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The short-living cosmogenic isotope 7Be, which is produced by cosmic rays in the atmosphere, is often used as a tracer for atmospheric dynamics, with precise and high-resolution measurements covering the recent decades. The long-living isotope 10Be, as measured in polar ice cores with an annual resolution, is a proxy for long-term cosmic-ray variability, whose signal can, however, be distorted by atmospheric transport and deposition that need to be properly modeled to be accounted for. While transport of 7Be can be modeled with high accuracy using the known meteorological fields, atmospheric transport of 10Be was typically modeled using case-study-specific simulations or simplified box models based on parameterizations. Thus, there is a need for a realistic model able to simulate atmospheric transport and deposition of beryllium with a focus on polar regions and (inter)annual timescales that is potentially able to operate in a self-consistent mode without the prescribed meteorology. Since measurements of 10Be are extremely laborious and hence scarce, it is difficult to compare model results directly with measurement data. On the other hand, the two beryllium isotopes are believed to have similar transport and deposition properties, being different only in production and lifetime, and thus the results of 7Be transport can be generally applied to 10Be. Here we present a new model, called CCM SOCOL-AERv2-BE, to trace isotopes of 7Be and 10Be in the atmosphere based on the chemistry–climate model (CCM) SOCOL (SOlar Climate Ozone Links), which has been improved by including modules for the production, deposition, and transport of 7Be and 10Be. Production of the isotopes was modeled for both galactic and solar cosmic rays by applying the CRAC (Cosmic Ray Atmospheric Cascade) model. Transport of 7Be was modeled without additional gravitational settling due to the submicron size of the background aerosol particles. An interactive deposition scheme was applied including both wet and dry deposition. Modeling was performed using a full nudging to the meteorological fields for the period of 2002–2008 with a spin-up period of 1996–2001. The modeled concentrations of 7Be in near-ground air were compared with the measured ones at a weekly time resolution in four nearly antipodal high-latitude locations: two in the Northern (Finland and Canada) and two in the Southern (Chile and the Kerguelen Islands) Hemisphere. The model results agree with the measurements in the absolute level within error bars, implying that the production, decay, and lateral deposition are correctly reproduced. The model also correctly reproduces the temporal variability of 7Be concentrations on annual and sub-annual scales, including the presence and absence of the annual cycle in the Northern and Southern Hemisphere, respectively. We also modeled the production and transport of 7Be for a major solar energetic particle event (SPE) on 20 January 2005, which appears insufficient to produce a measurable signal but may serve as a reference event for historically known extreme SPEs. Thus, a new full 3D time-dependent model, based on CCM SOCOL, of 7Be and 10Be atmospheric production, transport, and deposition has been developed. Comparison with real data on the 7Be concentration in the near-ground air validates the model and its accuracy.

In this paper, we present a new version of the chemistry–climate model SOCOL-AERv2 supplemented by an iodine chemistry module. We perform three 20-year ensemble experiments to assess the validity of the modeled iodine and to quantify the effects of iodine on ozone. The iodine distributions obtained with SOCOL-AERv2-I agree well with AMAX-DOAS observations and with CAM-chem model simulations. For the present-day atmosphere, the model suggests that the iodine-induced chemistry leads to a 3 %–4 % reduction in the ozone column, which is greatest at high latitudes. The model indicates the strongest influence of iodine in the lower stratosphere with 30 ppbv less ozone at low latitudes and up to 100 ppbv less at high latitudes. In the troposphere, the account of the iodine chemistry reduces the tropospheric ozone concentration by 5 %–10 % depending on geographical location. In the lower troposphere, 75 % of the modeled ozone reduction originates from inorganic sources of iodine, 25 % from organic sources of iodine. At 50 hPa, the results show that the impacts of iodine from both sources are comparable. Finally, we determine the sensitivity of ozone to iodine by applying a 2-fold increase in iodine emissions, as it might be representative for iodine by the end of this century. This reduces the ozone column globally by an additional 1.5 %–2.5 %. Our results demonstrate the sensitivity of atmospheric ozone to iodine chemistry for present and future conditions, but uncertainties remain high due to the paucity of observational data of iodine species.

This paper features the new atmosphere–ocean–aerosol–chemistry–climate model, SOlar Climate Ozone Links (SOCOL) v4.0, and its validation. The new model was built by interactively coupling the Max Planck Institute Earth System Model version 1.2 (MPI-ESM1.2) (T63, L47) with the chemistry (99 species) and size-resolving (40 bins) sulfate aerosol microphysics modules from the aerosol–chemistry–climate model, SOCOL-AERv2. We evaluate its performance against reanalysis products and observations of atmospheric circulation, temperature, and trace gas distribution, with a focus on stratospheric processes. We show that SOCOLv4.0 captures the low- and midlatitude stratospheric ozone well in terms of the climatological state, variability and evolution. The model provides an accurate representation of climate change, showing a global surface warming trend consistent with observations as well as realistic cooling in the stratosphere caused by greenhouse gas emissions, although, as in previous model versions, a too-fast residual circulation and exaggerated mixing in the surf zone are still present. The stratospheric sulfur budget for moderate volcanic activity is well represented by the model, albeit with slightly underestimated aerosol lifetime after major eruptions. The presence of the interactive ocean and a successful representation of recent climate and ozone layer trends make SOCOLv4.0 ideal for studies devoted to future ozone evolution and effects of greenhouse gases and ozone-destroying substances, as well as the evaluation of potential solar geoengineering measures through sulfur injections. Potential further model improvements could be to increase the vertical resolution, which is expected to allow better meridional transport in the stratosphere, as well as to update the photolysis calculation module and budget of mesospheric odd nitrogen. In summary, this paper demonstrates that SOCOLv4.0 is well suited for applications related to the stratospheric ozone and sulfate aerosol evolution, including its participation in ongoing and future model intercomparison projects.

Water vapor (H2O) is the source of reactive hydrogen radicals in the middle atmosphere, whereas carbon monoxide (CO), being formed by CO2 photolysis, is suitable as a dynamical tracer. In the mesosphere, both H2O and CO are sensitive to solar irradiance (SI) variability because of their destruction/production by solar radiation. This enables us to analyze the solar signal in both models and observed data. Here, we evaluate the mesospheric H2O and CO response to solar irradiance variability using the Chemistry-Climate Model Initiative (CCMI-1) simulations and satellite observations. We analyzed the results of four CCMI models (CMAM, EMAC-L90MA, SOCOLv3, and CESM1-WACCM 3.5) operated in CCMI reference simulation REF-C1SD in specified dynamics mode, covering the period from 1984–2017. Multiple linear regression analyses show a pronounced and statistically robust response of H2O and CO to solar irradiance variability and to the annual and semiannual cycles. For periods with available satellite data, we compared the simulated solar signal against satellite observations, namely the GOZCARDS composite for 1992–2017 for H2O and Aura/MLS measurements for 2005–2017 for CO. The model results generally agree with observations and reproduce an expected negative and positive correlation for H2O and CO, respectively, with solar irradiance. However, the magnitude of the response and patterns of the solar signal varies among the considered models, indicating differences in the applied chemical reaction and dynamical schemes, including the representation of photolyzes. We suggest that there is no dominating thermospheric influence of solar irradiance in CO, as reported in previous studies, because the response to solar variability is comparable with observations in both low-top and high-top models. We stress the importance of this work for improving our understanding of the current ability and limitations of state-of-the-art models to simulate a solar signal in the chemistry and dynamics of the middle atmosphere.

