Stratospheric biomass burning aerosols compensate record-breaking ozone depletion over the Arctic in spring 2020

Domain: chemistry
Published: 2026-02-17
Editorial outcome: major_revision

Abstract
Biomass burning aerosols reaching the stratosphere (SBBA) present an emerging yet understudied threat to Arctic ozone (O3). Previous work focuses primarily on SBBA-induced heterogeneous chemistry, while their dynamical effects – altering temperature and circulation – have received less attention. Here, we assess both the chemical and dynamical impacts of SBBA over the Arctic during 2019–2020, a period marked by unusually high SBBA loading and O3 depletion. With satellite-constrained modelling, we show that SBBA cause a net increase in Arctic O3, compensating for 19% of the observed depletion in spring 2020. Dynamical processes dominate this effect via stratospheric heating and enhanced poleward O3 transport. We link this SBBA event to a confluence of northward fire activities and an anomalous polar cyclonic system. Given projected increases in boreal fires and their northward extension, our findings highlight the critical need to integrate both chemical and dynamical SBBA effects to accurately assess O3 budget and its consequences in a changing climate.

Introduction
Stratospheric ozone (O3) plays a critical role in Earth’s climate and ecosystems1,2, yet faces an emerging threat from the intensification of large-scale wildfires3. Studies have shown that biomass burning aerosols (BBA) in the stratosphere (stratospheric BBA, or SBBA) can deplete O3 by enhancing chlorine activation4 and heterogeneous reactions3,5. A striking example is the 2019/2020 Australian bushfire, which has led to widespread perturbations in O3 concentration across the Southern Hemisphere6,7. The impact of BBA on O3 is of particular concern in polar regions, where O3 variability not only has local impacts but also contributes to broader hemispheric climate feedbacks8.

Despite recent progress, the effects of SBBA on Arctic O3 remain poorly understood. While existing studies mostly consider the stratospheric aerosols as of volcanic origin, Ohneiser et al. (2021)9 first reported the presence of SBBA in the Arctic. Subsequent studies have demonstrated that SBBA often coincides with O3 depletion episodes driven by enhanced heterogeneous chemistry9,10, which is in line with modelling work extensively done for the Antarctic3,5,6. However, BBA also serves as an effective climate forcer in the Arctic, posing sizable impacts on radiation budget11, temperature12, cloudiness13, and sea ice coverage14. Temperature changes induced by SBBA are particularly relevant for O3, as Arctic O3 depletion is strongly linked to the persistence of cold temperatures under a stable polar vortex15, which triggers a record-high O3 depletion in spring 202016. Additionally, as Arctic O3 is strongly affected by the poleward transport of O3-rich air from lower latitudes via Brewer–Dobson circulation (BDC)17, any SBBA-driven thermal anomalies might further modulate Arctic O3 levels by modifying the circulation pattern. The magnitude of SBBA-driven dynamical climate feedbacks on O3 and how they compare with heterogeneous chemistry remain key barriers to understanding the role of SBBA. Addressing such gaps is essential, especially given projections of increasing wildfire frequencies and aerosol emissions in boreal regions11,18, which could render the Arctic increasingly vulnerable in terms of O3 stability.

Here, with satellite-constrained simulations based on CESM2 (the Community Earth System Model 2)19, we quantify and compare how Arctic O3 responds to the SBBA from chemical and dynamical perspectives. Our analysis focuses on the years 2019 and 2020, when a record-high SBBA loading and O3 depletion are observed. The presence and impacts of SBBA in this period are further linked with climate anomalies, providing insights into a specific feedback mechanism that affects Arctic O3 variability via BBA in a warming climate.

Results
According to CALIOP (the Cloud-Aerosol Lidar with Orthogonal Polarisation) observations, the stratospheric aerosol optical depth (SAOD) over the Arctic (> 60°N) reaches a peak anomaly of 0.033 during the autumn of 2019 (August–October, Fig. 1a), making the total SAOD more than double relative to the multi-year average (0.026, Fig. S1a). Positive anomalies in SAOD are widespread across much of the high-latitude Northern Hemisphere, with the majority of these aerosols confined to the lower stratosphere (below the 100 hPa height, Fig. 1c). Similar anomalies in stratospheric aerosols are also found in 2008 and 2009, which have been attributed to volcanic eruptions20,21. Although a volcanic eruption also occurs at middle latitudes (Raikoke, 48.29°N, 153.25°E) in summer 201922, field measurements suggest its contribution to Arctic stratospheric aerosol burden is comparatively minor, about an order of magnitude weaker than the signal associated with biomass burning9,10. Multiple lines of evidence from satellite observations further support the dominance of SBBA in the 2019 stratospheric aerosol enhancement. Firstly, the Angstrom Exponent (AE)–a parameter describing the spectral dependence of aerosol extinction on wavelength23–retrieved over the Arctic during summer 2019 for altitudes between 10–16 km is lower than both the multi-year average (Fig. S2) and values for years with abundant volcanic aerosols (Fig. S3), which agrees with previous studies showing lower AE values when fire smoke dominates over volcanic aerosols9. Secondly, measurements from MLS (the Microwave Limb Sounder) do not show SO2 or sulphate enhancements in 2019 comparable to those observed in 2008 and 2009 (Figs. S4 and S5), in line with our model sensitivity simulations, which suggest that volcanic emissions are not a major contributor in the 2019 episode (Methods). This is consistent with existing studies demonstrating that the emission from Raikoke eruption is insufficient to explain the large aerosol optical depth at upper troposphere and lower stratosphere (UTLS) in 20199,24. Third, the observed warming at the lower stratosphere during summer 2019 indicates the presence of solar-absorbing aerosols such as brown carbon and black carbon (Fig. S6), which is unlikely to be associated with the sulphate heating due to infrared radiation absorption25 given the low concentration (Fig. S5). The evidence clearly demonstrates the dominance of BBA rather than volcanic aerosols in the Arctic stratosphere.

