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The MagellanPlus workshop "BlackGate"addressed fundamental questions concerning the dynamic evolution of the Mediterranean-Black Sea (MBS) gateway and its palaeoenvironmental consequences. This gateway drives the Miocene-Quaternary circulation patterns in the Black Sea and governs its present status as the world's largest example of marine anoxia. The exchange history of the MBS gateway is poorly constrained because continuous Pliocene-Quaternary deposits are not exposed on land adjacent to the Black Sea or northern Aegean. Gateway exchange is controlled by climatic (glacio-eustatic-driven sea-level fluctuations) and tectonic processes in the catchment as well as tectonic propagation of the North Anatolian Fault Zone (NAFZ) in the gateway area itself. Changes in connectivity trigger dramatic palaeoenvironmental and biotic turnovers in both the Black Sea and Mediterranean domains. Drilling a Messinian to Holocene transect across the MBS gateway will recover high-amplitude records of continent-scale hydrological changes during glacial-interglacial cycles and allow us to reconstruct marine and freshwater fluxes, biological turnover events, deep biospheric processes, subsurface gradients in primary sedimentary properties, patterns and processes controlling anoxia, chemical perturbations and carbon cycling, growth and propagation of the NAFZ, the timing of land bridges for Africa and/or Asia-Europe mammal migration, and the presence or absence of water exchange during the Messinian salinity crisis. During thorough discussions at the workshop, three key sites were selected for potential drilling using a mission-specific platform (MSP): one on the Turkish margin of the Black Sea (Arkhangelsky Ridge, 400mb.s.f., metres below the seafloor), one on the southern margin of the Sea of Marmara (North Imrali Basin, 750mb.s.f.), and one in the Aegean (North Aegean Trough, 650mb.s.f.). All sites target Quaternary oxic-anoxic marl-sapropel cycles. Plans include recovery of Pliocene lacustrine sediments and mixed marine-brackish Miocene sediments from the Black Sea and the Aegean. MSP drilling is required because the JOIDES Resolution cannot pass under the Bosporus bridges. The wider goals are in line with the aims and scope of the International Ocean Discovery Program (IODP) "2050 Science Framework: Exploring Earth by Scientific Ocean Drilling"and relate specifically to the strategic objectives "Earth's climate system", "Tipping points in Earth's history", and "Natural hazards impacting society".

This dataset describes two 17 m long sediment cores taken from beneath two thermokarst lakes in the Yukechi Alas, Central Yakutia, Russia. The first core was taken from below an Alas thermokarst lake (YU-L7; 61.76397°N, 130.46442°E) and the second core below and Yedoma lake (YU-L15; 61.76086°N, 130.47466°E). The dataset presents biogeochemical and biomarker parameters of sediment cores YU-L7 and YU-L15. Biogeochemical analyses include total carbon (TC) content, total organic carbon (TOC) content, total nitrogen (TN) content. Biomarker parameters include the n-alkane concentration, average chain length (ACL), carbon preference index (CPI), brGDGT concentration, archaeol concentration and the isoGDGT-0 concentration. The n-alkanes were measured in the aliphatic fraction by gas chromatography-mass spectromety using a Trace GC Ultra coupled to a DSQ MS. The branched and isoprenoid glycerol dialkyl glycerol tetraethers, as well as the dialkyl glycerol diether lipid (archaeol) were measured in the NSO fraction using a Shimadzu LC-10AD high-performance liquid chromatograph coupled to a Finnigan TSQ 7000 mass spectrometer via an atmospheric pressure chemical ionization interface. The pH soil is the sediment pH which was assessed by adding 6.12 mL of 0.01 M CaCl~2~ to ~2.5 g dried sediment and measuring with a Multilab 540 (WTW) at 20°C.

