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Volcanic eruptions and wildfires can impact stratospheric chemistry. We apply tracer‐tracer correlations to satellite data from Atmospheric Chemistry Experiment—Fourier Transform Spectrometer and the Halogen Occultation Experiment at 68 hPa to consistently compare the chemical impact on HCl after multiple wildfires and volcanic eruptions of different magnitudes. The 2020 Australian New Year (ANY) fire displayed an order of magnitude less stratospheric aerosol extinction than the 1991 Pinatubo eruption, but showed similar large changes in mid‐latitude lower stratosphere HCl. While the mid‐latitude aerosol loadings from the 2015 Calbuco and 2022 Hunga volcanic eruptions were similar to the ANY fire, little impact on HCl occurred. The 2009 Australian Black Saturday fire and 2021 smoke remaining from 2020 yield small HCl changes, at the edge of the detection method. These observed contrasts across events highlight greater reactivity for smoke versus volcanic aerosols at warm temperatures. Plain Language Summary: An unprecedented change in HCl was observed in the lower stratosphere after the 2020 Australian New Year (ANY) wildfire using satellite records since 2004. In this study, we conduct a consistent analysis of HCl impacts using an additional satellite product with measurements since 1991 to examine effects of the catastrophic 1991 Pinatubo volcanic eruption and smaller eruptions, and compare them to the 2020 ANY fire (and remaining smoke in 2021), as well as the much smaller 2009 Australian Black Saturday (ABS) bushfire. This allows analysis of different types of particles (smoke vs. volcanic) and the extremes of each observed to date. While the Pinatubo eruption displayed 10 times greater aerosol loading in the stratosphere than the ANY fire, these two events led to similar net chemical changes in HCl. In contrast, no significant changes in HCl were observed in the lower stratosphere following the Hunga and Calbuco volcanic eruptions, which displayed similar levels of extinction to ANY. Small effects were observed from ABS fire and in 2021, allowing identification of the lower limit of the amount of smoke affecting HCl. These contrasts between events indicate that the wildfire smoke aerosols must be more reactive insofar as chlorine chemistry is concerned. Key Points: The tracer‐tracer correlation method reveals chemical perturbations associated with volcanic aerosols or smokeThe 1991 Pinatubo eruption and the 2020 Australian wildfire markedly perturbed HCl in the southern mid‐latitude lower stratosphereThe Pinatubo eruption had 10 times more aerosol loading than the Australian wildfire, but similar decreases in HCl [ABSTRACT FROM AUTHOR]

Following the Hunga Tonga–Hunga Ha'apai (HTHH) eruption in January 2022, significant reductions in stratospheric hydrochloric acid (HCl) were observed in the Southern Hemisphere mid‐latitudes during the latter half of 2022, suggesting potential chlorine activation. The objective of this study is to comprehensively understand the loss of HCl in the aftermath of HTHH. Satellite measurements and a global chemistry‐climate model are employed for the analysis. We find strong agreement of 2022 anomalies between the modeled and the measured data. The observed tracer‐tracer relations between nitrous oxide (N2O) and HCl indicate a significant role of chemical processing in the observed HCl reduction, especially during the austral winter of 2022. Further examining the roles of chlorine gas‐phase and heterogeneous chemistry, we find that heterogeneous chemistry emerges as the primary driver for the chemical loss of HCl, and the reaction between hypobromous acid (HOBr) and HCl on sulfate aerosols is the dominant loss process. Plain Language Summary: After the eruption of the Hunga Tonga–Hunga Ha'apai (HTHH) volcano in January 2022, there was a substantial decrease in stratospheric hydrochloric acid (HCl) in the Southern Hemisphere mid‐latitudes in the latter part of 2022. This decrease suggests that a chemical reaction involving chlorine processing might have happened. This study aims to comprehensively understand the significant loss of HCl following the HTHH eruption, utilizing satellite measurements and a global chemistry‐climate model for analysis. The anomalies in 2022 show remarkable agreement between the modeled and measured data. By comparing the levels of HCl with another gas called nitrous oxide (N2O), we discover that a lot of the HCl loss was due to chemical reactions, especially during the Southern Hemisphere winter. Upon further investigation into the role of chlorine gas‐phase and heterogeneous chemistry, heterogeneous chemistry emerges as a primary driver for the chemical loss of HCl. The reaction between hypobromous acid (HOBr) and HCl on sulfate aerosols is identified as the dominant loss process. Key Points: Analysis using both model and satellites suggest a significant role of chemical processing in the observed HCl reduction at 20 kmAnalysis of gas‐ and heterogeneous‐phase reactions indicates that heterogeneous chemistry is the main driver for the chemical loss of HClThe dominant heterogeneous loss for HCl is via HOBr + HCl, with HCl + OH also significant due to enhanced OH from heterogeneous chemistry [ABSTRACT FROM AUTHOR]

