ALBERT

Description: A number of climate modeling studies have shown that differences between typical choices for representing ozone can affect climate change projections. Here we investigate potential climate impacts of a specific ozone representation used in simulations of the Hadley Centre Global Environment Model for the Coupled Model Intercomparison Project Phase 5. The method considers ozone changes only in the troposphere and lower stratosphere and prescribes stratospheric ozone elsewhere. For a standard climate sensitivity simulation, we find that this method leads to significantly increased global warming and specific patterns of regional surface warming compared with a fully interactive atmospheric chemistry setup. We explain this mainly by the suppressed part of the stratospheric ozone changes and the associated alteration of the stratospheric water vapor feedback. This combined effect is modulated by simultaneous cirrus cloud changes. We underline the need to understand better how representations of ozone can affect climate modeling results and, in particular, global and regional climate sensitivity estimates. ©2018. American Geophysical Union. All Rights Reserved.

Description: Measurement data from the long-term passenger aircraft project IAGOS-CARIBIC are often used to derive climatologies of trace gases in the upper troposphere and lower stratosphere (UTLS). We investigate to what extent such climatologies are representative of the true state of the atmosphere. Climatologies are considered relative to the tropopause in mid-latitudes (35 to 75° N) for trace gases with different atmospheric lifetimes. Using the chemistry–climate model EMAC, we sample the modeled trace gases along CARIBIC flight tracks. Representativeness is then assessed by comparing the CARIBIC sampled model data to the full climatological model state. Three statistical methods are applied for the investigation of representativeness: the Kolmogorov–Smirnov test and two scores based on the variability and relative differences. Two requirements for any score describing representativeness are essential: representativeness is expected to increase (i) with the number of samples and (ii) with decreasing variability of the species considered. Based on these two requirements, we investigate the suitability of the different statistical measures for investigating representativeness. The Kolmogorov–Smirnov test is very strict and does not identify any trace-gas climatology as representative – not even of long-lived trace gases. In contrast, the two scores based on either variability or relative differences show the expected behavior and thus appear applicable for investigating representativeness. For the final analysis of climatological representativeness, we use the relative difference score and calculate a representativeness uncertainty for each trace gas in percent. In order to justify the transfer of conclusions about representativeness of individual trace gases from the model to measurements, we compare the trace gas variability between model and measurements. We find that the model reaches 50–100 % of the measurement variability. The tendency of the model to underestimate the variability is caused by the relatively coarse spatial and temporal model resolution. In conclusion, we provide representativeness uncertainties for several species for tropopause-referenced climatologies. Long-lived species like CO2 have low uncertainties ( ≤ 0.4 %), while shorter-lived species like O3 have larger uncertainties (10–15 %). Finally, we translate the representativeness score into a number of flights that are necessary to achieve a certain degree of representativeness. For example, increasing the number of flights from 334 to 1000 would reduce the uncertainty in CO to a mere 1 %, while the uncertainty for shorter-lived species like NO would drop from 80 to 10 %.

Description: The European Climate Research Alliance (ECRA) is an association of leading European research institutions in the field of climate research (http://www.ecra-climate.eu/, last access: 6 December 2018). ECRA is a bottom-up initiative and helps to facilitate the development of climate change research, combining the capacities of national research institutions, and inducing closer ties between existing national research initiatives, projects and infrastructures. ECRA works as an open platform to bring together climate researchers, providing excellent scientific expertise for policy makers and of societal relevance. The ECRA Board consists of representatives of ECRA partners and decides on governance, scientific priorities, and organisational matters. Currently organized into four Collaborative Programmes, climate scientists share their knowledge, experience and expertise to identify the most important research requirements for the future, thus developing a foresight approach. The CPs cover the topics: (1) Arctic variability and change, (2) Sea level changes and coastal impacts, (3) Changes in the hydrological cycle and (4) High impact events. The CP activities are planned in workshops and participation is open to all interested scientists from the relevant research fields. In particular, young researchers are actively encouraged to join the network. Each CP develops its joint research priorities for shaping European research into the future. Because scientific themes are interconnected, the four Collaborative Programmes interact with each other, e.g. through the organization of common workshops or joint applications. In addition, the Collaborative Programme leads attend the Board meetings. The different formats of ECRA meetings range from scientific workshops to briefing events and side events at conferences to involve different groups of interests. This facilitates the interaction of scientists, various stakeholder groups and politicians. A biennial open ECRA General Assembly that is organised in Brussels represents an umbrella event and acts as a platform for discussion and contact with stakeholders. This event is an excellent opportunity to jointly discuss research priorities of high societal relevance.

