Stratospheric ozone in the Earth system

Ozone in the stratosphere protects life on Earth by absorbing much of the ultraviolet solar radiation, as well as being a major source of ozone to the troposphere. A number of factors can influence stratospheric ozone levels and explain past, present and future changes. While there is a large literature exploring changes in stratospheric ozone due to, for example, ozone depleting substances (ODSs) and climate change, the study of its interactions with the rest of the Earth system is relatively recent. The work presented in this thesis investigates changes in stratospheric ozone and its links with other elements of the Earth system (tropospheric chemical composition and climate), using observations, a global chemistry-climate model (CESM1-WACCM), and existing multi-model output. This work evaluates past changes and explores future evolution of stratospheric ozone and associated climate impacts using multi-model output (ACCMIP simulations) from the pre-industrial period to the end of the 21st century. ACCMIP multi-model mean total column ozone trends compare favourably against observations. These models show a strong link between the Antarctic ozone hole and surface climate, which demonstrates that stratospheric ozone changes are coupled with the troposphere. A series of sensitivity simulations is conducted to investigate multi-decadal variability. A striking finding is that low frequency variability of ozone in the tropical middle stratosphere resembles multi-decadal climate variability in Pacific Ocean sea surface temperatures. This analysis also shows that internally generated climate variability is the leading factor explaining recent negative trends of mid-stratospheric tropical ozone. Finally, an additional set of sensitivity simulations is performed to quantify future radiative forcing between 2000s and 2100s that results from changes in ozone due to climate change, ODSs and methane concentrations. These results highlight the importance of stratosphere-troposphere exchange, as well as the key role of the stratosphere controlling the tropospheric ozone forcing

Stratospheric ozone change and related climate impacts over 1850-2100 as modelled by the ACCMIP ensemble

Stratospheric ozone and associated climate impacts in the Atmospheric Chemistry and Climate Model Intercomparison Project (ACCMIP) simulations are evaluated in the recent past (1980–2000), and examined in the long-term (1850–2100) using the Representative Concentration Pathways (RCPs) low- and high-emission scenarios (RCP2.6 and RCP8.5, respectively) for the period 2000–2100. ACCMIP multi-model mean total column ozone (TCO) trends compare favourably, within uncertainty estimates, against observations. Particularly good agreement is seen in the Antarctic austral spring (−11.9 % dec−1 compared to observed  ∼  −13.9 ± 10.4 % dec−1), although larger deviations are found in the Arctic's boreal spring (−2.1 % dec−1 compared to observed  ∼  −5.3 ± 3.3 % dec−1). The simulated ozone hole has cooled the lower stratosphere during austral spring in the last few decades (−2.2 K dec−1). This cooling results in Southern Hemisphere summertime tropospheric circulation changes captured by an increase in the Southern Annular Mode (SAM) index (1.3 hPa dec−1). In the future, the interplay between the ozone hole recovery and greenhouse gases (GHGs) concentrations may result in the SAM index returning to pre-ozone hole levels or even with a more positive phase from around the second half of the century (−0.4 and 0.3 hPa dec−1 for the RCP2.6 and RCP8.5, respectively). By 2100, stratospheric ozone sensitivity to GHG concentrations is greatest in the Arctic and Northern Hemisphere midlatitudes (37.7 and 16.1 DU difference between the RCP2.6 and RCP8.5, respectively), and smallest over the tropics and Antarctica continent (2.5 and 8.1 DU respectively). Future TCO changes in the tropics are mainly determined by the upper stratospheric ozone sensitivity to GHG concentrations, due to a large compensation between tropospheric and lower stratospheric column ozone changes in the two RCP scenarios. These results demonstrate how changes in stratospheric ozone are tightly linked to climate and show the benefit of including the processes interactively in climate models

Non-Linear Dimensionality Reduction with a Variational Autoencoder Decoder to Understand Convective Processes in Climate Models

