally is computationally expensive; the capability to focus on specific geographic regions using a multiscale grid is desirable. Here, we develop, validate, and demonstrate stretched grids in the GEOS-Chem atmospheric chemistry model in its high-performance implementation (GCHP). These multiscale grids are specified at runtime by four parameters that offer users nimble control of the region that is refined and the resolution of the refinement. We validate the stretched-grid simulation versus global cubed-sphere simulations. We demonstrate the operation and flexibility of stretched-grid simulations with two case studies that compare simulated tropospheric NO2 column densities from stretched-grid and cubed-sphere simulations to retrieved column densities from the TROPOspheric Monitoring Instrument (TROPOMI). The first case study uses a stretched grid with a broad refinement covering the contiguous US to produce simulated columns that perform similarly to a C180 (∼ 50 km) cubed-sphere simulation at less than one-ninth the computational expense. The second case study experiments with a large stretch factor for a global stretched-grid simulation with a highly localized refinement with ∼10 km resolution for California. We find that the refinement improves spatial agreement with TROPOMI columns compared to a C90 cubed-sphere simulation of comparable computational demands. Overall, we find that stretched grids in GEOS-Chem are a practical tool for fine-resolution regional- or continental-scale simulations of atmospheric chemistry. Stretched grids are available in GEOS-Chem version 13.0.0.

The NASA Atmospheric Tomography (ATom) mission built a photochemical climatology of air parcels based on in situ measurements with the NASA DC-8 aircraft along objectively planned profiling transects through the middle of the Pacific and Atlantic oceans. In this paper we present and analyze a data set of 10 s (2 km) merged and gap-filled observations of the key reactive species driving the chemical budgets of O3 and CH4 (O3, CH4, CO, H2O, HCHO, H2O2, CH3OOH, C2H6, higher alkanes, alkenes, aromatics, NOx, HNO3, HNO4, peroxyacetyl nitrate, other organic nitrates), consisting of 146 494 distinct air parcels from ATom deployments 1 through 4. Six models calculated the O3 and CH4 photochemical tendencies from this modeling data stream for ATom 1. We find that 80 %–90 % of the total reactivity lies in the top 50 % of the parcels and 25 %–35 % in the top 10 %, supporting previous model-only studies that tropospheric chemistry is driven by a fraction of all the air. In other words, accurate simulation of the least reactive 50 % of the troposphere is unimportant for global budgets. Surprisingly, the probability densities of species and reactivities averaged on a model scale (100 km) differ only slightly from the 2 km ATom data, indicating that much of the heterogeneity in tropospheric chemistry can be captured with current global chemistry models. Comparing the ATom reactivities over the tropical oceans with climatological statistics from six global chemistry models, we find excellent agreement with the loss of O3 and CH4 but sharp disagreement with production of O3. The models sharply underestimate O3 production below 4 km in both Pacific and Atlantic basins, and this can be traced to lower NOx levels than observed. Attaching photochemical reactivities to measurements of chemical species allows for a richer, yet more constrained-to-what-matters, set of metrics for model evaluation.

This paper describes version 2.0 of the Global Change and Air Pollution (GCAP 2.0) model framework, a one-way offline coupling between version E2.1 of the NASA Goddard Institute for Space Studies (GISS) general circulation model (GCM) and the GEOS-Chem global 3-D chemical-transport model (CTM). Meteorology for driving GEOS-Chem has been archived from the E2.1 contributions to phase 6 of the Coupled Model Intercomparison Project (CMIP6) for the pre-industrial era and the recent past. In addition, meteorology is available for the near future and end of the century for seven future scenarios ranging from extreme mitigation to extreme warming. Emissions and boundary conditions have been prepared for input to GEOS-Chem that are consistent with the CMIP6 experimental design. The model meteorology, emissions, transport, and chemistry are evaluated in the recent past and found to be largely consistent with GEOS-Chem driven by the Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) product and with observational constraints.