This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made., Precipitating auroral and radiation belt electrons are considered an important part of the natural forcing of the climate system. Recent studies suggest that this forcing is underestimated in current chemistry-climate models. The High Energy Particle Precipitation in the Atmosphere III intercomparison experiment is a collective effort to address this point. Here, eight different estimates of medium energy electron (MEE) urn:x-wiley:21699380:media:jgra56926:jgra56926-math-0001 ionization rates are assessed during a geomagnetic active period in April 2010. The objective is to understand the potential uncertainty related to the MEE energy input. The ionization rates are all based on the Medium Energy Proton and Electron Detector (MEPED) on board the NOAA/POES and EUMETSAT/MetOp spacecraft series. However, different data handling, ionization rate calculations, and background atmospheres result in a wide range of mesospheric electron ionization rates. Although the eight data sets agree well in terms of the temporal variability, they differ by about an order of magnitude in ionization rate strength both during geomagnetic quiet and disturbed periods. The largest spread is found in the aftermath of enhanced geomagnetic activity. Furthermore, governed by different energy limits, the atmospheric penetration depth varies, and some differences related to latitudinal coverage are also evident. The mesospheric NO densities simulated with the Whole Atmospheric Community Climate Model driven by highest and lowest ionization rates differ by more than a factor of eight. In a follow-up study, the atmospheric responses are simulated in four chemistry-climate models (CCM) and compared to satellite observations, considering both the CCM structure and the ionization forcing. © 2021. The Authors., This study as well as the companion paper are a collaborative effort of the working group five: Medium Energy Electrons (MEE) Model-Measurement intercomparison of the SPARC Solaris-Heppa initiative, see solarisheppa.geomar.de. The authors thank the SPARC/WCRP for supporting the initial working group meetings. H. Nesse Tyssøy is supported by the Norwegian Research Council (NRC) under contract 223252 and 302040. S. Bender and C. Smith-Johnsen are also supported by the NRC under contract 223252. T. Asikainen is supported by the Academy of Finland (PROSPECT project no: 321440). B. Funke acknowledges financial support from the Agencia Estatal de Investigación of the Ministerio de Ciencia, Innovación y Universidades through projects ESP2017-87 143-R and PID2019-110689RB-I00, as well as the Centre of Excellence “Severo Ochoa” award to the Instituto de Astrofísica de Andalucía (SEV-2017-0709). J. Pettit's work is funded by NSF CEDAR grant AGS 1651 428. E.Rozanov's and T. Sukhodolov's work on the manuscript is done in the SPbSU “Ozone Layer and Upper Atmosphere Research Laboratory” supported by the Ministry of Science and Higher Education of the Russian Federation under agreement 075-15-2021-583 and was partly supported by German Russian cooperation project ”H-EPIC” funded by the Russian Foundation for Basic Research (RFBR project No 20-55-12 020). M. Sinnhuber work was partly supported by the German Research Foundation DFG (grant SI 1088/7-1). The work of P. T. Verronen is supported by the Academy of Finland (project No. 335 555 ICT-SUNVAC). The development of AISstom has been supported by the German Science Foundation (DFG; grant no. WI4417/2-1). J.M. Wissing is supported by the German Aerospace Center (DLR; grant no. D/921/67 284 894). M. Sinnhuber, M. A. Clilverd, B. Funke, C. E. Randall, C. J. Rodger, J. M. Wissing, and P. T. Verronen would like to thank the International Space Science Institute, Bern, Switzerland for supporting the project ”Quantifying Hemispheric Differences in Particle Forcing Effects on Stratospheric Ozone” (Leader: D. R. Marsh).

The modeling study presented here aims to estimate how uncertainties in global hydroxyl radical (OH) distributions, variability, and trends may contribute to resolving discrepancies between simulated and observed methane (CH4) changes since 2000. A multi-model ensemble of 14 OH fields was analyzed and aggregated into 64 scenarios to force the offline atmospheric chemistry transport model LMDz (Laboratoire de Meteorologie Dynamique) with a standard CH4 emission scenario over the period 2000–2016. The multi-model simulated global volume-weighted tropospheric mean OH concentration ([OH]) averaged over 2000–2010 ranges between 8.7×105 and 12.8×105 molec cm−3. The inter-model differences in tropospheric OH burden and vertical distributions are mainly determined by the differences in the nitrogen oxide (NO) distributions, while the spatial discrepancies between OH fields are mostly due to differences in natural emissions and volatile organic compound (VOC) chemistry. From 2000 to 2010, most simulated OH fields show an increase of 0.1–0.3×105 molec cm−3 in the tropospheric mean [OH], with year-to-year variations much smaller than during the historical period 1960–2000. Once ingested into the LMDz model, these OH changes translated into a 5 to 15 ppbv reduction in the CH4 mixing ratio in 2010, which represents 7 %–20 % of the model-simulated CH4 increase due to surface emissions. Between 2010 and 2016, the ensemble of simulations showed that OH changes could lead to a CH4 mixing ratio uncertainty of >±30 ppbv. Over the full 2000–2016 time period, using a common state-of-the-art but nonoptimized emission scenario, the impact of [OH] changes tested here can explain up to 54 % of the gap between model simulations and observations. This result emphasizes the importance of better representing OH abundance and variations in CH4 forward simulations and emission optimizations performed by atmospheric inversions.

We perform the first multi-model intercomparison of the impact of nudged meteorology on the stratospheric residual circulation using hindcast simulations from the Chemistry–Climate Model Initiative (CCMI). We examine simulations over the period 1980–2009 from seven models in which the meteorological fields are nudged towards a reanalysis dataset and compare these with their equivalent free-running simulations and the reanalyses themselves. We show that for the current implementations, nudging meteorology does not constrain the mean strength of the stratospheric residual circulation and that the inter-model spread is similar, or even larger, than in the free-running simulations. The nudged models generally show slightly stronger upwelling in the tropical lower stratosphere compared to the free-running versions and exhibit marked differences compared to the directly estimated residual circulation from the reanalysis dataset they are nudged towards. Downward control calculations applied to the nudged simulations reveal substantial differences between the climatological lower-stratospheric tropical upward mass flux (TUMF) computed from the modelled wave forcing and that calculated directly from the residual circulation. This explicitly shows that nudging decouples the wave forcing and the residual circulation so that the divergence of the angular momentum flux due to the mean motion is not balanced by eddy motions, as would typically be expected in the time mean. Overall, nudging meteorological fields leads to increased inter-model spread for most of the measures of the mean climatological stratospheric residual circulation assessed in this study. In contrast, the nudged simulations show a high degree of consistency in the inter-annual variability in the TUMF in the lower stratosphere, which is primarily related to the contribution to variability from the resolved wave forcing. The more consistent inter-annual variability in TUMF in the nudged models also compares more closely with the variability found in the reanalyses, particularly in boreal winter. We apply a multiple linear regression (MLR) model to separate the drivers of inter-annual and long-term variations in the simulated TUMF; this explains up to ∼75 % of the variance in TUMF in the nudged simulations. The MLR model reveals a statistically significant positive trend in TUMF for most models over the period 1980–2009. The TUMF trend magnitude is generally larger in the nudged models compared to their free-running counterparts, but the intermodel range of trends doubles from around a factor of 2 to a factor of 4 due to nudging. Furthermore, the nudged models generally do not match the TUMF trends in the reanalysis they are nudged towards for trends over different periods in the interval 1980–2009. Hence, we conclude that nudging does not strongly constrain long-term trends simulated by the chemistry–climate model (CCM) in the residual circulation. Our findings show that while nudged simulations may, by construction, produce accurate temperatures and realistic representations of fast horizontal transport, this is not typically the case for the slower zonal mean vertical transport in the stratosphere. Consequently, caution is required when using nudged simulations to interpret the behaviour of stratospheric tracers that are affected by the residual circulation.

SOCOL-AERv1 was developed as an aerosol–chemistry–climate model to study the stratospheric sulfur cycle and its influence on climate and the ozone layer. It includes a sectional aerosol model that tracks the sulfate particle size distribution in 40 size bins, between 0.39 nm and 3.2 µm. Sheng et al. (2015) showed that SOCOL-AERv1 successfully matched observable quantities related to stratospheric aerosol. In the meantime, SOCOL-AER has undergone significant improvements and more observational datasets have become available. In producing SOCOL-AERv2 we have implemented several updates to the model: adding interactive deposition schemes, improving the sulfate mass and particle number conservation, and expanding the tropospheric chemistry scheme. We compare the two versions of the model with background stratospheric sulfate aerosol observations, stratospheric aerosol evolution after Pinatubo, and ground-based sulfur deposition networks. SOCOL-AERv2 shows similar levels of agreement as SOCOL-AERv1 with satellite-measured extinctions and in situ optical particle counter (OPC) balloon flights. The volcanically quiescent total stratospheric aerosol burden simulated in SOCOL-AERv2 has increased from 109 Gg of sulfur (S) to 160 Gg S, matching the newly available satellite estimate of 165 Gg S. However, SOCOL-AERv2 simulates too high cross-tropopause transport of tropospheric SO2 and/or sulfate aerosol, leading to an overestimation of lower stratospheric aerosol. Due to the current lack of upper tropospheric SO2 measurements and the neglect of organic aerosol in the model, the lower stratospheric bias of SOCOL-AERv2 was not further improved. Model performance under volcanically perturbed conditions has also undergone some changes, resulting in a slightly shorter volcanic aerosol lifetime after the Pinatubo eruption. With the improved deposition schemes of SOCOL-AERv2, simulated sulfur wet deposition fluxes are within a factor of 2 of measured deposition fluxes at 78 % of the measurement stations globally, an agreement which is on par with previous model intercomparison studies. Because of these improvements, SOCOL-AERv2 will be better suited to studying changes in atmospheric sulfur deposition due to variations in climate and emissions.

