Arctic stratospheric ozone as a precursor of ENSO events since 2000s

Arctic stratospheric ozone as a precursor of ENSO events since 2000s | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Arctic stratospheric ozone as a precursor of ENSO events since 2000s Jae-Heung Park, Ja-ho Koo, Jong-Seong Kug, Su-Jung Lee, Mi-Kyung Sung, and 8 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5942136/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Recent depletion of the Arctic Stratospheric Ozone (ASO) has raised significant concerns about its impact on surface climate and weather. By analyzing observational reanalysis dataset and the Ozone Monitoring Instrument, here we found that the relevant variations in springtime ASO can be a potential precursor of El Niño–Southern Oscillation in the subsequent winter since 2000s. During this period, springtime ASO variability become pronounced, particularly over the Eurasian continent, due to the asymmetrical structure of the Arctic stratospheric polar vortex. With the return of solar radiation to the Arctic in spring, increased ASO leads to more absorption of solar radiation over Eurasia, contributing to localized anomalous heating. This stratospheric heating induces upper-tropospheric cyclonic circulation over Siberia, resulting in the propagation of atmospheric stationary waves toward the tropical Pacific. As a result, upper-level easterly and low-level westerly wind anomalies emerge over the equatorial Pacific. This baroclinic atmospheric anomaly over the equatorial Pacific promotes El Niño development by modulating the Walker circulation (c.f., La Niña for the opposite case). These results highlight the critical role of chemical-radiative-dynamical processes in the Arctic stratosphere for understanding surface climate phenomena. Earth and environmental sciences/Climate sciences/Atmospheric science Earth and environmental sciences/Climate sciences/Ocean sciences Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Stratospheric ozone plays two primary roles in Earth’s system. First, it protects both plants and animals by absorbing harmful ultraviolet radiations which are detrimental to their health and survival 1–4 . Second, by absorbing solar radiations, it regulates large-scale atmospheric circulations 5–8 , which in turn influences global scale hydrological cycles 9–11 . That is, the influences of stratospheric ozone extend beyond ecosystems, affecting climate and weather patterns. In this context, the significant depletion of stratospheric ozone–caused by the use of chlorofluorocarbons (CFCs)–has been a major concern and the focus of extensive research 2,5,12–18 since its first detection over the Antarctic in 1985 (i.e., ozone hole, less than 220 Dobson Units) 19 . For the Arctic, ozone depletion events have been reported since mid-1990s 20–24 . Particularly, the Arctic stratospheric ozone (ASO) depletion in 2020 25–28 reached levels comparable to those of the Antarctic ozone hole. However, both the frequency and intensity of ozone depletion over the Arctic are typically lower and more irregular than those over the Antarctic. The difference between the two poles arises from the greater atmospheric variability over the Arctic, in association with Stratospheric Polar Vortex (SPV) 29 and Brewer–Dobson Circulation (BDC) 30 . The SPV and BDC are also thermodynamically interconnected 31 , i.e., strong (weak) SPV accompanies weak (strong) BDC. When the SPV strengthens, accompanying extremely cold temperatures (below -80°C), greater chemical ozone depletion occurs due to higher concentrations of active chlorine on the polar stratospheric clouds (PSCs). A strong SPV also limits air mixing into the vortex, and also reduces the ozone transport from the tropics and summer hemisphere to the Arctic via the BDC 31 . In short, ASO is more likely to be depleted when the SPV is strong and the BDC is weak, and vice versa. It has been reported that the variability of ASO can influence surface climate and weather patterns, particularly in the spring when solar radiation returns to the Arctic 32–34 . Studies have shown that depleted springtime ASO has contributed to Arctic Sea ice reduction by increasing both sea ice outflow toward the Atlantic Ocean and surface net heat fluxes 35 . Additionally, extreme ASO depletion modifies atmospheric stability and leads to the formation of high clouds, which increases downward longwave radiation, linking to surface warming over Siberia 32 . ASO variability also affects sea surface temperature (SST) anomalies in the North Pacific via atmospheric teleconnections. 36 Notably, Xie et al. (2016) 37 proposed that a decrease (increase) in springtime ASO leads to El Nino (La Nina) with about a 20-month lag, linked to the North Pacific Oscillation and the Victoria mode (a.k.a., North Pacific Gyre Oscillation) based on the analysis of reanalysis dataset from 1986 to 2015. Meanwhile, significant changes in the characteristics of the SPV have been observed since the 2000s 38,39 , coinciding with Arctic climate changes 40–42 . The SPV has weakened due to factors such as the Arctic sea ice loss 43–45 and increased snow cover 46,47 , and it now tends to exhibit a more asymmetrical structure 45,48 . This altered feature of SPV is expected to impact the spatiotemporal distribution of ASO 45,46,49 . Consequently, the modified ASO may trigger weather and climate phenomena that differ from those observed in earlier periods 34 . However, research on this topic remains limited and requires further investigation. As noted earlier, a previous study showed that ASO was negatively correlated with ENSO through pathways in the North Pacific during 1986-2015, with a lag of approximately 20 months 37 . Based on the previous findings, this study revisits the mechanism through which ASO has affected the tropical Pacific since the 2000s, aligned with recent SPV changes. We analyzed two observational reanalysis datasets (ECMWF Reanalysis Version 5 (ERA5) for the main figures and Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA2) for the supplementary figures) as well as Ozone Monitoring Instrument (OMI). The consistent results across datasets suggest that springtime ASO has the potential to be a precursor of ENSO events in the following winter with a lag of 8 months through atmospheric teleconnections across the Eurasian continent. We discuss the implications of these findings for how the stratosphere influences troposphere and contributes to the development of ENSO events in recent decades. Results A new connection between spring ASO and the following winter ENSO since 2000 To explore the decadal modulation of the ASO–ENSO relationship from 1980 to 2023, we conducted a 252-month running lead-lag correlation analysis between ASO and ENSO indices on a monthly timescale. Herein, the monthly ASO index is obtained by averaging monthly ozone concentration over 70–90°N at 100–200hPa, while the monthly Nino3.4 index (c.f., Nino3.4 region: 120–170°W, 5°S-5°N) is adopted as the monthly ENSO index. To focus on variability, we removed climatological mean and trends from both the monthly ASO and ENSO indices within each 252-month running window, although this detrending had minimal effect on our result because their trends are small. The results of the lead-lag correlation analysis are illustrated in Fig. 1 a (refer to Supplementary Fig. 1 for MERRA2), where negative values on x-axis indicate how many months ASO leads ENSO, and positive values indicate how many months ENSO leads ASO. Overall, the ENSO-leading-ASO signals are not significant and remain mostly positive throughout the period. In contrast, the ASO-leading-ENSO signals undergo a pronounced change around the early 2000s. Before this period, ASO negatively led ENSO with approximately a 20-month lag, with the strongest signals observed in the mid-to-late 1990s. Here, the negative correlation indicates that a stratospheric condition with increased ozone concentrations tends to lead to La Nina 20 months later. This finding aligns with the previous study by Xie et al. (2016) 37 . However, these negative ASO-leading-ENSO signals gradually weakened over time, while positive ASO-leading-ENSO signals with an 8-month lag emerged after the early 2000s. The result from Fig. 1 a reveals the emergence of an unprecedent ASO–ENSO relationship since the early 2000s, which indicates that increased