Important uncertainties remain in our understanding of the spatial and temporal variability of atmospheric hydroxyl radical concentration ([OH]). Carbon-14-containing carbon monoxide (14CO) is a useful tracer that can help in the characterization of [OH] variability. Prior measurements of atmospheric 14CO concentration ([14CO] are limited in both their spatial and temporal extent, partly due to the very large air sample volumes that have been required for measurements (500–1000 L at standard temperature and pressure, L STP) and the difficulty and expense associated with the collection, shipment, and processing of such samples. Here we present a new method that reduces the air sample volume requirement to ≈90 L STP while allowing for [14CO] measurement uncertainties that are on par with or better than prior work (≈3 % or better, 1σ). The method also for the first time includes accurate characterization of the overall procedural [14CO] blank associated with individual samples, which is a key improvement over prior atmospheric 14CO work. The method was used to make measurements of [14CO] at the NOAA Mauna Loa Observatory, Hawaii, USA, between November 2017 and November 2018. The measurements show the expected [14CO] seasonal cycle (lowest in summer) and are in good agreement with prior [14CO] results from another low-latitude site in the Northern Hemisphere. The lowest overall [14CO] uncertainties (2.1 %, 1σ) are achieved for samples that are directly accompanied by procedural blanks and whose mass is increased to ≈50 µgC (micrograms of carbon) prior to the 14C measurement via dilution with a high-CO 14C-depleted gas.

The evolution of tropospheric ozone from 1850 to 2100 has been studied using data from Phase 6 of the Coupled Model Intercomparison Project (CMIP6). We evaluate long-term changes using coupled atmosphere–ocean chemistry–climate models, focusing on the CMIP Historical and ScenarioMIP ssp370 experiments, for which detailed tropospheric-ozone diagnostics were archived. The model ensemble has been evaluated against a suite of surface, sonde and satellite observations of the past several decades and found to reproduce well the salient spatial, seasonal and decadal variability and trends. The multi-model mean tropospheric-ozone burden increases from 247 ± 36 Tg in 1850 to a mean value of 356 ± 31 Tg for the period 2005–2014, an increase of 44 %. Modelled present-day values agree well with previous determinations (ACCENT: 336 ± 27 Tg; Atmospheric Chemistry and Climate Model Intercomparison Project, ACCMIP: 337 ± 23 Tg; Tropospheric Ozone Assessment Report, TOAR: 340 ± 34 Tg). In the ssp370 experiments, the ozone burden increases to 416 ± 35 Tg by 2100. The ozone budget has been examined over the same period using lumped ozone production (PO3) and loss (LO3) diagnostics. Both ozone production and chemical loss terms increase steadily over the period 1850 to 2100, with net chemical production (PO3-LO3) reaching a maximum around the year 2000. The residual term, which contains contributions from stratosphere–troposphere transport reaches a minimum around the same time before recovering in the 21st century, while dry deposition increases steadily over the period 1850–2100. Differences between the model residual terms are explained in terms of variation in tropopause height and stratospheric ozone burden.

We analyse historical (1850–2014) atmospheric hydroxyl (OH) and methane lifetime data from Coupled Model Intercomparison Project Phase 6 (CMIP6)/Aerosols and Chemistry Model Intercomparison Project (AerChemMIP) simulations. Tropospheric OH changed little from 1850 up to around 1980, then increased by around 9 % up to 2014, with an associated reduction in methane lifetime. The model-derived OH trends from 1980 to 2005 are broadly consistent with trends estimated by several studies that infer OH from inversions of methyl chloroform and associated measurements; most inversion studies indicate decreases in OH since 2005. However, the model results fall within observational uncertainty ranges. The upward trend in modelled OH since 1980 was mainly driven by changes in anthropogenic near-term climate forcer emissions (increases in anthropogenic nitrogen oxides and decreases in CO). Increases in halocarbon emissions since 1950 have made a small contribution to the increase in OH, whilst increases in aerosol-related emissions have slightly reduced OH. Halocarbon emissions have dramatically reduced the stratospheric methane lifetime by about 15 %–40 %; most previous studies assumed a fixed stratospheric lifetime. Whilst the main driver of atmospheric methane increases since 1850 is emissions of methane itself, increased ozone precursor emissions have significantly modulated (in general reduced) methane trends. Halocarbon and aerosol emissions are found to have relatively small contributions to methane trends. These experiments do not isolate the effects of climate change on OH and methane evolution; however, we calculate residual terms that are due to the combined effects of climate change and non-linear interactions between drivers. These residual terms indicate that non-linear interactions are important and differ between the two methodologies we use for quantifying OH and methane drivers. All these factors need to be considered in order to fully explain OH and methane trends since 1850; these factors will also be important for future trends.

