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Abstract During polar spring, periods of elevated tropospheric bromine drive near complete removal of surface ozone. These events impact the tropospheric oxidative capacity and are an area of active research with multiple approaches for representing the underlying processes in global models. We present a method for parameterizing emissions of molecular bromine (Br2) over the Arctic using satellite retrievals of bromine monoxide (BrO) from the Ozone Monitoring Instrument (OMI). OMI retrieves column BrO with daily near global coverage, and we use the GEOS‐Chem chemical mechanism, run online within the Goddard Earth Observing System Earth System Model to identify hotspots of BrO likely associated with polar processes. To account for uncertainties in modeling background BrO, hotspots are only identified where the difference between OMI and modeled columns exceeds a statistical threshold. The resulting hotspot columns are a lower‐limit for the portion of OMI BrO attributable to bromine explosion events. While these hotspots are correlated with BrO measured in the lower troposphere over the Arctic Ocean, a case study of missing detections of near‐surface BrO is identified. Daily flux of Br2 is estimated from hotspot columns of BrO using internal model parameters. When the emissions are applied, BrO hotspots are modeled with a 5% low bias. The sensitivity of the resulting ozone simulations to the treatment of background uncertainties in the BrO column is demonstrated. While periods of isolated, large (>50%) decreases in surface ozone are modeled, this technique does not simulate the low ozone observed at coastal stations and consistently underestimates ozone loss during March.

The sixth phase of the Coupled Model Intercomparison Project (CMIP6) is the latest modeling effort for general circulation models to simulate and project various aspects of climate change. Many of the general circulation models (GCMs) participating in CMIP6 provide archived output that can be used to calculate effective climate sensitivity (ECS) and forecast future temperature change based on emissions scenarios from several Shared Socioeconomic Pathways (SSPs). Here we use our multiple linear regression energy balance model, the Empirical Model of Global Climate (EM-GC), to simulate and project changes in global mean surface temperature (GMST), calculate ECS, and compare to results from the CMIP6 multi-model ensemble. An important aspect of our study is a comprehensive analysis of uncertainties due to radiative forcing of climate from tropospheric aerosols (AER RF) in the EM-GC framework. We quantify the attributable anthropogenic warming rate (AAWR) from the climate record using the EM-GC and use AAWR as a metric to determine how well CMIP6 GCMs replicate human-driven global warming over the last 40 years. The CMIP6 multi-model ensemble indicates a median value of AAWR over 1975–2014 of 0.221 ∘C per decade (range of 0.151 to 0.299 ∘C per decade; all ranges given here are for 5th and 95th confidence intervals), which is notably faster warming than our median estimate for AAWR of 0.157 ∘C per decade (range of 0.120 to 0.195 ∘C per decade) inferred from the analysis of the Hadley Centre Climatic Research Unit version 5 data record for GMST. Estimates of ECS found using the EM-GC assuming that climate feedback does not vary over time (best estimate 2.33 ∘C; range of 1.40 to 3.57 ∘C) are generally consistent with the range of ECS of 1.5 to 4.5 ∘C given by the IPCC's Fifth Assessment Report. The CMIP6 multi-model ensemble exhibits considerably larger values of ECS (median 3.74 ∘C; range of 2.19 to 5.65 ∘C). Our best estimate of ECS increases to 3.08 ∘C (range of 2.23 to 5.53 ∘C) if we allow climate feedback to vary over time. The dominant factor in the uncertainty for our empirical determinations of AAWR and ECS is imprecise knowledge of AER RF for the contemporary atmosphere, though the uncertainty due to time-dependent climate feedback is also important for estimates of ECS. We calculate the likelihood of achieving the Paris Agreement target (1.5 ∘C) and upper limit (2.0 ∘C) of global warming relative to pre-industrial for seven of the SSPs using both the EM-GC and the CMIP6 multi-model ensemble. In our model framework, SSP1-2.6 has a 53 % probability of limiting warming at or below the Paris target by the end of the century, and SSP4-3.4 has a 64 % probability of achieving the Paris upper limit. These estimates are based on the assumptions that climate feedback has been and will remain constant over time since the prior temperature record can be fit so well assuming constant climate feedback. In addition, we quantify the sensitivity of future warming to the curbing of the current rapid growth of atmospheric methane and show that major near-term limits on the future growth of methane are especially important for achievement of the 1.5 ∘C goal of future warming. We also quantify warming scenarios assuming climate feedback will rise over time, a feature common among many CMIP6 GCMs; under this assumption, it becomes more difficult to achieve any specific warming target. Finally, we assess warming projections in terms of future anthropogenic emissions of atmospheric carbon. In our model framework, humans can emit only another 150±79 Gt C after 2019 to have a 66 % likelihood of limiting warming to 1.5 ∘C and another 400±104 Gt C to have the same probability of limiting warming to 2.0 ∘C. Given the estimated emission of 11.7 Gt C per year for 2019 due to combustion of fossil fuels and deforestation, our EM-GC simulations suggest that the 1.5 ∘C warming target of the Paris Agreement will not be achieved unless carbon and methane emissions are severely curtailed in the next 10 years.