Greenland Ice-Core Chronology 2005 (GICC05) annual layer depths for various Greenland ice cores. This is the high-resolution version (full, annual resolution) data file. Previously, 10- and 20-year resolution data files containing the time scale and resampled d18O data have been released for different time intervals together with the papers mentioned below. Ages are reported as years before A.D. 2000 / 2000 CE, abbreviated b2k.The file contains the location of the annual markers in the GICC05 time scale for each core's depth sections where data was available and sufficiently resolved to allow annual dating. Details are given in the papers listed below. The markers are placed in the winter and spring depending on the availability of data (e.g. using the winter d18O minimum, winter Sodium concentration maximum, spring dust/Calcium concentration maximum, or visual stratigraphy grey-scale peaks in the deepest parts). Across data gaps, markers are placed by interpolation or using other impurity species with different seasonality (e.g. using summer Ammonium or Nitrate peaks). Therefore, the criteria for where the annual markers are places vary between sections, and care should be taken when interpreting data on annual scale. The dating of the 0-7.9 ka b2k part is described in the paper Vinther et al., 2006The dating of the 7.9-14.7 ka b2k part is described in the paper Rasmussen et al., 2006The dating of the 14.7-41.8 ka b2k part is described in the paper Andersen et al., 2006The dating of the 41.8-60.0 ka b2k part is described in the paper Svensson et al., 2008When counting layers, uncertainty is introduced when an annual layer is backed up by evidence only in some of the data series, or when a certain well-resolved feature is suspected to contain more than one annual layer. The cases of ambiguity in the annual layer identification process have been marked using so-called uncertain layer markings. These uncertain layer markings were included in the time scale as ½ ± ½ years, with the ± ½ years forming the basis for quantifying the so-called maximum counting error. The concept of maximum counting error is further discussed in Rasmussen et al. (2006). In a standard deviation context, the maximum counting error can be regarded as 2 sigma as discussed in Andersen et al. (2006).In the Holocene, GS-1, and GI-2, the published time scale was derived from annual layer markings by manually determining which half of the uncertain layer markings to count as years, and which to skip. The maximum counting error was estimated from the number of uncertain layer markings as a constant relative uncertainty for each period with similar data availability and characteristics: 21-3,845 a b2k (0.25%), 3,846-6,905 a b2k (0.5%), 6,906-10,276 a b2k (2%), 10,277-11,703 a b2k (0.67%), 11,703-12,896 a b2k (3,3%), 12,896-14,075 a b2k (2.6%), 14,075-14,692 a b2k (2.7%) (see table 2 in Vinther et al, 2006, and table 3 in Rasmussen et al., 2006). From GS-2 and below (Andersen et al., 2006; Svensson et al., 2008) every 2nd uncertain layer was counted as a year and the maximum counting uncertainty increased by one year (giving rise to a variable relative counting error ranging from 4% in the warm interstadial periods to 7% in the cold stadials, and averaging 5.3%). In data set "Greenland NGRIP2 Ice-Core annual layer markings"(https://doi.pangaea.de/10.1594/PANGAEA.943194), the depths of the annual layer markings (including the uncertain ones) are provided with indication of which of these were counted as annual layers. This data set is only available below 10.2 ka. Above this, the locations of the discarded half of the uncertain layer markings have only been recorded on paper.The NGRIP1 core reaches down to a depth of 1372 m. The NGRIP2 core (drilled 20 meters away from the NGRIP1 core) reaches from surface to bedrock, but high-resolution measurements have only been carried out downwards from 1346 m. In the 26 m overlap zone, the cores are offset by 0.43 m on average, probably due to uncertainties in the logging procedure (see Schøtt Hvidberg et al., Ann. Glac. 35, 2002). Thus, the same features appear at larger depths in the NGRIP1 than in the NGRIP2 core. We recommend that NGRIP1 depths are used until 9820 b2k, and NGRIP2 depths are used below this.Note that the GICC05 time scale has later been revised. The first section of the new time scale, named GICC21, is described in the paper "A multi-ice-core, annual-layer-counted Greenland ice-core chronology for the last 3800 years: GICC21", Climate of the Past volume 18, p. 1125-1150, 2022, https://doi.org/10.5194/cp-18-1125-2022. Updated GICC21 annual-layer positions are released in the supplement to the paper. Annual markers forming the GICC05 time scale for NGRIP1, NGRIP2, GRIP, and DYE-3 where data was available and sufficiently resolved to allow annual dating. The markers are placed in the winter and spring depending on the availability of data (e.g. using the winter d18O minimum, winter Sodium concentration maximum, spring dust/Calcium concentration maximum, or visual stratigraphy grey-scale peaks in the deepest parts). Across data gaps, markers are placed by interpolation or using other impurity species with different seasonality (e.g. using summer Ammonium or Nitrate peaks). Therefore, the criteria for where the annual markers are places vary between sections, and care should be taken when interpreting data on annual scale. Ages are reported as years before A.D. 2000 / 2000 CE, abbreviated b2k. Depths (in meter) are true depths below the undisturbed surface the year when drilling started.

Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate is critical to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe and synthesize data sets and methodologies to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (EFOS) are based on energy statistics and cement production data, while emissions from land-use change (ELUC), mainly deforestation, are based on land use and land-use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly, and its growth rate (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) is estimated with global ocean biogeochemistry models and observation-based data products. The terrestrial CO2 sink (SLAND) is estimated with dynamic global vegetation models. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the year 2021, EFOS increased by 5.1 % relative to 2020, with fossil emissions at 10.1 ± 0.5 GtC yr−1 (9.9 ± 0.5 GtC yr−1 when the cement carbonation sink is included), and ELUC was 1.1 ± 0.7 GtC yr−1, for a total anthropogenic CO2 emission (including the cement carbonation sink) of 10.9 ± 0.8 GtC yr−1 (40.0 ± 2.9 GtCO2). Also, for 2021, GATM was 5.2 ± 0.2 GtC yr−1 (2.5 ± 0.1 ppm yr−1), SOCEAN was 2.9 ± 0.4 GtC yr−1, and SLAND was 3.5 ± 0.9 GtC yr−1, with a BIM of −0.6 GtC yr−1 (i.e. the total estimated sources were too low or sinks were too high). The global atmospheric CO2 concentration averaged over 2021 reached 414.71 ± 0.1 ppm. Preliminary data for 2022 suggest an increase in EFOS relative to 2021 of +1.0 % (0.1 % to 1.9 %) globally and atmospheric CO2 concentration reaching 417.2 ppm, more than 50 % above pre-industrial levels (around 278 ppm). Overall, the mean and trend in the components of the global carbon budget are consistently estimated over the period 1959–2021, but discrepancies of up to 1 GtC yr−1 persist for the representation of annual to semi-decadal variability in CO2 fluxes. Comparison of estimates from multiple approaches and observations shows (1) a persistent large uncertainty in the estimate of land-use change emissions, (2) a low agreement between the different methods on the magnitude of the land CO2 flux in the northern extratropics, and (3) a discrepancy between the different methods on the strength of the ocean sink over the last decade. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding of the global carbon cycle compared with previous publications of this data set.

Greenland Ice-Core Chronology 2005 (GICC05) annual layer depths for various Greenland ice cores. This is the high-resolution version (full, annual resolution) data file. Previously, 10- and 20-year resolution data files containing the time scale and resampled d18O data have been released for different time intervals together with the papers mentioned below. Ages are reported as years before A.D. 2000 / 2000 CE, abbreviated b2k.The file contains the location of the annual markers in the GICC05 time scale for each core's depth sections where data was available and sufficiently resolved to allow annual dating. Details are given in the papers listed below. The markers are placed in the winter and spring depending on the availability of data (e.g. using the winter d18O minimum, winter Sodium concentration maximum, spring dust/Calcium concentration maximum, or visual stratigraphy grey-scale peaks in the deepest parts). Across data gaps, markers are placed by interpolation or using other impurity species with different seasonality (e.g. using summer Ammonium or Nitrate peaks). Therefore, the criteria for where the annual markers are places vary between sections, and care should be taken when interpreting data on annual scale. The dating of the 0-7.9 ka b2k part is described in the paper Vinther et al., 2006The dating of the 7.9-14.7 ka b2k part is described in the paper Rasmussen et al., 2006The dating of the 14.7-41.8 ka b2k part is described in the paper Andersen et al., 2006The dating of the 41.8-60.0 ka b2k part is described in the paper Svensson et al., 2008When counting layers, uncertainty is introduced when an annual layer is backed up by evidence only in some of the data series, or when a certain well-resolved feature is suspected to contain more than one annual layer. The cases of ambiguity in the annual layer identification process have been marked using so-called uncertain layer markings. These uncertain layer markings were included in the time scale as ½ ± ½ years, with the ± ½ years forming the basis for quantifying the so-called maximum counting error. The concept of maximum counting error is further discussed in Rasmussen et al. (2006). In a standard deviation context, the maximum counting error can be regarded as 2 sigma as discussed in Andersen et al. (2006).In the Holocene, GS-1, and GI-2, the published time scale was derived from annual layer markings by manually determining which half of the uncertain layer markings to count as years, and which to skip. The maximum