Description: The 11-year solar cycle forcing is recognised as an important atmospheric forcing; however, there remain uncertainties in characterising the effects of solar variability on the atmosphere from observations and models. Here we present the first detailed assessment of the atmospheric response to the 11-year solar cycle in the UM-UKCA (Unified Model coupled to the United Kingdom Chemistry and Aerosol model) chemistry–climate model (CCM) using a three-member ensemble over the recent past (1966–2010). Comparison of the model simulations is made with satellite observations and reanalysis datasets. The UM-UKCA model produces a statistically significant response to the 11-year solar cycle in stratospheric temperatures, ozone and zonal winds. However, there are also differences in magnitude, spatial structure and timing of the signals compared to observational and reanalysis estimates. This could be due to deficiencies in the model performance, and so we include a critical discussion of the model limitations, and/or uncertainties in the current observational estimates of the solar cycle signals. Importantly, in contrast to many previous studies of the solar cycle impacts, we pay particular attention to the role of the chosen analysis method in UM-UKCA by comparing the model composite and a multiple linear regression (MLR) results. We show that the stratospheric solar responses diagnosed using both techniques largely agree with each other within the associated uncertainties; however, the results show that apparently different signals can be identified by the methods in the troposphere and in the tropical lower stratosphere. Lastly, we examine how internal atmospheric variability affects the detection of the 11-year solar responses in the model by comparing the results diagnosed from the three individual ensemble members (as opposed to those diagnosed from the full ensemble). We show overall agreement between the responses diagnosed for the ensemble members in the tropical and mid-latitude mid-stratosphere to lower mesosphere but larger apparent differences at Northern Hemisphere (NH) high latitudes during the dynamically active season. Our UM-UKCA results suggest the need for long data sets for confident detection of solar cycle impacts in the atmosphere, as well as for more research on possible interdependence of the solar cycle forcing with other atmospheric forcings and processes (e.g. Quasi-Biennial Oscillation, QBO; El Niño–Southern Oscillation, ENSO).

Description: We present model simulations with the atmospheric chemistry–climate model ECHAM5/MESSy Atmospheric Chemistry (EMAC) nudged toward European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim reanalyses for the Arctic winters 2009/2010 and 2010/2011. This study is the first to perform an extensive assessment of the performance of the EMAC model for Arctic winters as previous studies have only made limited evaluations of EMAC simulations which also were mainly focused on the Antarctic winter stratosphere. We have chosen the two extreme Arctic winters 2009/2010 and 2010/2011 to evaluate the formation of polar stratospheric clouds (PSCs) and the representation of the chemistry and dynamics of the polar winter stratosphere in EMAC. The EMAC simulations are compared to observations by the Michelson Interferometer for Passive Atmospheric Soundings (Envisat/MIPAS) and the observations from the Aura Microwave Limb Sounder (Aura/MLS). The Arctic winter 2010/2011 was one of the coldest stratospheric winters on record, leading to the strongest depletion of ozone measured in the Arctic. The Arctic winter 2009/2010 was, from the climatological perspective, one of the warmest stratospheric winters on record. However, it was distinguished by an exceptionally cold stratosphere (colder than the climatological mean) from mid-December 2009 to mid-January 2010, leading to prolonged PSC formation and existence. Significant denitrification, the removal of HNO3 from the stratosphere by sedimentation of HNO3-containing polar stratospheric cloud particles, occurred in that winter. In our comparison, we focus on PSC formation and denitrification. The comparisons between EMAC simulations and satellite observations show that model and measurements compare well for these two Arctic winters (differences for HNO3 generally within ±20 %) and thus that EMAC nudged toward ECMWF ERA-Interim reanalyses is capable of giving a realistic representation of the evolution of PSCs and associated sequestration of gas-phase HNO3 in the polar winter stratosphere. However, simulated PSC volume densities are smaller than the ones derived from Envisat/MIPAS observations by a factor of 3–7. Further, PSCs in EMAC are not simulated as high up (in altitude) as they are observed. This underestimation of PSC volume density and vertical extension of the PSCs results in an underestimation of the vertical redistribution of HNO3 due to denitrification/re-nitrification. The differences found here between model simulations and observations stipulate further improvements in the EMAC set-up for simulating PSCs.