ozone concentrations lead to El Nino during the current decades. Building on this, we further examined their lead-lagged correlation, focusing on the recent period from 2002 to 2023 (the second half of the total period from 1980 to 2023). Similar to Fig. 1 a, the x-axis in Fig. 1 b indicates how many months ASO leads the ENSO indices, while the y-axis indicates the calendar months from November (bottom) to October (top). It shows that ASO-leading-ENSO signals are significant when ASO from March to April leads ENSO by 2 to 10 months. The highest correlation coefficient is 0.63 when ASO in April leads ENSO in the following November. These results suggest that springtime ASO tends to lead ENSO in the following winter season since the early 2000s. Based on Fig. 1 b, we defined a March–April (MA) ASO index and a November–December (ND) ENSO index by averaging the monthly ASO and ENSO indices for March to April and November to December, respectively. Figure 1 c shows both the MA-ASO and ND-ENSO indices. Their correlation coefficient is 0.57, which is statistically significant at the 99% confidence level. In addition to the reanalysis datasets, we utilized satellite data, OMI/Aura Ozone (OMTO3, Method). Although OMTO3 provides total column ozone (TCO), instead of three-dimensional ozone, and its temporal coverage is relatively short, spanning from 2005 to 2023, TCO serves as a suitable proxy for stratospheric ozone due to the highest ozone concentrations occurring in the stratosphere. Following a method applied to the ASO index, we obtained an Arctic TCO index by averaging TCO over 70–90°N during March-April, wherein climatological mean and trends are removed (Fig. 1 c). We found that the correlation coefficient between MA-Arctic-TCO and MA-ASO indices is 0.79 (0.80 for MERRA2, Supplementary Fig. 1), statistically significant at the 99% confidence level. Also, the correlation coefficient between MA-Arctic TCO and ND-ENSO indices is 0.52 (0.52 for MERRA2, Supplementary Fig. 1), statistically significant at the 95% confidence level. These findings align with results from the reanalysis dataset, supporting the reliability of observational reanalysis data since the 2000s. How springtime ASO affects subsequent wintertime ENSO? We aim to investigate how the springtime ASO is linked to the subsequent wintertime ENSO events since the early 2000s. To do this, we regressed ozone concentration, air temperature, and wind anomalies at 200hPa from February–March (FM) to May–June (MJ) (Fig. 2 a-d) and wind anomalies at 850hPa and SST anomalies from March–April (MA) to November–December (ND) (Fig. 2 e-h) regressed onto the MA–ASO index (Supplementary Fig. 2–3 for MERRA2). We note that the results below remain largely unchanged even when simultaneous ENSO signals are removed from ASO index (Supplementary Fig. 4), indicating that our findings are not influenced by the ENSO autocorrelation effect. In February–March (Fig. 2 a), ozone concentration is significantly elevated across the Arctic, accompanied by large-scale anomalous warming over the Arctic and circumpolar easterly wind anomalies. These results are in line with weakened SPV and strengthened BDC, as the weakened SPV favors reduced chemical ozone depletion and the strengthened BDC enables more ozone intrusion from the tropics to the Arctic. Simultaneously, the downward motion associated with the strengthened BDC causes adiabatic warming over the Arctic. As SPV becomes weakened and contracts from winter to spring, significant easterly wind anomalies are only observed over the high-latitudes of Eurasia in March–April (Fig. 2 b). Simultaneously, the localized warming over the high latitudes of the Eurasian continent occurs under weakened downward motion of the BDC during the transition from winter to spring. For ozone, its concentrations remain elevated across the Arctic. However, they become increasingly concentrated over the Eurasian continent, coinciding with a warming pattern. It is inferred that the absorption of solar radiation by the elevated ozone concentrations intensifies this localized warming, as sunlight returns to the Arctic in spring following the polar night. At this moment, cyclonic circulation of the southern area of the easterly wind anomalies and warming begins to form. In April–May (Fig. 2 c), the tropospheric upper-level cyclonic circulation anomaly over Siberia develops further with anomalous stratospheric warming and enhanced ozone concentrations. This localized warming is also pronounced at higher altitudes (e.g., 50hPa), and disappears at lower altitudes (e.g., 300hPa), indicating thermal expansion centered over the stratosphere. It is known that negative (positive) geopotential height anomalies are located over the bottom (upper) part of the thermal expansion. In this regard, anomalous cyclonic circulation could be located at the bottom area of the thermal expansion. Thus, the upper-tropospheric cyclonic circulation anomaly emerges over Siberia in Fig. 2 b. Notably, this cyclonic circulation anomaly generates atmospheric waves that propagate southeastward, creating a sequence of anticyclonic, cyclonic, and anticyclonic circulations over East Asia, the western North Pacific, and the subtropical North Pacific, respectively. In other words, the atmospheric wave propagation extends from Siberia to the tropical Pacific. As a result, easterly wind anomalies develop along the western to central equatorial Pacific, persisting into May–June (Fig. 2 d). These upper-level easterly wind anomalies are expected to be connected to the lower-level westerly wind anomalies, reflecting the baroclinic vertical structure over the equatorial Pacific 50 , 51 , which helps to initiate the development of El Nino. Meanwhile, Fig. 2 e-h illustrates SST and low-level wind anomalies at 850hPa from MA to ND seasons, in association with the MA-ASO index. In March–April (Fig. 2 e), easterly and northeasterly wind anomalies are observed over the high latitudes of Eurasia and western Siberia. Regarding these wind anomalies, an anomalous cyclonic circulation over Siberia is observed in April–May (Fig. 2 f). This circulation appears to be connected to the anticyclonic circulation over the Korea–Japan region and a cyclonic circulation over the tropical western North Pacific, forming a wave-like pattern. These findings suggest a tropospheric pathway linking the high latitudes of Eurasia to the tropical Pacific, with a vertical connection driven by upper-level circulations. Over the tropical Pacific, westerly wind anomalies begin to develop over the western tropical Pacific from March–April to May–June (Fig. 2 e-g), in association with upper-level easterly wind anomalies. These low-level westerly wind anomalies initiate anomalous SST warming along the equatorial Pacific through the Bjerknes feedback, likely driving the development of an El Nino from spring to winter (Fig. 2 h). The role of ASO-relevant forcing in modulating atmospheric circulations Figure 2 demonstrates that a stratospheric warming over Siberia associated with the ASO in spring accompanies an upper-tropospheric cyclonic circulation anomaly, which becomes a source of atmospheric waves propagating toward the tropical Pacific 52 , 53 . To examine how the upper-level cyclonic circulation over Siberia generates atmospheric waves that propagate toward the tropical Pacific, we utilized the Stationary Wave Model (SWM)—a simplified atmospheric general circulation model (details provided in the Methods). For this experiment, the climatological mean state of the atmosphere during spring 2002–2023 was used as the background atmospheric condition. Then, vorticity forcing over Siberia, resembling the upper-level cyclonic circulation in Fig. 2 c, was applied to assess its effect on stationary atmospheric circulation. Figure 3 a illustrates the horizontal and vertical structure of atmospheric vorticity forcing, with a maximum at the 0.17 sigma level. The corresponding anomalous stationary atmospheric response at the same level is shown in Fig. 3 b. Notably, this atmospheric response remains consistent even with slight adjustments to the horizontal or vertical location of the vorticity forcing. In Fig. 3 b, the response shows a series of cyclonic and anticyclonic flows over Siberia, the western North Pacific, the subtropical western North Pacific, and the tropical Pacific, under the background atmospheric