An assessment of global particulate nitrate and ammonium aerosol based on simulations from nine models participating in the Aerosol Comparisons between Observations and Models (AeroCom) phase III ...study is presented. A budget analysis was conducted to understand the typical magnitude, distribution, and diversity of the aerosols and their precursors among the models. To gain confidence regarding model performance, the model results were evaluated with various observations globally, including ground station measurements over North America, Europe, and east Asia for tracer concentrations and dry and wet depositions, as well as with aircraft measurements in the Northern Hemisphere mid-to-high latitudes for tracer vertical distributions. Given the unique chemical and physical features of the nitrate occurrence, we further investigated the similarity and differentiation among the models by examining (1) the pH-dependent NH3 wet deposition; (2) the nitrate formation via heterogeneous chemistry on the surface of dust and sea salt particles or thermodynamic equilibrium calculation including dust and sea salt ions; and (3) the nitrate coarse-mode fraction (i.e., coarse/total). It is found that HNO3, which is simulated explicitly based on full O3-HOx-NOx-aerosol chemistry by all models, differs by up to a factor of 9 among the models in its global tropospheric burden. This partially contributes to a large difference in NO3(-), whose atmospheric burden differs by up to a factor of 13. The atmospheric burdens of NH3 and NHC 4 differ by 17 and 4, respectively. Analyses at the process level show that the large diversity in atmospheric burdens of NO3(-), NH3, and NHC4(+) is also related to deposition processes. Wet deposition seems to be the dominant process in determining the diversity in NH3 and NHC 4 lifetimes. It is critical to correctly account for contributions of heterogeneous chemical production of nitrate on dust and sea salt, because this process overwhelmingly controls atmospheric nitrate production (typically greater than 80 %) and determines the coarse- and fine-mode distribution of nitrate aerosol.
The lifetime of nitrous oxide, the third‐most‐important human‐emitted greenhouse gas, is based to date primarily on model studies or scaling to other gases. This work calculates a semiempirical ...lifetime based on Microwave Limb Sounder satellite measurements of stratospheric profiles of nitrous oxide, ozone, and temperature; laboratory cross‐section data for ozone and molecular oxygen plus kinetics for O(1D); the observed solar spectrum; and a simple radiative transfer model. The result is 116 ± 9 years. The observed monthly‐to‐biennial variations in lifetime and tropical abundance are well matched by four independent chemistry‐transport models driven by reanalysis meteorological fields for the period of observation (2005–2010), but all these models overestimate the lifetime due to lower abundances in the critical loss region near 32 km in the tropics. These models plus a chemistry‐climate model agree on the nitrous oxide feedback factor on its own lifetime of 0.94 ± 0.01, giving N2O perturbations an effective residence time of 109 years. Combining this new empirical lifetime with model estimates of residence time and preindustrial lifetime (123 years) adjusts our best estimates of the human‐natural balance of emissions today and improves the accuracy of projected nitrous oxide increases over this century.
Key Points
Nitrous oxide lifetime is computed empirically from MLS satellite data
Empirical N2O lifetimes compared with models including interannual variability
Results improve values for present anthropogenic and preindustrial emissions
Satellite-based retrievals of tropospheric NO2 columns are widely used to infer NOx (≡ NO + NO2) emissions. These retrievals rely on model information for the vertical distribution of NO2. The free ...tropospheric background above 2 km is particularly important because the sensitivity of the retrievals increases with altitude. Free tropospheric NOx also has a strong effect on tropospheric OH and ozone concentrations. Here we use observations from three aircraft campaigns (SEAC4RS, DC3, and ATom) and four atmospheric chemistry models (GEOS-Chem, GMI, TM5, and CAMS) to evaluate the model capabilities for simulating NOx in the free troposphere and attribute it to sources. NO2 measurements during the Studies of Emissions and Atmospheric Composition, Clouds, and Climate Coupling by Regional Surveys (SEAC4RS) and Deep Convective Clouds and Chemistry (DC3) campaigns over the southeastern U.S. in summer show increasing concentrations in the upper troposphere above 10 km, which are not replicated by the GEOS-Chem, although the model is consistent with the NO measurements. Using concurrent NO, NO2, and ozone observations from a DC3 flight in a thunderstorm outflow, we show that the NO2 measurements in the upper troposphere are biased high, plausibly due to interference from thermally labile NO2 reservoirs such as peroxynitric acid (HNO4) and methyl peroxy nitrate (MPN). We find that NO2 concentrations calculated from the NO measurements and NO–NO2 photochemical steady state (PSS) are more reliable to evaluate the vertical profiles of NO2 in models. GEOS-Chem reproduces the shape of the PSS-inferred NO2 profiles throughout the troposphere for SEAC4RS and DC3 but overestimates NO2 concentrations by about a factor of 2. The model underestimates MPN and alkyl nitrate concentrations, suggesting missing organic NOx chemistry. On the other hand, the standard GEOS-Chem model underestimates NO observations from the Atmospheric Tomography Mission (ATom) campaigns over the Pacific and Atlantic oceans, indicating a missing NOx source over the oceans. We find that we can account for this missing source by including in the model the photolysis of particulate nitrate on sea salt aerosols at rates inferred from laboratory studies and field observations of nitrous acid (HONO) over the Atlantic. The median PSS-inferred tropospheric NO2 column density for the ATom campaign is 1.7 ± 0.44 × 1014 molec. cm-2, and the NO2 column density simulated by the four models is in the range of 1.4–2.4 × 1014 molec. cm-2, implying that the uncertainty from using modeled NO2 tropospheric columns over clean areas in the retrievals for stratosphere–troposphere separation is about 1 × 1014 molec. cm-2. We find from GEOS-Chem that lightning is the main primary NOx source in the free troposphere over the tropics and southern midlatitudes, but aircraft emissions dominate at northern midlatitudes in winter and in summer over the oceans. Particulate nitrate photolysis increases ozone concentrations by up to 5 ppbv (parts per billion by volume) in the free troposphere in the northern extratropics in the model, which would largely correct the low model bias relative to ozonesonde observations. Global tropospheric OH concentrations increase by 19 %. The contribution of the free tropospheric background to the tropospheric NO2 columns observed by satellites over the contiguous U.S. increases from 25 ± 11 % in winter to 65 ± 9 % in summer, according to the GEOS-Chem vertical profiles. This needs to be accounted for when deriving NOx emissions from satellite NO2 column measurements.
