ALBERT

Description: 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.

Description: We examine the relative contribution of processes controlling the interannual variability (IAV) of tropospheric ozone over four sub-regions of the southern hemispheric tropospheric ozone maximum (SHTOM) over a twenty-year period. Our study is based on hindcast simulations from the National Aeronautics and Space Administration Global Modeling Initiative – Chemistry transport model (NASA GMI-CTM) of tropospheric and stratospheric chemistry, driven by assimilated Modern Era Retrospective-Analysis for Research and Applications (MERRA) meteorological fields. Our analysis shows that over SHTOM region, the IAV of the stratospheric contribution is the most important factor driving the IAV of upper tropospheric ozone (270 hPa), where ozone has a strong radiative effect. Over the south Atlantic region, the contribution from surface emissions to the IAV of ozone exceeds that from stratospheric input at and below 430 hPa. Over the south Indian Ocean, the IAV of stratospheric ozone makes the largest contribution to the IAV of ozone with little or no influence from surface emissions at 270 hPa and 430 hPa in austral winter. Over the tropical south Atlantic region, the contribution from IAV of stratospheric input dominates in austral winter at 270 hPa and drops to less than half but is still significant at 430 hPa. Emission contributions are not significant at these two levels, even during September. The IAV of lightning over this region also contributes to the IAV of ozone in September and December. Over the tropical southeastern Pacific, the contribution of the IAV of stratospheric input is significant at 270 hPa and 430 hPa in austral winter, and emissions have little influence.

Description: An assessment of global nitrate and ammonium aerosol based on simulations from nine models participating in the AeroCom Phase III study is presented. A budget analyses was conducted to understand the typical magnitude, distribution, and diversity of the aerosols and their precursors among the models. To gain confidence on 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-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; 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. Analyses at the process level show that the large diversity in atmospheric burdens of NO3−, NH3, and NH4+ is also related to deposition processes. Wet deposition seems to be the dominant process in determining the diversity in NH3 and NH4+ 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 〉 80 %) and determines the coarse and fine mode distribution of nitrate aerosol.

Description: 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 vertically. Six global models have prepared such climatologies (at model resolution) for August with emphasis on the vast central Pacific and Atlantic Ocean basins. We show clear 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 multi-dimensional probability densities of key species weighted by 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. 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 observed climatology is anticipated from the NASA Atmospheric Tomography (ATom) aircraft mission (2015–2020), measuring the key species, executing profiles over the Pacific and Atlantic Ocean basins. This work is a core part of the design of ATom.

Description: We examine the capability of the Global Modeling Initiative (GMI) chemistry and transport model to reproduce global mid-tropospheric (618 hPa) O3-CO correlations determined by the measurements from Tropospheric Emission Spectrometer (TES) aboard NASA’s Aura satellite during boreal summer (July–August). The model is driven by three meteorological data sets (fvGCM with sea surface temperature for 1995, GEOS4-DAS for 2005, and MERRA for 2005), allowing us to examine the sensitivity of model O3-CO correlations to input meteorological data. Model simulations of radionuclide tracers (222Rn, 210Pb, and 7Be) are used to illustrate the differences in transport-related processes among the meteorological data sets. Simulated O3 values are evaluated with climatological ozone profiles from ozonesonde measurements and satellite tropospheric O3 columns. Despite the fact that the three simulations show significantly different global and regional distributions of O3 and CO concentrations, all simulations show similar patterns of O3-CO correlations on a global scale. These patterns are consistent with those derived from TES observations, except in the tropical easterly biomass burning outflow regions. Discrepancies in regional O3-CO correlation patterns in the three simulations may be attributed to differences in convective transport, stratospheric influence, and subsidence, among other processes. To understand how various emissions drive global O3-CO correlation patterns, we examine the sensitivity of GMI/MERRA model-calculated O3 and CO concentrations and their correlations to emission types (fossil fuel, biomass burning, biogenic, and lightning NOx emissions). Fossil fuel and biomass burning emissions are mainly responsible for the strong positive O3-CO correlations over continental outflow regions in both hemispheres. Biogenic emissions have a relatively smaller impact on O3-CO correlations than other emissions, but are largely responsible for the negative correlations over the tropical eastern Pacific, reflecting the fact that O3 is consumed and CO generated during the atmospheric oxidation process of isoprene under low NOx conditions. We find that lightning NOx emissions degrade both positive correlations at mid-/high- latitudes and negative correlations in the tropics because ozone production downwind of lightning NOx emissions is not directly related to the emission and transport of CO. Our study concludes that O3-CO correlations may be used effectively to constrain the sources of regional tropospheric O3 in global 3-D models, especially for those regions where convective transport of pollution plays an important role.

Description: 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. ATom made profiling circumnavigations of the troposphere over four seasons during 2016–2018. J-values are a primary chemical control over tropospheric ozone and methane abundances and their greenhouse effects. Clouds have been recognized for more than three decades as being an important factor in tropospheric chemistry. The ATom climatology of J-values is a unique test of how the chemistry models treat clouds. This work focuses on measurements over the Pacific during the first deployment (ATom-1) in August 2016. Nine global chemistry–climate or –transport models provide J-values for the domains measured in ATom-1. We compare mean profiles over a range of cloudy and clear conditions; but, more importantly, we build a statistical picture of the impact of clouds on J-values through the distribution of the ratio of J-cloudy to J-clear. In detail, the models show largely disparate patterns. When compared with measurements, there is some limited, broad agreement. Models here have resolutions of 50–200km and thus reduce the occurrence of clear sky when averaging over grid cells. In situ measurements also average the scattered sunlight, but only out to scales of 10s of km. 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.