To provide insight into the planetary boundary layer (PBL) production of ozone (O3) over the North China Plain, the Air chemistry Research in Asia (ARIAs) campaign conducted aircraft measurements of air pollutants over Hebei Province, China, between May and June 2016. We evaluate vertical profiles of trace gas species including O3, nitrogen oxides (NOx), carbon monoxide (CO), and volatile organic compounds (VOCs) and relate to rates of O3 production. This analysis shows measured O3 levels ranged from 45 to 146 ppbv, with the peak median concentration (∼ 92 ppbv) occurring between 1000 and 1500 m. The NOx concentrations exhibited strong spatial and altitudinal variations, with a maximum of 53 ppbv. Ratios of CO∕CO2 indicate the prevalence of low-efficiency combustion from biomass burning and residential coal burning but indicate some success of regional pollution controls compared to earlier studies in China. Concentrations of total measured VOCs reveal alkanes dominate the total measured volume mixing ratio of VOCs (68 %), and sources include vehicular emissions, fuel and solvent evaporation, and biomass burning. Alkanes and alkenes/alkynes are responsible for 74 % of the total VOC reactivity assessed by calculating the OH loss rates, while aromatics contribute the most to the total ozone formation potential (OFP) (43 %) with toluene, m/p-xylene, ethylene, propylene, and i-pentane playing significant roles in the aloft production of O3 in this region. In the PBL below 500 m, box model calculations constrained by measured precursors indicate the peak rate of mean O3 production was ∼ 7 ppbv h−1. Pollution frequently extended above the PBL into the lower free troposphere around 3000 m, where NO2 mixing ratios (∼ 400 pptv) led to net production rates of O3 up to ∼ 3 ppbv h−1; this pollution can travel substantial distances downwind. The O3 sensitivity regime is determined to be NOx-limited throughout the PBL, whereas it is more VOC-limited at low altitudes near urban centers, demonstrating that control of both VOCs and NOx is needed to reduce aloft O3 pollution over Hebei.

Reduced-complexity climate models (RCMs) are critical in the policy and decision making space, and are directly used within multiple Intergovernmental Panel on Climate Change (IPCC) reports to complement the results of more comprehensive Earth system models. To date, evaluation of RCMs has been limited to a few independent studies. Here we introduce a systematic evaluation of RCMs in the form of the Reduced Complexity Model Intercomparison Project (RCMIP). We expect RCMIP will extend over multiple phases, with Phase 1 being the first. In Phase 1, we focus on the RCMs' global-mean temperature responses, comparing them to observations, exploring the extent to which they emulate more complex models and considering how the relationship between temperature and cumulative emissions of CO2 varies across the RCMs. Our work uses experiments which mirror those found in the Coupled Model Intercomparison Project (CMIP), which focuses on complex Earth system and atmosphere–ocean general circulation models. Using both scenario-based and idealised experiments, we examine RCMs' global-mean temperature response under a range of forcings. We find that the RCMs can all reproduce the approximately 1 ∘C of warming since pre-industrial times, with varying representations of natural variability, volcanic eruptions and aerosols. We also find that RCMs can emulate the global-mean temperature response of CMIP models to within a root-mean-square error of 0.2 ∘C over a range of experiments. Furthermore, we find that, for the Representative Concentration Pathway (RCP) and Shared Socioeconomic Pathway (SSP)-based scenario pairs that share the same IPCC Fifth Assessment Report (AR5)-consistent stratospheric-adjusted radiative forcing, the RCMs indicate higher effective radiative forcings for the SSP-based scenarios and correspondingly higher temperatures when run with the same climate settings. In our idealised setup of RCMs with a climate sensitivity of 3 ∘C, the difference for the ssp585–rcp85 pair by 2100 is around 0.23∘C(±0.12 ∘C) due to a difference in effective radiative forcings between the two scenarios. Phase 1 demonstrates the utility of RCMIP's open-source infrastructure, paving the way for further phases of RCMIP to build on the research presented here and deepen our understanding of RCMs.