counting error was estimated from the number of uncertain layer markings as a constant relative uncertainty for each period with similar data availability and characteristics: 21-3,845 a b2k (0.25%), 3,846-6,905 a b2k (0.5%), 6,906-10,276 a b2k (2%), 10,277-11,703 a b2k (0.67%), 11,703-12,896 a b2k (3,3%), 12,896-14,075 a b2k (2.6%), 14,075-14,692 a b2k (2.7%) (see table 2 in Vinther et al, 2006, and table 3 in Rasmussen et al., 2006). From GS-2 and below (Andersen et al., 2006; Svensson et al., 2008) every 2nd uncertain layer was counted as a year and the maximum counting uncertainty increased by one year (giving rise to a variable relative counting error ranging from 4% in the warm interstadial periods to 7% in the cold stadials, and averaging 5.3%). In data set "Greenland NGRIP2 Ice-Core annual layer markings"(https://doi.pangaea.de/10.1594/PANGAEA.943194), the depths of the annual layer markings (including the uncertain ones) are provided with indication of which of these were counted as annual layers. This data set is only available below 10.2 ka. Above this, the locations of the discarded half of the uncertain layer markings have only been recorded on paper.The NGRIP1 core reaches down to a depth of 1372 m. The NGRIP2 core (drilled 20 meters away from the NGRIP1 core) reaches from surface to bedrock, but high-resolution measurements have only been carried out downwards from 1346 m. In the 26 m overlap zone, the cores are offset by 0.43 m on average, probably due to uncertainties in the logging procedure (see Schøtt Hvidberg et al., Ann. Glac. 35, 2002). Thus, the same features appear at larger depths in the NGRIP1 than in the NGRIP2 core. We recommend that NGRIP1 depths are used until 9820 b2k, and NGRIP2 depths are used below this.Note that the GICC05 time scale has later been revised. The first section of the new time scale, named GICC21, is described in the paper "A multi-ice-core, annual-layer-counted Greenland ice-core chronology for the last 3800 years: GICC21", Climate of the Past volume 18, p. 1125-1150, 2022, https://doi.org/10.5194/cp-18-1125-2022. Updated GICC21 annual-layer positions are released in the supplement to the paper. Annual markers forming the GICC05 time scale for NGRIP1, NGRIP2, GRIP, and DYE-3 where data was available and sufficiently resolved to allow annual dating. The markers are placed in the winter and spring depending on the availability of data (e.g. using the winter d18O minimum, winter Sodium concentration maximum, spring dust/Calcium concentration maximum, or visual stratigraphy grey-scale peaks in the deepest parts). Across data gaps, markers are placed by interpolation or using other impurity species with different seasonality (e.g. using summer Ammonium or Nitrate peaks). Therefore, the criteria for where the annual markers are places vary between sections, and care should be taken when interpreting data on annual scale. Ages are reported as years before A.D. 2000 / 2000 CE, abbreviated b2k. Depths (in meter) are true depths below the undisturbed surface the year when drilling started.

This study considers year-to-year and decadal variations in as well as secular trends of the sea–air CO2 flux over the 1957–2020 period, as constrained by the pCO2 measurements from the SOCATv2021 database. In a first step, we relate interannual anomalies in ocean-internal carbon sources and sinks to local interannual anomalies in sea surface temperature (SST), the temporal changes in SST (dSST/dt), and squared wind speed (u2), employing a multi-linear regression. In the tropical Pacific, we find interannual variability to be dominated by dSST/dt, as arising from variations in the upwelling of colder and more carbon-rich waters into the mixed layer. In the eastern upwelling zones as well as in circumpolar bands in the high latitudes of both hemispheres, we find sensitivity to wind speed, compatible with the entrainment of carbon-rich water during wind-driven deepening of the mixed layer and wind-driven upwelling. In the Southern Ocean, the secular increase in wind speed leads to a secular increase in the carbon source into the mixed layer, with an estimated reduction in the sink trend in the range of 17 % to 42 %. In a second step, we combined the result of the multi-linear regression and an explicitly interannual pCO2-based additive correction into a “hybrid” estimate of the sea–air CO2 flux over the period 1957–2020. As a pCO2 mapping method, it combines (a) the ability of a regression to bridge data gaps and extrapolate into the early decades almost void of pCO2 data based on process-related observables and (b) the ability of an auto-regressive interpolation to follow signals even if not represented in the chosen set of explanatory variables. The “hybrid” estimate can be applied as an ocean flux prior for atmospheric CO2 inversions covering the whole period of atmospheric CO2 data since 1957.