state of April–May. This identical wave propagation pattern is also obtained under background atmospheric state of March–April (Supplementary Fig. 5). This stationary wave pattern closely resembles the atmospheric waves regressed onto the MA-ASO index (Fig. 2 c). Thus, the results from the SWM suggest that vorticity forcing induced by ASO can generate atmospheric waves propagating toward the tropical Pacific, influencing the development of ENSO. To diagnose the direction of wave propagation associated with upper-level cyclonic circulation over Siberia during spring, we analyzed the wave activity flux (WAF) 54 at 200hPa for April–May (Fig. 3 c and Supplementary Fig. 5 for March–April) under conditions of enhanced springtime ASO (Fig. 2 c) from ERA5. The results reveal that the WAF propagates from Siberia through East Asia to the western North Pacific. These findings, derived from the SWM experiment and WAF analysis, underscore the role of springtime ASO in modulating upper-level atmospheric circulation through atmospheric heating. The role of SPV changes in the ASO–ENSO relationship Figure 1 a shows that the lagged ASO–ENSO relationship has changed since the early 2000s. This change coincides with the notable changes in the Arctic such as a significant decline in sea ice (c.f., polar amplification). Given these changes, it is essential to investigate how the climatological mean state changes have influenced the ASO–ENSO relationships. Previous studies have shown that the SPV weakened after the 2000s, coinciding with an increase in Eurasian snow cover and enhanced vertically propagation of planetary waves 46 , 47 . Additionally, the shape of SPV transitioned from a symmetric, circular structure to more asymmetric forms, such as a tilt toward Eurasia or a split, "peanut-shaped" pattern, which has become more frequent. To investigate SPV changes after the 2000s, we analyzed 21 years of data from two periods: the first half period (1980–2001) and the second half period (2002–2023). Figure 4 shows the zonal wind, geopotential height, and temperature at 100hPa for February–March and March–April, regressed onto the zonal wind index, which is obtained by averaging the zonal wind at 100hPa over the 60–90°N in February (Supplementary Fig. 6 for MERRA2). During 1980–2001, the SPV maintained its strength well in February–March and it remained relatively symmetric although it slightly weakened in March–April. In contrast, during 2002–2023, the SPV retained a symmetric structure in February–March, but became more asymmetric in March–April, with increased variability toward both Eurasia and North America. The tilt toward the Eurasian continent became more pronounced 38 , 39 , providing a favorable condition for pronounced ozone variability over this region compared to other region, (Supplementary Fig. 7), which, in turn, is expected to induce change in weather and climate 32 . In summary, the changes in SPV characteristics after the 2000s provide a favorable condition for increased ozone variability over Eurasia in spring, which contributes to the generation of atmospheric waves toward the tropical Pacific and thus the emergence of the ASO–ENSO correlation observed in recent decades. Discussion A previous study by Xie et al. (2016) 37 , which analyzed observational reanalysis data from 1986 to 2015, identified a negative relationship between springtime ASO variations and the occurrence of ENSO events approximately 20 months later through a North Pacific pathway. Building on this, we revisited the ASO-ENSO relationship during the period from 1980 to 2023, a time of significant Arctic climate change. Our findings reveal a shift to a positive ASO–ENSO relationship during 2002–2023, where increases or decreases in ASO now lead to the development of El Niño or La Niña with an 8-month lag via a Eurasia pathway. We mainly attribute this different ASO–ENSO relationship between the two periods to the modified horizontal distribution of ASO, subjected to the SPV characteristics. Therefore, examination of both SPV characteristics and horizontal distribution of ASO would be beneficial to understand how the stratosphere affects tropospheric atmospheric circulations. Chemistry climate models projected that BDC will increase under global warming period 55 – 57 , in which weak and asymmetric structure of the SPV is expected. As long as the recent ASO–ENSO correlation seems to be connected to the weakening and asymmetric structure of the SPV and strengthened BDC, their relationship is expected to remain significant in future climates. Nonetheless, to gain deeper insight, it will be essential to compare historical data with global warming scenarios from various climate models, while considering the underlying chemical, radiative, and dynamic processes. This approach will be critical for understanding future climate variability and change. Method Stationary Wave Model (SWM) The SWM is a nonlinear baroclinic model with a dry dynamical core and 14 vertical levels on sigma coordinates. Its horizontal resolution is truncated at rhomboidal 30. This model was devised to understand how the atmospheric stationary waves propagate given atmospheric perturbations. To perform SWM experiments, the (mostly monthly or seasonal) background atmospheric state is first fixed. Then, under the fixed background state, steady atmospheric vorticity or heating forcings are prescribed until stationary atmospheric waves are obtained (mostly 30 to 60 days). The response to the forcing shown in Fig. 4 is averaged for 55 days, since the steady forcing is exerted. Further details of the model equations or information can be found in Ting and Yu (1998) and Wang and Ting (1999). Declarations Data availability. Reanalysis Dataset: We utilized the ECMWF Reanalysis v5 (ERA5) and the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2). ERA5 is the fifth generation of ECMWF reanalysis for the global climate and weather for the past 4 to 7 decades, produced using 4D-Var data assimilation in CY41R2 of ECMWF’s Integrated Forecast System (IFS), with 137 hybrid sigma/pressure levels in the vertical, with the top level at 0.01 hPa. MERRA2 is a global atmospheric reanalysis produced by the NASA Global Modeling and Assimilation Office (GMAO). It spans the satellite observing era from 1980 to the present. The goals of MERRA2 are to provide a regularly-gridded, homogeneous record of the global atmosphere, and to incorporate additional aspects of the climate system including trace gas constituents (stratospheric ozone), and improved land surface representation, and cryospheric processes. MERRA2 is also the first satellite-era global reanalysis to assimilate space-based observations of aerosols and represent their interactions with other physical processes in the climate system. In this study, the satellite ozone dataset is also utilized. The OMTO3e dataset is selected, which is a Level-3 Aura/OMI product providing global gridded data of TOMS-like total column ozone. It features a spatial resolution of 0.25° latitude by 0.25° longitude. The OMTO3e product is generated by selecting the highest-quality level-2 total column ozone data (OMTO3) for each grid cell, prioritizing pixels with the shortest path length. Each OMTO3e file includes daily measurements of total column ozone, radiative cloud fraction, and solar and viewing zenith angles, derived from approximately 15 satellite orbits. The above datasets can be downloaded from open URL. ERA5: https://www.metoffice.gov.uk/hadobs/hadisst/data/download.html. MERRA2: https://gmao.gsfc.nasa.gov/reanalysis/MERRA-2/data_access/. OMTO3: https://disc.gsfc.nasa.gov/datasets/OMDOAO3e_003/summary. Code availability. Codes used in the manuscript are available upon reasonable requests from J.-H. Park ( [email protected] ). Acknowledgments. J.-H. Park was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (NRF-2023R1A2C1004083 and RS-2023-00219830, NRF-2023R1A2C1004083). Author Contributions. J.-H. Park started the research with the initial idea and produced the initial results. Competing interests. The authors declare no competing interests. References Slaper H, Velders GJM, Daniel JS, De Gruijl FR, Van der Leun (1996) J. C. Estimates of ozone depletion and skin cancer incidence to examine the Vienna Convention achievements. Nature 384, 256–258 Solomon S (1999) Stratospheric ozone depletion: A review of concepts and history. 