Future trajectories of the stratospheric trace gas background will alter the rates of bromine- and chlorine-mediated catalytic ozone destruction via changes in the partitioning of inorganic halogen reservoirs and the underlying temperature structure of the stratosphere. The current formulation of the bromine alpha factor, the ozone-destroying power of stratospheric bromine atoms relative to stratospheric chlorine atoms, is invariant with the climate state. Here, we refactor the bromine alpha factor, introducing normalization to a benchmark chemistry–climate state, and formulate Equivalent Effective Stratospheric Benchmark-normalized Chlorine (EESBnC) to reflect changes in the rates of both bromine- and chlorine-mediated ozone loss catalysis with time. We show that the ozone-processing power of the extrapolar stratosphere is significantly perturbed by future climate assumptions. Furthermore, we show that our EESBnC-based estimate of the extrapolar ozone recovery date is in closer agreement with extrapolar ozone recovery dates predicted using more sophisticated 3-D chemistry–climate models than predictions made using equivalent effective stratospheric chlorine (EESC).

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.

Abstract Over the last decades, climate science has evolved rapidly across multiple expert domains. Our best tools to capture state‐of‐the‐art knowledge in an internally self‐consistent modeling framework are the increasingly complex fully coupled Earth System Models (ESMs). However, computational limitations and the structural rigidity of ESMs mean that the full range of uncertainties across multiple domains are difficult to capture with ESMs alone. The tools of choice are instead more computationally efficient reduced complexity models (RCMs), which are structurally flexible and can span the response dynamics across a range of domain‐specific models and ESM experiments. Here we present Phase 2 of the Reduced Complexity Model Intercomparison Project (RCMIP Phase 2), the first comprehensive intercomparison of RCMs that are probabilistically calibrated with key benchmark ranges from specialized research communities. Unsurprisingly, but crucially, we find that models which have been constrained to reflect the key benchmarks better reflect the key benchmarks. Under the low‐emissions SSP1‐1.9 scenario, across the RCMs, median peak warming projections range from 1.3 to 1.7°C (relative to 1850–1900, using an observationally based historical warming estimate of 0.8°C between 1850–1900 and 1995–2014). Further developing methodologies to constrain these projection uncertainties seems paramount given the international community's goal to contain warming to below 1.5°C above preindustrial in the long‐term. Our findings suggest that users of RCMs should carefully evaluate their RCM, specifically its skill against key benchmarks and consider the need to include projections benchmarks either from ESM results or other assessments to reduce divergence in future projections.

We infer surface fluxes of bromoform (CHBr3) and dibromoform (CH2Br2) from aircraft observations over the western Pacific using a tagged version of the GEOS-Chem global 3-D atmospheric chemistry model and a maximum a posteriori inverse model. Using GEOS-Chem (GC) as an intermediary, we find that the distribution of a priori ocean emissions of these gases are reasonably consistent with observed atmospheric mole fractions of CHBr3 (r = 0.62) and CH2Br2 (r = 0.38). These a priori emissions result in a positive model bias in CHBr3 peaking in the marine boundary layer, but reproduce observed values of CH2Br2 with no significant bias by virtue of its longer atmospheric lifetime. Using GEOS-Chem, we find that observed variations in atmospheric CHBr3 are determined equally by sources over the western Pacific and those outside the study region, but observed variations in CH2Br2 are determined mainly by sources outside the western Pacific. Numerical closed-loop experiments show that the spatial and temporal distribution of boundary layer aircraft data have the potential to substantially improve current knowledge of these fluxes, with improvements related to data density. Using the aircraft data, we estimate aggregated regional fluxes of 3.6±0.3×108 and 0.7±0.1×108 g month−1 for CHBr3 and CH2Br2 over 130–155°E and 0–12° N, respectively, which represent reductions of 20 %–40 % of the prior inventories by Ordóñez et al. (2012) and substantial spatial deviations from different a priori inventories. We find no evidence to support a robust linear relationship between CHBr3 and CH2Br2 oceanic emissions, as used by previous studies. We find that over regions with dense observation coverage, our choice of a priori inventory does not significantly impact our reported a posteriori flux estimates.

