Variability and trends of upper-tropospheric aerosols over the Asian summer monsoon region: An AeroCom multi-model study

Chin, Mian; Wright, Jonathon S.; Bian, Huisheng; Tan, Qian; Pan, Xiaohua; Takemura, Toshihiko; Matsui, Hitoshi; Tsigaridis, Kostas; Bauer, Susanne; Ginoux, Paul; Peng, Yiran; Guo, Zengyuan; Fadnavis, Suvarna; Laakso, Anton; Burrows, John P.; Taha, Ghassan; Kar, Jayanta; Rozanov, Alexei; Arosio, Carlo; Rieger, Landon; Bourassa, Adam

doi:10.5194/egusphere-2025-6257

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https://doi.org/10.5194/egusphere-2025-6257

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14 Jan 2026

| 14 Jan 2026

Status: this preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).

Variability and trends of upper-tropospheric aerosols over the Asian summer monsoon region: An AeroCom multi-model study

Mian Chin, Jonathon S. Wright, Huisheng Bian, Qian Tan, Xiaohua Pan, Toshihiko Takemura, Hitoshi Matsui, Kostas Tsigaridis, Susanne Bauer, Paul Ginoux, Yiran Peng, Zengyuan Guo, Suvarna Fadnavis, Anton Laakso, John P. Burrows, Ghassan Taha, Jayanta Kar, Alexei Rozanov, Carlo Arosio, Landon Rieger, and Adam Bourassa

Abstract. Aerosols in the upper troposphere play an important role in Earth’s radiative balance and atmospheric composition. Satellite observations have revealed a recurrent enhancement of aerosol extinction coefficient (AEC) in the upper troposphere and near the tropopause over the Asian summer monsoon (ASM) anticyclone (ASMA) region during July–August. However, substantial uncertainties remain regarding (i) the influence of ASM dynamics and climate variability on these aerosols, (ii) the extent to which the upper-tropospheric aerosol trends reflect changes in surface pollutant emissions, and (iii) the ability of global models to simulate aerosol amounts, variability, and key controlling processes in the upper-tropospheric ASMA region. Here, we present results from an AeroCom-coordinated global multi-model study addressing these issues. Using simulations from nine models for 2000–2018, we find large inter-model differences in non-volcanic AEC over the upper-tropospheric ASMA region, with coefficients of variation ranging from 64 % to 86 %. Approximately half of this spread is attributable to differences in transport and wet removal processes, as diagnosed using common tracers, with discrepancies in wet removal contributing about eight times more than those associated with transport. The multi-model ensemble indicates an overall increase in non-volcanic AEC over the past two decades, consistent with rising anthropogenic emissions in Asia, while interannual variability is linked to climate variability as represented by the Multivariate ENSO Index. Through comparison with satellite observations, we further identify persistent model deficiencies, particularly in the representation of volcanic aerosols, and highlight priorities for future coordinated model developments and evaluation.

Received: 15 Dec 2025 – Discussion started: 14 Jan 2026

Competing interests: At least one of the (co-)authors is a member of the editorial board of Atmospheric Chemistry and Physics.

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'Comment on egusphere-2025-6257', Anonymous Referee #1, 02 Feb 2026 reply
Summary
The manuscript titled "Variability and trends of upper-tropospheric aerosols over the Asian summer monsoon region: An AeroCom multi-model study" evaluates nine global models from AeroCom Phase-III UTLS regarding their predictions of aerosol extinction coefficients (AEC) in the Asian Summer Monsoon Anticyclone (ASMA) region.

The inter-comparison shows large discrepancies in volcanic AEC between models. For non-volcanic aerosols, a high coefficient of variation was also found. By using two tracers, the authors diagnosed the extent to which convective transport and wet removal explain these inter-model differences. The analysis suggests that differences in wet removal contribute more significantly to the diversity of AEC in the ASMA region than differences in transport. Based on these results, recommendations are made to improve, constrain, and evaluate global models.