North Atlantic sea surface temperatures (NASST), particularly in the subpolar region, are among the most predictable in the world's oceans. However, the relative importance of atmospheric and oceanic controls on their variability at multidecadal timescales remain uncertain. Neural networks (NNs) are trained to examine the relative importance of oceanic and atmospheric predictors in predicting the NASST state in the Community Earth System Model 1 (CESM1). In the presence of external forcings, oceanic predictors outperform atmospheric predictors, persistence, and random chance baselines out to 25‐year leadtimes. Layer‐wise relevance propagation is used to unveil the sources of predictability, and reveal that NNs consistently rely upon the Gulf Stream‐North Atlantic Current region for accurate predictions. Additionally, CESM1‐trained NNs successfully predict the phasing of multidecadal variability in an observational data set, suggesting consistency in physical processes driving NASST variability between CESM1 and observations. Plain Language Summary: North Atlantic sea surface temperatures, particularly in the subpolar region, are among the most predictable locations in the world's oceans. However, it remains uncertain if processes in the atmosphere or ocean are more important for driving temperature fluctuations in this region occurring over multiple decades. We use a machine learning approach to predict the sea surface temperature state from climate model outputs, given snapshots of atmospheric or oceanic variables. Ocean variables lead to more accurate predictions relative to atmospheric variables and standard prediction baselines out to 25 years ahead if processes that drive the trends in climate, such as human‐induced warming, are present in the data. These successful predictions arise consistently from the same region near the Gulf Stream‐North Atlantic Current region. Despite being trained on climate models, the neural networks can predict the timing of observed positive and negative states of real‐world sea surface temperatures, suggesting that there is potential for using model output to train neural networks at predicting the actual North Atlantic sea surface variability. Key Points: Neural networks outperform persistence forecasts in predicting extreme states of North Atlantic sea surface temperature out to 25 yearsAn explainable neural network technique reveals successful predictions rely consistently on the Transition Zone regionNeural networks trained on climate model output predict the phasing of multidecadal variability on an observation‐based data set [ABSTRACT FROM AUTHOR]

For trace gases destroyed in the stratosphere, mass flux across the tropopause can substantially influence observed surface hemispheric differences (NH‐SH). Here, we quantify associations between observed stratospheric and tropospheric NH‐SH growth rate anomalies of CFC‐11, CFC‐12, and N2O. We employ a chemistry climate model along with satellite and global surface station observations. Our model explains 60% of observed N2O NH‐SH growth rate variability from 2005 to 2019, compared to 30% for CFC‐11% and 40% for CFC‐12, supporting evidence that unexpected anthropogenic emissions caused sustained positive NH‐SH anomalies in these CFCs from 2012 to 2017. Between 2012 and 2015, the observed CFC‐11 NH‐SH difference grew by 1.7 ppt; our model explains 0.5 ± 0.1 ppt of this growth, but not the duration. Our model suggests that in the absence of further emission anomalies, new NH‐SH positive tracer anomalies should have occurred in 2020, and predicts small negative anomalies in 2021. Plain Language Summary: Changes in the North‐South difference of surface trace gas abundances, denoted NH‐SH, are often used as evidence of new emissions. However, atmospheric dynamics can also influence measurements of NH‐SH. Importantly, anomalies in trace gas abundances in the stratosphere are transported down to the troposphere, influencing tropospheric NH‐SH values. We quantify the stratospheric influence on NH‐SH in models and observations for CFC‐11, CFC‐12, and N2O. We provide a simple model to account for future stratospheric anomalies at the surface. Our model suggests that 60% of the variability in NH‐SH can be explained by stratospheric anomalies. Following 2013, there was a sustained positive NH‐SH anomaly in observations. Our results indicate that stratospheric influences can only partially explain this anomaly, supporting earlier work that an expected emission led to the observed positive NH‐SH anomaly. This work shows that stratospheric observations improves interpretation of future emissions. Key Points: Stratospheric anomalies in trace gas mole fractions influence tropospheric North‐South tracer differences and provide predictabilityOur model suggests 0.5 ± 0.1 ppt of the NH‐SH surface growth in CFC‐11 after 2012 can be explained by stratospheric anomaliesIn the absence of anomalous emissions, 60%–70% of the variability in NH‐SH tracers can be explained by stratospheric anomalies [ABSTRACT FROM AUTHOR]