We have derived values of the ultraviolet index (UVI) at solar noon using the Tropospheric Ultraviolet Model (TUV) driven by ozone, temperature and aerosol fields from climate simulations of the first phase of the Chemistry-Climate Model Initiative (CCMI-1). Since clouds remain one of the largest uncertainties in climate projections, we simulated only the clear-sky UVI. We compared the modelled UVI climatologies against present-day climatological values of UVI derived from both satellite data (the OMI-Aura OMUVBd product) and ground-based measurements (from the NDACC network). Depending on the region, relative differences between the UVI obtained from CCMI/TUV calculations and the ground-based measurements ranged between −5.9 % and 10.6 %. We then calculated the UVI evolution throughout the 21st century for the four Representative Concentration Pathways (RCPs 2.6, 4.5, 6.0 and 8.5). Compared to 1960s values, we found an average increase in the UVI in 2100 (of 2 %–4 %) in the tropical belt (30∘ N–30∘ S). For the mid-latitudes, we observed a 1.8 % to 3.4 % increase in the Southern Hemisphere for RCPs 2.6, 4.5 and 6.0 and found a 2.3 % decrease in RCP 8.5. Higher increases in UVI are projected in the Northern Hemisphere except for RCP 8.5. At high latitudes, ozone recovery is well identified and induces a complete return of mean UVI levels to 1960 values for RCP 8.5 in the Southern Hemisphere. In the Northern Hemisphere, UVI levels in 2100 are higher by 0.5 % to 5.5 % for RCPs 2.6, 4.5 and 6.0 and they are lower by 7.9 % for RCP 8.5. We analysed the impacts of greenhouse gases (GHGs) and ozone-depleting substances (ODSs) on UVI from 1960 by comparing CCMI sensitivity simulations (1960–2100) with fixed GHGs or ODSs at their respective 1960 levels. As expected with ODS fixed at their 1960 levels, there is no large decrease in ozone levels and consequently no sudden increase in UVI levels. With fixed GHG, we observed a delayed return of ozone to 1960 values, with a corresponding pattern of change observed on UVI, and looking at the UVI difference between 2090s values and 1960s values, we found an 8 % increase in the tropical belt during the summer of each hemisphere. Finally we show that, while in the Southern Hemisphere the UVI is mainly driven by total ozone column, in the Northern Hemisphere both total ozone column and aerosol optical depth drive UVI levels, with aerosol optical depth having twice as much influence on the UVI as total ozone column does.

Energetic particle precipitation (EPP) affects the chemistry of the polar middle atmosphere by producing reactive nitrogen (NOy) and hydrogen (HOx) species, which then catalytically destroy ozone. Recently, there have been major advances in constraining these particle impacts through a parametrization of NOy based on high-quality observations. Here we investigate the effects of low (auroral) and middle (radiation belt) energy range electrons, separately and in combination, on reactive nitrogen and hydrogen species as well as on ozone during Southern Hemisphere winters from 2002 to 2010 using the SOCOL3-MPIOM chemistry-climate model. Our results show that, in the absence of solar proton events, low-energy electrons produce the majority of NOy in the polar mesosphere and stratosphere. In the polar vortex, NOy subsides and affects ozone at lower altitudes, down to 10 hPa. Comparing a year with high electron precipitation with a quiescent period, we found large ozone depletion in the mesosphere; as the anomaly propagates downward, 15 % less ozone is found in the stratosphere during winter, which is confirmed by satellite observations. Only with both low- and middle-energy electrons does our model reproduce the observed stratospheric ozone anomaly.

Precipitating auroral and radiation belt electrons are considered to play an important part in the natural forcing of the middle atmosphere with a possible impact on the climate system. Recent studies suggest that this forcing is underestimated in current chemistry‐climate models. The HEPPA III intercomparison experiment is a collective effort to address this point. In this study, we apply electron ionization rates from three data‐sets in four chemistry‐climate models during a geomagnetically active period in April 2010. Results are evaluated by comparison with observations of nitric oxide (NO) in the mesosphere and lower thermosphere. Differences between the ionization rate data‐sets have been assessed in a companion study. In the lower thermosphere, NO densities differ by up to one order of magnitude between models using the same ionization rate data‐sets due to differences in the treatment of NO formation, model climatology, and model top height. However, a good agreement in the spatial and temporal variability of NO with observations lends confidence that the electron ionization is represented well above 80 km. In the mesosphere, the averages of model results from all chemistry‐climate models differ consistently with the differences in the ionization‐rate data‐sets, but are within the spread of the observations, so no clear assessment on their comparative validity can be provided. However, observed enhanced amounts of NO in the mid‐mesosphere below 70 km suggest a relevant contribution of the high‐energy tail of the electron distribution to the hemispheric NO budget during and after the geomagnetic storm on April 6., Key Points: Differences between multi‐model mean results at high latitudes are consistent with differences in the ionization rate data‐sets used. Electron precipitation above 80 km is well reproduced for all ionization rate data‐sets despite large differences between individual CCMs. Anisotropic precipitation from ≥300 keV electrons could provide up to 0.05–0.15 Gmol NO per hemisphere in storm main and recovery phase., Norwegian Research Council (NRC), Research Council of Norway, Agencia Estatal de Investigación of the Ministerio de Ciencia, Innovación y Universidades, Instituto de Astrofísica de Andalucía, Russian Foundation for Basic Research, Ministry of Science and Higher Education of the Russian Federation, Russian Science Foundation, Academy of Finland, German Aerospace Center, German Science Foundation, Ministry of Science, Research and the Arts Baden‐Württemberg, Federal Ministry of Education and Research, International Space Science Institute

An accurate quantification of the stratospheric ozone feedback in climate change simulations requires knowledge of the ozone response to increased greenhouse gases. Here, we present an analysis of the ozone layer response to an abrupt quadrupling of CO(2) concentrations in four chemistry-climate models. We show that increased CO(2) levels lead to a decrease in ozone concentrations in the tropical lower stratosphere, and an increase over the high latitudes and throughout the upper stratosphere. This pattern is robust across all models examined here, although important inter-model differences in the magnitude of the response are found. As a result of the cancellation between upper and lower stratospheric ozone, the total column ozone response in the tropics is small, and appears to be model dependent. A substantial portion of the spread in the tropical column ozone is tied to inter-model spread in upwelling. The high latitude ozone response is strongly seasonally dependent, and shows increases peaking in late-winter and spring of each hemisphere, with prominent longitudinal asymmetries. The range of ozone responses to CO(2) reported in this paper has the potential to induce significant radiative and dynamical effects on the simulated climate. Hence, these results highlight the need of using an ozone dataset consistent with CO(2) forcing in models involved in climate sensitivity studies.

International audience; Atmospheric electric fields (AEFs) are produced by both natural processes and electrical infrastructure and are increasingly recognized to influence and interfere with various organisms and biological processes, including human well-being. Atmospheric electric fields, in particular electromagnetic fields (EMFs), currently attract a lot of scientific attention due to emerging technologies such as 5G and satellite internet. However, a broader retrospective analysis of available data for both natural and artificial AEFs and EMFs is hampered due to a lack of a semantic approach, preventing data sharing and advancing our understanding of its intrinsic links. Therefore, here we create an ontology (ENET_Ont) for existing (big) data on AEFs within the context of biological systems that is derived from different disciplines that are distributed over many databases. Establishing an environment for data sharing provided by the proposed ontology approach will increase the value of existing data and facilitate reusability for other communities, especially those focusing on public health, ecology, environmental health, biology, climatology as well as bioinformatics.