The hydroxyl radical (OH) plays critical roles within the troposphere, such as determining the lifetime of methane (CH4), yet is challenging to model due to its fast cycling and dependence on a multitude of sources and sinks. As a result, the reasons for variations in OH and the resulting methane lifetime (τCH4), both between models and in time, are difficult to diagnose. We apply a neural network (NN) approach to address this issue within a group of models that participated in the Chemistry-Climate Model Initiative (CCMI). Analysis of the historical specified dynamics simulations performed for CCMI indicates that the primary drivers of τCH4 differences among 10 models are the flux of UV light to the troposphere (indicated by the photolysis frequency JO1D), the mixing ratio of tropospheric ozone (O3), the abundance of nitrogen oxides (NOx≡NO+NO2), and details of the various chemical mechanisms that drive OH. Water vapour, carbon monoxide (CO), the ratio of NO:NOx, and formaldehyde (HCHO) explain moderate differences in τCH4, while isoprene, methane, the photolysis frequency of NO2 by visible light (JNO2), overhead ozone column, and temperature account for little to no model variation in τCH4. We also apply the NNs to analysis of temporal trends in OH from 1980 to 2015. All models that participated in the specified dynamics historical simulation for CCMI demonstrate a decline in τCH4 during the analysed timeframe. The significant contributors to this trend, in order of importance, are tropospheric O3, JO1D, NOx, and H2O, with CO also causing substantial interannual variability in OH burden. Finally, the identified trends in τCH4 are compared to calculated trends in the tropospheric mean OH concentration from previous work, based on analysis of observations. The comparison reveals a robust result for the effect of rising water vapour on OH and τCH4, imparting an increasing and decreasing trend of about 0.5 % decade−1, respectively. The responses due to NOx, ozone column, and temperature are also in reasonably good agreement between the two studies.

Measurements from actinic flux spectroradiometers on board the NASA DC-8 during the Atmospheric Tomography (ATom) mission provide an extensive set of statistics on how clouds alter photolysis rates (J values) throughout the remote Pacific and Atlantic Ocean basins. J values control tropospheric ozone and methane abundances, and thus clouds have been included for more than three decades in tropospheric chemistry modeling. ATom made four profiling circumnavigations of the troposphere capturing each of the seasons during 2016–2018. This work examines J values from the Pacific Ocean flights of the first deployment, but publishes the complete Atom-1 data set (29 July to 23 August 2016). We compare the observed J values (every 3 s along flight track) with those calculated by nine global chemistry–climate/transport models (globally gridded, hourly, for a mid-August day). To compare these disparate data sets, we build a commensurate statistical picture of the impact of clouds on J values using the ratio of J-cloudy (standard, sometimes cloudy conditions) to J-clear (artificially cleared of clouds). The range of modeled cloud effects is inconsistently large but they fall into two distinct classes: (1) models with large cloud effects showing mostly enhanced J values aloft and or diminished at the surface and (2) models with small effects having nearly clear-sky J values much of the time. The ATom-1 measurements generally favor large cloud effects but are not precise or robust enough to point out the best cloud-modeling approach. The models here have resolutions of 50–200 km and thus reduce the occurrence of clear sky when averaging over grid cells. In situ measurements also average scattered sunlight over a mixed cloud field, but only out to scales of tens of kilometers. A primary uncertainty remains in the role of clouds in chemistry, in particular, how models average over cloud fields, and how such averages can simulate measurements.

Nitrogen oxides (NOx≡NO+NO2) in the upper troposphere (UT) have a large impact on global tropospheric ozone and OH (the main atmospheric oxidant). New cloud-sliced observations of UT NO2 at 450–280 hPa (∼6–9 km) from the Ozone Monitoring Instrument (OMI) produced by NASA and the Royal Netherlands Meteorological Institute (KNMI) provide global coverage to test our understanding of the factors controlling UT NOx. We find that these products offer useful information when averaged over coarse scales (20∘×32∘, seasonal), and that the NASA product is more consistent with aircraft observations of UT NO2. Correlation with Lightning Imaging Sensor (LIS) and Optical Transient Detector (OTD) satellite observations of lightning flash frequencies suggests that lightning is the dominant source of NOx to the upper troposphere except for extratropical latitudes in winter. The NO2 background in the absence of lightning is 10–20 pptv. We infer a global mean NOx yield of 280±80 moles per lightning flash, with no significant difference between the tropics and midlatitudes, and a global lightning NOx source of 5.9±1.7 Tg N a−1. There is indication that the NOx yield per flash increases with lightning flash footprint and with flash energy.

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.

