Water vapour in the upper troposphere and stratosphere has a significant impact both on the radiative and chemical properties of the atmosphere. Reliable water vapour climate data records (CDRs) are essential for use in climate research, to assess vertically resolved trends and associated radiative impacts. Within the ESA Water Vapour Climate Change Initiative (WV_cci), new vertically resolved water vapour CDRs in the stratosphere and UTLS were merged from a range of satellite observations. In this contribution, we provide an overview of these CDRs, highlighting innovations in the merging methodologies and results from a detailed quality assessment. In particular, the long-term trends derived from the new water vapour CDRs are compared to other merged datasets, reanalyses, and simulations from chemistry-climate models, with the ESA WV_cci CDRs deemed to be valuable new datasets for climate studies. We conclude that, mostly driven by dynamical variability, the derived water vapour trends vary significantly depending on the dataset used, chosen time period and location in the atmosphere. Using an off-line radiative transfer model, we estimate the consequence of these differences on the radiative forcing from water vapour changes in the upper troposphere and stratosphere over the past 30+ years.

Emissions of the potent greenhouse gas perfluorocyclobutane (c-C4F8, PFC-318, octafluorocyclobutane) into the global atmosphere inferred from atmospheric measurements have been increasing sharply since the early 2000s. We find that these inferred emissions are highly correlated with the production of hydrochlorofluorocarbon-22 (HCFC-22, CHClF2) for feedstock (FS) uses, because almost all HCFC-22 FS is pyrolyzed to produce (poly)tetrafluoroethylene ((P)TFE) and hexafluoropropylene (HFP), a process in which c-C4F8 is a known by-product, causing a significant fraction of global c-C4F8 emissions. We find a global emission factor of ∼0.003 kg c-C4F8 per kilogram of HCFC-22 FS pyrolyzed. Mitigation of these c-C4F8 emissions, e.g., through process optimization, abatement, or different manufacturing processes, such as refined methods of electrochemical fluorination and waste recycling, could reduce the climate impact of this industry. While it has been shown that c-C4F8 emissions from developing countries dominate global emissions, more atmospheric measurements and/or detailed process statistics are needed to quantify c-C4F8 emissions at country to facility levels.

Caption: Lightning discharges appear in various colours depending on the scatter of light inside the thundercloud and in the atmosphere.The intracloud lightning discharges in the centre of the thundercloud appear to be white with a bluish tint, and the cloud-to-ground discharge below appears to be orange.The right hand side of the thundercloud exhibits a green tint that is attributed to the unique composition of hydrometeors inside the thundercloud.The photo was taken in the late evening of 10 September 2013, near Tarragona in northeastern Spain.

Significance We demonstrate the need to detect and track unexpected substances in the atmosphere and to locate their sources. Here, we report on three hydrochlorofluorocarbons (HCFCs) that have no known end-uses. HCFC-132b ( C H 2 C l C C l F 2 ) is newly discovered in the global atmosphere. We identify East Asia as the dominant source region for global emissions of this compound and of HCFC-133a ( C H 2 C l C F 3 ). We also quantify global emissions of HCFC-31 ( C H 2 ClF). These compounds are most likely emitted as intermediate by-products of chemical production processes. The early discovery and identification of such unexpected emissions can identify the related industrial practices and help to develop and manage environmental policies to reduce unwanted and potentially harmful emissions before the scale of the problem becomes more costly to mitigate.