Most research on mechanisms of aging is being conducted in a very limited number of classical model species, i.e., laboratory mouse (Mus musculus), rat (Rattus norvegicus domestica), the common fruit fly (Drosophila melanogaster) and roundworm (Caenorhabditis elegans). The obvious advantages of using these models are access to resources such as strains with known genetic properties, high-quality genomic and transcriptomic sequencing data, versatile experimental manipulation capabilities including well-established genome editing tools, as well as extensive experience in husbandry. However, this approach may introduce interpretation biases due to the specific characteristics of the investigated species, which may lead to inappropriate, or even false, generalization. For example, it is still unclear to what extent knowledge of aging mechanisms gained in short-lived model organisms is transferable to long-lived species such as humans. In addition, other specific adaptations favoring a long and healthy life from the immense evolutionary toolbox may be entirely missed. In this review, we summarize the specific characteristics of emerging animal models that have attracted the attention of gerontologists, we provide an overview of the available data and resources related to these models, and we summarize important insights gained from them in recent years. The models presented include short-lived ones such as killifish (Nothobranchius furzeri), long-lived ones such as primates (Callithrix jacchus, Cebus imitator, Macaca mulatta), bathyergid mole-rats (Heterocephalus glaber, Fukomys spp.), bats (Myotis spp.), birds, olms (Proteus anguinus), turtles, greenland sharks, bivalves (Arctica islandica), and potentially non-aging ones such as Hydra and Planaria.

We present novel measurements of the carbon isotope composition of CFC-11 (CCl3F), CFC-12 (CCl2F2), and CFC-113 (CF2ClCFCl2), three atmospheric trace gases that are important for both stratospheric ozone depletion and global warming. These measurements were carried out on air samples collected in the stratosphere – the main sink region for these gases – and on air extracted from deep polar firn snow. We quantify, for the first time, the apparent isotopic fractionation, ϵapp(13C), for these gases as they are destroyed in the high- and mid-latitude stratosphere: ϵapp(CFC-12, high-latitude) =(-20.2±4.4) ‰, and ϵapp(CFC-113, high-latitude) =(-9.4±4.4) ‰, ϵapp(CFC-12, mid-latitude) =(-30.3±10.7) ‰, and ϵapp(CFC-113, mid-latitude) =(-34.4±9.8) ‰. Our CFC-11 measurements were not sufficient to calculate ϵapp(CFC-11), so we instead used previously reported photolytic fractionation for CFC-11 and CFC-12 to scale our ϵapp(CFC-12), resulting in ϵapp(CFC-11, high-latitude) =(-7.8±1.7) ‰ and ϵapp(CFC-11, mid-latitude) =(-11.7±4.2) ‰. Measurements of firn air were used to construct histories of the tropospheric isotopic composition, δT(13C), for CFC-11 (1950s to 2009), CFC-12 (1950s to 2009), and CFC-113 (1970s to 2009), with δT(13C) increasing for each gas. We used ϵapp(high-latitude), which was derived from more data, and a constant isotopic composition of emissions, δE(13C), to model δT(13C, CFC-11), δT(13C, CFC-12), and δT(13C, CFC-113). For CFC-11 and CFC-12, modelled δT(13C) was consistent with measured δT(13C) for the entire period covered by the measurements, suggesting that no dramatic change in δE(13C, CFC-11) or δE(13C, CFC-12) has occurred since the 1950s. For CFC-113, our modelled δT(13C, CFC-113) did not agree with our measurements earlier than 1980. This discrepancy may be indicative of a change in δE(13C, CFC-113). However, this conclusion is based largely on a single sample and only just significant outside the 95 % confidence interval. Therefore more work is needed to independently verify this temporal trend in the global tropospheric 13C isotopic composition of CFC-113. Our modelling predicts increasing δT(13C, CFC-11), δT(13C, CFC-12), and δT(13C, CFC-113) into the future. We investigated the effect of recently reported new CFC-11 emissions on background δT(13C, CFC-11) by fixing model emissions after 2012 and comparing δT(13C, CFC-11) in this scenario to the model base case. The difference in δT(13C, CFC-11) between these scenarios was 1.4 ‰ in 2050. This difference is smaller than our model uncertainty envelope and would therefore require improved modelling and measurement precision as well as better quantified isotopic source compositions to detect.

