Using  the HadGEM3-GC3.1 climate model, the authors investigate the impacts of reduced shipping SO₂ emissions. They estimate the aerosol effective radiative forcing caused by this reduction to be 0.13 W/m². Ensembles of global coupled simulations from 2020-2049 predict a global mean warming of 0.04 K averaged over this period. The authors suggest that the impact of shipping emission reductions could represent a significant contribution to the rapid global temperature rise observed from 2022 to 2023. While the authors have conducted extensive simulations and applied various methods to reach their conclusions, there are several concerns regarding the numerical design and data analysis.

My major concern is with the methodology used to adjust variations in temperature from the 1850s to the 2020s using differences in global annual temperature between CMIP6 PD and PI. Given the significant internal biases among models, this approach seems unreasonable. I recommend that the authors run additional PI simulations using the HadGEM3-GC3.1 model to estimate PD-PI differences and then compare these values with the CMIP6 datasets.

Following the reviewer’s comment, we have switched to CMIP6 historical ensemble with HADGEM3 GC3.1 (rather than UKESM1), the same model used in this study. Gillet et al. (2021) shows this ensemble produces PI to PD warming close to the middle of the multi-model and observed ranges. Since we used the simulation results for 2013-2015 from this ensemble as the initial conditions for our simulations, the adjustments previously applied to the pre-2020 climate are no longer necessary. Even though this is a small ensemble with only 4 members, by using the long term mean for 1850-1900 as the PI baseline, the uncertainty from internal variability should have been minimised. This change has only a small effect on global warming predictions, although relatively large changes can be seen regionally.

Additionally, there are concerns about several other conclusions, some of which appear misleading:

1.    Aerosol Effective Radiative Forcing: The statement that "the global aerosol effective radiative forcing caused by reduced shipping emissions is estimated to be 0.13 W/m², which is equivalent to about 50% of the positive forcing caused by the global reduction in all anthropogenic aerosols since the late 20th century" is misleading. Reductions in anthropogenic emissions since the late 20th century have contributed to warming primarily due to a decrease in scattering aerosols, and to cooling due to absorbing aerosols like soot. This statement could be misinterpreted to suggest that half of the aerosol warming effect is from shipping reductions alone.

With this statement we did not intend to imply that half of the aerosol warming effect caused by aerosol reductions after the late 20th Century period was from the shipping reductions, but rather that we estimate that the shipping emissions likely caused an additional warming that is equivalent to 50% of the net warming from the historical aerosol reductions after the late 20th Century. We have refined the abstract to make this clearer as follows:

“The global aerosol effective radiative forcing caused by reduced shipping emissions is estimated to be 0.13 W m-2, which is equivalent to an additional ~50% to the net positive forcing resulting from the reduction in all anthropogenic aerosols from the late 20th century to the pre-2020 era.”

2.    Temperature and Precipitation Changes (Figures 4 and 5): The authors discuss changes in temperature and precipitation, but only a few areas show statistical significance. As a result, the discussion about the warming trend lacks robustness.

As the reviewer points out, Figure 4 shows statistically significant warming only in small regions. However, when we take global decadal mean temperatures, we obtain statistically significant differences between the two ensembles in the 2030s and 2040s as indicated by the p-values and the green error bars shown in figure 6. We also found statistically significant temperature differences in several regions and decades in figure 7. We discuss the warming effects mainly based on these figures rather than figures 4 and 5.

3.    Walker Circulation (Figure Analysis): The authors note a reduction in LW at the TOA in the western tropical Pacific Ocean and attribute this to a strengthening of the Walker Circulation. However, they do not discuss changes in SW, pressure gradients, or sea surface temperature, which are necessary to support this claim.

We thank the reviewer for highlighting this. We have updated the manuscript to provide a fuller picture . The patterns in SSTs are strongly correlated with the 1.5m temperature (shown in the manuscript) over the ocean (which is why we have not explicitly shown SSTs separately).  The change in SW radiative flux is dominant in the net radiative balance at the TOA globally and in most regions (see Figure S4, which has been revised following this comment), which is expected given the aerosol driver, but the region around the maritime continent and tropical Pacific are unique in that LW change dominates, as shown in Figure S4.   We wanted to keep the focus on LW in the main manuscript and included additional text as well as plots for SW and net flux changes (top and bottom panels) to Figure S4 to provide this fuller picture in the supplementary information. 