The Stratosphere-troposphere Processes and their Role in Climate (SPARC) Data Initiative (SPARC, 2017) performed the first comprehensive assessment of currently available stratospheric composition measurements obtained from an international suite of space-based limb sounders. The initiative's main objectives were (1) to assess the state of data availability, (2) to compile time series of vertically resolved, zonal monthly mean trace gas and aerosol fields, and (3) to perform a detailed intercomparison of these time series, summarizing useful information and highlighting differences among datasets. The datasets extend over the region from the upper troposphere to the lower mesosphere (300–0.1 hPa) and are provided on a common latitude–pressure grid. They cover 26 different atmospheric constituents including the stratospheric trace gases of primary interest, ozone (O3) and water vapor (H2O), major long-lived trace gases (SF6, N2O, HF, CCl3F, CCl2F2, NOy), trace gases with intermediate lifetimes (HCl, CH4, CO, HNO3), and shorter-lived trace gases important to stratospheric chemistry including nitrogen-containing species (NO, NO2, NOx, N2O5, HNO4), halogens (BrO, ClO, ClONO2, HOCl), and other minor species (OH, HO2, CH2O, CH3CN), and aerosol. This overview of the SPARC Data Initiative introduces the updated versions of the SPARC Data Initiative time series for the extended time period 1979–2018 and provides information on the satellite instruments included in the assessment: LIMS, SAGE I/II/III, HALOE, UARS-MLS, POAM II/III, OSIRIS, SMR, MIPAS, GOMOS, SCIAMACHY, ACE-FTS, ACE-MAESTRO, Aura-MLS, HIRDLS, SMILES, and OMPS-LP. It describes the Data Initiative's top-down climatological validation approach to compare stratospheric composition measurements based on zonal monthly mean fields, which provides upper bounds to relative inter-instrument biases and an assessment of how well the instruments are able to capture geophysical features of the stratosphere. An update to previously published evaluations of O3 and H2O monthly mean time series is provided. In addition, example trace gas evaluations of methane (CH4), carbon monoxide (CO), a set of nitrogen species (NO, NO2, and HNO3), the reactive nitrogen family (NOy), and hydroperoxyl (HO2) are presented. The results highlight the quality, strengths and weaknesses, and representativeness of the different datasets. As a summary, the current state of our knowledge of stratospheric composition and variability is provided based on the overall consistency between the datasets. As such, the SPARC Data Initiative datasets and evaluations can serve as an atlas or reference of stratospheric composition and variability during the “golden age” of atmospheric limb sounding. The updated SPARC Data Initiative zonal monthly mean time series for each instrument are publicly available and accessible via the Zenodo data archive (Hegglin et al., 2020).

The potent greenhouse gas sulfuryl fluoride (SO 2 F 2 ) is increasingly used as a fumigant, replacing methyl bromide, whose structural and soil fumigation uses have been phased out under the Montreal Protocol. We use measurements on archived air samples and in situ observations from the Advanced Global Atmospheric Gases Experiment (AGAGE) and a box model of the global atmosphere to show a global increase of SO 2 F 2 mole fraction from 0.3 ± 0.02 to 2.5 ± 0.08 ppt along with a global increase in emissions from 0.5 ± 0.4 Gg yr −1 to 2.9 ± 0.4 Gg yr −1 from 1978 to 2019. Based on a hybrid model incorporating bottom‐up industry data and a top‐down downscaling approach, we estimate the spatial distribution and trend in SO 2 F 2 regional emissions between 2000 and 2019 and propose that the global emissions increase is driven by the growing use of SO 2 F 2 in structural fumigation in North America and in postharvest treatment of grains and other agricultural products worldwide.