Shifting from model evaluation to physical trends, the study uses the multi-model mean from 2000 to 2018 to investigate trends in atmospheric conditions. A statistically significant increase in AEC of approximately 1.2% per year is found, which correlates with increasing Asian aerosol emissions. Finally, the authors show that the interannual variability of AEC can be linked to climate variability through the Multivariate El Niño/Southern Oscillation (ENSO) Index (MEI.v2).

General comments
Overall, this is a scientifically sound and well-written manuscript. It is relevant to evaluate inter-model differences and their causes for understanding the effects of different model parameters and improving the reliability of aerosol simulations. The manuscript furthermore provides good recommendations for improving, constraining, and evaluating future models. I also appreciate that the study extends the scope beyond the model inter-comparison to analyze physical trends in atmospheric conditions. The writing is clear, supported by effective figures and tables. The study fits well within the aims and scope of Atmospheric Chemistry and Physics. I believe this manuscript is suitable for publication in Atmospheric Chemistry and Physics after addressing the minor comments listed below.

Minor comments
In subsection 2.1, the authors mention the use of several emission datasets to cover the full simulation period of 2000 to 2018. Specifically, anthropogenic emissions from 2015–2018 are taken to be constant based on 2014 data, and volcanic emissions switch from EP-TOMS to Aura-OMI in 2004. While I recognize that this is a standard and necessary strategy given data availability, it is good practice to briefly discuss how these discontinuities might influence the results or cite references that discuss this. Given that a key finding of the manuscript is a statistically significant trend in AEC, could the authors clarify how holding anthropogenic emissions constant for the final four years might influence that trend? A brief comment on the potential artifacts introduced by switching satellite instruments for volcanic data would also be beneficial.

On lines 304–307, the authors state that R²≈0.50 is "consistent with a simple summation of the CV values... which is roughly half of the 79% CV." This comparison is mathematically difficult to justify. Coefficients of variation, which are derived from standard deviations, do not sum linearly. For independent variables, variances add linearly, while standard deviations add as the square root of the sum. R² represents the fraction of explained variance, whereas CV represents a fraction of standard deviation. An R² of 0.50 implies that ~71% of the standard deviation is explained, which contradicts that the summed CVs are only half of the total. I suggest removing this specific sentence as the result of R²=0.505 stands strong enough on its own without this non-rigorous comparison.

There is no clear description of which statistical test was used to determine the statistical significance of the increasing AEC trend in subsection 3.4. Based on the caption of Fig. 10, I conclude that a Student's t-test was used. The standard Student t-test relies on assumptions that may not hold for this data, particularly the assumption of independence. Time series of aerosol extinction coefficients often have autocorrelation. Could the authors clarify exactly which type of t-test was used and if any adjustments were made to account for autocorrelation? If a standard Student t-test was used, I suggest performing a more robust test, such as the Mann-Kendall test, to confirm the results.

The authors correctly note in subsection 3.1 that satellite retrievals below the tropopause are limited by cloud presence. However, deep convection in the ASMA region can also reach the tropopause (100 hPa). I would thus expect that even at the studied height of Fig. 2 the satellite data misses some times when clouds are present, whereas the models likely span the full period. Was any filtering applied to the model data to match the satellite data availability? Otherwise, this discrepancy in data availability could bias the comparison.

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Citation: https://doi.org/10.5194/egusphere-2025-6257-RC1

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Short summary

Aerosols in the upper troposphere influence weather and climate. The Asian summer monsoon efficiently transports surface pollutants upward, shaping aerosol amounts and variability in the upper troposphere. Using multiple global models, this study finds a summertime increase in upper-tropospheric aerosols of about 1.2 % per year from 2000 to 2018 over Asia, consistent with rising pollutant emissions, while year-to-year changes are mainly driven by climate variability affecting monsoon dynamics.


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