Deep learning can accurately represent sub-grid-scale convective processes in climate models, learning from high resolution simulations. However, deep learning methods usually lack interpretability due to large internal dimensionality, resulting in reduced trustworthiness in these methods. Here, we use Variational AutoEncoder (VAE) decoder structures, a non-linear dimensionality reduction technique, to learn and understand convective processes in an aquaplanet superparameterized climate model simulation, where deep convective processes are simulated explicitly. We show that similar to previous deep learning studies based on feed-forward neural nets, the VAE is capable of learning and accurately reproducing convective processes. In contrast to past work, we show this can be achieved by compressing the original information into only five latent nodes. As a result, the VAE can be used to understand convective processes and delineate modes of convection through the exploration of its latent dimensions. A close investigation of the latent space enables the identification of different convective regimes: a) stable conditions are clearly distinguished from deep convection with low outgoing longwave radiation and strong precipitation; b) high optically thin cirrus-like clouds are separated from low optically thick cumulus clouds; and c) shallow convective processes are associated with large-scale moisture content and surface diabatic heating. Our results demonstrate that VAEs can accurately represent convective processes in climate models, while enabling interpretability and better understanding of sub-grid-scale physical processes, paving the way to increasingly interpretable machine learning parameterizations with promising generative properties.Comment: main paper: 28 pages, 11 figures; supporting informations: 27 pages, 12 figures, 11 tables; Submitted to 'Journal of Advances in Modeling Earth Systems' (JAMES

Causally-informed deep learning to improve climate models and projections

Climate models are essential to understand and project climate change, yet long-standing biases and uncertainties in their projections remain. This is largely associated with the representation of subgrid-scale processes, particularly clouds and convection. Deep learning can learn these subgrid-scale processes from computationally expensive storm-resolving models. Yet, climate simulations with embedded neural network parameterizations are still challenging and highly depend on the deep learning solution. This is likely associated with spurious non-physical correlations learned by the neural networks due to the complexity of the physical dynamical system. We apply a causal discovery method to unveil key physical drivers in the set of input predictors of atmospheric subgrid-scale processes of a superparameterized climate model. We show that the climate simulations with causally-informed neural network parameterizations clearly outperform the non-causal approach. These results demonstrate that the combination of causal discovery and deep learning helps removing spurious correlations and optimizing the neural network algorithm

Seasonal impact of biogenic very short-lived bromocarbons on lowermost stratospheric ozone between 60° N and 60° S during the 21st century