Climate models consistently predict an acceleration of the Brewer–Dobson circulation (BDC) due to climate change in the 21st century. However, the strength of this acceleration varies considerably among individual models, which constitutes a notable source of uncertainty for future climate projections. To shed more light upon the magnitude of this uncertainty and on its causes, we analyse the stratospheric mean age of air (AoA) of 10 climate projection simulations from the Chemistry-Climate Model Initiative phase 1 (CCMI-I), covering the period between 1960 and 2100. In agreement with previous multi-model studies, we find a large model spread in the magnitude of the AoA trend over the simulation period. Differences between future and past AoA are found to be predominantly due to differences in mixing (reduced aging by mixing and recirculation) rather than differences in residual mean transport. We furthermore analyse the mixing efficiency, a measure of the relative strength of mixing for given residual mean transport, which was previously hypothesised to be a model constant. Here, the mixing efficiency is found to vary not only across models, but also over time in all models. Changes in mixing efficiency are shown to be closely related to changes in AoA and quantified to roughly contribute 10 % to the long-term AoA decrease over the 21st century. Additionally, mixing efficiency variations are shown to considerably enhance model spread in AoA changes. To understand these mixing efficiency variations, we also present a consistent dynamical framework based on diffusive closure, which highlights the role of basic state potential vorticity gradients in controlling mixing efficiency and therefore aging by mixing.

Previous multi-model intercomparisons have shown that chemistry–climate models exhibit significant biases in tropospheric ozone compared with observations. We investigate annual-mean tropospheric column ozone in 15 models participating in the SPARC–IGAC (Stratosphere–troposphere Processes And their Role in Climate–International Global Atmospheric Chemistry) Chemistry-Climate Model Initiative (CCMI). These models exhibit a positive bias, on average, of up to 40 %–50 % in the Northern Hemisphere compared with observations derived from the Ozone Monitoring Instrument and Microwave Limb Sounder (OMI/MLS), and a negative bias of up to ∼ 30 % in the Southern Hemisphere. SOCOLv3.0 (version 3 of the Solar-Climate Ozone Links CCM), which participated in CCMI, simulates global-mean tropospheric ozone columns of 40.2 DU – approximately 33 % larger than the CCMI multi-model mean. Here we introduce an updated version of SOCOLv3.0, SOCOLv3.1, which includes an improved treatment of ozone sink processes, and results in a reduction in the tropospheric column ozone bias of up to 8 DU, mostly due to the inclusion of N2O5 hydrolysis on tropospheric aerosols. As a result of these developments, tropospheric column ozone amounts simulated by SOCOLv3.1 are comparable with several other CCMI models. We apply Gaussian process emulation and sensitivity analysis to understand the remaining ozone bias in SOCOLv3.1. This shows that ozone precursors (nitrogen oxides (NOx), carbon monoxide, methane and other volatile organic compounds, VOCs) are responsible for more than 90 % of the variance in tropospheric ozone. However, it may not be the emissions inventories themselves that result in the bias, but how the emissions are handled in SOCOLv3.1, and we discuss this in the wider context of the other CCMI models. Given that the emissions data set to be used for phase 6 of the Coupled Model Intercomparison Project includes approximately 20 % more NOx than the data set used for CCMI, further work is urgently needed to address the challenges of simulating sub-grid processes of importance to tropospheric ozone in the current generation of chemistry–climate models.

Major mid-winter stratospheric sudden warmings (SSWs) are the largest instance of wintertime variability in the Arctic stratosphere. Because SSWs are able to cause significant surface weather anomalies on intra-seasonal timescales, several previous studies have focused on their potential future change, as might be induced by anthropogenic forcings. However, a wide range of results have been reported, from a future increase in the frequency of SSWs to an actual decrease. Several factors might explain these contradictory results, notably the use of different metrics for the identification of SSWs and the impact of large climatological biases in single-model studies. To bring some clarity, we here revisit the question of future SSW changes, using an identical set of metrics applied consistently across 12 different models participating in the Chemistry–Climate Model Initiative. Our analysis reveals that no statistically significant change in the frequency of SSWs will occur over the 21st century, irrespective of the metric used for the identification of the event. Changes in other SSW characteristics – such as their duration, deceleration of the polar night jet, and the tropospheric forcing – are also assessed: again, we find no evidence of future changes over the 21st century., Blanca Ayarzagüena was funded by the European Project 603557-STRATOCLIM under the FP7-ENV.2013.6.1-2 programme and “Ayudas para la contratación de personal postdoctoral en formación en docencia e investigación en departamentos de la Universidad Complutense de Madrid”. Blanca Ayarzagüena and Ulrike Langematz wish to acknowledge the Deutsche Forschungsgemeinschaft (DFG) within the research programme SHARP under the grant LA 1025/15-1. Lorenzo M. Polvani is grateful for the continued support of the US National Science Foundation. The work of Neal Butchart, Steven C. Hardiman, and Fiona M. O'Connor was supported by the Joint BEIS/Defra Met Office Hadley Centre Climate Programme (GA01101). Neal Butchart and Steven C. Hardiman were supported by the European Community within the StratoClim project (grant 603557). Olaf Morgenstern and Guang Zeng acknowledge the UK Met Office for use of the Met Office Unified Model (MetUM). This research was supported by the New Zealand Government's Strategic Science Investment Fund (SSIF) through the NIWA programme CACV. Olaf Morgenstern acknowledges funding by the New Zealand Royal Society Marsden Fund (grant 12-NIW-006) and by the Deep South National Science Challenge (http://www.deepsouthchallenge.co.nz, last access: 21 March 2018). The authors wish to acknowledge the contribution of New Zealand eScience Infrastructure (NeSI) high-performance computing (HPC) facilities to the results of this research. New Zealand's national facilities are provided by NeSI and funded jointly by NeSI's collaborator institutions and through the Ministry of Business, Innovation & Employment's Research Infrastructure programme (https://www.nesi.org.nz, last access: 21 March 2018). The EMAC simulations were performed at the German Climate Computing Centre (DKRZ) through support from the Bundesministerium für Bildung und Forschung (BMBF). DKRZ and its Scientific Steering Committee are gratefully acknowledged for providing the HPC and data archiving resources for the consortial project ESCiMo (Earth System Chemistry integrated Modelling). CCSRNIES's research was supported by the Environment Research and Technology Development Funds of the Ministry of the Environment (2-1303) and Environment Restoration and Conservation Agency (2-1709), Japan, and computations were performed on NEC-SX9/A(ECO) and NEC SX-ACE computers at the Center for Global Environmental Research, NIES. The authors wish to thank two anonymous referees for their helpful comments.

We evaluate how the coupled aerosol–chemistry–climate model SOCOL-AERv1.0 represents the influence of the 1991 eruption of Mt. Pinatubo on stratospheric aerosol properties and atmospheric state. The aerosol module is coupled to the radiative and chemical modules and includes comprehensive sulfur chemistry and microphysics, in which the particle size distribution is represented by 40 size bins with radii spanning from 0.39 nm to 3.2 µm. SOCOL-AER simulations are compared with satellite and in situ measurements of aerosol parameters, temperature reanalyses, and ozone observations. In addition to the reference model configuration, we performed series of sensitivity experiments looking at different processes affecting the aerosol layer. An accurate sedimentation scheme is found to be essential to prevent particles from diffusing too rapidly to high and low altitudes. The aerosol radiative feedback and the use of a nudged quasi-biennial oscillation help to keep aerosol in the tropics and significantly affect the evolution of the stratospheric aerosol burden, which improves the agreement with observed aerosol mass distributions. The inclusion of van der Waals forces in the particle coagulation scheme suggests improvements in particle effective radius, although other parameters (such as aerosol longevity) deteriorate. Modification of the Pinatubo sulfur emission rate also improves some aerosol parameters, while it worsens others compared to observations. Observations themselves are highly uncertain and render it difficult to conclusively judge the necessity of further model reconfiguration. The model revealed problems in reproducing aerosol sizes above 25 km and also in capturing certain features of the ozone response. Besides this, our results show that SOCOL-AER is capable of predicting the most important global-scale atmospheric effects following volcanic eruptions, which is also a prerequisite for an improved understanding of solar geoengineering effects from sulfur injections to the stratosphere.