Following the consistently high SBBA observations in 2019, a record-high O3 depletion in spring 2020 (February–April) is observed during the past four decades (Fig. 1b). The maximum depletion reaches 78 DU (Dobson units) in March, with 37% of the Arctic areas experiencing a O3 loss exceeding 100 DU. The depletion is most pronounced in the mid-to-upper stratosphere according to OMPS (Ozone Mapping and Profiler Suite) observations, with reductions in O3 of up to 27% at 50 hPa height (Fig. 1d). We identify a significant positive correlation between total column ozone (TCO) and stratospheric temperature at 50 hPa, with 2020 exhibiting the lowest stratospheric temperature on record for the past two decades (with an anomaly of −6°C, Fig. S7). This anomalously low temperature favours the formation of polar stratospheric clouds (PSC) by threefold compared to a climatology26 (Fig. S8), and triggers several conditions conducive to heterogeneous chemical reactions, including the chlorine activation via conversion of HCl to ClO (Fig. S9b, S9c) and condensation of HNO3 into nitric acid trihydrate (NAT, Fig. S9d), both of which facilitate catalytic O3 destruction15,16.

While existing studies have primarily attributed the record-breaking Arctic O3 depletion to dynamical drivers, including weakened wave activities and a suppressed BDC15,27,28, few have considered the potential impacts of SBBA. Given the sensitivity of O3 concentration to temperature and the capacity of BBA to perturb both radiative budget and chemical processes, we hypothesise that the 2019 SBBA event plays a role in the observed Arctic O3 depletion in 2020.

We employ the CESM2 driven by GFED (Global Fire Emission Database 4s)29 to investigate the impacts of anomalous SBBA on the O3 concentration for the 2019–2020 period. To better represent the vertical distribution of SBBA, the fire injection profiles are modified to match satellite observations from CALIOP (see Methods). With this observationally constrained model, we conduct three sets of simulations: two climatological runs from 2000 to 2023 with (CLIM) and without (NOBB) fire emissions, and a 20-member ensemble run (FIRE19) focusing on the specific influence of 2019 fire injections. Paired simulations are conducted for all the three experiments with either the default or updated stratospheric chemistry schemes to fully account for the dynamical and chemical impacts of SBBA (see Methods). By comparing CLIM and FIRE19, we show that the 2019 SBBA overall lead to an Arctic TCO increase by 11.5 DU (−2.8–25.5 DU as interquartile range) during spring 2020. Relative to the 2000-2023 average level, such an increase offsets 19% of the observed O3 depletion (59 DU).

To disentangle the underlying mechanisms, we separate the SBBA effects on O3 into chemical (by enhancing heterogeneous reactions and the resulting consequences) and dynamical (by altering temperature and circulation) components by applying varying stratospheric chemistry schemes (see Methods). Our simulations show that SBBA-induced heterogeneous chemistry leads to a TCO reduction of 6.1 DU (10% of the observed depletion) during spring 2020. However, this effect is overwhelmed by a dynamically driven O3 increase of 17.6 DU (4.4–31.7 DU), resulting in a net positive anomaly (Fig. S10). Vertical profiles demonstrate that the compensation between the two effects occurs primarily above 100 hPa height, below which the dynamical impacts dominate (Fig. 2b). Strong chemical impacts are found between 10 and 100 hPa level, yielding an average O3 depletion of 0.09 ppmv. However, the accompanying dynamical impacts produce an O3 increase that is roughly 50% larger (0.14 ppmv). Consequently, O3 concentrations rise by a net 0.05 ppmv at this altitude range, contributing substantially to the positive Arctic TCO anomaly. These results suggest that, in the absence of the 2019 SBBA event–particularly the dynamical impacts–Arctic O3 depletion would have been more severe. While the typical threshold for an O3 hole is defined by a TCO below 220 DU30, such values have not been observed in the Arctic on a monthly basis in OMPS dataset. However, our results suggest that without the 2019 SBBA, this threshold would have been exceeded over an area of approximately 1.8 × 104 km2 in March 2020 (Fig. S11).

Our further analysis reveals that the impacts of SBBA on O3 arise primarily through their perturbations to local temperature and large-scale circulation. By comparing FIRE19 and CLIM simulations with varied chemistry schemes (Methods), we decompose the SBBA-induced effects into three temporal stages based on the distinct temporal evolution of SBBA, O3, and climate dynamics. In Stage-1 (July–October 2019) immediately after the SBBA injection, a dense aerosol layer forms below 100 hPa height as also observed by CALIOP (Fig. 1c), resulting in a strong thermal dipole with heating within and weak cooling above the layer (Fig. 3d). Such a dipole structure is induced by the solar absorption of BBA, which cannot be formed in the case of volcanic aerosols as widely studied in previous studies. This initial heating within the aerosol layer increases O3 by disrupting ice cloud content (Fig. S12) and suppressing chlorine/bromine activation (Fig. S13). MLS and ERA5 data record a similar heating pattern (Fig. S14), which becomes obscured after September, possibly masked by the further changes associated with the rapid polar vortex development31,32 (Fig. S15). Simultaneously, this thermal structure facilitates upwelling above 200 hPa height (i.e., negative anomalies in residual vertical velocity, Fig. S16) and dilutes O3-rich air in the middle stratosphere (Fig. 3b1), which is corroborated by OMPS and ERA5 data (Fig. S17). While in Stage-2 (November 2019–January 2020) which marks the onset of the polar vortex (Fig. S18), the lower-stratospheric warming persists, promoting upward wave penetration and leading to an EP (Eliassen-Palm) flux convergence at upper stratosphere (Fig. S19). This is accompanied by an enhanced poleward O3 transport via enhanced BDC, as indicated by the tightened residual meridional velocity (Fig. S20). However, this effect is largely overridden by a dominant chemical-radiative feedback loop. The initial chemical O3 depletion caused by SBBA cools the lower stratosphere (Fig. S21), enhancing vertical stability, suppressing wave penetration, and ultimately weakening the BDC (Fig. S19). This reduced poleward transport synergises with direct chemical depletion by SBBA, leading to a substantial decline in Arctic TCO (13.1 DU) during this period. Stage-3 (February–April 2020) sees the dynamical effects re-intensify and become dominant as the background BDC strengthens seasonally. The SBBA-induced strengthening of the BDC enhances poleward O3 transport and downwelling over the Arctic (Figs. S16, S20), which warms the stratosphere, weakens the polar vortex (Fig. 3e4), and suppresses PSC formation (Fig. S22), driving a net increase in O3 concentration (Fig. 3a4). Overall, our results highlight that the impacts of SBBA on Arctic O3 during 2019–2020 are governed more by dynamic feedbacks—particularly via local heating and circulation modulation—than by chemical pathways.