Biogenic very short-lived bromocarbons (VSLBr) currently represent ∼25 % of the total stratospheric bromine loading. Owing to their much shorter lifetime compared to anthropogenic long-lived bromine (e.g. halons) and chlorine (e.g. chlorofluorocarbons), the impact of VSLBr on ozone peaks in the lowermost stratosphere, which is a key climatic and radiative atmospheric region. Here we present a modelling study of the evolution of stratospheric ozone and its chemical loss within the tropics and at mid-latitudes during the 21st century. Two different experiments are explored: considering and neglecting the additional stratospheric injection of 5 ppt biogenic bromine naturally released from the ocean. Our analysis shows that the inclusion of VSLBr results in a realistic stratospheric bromine loading and improves the agreement between the model and satellite observations of the total ozone column (TOC) for the 1980?2015 period at mid-latitudes. We show that the overall ozone response to VSLBr at mid-latitudes follows the stratospheric evolution of long-lived inorganic chlorine and bromine throughout the 21st century. Additional ozone loss due to VSLBr is maximized during the present-day period (1990?2010), with TOC differences of −8 DU (−3 %) and −5.5 DU (−2 %) for the Southern Hemisphere and Northern Hemisphere mid-latitudes (SH-MLs and NH-MLs), respectively. Moreover, the projected TOC differences at the end of the 21st century are ∼50 % lower than the values found for the present-day period.We find that seasonal VSLBr impact on lowermost stratospheric ozone at mid-latitude is influenced by the seasonality of the heterogeneous inorganic-chlorine reactivation processes on ice crystals. Indeed, due to the more efficient reactivation of chlorine reservoirs (mainly ClONO2 and HCl) within the colder SH-ML lowermost stratosphere, the seasonal VSLBr impact shows a small but persistent hemispheric asymmetry through the whole modelled period. Our results indicate that, although the overall VSLBr-driven ozone destruction is greatest during spring, the halogen-mediated (Halogx-Loss) ozone loss cycle in the mid-latitude lowermost stratosphere during winter is comparatively more efficient than the HOx cycle with respect to other seasons. Indeed, when VSLBr are considered, Halogx-Loss dominates wintertime lowermost stratospheric ozone loss at SH-MLs between 1985 and 2020, with a contribution of inter-halogen ClOx?BrOx cycles to Halogx-Loss of ∼50 %.Within the tropics, a small (<−2.5 DU) and relatively constant (∼−1 %) ozone depletion mediated by VSLBr is closely related to their fixed emissions throughout the modelled period. By including the VSLBr sources, the seasonal Halogx-Loss contribution to lowermost stratospheric ozone loss is practically dominated by the BrOx cycle, reflecting the low sensitivity of very short-lived (VSL) bromine to background halogen abundances to drive tropical stratospheric ozone depletion. We conclude that the link between biogenic bromine sources and seasonal changes in heterogeneous chlorine reactivation is a key feature for future projections of mid-latitude lowermost stratospheric ozone during the 21st century.Fil: Barrera, Javier Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto Interdisciplinario de Ciencias Básicas. - Universidad Nacional de Cuyo. Instituto Interdisciplinario de Ciencias Básicas; ArgentinaFil: Fernandez, Rafael Pedro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto Interdisciplinario de Ciencias Básicas. - Universidad Nacional de Cuyo. Instituto Interdisciplinario de Ciencias Básicas; Argentina. Consejo Superior de Investigaciones Científicas; España. Universidad Tecnológica Nacional; ArgentinaFil: Iglesias Suarez, Fernando. Consejo Superior de Investigaciones Científicas; EspañaFil: Cuevas, Carlos Alberto. Consejo Superior de Investigaciones Científicas; EspañaFil: Lamarque, Jean Francois. National Center for Atmospheric Research; Estados UnidosFil: Saiz-lopez, Alfonso. Consejo Superior de Investigaciones Científicas; Españ

Deep Learning Based Cloud Cover Parameterization for ICON

A promising approach to improve cloud parameterizations within climate models and thus climate projections is to use deep learning in combination with training data from storm-resolving model (SRM) simulations. The ICOsahedral Non-hydrostatic (ICON) modeling framework permits simulations ranging from numerical weather prediction to climate projections, making it an ideal target to develop neural network (NN) based parameterizations for sub-grid scale processes. Within the ICON framework, we train NN based cloud cover parameterizations with coarse-grained data based on realistic regional and global ICON SRM simulations. We set up three different types of NNs that differ in the degree of vertical locality they assume for diagnosing cloud cover from coarse-grained atmospheric state variables. The NNs accurately estimate sub-grid scale cloud cover from coarse-grained data that has similar geographical characteristics as their training data. Additionally, globally trained NNs can reproduce sub-grid scale cloud cover of the regional SRM simulation. Using the game-theory based interpretability library SHapley Additive exPlanations, we identify an overemphasis on specific humidity and cloud ice as the reason why our column-based NN cannot perfectly generalize from the global to the regional coarse-grained SRM data. The interpretability tool also helps visualize similarities and differences in feature importance between regionally and globally trained column-based NNs, and reveals a local relationship between their cloud cover predictions and the thermodynamic environment. Our results show the potential of deep learning to derive accurate yet interpretable cloud cover parameterizations from global SRMs, and suggest that neighborhood-based models may be a good compromise between accuracy and generalizability

Tropospheric Chemical Impact of Considering a Surrogate vs. an Explicit VSLBr Mechanism on the O3 and HOx Distributions within the CAM-Chem model

