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The January 2022 eruption of Hunga Tonga‐Hunga Ha'apai (HTHH) injected a huge amount (∼150 Tg) of water vapor (H2O) into the stratosphere, along with small amount of SO2. An off‐line 3‐D chemical transport model (CTM) successfully reproduces the spread of the injected H2O through October 2023 as observed by the Microwave Limb Sounder. Dehydration in the 2023 Antarctic polar vortex caused the first substantial (∼20 Tg) removal of HTHH H2O from the stratosphere. The CTM indicates that this process will dominate removal of HTHH H2O for the coming years, giving an overall e‐folding timescale of 4 years; around 25 Tg of the injected H2O is predicted to still remain in the stratosphere by 2030. Following relatively low Antarctic column ozone in midwinter 2023 due to transport effects, additional springtime depletion due to H2O‐related chemistry was small and maximized at the vortex edge (10 DU in column). Plain Language Summary: Around 150 Tg (150 million tons) of water vapor was injected into the stratosphere during the eruption of Hunga Tonga‐Hunga Ha'apai. Water vapor is a greenhouse gas and this increase is expected to have a warming effect in the troposphere, as well causing perturbations in stratospheric chemistry and aerosols. We use an atmospheric model to study the residence time of this excess water vapor and its impact on the recent Antarctic ozone hole. The model performance is evaluated by comparison with satellite measurements. Wintertime dehydration in the Antarctic stratosphere in 2023 is found to be an important mechanism for removal of the volcanic water from the stratosphere. However, the overall removal rate is predicted to be slow; around 25 Tg (17%) is still present in 2030. The direct impact of the excess water vapor on ozone via chemical processes in the Antarctic ozone hole in 2023 is small. Key Points: Antarctic dehydration is a major removal pathway of stratospheric H2O injected from Hunga Tonga‐Hunga Ha'apai (HTHH) eruptionHTHH H2O caused small (up to 10 DU) additional chemical ozone depletion in 2023 Antarctic springModel indicates e‐folding timescale of 4 years for removal of HTHH H2O from stratosphere [ABSTRACT FROM AUTHOR]

High quality stratospheric ozone profile datasets are a key requirement for accurate quantification and attribution of long-term ozone changes. Satellite instruments obtain stratospheric ozone profile measurements over typical mission durations of 5-15 years. Various methodologies have then been applied to merge and homogenise the different satellite data in order to create longer term observation-based ozone profile datasets with minimal data gaps. However, individual satellite instruments use different measurement methods, sampling patterns and retrieval algorithms which complicate the merging of these different datasets. In contrast, atmospheric chemical models can produce chemically consistent long-term ozone simulations based on specified changes in external forcings, but they are subject to the deficiencies associated with incomplete understanding of complex atmospheric processes and uncertain photochemical parameters. Here, we use chemically self-consistent output from the TOMCAT 3-D chemical transport model (CTM) and a Random-Forest (RF) ensemble learning method to create a merged 42-year (1979-2020) stratospheric ozone profile dataset (ML-TOMCAT V1.0). The underlying CTM simulation was forced by meteorological reanalyses, specified trends in long-lived source gas, solar flux and aerosol variations. The RF is trained using the Stratospheric Water and OzOne Satellite Homogenized (SWOOSH) dataset over the time periods of the Microwave Limb Sounder (MLS) from the Upper Atmosphere Research Satellite (UARS) (1991-1998) and Aura (2005-2016) missions. We find that ML-TOMCAT shows excellent agreement with available independent satellite-based datasets which use pressure as the vertical coordinate (e.g. GOZCARDS, SWOOSH for non-MLS periods) but weaker agreement with the datasets which are height-based (e.g. SAGE-CCI-OMPS, SCIAMACHY-OMPS). We find that at almost all stratospheric levels ML-TOMCAT ozone concentrations are well within uncertainties in the observational datasets. The ML-TOMCAT dataset is thus ideally suited for the evaluation of model ozone profiles from the tropopause to 0.1 hPa. ML-TOMCAT data is freely available via https://zenodo.org/record/4997959#.YNzleUlKiUk (Dhomse et al., 2021). [ABSTRACT FROM AUTHOR]