Given that the anomalous climate conditions of spring 2020, characterized by the exceptionally low temperatures and strong polar vortex15,27,28, can influence O3 evolution, we additionally perform a hybrid simulation integrating free-running and nudged configurations (see Methods). This framework more accurately reproduces the observed temperature anomalies and O3 depletion for the focused period (Figs. S23–S24). Importantly, the estimated dynamical and chemical impacts of SBBA derived from this hybrid approach are consistent with those from the free-running simulations discussed above (Fig. S25), which demonstrates that our findings are robust and largely independent of the background climate state. In addition, our results highlight the warming induced by SBBA, which is validated against MLS and ERA5 data. Although aerosol modelling is constrained by CALIOP observations, our modelled warming shows notable overestimation (Fig. S26b, c). To evaluate the potential impacts of such bias, we conduct a sensitivity test by reducing BBA emissions to align the modelled temperature response with observations, which suggests an optimal scaling factor of 0.5 (Methods). A 10-member ensemble using half GFED emissions further indicates a net TCO increase of 5.7 DU (with an interquartile range of −8.7–19.5 DU) during spring 2020 (Fig. S26a). This falls well within the uncertainty range of the default GFED-driven simulations, further demonstrating the robustness of our conclusions.

Possible drivers for the 2019 SBBA episode
Given the impacts of SBBA on Arctic O3, we further investigate the drivers behind the exceptional stratospheric injection of BBA in summer 2019. Field measurements indicate that the SBBA in the Arctic primarily originate from Siberia9,10, consistent with global emission inventories identifying Siberia as the dominant source of boreal BBA emissions in 2019 (Fig. S27). While intense biomass burning can inject smoke into the UTLS via pyrocumulonimbus activity33 and self-lifting with sufficient black carbon content9, the intensity of fires alone cannot explain the anomalous 2019 event. In fact, BBA emissions from Siberia are similar in 2020 and even higher in 2021 (by 20–90% across multiple inventories) compared with 2019, yet no substantial stratospheric aerosol signal is detected over the Arctic for these years (Fig. 4b). This discrepancy points to additional factors shaping SBBA distributions.

Our analysis reveals that the 2019 fire season is characterized by a unique combination of northward fire occurrence and anomalous atmospheric circulation at UTLS. As shown in Fig. 4a, b and Fig. S28, satellite observations demonstrate elevated stratospheric aerosol loading during all three selected intense fire years (2019–2021), yet only in 2019 do the aerosols reach the Arctic stratosphere efficiently. In contrast, stratospheric aerosols in 2020 and 2021 remain largely confined to the mid-latitude Westerlies (40–60°N). Such a discrepancy becomes most apparent in July, when the frequency and intensity of Siberian fires peak (Fig. S29). It has been well documented that plumes from intense fire activities can reach the UTLS level by self-lifting, provided sufficient black carbon content and solar radiation7,9, while the subsequent transport and distribution of these aerosols depend strongly on prevailing circulation patterns. By mapping the spatial distribution of extreme fires in July which are defined as daily fire radiative power exceeding 100 MW per 0.1° grid cell (i.e., approximately top 10% of severity across the boreal zone for the entire 2003–2023 period), we find that over 15% of the extreme fires in 2019 occur northward of 65°N, ranking the second in terms of extreme fire frequency following 2020. Concurrently, there is a pronounced low geopotential anomaly at the 300 hPa level developed over East Siberia, forming a strong cyclone system that enhances vertical motion and poleward transport of aerosols emitted from eastern and northern Siberia (Fig. 4c). In comparison, extreme fires in 2021 are located farther south, and circulation anomalies in 2020 are much weaker. Under such conditions, lofted BBA in 2020 and 2021 are trapped by mid-latitude anticyclonic systems and advected southward and downward into the mid-latitude Westerlies, failing to reach the Arctic stratosphere. Additionally, while we identify numerous extreme fire events during the 2003–2023 period other than 2019–2021, the resulting plumes do not efficiently reach the Arctic stratosphere. This outcome is primarily attributed to the absence of the specific coupling between fire location and atmospheric circulation that is observed in 2019 (Fig. 4f and Fig. S30). This suggests that, beyond fire intensity, the circulation pattern plays an important role in determining the distribution of SBBA at mid-to-high latitude in the Northern Hemisphere.

Methods
Observational data
This study focuses on the Arctic region (> 60°N) during the period 2000–2023. Observations for stratospheric aerosols and O3 were mainly obtained from satellite datasets. For aerosols, we used the total extinction profiles and SAOD data from CALIOP41 (2006–2021, monthly) and OMPS42 (2012–2023, daily), both of which have been extensively validated in previous studies41,43. The SAOD from CALIOP was mainly used to validate model results and was obtained by integrating the monthly mean aerosol extinction coefficients from 1 km below the MERRA-2 (The Modern-Era Retrospective analysis for Research and Applications, version 2) tropopause height to 36 km. The aerosol extinction coefficients (EC) at multiple wavelengths (λ) from CALIOP and OMPS were further used to calculate the Angstrom Exponent (AE)23 using Eq. (1)

AE = log(ECλ1/ECλ2) / log(λ2/λ1) (1)

In addition, we also used MODIS (Moderate Resolution Imaging Spectroradiometer) observations for total aerosol optical depth44 to independently validate our aerosol injection parameterization in modified simulations. For O3, the O3 volume mixing ratio data were taken from SWOOSH (Stratospheric Water and Ozone Satellite Homogenised), which merges multi-source satellite records45. TCO for the whole study period was collected from NASA Ozone Watch (https://ozonewatch.gsfc.nasa.gov/), which integrates OMPS retrieval and MERRA-2 reanalysis. Gridded TCO data from OMPS were also used to validate model performance. MLS L3 observations of temperature, ClO, HCl, and HNO3 from 2004 to 2023 were used to further verify our analysis (https://science.nasa.gov/mission/aura/mls). The meteorological data were obtained from ERA5 for circulation analysis46. Daily fire radiative power data at 0.1-degree resolution from 2003 to 2023 were obtained from GFAS (the Global Fire Assimilation System), which are originally based on MODIS active fire products47.

