An expected global increase in bioenergy-crop cultivation as an alternative to fossil fuels will have consequences on both global climate and local air quality through changes in biogenic emissions of volatile organic compounds (VOCs). While greenhouse gas emissions may be reduced through the substitution of next-generation bioenergy crops such as eucalyptus, giant reed, and switchgrass for fossil fuels, the choice of species has important ramifications for human health, potentially reducing the benefits of conversion due to increases in ozone (O3) and fine particulate matter (PM2.5) levels as a result of large changes in biogenic emissions. Using the Community Earth System Model we simulate the conversion of marginal and underutilized croplands worldwide to bioenergy crops under varying future anthropogenic emissions scenarios. A conservative global replacement using high VOC-emitting crop profiles leads to modeled population-weighted O3 increases of 5-27 ppb in India, 1-9 ppb in China, and 1-6 ppb in the United States, with peak PM2.5 increases of up to 2 μg m^-3. We present a metric for the regional evaluation of candidate bioenergy crops, as well as results for the application of this metric to four representative emissions profiles using four replacement scales (10-100% maximum estimated available land). Finally, we assess the total health and climate impacts of biogenic emissions, finding that the negative consequences of using high-emitting crops could exceed 50% of the positive benefits of reduced fossil fuel emissions in value.

A system for simulating aerosols has been developed using a chemical transport model together with an assimilation of satellite aerosol retrievals. The methodology and model components are described in this paper, and the modeled distribution of aerosols for the Indian Ocean Experiment (INDOEX) is presented by Rasch et al. [this issue]. The system generated aerosol forecasts to guide deployment of ships and aircraft during INDOEX. The system consists of the Model of Atmospheric Transport and Chemistry (MATCH) combined with an assimilation package developed for applications in atmospheric chemistry. MATCH predicts the evolution of sulfate, carbonaceous, and mineral dust aerosols, and it diagnoses the distribution of sea salt aerosols. The model includes a detailed treatment of the sources, chemical transformation, transport, and deposition of the aerosol species. The aerosol forecasts involve a two-stage process. During the assimilation phase the total column aerosol optical depth (AOD) is estimated from the model aerosol fields. The model state is then adjusted to improve the agreement between the simulated AOD and satellite retrievals of AOD. During the subsequent integration phase the aerosol fields are evolved using meteorological fields from an external model. Comparison of the modeled AOD against estimates of the AOD from INDOEX Sun photometer data show that the differences in daily means are -0.03 ± 0.06. Although the initial application is limited to the Indian Ocean, the methodology could be extended to derive global aerosol analyses combining in situ and remotely sensed aerosol observations. Copyright 2001 by the American Geophysical Union.

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 14ĝ€880 parcels along 180°ĝ€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 10ĝ€% of parcels control 25-30ĝ€% of the total reactivities), but do not fully agree on which parcels comprise the top 10ĝ€%. 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.

The Aerosol Chemistry Model Intercomparison Project (AerChemMIP) is endorsed by the Coupled-Model Intercomparison Project 6 (CMIP6) and is designed to quantify the climate and air quality impacts of aerosols and chemically reactive gases. These are specifically near-term climate forcers (NTCFs: methane, tropospheric ozone and aerosols, and their precursors), nitrous oxide and ozone-depleting halocarbons. The aim of AerChemMIP is to answer four scientific questions.

1. How have anthropogenic emissions contributed to global radiative forcing and affected regional climate over the historical period?

2. How might future policies (on climate, air quality and land use) affect the abundances of NTCFs and their climate impacts?

3.How do uncertainties in historical NTCF emissions affect radiative forcing estimates?

4. How important are climate feedbacks to natural NTCF emissions, atmospheric composition, and radiative effects?

These questions will be addressed through targeted simulations with CMIP6 climate models that include an interactive representation of tropospheric aerosols and atmospheric chemistry. These simulations build on the CMIP6 Diagnostic, Evaluation and Characterization of Klima (DECK) experiments, the CMIP6 historical simulations, and future projections performed elsewhere in CMIP6, allowing the contributions from aerosols and/or chemistry to be quantified. Specific diagnostics are requested as part of the CMIP6 data request to highlight the chemical composition of the atmosphere, to evaluate the performance of the models, and to understand differences in behaviour between them.

