the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 12 May 2025
Unveiling Sulfate Aerosol Persistence as the Dominant Control of the Systematic Cooling Bias in CMIP6 Models: Quantification and Corrective Strategies
Abstract. Including sophisticated aerosol schemes in the models of the sixth Coupled Model Inter-comparison Project (CMIP6) has not improved historical climate simulations. In particular, the models underestimate the surface air temperature anomaly (SATa) when anthropogenic sulfur emissions increased in 1960~1990, making the reliability of the CMIP6 projections questionable. Biases in cooling among the models are correlated with sulfate burden and the deposition of sulfur is the process responsible. We show that the lifetime of atmospheric sulfur, defined by a new global index for sulfur deposition (an "Effective Sulfur Retention Timescale" (ESRT)), determines the cooling biases. Reducing the biases to within the observational uncertainty is consistent with a physically plausible ESRT of around one day, whereas the CMIP6 models overestimate this timescale. Based on targeting a reduction of ESRT, post-CMIP6 improvements to two models are shown to greatly improve SATa reproduction.
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RC1: 'Comment on egusphere-2025-1059', Anonymous Referee #1, 12 May 2025
The manuscript firstly points out that most CMIP6 earth system models (with interactive atmospheric sulfate cycle) present cold biases in the period 1960-1990 (called PHC in the manuscript, pot-hole cooling). The authors performed then a series of investigations searching the relation of this cold bias with sulfate sources and sinks across the available CMIP6 models. The authors finally proposed a single parameter āESRTā, effective sulfate retention time. This is an interesting diagnostic, relatively stable for a given model and quite useful to characterize its sulfate cycle. It was shown that ESRT has a good capacity to explain the cold bias across models. It is also interesting to see that the authors use the temperature anomalies of the PHC period to āconstrainā the optimal value of ESRT. This optimal value is then used to approximate the ārightā sulfate deposition rate which is furthermore used in the BCC model with improved performance.
All that said, I have a small concern for what shown in Fig. 1a displaying temperature time series. From those curves, I can deduce that the cold bias of models in the PHC period is not exceptional, not as the authors pointed out, since there is a good trend compared to observation. But the cold bias (at least in the multi-model ensemble mean) occurred before the PHC period, roughly at the point of 1935 where models drift significantly from observation and the cold bias remains for the rest of the time, including the PHC period (1960-1990).
Citation: https://doi.org/10.5194/egusphere-2025-1059-RC1 -
AC1: 'Reply on RC1', Jie Zhang, 15 May 2025
Thank you for your comments. We reference Figure 12 from Flynn and Mauritsen (2020), which evaluates historical surface temperature anomalies in CMIP5 and CMIP6 models. Their analysis indicates that the CMIP5 multi-model ensemble mean effectively captured the instrumental record with observation falling well within model spread ā a consistency also noted in CMIP3 models assessed in the IPCC Third Assessment Report (IPCC AR3). In contrast, a majority of CMIP6 models exhibit a cold bias in surface temperature, marking a notable departure from earlier model generations.
You are right. The cold bias occurred before the PHC period, roughly at the point of 1935. We think it is also attributed to elevated sulfate aerosol burdens as shown in Fig.1b. The selection of the 1960ā1990 as PHC period in our analysis stems from its alignment with accelerated anthropogenic emissions, particularly of sulfate precursors (e.g., SOā). These emissions amplify aerosol-induced radiative cooling, which exacerbates the model-observation divergence during this era. By focusing on this interval, we aim to isolate the climate impacts of anthropogenic aerosols during a period of rapidly increasing industrial activity.
Reference:
Flynn CM, Mauritsen T (2020) On the climate sensitivity and historical warming evolution in recent coupled model ensembles. Atmos Chem Phys 20(13):7829-7842 doi:10.5194/acp-20-7829-2020
Citation: https://doi.org/10.5194/egusphere-2025-1059-AC1
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AC1: 'Reply on RC1', Jie Zhang, 15 May 2025
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RC2: 'Comment on egusphere-2025-1059', Stephen E. Schwartz, 14 May 2025
I have major concern over the definition of the quantity that the authors call the ESRT, effective sulfur retention time scale, This is a non-conventional definition of a residence time that may account for the short (ca 1 day) values reported, and certainly precluding comparison with other measures of lifetime in the literature.Ā
The authors seem unaware of the large prior literature pertinent to this study.Ā
I elaborate on these concerns in the pdf review.Ā
Stephen E. Schwartz
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AC2: 'Reply on RC2', Jie Zhang, 05 Jun 2025
We thank Dr. Schwartz for the constructive critique, particularly for highlighting the importance of distinguishing the "effective sulfur residence time" (ESRT) from other lifetime measures reported in the literature. We acknowledge that the term "effective sulfur residence time (ESRT)" is potentially misleading, as it primarily serves as a diagnostic tool for model tuning rather than representing a physical timescale. The conventional definition of sulfate lifetime remains critical for validating the model's physical realism.
As suggested, we have calculated sulfate lifetimes in the CMIP6 models, BCC-ESM1-1, and UKESM1-1-LL. The model-calculated sulfate lifetimes are consistent with previous literature.Ā We also refine the constraints for the Sulfur Assessment Metric for ESMs (SAME, the renamed metric).Ā
The supplementary analysis is detailed in the accompanying PDF file. The manuscript will be revised based on this supplementary analysis.
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AC2: 'Reply on RC2', Jie Zhang, 05 Jun 2025
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