The stratospheric age of air (AoA) is a useful measure of the overall capabilities of a general circulation model (GCM) to simulate stratospheric transport. Previous studies have reported a large spread in the simulation of AoA by GCMs and coupled chemistry–climate models (CCMs). Compared to observational estimates, simulated AoA is mostly too low. Here we attempt to untangle the processes that lead to the AoA differences between the models and between models and observations. AoA is influenced by both mean transport by the residual circulation and two-way mixing; we quantify the effects of these processes using data from the CCM inter-comparison projects CCMVal-2 (Chemistry–Climate Model Validation Activity 2) and CCMI-1 (Chemistry–Climate Model Initiative, phase 1). Transport along the residual circulation is measured by the residual circulation transit time (RCTT). We interpret the difference between AoA and RCTT as additional aging by mixing. Aging by mixing thus includes mixing on both the resolved and subgrid scale. We find that the spread in AoA between the models is primarily caused by differences in the effects of mixing and only to some extent by differences in residual circulation strength. These effects are quantified by the mixing efficiency, a measure of the relative increase in AoA by mixing. The mixing efficiency varies strongly between the models from 0.24 to 1.02. We show that the mixing efficiency is not only controlled by horizontal mixing, but by vertical mixing and vertical diffusion as well. Possible causes for the differences in the models' mixing efficiencies are discussed. Differences in subgrid-scale mixing (including differences in advection schemes and model resolutions) likely contribute to the differences in mixing efficiency. However, differences in the relative contribution of resolved versus parameterized wave forcing do not appear to be related to differences in mixing efficiency or AoA.

Continued anthropogenic greenhouse gas (GHG) emissions are expected to cause further global warming throughout the 21st century. Understanding the role of natural forcings and their influence on global warming is thus of great interest. Here we investigate the impact of a recently proposed 21st century grand solar minimum on atmospheric chemistry and climate using the SOCOL3-MPIOM chemistry–climate model with an interactive ocean element. We examine five model simulations for the period 2000–2199, following the greenhouse gas concentration scenario RCP4.5 and a range of different solar forcings. The reference simulation is forced by perpetual repetition of solar cycle 23 until the year 2199. This reference is compared with grand solar minimum simulations, assuming a strong decline in solar activity of 3.5 and 6.5 W m−2, respectively, that last either until 2199 or recover in the 22nd century. Decreased solar activity by 6.5 W m−2 is found to yield up to a doubling of the GHG-induced stratospheric and mesospheric cooling. Under the grand solar minimum scenario, tropospheric temperatures are also projected to decrease compared to the reference. On the global scale a reduced solar forcing compensates for at most 15 % of the expected greenhouse warming at the end of the 21st and around 25 % at the end of the 22nd century. The regional effects are predicted to be significant, in particular in northern high-latitude winter. In the stratosphere, the reduction of around 15 % of incoming ultraviolet radiation leads to a decrease in ozone production by up to 8 %, which overcompensates for the anticipated ozone increase due to reduced stratospheric temperatures and an acceleration of the Brewer–Dobson circulation. This, in turn, leads to a delay in total ozone column recovery from anthropogenic halogen-induced depletion, with a global ozone recovery to the pre-ozone hole values happening only upon completion of the grand solar minimum.

The eruption of Mt. Tambora in 1815 was the largest volcanic eruption of the past 500 years. The eruption had significant climatic impacts, leading to the 1816 year without a summer, and remains a valuable event from which to understand the climatic effects of large stratospheric volcanic sulfur dioxide injections. The eruption also resulted in one of the strongest and most easily identifiable volcanic sulfate signals in polar ice cores, which are widely used to reconstruct the timing and atmospheric sulfate loading of past eruptions. As part of the Model Intercomparison Project on the climatic response to Volcanic forcing (VolMIP), five state-of-the-art global aerosol models simulated this eruption. We analyse both simulated background (no Tambora) and volcanic (with Tambora) sulfate deposition to polar regions and compare to ice core records. The models simulate overall similar patterns of background sulfate deposition, although there are differences in regional details and magnitude. However, the volcanic sulfate deposition varies considerably between the models with differences in timing, spatial pattern and magnitude. Mean simulated deposited sulfate on Antarctica ranges from 19 to 264 kg km−2 and on Greenland from 31 to 194 kg km−2, as compared to the mean ice-core-derived estimates of roughly 50 kg km−2 for both Greenland and Antarctica. The ratio of the hemispheric atmospheric sulfate aerosol burden after the eruption to the average ice sheet deposited sulfate varies between models by up to a factor of 15. Sources of this inter-model variability include differences in both the formation and the transport of sulfate aerosol. Our results suggest that deriving relationships between sulfate deposited on ice sheets and atmospheric sulfate burdens from model simulations may be associated with greater uncertainties than previously thought.

To simulate the impacts of volcanic eruptions on the stratosphere, chemistry–climate models that do not include an online aerosol module require temporally and spatially resolved aerosol size parameters for heterogeneous chemistry and aerosol radiative properties as a function of wavelength. For phase 1 of the Chemistry-Climate Model Initiative (CCMI-1) and, later, for phase 6 of the Coupled Model Intercomparison Project (CMIP6) two such stratospheric aerosol data sets were compiled, whose functional capability and representativeness are compared here. For CCMI-1, the SAGE-4λ data set was compiled, which hinges on the measurements at four wavelengths of the SAGE (Stratospheric Aerosol and Gas Experiment) II satellite instrument and uses ground-based lidar measurements for gap-filling immediately after the 1991 Mt Pinatubo eruption, when the stratosphere was too optically opaque for SAGE II. For CMIP6, the new SAGE-3λ data set was compiled, which excludes the least reliable SAGE II wavelength and uses measurements from CLAES (Cryogenic Limb Array Etalon Spectrometer) on UARS, the Upper Atmosphere Research Satellite, for gap-filling following the Mt Pinatubo eruption instead of ground-based lidars. Here, we performed SOCOLv3 (Solar Climate Ozone Links version 3) chemistry–climate model simulations of the recent past (1986–2005) to investigate the impact of the Mt Pinatubo eruption in 1991 on stratospheric temperature and ozone and how this response differs depending on which aerosol data set is applied. The use of SAGE-4λ results in heating and ozone loss being overestimated in the tropical lower stratosphere compared to observations in the post-eruption period by approximately 3 K and 0.2 ppmv, respectively. However, less heating occurs in the model simulations based on SAGE-3λ, because the improved gap-filling procedures after the eruption lead to less aerosol loading in the tropical lower stratosphere. As a result, simulated tropical temperature anomalies in the model simulations based on SAGE-3λ for CMIP6 are in excellent agreement with MERRA and ERA-Interim reanalyses in the post-eruption period. Less heating in the simulations with SAGE-3λ means that the rate of tropical upwelling does not strengthen as much as it does in the simulations with SAGE-4λ, which limits dynamical uplift of ozone and therefore provides more time for ozone to accumulate in tropical mid-stratospheric air. Ozone loss following the Mt Pinatubo eruption is overestimated by up to 0.1 ppmv in the model simulations based on SAGE-3λ, which is a better agreement with observations than in the simulations based on SAGE-4λ. Overall, the CMIP6 stratospheric aerosol data set, SAGE-3λ, allows SOCOLv3 to more accurately simulate the post-Pinatubo eruption period.

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.