The Paris Agreement of December 2015 stated a goal to pursue efforts to keep global temperatures below 1.5°C above preindustrial levels and well below 2°C. The IPCC was charged with assessing climate impacts at these temperature levels, but fully coupled equilibrium climate simulations do not currently exist to inform such assessments. In this study, we produce a set of scenarios using a simple model designed to achieve long-term 1.5 and 2°C temperatures in a stable climate. These scenarios are then used to produce century-scale ensemble simulations using the Community Earth System Model, providing impact-relevant long-term climate data for stabilization pathways at 1.5 and 2°C levels and an overshoot 1.5°C case, which are realized (for the 21st century) in the coupled model and are freely available to the community. Here we describe the design of the simulations and a brief overview of their impact-relevant climate response. Exceedance of historical record temperature occurs with 60% greater frequency in the 2°C climate than in a 1.5°C climate aggregated globally, and with twice the frequency in equatorial and arid regions. Extreme precipitation intensity is statistically significantly higher in a 2.0°C climate than a 1.5°C climate in some specific regions (but not all). The model exhibits large differences in the Arctic, which is ice-free with a frequency of 1 in 3 years in the 2.0°C scenario, and 1 in 40 years in the 1.5°C scenario. Significance of impact differences with respect to multi-model variability is not assessed.

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 100km scale models with 2km 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.

Abstract. 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.

The Community Earth System Model (CESM1) CAM4-chem has been used to perform the Chemistry Climate Model Initiative (CCMI) reference and sensitivity simulations. In this model, the Community Atmospheric Model version 4 (CAM4) is fully coupled to tropospheric and stratospheric chemistry. Details and specifics of each configuration, including new developments and improvements are described. CESM1 CAM4-chem is a low-top model that reaches up to approximately 40km and uses a horizontal resolution of 1.9° latitude and 2.5° longitude. For the specified dynamics experiments, the model is nudged to Modern-Era Retrospective Analysis for Research and Applications (MERRA) reanalysis. We summarize the performance of the three reference simulations suggested by CCMI, with a focus on the last 15 years of the simulation when most observations are available. Comparisons with selected data sets are employed to demonstrate the general performance of the model. We highlight new data sets that are suited for multi-model evaluation studies. Most important improvements of the model are the treatment of stratospheric aerosols and the corresponding adjustments for radiation and optics, the updated chemistry scheme including improved polar chemistry and stratospheric dynamics and improved dry deposition rates. These updates lead to a very good representation of tropospheric ozone within 20% of values from available observations for most regions. In particular, the trend and magnitude of surface ozone is much improved compared to earlier versions of the model. Furthermore, stratospheric column ozone of the Southern Hemisphere in winter and spring is reasonably well represented. All experiments still underestimate CO most significantly in Northern Hemisphere spring and show a significant underestimation of hydrocarbons based on surface observations.

Halogenated very short lived substances (VSLS) affect the ozone budget in the atmosphere. Brominated VSLS are naturally emitted from the ocean, and current oceanic emission inventories vary dramatically. We present a new global oceanic emission inventory of Br-VSLS (bromoform and dibromomethane), considering the physical forcing in the ocean and the atmosphere, as well as the ocean biogeochemistry control. A data-oriented machine-learning emulator was developed to couple the air-sea exchange with the ocean biogeochemistry. The predicted surface seawater concentrations and the surface atmospheric mixing ratios of Br-VSLS are evaluated with long-term, global-scale observations; and the predicted vertical distributions of Br-VSLS are compared to the global airborne observations in both boreal summer and winter. The global marine emissions of bromoform and dibromomethane are estimated to be 385 and 54 Gg Br per year, respectively. The new oceanic emission inventory of Br-VSLS is more skillful than the widely used top-down approaches for representing the seasonal/spatial variations and the annual means of atmospheric concentrations. The new approach improves the model predictability for the coupled Earth system model and can be used as a basis for investigating the past and future ocean emissions and feedbacks under climate change. This model framework can be used to calculate the bidirectional oceanic fluxes for other compounds of interest.