Model configuration and observational constraints
We used the CESM2 (Community Earth System Model version 2.1.3) to study the impacts of SBBA on O3 concentration. Given our focus on stratospheric processes, we utilised WACCM (Whole Atmosphere Community Climate Model) as the atmospheric component, which includes fully interactive chemistry for both troposphere and stratosphere48. All simulations were run at a horizontal resolution of 1.9° latitude × 2.5° longitude with 70 vertical layers stretching from surface to 6 × 10−6 hPa (140 km). Emissions of anthropogenic and biomass burning (BB) sources were taken from GEMS (Global Emission Modelling System, https://gems.sustech.edu.cn/) and GFED (Global Fire Emission Database 4s, https://www.globalfiredata.org/), respectively. To isolate the impacts of BBA, we fixed anthropogenic emissions to 2010 level for all simulations. The modelled vertical profiles of aerosol extinction at 550 nm over the Arctic were validated against CALIOP observations, showing notable underestimation of stratospheric aerosols using the default configuration (Fig. S1). We therefore modified the fire emission profiles by uniformly distributing the BB emission from the surface to a prescribed height, while keeping the total emission intensity the same as that in GFED. Sensitivity tests indicated that an injection height of 12 km yielded good agreement with CALIOP profiles for the 2019 fire season, while 5 km provided a reasonable fit for other years (Fig. S1). These modifications also brought models more in line with MODIS observation for total aerosol optical depth, which independently verified our parameterization (Fig. S32). The adjusted emission profiles were applied throughout this study.

As there was a strong eruption at Raikoke volcano (48.29°N, 153.25°E) on 21-22 June 2019 that might potentially affect stratospheric aerosols and O3, we made paired sensitivity simulations with and without this particular source. The total amounts of SO2 emissions and vertical profile parameterisation followed Cai et al. 202222. The modelled output showed negligible differences between the two simulations for Arctic O3. We therefore excluded the impacts of volcano emissions in our study.

Model experiment setup
To investigate the impacts of SBBA, we designed the following three experiments:
1. CLIM, which was a climatology run from 2000 to 2023 driven by annually varying GFED emissions, with all BB emissions injected from surface to 5 km height. This experiment served as the baseline and represented typical BB conditions. The modelled TCO from CLIM was further validated with observations from OMPS, demonstrating good agreement in terms of both spatial patterns and seasonal evolution (Fig. S33).
2. FIRE19, which ran successively for 40 years with repeating emissions from 2019 to 2020 (20-member ensemble). The BB emissions in 2019 were injected from the surface to 12 km to match observed aerosol profiles (Fig. S1). The difference between FIRE19 and CLIM indicates the impacts of abnormal SBBA seen from observations, which is the core of the present study.
3. NOBB, which was similar to CLIM except that all BB emissions were switched off.

All the above experiments were initialised from identical initial conditions and were run for 4 years prior to analysis as spin-up. Data for the 24 years from CLIM and NOBB runs were averaged to provide a climatology baseline. Given our focus on the O3 anomaly induced by the 2019 SBBA event relative to climatological conditions, the core of our analysis centred on the differences between FIRE19 and CLIM simulations.

The default WACCM configuration calculates heterogeneous chemical reaction rates based on aerosol surface area density for three types (sulphate, nitric acid trihydrate, and water-ice aerosols)48, which, however, does not account for the impacts of BBA. To address this and allow for the separation of effects, we conducted the following paired simulations for the FIRE19, CLIM, and NOBB experiments, leveraging two distinct chemical schemes:
• Default chemistry scheme: fire aerosols did not directly participate in heterogeneous chemical reactions in the stratosphere, so that only the dynamical impacts (e.g., modifications on radiation, temperature, and circulation) were captured.
• Updated chemistry scheme: following Solomon et al. (2023)4, this scheme allowed organic aerosols to enhance O3-depleting heterogeneous chemical reactions.

This approach allows us to distinguish the total SBBA influences into two components. The ‘dynamical impacts’ were quantified by the FIRE19–CLIM results under the default chemistry scheme, primarily reflecting aerosol-induced alterations to temperature and circulation. The ‘chemical impacts’ were estimated as the difference of FIRE19–CLIM results between the updated and default chemistry schemes, capturing the effects stemming from BBA heterogeneous reactions and the subsequent impacts of O3 depletion. We note, however, that this partitioning is not absolute due to the inherent interactions between dynamical and chemical processes. For instance, dynamical effects can modify ice cloud content and PSC formation, thereby altering the O3 chemical loss rate. Conversely, chemical loss of O3 subsequently lead to changes in temperature via interactions with longwave radiation. Throughout this paper, the terms ‘dynamical’ and ‘chemical’ were used to refer to the initial and direct effects of SBBA rather than the overall, non-linear coupled responses.

To better interpret the impacts of SBBA, we divided the focused study period (July 2019–April 2020) into three distinct stages. Stage-1 (July–October 2019) represents the period of high SBBA loading immediately following the aerosol injection. Stage-2 (November 2019–January 2020) is defined as a transition period, coinciding with the initial development of the polar vortex (Fig. S18). Stage-3 (February–April 2020) is the primary focus of this study, during which a record-high Arctic ozone depletion was observed (Fig. 1b).

To account for the anomalous meteorological conditions of spring 2020, we further developed a hybrid simulation framework. First, a fully nudged simulation towards ERA5 for 2019–2020 was performed to generate realistic initial conditions. For each month from January to April 2020, we then conducted the following three experiments:
1. Baseline: A free-running simulation initialized from the nudged state at the end of the previous month.
2. Perturbed dynamic: Similar to ‘Baseline’, but with the initial conditions adjusted to remove the estimated dynamical effects of SBBA from the previous month, as derived from the earlier free-running simulations. Such perturbations were applied to both atmospheric constituents (O3, aerosols, precursors, etc.) and meteorological fields (temperature, geopotentials, wind, etc.). As our earlier free-running simulations present 20-member ensembles, this perturbated experiment also consisted of 20 ensemble members, with each initialized with the corresponding member in the free-running ensemble.
3. Perturbed chemistry: Identical to ‘Perturbed dynamic’ except that the perturbations reflect the estimated chemical impacts of SBBA rather than dynamical ones.

The deviations of the two perturbated experiments from ‘baseline’ were then used to quantify the dynamical and chemical impacts of SBBA. This approach disentangled the dynamical and chemical influences of SBBA while maintaining generally realistic meteorological conditions for the focused period (Fig. S23). Note that these experiments were not conducted for 2019, as observations indicated that the temperature and O3 concentration in 2019 were close to 2000–2023 climatological levels, which were already captured accurately by our free-running simulations (Figs. S23–S24). Given the agreement of the SBBA impacts between the above free runs and this hybrid simulation (Fig. S25), we retain the conclusions derived from the original free-running ensembles.