The contribution of very short-lived bromine (VSLBr) represent 5 ± 2 ppt (∼25%) of total stratospheric bromine (WMO, 2018), which is still nowadays dominated by long-lived bromocarbons that do not impact on tropospheric chemistry. Due to their shorter lifetimes, the overall injection to the stratosphere of VSLBr compounds possesses two distinct pathways: i) Source Gas Injection (SGI), where the brominated species are injected as they were emitted at the surface; and ii) Product Gas Injection (PGI), where the photochemical processing of reactive species arising from SG degradation must be considered. Depending on the partitioning and distribution of SGI and PGI, the chemical impact of VSLBr on tropospheric and lowermost stratospheric ozone, HOx and other oxidizing species can be very different. Many Chemistry Climate Models (CCMs) include a simplified treatment of tropospheric VSLBr sources by assuming a long-lived halocarbon (usually CH3Br) as a Surrogate for VSLBr. Even though these surrogate models possess a consistent evolution of the stratospheric bromine loading, CCMs including an explicit VSLBr representation compare better with organic and inorganic bromine observations in the lowermost stratosphere (Wales et al., 2018). Here we used the halogenated version of the CAM-Chem model (Fernandez et al., 2014) to evaluate the chemical impact of considering an explicit treatment of VSLBr versus considering a simplified tropospheric treatment of long-lived CH3Br as surrogate of VSLBr. The explicit mechanism considers a full gas- and aerosol- phase chemical scheme (including sea-salt dehalogenation) as well as time dependent and geographically-distributed VSLBr emissions inventory (Ordoñez et al., 2012), which replaces the typical lower-boundary surface conditions for longlived compounds usually considered in CCMs. An additional baseline simulation neglecting the contribution of VSLBr is also considered. First we show the differences in the overall inorganic bromine (Bry) burden as a function of altitude, latitude and time of the year, and compare the model changes on SGI and PGI for each model configuration. Based on the vertical and latitudinal Bry distributions, we focus the analysis on determining the surrogate vs. explicit VSLBr impact on the tropospheric ozone burden, as well as the changes in HOx and NOx mixing ratios within different regions. In particular, seasonal variations in the Odd-Oxygen chemical loss channels during within the marine boundary layer (MBL), tropical tropopause layer (TTL) and mid-latitudes upper troposphere (UT) are evaluated. Our results indicate that the impact of VSLBr species is strongly underestimated when a simplified treatment of tropospheric VSLBr chemistry is considered, which might have strong climatic impacts.Fil: Fernández, Rafael Pedro. Universidad Nacional de Cuyo. Facultad de Ciencias Exactas y Naturales. Departamento de Física; Argentina. Consejo Superior de Investigaciones Científicas. Instituto de Química Física; España. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza; ArgentinaFil: Barrera, Javier Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza; Argentina. Universidad Nacional de Cuyo. Facultad de Ciencias Exactas y Naturales. Departamento de Física; ArgentinaFil: Iglesias Suarez, Fernando. Consejo Superior de Investigaciones Científicas. Instituto de Química Física; EspañaFil: Cuevas, Carlos Alberto. Consejo Superior de Investigaciones Científicas. Instituto de Química Física; EspañaFil: Kinnison, Douglas E.. No especifíca;Fil: Lamarque, Jean Francoise. No especifíca;Fil: Tilmes, Simone. No especifíca;Fil: Wales, Pamela. University of Maryland; Estados UnidosFil: Nicely, Julie M.. No especifíca;Fil: Salawitch, Ross J.. University of Maryland; Estados UnidosFil: Saiz Lopez, Alfonso. Consejo Superior de Investigaciones Científicas. Instituto de Química Física; España. University of Maryland; Estados UnidosEGU General Assembly 2019VienaAustriaEuropean Geosciences Unio

Climate policy implications of nonlinear decline of Arctic land permafrost and other cryosphere elements