As part of the Model Intercomparison Project on the climatic response to Volcanic forcing (VolMIP), several climate modeling centers performed a coordinated pre-study experiment with interactive stratospheric aerosol models simulating the volcanic aerosol cloud from an eruption resembling the 1815 Mt. Tambora eruption (VolMIP-Tambora ISA ensemble). The pre-study provided the ancillary ability to assess intermodel diversity in the radiative forcing for a large stratospheric-injecting equatorial eruption when the volcanic aerosol cloud is simulated interactively. An initial analysis of the VolMIP-Tambora ISA ensemble showed large disparities between models in the stratospheric global mean aerosol optical depth (AOD). In this study, we now show that stratospheric global mean AOD differences among the participating models are primarily due to differences in aerosol size, which we track here by effective radius. We identify specific physical and chemical processes that are missing in some models and/or parameterized differently between models, which are together causing the differences in effective radius. In particular, our analysis indicates that interactively tracking hydroxyl radical (OH) chemistry following a large volcanic injection of sulfur dioxide (SO2) is an important factor in allowing for the timescale for sulfate formation to be properly simulated. In addition, depending on the timescale of sulfate formation, there can be a large difference in effective radius and subsequently AOD that results from whether the SO2 is injected in a single model grid cell near the location of the volcanic eruption, or whether it is injected as a longitudinally averaged band around the Earth.

Effects of the Quasi-Biennial Oscillation (QBO) on tropospheric climate are not always strong or they appear only intermittently. Studying them requires long time series of both the QBO and climate variables, which has restricted previous studies to the past 30–50 years. Here we use the benefits of an existing QBO reconstruction back to 1908. We first investigate additional, newly digitized historical observations of stratospheric winds to test the reconstruction. Then we use the QBO time series to analyse atmospheric data sets (reconstructions and reanalyses) as well as the results of coupled ocean–atmosphere–chemistry climate model simulations that were forced with the reconstructed QBO. We investigate effects related to (1) tropical–extratropical interaction in the stratosphere, wave–mean flow interaction and subsequent downward propagation, and (2) interaction between deep tropical convection and stratospheric flow. We generally find weak connections, though some are statistically significant over the 100-year period and consistent with model results. Apparent multidecadal variations in the connection between the QBO and the investigated climate responses are consistent with a small effect in the presence of large variability, with one exception: the imprint on the northern polar vortex, which is seen in recent reanalysis data, is not found in the period 1908–1957. Conversely, an imprint in Berlin surface air temperature is only found in 1908–1957 but not in the recent period. Likewise, in the model simulations both links tend to appear alternatingly, suggesting a more systematic modulation due to a shift in the circulation, for example. Over the Pacific warm pool, we find increased convection during easterly QBO, mainly in boreal winter in observation-based data as well as in the model simulations, with large variability. No QBO effects were found in the Indian monsoon strength or Atlantic hurricane frequency.

Stratospheric water vapour (SWV) is an important component of the Earth's atmosphere as it affects both radiative balance and the chemistry of the atmosphere. Key processes driving changes in SWV include dehydration of air masses transiting the cold-point tropopause (CPT) and methane oxidation. We use a chemistry–climate model to simulate changes in SWV through the 21st century following the four canonical representative concentration pathways (RCPs). Furthermore, we quantify the contribution that methane oxidation makes to SWV following each of the RCPs. Although the methane contribution to SWV maximizes in the upper stratosphere, modelled SWV trends are found to be driven predominantly by warming of the CPT rather than by increasing methane oxidation. SWV changes by −5 to 60 % (depending on the location in the atmosphere and emissions scenario) and increases in the lower stratosphere in all RCPs through the 21st century. Because the lower stratosphere is where water vapour radiative forcing maximizes, SWV's influence on surface climate is also expected to increase through the 21st century.

Understanding and modeling the large-scale transport of trace gases and aerosols is important for interpreting past (and projecting future) changes in atmospheric composition. Here we show that there are large differences in the global-scale atmospheric transport properties among the models participating in the IGAC SPARC Chemistry–Climate Model Initiative (CCMI). Specifically, we find up to 40 % differences in the transport timescales connecting the Northern Hemisphere (NH) midlatitude surface to the Arctic and to Southern Hemisphere high latitudes, where the mean age ranges between 1.7 and 2.6 years. We show that these differences are related to large differences in vertical transport among the simulations, in particular to differences in parameterized convection over the oceans. While stronger convection over NH midlatitudes is associated with slower transport to the Arctic, stronger convection in the tropics and subtropics is associated with faster interhemispheric transport. We also show that the differences among simulations constrained with fields derived from the same reanalysis products are as large as (and in some cases larger than) the differences among free-running simulations, most likely due to larger differences in parameterized convection. Our results indicate that care must be taken when using simulations constrained with analyzed winds to interpret the influence of meteorology on tropospheric composition.

>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.

Ozone fields simulated for the first phase of the Chemistry-Climate Model Initiative (CCMI-1) will be used as forcing data in the 6th Coupled Model Intercomparison Project. Here we assess, using reference and sensitivity simulations produced for CCMI-1, the suitability of CCMI-1 model results for this process, investigating the degree of consistency amongst models regarding their responses to variations in individual forcings. We consider the influences of methane, nitrous oxide, a combination of chlorinated or brominated ozone-depleting substances, and a combination of carbon dioxide and other greenhouse gases. We find varying degrees of consistency in the models' responses in ozone to these individual forcings, including some considerable disagreement. In particular, the response of total-column ozone to these forcings is less consistent across the multi-model ensemble than profile comparisons. We analyse how stratospheric age of air, a commonly used diagnostic of stratospheric transport, responds to the forcings. For this diagnostic we find some salient differences in model behaviour, which may explain some of the findings for ozone. The findings imply that the ozone fields derived from CCMI-1 are subject to considerable uncertainties regarding the impacts of these anthropogenic forcings. We offer some thoughts on how to best approach the problem of generating a consensus ozone database from a multi-model ensemble such as CCMI-1.

The impact of changes in incoming solar irradiance on stratospheric ozone abundances should be included in climate simulations to aid in capturing the atmospheric response to solar cycle variability. This study presents the first systematic comparison of the representation of the 11-year solar cycle ozone response (SOR) in chemistry–climate models (CCMs) and in pre-calculated ozone databases specified in climate models that do not include chemistry, with a special focus on comparing the recommended protocols for the Coupled Model Intercomparison Project Phase 5 and Phase 6 (CMIP5 and CMIP6). We analyse the SOR in eight CCMs from the Chemistry–Climate Model Initiative (CCMI-1) and compare these with results from three ozone databases for climate models: the Bodeker Scientific ozone database, the SPARC/Atmospheric Chemistry and Climate (AC&C) ozone database for CMIP5 and the SPARC/CCMI ozone database for CMIP6. The peak amplitude of the annual mean SOR in the tropical upper stratosphere (1–5 hPa) decreases by more than a factor of 2, from around 5 to 2 %, between the CMIP5 and CMIP6 ozone databases. This substantial decrease can be traced to the CMIP5 ozone database being constructed from a regression model fit to satellite and ozonesonde measurements, while the CMIP6 database is constructed from CCM simulations. The SOR in the CMIP6 ozone database therefore implicitly resembles the SOR in the CCMI-1 models. The structure in latitude of the SOR in the CMIP6 ozone database and CCMI-1 models is considerably smoother than in the CMIP5 database, which shows unrealistic sharp gradients in the SOR across the middle latitudes owing to the paucity of long-term ozone measurements in polar regions. The SORs in the CMIP6 ozone database and the CCMI-1 models show a seasonal dependence with enhanced meridional gradients at mid- to high latitudes in the winter hemisphere. The CMIP5 ozone database does not account for seasonal variations in the SOR, which is unrealistic. Sensitivity experiments with a global atmospheric model without chemistry (ECHAM6.3) are performed to assess the atmospheric impacts of changes in the representation of the SOR and solar spectral irradiance (SSI) forcing between CMIP5 and CMIP6. The larger amplitude of the SOR in the CMIP5 ozone database compared to CMIP6 causes a likely overestimation of the modelled tropical stratospheric temperature response between 11-year solar cycle minimum and maximum by up to 0.55 K, or around 80 % of the total amplitude. This effect is substantially larger than the change in temperature response due to differences in SSI forcing between CMIP5 and CMIP6. The results emphasize the importance of adequately representing the SOR in global models to capture the impact of the 11-year solar cycle on the atmosphere. Since a number of limitations in the representation of the SOR in the CMIP5 ozone database have been identified, we recommend that CMIP6 models without chemistry use the CMIP6 ozone database and the CMIP6 SSI dataset to better capture the climate impacts of solar variability. The SOR coefficients from the CMIP6 ozone database are published with this paper.