Our analysis suggested that SBBA-induced impacts on Arctic O3 were tightly associated with stratospheric aerosol warming. While the initial aerosols simulations were constrained using CALIOP data, comparisons against MLS observations and ERA5 reanalysis revealed an overestimation of the SBBA-induced warming (Fig. S26b, c). To quantify the impacts of this bias, we conducted a series of sensitivity experiments by linearly scaling the BBA emissions from 1.0 down to 0.1, and evaluated the modelled stratospheric temperature response against observed anomalies from MLS for the summer of 2019 (July and August). A scaling factor of 0.5 was determined to yield the optimal agreement between the modelled and observed temperature magnitudes (Figs. S14, S26). Consequently, this factor was applied to the BBA emissions to perform a 10-member ensemble run, which utilised a configuration identical to FIRE19 using an updated chemistry scheme, with the sole exception of the adjusted emission magnitude.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "Review of manuscript entitled “Stratosphere biomass burning aerosols compensate record-breaking ozone depletion over the Arctic in spring 2020”, authored by Qirui Zhong, Sander Veraverbeje, Pengfei Yu, Jianmin Ma, and Shu Tao. This manuscript examines the influence of stratospheric biomass burning aerosols (SBBA) on Arctic ozone. The analysis is based on free-running experiments with the CESM2-WACCM chemistry–climate model, incorporating the observed SBBA loading for the period 2000–2023. In addition, a dedicated case study focuses on the 2019–2020 winter, when severe ozone depletion occurred in March 2020. This case study employs a 20-member ensemble of two-year time-slice simulations, each repeatedly imposing the observed 2019–2020 SBBA loading. By switching the heterogeneous reactions of SBBA on and off, the experiments are designed to disentangle two distinct effects of SBBA on ozone: (1) stratospheric warming and (2) direct chemical destruction. It is concluded that the presence of SBBA in the Arctic stratosphere during the winter of 2019-2020 mitigated the extent of ozone depletion that would have occurred in its absence, and a quantification of this effect is given. However, the experimental design precludes drawing such conclusions. As a result, we cannot recommend publication of the manuscript unless our concerns are addressed. Our major comments are provided below. Major comments: • The study aims to quantify the role of SBBA in Arctic ozone, using as a case study the elevated SBBA concentrations in 2019–2020, which coincided with record Arctic ozone depletion. To this end, the experiments labeled ‘FIRE19’ prescribe the observed 2019-2020 SBBA emissions, constructing a 20-member ensemble for that period. However, these experiments do not reproduce the observed Arctic ozone loss of that winter (see Fig. 2a), very likely because the specific dynamical conditions of 2019–2020 are not captured. Indeed, Figure 2 shows that for the 2019–2020 episode, the FIRE19 ensemble mean produces an increase in the total ozone column relative to climatology, which is in complete contrast to the observations. We consider this point to be critical: there is no basis for assuming that the effect of SBBA on Arctic ozone is independent of the dynamical conditions. For example, the stratospheric warming induced by SBBA would have very different consequences for ozone if the baseline temperatures were sufficiently low to enable PSC formation. However, the assessment of SBBA effects on ozone during that winter is based on extrapolating the FIRE19 results to the specific dynamical conditions of 2019-2020, rather than on simulations that explicitly reproduce them. An alternative to FIRE19 would be to conduct experiments with and without the 2019-2020 SBBA concentrations, while nudging the meteorological conditions to the reanalysis. This approach is available in CESM2-WACCM through the specified dynamics (SD-WACCM) configuration. Its main strength is that the low spring temperatures that favored the severe ozone depletion of that winter would be realistically reproduced. Its main limitation, however, is that it would not allow the dynamical and chemical effects of SBBA to be separated. • The analysis lacks any estimation of statistical significance, which is necessary to assess the robustness of the results. For example, in Figure 2a-b, it would be very informative to see the spread of the individual ensemble members, or to include an estimation of the confidence interval. Same for the rest of the figures. • There are several inconsistencies in the dynamical explanations. For example, in lines 145 onwards, it is stated that the warming of the lower stratosphere introduces instability into the vortex, suppressing wave penetration, which leads to higher divergence of the EP flux and thus strengthened BDC. This is inconsistent, since the divergence of the EP flux leads to a weakening of the BDC. Similarly, in line 166, higher divergence of the EP flux is associated with a weakening of the polar vortex, which is again inconsistent. • All figures include multiple panels, which makes it difficult to identify what is being discussed in the text. It would be helpful to add individual titles to each panel indicating the variable and the month/season represented, as well as referencing more clearly in the text which figure and panel is being discussed. This suggestion also extends to the figures in the Supplementary Material. Specific comments: • Line 62: Figure 1a shows anomalies, so it would be clearer to refer to anomalies also in the text. • Line 73: It would be helpful to explain what the Angstrom Exponent is. • Caption Figure 1: The text defines SAOD, but not AOD. • Line 114: This is related to the first major comment: if the ozone depletion event is not reproduced in the model, it cannot be extrapolated from observations to make this estimate. • Line 124 : How is that 26% calculated? The same applies to the 50% in line 125. • Line 128-132: Again, without the model reproducing the 2020 ozone depletion event, it is not correct to extrapolate to observations. • Line 136 and following: How were the three time stages determined? • Figure S14: There must be an error in the units, since typical EPFD values in ms-2 are of the order of 1e-5. • Line 179 and 195: UPLS should be UTLS. • Line 204: If Figure 4 shows the absolute field (not anomalies), it appears that 2020 would be the year with the largest circulation anomalies. I recommend that instead of representing the maps with the absolute value, the anomalies with respect to the climatological period should be represented. • Line 208: The geopotential pattern in 2020 does not resemble the climatology, presenting much lower geopotential values at high latitudes. • Line 218: According to Figure 22, geopotential values increase in all regions north of 40N, not only in polar regions (although the color scale chosen is a bit confusing). Please explain how the trend is calculated. Is it the multi-model mean that is represented? For each model, do you use only