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J Clim 23:5349–5374 Li F, Austin J, Wilson J (2008) The strength of the Brewer-Dobson circulation in a changing climate: Coupled chemistry-climate model simulations. J Clim 21:40–57 Garcia RR, Randel WJ (2008) Acceleration of the brewer-dobson circulation due to increases in greenhouse gases. J Atmos Sci 65:2731–2739 Additional Declarations There is NO Competing Interest. Supplementary Files Supplementary20250201.docx SUPPLEMENTARY INFO Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-5942136","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":415425973,"identity":"17227706-85ea-40ab-8427-a05e0541e40f","order_by":0,"name":"Jae-Heung Park","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAz0lEQVRIiWNgGAWjYBACxhkMDAcSDCR4+EG8hALitDAeeFBhISfZANJiQIw1EgzMBx+cqTA2OADiEaOFeXbvgQOJbRKJm8+vTvzwwIBBnl/sAAGHzTmXANay7cbbzRJAhxnOnJ1AQMuMHAOolrMbQFoSDG4Tq2XzjLObfxCvJeGMhLEBf+82Ym3JSziQUCEhJ3GDd5sFMIII+8VwRu7hjz8M6nj4+89uvvmjwkaeX5qQlgYeKEsCrFICv3IQkGeAaeE/QFj1KBgFo2AUjEwAAPU4S/e+JkBQAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0002-8556-2314","institution":"Seoul National University","correspondingAuthor":true,"prefix":"","firstName":"Jae-Heung","middleName":"","lastName":"Park","suffix":""},{"id":415425974,"identity":"8f36667a-99ba-4d4f-9161-0d5e6a920efd","order_by":1,"name":"Ja-ho Koo","email":"","orcid":"","institution":"Yonsei University","correspondingAuthor":false,"prefix":"","firstName":"Ja-ho","middleName":"","lastName":"Koo","suffix":""},{"id":415425975,"identity":"eb147cbc-0c42-4ccc-bce2-04d6e36f5829","order_by":2,"name":"Jong-Seong Kug","email":"","orcid":"","institution":"Seoul National University","correspondingAuthor":false,"prefix":"","firstName":"Jong-Seong","middleName":"","lastName":"Kug","suffix":""},{"id":415425976,"identity":"73b9d030-2aa1-4675-a317-4b7a73523b82","order_by":3,"name":"Su-Jung Lee","email":"","orcid":"","institution":"Hanyang University","correspondingAuthor":false,"prefix":"","firstName":"Su-Jung","middleName":"","lastName":"Lee","suffix":""},{"id":415425977,"identity":"1a40dd5a-96cb-47b0-acc1-28ee5990de80","order_by":4,"name":"Mi-Kyung Sung","email":"","orcid":"https://orcid.org/0000-0002-7659-6571","institution":"Korea Institute of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Mi-Kyung","middleName":"","lastName":"Sung","suffix":""},{"id":415425978,"identity":"01938ae7-47e9-490c-a831-9f2a52575ddd","order_by":5,"name":"Joowan Kim","email":"","orcid":"","institution":"Kongju National University","correspondingAuthor":false,"prefix":"","firstName":"Joowan","middleName":"","lastName":"Kim","suffix":""},{"id":415425979,"identity":"1f2c7f3e-f861-4c05-8b38-9c0e8dbd5651","order_by":6,"name":"Eun-Chul Chang","email":"","orcid":"https://orcid.org/0000-0002-5784-447X","institution":"Kongju National University","correspondingAuthor":false,"prefix":"","firstName":"Eun-Chul","middleName":"","lastName":"Chang","suffix":""},{"id":415425980,"identity":"458cf968-b0be-4cf0-8b4a-58eb38c85bb1","order_by":7,"name":"Young-Min Yang","email":"","orcid":"https://orcid.org/0000-0002-3048-6430","institution":"Nanjing University of information science and technology","correspondingAuthor":false,"prefix":"","firstName":"Young-Min","middleName":"","lastName":"Yang","suffix":""},{"id":415425981,"identity":"5e8338f8-5c95-4fbc-ab3c-6c5b74386923","order_by":8,"name":"Sang Seo Park","email":"","orcid":"","institution":"Ulsan National Institute of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Sang","middleName":"Seo","lastName":"Park","suffix":""},{"id":415425982,"identity":"9edf9880-15b2-428f-bfc2-54a6074d7fec","order_by":9,"name":"Kyung-Hwan Kwak","email":"","orcid":"","institution":"Kangwon National University","correspondingAuthor":false,"prefix":"","firstName":"Kyung-Hwan","middleName":"","lastName":"Kwak","suffix":""},{"id":415425983,"identity":"ae1c9bf6-55e5-4f61-adab-337b54adb29b","order_by":10,"name":"Ji-Hoon Oh","email":"","orcid":"https://orcid.org/0000-0001-8484-8997","institution":"Seoul National University","correspondingAuthor":false,"prefix":"","firstName":"Ji-Hoon","middleName":"","lastName":"Oh","suffix":""},{"id":415425984,"identity":"96bda011-c560-4e25-8165-241f10acb7c8","order_by":11,"name":"Hyung-Jeon Kang","email":"","orcid":"","institution":"Seoul National University","correspondingAuthor":false,"prefix":"","firstName":"Hyung-Jeon","middleName":"","lastName":"Kang","suffix":""},{"id":415425985,"identity":"05f75f1d-548f-4793-b6c6-92c9fd26863e","order_by":12,"name":"Soon-Il An","email":"","orcid":"https://orcid.org/0000-0002-0003-429X","institution":"Yonsei University","correspondingAuthor":false,"prefix":"","firstName":"Soon-Il","middleName":"","lastName":"An","suffix":""}],"badges":[],"createdAt":"2025-02-01 14:05:06","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5942136/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5942136/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":76574031,"identity":"af4a7f94-ea46-4075-9352-e7fc65179e4a","added_by":"auto","created_at":"2025-02-18 14:02:17","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":451742,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eInterdecadal modulation of the relationship between ASO and ENSO.\u003c/strong\u003e (a) 252-month (21-year) running lead-lagged correlation coefficients between the ASO and Niño-3.4 for the period 1980–2023 (y-axis). Negative and positive values on the x-axis indicate leads of ASO and Niño3.4 at monthly timescales, respectively. Hatching indicates values above 0.25 at a 95% confidence level using a two-tailed Student’s t-test (degree of freedom: 60). (b) Lagged correlation between the ASO and Niño-3.4 indices for the period 2002–2023, where the x-axis indicates the number of months by which the ASO index leads the Niño-3.4 index; the y-axis indicates the period of November to the following October. The negative maximum is found at 7 (x-axis) during April (y-axis), indicating that the ASO in April negatively leads ENSO with a lag of 7 months. Hatching indicates the 95% confidence level using a two-tailed Student’s t-test (degree of freedom: 20). (c) Red and black lines indicate the March-April (MA) ASO index and the November-December (ND) Niño-3.4 index from 2002-2023. Herein, the purple line indicates the March-April (MA) Arctic total column ozone (TCO) index, obtained by averaging TCO over 70-90°N from OMI (2005-2023). The correlation coefficient between them is 0.57, significant at the 99% confidence level by student-t-test (degree of freedom: 20).\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-5942136/v1/7d1aad9d3a6d48d70ebeb781.png"},{"id":76574032,"identity":"c739eb97-1692-46fc-b7c8-1e656f2b74fe","added_by":"auto","created_at":"2025-02-18 14:02:17","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":388012,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEvolution of atmospheric circulation and ENSO in terms of the springtime ASO.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e(a) Regressed air temperature (shading, °C, shading bar shown at bottom), ozone concentration (contour, interval: 40 ppb), and wind anomaly (vector, at 850 hPa) at 200hPa in March–April against the springtime (March-April) ASO index for the period 2002–2023. Anomalous air temperature is marked with a 95% confidence level when the Student’s t-test is satisfied. For winds, the areas satisfying 95% and 85% confidence level by the Student’s t-test are marked with black and grey color, respectively. (b), (c), and (d) show similar figures to (a), but in March-April, April-May, May-June, respectively. For the Student’s t-test, the degree of freedom is fixed at 20. (e) Regressed SSTA, air temperature anomaly (shading, °C, shading bar shown at bottom), low-level wind anomaly (vector, at 850 hPa) in March–April against the springtime (March-April) ASO index for the period 2002–2023. Anomalous SST and winds are marked with a 95% confidence level when the Student’s t-test is satisfied (degree of freedom: 20). (f), (g), and (h) show similar figures to the (a), but in April-May, May-June, and November-December, respectively.\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-5942136/v1/9a0da9575baf5b61715f5292.png"},{"id":76574035,"identity":"c50cce71-26ba-44c6-96f7-dd0cabf7dc86","added_by":"auto","created_at":"2025-02-18 14:02:17","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":341851,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eStationary wave model experiments with springtime ASO.