Arctic feedbacks accelerate climate change through carbon releases from thawing permafrost and higher solar absorption from reductions in the surface albedo, following loss of sea ice and land snow. Here, we include dynamic emulators of complex physical models in the integrated assessment model PAGE-ICE to explore nonlinear transitions in the Arctic feedbacks and their subsequent impacts on the global climate and economy under the Paris Agreement scenarios. The permafrost feedback is increasingly positive in warmer climates, while the albedo feedback weakens as the ice and snow melt. Combined, these two factors lead to significant increases in the mean discounted economic effect of climate change: +4.0% ($24.8 trillion) under the 1.5 °C scenario, +5.5$33.8 trillion) under the 2 °C scenario, and +4.8% ($66.9 trillion) under mitigation levels consistent with the current national pledges. Considering the nonlinear Arctic feedbacks makes the 1.5 °C target marginally more economically attractive than the 2 °C target, although both are statistically equivalent.This work is part of the ICE-ARC project funded by the European Union’s 7th Framework Programme, (grant 603887, contribution 006). D.Y. received additional funding from ERIM, Erasmus University Rotterdam, and Paul Ekins at the ISR, University College London. K.S. was funded by NSF (grant 1503559) and NASA (grants NNX14A154G, NNX17AC59A). E.J. was funded by the NGEE Arctic project supported by the BER Office of Science at the U.S. DOE. Y.E. was funded by the NSF (grant 1900795). E.B. was supported by the UK Met Office Hadley Centre Climate Programme funded by BEIS and DEFRA

IL-6 serum levels predict severity and response to tocilizumab in COVID-19: An observational study

Background: Patients with coronavirus disaese 2019 (COVID-19) can develop a cytokine release syndrome that eventually leads to acute respiratory distress syndrome requiring invasive mechanical ventilation (IMV). Because IL-6 is a relevant cytokine in acute respiratory distress syndrome, the blockade of its receptor with tocilizumab (TCZ) could reduce mortality and/or morbidity in severe COVID-19. Objective: We sought to determine whether baseline IL-6 serum levels can predict the need for IMV and the response to TCZ. Methods: A retrospective observational study was performed in hospitalized patients diagnosed with COVID-19. Clinical information and laboratory findings, including IL-6 levels, were collected approximately 3 and 9 days after admission to be matched with preadministration and postadministration of TCZ. Multivariable logistic and linear regressions and survival analysis were performed depending on outcomes: need for IMV, evolution of arterial oxygen tension/fraction of inspired oxygen ratio, or mortality. Results: One hundred forty-six patients were studied, predominantly males (66%); median age was 63 years. Forty-four patients (30%) required IMV, and 58 patients (40%) received treatment with TCZ. IL-6 levels greater than 30 pg/mL was the best predictor for IMV (odds ratio, 7.1; P < .001). Early administration of TCZ was associated with improvement in oxygenation (arterial oxygen tension/fraction of inspired oxygen ratio) in patients with high IL-6 (P = .048). Patients with high IL-6 not treated with TCZ showed high mortality (hazard ratio, 4.6; P = .003), as well as those with low IL-6 treated with TCZ (hazard ratio, 3.6; P = .016). No relevant serious adverse events were observed in TCZ-treated patients. Conclusions: Baseline IL-6 greater than 30 pg/mL predicts IMV requirement in patients with COVID-19 and contributes to establish an adequate indication for TCZ administrationThis study was funded by Spanish Ministry of Economy, Industry and Competitiveness (MINECO) and Instituto de Salud Carlos III (grant nos. RD16/0011/0012 and PI18/ 0371 to I.G.A., grant no. PI19/00549 to A.A., and grant no. SAF2017-82886-R to F.S.-M.) and co-funded by the European Regional Development Fund. The study was also funded by ‘‘La Caixa Banking Foundation’’ (grant no. HR17-00016 to F.S.-M.) and ‘‘Fondos Supera COVID19’’ by Banco de Santander and CRUE. None of these sponsors have had any role in study design; in the collection, analysis, and interpretation of data; in the writing of the report; and in the decision to submit the article for publicatio

Correction : Chaparro et al. Incidence, Clinical Characteristics and Management of Inflammatory Bowel Disease in Spain: Large-Scale Epidemiological Study. J. Clin. Med. 2021, 10, 2885

The authors wish to make the following corrections to this paper [...]