one ensemble member? or the ensemble mean? How is the statistical significance calculated? • Line 221: What do the authors mean by “reverse the patterns”? Is it meant that lows will more likely occur in mid-latitudes and highs in high latitudes? • Line 225: How were these similarities calculated? Using spatial correlations, just by looking for similar geopotential values in certain regions, etc.? Please clarify. • Line 213 to 227 (future projections): This paragraph does not substantially contribute to the analysis. If the goal is to assess the likelihood of the July 2019 pattern in the future, more extensive analysis is needed. We recommend removing this paragraph and enhancing the previous discussion to better demonstrate the role of the July 2019 Siberian low in aerosol injection into the stratosphere. • Line 234-236: We do not agree that this has been demonstrated in the manuscript, as the current experimental design does not permit extrapolation of the model results to the observations. • Line 258-259: We do not agree with this conclusion. The result that the average geopotential will increase does not imply that extreme events (assuming that 2019 is one) will become more or less frequent in the future. In fact, it remains unclear how often a 2019-like pattern occurs in the current climatology and how its frequency might change under future conditions. • Methods: Many of the databases mentioned in this section lack references where further information can be found.", "reviewer_2": "General The manuscript deals with a very relevant and modern topic of atmospheric science. It deals with the impact of wildfire smoke on the stratospheric ozone layer in the Arctic and tries to combine aspects of air chemistry (ozone depletion) and atmospheric dynamics (vertical and horiziontal transport of ozone) over the Arctic in the spring of 2020 to explain and quantify the influence of wildfire smoke on the observed record-breaking ozone reduction. The manuscript is carefully written. An in-depth discussion is presented. The paper is very attractive and fits well into the Nature publication strategy. Minor revisions are needed. My detailed comments are given below. However, let me start with my main point: The observed record-breaking ozone reduction event over the Arctic in spring 2020 as well as the strong decrease of the ozone content over Antarctica in 2020 and 2021 occurred in the presence of strong wildfire smoke layers. During these time periods with dense wildfire smoke layer, extraordinarily strong polar vortices developed. Is this pure coincidence? Keeping this in mind, my question is with respect to the Arctic 2020 ozone hole: What caused the rather strong ozone minimum over the Arctic in the spring of 2020? Can we be sure that the impact of smoke is well described by your analysis? Or, was the smoke even responsible for the evolution of the strong vortex, the cold temperatures, the changes in the circulation structures and wave activity, the Brewer Dobson circulation features, PSC occurrence frequency, PSC characteristics and related chlorine and ozone chemistry aspects? I was hoping to get an answer to this overall question in this manuscript! I would appreciate if this point would be discussed somewhere in the revised manuscript. Detailed comments: Line 29: To my opinion, the potential impact of wildfire smoke on stratospheric ozone reduction was mentioned for the first time in the paper of Ohneiser et al. (ACP, 2021). This should be mentioned in the introduction. Nobody obviously expected a strong wildfire smoke layer over the Arctic in 2019-2020. The research community obviously assumed that all the aerosol in the UTLS height range was just sulfate aerosol, originating from the Raikoke volcanic eruption. Line 62: The Arctic UTLS optical depth (at 500-550 nm) of about 0.06 in the late summer and autumn of 2019 is documented in the paper of Ansmann et al. (JGR 2024). In this publication, direct extinction observations are discussed. In the case of CALIOP backscatter lidar, the extinction coefficients have to be estimated from the 532 nm backscatter coefficients by assuming an extinction-to-backscatter ratio (lidar ratio). CALIOP assumes a lidar ratio of 70sr in this conversion, but Ohneiser et al. (2021) shows that the lidar ratio was about 85sr for this Siberian wildfire smoke. To my opinion, the UTLS AOD is the relevant quantity in the Arctic (not the stratospheric AOD, denoted as SAOD). In the Arctic, the tropopause (as a barrier between troposphere and stratosphere in midlatitudes) does not play a role. The stratospheric AOD was much lower than 0.06 (as shown in the Ansmann comment paper, JGR, 2024). Lines 72-85: If the Angstroem exponent (AE) is used to corroborate that the smoke dominated, one needs to mention always the wavelength range. Lidar observations in the 355-532nm spectral range show smoke AE values close to zero (Ohneiser et al., 2021), AE values for the spectral range from 510 to 870 nm may be close to 1. This points to the fact that the smoke particles form an accumulation-mode size distribution (shifted a bit to large particles, we may denote this as aged accumulation mode). However, the volcanic sulfate particles also show an aged accumulation mode, so that AE cannot be used to clearly distinguish between smoke and volcanic sulfate particles. Furthermore, the lidar ratios for smoke were obviously around 50, 85, and about 100sr for 355, 532, and 1064 nm (see here also the papers of Haarig et al., ACP, 2018, Ohneiser et al., ACP 2020, ACP 2022). This means that the CALIOP-related AE values have to be handled with caution. The CALIOP backscatter values were converted into extinction values by using lidar ratios of 70sr at 532 nm and 40sr at 1064 nm, and not by using 70sr (or even 85sr at 532 nm as observed by Ohneiser et al., 2021) and 90-110sr at 1064 nm. This has then a big impact on the AE values. Line 80: The Sarychev (June 2009) volcanic SO2 amount was about 25% lower than the Raikoke (June 2019) SO2 amount. The Sarychev-related maximum AOD values were around 0.02 (at 550nm), as shown in many paper (e.g., Haywood et al, JGR 2010), and the Raikoke AODs were thus about 0.025 and lower… Such values cannot explain the observed ULTS AODs (at 532 nm) of more than 0.1 in the later summer of 2019 over high northern latitudes as shown in the Ohneiser et al. 2021 paper. Line 80 (and Figs S3-S4): Boone et al. (JGR, 2022) found the opposite! Please check that paper and expand the discussion. Line 83 and 84: The BC content was probably less than 5%. More than 95% was organic carbon (OC). OC is absorbing, even in the 500-600 nm wavelength range, and warms the air in this way. Sulfate on the other hand only scatters sun light, and does not warm the UTLS height range. This should be emphasized as a convincing argument for the presence of smoke. Line 95-96: Here, a reference is needed, maybe Rex et al., 2004? Line 102: What was the reason for the rather low temperatures in the winter 2019-2020? Is there an explanation available? Please check the numerous papers published on the record breaking