We develop a new protocol for merging in situ measurements with 3-D model simulations of atmospheric chemistry with the goal of integrating these data to identify the most reactive air parcels in terms of tropospheric production and loss of the greenhouse gases ozone and methane. Presupposing that we can accurately measure atmospheric composition, we examine whether models constrained by such measurements agree on the chemical budgets for ozone and methane. In applying our technique to a synthetic data stream of 14 880 parcels along 180° W, we are able to isolate the performance of the photochemical modules operating within their global chemistry-climate and chemistry-transport models, removing the effects of modules controlling tracer transport, emissions, and scavenging. Differences in reactivity across models are driven only by the chemical mechanism and the diurnal cycle of photolysis rates, which are driven in turn by temperature, water vapor, solar zenith angle, clouds, and possibly aerosols and overhead ozone, which are calculated in each model. We evaluate six global models and identify their differences and similarities in simulating the chemistry through a range of innovative diagnostics. All models agree that the more highly reactive parcels dominate the chemistry (e.g., the hottest 10 % of parcels control 25–30 % of the total reactivities), but do not fully agree on which parcels comprise the top 10 %. Distinct differences in specific features occur, including the spatial regions of maximum ozone production and methane loss, as well as in the relationship between photolysis and these reactivities. Unique, possibly aberrant, features are identified for each model, providing a benchmark for photochemical module development. Among the six models tested here, three are almost indistinguishable based on the inherent variability caused by clouds, and thus we identify four, effectively distinct, chemical models. Based on this work, we suggest that water vapor differences in model simulations of past and future atmospheres may be a cause of the different evolution of tropospheric O3 and CH4, and lead to different chemistry-climate feedbacks across the models.

An approach for analysis and modeling of global atmospheric chemistry is developed for application to measurements that provide a tropospheric climatology of those heterogeneously distributed, reactive species that control the loss of methane and the production and loss of ozone. We identify key species (e.g., O3, NOx, HNO3, HNO4, C2H3NO5, H2O, HOOH, CH3OOH, HCHO, CO, CH4, C2H6, acetaldehyde, acetone) and presume that they can be measured simultaneously in air parcels on the scale of a few km horizontally and a few tenths of a km vertically. As a first step, six global models have prepared such climatologies sampled at the modeled resolution for August with emphasis on the vast central Pacific Ocean basin. Objectives of this paper are to identify and characterize differences in model-generated reactivities as well as species covariances that could readily be discriminated with an unbiased climatology. A primary tool is comparison of multidimensional probability densities of key species weighted by the mass of such parcels or frequency of occurrence as well as by the reactivity of the parcels with respect to methane and ozone. The reactivity-weighted probabilities tell us which parcels matter in this case, and this method shows skill in differentiating among the models' chemistry. Testing 100 km scale models with 2 km measurements using these tools also addresses a core question about model resolution and whether fine-scale atmospheric structures matter to the overall ozone and methane budget. A new method enabling these six global chemistry–climate models to ingest an externally sourced climatology and then compute air parcel reactivity is demonstrated. Such an objective climatology containing these key species is anticipated from the NASA Atmospheric Tomography (ATom) aircraft mission (2015–2020), executing profiles over the Pacific and Atlantic Ocean basins. This modeling study addresses a core part of the design of ATom.

We use a statistical model to investigate the effect of 2000–2050 climate change on fine particulate matter (PM2. 5) air quality across the contiguous United States. By applying observed relationships of PM2. 5 and meteorology to the IPCC Coupled Model Intercomparision Project Phase 5 (CMIP5) archives, we bypass some of the uncertainties inherent in chemistry-climate models. Our approach uses both the relationships between PM2. 5 and local meteorology as well as the synoptic circulation patterns, defined as the singular value decomposition (SVD) pattern of the spatial correlations between PM2. 5 and meteorological variables in the surrounding region. Using an ensemble of 19 global climate models (GCMs) under the RCP4.5 scenario, we project an increase of 0.4–1.4 µg m−3 in annual mean PM2. 5 in the eastern US and a decrease of 0.3–1.2 µg m−3 in the Intermountain West by the 2050s, assuming present-day anthropogenic sources of PM2. 5. Mean summertime PM2. 5 increases as much as 2–3 µg m−3 in the eastern United States due to faster oxidation rates and greater mass of organic aerosols from biogenic emissions. Mean wintertime PM2. 5 decreases by 0.3–3 µg m−3 over most regions in the United States, likely due to the volatilization of ammonium nitrate. Our approach provides an efficient method to calculate the potential climate penalty on air quality across a range of models and scenarios. We find that current atmospheric chemistry models may underestimate or even fail to capture the strongly positive sensitivity of monthly mean PM2. 5 to temperature in the eastern United States in summer, and they may underestimate future changes in PM2. 5 in a warmer climate. In GEOS-Chem, the underestimate in monthly mean PM2. 5–temperature relationship in the east in summer is likely caused by overly strong negative sensitivity of monthly mean low cloud fraction to temperature in the assimilated meteorology ( ∼ −0.04 K−1) compared to the weak sensitivity implied by satellite observations (±0.01 K−1). The strong negative dependence of low cloud cover on temperature in turn causes the modeled rates of sulfate aqueous oxidation to diminish too rapidly as temperatures rise, leading to the underestimate of sulfate–temperature slopes, especially in the south. Our work underscores the importance of evaluating the sensitivity of PM2. 5 to its key controlling meteorological variables in climate-chemistry models on multiple timescales before they are applied to project future air quality.