\u003c/strong\u003e (a) Horizontal and vertical (inside panel) structure of steady vorticity forcing. (b) Steady response of atmospheric circulation (i.e., stream function) to the vorticity forcing described in (a) under the April-May mean state of atmosphere variables. (c) Geopotential height anomalies at 200hPa in April–May (shading, m) regressed on the ASO index and the relevant wave activity flux (vector) from ERA5.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-5942136/v1/32efb4df8b19dc566ffa95f3.png"},{"id":76576483,"identity":"e5eef836-86be-4b47-8911-8fd3ac2018c3","added_by":"auto","created_at":"2025-02-18 14:18:20","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":766994,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eComparison between SPV variability between 1980-2001 and 2002-2023.\u003c/strong\u003e (a) Geopotential height (contour, m2/s2), temperature (shading, °C), and wind (vectors, m/s) anomalies at 100hPa in February–March regressed onto the zonal wind index (100hPa, February, refer to the manuscript) during 1980-2001. (b) Similar to (a), but in March–April. (c) and (d) are similar to (a) and (b), but during 2002-2023.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-5942136/v1/0d56cf658735729c7c8efd87.png"},{"id":80067564,"identity":"4844d224-dd29-457c-a7ce-0e739748e40e","added_by":"auto","created_at":"2025-04-07 13:33:59","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2517958,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5942136/v1/859a0bd3-42d4-40eb-9e0d-d6ff3c2eb486.pdf"},{"id":76575867,"identity":"e1fdec2c-f737-49ab-a79c-4fb0702d0198","added_by":"auto","created_at":"2025-02-18 14:10:17","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":5192801,"visible":true,"origin":"","legend":"SUPPLEMENTARY INFO","description":"","filename":"Supplementary20250201.docx","url":"https://assets-eu.researchsquare.com/files/rs-5942136/v1/83176337c3bbc3a31a973a05.docx"}],"financialInterests":"There is \u003cb\u003eNO\u003c/b\u003e Competing Interest.","formattedTitle":"Arctic stratospheric ozone as a precursor of ENSO events since 2000s","fulltext":[{"header":"Introduction","content":"\u003cp\u003eStratospheric ozone plays two primary roles in Earth\u0026rsquo;s system. First, it protects both plants and animals by absorbing harmful ultraviolet radiations which are detrimental to their health and survival\u003csup\u003e1\u0026ndash;4\u003c/sup\u003e. Second, by absorbing solar radiations, it regulates large-scale atmospheric circulations\u003csup\u003e5\u0026ndash;8\u003c/sup\u003e, which in turn influences global scale hydrological cycles\u003csup\u003e9\u0026ndash;11\u003c/sup\u003e. That is, the influences of stratospheric ozone extend beyond ecosystems, affecting climate and weather patterns. In this context, the significant depletion of stratospheric ozone\u0026ndash;caused by the use of chlorofluorocarbons (CFCs)\u0026ndash;has been a major concern and the focus of extensive research\u003csup\u003e2,5,12\u0026ndash;18\u003c/sup\u003e since its first detection over the Antarctic in 1985 (i.e., ozone hole, less than 220 Dobson Units)\u003csup\u003e19\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eFor the Arctic, ozone depletion events have been reported since mid-1990s\u003csup\u003e20\u0026ndash;24\u003c/sup\u003e. Particularly, the Arctic stratospheric ozone (ASO) depletion in 2020\u003csup\u003e25\u0026ndash;28\u003c/sup\u003e reached levels comparable to those of the Antarctic ozone hole. However, both the frequency and intensity of ozone depletion over the Arctic are typically lower and more irregular than those over the Antarctic. The difference between the two poles arises from the greater atmospheric variability over the Arctic, in association with Stratospheric Polar Vortex (SPV)\u003csup\u003e29\u003c/sup\u003e and Brewer\u0026ndash;Dobson Circulation (BDC)\u003csup\u003e30\u003c/sup\u003e.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe SPV and BDC are also thermodynamically interconnected\u003csup\u003e31\u003c/sup\u003e, i.e., strong (weak) SPV accompanies weak (strong) BDC. When the SPV strengthens, accompanying extremely cold temperatures (below -80\u0026deg;C), greater chemical ozone depletion occurs due to higher concentrations of active chlorine on the polar stratospheric clouds (PSCs). A strong SPV also limits air mixing into the vortex, and also reduces the ozone transport from the tropics and summer hemisphere to the Arctic via the BDC\u003csup\u003e31\u003c/sup\u003e. In short, ASO is more likely to be depleted when the SPV is strong and the BDC is weak, and vice versa.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIt has been reported that the variability of ASO can influence surface climate and weather patterns, particularly in the spring when solar radiation returns to the Arctic\u003csup\u003e32\u0026ndash;34\u003c/sup\u003e. Studies have shown that depleted springtime ASO has contributed to Arctic Sea ice reduction by increasing both sea ice outflow toward the Atlantic Ocean and surface net heat fluxes\u003csup\u003e35\u003c/sup\u003e. Additionally, extreme ASO depletion modifies atmospheric stability and leads to the formation of high clouds, which increases downward longwave radiation, linking to surface warming over Siberia\u003csup\u003e32\u003c/sup\u003e. ASO variability also affects sea surface temperature (SST) anomalies in the North Pacific via atmospheric teleconnections.\u003csup\u003e36\u003c/sup\u003e Notably, Xie et al. (2016)\u003csup\u003e37\u003c/sup\u003e proposed that a decrease (increase) in springtime ASO leads to El Nino (La Nina) with about a 20-month lag, linked to the North Pacific Oscillation and the Victoria mode (a.k.a., North Pacific Gyre Oscillation) based on the analysis of reanalysis dataset from 1986 to 2015.\u003c/p\u003e\n\u003cp\u003eMeanwhile, significant changes in the characteristics of the SPV have been observed since the 2000s\u003csup\u003e38,39\u003c/sup\u003e, coinciding with Arctic climate changes\u003csup\u003e40\u0026ndash;42\u003c/sup\u003e. The SPV has weakened due to factors such as the Arctic sea ice loss\u003csup\u003e43\u0026ndash;45\u003c/sup\u003e and increased snow cover\u003csup\u003e46,47\u003c/sup\u003e, and it now tends to exhibit a more asymmetrical structure\u003csup\u003e45,48\u003c/sup\u003e. This altered feature of SPV is expected to impact the spatiotemporal distribution of ASO\u003csup\u003e45,46,49\u003c/sup\u003e. Consequently, the modified ASO may trigger weather and climate phenomena that differ from those observed in earlier periods\u003csup\u003e34\u003c/sup\u003e. However, research on this topic remains limited and requires further investigation.\u003c/p\u003e\n\u003cp\u003eAs noted earlier, a previous study showed that ASO was negatively correlated with ENSO through pathways in the North Pacific during 1986-2015, with a lag of approximately 20 months\u003csup\u003e37\u003c/sup\u003e. Based on the previous findings, this study revisits the mechanism through which ASO has affected the tropical Pacific since the 2000s, aligned with recent SPV changes. We analyzed two observational reanalysis datasets (ECMWF Reanalysis Version 5 (ERA5) for the main figures and Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA2) for the supplementary figures) as well as Ozone Monitoring Instrument (OMI). The consistent results across datasets suggest that springtime ASO has the potential to be a precursor of ENSO events in the following winter with a lag of 8 months through atmospheric teleconnections across the Eurasian continent. We discuss the implications of these findings for how the stratosphere influences troposphere and contributes to the development of ENSO events in recent decades.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec2\" class=\"Section2\"\u003e \u003ch2\u003eA new connection between spring ASO and the following winter ENSO since 2000\u003c/h2\u003e \u003cp\u003eTo explore the decadal modulation of the ASO\u0026ndash;ENSO relationship from 1980 to 2023, we conducted a 252-month running lead-lag correlation analysis between ASO and ENSO indices on a monthly timescale. Herein, the monthly ASO index is obtained by averaging monthly ozone concentration over 70\u0026ndash;90\u0026deg;N at 100\u0026ndash;200hPa, while the monthly Nino3.4 index (c.f., Nino3.4 region: 120\u0026ndash;170\u0026deg;W, 5\u0026deg;S-5\u0026deg;N) is adopted as the monthly ENSO index. To focus on variability, we removed climatological mean and trends from both the monthly ASO and ENSO indices within each 252-month running window, although this detrending had minimal effect on our result because their trends are small.