Sea spray aerosol particles are a recognised type of ice-nucleating particles under mixed-phase cloud conditions. Entities that are responsible for the heterogeneous ice nucleation ability include intact or fragmented cells of marine microorganisms as well as organic matter released by cell exudation. Only a small fraction of sea spray aerosol is transported to the upper troposphere, but there are indications from mass-spectrometric analyses of the residuals of sublimated cirrus particles that sea salt could also contribute to heterogeneous ice nucleation under cirrus conditions. Experimental studies on the heterogeneous ice nucleation ability of sea spray aerosol particles and their proxies at temperatures below 235 K are still scarce. In our article, we summarise previous measurements and present a new set of ice nucleation experiments at cirrus temperatures with particles generated from sea surface microlayer and surface seawater samples collected in three different regions of the Arctic and from a laboratory-grown diatom culture (Skeletonema marinoi). The particles were suspended in the Aerosol Interaction and Dynamics in the Atmosphere (AIDA) cloud chamber and ice formation was induced by expansion cooling. We confirmed that under cirrus conditions, apart from the ice-nucleating entities mentioned above, also crystalline inorganic salt constituents can contribute to heterogeneous ice formation. This takes place at temperatures below 220 K, where we observed in all experiments a strong immersion freezing mode due to the only partially deliquesced inorganic salts. The inferred ice nucleation active surface site densities for this nucleation mode reached a maximum of about 5×1010 m−2 at an ice saturation ratio of 1.3. Much smaller densities in the range of 108–109 m−2 were observed at temperatures between 220 and 235 K, where the inorganic salts fully deliquesced and only the organic matter and/or algal cells and cell debris could contribute to heterogeneous ice formation. These values are 2 orders of magnitude smaller than those previously reported for particles generated from microlayer suspensions collected in temperate and subtropical zones. While this difference might simply underline the strong variability of the number of ice-nucleating entities in the sea surface microlayer across different geographical regions, we also discuss how instrumental parameters like the aerosolisation method and the ice nucleation measurement technique might affect the comparability of the results amongst different studies.

Stratospheric ozone and water vapour are key components of the Earth system, and past and future changes to both have important impacts on global and regional climate. Here, we evaluate long-term changes in these species from the pre-industrial period (1850) to the end of the 21st century in Coupled Model Intercomparison Project phase 6 (CMIP6) models under a range of future emissions scenarios. There is good agreement between the CMIP multi-model mean and observations for total column ozone (TCO), although there is substantial variation between the individual CMIP6 models. For the CMIP6 multi-model mean, global mean TCO has increased from ∼ 300 DU in 1850 to ∼ 305 DU in 1960, before rapidly declining in the 1970s and 1980s following the use and emission of halogenated ozone-depleting substances (ODSs). TCO is projected to return to 1960s values by the middle of the 21st century under the SSP2-4.5, SSP3-7.0, SSP4-3.4, SSP4-6.0, and SSP5-8.5 scenarios, and under the SSP3-7.0 and SSP5-8.5 scenarios TCO values are projected to be ∼ 10 DU higher than the 1960s values by 2100. However, under the SSP1-1.9 and SSP1-1.6 scenarios, TCO is not projected to return to the 1960s values despite reductions in halogenated ODSs due to decreases in tropospheric ozone mixing ratios. This global pattern is similar to regional patterns, except in the tropics where TCO under most scenarios is not projected to return to 1960s values, either through reductions in tropospheric ozone under SSP1-1.9 and SSP1-2.6, or through reductions in lower stratospheric ozone resulting from an acceleration of the Brewer–Dobson circulation under other Shared Socioeconomic Pathways (SSPs). In contrast to TCO, there is poorer agreement between the CMIP6 multi-model mean and observed lower stratospheric water vapour mixing ratios, with the CMIP6 multi-model mean underestimating observed water vapour mixing ratios by ∼ 0.5 ppmv at 70 hPa. CMIP6 multi-model mean stratospheric water vapour mixing ratios in the tropical lower stratosphere have increased by ∼ 0.5 ppmv from the pre-industrial to the present-day period and are projected to increase further by the end of the 21st century. The largest increases (∼ 2 ppmv) are simulated under the future scenarios with the highest assumed forcing pathway (e.g. SSP5-8.5). Tropical lower stratospheric water vapour, and to a lesser extent TCO, shows large variations following explosive volcanic eruptions.