We have developed a procedure for retrieving atmospheric abundances of HFC-23 (CHF3) with a ground-based Fourier transform infrared (FTIR) spectrometer and analyzed the spectra observed at Rikubetsu, Japan (43.5∘ N, 143.8∘ E), and at Syowa Station, Antarctica (69.0∘ S, 39.6∘ E). The FTIR retrievals were carried out with the SFIT4 retrieval program, and the two spectral windows of 1138.5–1148.0 cm−1 and 1154.0–1160.0 cm−1 in the overlapping ν2 and ν5 vibrational–rotational transition bands of HFC-23 were used to avoid strong H2O absorption features. We considered O3, N2O, CH4, H2O, HDO, CFC-12 (CCl2F2), HCFC-22 (CHClF2), peroxyacetyl nitrate (PAN) (CH3C(O)OONO2), HCFC-141b (CH3CCl2F), and HCFC-142b (CH3CClF2) to be interfering species. Vertical profiles of H2O, HDO, and CH4 are preliminarily retrieved with other independent spectral windows because these profiles may induce large uncertainties in the HFC-23 retrieval. Each HFC-23 retrieval has only one piece of vertical information with sensitivity to HFC-23 in the troposphere and the lower stratosphere. Retrieval errors mainly arise from the systematic uncertainties of the spectroscopic parameters used to obtain HFC-23, H2O, HDO, and CH4 abundances. For comparison between FTIR-retrieved HFC-23 total columns and surface dry-air mole fractions provided by AGAGE (Advanced Global Atmospheric Gases Experiment), FTIR-retrieved HFC-23 dry-air column-averaged mole fractions (XHFC-23) were calculated. The FTIR-retrieved XHFC-23 values at Rikubetsu and Syowa Station have negative biases of −15 % to −20 % and −25 % compared to the AGAGE datasets, respectively. These negative biases might mainly come from systematic uncertainties of HFC-23 spectroscopic parameters. The trend of the FTIR-retrieved XHFC-23 data at Rikubetsu was derived for December to February (DJF) observations, which are considered to represent the background values when an air mass reaching Rikubetsu has the least influence by transport of HFC-23 emissions from nearby countries. The DJF trend of Rikubetsu over the 1997–2009 period is 0.810 ± 0.093 ppt yr−1 (ppt: parts per trillion), which is in good agreement with the trend derived from the annual global mean datasets of the AGAGE 12-box model for the same period (0.820 ± 0.013 ppt yr−1). The DJF trend of Rikubetsu over the 2008–2019 period is 0.928 ± 0.108 ppt yr−1, which is consistent with the trend in the AGAGE in situ measurements at Trinidad Head (41.1∘ N, 124.2∘ W) for the same period (0.994 ± 0.001 ppt yr−1). The trend of the FTIR-retrieved XHFC-23 data at Syowa Station over the 2007–2016 period is 0.819 ± 0.071 ppt yr−1, which is consistent with that derived from the AGAGE in situ measurements at Cape Grim (40.7∘ S, 144.7∘ E) for the same period (0.874 ± 0.002 ppt yr−1). Although there are systematic biases in the FTIR-retrieved XHFC-23 at both sites, these results indicate that ground-based FTIR observations have the capability to monitor the long-term trend of atmospheric HFC-23. If this FTIR measurement technique were extended to other Network for the Detection of Atmospheric Composition Change (NDACC) ground-based FTIR sites around world, the measurements reported from these sites would complement the global AGAGE observations by filling spatial and temporal gaps and may lead to improved insights about changes in regional and global emissions of HFC-23 and its role in global warming.

The Stratospheric Aerosol and Gas Experiment III on the International Space Station (SAGE III/ISS) was launched on 19 February 2017 and began routine operation in June 2017. The first 2 years of SAGE III/ISS (v5.1) solar occultation ozone data were evaluated by using correlative satellite and ground‐based measurements. Among the three (MES, AO3, and MLR) SAGE III/ISS retrieved solar ozone products, AO3 ozone shows the smallest bias and best precision, with mean biases less than 5% for altitudes ~15–55 km in the midlatitudes and ~20–55 km in the tropics. In the lower stratosphere and upper troposphere, AO3 ozone shows high biases that increase with decreasing altitudes and reach ~10% near the tropopause. Preliminary studies indicate that those high biases primarily result from the contributions of the oxygen dimer (O4) not being appropriately removed within the ozone channel. The precision of AO3 ozone is estimated to be ~3% for altitudes between 20 and 40 km. It degrades to ~10–15% in the lower mesosphere (~55 km) and ~20–30% near the tropopause. There could be an altitude registration error of ~100 m in the SAGE III/ISS auxiliary temperature and pressure profiles. This, however, does not affect retrieved ozone profiles in native number density on geometric altitude coordinates. In the upper stratosphere and lower mesosphere (~40–55 km), the SAGE III/ISS (and SAGE II) retrieved ozone values show sunrise/sunset differences of ~5–8%, which are almost twice as large as what was observed by other satellites or model predictions. This feature needs further study.

3 Peter G. Simmonds, Matthew Rigby, Alistair J. Manning, Sunyoung Park, Kieran M. 4 Stanley, Archie McCulloch, Stephan Henne, Francesco Graziosi, Michela Maione, 5 Jgor Arduini, Stefan Reimann, Martin K. Vollmer, Jens Mühle, Simon O’Doherty, 6 Dickon Young, Paul B. Krummel, Paul J. Fraser, Ray F. Weiss, Peter K. Salameh, 7 Christina M. Harth, Mi-Kyung Park, Hyeri Park, Tim Arnold, Chris Rennick, L. Paul 8 Steele, Blagoj Mitrevski, Ray H. J. Wang, and Ronald G. Prinn. 9