The Stratospheric Sulfur and its Role in Climate (SSiRC) interactive stratospheric aerosol model intercomparison project (ISA-MIP) explores uncertainties in the processes that connect volcanic emission of sulphur gas species and the radiative forcing associated with the resulting enhancement of the stratospheric aerosol layer. The central aim of ISA-MIP is to constrain and improve interactive stratospheric aerosol models and reduce uncertainties in the stratospheric aerosol forcing by comparing results of standardized model experiments with a range of observations. In this paper we present 4 co-ordinated inter-model experiments designed to investigate key processes which influence the formation and temporal development of stratospheric aerosol in different time periods of the observational record. The Background (BG) experiment will focus on microphysics and transport processes under volcanically quiescent conditions, when the stratospheric aerosol is controlled by the transport of aerosols and their precursors from the troposphere to the stratosphere. The Transient Aerosol Record (TAR) experiment will explore the role of small- to moderate-magnitude volcanic eruptions, anthropogenic sulphur emissions and transport processes over the period 1998-2012 and their role in the warming hiatus. Two further experiments will investigate the stratospheric sulphate aerosol evolution after major volcanic eruptions. The Historical Eruptions SO2 Emission Assessment (HErSEA) experiment will focus on the uncertainty in the initial emission of recent large-magnitude volcanic eruptions, while the Pinatubo Emulation in Multiple models (PoEMS) experiment will provide a comprehensive uncertainty analysis of the radiative forcing from the 1991 Mt. Pinatubo eruption. [ABSTRACT FROM AUTHOR]

We present an overview of state-of-the-art chemistry-climate and chemistry transport models that are used within phase 1 of the Chemistry-Climate Model Initiative (CCMI-1). The CCMI aims to conduct a detailed evaluation of participating models using process-oriented diagnostics derived from observations in order to gain confidence in the models' projections of the stratospheric ozone layer, tropospheric composition, air quality, where applicable global climate change, and the interactions between them. Interpretation of these diagnostics requires detailed knowledge of the radiative, chemical, dynamical, and physical processes incorporated in the models. Also an understanding of the degree to which CCMI-1 recommendations for simulations have been followed is necessary to understand model responses to anthropogenic and natural forcing and also to explain intermodel differences. This becomes even more important given the ongoing development and the ever-growing complexity of these models. This paper also provides an overview of the available CCMI-1 simulations with the aim of informing CCMI data users. [ABSTRACT FROM AUTHOR]

The enhancement of the stratospheric aerosol layer by volcanic eruptions induces a complex set of responses causing global and regional climate effects on a broad range of timescales. Uncertainties exist regarding the climatic response to strong volcanic forcing identified in coupled climate simulations that contributed to the fifth phase of the Coupled Model Intercomparison Project (CMIP5). In order to better understand the sources of these model diversities, the Model Intercomparison Project on the climatic response to Volcanic forcing (VolMIP) has defined a coordinated set of idealized volcanic perturbation experiments to be carried out in alignment with the CMIP6 protocol. VolMIP provides a common stratospheric aerosol data set for each experiment to minimize differences in the applied volcanic forcing. It defines a set of initial conditions to assess how internal climate variability contributes to determining the response. VolMIP will assess to what extent volcanically forced responses of the coupled ocean-atmosphere system are robustly simulated by state-of-the-art coupled climate models and identify the causes that limit robust simulated behavior, especially differences in the treatment of physical processes. This paper illustrates the design of the idealized volcanic perturbation experiments in the VolMIP protocol and describes the common aerosol forcing input data sets to be used. [ABSTRACT FROM AUTHOR]

We present an overview of state-of-the-art chemistry-climate and -transport models that are used within the Chemistry-Climate Model Initiative (CCMI). CCMI aims to conduct a detailed evaluation of participating models using process-oriented diagnostics derived from observations in order to gain confidence in the models' projections of the stratospheric ozone layer, air quality, where applicable global climate change, and the interactions between them. Interpretation of these diagnostics requires detailed knowledge of the radiative, chemical, dynamical, and physical processes incorporated in the models. Also an understanding of the degree to which CCMI recommendations for simulations have been followed is necessary to understand model response to anthropogenic and natural forcing and also to explain inter-model differences. This becomes even more important given the ongoing development and the ever-growing complexity of these models. This paper also provides an overview of the available CCMI simulations with the aim to inform CCMI data users. [ABSTRACT FROM AUTHOR]