The calculations of electron beam characteristics in the accelerator of sterilization installation with the local radiation shielding in relation to the use of a magnetron with a larger pulse power are made. It is shown that a simple method on the basis of “moving” of cathode- heating unit toward the anode plane of the injector may be used for increasing of current and power of accelerated beam.

Through the 21st century, anthropogenic emissions of the greenhouse gases N2O and CH4 are projected to increase, thus increasing their atmospheric concentrations. Consequently, reactive nitrogen species produced from N2O and reactive hydrogen species produced from CH4 are expected to play an increasingly important role in determining stratospheric ozone concentrations. Eight chemistry-climate model simulations were performed to assess the sensitivity of stratospheric ozone to different emissions scenarios for N2O and CH4. Global-mean total column ozone increases through the 21st century in all eight simulations as a result of CO2-induced stratospheric cooling and decreasing stratospheric halogen concentrations. Larger N2O concentrations were associated with smaller ozone increases, due to reactive nitrogen-mediated ozone destruction. In the simulation with the largest N2O increase, global-mean total column ozone increased by 4.3 DU through the 21st century, compared with 10.0 DU in the simulation with the smallest N2O increase. In contrast, larger CH4 concentrations were associated with larger ozone increases; global-mean total column ozone increased by 16.7 DU through the 21st century in the simulation with the largest CH4 concentrations and by 4.4 DU in the simulation with the lowest CH4 concentrations. CH4 leads to ozone loss in the upper and lower stratosphere by increasing the rate of reactive hydrogen-mediated ozone loss cycles, however in the lower stratosphere and troposphere, CH4 leads to ozone increases due to photochemical smog-type chemistry. In addition to this mechanism, total column ozone increases due to H2O-induced cooling of the stratosphere, and slowing of the chlorine-catalyzed ozone loss cycles due to an increased rate of the CH4 + Cl reaction. Stratospheric column ozone through the 21st century exhibits a near-linear response to changes in N2O and CH4 surface concentrations, which provides a simple parameterization for the ozone response to changes in these gases.

Time series of total column abundances of hydrogen chloride (HCl), chlorine nitrate (ClONO2), and hydrogen fluoride (HF) were determined from ground-based Fourier transform infrared (FTIR) spectra recorded at 17 sites belonging to the Network for the Detection of Atmospheric Composition Change (NDACC) and located between 80.05° N and 77.82° S. By providing such a near-global overview on ground-based measurements of the two major stratospheric chlorine reservoir species, HCl and ClONO2, the present study is able to confirm the decrease of the atmospheric inorganic chlorine abundance during the last few years. This decrease is expected following the 1987 Montreal Protocol and its amendments and adjustments, where restrictions and a subsequent phase-out of the prominent anthropogenic chlorine source gases (solvents, chlorofluorocarbons) were agreed upon to enable a stabilisation and recovery of the stratospheric ozone layer. The atmospheric fluorine content is expected to be influenced by the Montreal Protocol, too, because most of the banned anthropogenic gases also represent important fluorine sources. But many of the substitutes to the banned gases also contain fluorine so that the HF total column abundance is expected to have continued to increase during the last few years. The measurements are compared with calculations from five different models: the two-dimensional Bremen model, the two chemistry-transport models KASIMA and SLIMCAT, and the two chemistry-climate models EMAC and SOCOL. Thereby, the ability of the models to reproduce the absolute total column amounts, the seasonal cycles, and the temporal evolution found in the FTIR measurements is investigated and inter-compared. This is especially interesting because the models have different architectures. The overall agreement between the measurements and models for the total column abundances and the seasonal cycles is good. Linear trends of HCl, ClONO2, and HF are calculated from both measurement and model time series data, with a focus on the time range 2000–2009. This period is chosen because from most of the measurement sites taking part in this study, data are available during these years. The precision of the trends is estimated with the bootstrap resampling method. The sensitivity of the trend results with respect to the fitting function, the time of year chosen and time series length is investigated, as well as a bias due to the irregular sampling of the measurements. The measurements and model results investigated here agree qualitatively on a decrease of the chlorine species by around 1% yr−1. The models simulate an increase of HF of around 1% yr−1. This also agrees well with most of the measurements, but some of the FTIR series in the Northern Hemisphere show a stabilisation or even a decrease in the last few years. In general, for all three gases, the measured trends vary more strongly with latitude and hemisphere than the modelled trends. Relative to the FTIR measurements, the models tend to underestimate the decreasing chlorine trends and to overestimate the fluorine increase in the Northern Hemisphere. At most sites, the models simulate a stronger decrease of ClONO2 than of HCl. In the FTIR measurements, this difference between the trends of HCl and ClONO2 depends strongly on latitude, especially in the Northern Hemisphere.

Apoptosis plays a role in the elimination of DNA-damaged cells thus protecting the host from cancer development. Some data indicate that normal variations within the sequence of apoptotic genes may lead to suboptimal apoptotic capacity and therefore increased cancer risk. We tested 19 coding apoptotic gene SNPs in 2-stage molecular epidemiological study. For the preliminary sorting of SNP candidates, we employed a “comparison of extremes” approach, where 111 patients with highly pronounced LC susceptibility (non-smokers or young-onset light smokers) were analyzed against 110 subjects with the evidence for LC tolerance (elderly tumor-free heavy smokers). Three genotypes demonstrated possible association with LC risk (Leu/Leu-homozygotes for Casp5 Val318Leu versus other genotypes: OR = 2.47 (95% CI: 1.07–5.69), p = 0.03; His-carriers for Casp8 His302Asp: OR = 2.26 (95% CI: 1.18–4.31), p = 0.02; Arg-carriers for DR4 Lys441Arg: OR = 1.89 (95% CI: 1.05–3.40), p = 0.03), and therefore were selected for the validation. The extended study included 2 case-control series, namely subjects from Russia (351 LC cases and 538 controls) and Moldova (296 LC cases and 295 controls). Interestingly, all three candidate genotypes consistently demonstrated OR above 1 both in Russian and in Moldovian groups. Although the combined Mantel–Haenszel analysis yet failed to reach statistical significance (OR = 1.22 (95% CI: 0.90–1.65), p = 0.21; OR = 1.17 (95% CI: 0.92–1.50), p = 0.21; OR = 1.19 (95% CI: 0.95–1.51), p = 0.14, respectively), the obtained data indicate that Casp5, Casp8 and DR4 gene polymorphisms may deserve consideration in large-scale case-control studies of LC risk modifiers.

After strong volcanic eruptions stratospheric ozone changes are modulated by heterogeneous chemical reactions (HET) and dynamical perturbations related to the radiative heating in the lower stratosphere (RAD). Here, we assess the relative importance of both processes as well as the effect of the resulting ozone changes on the dynamics using ensemble simulations with the atmosphere–ocean–chemistry–climate model (AOCCM) SOCOL-MPIOM forced by eruptions with different strength. The simulations are performed under present day and preindustrial conditions to investigate changes in the response behaviour. The results show that the HET effect is only relevant under present day conditions and causes a pronounced global reduction of column ozone. These ozone changes further lead to a slight weakening of the Northern Hemisphere (NH) polar vortex during mid-winter. Independent from the climate state the RAD mechanism changes the column ozone pattern with negative anomalies in the tropics and positive anomalies in the mid-latitudes. The influence of the climate state on the RAD mechanism significantly differs in the polar latitudes, where an amplified ozone depletion during the winter months is simulated under present day conditions. This is in contrast to the preindustrial state showing a positive column ozone response also in the polar area. The dynamical response of the stratosphere is clearly dominated by the RAD mechanism showing an intensification of the NH polar vortex in winter. Still under present day conditions ozone changes due to the RAD mechanism slightly reduce the response of the polar vortex after the eruption.