We report a 40-year history of SF6 atmospheric mole fractions measured at the Advanced Global Atmospheric Gases Experiment (AGAGE) monitoring sites, combined with archived air samples, to determine emission estimates from 1978 to 2018. Previously we reported a global emission rate of 7.3±0.6 Gg yr−1 in 2008 and over the past decade emissions have continued to increase by about 24 % to 9.04±0.35 Gg yr−1 in 2018. We show that changing patterns in SF6 consumption from developed (Kyoto Protocol Annex-1) to developing countries (non-Annex-1) and the rapid global expansion of the electric power industry, mainly in Asia, have increased the demand for SF6-insulated switchgear, circuit breakers, and transformers. The large bank of SF6 sequestered in this electrical equipment provides a substantial source of emissions from maintenance, replacement, and continuous leakage. Other emissive sources of SF6 occur from the magnesium, aluminium, and electronics industries as well as more minor industrial applications. More recently, reported emissions, including those from electrical equipment and metal industries, primarily in the Annex-1 countries, have declined steadily through substitution of alternative blanketing gases and technological improvements in less emissive equipment and more efficient industrial practices. Nevertheless, there are still demands for SF6 in Annex-1 countries due to economic growth, as well as continuing emissions from older equipment and additional emissions from newly installed SF6-insulated electrical equipment, although at low emission rates. In addition, in the non-Annex-1 countries, SF6 emissions have increased due to an expansion in the growth of the electrical power, metal, and electronics industries to support their continuing development. There is an annual difference of 2.5–5 Gg yr−1 (1990–2018) between our modelled top-down emissions and the UNFCCC-reported bottom-up emissions (United Nations Framework Convention on Climate Change), which we attempt to reconcile through analysis of the potential contribution of emissions from the various industrial applications which use SF6. We also investigate regional emissions in East Asia (China, S. Korea) and western Europe and their respective contributions to the global atmospheric SF6 inventory. On an average annual basis, our estimated emissions from the whole of China are approximately 10 times greater than emissions from western Europe. In 2018, our modelled Chinese and western European emissions accounted for ∼36 % and 3.1 %, respectively, of our global SF6 emissions estimate.

Anthropogenic increases in atmospheric greenhouse gas concentrations are the main driver of current and future climate change. The integrated assessment community has quantified anthropogenic emissions for the shared socio-economic pathway (SSP) scenarios, each of which represents a different future socio-economic projection and political environment. Here, we provide the greenhouse gas concentrations for these SSP scenarios – using the reduced-complexity climate–carbon-cycle model MAGICC7.0. We extend historical, observationally based concentration data with SSP concentration projections from 2015 to 2500 for 43 greenhouse gases with monthly and latitudinal resolution. CO2 concentrations by 2100 range from 393 to 1135 ppm for the lowest (SSP1-1.9) and highest (SSP5-8.5) emission scenarios, respectively. We also provide the concentration extensions beyond 2100 based on assumptions regarding the trajectories of fossil fuels and land use change emissions, net negative emissions, and the fraction of non-CO2 emissions. By 2150, CO2 concentrations in the lowest emission scenario are approximately 350 ppm and approximately plateau at that level until 2500, whereas the highest fossil-fuel-driven scenario projects CO2 concentrations of 1737 ppm and reaches concentrations beyond 2000 ppm by 2250. We estimate that the share of CO2 in the total radiative forcing contribution of all considered 43 long-lived greenhouse gases increases from 66 % for the present day to roughly 68 % to 85 % by the time of maximum forcing in the 21st century. For this estimation, we updated simple radiative forcing parameterizations that reflect the Oslo Line-By-Line model results. In comparison to the representative concentration pathways (RCPs), the five main SSPs (SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5) are more evenly spaced and extend to lower 2100 radiative forcing and temperatures. Performing two pairs of six-member historical ensembles with CESM1.2.2, we estimate the effect on surface air temperatures of applying latitudinally and seasonally resolved GHG concentrations. We find that the ensemble differences in the March–April–May (MAM) season provide a regional warming in higher northern latitudes of up to 0.4 K over the historical period, latitudinally averaged of about 0.1 K, which we estimate to be comparable to the upper bound (∼5 % level) of natural variability. In comparison to the comparatively straight line of the last 2000 years, the greenhouse gas concentrations since the onset of the industrial period and this studies' projections over the next 100 to 500 years unequivocally depict a “hockey-stick” upwards shape. The SSP concentration time series derived in this study provide a harmonized set of input assumptions for long-term climate science analysis; they also provide an indication of the wide set of futures that societal developments and policy implementations can lead to – ranging from multiple degrees of future warming on the one side to approximately 1.5 ∘C warming on the other.