Arctic ozone hole and the low temperatures, published in 2020 and 2021. Note, that almost all if ot all of these papers ignored the smoke because the authors were not aware of the smoke! The temperatures deviated from the longterm mean by 8-10K. That caused a high PSC occurrence frequency according to the Rex et al. 2004 paper. Figure 1: It is confusing that the x-axis in Fig.1a and the x-axis in Fig.1b, both show the same numbers from 1 to 12, but no information on the year (2019 in 1a, 2020 in 1b) is given. We need a description below the numbers: Month in 2019 (in a), Month in 2020 (in b). Similarily, I would add A19, S19, O19 in the panels c1, c2, and c3, respectively, to facilitate understanding of this complex figure, and F20, M20, A20 in panels d1, d2, and d3, respectively. Line 114: My question from above: What explains the record-breaking ozone reduction in 2020, coincidentally (?) occurring with this record-breaking smoke pollution? Figure 2: I would add: Month in 2019-2020 below the numbers of the x-axis in Figure 2a. Furthermore, it is not easy to identify all the different curves by using just different colors and line styles. Some symbols would facilitate identification. Again! What caused the TCO anomaly of -70DU in March 2020? You run models that simulate meteorological and chemical processes, you should be able to answer this question! If you are not able to simulate (and resolve) all the impacting dynamical and air chemical processes in detail you should mention that, and provide the reasons in the discussion. It is simply not satisfactory if no hypothesis is provided regarding the basic reasons and causes for the strong ozone reduction by 70 DU. Line 142: It seems to be that the warming of the layer from 300 to 150 hPa during the stage-1 period (July to October 2019) in Figure 3d2 and cooling at heights above the 100 hPa level is of key importance for all the changes in vertical and horizontal transport and circulation patterns. That should be better highlighted. And such warming events can only be produced in the presence of absorbing smoke (and not in the case of a volcanic sulfate layer). That should be clearly stated. Line 153. It is confusing the read: …especially above 50 hPa where few aerosols are located. Above 50 hPa means…. at 60, 70 80 hPa….. But you probably want to say: especially at heights above the 50 hPa level where few aerosols are located. Line 169-172: The statements, presented here, sound like facts… although the simulations allow the development of hypotheses, only. And the final question remains: What caused the record-breaking ozone reduction, if not the smoke impact via radiative, chemical, and dynamical processes? Figure 3: … Month in 2019-2020 … could be added as x-axis text. Line 180: Besides the impact of pyroCb, smoke can ascend via self-lofting as explained by Ohneiser et al. (ACP, 2021 and ACP, 2023). Line 193-194: There were definitely no pyroCbs over central eastern Siberia in July and August 2019! Please provide respective satellite images to corroborate your statement! Otherwise, remove the statement. However, self-lofting obviously took place and transported the smoke up to the UTLS region (Ohneiser et al., 2021). Figure 4: … in Northern Hemisphere. (a,b?) Daily series of SAOD… and not (a,c) Daily…. , may be I am wrong: (a,b) instead of (a,c). Line 213-227: Please avoid speculation. Keep in mind that the smoke ascended many kilometers upward during the summer months as long as sun light was available over Arctic regions, and this aspect is most probably not considered in the simulation model. And you also do not include any Raikoke sulfate impact on ozone depletion in your study. Lines 229-247: To my opinion, self-lofting of smoke plus the mentioned favorable 2019 mesoscale atmospheric conditions were responsible for the transport of smoke into the Arctic stratosphere. Line 239-240: Regarding aerosol-cloud interaction by BBA… What do you mean here? Please provide references. Lines 251-254: The combination of self-lofting of smoke and the anomalous high-altitude cyclone obviously favored the upward and poleward transport. Lines 260-264: Please avoid speculate statements. There are so many additional figures, Fig. S1-S26. Do we need all of them? Fig. S2: CALIOP AE values (532/1064) may not be ok. The extinction values are obtained by using a lidar ratio of 70sr at 532 nm and of 40sr at 1064 nm. But observed lidar ratios are typically 70sr at 532 nm and 90-110sr at 1064 nm (Haarig, ACP, 2018) and Ohneiser et al. (ACP, 2020). The upper layer in Fig S2b is, to my opinion, caused by Raikoke sulfate aerosol. Fig S3: Please check the paper of Boone et al. (JGR, 2022). Fig. S6 In the spring of 2010 (after the Sarychev eruption), no ozone reduction is visible. One can assume that the same impact is then given for the Raikoke eruption (ozone conditions in the spring of 2020). So, the record-breaking ozone reduction in 2020 may be fully the result of the impact of the unusually strong smoke pollution? Any own explanation? This topic should be discussed. Fig. S11: The shown results are speculative. A trustworthy approach to consider smoke particles as INPs is most probably not implemented in the model. Fig. S15: How well is the model able to properly simulate the impact of smoke traces and volcanic sulfate particles on NAT (PSCs) formation and PSC microphysical properties? Fig. S18: X-axis, please add …Year … below the numbers. Fig. S19: Stratospheric AOD considers the vertical range from the tropopause to 25 km height? And the Tropopause is well known? The Raikoke-related stratospheric AOD was up to a maximum of 0.025 in August 2019 and then only 0.015 in September 2019. Fig S20: Please add … Month of the year 2019 …. below the x-axis numbers. References mentioned in the review, but not in the manuscript: Ansmann, A., Veselovskii, I., Ohneiser, K., and Chudnovsky, A.: Comment on “Stratospheric Aerosol Composition Observed by the Atmospheric Chemistry Experiment Following the 2019 Raikoke Eruption” by Boone et al., J. Geophys. Res.