The BRCA1 4153delA allele is frequently referred to as the Russian founder mutation, as it was initially detected in several cancer families from Moscow. Our earlier studies have demonstrated 1% occurrence of BRCA1 4153delA heterozygosity in familial and/or early-onset and/or bilateral Russian breast cancer (BC) patients. Since literature data suggest that the 4153delA variant is more associated with ovarian cancer (OC) than with BC, we expected to reveal a highly elevated frequency of this genotype in Russian ovarian cancer series. However, real-time allele-specific PCR genotyping has detected only two BRCA1 4153delA carriers out of 177 unselected OC patients (1.1%). Both these carriers were early-onset and had serous carcinomas of grade 3. Thus, our study supports neither the Russian origin of BRCA1 4153delA mutation, nor its selectivity towards ovarian versus breast cancer predisposition.

BRCA1 5382insC variant was repeatedly detected in Jewish breast cancer (BC) families residing in USA and Israel as well as in non-Jewish familial BC patients from Poland, Latvia, Hungary, Russia and some other European countries. However, the distribution of BRCA1 5382insC mutation in unselected BC cases vs. controls has been systematically investigated mainly in Ashkenazi Jews. Here we applied a case-control study design in order to evaluate the impact of BRCA1 5382insC allele on BC incidence in St Petersburg, Russia. High frequency of the BRCA1 5382insC allele was detected in a group of bilateral breast cancer patients (10.4%; 15/144). Randomly selected unilateral BC cases demonstrated noticeable occurrence of BRCA1 5382insC mutation as well (3.7%; 32/857), with evident excess of the carriers in the early-onset (40 years) category (6.1%; 6/99) and in patients reporting breast and/or ovarian tumours in first-degree relatives (11.3%; 11/97). Strikingly, none of 478 middle-aged controls and 344 elderly tumour-free women carried the 5382insC variant. The presented data confirm a noticeable contribution of BRCA1 5382insC mutation in BC development in Russia, that may justify an extended BRCA1 5382insC testing within this population.

This study was aimed to assess the role of CHEK2 1100delC mutation in breast cancer (BC) predisposition in Russia. The 1100delC allele was detected in 14/660 (2.1%) unilateral BC cases and in 8/155 (5.2%) patients with the bilateral form of the disease, but only in 1/448 (0.2%) middle-aged control females and in none of 373 elderly tumor-free women. The obtained data point at potentially high clinical relevance of CHEK2 1100delC testing in females of Russian origin and warrant similar case-control studies in ethnically and geographically related regions, especially in Ukraine, Belarus and Baltic countries.

A pronounced ENSO cycle occurred from 1986 to 1989, accompanied by distinct dynamical and chemical anomalies in the global troposphere and stratosphere. Reproducing these effects with current climate models not only provides a model test but also contributes to our still limited understanding of ENSO's effect on stratosphere-troposphere coupling. We performed several sets of ensemble simulations with a chemical climate model (SOCOL) forced with global sea surface temperatures. Results were compared with observations and with large-ensemble simulations performed with an atmospheric general circulation model (MRF9). We focus our analysis on the extratropical stratosphere and its coupling with the troposphere. In this context, the circulation over the North Atlantic sector is particularly important. Relative to the La Niña winter 1989, observations for the El Niño winter 1987 show a negative North Atlantic Oscillation index with corresponding changes in temperature and precipitation patterns, a weak polar vortex, a warm Arctic middle stratosphere, negative and positive total ozone anomalies in the tropics and at middle to high latitudes, respectively, as well as anomalous upward and poleward Eliassen-Palm (EP) flux in the midlatitude lower stratosphere. Most of the tropospheric features are well reproduced in the ensemble means in both models, though the amplitudes are underestimated. In the stratosphere, the SOCOL simulations compare well with observations with respect to zonal wind, temperature, EP flux, meridional mass streamfunction, and ozone, but magnitudes are underestimated in the middle stratosphere. With respect to the mechanisms relating ENSO to stratospheric circulation, the results suggest that both, upward and poleward components of anomalous EP flux are important for obtaining the stratospheric signal and that an increase in strength of the Brewer-Dobson circulation is part of that signal.

In this paper we document 'SOCOL', a new chemistry-climate model, which has been ported for regular PCs and shows good wall-clock performance. An extensive validation of the model results against present-day climate data obtained from observations and assimilation data sets shows that the model describes the climatological state of the atmosphere for the late 1990s with reasonable accuracy. The model has a significant temperature bias only in the upper stratosphere and near the tropopause at high latitudes. The latter is the result of the rather low vertical resolution of the model near the tropopause. The former can be attributed to a crude representation of radiation heating in the middle atmosphere. A comparison of the simulated and observed link between the tropical stratospheric structure and the strength of the polar vortex shows that in general, both observations and simulations reveal a higher temperature and ozone mixing ratio in the lower tropical stratosphere for the case with stronger Polar night jet (PNJ) and slower Brewer-Dobson circulation as predicted by theoretical studies.

In the present work we consider the estimation algorithm of the appearance time of the high-frequency Gaussian random pulse with free-form envelope against white noise. Contrary to the known studies, we supposed the useful signal duration to be known inaccurately. We found the asymptotically exact analytical dependences for the conditional bias and variance of the appearance time estimate on the basis of the local Markov approximation method. Then, by the methods of statistical computer modeling, we established that the received theoretical results adequately agrees with the corresponding experimental data in a wide range of output signal-to-noise ratios.

A new effect — the splitting of the tips (branching) of a microwave streamer arising from a pre-existing dense plasma cloud in an above-threshold electric field — is obtained numerically on the basis of a planar two-dimensional model. The causes of this phenomenon and the factors suppressing it are found. An expression is obtained for the value of the cloud radius above which branching occurs.

As the understanding and representation of the impacts of volcanic eruptions on climate have improved in the last decades, uncertainties in the stratospheric aerosol forcing from large eruptions are now not only linked to visible optical depth estimates on a global scale but also to details on the size, latitude and altitude distributions of the stratospheric aerosols. Based on our understanding of these uncertainties, we propose a new model-based approach to generating a volcanic forcing for General-Circulation-Model (GCM) and Chemistry-Climate-Model (CCM) simulations. This new volcanic forcing, covering the 1600–present period, uses an aerosol microphysical model to provide a realistic, physically consistent treatment of the stratospheric sulfate aerosols. Twenty-six eruptions were modeled individually using the latest available ice cores aerosol mass estimates and historical data on the latitude and date of eruptions. The evolution of aerosol spatial and size distribution after the sulfur dioxide discharge are hence characterized for each volcanic eruption. Large variations are seen in hemispheric partitioning and size distributions in relation to location/date of eruptions and injected SO2 masses. Results for recent eruptions are in good agreement with observations. By providing accurate amplitude and spatial distributions of shortwave and longwave radiative perturbations by volcanic sulfate aerosols, we argue that this volcanic forcing may help refine the climate model responses to the large volcanic eruptions since 1600. The final dataset consists of 3-D values (with constant longitude) of spectrally resolved extinction coefficients, single scattering albedos and asymmetry factors calculated for different wavelength bands upon request. Surface area densities for heterogeneous chemistry are also provided.

The lack of long and reliable time series of solar spectral irradiance (SSI) measurements makes an accurate quantification of solar contributions to recent climate change difficult. Whereas earlier SSI observations and models provided a qualitatively consistent picture of the SSI variability, recent measurements by the SORCE satellite suggest a significantly stronger variability in the ultraviolet (UV) spectral range and changes in the visible and near-infrared (NIR) bands in anti-phase with the solar cycle. A number of recent chemistry-climate model (CCM) simulations have shown that this might have significant implications on the Earth's atmosphere. Motivated by these results, we summarize here our current knowledge of SSI variability and its impact on Earth's climate. We present a detailed overview of existing SSI measurements and provide thorough comparison of models available to date. SSI changes influence the Earth's atmosphere, both directly, through changes in shortwave (SW) heating and therefore, temperature and ozone distributions in the stratosphere, and indirectly, through dynamical feedbacks. We investigate these direct and indirect effects using several state-of-the art CCM simulations forced with measured and modeled SSI changes. A unique asset of this study is the use of a common comprehensive approach for an issue that is usually addressed separately by different communities. Omissis. Finally, we discuss the reliability of the available data and we propose additional coordinated work, first to build composite SSI datasets out of scattered observations and to refine current SSI models, and second, to run coordinated CCM experiments., 34 pages, 12 figures, accepted for publication in ACP