© 2023 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses). Corresponding author: Robert Dunn / robert.dunn@metoffice.gov.uk

We have analyzed near-global stratospheric data (and mesospheric data as well for H2O) in terms of absolute abundances, variability, and trends for O3, H2O, HCl, N2O, and HNO3, based on Aura Microwave Limb Sounder (MLS) data, as well as longer-term series from the Global OZone Chemistry And Related trace gas Data records for the Stratosphere (GOZCARDS). While we emphasize the evaluation of stratospheric models via data comparisons through 2014 to free-running (FR-WACCM) and specified dynamics (SD-WACCM) versions of the Community Earth System Model version 1 (CESM1) Whole Atmosphere Community Climate Model (WACCM), we also highlight observed stratospheric changes, using the most recent data from MLS. Regarding highlights from the satellite data, we have used multiple linear regression to derive trends based on zonal mean time series from Aura MLS data alone, between 60∘ S and 60∘ N. In the upper stratosphere, MLS O3 shows increases over 2005–2018 at ∼0.1–0.3 % yr−1 (depending on altitude and latitude) with 2σ errors of ∼0.2 % yr−1. For the lower stratosphere (LS), GOZCARDS O3 data for 1998–2014 point to small decreases between 60∘ S and 60∘ N, but the trends are more positive if the starting year is 2005. Southern midlatitudes (30–60∘ S) exhibit near-zero or slightly positive LS trends for 1998–2018. The LS O3 trends based on 2005–2018 MLS data are most positive (0.1–0.2 % yr−1) at these southern midlatitudes, although marginally statistically significant, in contrast to slightly negative or near-zero trends for 2005–2014. Given the high variability in LS O3, and the high sensitivity of trends to the choice of years used, especially for short periods, further studies are required for a robust longer-term LS trend result. For H2O, upper-stratospheric and mesospheric trends from GOZCARDS 1992–2010 data are near zero (within ∼0.2 % yr−1) and significantly smaller than trends (within ∼0.4–0.7 % yr−1) from MLS for 2005–2014 or 2005–2018. The latter short-term positive H2O trends are larger than expected from changes resulting from long-term increases in methane. We note that the very shallow solar flux maximum of solar cycle 24 has contributed to fairly large short-term mesospheric and upper-stratospheric H2O trends since 2005. However, given known drifts in the MLS H2O time series, MLS H2O trend results, especially after 2010, should be viewed as upper limits. The MLS data also show regions and periods of small HCl increases in the lower stratosphere, within the context of the longer-term stratospheric decrease in HCl, as well as interhemispheric–latitudinal differences in short-term HCl tendencies. We observe similarities in such short-term tendencies, and interhemispheric asymmetries therein, for lower-stratospheric HCl and HNO3, while N2O trend profiles exhibit anti-correlated patterns. In terms of the model evaluation, climatological averages for 2005–2014 from both FR-WACCM and SD-WACCM for O3, H2O, HCl, N2O, and HNO3 compare favorably with Aura MLS data averages over this period. However, the models at mid- to high latitudes overestimate mean MLS LS O3 values and seasonal amplitudes by as much as 50 %–60 %; such differences appear to implicate, in part, a transport-related model issue. At lower-stratospheric high southern latitudes, variations in polar winter and spring composition observed by MLS are well matched by SD-WACCM, with the main exception being for the early winter rate of decrease in HCl, which is too slow in the model. In general, we find that the latitude–pressure distributions of annual and semiannual oscillation amplitudes derived from MLS data are properly captured by the model amplitudes. In terms of closeness of fit diagnostics for model–data anomaly series, not surprisingly, SD-WACCM (driven by realistic dynamics) generally matches the observations better than FR-WACCM does. We also use root mean square variability as a more valuable metric to evaluate model–data differences. We find, most notably, that FR-WACCM underestimates observed interannual variability for H2O; this has implications for the time period needed to detect small trends, based on model predictions. The WACCM O3 trends generally agree (within 2σ uncertainties) with the MLS data trends, although LS trends are typically not statistically different from zero. The MLS O3 trend dependence on latitude and pressure is matched quite well by the SD-WACCM results. For H2O, MLS and SD-WACCM positive trends agree fairly well, but FR-WACCM shows significantly smaller increases; this discrepancy for FR-WACCM is even more pronounced for longer-term GOZCARDS H2O records. The larger discrepancies for FR-WACCM likely arise from its poorer correlations with cold point temperatures and with quasi-biennial oscillation (QBO) variability. For HCl, while some expected decreases in the global LS are seen in the observations, there are interhemispheric differences in the trends, and increasing tendencies are suggested in tropical MLS data at 68 hPa, where there is only a slight positive trend in SD-WACCM. Although the vertical gradients in MLS HCl trends are well duplicated by SD-WACCM, the model trends are always somewhat more negative; this deserves further investigation. The original MLS N2O product time series yield small positive LS tropical trends (2005–2012), consistent with models and with rates of increase in tropospheric N2O. However, longer-term series from the more current MLS N2O standard product are affected by instrument-related drifts that have also impacted MLS H2O. The LS short-term trend profiles from MLS N2O and HNO3 at midlatitudes in the two hemispheres have different signs; these patterns are well matched by SD-WACCM trends for these species. These model–data comparisons provide a reminder that the QBO and other dynamical factors affect decadal variability in a major way, notably in the lower stratosphere, and can thus significantly hinder the goals of robustly extracting (and explaining) small underlying long-term trends. The data sets and tools discussed here for model evaluation could be expanded to comparisons of species or regions not included here, as well as to comparisons between a variety of chemistry–climate models.