\u003c/p\u003e \u003cp\u003eThe results of the lead-lag correlation analysis are illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea (refer to Supplementary Fig.\u0026nbsp;1 for MERRA2), where negative values on x-axis indicate how many months ASO leads ENSO, and positive values indicate how many months ENSO leads ASO. Overall, the ENSO-leading-ASO signals are not significant and remain mostly positive throughout the period. In contrast, the ASO-leading-ENSO signals undergo a pronounced change around the early 2000s. Before this period, ASO negatively led ENSO with approximately a 20-month lag, with the strongest signals observed in the mid-to-late 1990s. Here, the negative correlation indicates that a stratospheric condition with increased ozone concentrations tends to lead to La Nina 20 months later. This finding aligns with the previous study by Xie et al. (2016)\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. However, these negative ASO-leading-ENSO signals gradually weakened over time, while positive ASO-leading-ENSO signals with an 8-month lag emerged after the early 2000s.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe result from Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea reveals the emergence of an unprecedent ASO\u0026ndash;ENSO relationship since the early 2000s, which indicates that increased ozone concentrations lead to El Nino during the current decades. Building on this, we further examined their lead-lagged correlation, focusing on the recent period from 2002 to 2023 (the second half of the total period from 1980 to 2023). Similar to Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea, the x-axis in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb indicates how many months ASO leads the ENSO indices, while the y-axis indicates the calendar months from November (bottom) to October (top). It shows that ASO-leading-ENSO signals are significant when ASO from March to April leads ENSO by 2 to 10 months. The highest correlation coefficient is 0.63 when ASO in April leads ENSO in the following November. These results suggest that springtime ASO tends to lead ENSO in the following winter season since the early 2000s.\u003c/p\u003e \u003cp\u003eBased on Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eb, we defined a March\u0026ndash;April (MA) ASO index and a November\u0026ndash;December (ND) ENSO index by averaging the monthly ASO and ENSO indices for March to April and November to December, respectively. Figure\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec shows both the MA-ASO and ND-ENSO indices. Their correlation coefficient is 0.57, which is statistically significant at the 99% confidence level.\u003c/p\u003e \u003cp\u003eIn addition to the reanalysis datasets, we utilized satellite data, OMI/Aura Ozone (OMTO3, Method). Although OMTO3 provides total column ozone (TCO), instead of three-dimensional ozone, and its temporal coverage is relatively short, spanning from 2005 to 2023, TCO serves as a suitable proxy for stratospheric ozone due to the highest ozone concentrations occurring in the stratosphere. Following a method applied to the ASO index, we obtained an Arctic TCO index by averaging TCO over 70\u0026ndash;90\u0026deg;N during March-April, wherein climatological mean and trends are removed (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ec). We found that the correlation coefficient between MA-Arctic-TCO and MA-ASO indices is 0.79 (0.80 for MERRA2, Supplementary Fig.\u0026nbsp;1), statistically significant at the 99% confidence level. Also, the correlation coefficient between MA-Arctic TCO and ND-ENSO indices is 0.52 (0.52 for MERRA2, Supplementary Fig.\u0026nbsp;1), statistically significant at the 95% confidence level. These findings align with results from the reanalysis dataset, supporting the reliability of observational reanalysis data since the 2000s.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eHow springtime ASO affects subsequent wintertime ENSO?\u003c/h2\u003e \u003cp\u003eWe aim to investigate how the springtime ASO is linked to the subsequent wintertime ENSO events since the early 2000s. To do this, we regressed ozone concentration, air temperature, and wind anomalies at 200hPa from February\u0026ndash;March (FM) to May\u0026ndash;June (MJ) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea-d) and wind anomalies at 850hPa and SST anomalies from March\u0026ndash;April (MA) to November\u0026ndash;December (ND) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ee-h) regressed onto the MA\u0026ndash;ASO index (Supplementary Fig.\u0026nbsp;2\u0026ndash;3 for MERRA2). We note that the results below remain largely unchanged even when simultaneous ENSO signals are removed from ASO index (Supplementary Fig.\u0026nbsp;4), indicating that our findings are not influenced by the ENSO autocorrelation effect.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn February\u0026ndash;March (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea), ozone concentration is significantly elevated across the Arctic, accompanied by large-scale anomalous warming over the Arctic and circumpolar easterly wind anomalies. These results are in line with weakened SPV and strengthened BDC, as the weakened SPV favors reduced chemical ozone depletion and the strengthened BDC enables more ozone intrusion from the tropics to the Arctic. Simultaneously, the downward motion associated with the strengthened BDC causes adiabatic warming over the Arctic.\u003c/p\u003e \u003cp\u003eAs SPV becomes weakened and contracts from winter to spring, significant easterly wind anomalies are only observed over the high-latitudes of Eurasia in March\u0026ndash;April (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb). Simultaneously, the localized warming over the high latitudes of the Eurasian continent occurs under weakened downward motion of the BDC during the transition from winter to spring. For ozone, its concentrations remain elevated across the Arctic. However, they become increasingly concentrated over the Eurasian continent, coinciding with a warming pattern. It is inferred that the absorption of solar radiation by the elevated ozone concentrations intensifies this localized warming, as sunlight returns to the Arctic in spring following the polar night. At this moment, cyclonic circulation of the southern area of the easterly wind anomalies and warming begins to form.\u003c/p\u003e \u003cp\u003eIn April\u0026ndash;May (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec), the tropospheric upper-level cyclonic circulation anomaly over Siberia develops further with anomalous stratospheric warming and enhanced ozone concentrations. This localized warming is also pronounced at higher altitudes (e.g., 50hPa), and disappears at lower altitudes (e.g., 300hPa), indicating thermal expansion centered over the stratosphere. It is known that negative (positive) geopotential height anomalies are located over the bottom (upper) part of the thermal expansion. In this regard, anomalous cyclonic circulation could be located at the bottom area of the thermal expansion. Thus, the upper-tropospheric cyclonic circulation anomaly emerges over Siberia in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb.\u003c/p\u003e \u003cp\u003eNotably, this cyclonic circulation anomaly generates atmospheric waves that propagate southeastward, creating a sequence of anticyclonic, cyclonic, and anticyclonic circulations over East Asia, the western North Pacific, and the subtropical North Pacific, respectively. In other words, the atmospheric wave propagation extends from Siberia to the tropical Pacific. As a result, easterly wind anomalies develop along the western to central equatorial Pacific, persisting into May\u0026ndash;June (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed). These upper-level easterly wind anomalies are expected to be connected to the lower-level westerly wind anomalies, reflecting the baroclinic vertical structure over the equatorial Pacific\u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e,\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e, which helps to initiate the development of El Nino.