This study evaluates the distribution and variation of carbon monoxide (CO) in the upper troposphere and lower stratosphere (UTLS) during 2004–2012 as simulated by two chemical transport models, using the latest version of Aura Microwave Limb Sounder (MLS) observations. The simulated spatial distributions, temporal variations and vertical transport of CO in the UTLS region are compared with those observed by MLS. We also investigate the impact of surface emissions and deep convection on CO concentrations in the UTLS over different regions, using both model simulations and MLS observations. Global Modeling Initiative (GMI) and GEOS-Chem simulations of UTLS CO both show similar spatial distributions to observations. The global mean CO values simulated by both models agree with MLS observations at 215 and 147 hPa, but are significantly underestimated by more than 40 % at 100 hPa. In addition, the models underestimate the peak CO values by up to 70 % at 100 hPa, 60 % at 147 hPa and 40 % at 215 hPa, with GEOS-Chem generally simulating more CO at 100 hPa and less CO at 215 hPa than GMI. The seasonal distributions of CO simulated by both models are in better agreement with MLS in the Southern Hemisphere (SH) than in the Northern Hemisphere (NH), with disagreements between model and observations over enhanced CO regions such as southern Africa. The simulated vertical transport of CO shows better agreement with MLS in the tropics and the SH subtropics than the NH subtropics. We also examine regional variations in the relationships among surface CO emission, convection and UTLS CO concentrations. The two models exhibit emission–convection–CO relationships similar to those observed by MLS over the tropics and some regions with enhanced UTLS CO.

Isoprene and its oxidation products are major players in the oxidative chemistry of the troposphere. Current understanding of the factors controlling biogenic isoprene emissions and of the fate of isoprene oxidation products in the atmosphere has been evolving rapidly. We use a climate–biosphere–chemistry modeling framework to evaluate the sensitivity of estimates of the tropospheric oxidative capacity to uncertainties in isoprene emissions and photochemistry. Our work focuses on two climate transitions: from the Last Glacial Maximum (LGM, 19 000–23 000 years BP) to the preindustrial (1770s) and from the preindustrial to the present day (1990s). We find that different oxidants have different sensitivities to the uncertainties tested in this study. Ozone is relatively insensitive, whereas OH is the most sensitive: changes in the global mean OH levels for the LGM-to-preindustrial transition range between −29 and +7 % and those for the preindustrial-to-present-day transition range between −8 and +17 % across our simulations. We find little variability in the implied relative LGM–preindustrial difference in methane emissions with respect to the uncertainties tested in this study. Conversely, estimates of the preindustrial-to-present-day and LGM-to-preindustrial changes in the global burden of secondary organic aerosol (SOA) are highly sensitive. We show that the linear relationship between tropospheric mean OH and tropospheric mean ozone photolysis rates, water vapor, and total emissions of NOx and reactive carbon – first reported in Murray et al. (2014) – does not hold across all periods with the new isoprene photochemistry mechanism. This study demonstrates how inadequacies in our current understanding of isoprene emissions and photochemistry impede our ability to constrain the oxidative capacities of the present and past atmospheres, its controlling factors, and the radiative forcing of some short-lived species such as SOA over time.