We use the GEOS-Chem global 3-D atmospheric chemistry transport model to interpret atmospheric observations of bromoform (CHBr3) and dibromomethane (CH2Br2) collected during the CAST and CONTRAST aircraft measurement campaigns over the western Pacific, January–February 2014. We use a new linearized, tagged version of CHBr3 and CH2Br2, allowing us to study the influence of emissions from specific geographical regions on observed atmospheric variations. The model describes 32 %–37 % of CHBr3 and 15 %–45 % of CH2Br2 observed variability during CAST and CONTRAST, reflecting model errors in vertical transport. The model has a mean positive bias of 30 % that is larger near the surface, reflecting errors in the poorly constrained prior emission estimates. We find using the model that observed variability of CHBr3 and CH2Br2 is driven by open ocean emissions where there is deep convection. Atmospheric variability above 6 km includes a significant contribution from coastal oceans, but it is still dominated by emissions from the open ocean and by older air masses that originate upwind. In the absence of reliable ocean emission estimates, we use a new physical age-of-air simulation to determine the relative abundance of halogens delivered by CHBr3 and CH2Br2 to the tropical transition layer (TTL). We find that 76 % (92 %) of air masses that originate from the ocean reach the TTL within two (three) atmospheric e-folding lifetimes of CHBr3 and almost all of them reach the TTL within one e-folding lifetime of CH2Br2. Over the duration of CAST and CONTRAST, and over our study region, oceans delivered a mean (range) CHBr3 and CH2Br2 mole fraction of 0.46 (0.13–0.72) and 0.88 (0.71–1.01) pptv, respectively, to the TTL, and a mean (range) Bry mole fraction of 3.14 (1.81–4.18) pptv from source gases to the upper troposphere.