 

4.    Temperature Comparison (2023 vs. 2016): The comparison of global temperatures in 2023 to 2016 is problematic. Although 2016 was a strong El Niño year, it does not necessarily represent the highest global mean temperature in the past decade. Moreover, the conclusion that "the effect of shipping emission reductions (if they have emerged) and the HTHH eruption could explain up to 0.08 K of the 0.17 K warming since 2016" lacks sufficient evidence and requires further clarification.

We appreciate this comment, as it has prompted us to clarify our thinking.  Tackling the first part of this comment first (whether 2023 and 2016 is a reasonable comparison).  We wanted to encapsulate just how large the global temperature increase was in 2023.  We accept the reviewer’s point, that different global temperature records either attribute 2016 or 2020 as the previous warmest year (due to the margins of error).  Different El Nino in 2016 and 2023 also leaves some ambiguity as an indicator of underlying climate change trend (because both El Nino events are unlikely to have represented the same magnitude of enhanced global temperature).  To qualify this sentence in the revised manuscript, we now reference the WMO assessment of 2023 temperatures (see copied and pasted text, below).  This now states the WMO estimates for the two previous record years (2016 and 2020) based on all available global temperature records. This text now qualifies the 2016 to 2023 trend based on the WMO estimate from all reconstructions (recognising that it is not an unambiguous estimate of the underlying warming) and now also includes the Dunstone et al, 2023 estimate of the warming not explained by global warming and ENSO variability (an additional +0.1–0.12°C that is unexplained).    This revised text now reads as follows: 

“What is the role of these SO2 cuts in the exceptional recent warming record? 2023 was recorded as 1.45 ± 0.12K above the pre-industrial era, which smashed the previous record years, 2016 and 2020 at 1.29 ±0.12K and 1.27 ±0.12K, respectively (WMO, 2024).  The emergence of El Nino in 2023 is likely to have contributed but is unlikely to explain the magnitude of the 2023 increase.  Whilst not unambiguous, the 2016 (strong El Niño) to 2023 (emerging El Nino) trend of 0.16°C would represent a considerable acceleration of global warming if this were caused by greenhouse gas driven climate change alone. Dunstone et al, 2024 estimate that there is likely to be an unexplained +0.1–0.12K to the 2023 temperatures, not explained by global warming and ENSO variability.”    

In response to the 2nd part of the reviewer’s comment, we have sought to qualify and clarify the conclusions drawn in this section.  We have done this by first citing Dunstone et al, 2024 who identified both the HTHH eruption and SO2 shipping cuts as potential explanations, where we first introduce this in the paragraph.  We have expanded the discussion to provide a more nuanced discussion – that now (a) identifies the 0.1 to 0.12K of unexplained warming in 2024 (Dunstone et al, 2024), (b) notes that if HTHH was on the upper end of the published estimates and if warming from shipping cuts has already emerged they might combine to explain 0.08k of this unexplained warming and (c) it is possible that neither of these factors may be playing a role in this unexplained warming.  The text now reads:

“could be a potential factor that may have influenced the warm 2023 temperatures.  Our 0.04K estimate of additional warming from SO2 shipping cuts provides a quantitative estimate that goes beyond Dunstone et al, 2024.   If the contribution of the HTHH is on the upper end of published estimates and if the warming effect of SO2 shipping cuts have emerged, then they could potentially combine to explain up to 0.08K of the 0.1k to 0.12K of unexplained 2023 warming identified in Dunstone et al, 2024.  The difference between the two contributors is that we would expect any warming from the HTHH eruption to rapidly decay (the e-folding timescale of volcanic global temperature impact is roughly 2.5 years) whereas the additional warming from SO2 shipping cuts is expected to persist. However, if the HTHH temperature contribution was more modest (or even negative) and/or warming from SO2 shipping cuts have not emerged then we need to look for other potential explanations (perhaps indicating a marked acceleration of global warming). Given the large unexplained warming in 2023, it is important that we do not dismiss SO2 cuts as a potential explanatory factor, given credible evidence from the experiments presented here, that such cuts are capable of affecting the global temperature record”