\u003c/p\u003e \u003cp\u003eMeanwhile, Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ee-h illustrates SST and low-level wind anomalies at 850hPa from MA to ND seasons, in association with the MA-ASO index. In March\u0026ndash;April (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ee), easterly and northeasterly wind anomalies are observed over the high latitudes of Eurasia and western Siberia. Regarding these wind anomalies, an anomalous cyclonic circulation over Siberia is observed in April\u0026ndash;May (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ef). This circulation appears to be connected to the anticyclonic circulation over the Korea\u0026ndash;Japan region and a cyclonic circulation over the tropical western North Pacific, forming a wave-like pattern. These findings suggest a tropospheric pathway linking the high latitudes of Eurasia to the tropical Pacific, with a vertical connection driven by upper-level circulations.\u003c/p\u003e \u003cp\u003eOver the tropical Pacific, westerly wind anomalies begin to develop over the western tropical Pacific from March\u0026ndash;April to May\u0026ndash;June (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ee-g), in association with upper-level easterly wind anomalies. These low-level westerly wind anomalies initiate anomalous SST warming along the equatorial Pacific through the Bjerknes feedback, likely driving the development of an El Nino from spring to winter (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eh).\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eThe role of ASO-relevant forcing in modulating atmospheric circulations\u003c/h3\u003e\n\u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e demonstrates that a stratospheric warming over Siberia associated with the ASO in spring accompanies an upper-tropospheric cyclonic circulation anomaly, which becomes a source of atmospheric waves propagating toward the tropical Pacific\u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e,\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e. To examine how the upper-level cyclonic circulation over Siberia generates atmospheric waves that propagate toward the tropical Pacific, we utilized the Stationary Wave Model (SWM)\u0026mdash;a simplified atmospheric general circulation model (details provided in the Methods). For this experiment, the climatological mean state of the atmosphere during spring 2002\u0026ndash;2023 was used as the background atmospheric condition. Then, vorticity forcing over Siberia, resembling the upper-level cyclonic circulation in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec, was applied to assess its effect on stationary atmospheric circulation.\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea illustrates the horizontal and vertical structure of atmospheric vorticity forcing, with a maximum at the 0.17 sigma level. The corresponding anomalous stationary atmospheric response at the same level is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb. Notably, this atmospheric response remains consistent even with slight adjustments to the horizontal or vertical location of the vorticity forcing. In Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb, the response shows a series of cyclonic and anticyclonic flows over Siberia, the western North Pacific, the subtropical western North Pacific, and the tropical Pacific, under the background atmospheric state of April\u0026ndash;May. This identical wave propagation pattern is also obtained under background atmospheric state of March\u0026ndash;April (Supplementary Fig.\u0026nbsp;5). This stationary wave pattern closely resembles the atmospheric waves regressed onto the MA-ASO index (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec). Thus, the results from the SWM suggest that vorticity forcing induced by ASO can generate atmospheric waves propagating toward the tropical Pacific, influencing the development of ENSO.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eTo diagnose the direction of wave propagation associated with upper-level cyclonic circulation over Siberia during spring, we analyzed the wave activity flux (WAF)\u003csup\u003e\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e at 200hPa for April\u0026ndash;May (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ec and Supplementary Fig.\u0026nbsp;5 for March\u0026ndash;April) under conditions of enhanced springtime ASO (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec) from ERA5. The results reveal that the WAF propagates from Siberia through East Asia to the western North Pacific. These findings, derived from the SWM experiment and WAF analysis, underscore the role of springtime ASO in modulating upper-level atmospheric circulation through atmospheric heating.\u003c/p\u003e\n\u003ch3\u003eThe role of SPV changes in the ASO–ENSO relationship\u003c/h3\u003e\n\u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003ea shows that the lagged ASO\u0026ndash;ENSO relationship has changed since the early 2000s. This change coincides with the notable changes in the Arctic such as a significant decline in sea ice (c.f., polar amplification). Given these changes, it is essential to investigate how the climatological mean state changes have influenced the ASO\u0026ndash;ENSO relationships. Previous studies have shown that the SPV weakened after the 2000s, coinciding with an increase in Eurasian snow cover and enhanced vertically propagation of planetary waves\u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e,\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e. Additionally, the shape of SPV transitioned from a symmetric, circular structure to more asymmetric forms, such as a tilt toward Eurasia or a split, \"peanut-shaped\" pattern, which has become more frequent.\u003c/p\u003e \u003cp\u003eTo investigate SPV changes after the 2000s, we analyzed 21 years of data from two periods: the first half period (1980\u0026ndash;2001) and the second half period (2002\u0026ndash;2023). Figure\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e shows the zonal wind, geopotential height, and temperature at 100hPa for February\u0026ndash;March and March\u0026ndash;April, regressed onto the zonal wind index, which is obtained by averaging the zonal wind at 100hPa over the 60\u0026ndash;90\u0026deg;N in February (Supplementary Fig.\u0026nbsp;6 for MERRA2). During 1980\u0026ndash;2001, the SPV maintained its strength well in February\u0026ndash;March and it remained relatively symmetric although it slightly weakened in March\u0026ndash;April. In contrast, during 2002\u0026ndash;2023, the SPV retained a symmetric structure in February\u0026ndash;March, but became more asymmetric in March\u0026ndash;April, with increased variability toward both Eurasia and North America. The tilt toward the Eurasian continent became more pronounced\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e,\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e, providing a favorable condition for pronounced ozone variability over this region compared to other region, (Supplementary Fig.\u0026nbsp;7), which, in turn, is expected to induce change in weather and climate\u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eIn summary, the changes in SPV characteristics after the 2000s provide a favorable condition for increased ozone variability over Eurasia in spring, which contributes to the generation of atmospheric waves toward the tropical Pacific and thus the emergence of the ASO\u0026ndash;ENSO correlation observed in recent decades.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eA previous study by Xie et al. (2016)\u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e, which analyzed observational reanalysis data from 1986 to 2015, identified a negative relationship between springtime ASO variations and the occurrence of ENSO events approximately 20 months later through a North Pacific pathway. Building on this, we revisited the ASO-ENSO relationship during the period from 1980 to 2023, a time of significant Arctic climate change. Our findings reveal a shift to a positive ASO\u0026ndash;ENSO relationship during 2002\u0026ndash;2023, where increases or decreases in ASO now lead to the development of El Ni\u0026ntilde;o or La Ni\u0026ntilde;a with an 8-month lag via a Eurasia pathway. We mainly attribute this different ASO\u0026ndash;ENSO relationship between the two periods to the modified horizontal distribution of ASO, subjected to the SPV characteristics. Therefore, examination of both SPV characteristics and horizontal distribution of ASO would be beneficial to understand how the stratosphere affects tropospheric atmospheric circulations.