>We analyse simulations performed for the Chemistry-Climate Model Initiative (CCMI) to estimate the return dates of the stratospheric ozone layer from depletion caused by anthropogenic stratospheric chlorine and bromine. We consider a total of 155 simulations from 20 models, including a range of sensitivity studies which examine the impact of climate change on ozone recovery. For the control simulations (unconstrained by nudging towards analysed meteorology) there is a large spread (±20 DU in the global average) in the predictions of the absolute ozone column. Therefore, the model results need to be adjusted for biases against historical data. Also, the interannual variability in the model results need to be smoothed in order to provide a reasonably narrow estimate of the range of ozone return dates. Consistent with previous studies, but here for a Representative Concentration Pathway (RCP) of 6.0, these new CCMI simulations project that global total column ozone will return to 1980 values in 2049 (with a 1σ uncertainty of 2043–2055). At Southern Hemisphere mid-latitudes column ozone is projected to return to 1980 values in 2045 (2039–2050), and at Northern Hemisphere mid-latitudes in 2032 (2020–2044). In the polar regions, the return dates are 2060 (2055–2066) in the Antarctic in October and 2034 (2025–2043) in the Arctic in March. The earlier return dates in the Northern Hemisphere reflect the larger sensitivity to dynamical changes. Our estimates of return dates are later than those presented in the 2014 Ozone Assessment by approximately 5–17 years, depending on the region, with the previous best estimates often falling outside of our uncertainty range. In the tropics only around half the models predict a return of ozone to 1980 values, around 2040, while the other half do not reach the 1980 value. All models show a negative trend in tropical total column ozone towards the end of the 21st century. The CCMI models generally agree in their simulation of the time evolution of stratospheric chlorine and bromine, which are the main drivers of ozone loss and recovery. However, there are a few outliers which show that the multi-model mean results for ozone recovery are not as tightly constrained as possible. Throughout the stratosphere the spread of ozone return dates to 1980 values between models tends to correlate with the spread of the return of inorganic chlorine to 1980 values. In the upper stratosphere, greenhouse gas-induced cooling speeds up the return by about 10–20 years. In the lower stratosphere, and for the column, there is a more direct link in the timing of the return dates of ozone and chlorine, especially for the large Antarctic depletion. Comparisons of total column ozone between the models is affected by different predictions of the evolution of tropospheric ozone within the same scenario, presumably due to differing treatment of tropospheric chemistry. Therefore, for many scenarios, clear conclusions can only be drawn for stratospheric ozone columns rather than the total column. As noted by previous studies, the timing of ozone recovery is affected by the evolution of N2O and CH4. However, quantifying the effect in the simulations analysed here is limited by the few realisations available for these experiments compared to internal model variability. The large increase in N2O given in RCP 6.0 extends the ozone return globally by ∼ 15 years relative to N2O fixed at 1960 abundances, mainly because it allows tropical column ozone to be depleted. The effect in extratropical latitudes is much smaller. The large increase in CH4 given in the RCP 8.5 scenario compared to RCP 6.0 also lengthens ozone return by ∼ 15 years, again mainly through its impact in the tropics. Overall, our estimates of ozone return dates are uncertain due to both uncertainties in future scenarios, in particular those of greenhouse gases, and uncertainties in models. The scenario uncertainty is small in the short term but increases with time, and becomes large by the end of the century. There are still some model–model differences related to well-known processes which affect ozone recovery. Efforts need to continue to ensure that models used for assessment purposes accurately represent stratospheric chemistry and the prescribed scenarios of ozone-depleting substances, and only those models are used to calculate return dates. For future assessments of single forcing or combined effects of CO2, CH4, and N2O on the stratospheric column ozone return dates, this work suggests that it is more important to have multi-member (at least three) ensembles for each scenario from every established participating model, rather than a large number of individual models.

We report measurements of bromine monoxide (BrO) and use an observationally constrained chemical box model to infer total gas-phase inorganic bromine (Bry) over the tropical western Pacific Ocean (tWPO) during the CONTRAST field campaign (January–February 2014). The observed BrO and inferred Bry profiles peak in the marine boundary layer (MBL), suggesting the need for a bromine source from sea-salt aerosol (SSA), in addition to organic bromine (CBry). Both profiles are found to be C-shaped with local maxima in the upper free troposphere (FT). The median tropospheric BrO vertical column density (VCD) was measured as 1.6×1013 molec cm−2, compared to model predictions of 0.9×1013 molec cm−2 in GEOS-Chem (CBry but no SSA source), 0.4×1013 molec cm−2 in CAM-Chem (CBry and SSA), and 2.1×1013 molec cm−2 in GEOS-Chem (CBry and SSA). Neither global model fully captures the C-shape of the Bry profile. A local Bry maximum of 3.6 ppt (2.9–4.4 ppt; 95 % confidence interval, CI) is inferred between 9.5 and 13.5 km in air masses influenced by recent convective outflow. Unlike BrO, which increases from the convective tropical tropopause layer (TTL) to the aged TTL, gas-phase Bry decreases from the convective TTL to the aged TTL. Analysis of gas-phase Bry against multiple tracers (CFC-11, H2O ∕ O3 ratio, and potential temperature) reveals a Bry minimum of 2.7 ppt (2.3–3.1 ppt; 95 % CI) in the aged TTL, which agrees closely with a stratospheric injection of 2.6 ± 0.6 ppt of inorganic Bry (estimated from CFC-11 correlations), and is remarkably insensitive to assumptions about heterogeneous chemistry. Bry increases to 6.3 ppt (5.6–7.0 ppt; 95 % CI) in the stratospheric "middleworld" and 6.9 ppt (6.5–7.3 ppt; 95 % CI) in the stratospheric "overworld". The local Bry minimum in the aged TTL is qualitatively (but not quantitatively) captured by CAM-Chem, and suggests a more complex partitioning of gas-phase and aerosol Bry species than previously recognized. Our data provide corroborating evidence that inorganic bromine sources (e.g., SSA-derived gas-phase Bry) are needed to explain the gas-phase Bry budget in the upper free troposphere and TTL. They are also consistent with observations of significant bromide in Upper Troposphere–Lower Stratosphere aerosols. The total Bry budget in the TTL is currently not closed, because of the lack of concurrent quantitative measurements of gas-phase Bry species (i.e., BrO, HOBr, HBr, etc.) and aerosol bromide. Such simultaneous measurements are needed to (1) quantify SSA-derived Bry in the upper FT, (2) test Bry partitioning, and possibly explain the gas-phase Bry minimum in the aged TTL, (3) constrain heterogeneous reaction rates of bromine, and (4) account for all of the sources of Bry to the lower stratosphere.