The oxidative capacity of past atmospheres is highly uncertain. We present here a new climate–biosphere–chemistry modeling framework to determine oxidant levels in the present and past troposphere. We use the GEOS-Chem chemical transport model driven by meteorological fields from the NASA Goddard Institute of Space Studies (GISS) ModelE, with land cover and fire emissions from dynamic global vegetation models. We present time-slice simulations for the present day, late preindustrial era (AD 1770), and the Last Glacial Maximum (LGM, 19–23 ka), and we test the sensitivity of model results to uncertainty in lightning and fire emissions. We find that most preindustrial and paleo climate simulations yield reduced oxidant levels relative to the present day. Contrary to prior studies, tropospheric mean OH in our ensemble shows little change at the LGM relative to the preindustrial era (0.5 ± 12 %), despite large reductions in methane concentrations. We find a simple linear relationship between tropospheric mean ozone photolysis rates, water vapor, and total emissions of NOx and reactive carbon that explains 72 % of the variability in global mean OH in 11 different simulations across the last glacial–interglacial time interval and the industrial era. Key parameters controlling the tropospheric oxidative capacity over glacial–interglacial periods include overhead stratospheric ozone, tropospheric water vapor, and lightning NOx emissions. Variability in global mean OH since the LGM is insensitive to fire emissions. Our simulations are broadly consistent with ice-core records of Δ17O in sulfate and nitrate at the LGM, and CO, HCHO, and H2O2 in the preindustrial era. Our results imply that the glacial–interglacial changes in atmospheric methane observed in ice cores are predominantly driven by changes in its sources as opposed to its sink with OH.

We used the GEOS-Chem chemistry-transport model to investigate impacts of surface emissions and dynamical processes on the spatial and temporal patterns of CO observed by the Microwave Limb Sounder (MLS) in the upper troposphere (UT) and lower stratosphere (LS). Model simulations driven by GEOS-4 and GEOS-5 assimilated fields present many features of the seasonal and inter-annual variation of CO in the upper troposphere and lower stratosphere. Both model simulations and the MLS data show a transition from semi-annual variations in the UT to annual variations in the LS. Tagged CO simulations indicate that the semi-annual variation of CO in the UT is determined mainly by the temporal overlapping of surface biomass burning from different continents as well as the north-south shifts of deep convection. Both GEOS-4 and GEOS-5 have maximum upward transport in April and May with a minimum in July to September. The CO peaks from the Northern Hemisphere (NH) fires propagate faster to the LS than do those from the Southern Hemisphere (SH) fires. Thus the transition from a semi-annual to an annual cycle around 80 hPa is induced by a combination of the CO signal at the tropopause and the annual cycle of the Brewer-Dobson circulation. In GEOS-5, the shift to an annual cycle occurs at a lower altitude than in MLS CO, a result of inadequate upward transport. We deduce vertical velocities from MLS CO, and use them to evaluate the velocities derived from the archived GEOS meteorological fields. We find that GEOS-4 velocities are similar to those from MLS CO between 215 hPa and 125 hPa, while the velocities in GEOS-5 are too low in spring and summer. The mean tropical vertical velocities from both models are lower than those inferred from MLS CO above 100 hPa, particularly in GEOS-5, with mean downward, rather than upward motion in boreal summer. Thus the models' CO maxima from SH burning are transported less effectively than those in MLS CO above 147 hPa and almost disappear by 100 hPa. The strongest peaks in the CO tape-recorder are in late 2004, 2006, and 2010, with the first two resulting from major fires in Indonesia and the last from severe burning in South America, all associated with intense droughts.

We examine the distribution of tropical tropospheric ozone (O3) from the Microwave Limb Sounder (MLS) and the Tropospheric Emission Spectrometer (TES) by using a global three-dimensional model of tropospheric chemistry (GEOS-Chem). MLS and TES observations of tropospheric O3 during 2005 to 2009 reveal a distinct, persistent O3 maximum, both in mixing ratio and tropospheric column, in May over the Equatorial Southern Indian Ocean (ESIO). The maximum is most pronounced in 2006 and 2008 and less evident in the other three years. This feature is also consistent with the total column O3 observations from the Ozone Mapping Instrument (OMI) and the Atmospheric Infrared Sounder (AIRS). Model results reproduce the observed May O3 maximum and the associated interannual variability. The origin of the maximum reflects a complex interplay of chemical and dynamic factors. The O3 maximum is dominated by the O3 production driven by lightning nitrogen oxides (NOx) emissions, which accounts for 62% of the tropospheric column O3 in May 2006. We find the contribution from biomass burning, soil, anthropogenic and biogenic sources to the O3 maximum are rather small. The O3 productions in the lightning outflow from Central Africa and South America both peak in May and are directly responsible for the O3 maximum over the western ESIO. The lightning outflow from Equatorial Asia dominates over the eastern ESIO. The interannual variability of the O3 maximum is driven largely by the anomalous anti-cyclones over the southern Indian Ocean in May 2006 and 2008. The lightning outflow from Central Africa and South America is effectively entrained by the anti-cyclones followed by northward transport to the ESIO.