Based on observations of the chlorofluorocarbons CFC-13 (chlorotrifluoromethane), ΣCFC-114 (combined measurement of both isomers of dichlorotetrafluoroethane), and CFC-115 (chloropentafluoroethane) in atmospheric and firn samples, we reconstruct records of their tropospheric histories spanning nearly 8 decades. These compounds were measured in polar firn air samples, in ambient air archived in canisters, and in situ at the AGAGE (Advanced Global Atmospheric Gases Experiment) network and affiliated sites. Global emissions to the atmosphere are derived from these observations using an inversion based on a 12-box atmospheric transport model. For CFC-13, we provide the first comprehensive global analysis. This compound increased monotonically from its first appearance in the atmosphere in the late 1950s to a mean global abundance of 3.18 ppt (dry-air mole fraction in parts per trillion, pmol mol−1) in 2016. Its growth rate has decreased since the mid-1980s but has remained at a surprisingly high mean level of 0.02 ppt yr−1 since 2000, resulting in a continuing growth of CFC-13 in the atmosphere. ΣCFC-114 increased from its appearance in the 1950s to a maximum of 16.6 ppt in the early 2000s and has since slightly declined to 16.3 ppt in 2016. CFC-115 increased monotonically from its first appearance in the 1960s and reached a global mean mole fraction of 8.49 ppt in 2016. Growth rates of all three compounds over the past years are significantly larger than would be expected from zero emissions. Under the assumption of unchanging lifetimes and atmospheric transport patterns, we derive global emissions from our measurements, which have remained unexpectedly high in recent years: mean yearly emissions for the last decade (2007–2016) of CFC-13 are at 0.48 ± 0.15 kt yr−1 (> 15 % of past peak emissions), of ΣCFC-114 at 1.90 ± 0.84 kt yr−1 (∼ 10 % of peak emissions), and of CFC-115 at 0.80 ± 0.50 kt yr−1 (> 5 % of peak emissions). Mean yearly emissions of CFC-115 for 2015–2016 are 1.14 ± 0.50 kt yr−1 and have doubled compared to the 2007–2010 minimum. We find CFC-13 emissions from aluminum smelters but if extrapolated to global emissions, they cannot account for the lingering global emissions determined from the atmospheric observations. We find impurities of CFC-115 in the refrigerant HFC-125 (CHF2CF3) but if extrapolated to global emissions, they can neither account for the lingering global CFC-115 emissions determined from the atmospheric observations nor for their recent increases. We also conduct regional inversions for the years 2012–2016 for the northeastern Asian area using observations from the Korean AGAGE site at Gosan and find significant emissions for ΣCFC-114 and CFC-115, suggesting that a large fraction of their global emissions currently occur in northeastern Asia and more specifically on the Chinese mainland.