Regulatory air quality models, such as the Community Multiscale Air Quality model (CMAQ), are used by federal and state agencies to guide policy decisions that determine how to best achieve adherence with National Ambient Air Quality Standards for surface ozone. We use observations of ozone and its important precursor NO2 to test the representation of the photochemistry and emission of ozone precursors within CMAQ. Observations of tropospheric column NO2 from the Ozone Monitoring Instrument (OMI), retrieved by two independent groups, show that the model overestimates urban NO2 and underestimates rural NO2 under all conditions examined for July and August 2011 in the US Northeast. The overestimate of the urban to rural ratio of tropospheric column NO2 for this baseline run of CMAQ (CB05 mechanism, mobile NOx emissions from the National Emissions Inventory; isoprene emissions from MEGAN v2.04) suggests this model may underestimate the importance of interstate transport of NOx. This CMAQ simulation leads to a considerable overestimate of the 2-month average of 8 h daily maximum surface ozone in the US Northeast, as well as an overestimate of 8 h ozone at AQS sites during days when the state of Maryland experienced NAAQS exceedances. We have implemented three changes within CMAQ motivated by OMI NO2 as well as aircraft observations obtained in July 2011 during the NASA DISCOVER-AQ campaign: (a) the modeled lifetime of organic nitrates within CB05 has been reduced by a factor of 10, (b) emissions of NOx from mobile sources has been reduced by a factor of 2, and (c) isoprene emissions have been reduced by using MEGAN v2.10 rather than v2.04. Compared to the baseline simulation, the CMAQ run using all three of these changes leads to considerably better simulation of column NO2 in both urban and rural areas, better agreement with the 2-month average of daily 8 h maximum ozone in the US Northeast, fewer number of false positives of an ozone exceedance throughout the domain, as well as an unbiased simulation of surface ozone at ground-based AQS sites in Maryland that experienced an ozone exceedance during July and August 2007. These modifications to CMAQ may provide a framework for use in studies focused on achieving future adherence to specific air quality standards for surface ozone by reducing emission of NOx from various anthropogenic sectors.

Very short-lived (VSL) bromocarbons are produced at a prodigious rate by ocean biology and these source compounds (SGVSL), together with their inorganic degradation products (PGVSL), are lofted by vigorous convection to the tropical tropopause layer (TTL). Using a state-of-the-art photochemical mechanism within a global model, we calculate annual average stratospheric injection of total bromine due to VSL sources to be 5 pptv (parts per trillion by volume), with ~ 3 pptv entering the stratosphere as PGVSL and ~ 2 pptv as SGVSL. The geographic distribution and partitioning of VSL bromine within the TTL, and its consequent stratospheric injection, is highly dependent on the oceanic flux, the strength of convection and the occurrence of heterogeneous recycling reactions. Our calculations indicate atomic Br should be the dominant inorganic species in large regions of the TTL during daytime, due to the low ozone and cold conditions of this region. We propose the existence of a "tropical ring of atomic bromine" located approximately between 15 and 19 km and between 30° N and 30° S. Daytime Br / BrO ratios of up to ~ 4 are predicted within this inhomogeneous ring in regions of highly convective transport, such as the tropical Western Pacific. Therefore, we suggest that experimental programs designed to quantify the bromine budget of the TTL and the stratospheric injection of VSL biogenic bromocarbons should include a strategy for the measurement of atomic Br during daytime as well as HOBr and BrCl during nighttime.