Description: The 2015/2016 Arctic winter was one of the coldest stratospheric winters in recent years. A stable vortex formed by early December and the early winter was exceptionally cold. Cold pool temperatures dropped below the nitric acid trihydrate (NAT) existence temperature of about 195 K, thus allowing polar stratospheric clouds (PSCs) to form. The low temperatures in the polar stratosphere persisted until early March, allowing chlorine activation and catalytic ozone destruction. Satellite observations indicate that sedimentation of PSC particles led to denitrification as well as dehydration of stratospheric layers. Model simulations of the 2015/2016 Arctic winter nudged toward European Centre for Medium-Range Weather Forecasts (ECMWF) analysis data were performed with the atmospheric chemistry–climate model ECHAM5/MESSy Atmospheric Chemistry (EMAC) for the Polar Stratosphere in a Changing Climate (POLSTRACC) campaign. POLSTRACC is a High Altitude and Long Range Research Aircraft (HALO) mission aimed at the investigation of the structure, composition and evolution of the Arctic upper troposphere and lower stratosphere (UTLS). The chemical and physical processes involved in Arctic stratospheric ozone depletion, transport and mixing processes in the UTLS at high latitudes, PSCs and cirrus clouds are investigated. In this study, an overview of the chemistry and dynamics of the 2015/2016 Arctic winter as simulated with EMAC is given. Further, chemical–dynamical processes such as denitrification, dehydration and ozone loss during the 2015/2016 Arctic winter are investigated. Comparisons to satellite observations by the Aura Microwave Limb Sounder (Aura/MLS) as well as to airborne measurements with the Gimballed Limb Observer for Radiance Imaging of the Atmosphere (GLORIA) performed aboard HALO during the POLSTRACC campaign show that the EMAC simulations nudged toward ECMWF analysis generally agree well with observations. We derive a maximum polar stratospheric O3 loss of ∼ 2 ppmv or 117 DU in terms of column ozone in mid-March. The stratosphere was denitrified by about 4–8 ppbv HNO3 and dehydrated by about 0.6–1 ppmv H2O from the middle to the end of February. While ozone loss was quite strong, but not as strong as in 2010/2011, denitrification and dehydration were so far the strongest observed in the Arctic stratosphere in at least the past 10 years.

Description: 〉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.

Description: We present a recently developed emission module for the ICON (ICOsahedral Non-hydrostatic)-ART (Aerosols and Reactive Trace gases) modelling framework. The emission module processes external flux data sets and increments the tracer volume mixing ratios in the boundary layer accordingly. The performance of the emission module is illustrated with simulations of acetone, using a simplified chemical depletion mechanism based on a reaction with OH and photolysis only. In our model setup, we calculate a tropospheric acetone lifetime of 33 days, which is in good agreement with the literature. We compare our results with ground-based as well as with airborne IAGOS-CARIBIC measurements in the upper troposphere and lowermost stratosphere (UTLS) in terms of phase and amplitude of the annual cycle. In all our ICON-ART simulations the general seasonal variability is well represented but uncertainties remain concerning the magnitude of the acetone mixing ratio in the UTLS region. In addition, the module for online calculations of biogenic emissions (MEGAN2.1) is implemented in ICON-ART and can replace the offline biogenic emission data sets. In a sensitivity study we show how different parametrisations of the leaf area index (LAI) change the emission fluxes calculated by MEGAN2.1 and demonstrate the importance of an adequate treatment of the LAI within MEGAN2.1. We conclude that the emission module performs well with offline and online emission fluxes and allows the simulation of the annual cycles of emissions-dominated substances.