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.
The ability of 11 models in simulating the aerosol vertical distribution from regional to global scales, as part of the second phase of the AeroCom model intercomparison initiative (AeroCom II), is ...assessed and compared to results of the first phase. The evaluation is performed using a global monthly gridded data set of aerosol extinction profiles built for this purpose from the CALIOP (Cloud‐Aerosol Lidar with Orthogonal Polarization) Layer Product 3.01. Results over 12 subcontinental regions show that five models improved, whereas three degraded in reproducing the interregional variability in Zα0–6 km, the mean extinction height diagnostic, as computed from the CALIOP aerosol profiles over the 0–6 km altitude range for each studied region and season. While the models' performance remains highly variable, the simulation of the timing of the Zα0–6 km peak season has also improved for all but two models from AeroCom Phase I to Phase II. The biases in Zα0–6 km are smaller in all regions except Central Atlantic, East Asia, and North and South Africa. Most of the models now underestimate Zα0–6 km over land, notably in the dust and biomass burning regions in Asia and Africa. At global scale, the AeroCom II models better reproduce the Zα0–6 km latitudinal variability over ocean than over land. Hypotheses for the performance and evolution of the individual models and for the intermodel diversity are discussed. We also provide an analysis of the CALIOP limitations and uncertainties contributing to the differences between the simulations and observations.
Key Points
The ability of 11 global models in simulating the aerosol vertical distribution is assessed
Hypotheses for the models performance and evolution and for the inter‐model diversity are discussed
An analysis of CALIOP limitations and uncertainties contributing to the discrepancies is provided
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.
The inorganic chlorine (Cly) and odd nitrogen (NOy) chemical families influence stratospheric O3. In January 2020 Australian wildfires injected record-breaking amounts of smoke into the southern ...stratosphere. Within 1-2 months ground-based and satellite observations showed Cly and NOy were repartitioned. Compared to decadal means, lower stratospheric (LS) HCl columns declined by ~30% between March and May while ClONO2 columns increased by 40-50%. The Cly perturbations recovered from June to October. The LS NO2 decreased from February to April, consistent with sulfate aerosol reactions, but returned to typical values by June - months earlier than the Cly recovery. Transport tracers show an air mass change explains the observed O3 decrease after April. Simulations assuming wildfire smoke behaves identically to sulfate aerosols couldn’t reproduce observed Cly changes, suggesting that their composition and chemistry differs from sulfate aerosols. This undermines our ability to predict ozone in a changing climate.
The hydroxyl radical (OH) is the primary daytime oxidant in the troposphere and provides the main loss mechanism for many pollutants and greenhouse gases, including methane (CH4). Global mean ...tropospheric OH differs by as much as 80% among various global models, for reasons that are not well understood. We use neural networks (NNs), trained using archived output from eight chemical transport models (CTMs) that participated in the Polar Study using Aircraft, Remote Sensing, Surface Measurements and Models, of Climate, Chemistry, Aerosols and Transport Model Intercomparison Project (POLMIP), to quantify the factors responsible for differences in tropospheric OH and resulting CH4 lifetime (Tau CH4) between these models. Annual average Tau CH4, for loss by OH only, ranges from 8.0 to 11.6 years for the eight POLMIP CTMs. The factors driving these differences were quantified by inputting 3-D chemical fields from one CTM into the trained NN of another CTM. Across all CTMs, the largest mean differences in Tau CH4 (Delta Tau CH4) result from variations in chemical mechanisms (Delta Tau CH4 = 0.46 years), the photolysis frequency (J) of O3 yields O(D-1) (0.31 years), local O3 (0.30 years), and CO (0.23 years). The Delta Tau CH4 due to CTM differences in NO(x) (NO + NO2) is relatively low (0.17 years), although large regional variation in OH between the CTMs is attributed to NO(x). Differences in isoprene and J(NO2) have negligible overall effect on globally averaged tropospheric OH, although the extent of OH variations due to each factor depends on the model being examined. This study demonstrates that NNs can serve as a useful tool for quantifying why tropospheric OH varies between global models, provided that essential chemical fields are archived.
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.
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.
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