\u003c/p\u003e \u003cp\u003eChemistry climate models projected that BDC will increase under global warming period\u003csup\u003e\u003cspan additionalcitationids=\"CR56\" citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u003c/sup\u003e, in which weak and asymmetric structure of the SPV is expected. As long as the recent ASO\u0026ndash;ENSO correlation seems to be connected to the weakening and asymmetric structure of the SPV and strengthened BDC, their relationship is expected to remain significant in future climates. Nonetheless, to gain deeper insight, it will be essential to compare historical data with global warming scenarios from various climate models, while considering the underlying chemical, radiative, and dynamic processes. This approach will be critical for understanding future climate variability and change.\u003c/p\u003e"},{"header":"Method","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eStationary Wave Model (SWM)\u003c/h2\u003e \u003cp\u003eThe SWM is a nonlinear baroclinic model with a dry dynamical core and 14 vertical levels on sigma coordinates. Its horizontal resolution is truncated at rhomboidal 30. This model was devised to understand how the atmospheric stationary waves propagate given atmospheric perturbations. To perform SWM experiments, the (mostly monthly or seasonal) background atmospheric state is first fixed. Then, under the fixed background state, steady atmospheric vorticity or heating forcings are prescribed until stationary atmospheric waves are obtained (mostly 30 to 60 days). The response to the forcing shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e is averaged for 55 days, since the steady forcing is exerted. Further details of the model equations or information can be found in Ting and Yu (1998) and Wang and Ting (1999).\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData availability.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eReanalysis Dataset: We utilized the ECMWF Reanalysis v5 (ERA5) and the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2). ERA5 is the fifth generation of ECMWF reanalysis for the global climate and weather for the past 4 to 7 decades, produced using 4D-Var data assimilation in CY41R2 of ECMWF\u0026rsquo;s Integrated Forecast System (IFS), with 137 hybrid sigma/pressure levels in the vertical, with the top level at 0.01 hPa.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMERRA2 is a global atmospheric reanalysis produced by the NASA Global Modeling and Assimilation Office (GMAO). It spans the satellite observing era from 1980 to the present. The goals of MERRA2 are to provide a regularly-gridded, homogeneous record of the global atmosphere, and to incorporate additional aspects of the climate system including trace gas constituents (stratospheric ozone), and improved land surface representation, and cryospheric processes. MERRA2 is also the first satellite-era global reanalysis to assimilate space-based observations of aerosols and represent their interactions with other physical processes in the climate system.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn this study, the satellite ozone dataset is also utilized. The OMTO3e dataset is selected, which is a Level-3 Aura/OMI product providing global gridded data of TOMS-like total column ozone. It features a spatial resolution of 0.25\u0026deg; latitude by 0.25\u0026deg; longitude. The OMTO3e product is generated by selecting the highest-quality level-2 total column ozone data (OMTO3) for each grid cell, prioritizing pixels with the shortest path length. Each OMTO3e file includes daily measurements of total column ozone, radiative cloud fraction, and solar and viewing zenith angles, derived from approximately 15 satellite orbits.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe above datasets can be downloaded from open URL. ERA5: https://www.metoffice.gov.uk/hadobs/hadisst/data/download.html. MERRA2: https://gmao.gsfc.nasa.gov/reanalysis/MERRA-2/data_access/. OMTO3: https://disc.gsfc.nasa.gov/datasets/OMDOAO3e_003/summary.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCode availability.\u003c/strong\u003e Codes used in the manuscript are available upon reasonable requests from J.-H. Park ([email protected]).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments.\u003c/strong\u003e J.-H. Park was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (NRF-2023R1A2C1004083 and RS-2023-00219830, NRF-2023R1A2C1004083).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions.\u003c/strong\u003e J.-H. Park started the research with the initial idea and produced the initial results.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests.\u003c/strong\u003e The authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSlaper H, Velders GJM, Daniel JS, De Gruijl FR, Van der Leun (1996) J. C. Estimates of ozone depletion and skin cancer incidence to examine the Vienna Convention achievements. \u003cem\u003eNature\u003c/em\u003e 384, 256\u0026ndash;258\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSolomon S (1999) Stratospheric ozone depletion: A review of concepts and history. Rev Geophys 37:275\u0026ndash;316\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKerr JB, McElroy CT (1993) Evidence for Large Upward Trends of Ultraviolet-B Radiation Linked to Ozone Depletion. 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J Atmos Sci 65:2731\u0026ndash;2739\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-5942136/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5942136/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eRecent depletion of the Arctic Stratospheric Ozone (ASO) has raised significant concerns about its impact on surface climate and weather. By analyzing observational reanalysis dataset and the Ozone Monitoring Instrument, here we found that the relevant variations in springtime ASO can be a potential precursor of El Niño–Southern Oscillation in the subsequent winter since 2000s. During this period, springtime ASO variability become pronounced, particularly over the Eurasian continent, due to the asymmetrical structure of the Arctic stratospheric polar vortex. With the return of solar radiation to the Arctic in spring, increased ASO leads to more absorption of solar radiation over Eurasia, contributing to localized anomalous heating. This stratospheric heating induces upper-tropospheric cyclonic circulation over Siberia, resulting in the propagation of atmospheric stationary waves toward the tropical Pacific. As a result, upper-level easterly and low-level westerly wind anomalies emerge over the equatorial Pacific. This baroclinic atmospheric anomaly over the equatorial Pacific promotes El Niño development by modulating the Walker circulation (c.f., La Niña for the opposite case). These results highlight the critical role of chemical-radiative-dynamical processes in the Arctic stratosphere for understanding surface climate phenomena.\u003c/p\u003e","manuscriptTitle":"Arctic stratospheric ozone as a precursor of ENSO events since 2000s","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-02-18 14:02:12","doi":"10.21203/rs.3.rs-5942136/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"46e25942-cab8-4eb4-b447-a856424c7775","owner":[],"postedDate":"February 18th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":44299852,"name":"Earth and environmental sciences/Climate sciences/Atmospheric science"},{"id":44299853,"name":"Earth and environmental sciences/Climate sciences/Ocean sciences"}],"tags":[],"updatedAt":"2025-04-07T13:25:52+00:00","versionOfRecord":[],"versionCreatedAt":"2025-02-18 14:02:12","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5942136","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5942136","identity":"rs-5942136","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}