Abstract. We evaluate the recently delivered Community Earth System Model version 1 (CESM1) Whole Atmosphere Community Climate Model (WACCM) using satellite-derived global composition datasets, focusing on the stratosphere. The simulations include free-running (FR-WACCM) and specified-dynamics (SD-WACCM) versions of the model. Model evaluations are made using global monthly zonal mean time series obtained by the Aura Microwave Limb Sounder (MLS), as well as longer-term global data records compiled by the Global Ozone Chemistry and Related Trace gas Data Records for the Stratosphere (GOZCARDS) project. A recent update (version 2.20) to the original GOZCARDS merged ozone (O3) data set is used. We discuss upper atmospheric climatology and zonal mean variability using O3, hydrogen chloride (HCl), nitrous oxide (N2O), nitric acid (HNO3), and water vapor (H2O) data. There are a few significant model/data mean biases, such as for lower stratospheric O3, for which the models overestimate the mean observed values and seasonal amplitudes. Another clear difference occurs for HNO3 during recurring winter periods of strong HNO3 enhancements at high latitudes; this stems from the known omission of ion chemistry relating to particle precipitation effects, in the global models used here. In the lower stratosphere at high southern latitudes, the variations in polar winter/spring composition observed by MLS are generally well matched by SD-WACCM, the main exception being for the early winter rate of decrease in HCl, which is too slow in the model. In general, the latitude/pressure distributions of annual and semi-annual oscillation amplitudes derived from the MLS data are properly captured by the corresponding model values. Nevertheless, detailed aspects of the interactions between the quasi-biennial, annual, and semi-annual ozone variations in the upper stratosphere are not as well represented by FR-WACCM as by SD-WACCM. One of the evaluation diagnostics we use represents the closeness of fit between the model/data anomaly time series, and we also consider the correlation coefficients. Not surprisingly, SD-WACCM, which is driven by realistic dynamics, generally matches observed deseasonalized anomalies better than FR-WACCM does. Other results indicate that the root mean square variability is sometimes found to be significantly smaller in FR-WACCM than in SD-WACCM and the observations. Most notably, FR-WACCM underestimates the observed interannual variability for H2O by ~ 30 %, typically, and by as much as a factor of two in some regions; this has some implications for the time needed to detect small trends. We have derived trends using a multivariate linear regression (MLR) model, and there is a robust signal in both MLS observations and WACCM of an upper stratospheric O3 increase from 2005 to 2014 by ~ 0.2–0.4 %/yr (±0.2 %/yr, 2σ), depending on which broad latitude bin (tropics or mid-latitudes) is considered. In the lower stratosphere, while some decreases are indicated for 1998–2014 (based on merged GOZCARDS O3), we find near-zero or positive trends when using MLS O3 data alone for 2005–2014, albeit with no robust statistical significance. SD-WACCM results track such positive tendencies (albeit with no statistical significance). For H2O, the most statistically significant trend result for 2005–2014 is an upper stratospheric increase, peaking at slightly more than 0.5 %/yr in the lower mesosphere, in fairly close agreement with SD-WACCM trends, but with smaller values in FR-WACCM. For HCl, while the lower stratospheric vertical gradients of MLS trends are duplicated to some extent by SD-WACCM, the model trends (decreases) are always on the low side of the data trends. There is little model-based indication (in SD-WACCM) of a significantly positive HCl trend derived from the MLS tropical series at 68 hPa; this deserves further study. For N2O, the MLS-derived trends (for 2005–2012) point to negative trends (of up to about −1 %/yr) in the NH mid-latitudes and positive trends (of up to about +3 %/yr) in the SH mid-latitudes, in good agreement with the asymmetry that exists in SD-WACCM trend results. The small observed positive N2O trends of ~ 0.2 %/yr in the 100 to 30 hPa tropical region are also consistent with model results (SD-WACCM in particular), which in turn are very close to the known rate of increase in tropospheric N2O. In the case of HNO3, MLS-derived lower stratospheric trend differences (for 2005–2014) between hemispheres are opposite in sign to those from N2O and in reasonable agreement with both WACCM results, despite large error bars. The data sets and tools discussed here for the evaluation of the models could be expanded to additional comparisons of species not included here, as well as to model intercomparisons using a variety of CCMs, keeping in mind that there are different parameterizations and approaches for both free-running and specified-dynamics simulations.