-Atmos., 129, e2022JD038080, https://doi.org/10.1029/2022JD038080, 2024. Haarig, M., Ansmann, A., Baars, H., Jimenez, C., Veselovskii, I., Engelmann, R., and Althausen, D.: Depolarization and lidar ratios at 355, 532, and 1064 nm and microphysical properties of aged tropospheric and stratospheric Canadian wildfire smoke, Atmos. Chem. Phys., 18, 11847–11861, https://doi.org/10.5194/acp-18-11847-2018, 2018. Haywood, J. M., Jones, A., Clarisse, L., Bourassa, A., Barnes, J., Telford, P., et al. (2010). Observations of the eruption of the Sarychev volcano and simulations using the HadGEM2 climate model. Journal of Geophysical Research, 115(D21), D21212. https://doi.org/10.1029/ 2010JD014447 Ohneiser, K., Ansmann, A., Baars, H., Seifert, P., Barja, B., Jimenez, C., Radenz, M., Teisseire, A., Floutsi, A., Haarig, M., Foth, A., Chudnovsky, A., Engelmann, R., Zamorano, F., Bühl, J., and Wandinger, U.: Smoke of extreme Australian bushfires observed in the stratosphere over Punta Arenas, Chile, in January 2020: optical thickness, lidar ratios, and depolarization ratios at 355 and 532 nm, Atmos. Chem. Phys., 20, 8003–8015, https://doi.org/10.5194/acp-20-8003-2020, 2020. Ohneiser, K., Ansmann, A., Kaifler, B., Chudnovsky, A., Barja, B., Knopf, D. A., Kaifler, N., Baars, H., Seifert, P., Villanueva, D., Jimenez, C., Radenz, M., Engelmann, R., Veselovskii, I., and Zamorano, F.: Australian wildfire smoke in the stratosphere: the decay phase in 2020/2021 and impact on ozone depletion, Atmos. Chem. Phys., 22, 7417–7442, https://doi.org/10.5194/acp-22-7417-2022, 2022 Ohneiser, K., Ansmann, A., Witthuhn, J., Deneke, H., Chudnovsky, A., Walter, G., and Senf, F.: Self-lofting of wildfire smoke in the troposphere and stratosphere: simulations and space lidar observations, Atmos. Chem. Phys., 23, 2901–2925, https://doi.org/10.5194/acp-23-2901-2023, 2023. Rex, M., Salawitch, R. J., von der Gathen, P., Harris, N. R. P., Chipperfield, M. P., and Naujokat, B.: Arctic ozone loss and climate change, Geophys. Res. Lett., 31, L04116, https://doi.org/10.1029/2003GL018844, 2004.", "reviewer_3": "This study investigates how stratospheric biomass burning aerosols (SBBA), which originated from wildfires in summer 2019, influenced the record-breaking Arctic ozone depletion in spring 2020. Using satellite-constrained modelling, the authors attempt to separate the chemical and dynamical impacts of SBBA on stratospheric ozone. They conclude that, although SBBA tend to reduce Arctic ozone levels through chemical processes, they also induce significant dynamic responses that offset approximately 19% of the observed ozone depletion in spring 2020 through stratospheric heating and enhanced poleward transport. This topic is of particular scientific interest given the increasing occurrence of boreal wildfires and their implications for stratospheric composition and circulation. However, the conclusions drawn by the authors regarding the dynamic impacts of SBBA and their magnitude are not yet fully supported by observational or modelling evidence. Further clarification and justification are required before the current version can be considered for publication. Major Concerns 1.According to the current results, my main concern is that the evidence is not solid enough to support the conclusion regarding the SBBA-induced changes in dynamic processes. The manuscript attributes substantial and persistent changes in ozone (O₃) (20–30%) to SBBA-induced heating in the lower stratosphere and cooling in the mid–upper stratosphere. This results in an increase of approximately 0.2 ppmv (around 10%) in Arctic ozone at 20 hPa in spring 2020. However, the modelled temperature anomalies are quite large (up to +4 K from July to October 2019 and +3 K in spring 2020), yet they lack observational validation. Given the significant uncertainties in model performance in the polar stratosphere, and considering that most SBBA had been transported below 200 hPa by late 2019, it is questionable whether radiative effects alone could generate such substantial circulation perturbations. The authors should provide stronger evidence to justify these large anomalies. For instance, can the significant lower-stratospheric warming in autumn 2019 and spring 2020, which is attributed to SBBA-driven dynamical changes, be corroborated by satellite or reanalysis temperature records? Presenting time–latitude cross sections of temperature anomalies from observations would provide essential validation. 2.The authors link the reduced zonal winds and enhanced poleward ozone transport observed in spring 2020 to an anomalous Brewer–Dobson Circulation (BDC), which was induced by the Southern Hemisphere Boreal Basin Anomaly (SBBA). However, this claim should be substantiated using reanalysis data (e.g. ERA5 or MERRA-2). Are the modelled zonal wind anomalies and BDC variations consistent with the reanalysis data? Can the BDC anomalies be clearly identified in the observations? Corresponding figures and diagnostics should be added for verification. 3.In the 'Methods' section, the authors attribute the difference between FIRE19 and NOBB to chemical impacts, since only heterogeneous chemistry on organic-rich particles is included in FIRE19. In contrast, the difference between CLIM and NOBB is used to represent dynamical impacts. However, the distinction between chemical and dynamic effects is not entirely clear-cut. After entering the stratosphere, biomass burning aerosols, particularly black carbon and organic carbon, can absorb and scatter solar radiation, thereby influencing O₃ chemistry by modifying radiative heating. Therefore, the separation of chemical and dynamical effects using CLIM/FIRE19/NOBB is conceptually debatable and requires further justification or discussion of limitations. Minor comments: 1.The manuscript primarily presents anomalies (e.g. for ClO, HCl, HNO₃, SAOD, temperature and zonal wind), but does not display the climatological mean values. Including reference states would help to quantify the magnitude of these anomalies. 2.Lines 61–62: The text states that 'the SAOD over the Arctic reached a peak value of 0.06 in autumn 2019 (August– October), which was more than double the multi-year average' (see Fig. 1a). However, Fig. 1a only shows colour scales up to 0.05 and does not display the climatological reference. Please clarify. 3.Please describe the method that used to calculate SAOD from CALIOP datasets. 4.Figures S1–S4 clearly demonstrate that the aerosols observed in the lower stratosphere of the Arctic from August to October 2019 were not volcanic sulphate aerosols. However, the manuscript should explain why the black carbon aerosols responsible for local warming in Figure S5 do not appear to have heated the lower stratosphere in the following months (September–October). As shown in Figure 1, the SBBA should now extend to around 200 hPa. 5.Figure S2: How was this figure calculated? Was the anomaly defined as the difference between 2019 and the average AOD for 2008 and 2009? Please specify. 6.Figure S9 shows the estimated TCO with the impacts of SBBA excluded. How is the TCO from the FIRE19 simulation estimated? 7.Figure S12 compares modelled ozone (O₃) anomalies with observations for July–September 2019. The observations are based on the difference between 2019 and the climatological mean, containing both natural variability and SBBA effects. In contrast, the model results isolate the SBBA contribution. If the authors attribute most of the 2019 O₃ anomaly to SBBA-driven dynamical changes, then strong temperature and circulation anomalies should also be evident in the reanalysis data for the same period. This consistency check is currently missing. 8.Line 346: “spun up” should be spin-up. 9.Regarding the adjusted biomass burning emission height, was only the injection height modified or was the emission intensity adjusted too? Please clarify.", "reviewer_4": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts."}, "author_response": "We sincerely thank the reviewer for their insightful and constructive feedback. These suggestions have been instrumental in refining our work. In particular"}]

Decision letter