Assessing combinations of regional MCB designed to target multiple climate response objectives

Mason, Alex M.; Henry, Matthew; Hirasawa, Haruki; O'Connor, Fiona M.; Haywood, James

doi:10.5194/egusphere-2025-5591

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https://doi.org/10.5194/egusphere-2025-5591

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25 Nov 2025

| 25 Nov 2025

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

Assessing combinations of regional MCB designed to target multiple climate response objectives

Alex M. Mason, Matthew Henry, Haruki Hirasawa, Fiona M. O'Connor, and James Haywood

Abstract. Marine Cloud Brightening (MCB) is a proposed method of Solar Radiation Modification (SRM). MCB proposes the injection of sea salt aerosols into marine clouds to enhance their reflectivity aiming to counteract greenhouse gas (GHG) driven warming. Modelling suggests that the climate effect of MCB depends on the location of deployments, with some regional MCB resulting in potentially undesirable climate changes. MCB in midlatitude regions was found to cause a relatively homogeneous temperature and precipitation change pattern. Here we seek to quantify the trade-offs associated with different MCB strategies and to design an “optimal” deployment strategy. This study analyses 42 MCB patch simulations in UKESM1.0, spanning fourteen different regions and three different injection rates. These simulations are used to inform deployments with the aim to restore the SSP2-4.5 2040s mean climate to a baseline of 2014–2033. Multiple climate targets, consisting of global mean surface air temperature, precipitation, Arctic September sea ice extent, southern oscillation index, and hemispheric mean temperatures, are used to inform the design of an optimised 14-region deployment and a reduced complexity optimised 6-region deployment, which we compare to the aforementioned 5-region midlatitude MCB deployment. Some improvements to the midlatitude MCB deployment are observed, in sea ice restoration and zonal mean temperature response. These results show it may be possible to design MCB strategies that target several climate responses simultaneously when combining regional MCB deployments. The results highlight the importance of including high latitude MCB to achieve Arctic sea ice restoration in UKESM1.0.

Received: 12 Nov 2025 – Discussion started: 25 Nov 2025

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Alex M. Mason, Matthew Henry, Haruki Hirasawa, Fiona M. O'Connor, and James Haywood

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RC1:
'Comment on egusphere-2025-5591', Anonymous Referee #1, 04 Jan 2026 reply
General Comments
This manuscript presents a systematic and carefully constructed framework for designing multi-region MCB deployments based on a large ensemble of regional patch simulations using UKESM1.0. The optimization strategy—sampling and filtering over more than one million possible combinations using multiple climate response targets—is both novel and well motivated, and the comparison with a midlatitude-only deployment provides a useful benchmark within the existing MCB literature.
With revisions that more fully address the methodological limitations and clarify their implications, I believe this work would make a strong and valuable contribution to the literature on MCB deployment design.

Major Comments
The paper’s central conclusions depend strongly on assumptions of linearity, additivity, and ERF-based scaling of coupled climate responses, which are not sufficiently stress-tested in the current analysis. While the optimized deployments are compelling as a proof-of-concept, the manuscript itself documents substantial nonlinearity and diminishing returns in ERF with increasing injection rate. These features raise important questions about the robustness of the scaling framework used to construct the optimized solutions. Equation (2) estimates the response of a MCB combination by scaling the 50 Tg yr^-1 coupled responses using ERF ratios derived from fixed-SST simulations. While this approach is pragmatic, the manuscript does not justify why ERF(50 Tg yr^-1) is used as the sole reference point, despite the availability of ERF estimates at 5 and 10 Tg yr^-1. Although the authors note substantial variability in the coupled responses at 5 and 10 Tg yr^-1, there is also appreciable variability at 50 Tg yr^-1. Moreover, since most optimized combinations allocate only small fractions (5–10 Tg yr^-1) to many regions, ERF(5 Tg yr^-1) or ERF(10 Tg yr^-1) may be more appropriate scaling references. Please consider a sensitivity test in which Eq. (2) is evaluated using ERF(5 Tg yr^-1) or ERF(10 Tg yr^-1) as the reference and discuss how the optimization results might change if the scaling reference were injection-rate dependent.

The manuscript states that an MCB combination strategy should avoid seeding only the Northern Hemisphere in order to minimize southward ITCZ shifts and associated impacts on vulnerable regions such as South Asia and the Sahel. However, the optimization framework does not include an explicit ITCZ metric, nor does it constrain NH and SH precipitation (ΔP) separately as target variables. Is there a specific reason these metrics were not included? Given the strong allocation of MCB patches in the NH in the optimized deployments, it seems important to more directly incorporate hemispheric or ITCZ-related precipitation responses into the optimization targets.

Minor comments
Line 119: According to Henry et al. (2025), sea-salt emissions in September in the NO are approximately twice as large as in other months, due to the seasonal maximum in open-ocean area. Given that the NO region plays a prominent role in the optimized deployments, it would be helpful to describe the seasonal variability more clearly in the main text, rather than only mentioning it briefly.

Line 227: Including a simple figure would improve transparency and help readers better understand the rationale for selecting 50 Tg yr^-1 as the reference deployment magnitude.

Technical corrections
Line 190: It is unclear whether ΔT and ΔP refer to global-mean values. If so, please state this explicitly and ensure that the same convention is applied consistently throughout the manuscript.

Line 211: “With comparison to the ERF responses in Figure 3…”. This appears to refer to Figure 2, which presents the ERF results. Please check and correct the figure numbering if necessary.

Figure 8: For clarity, it would be helpful to note in the caption that the black arrows are arbitrary or conceptual, rather than representing specific quantitative values, as they could otherwise be misleading.

Table 4: The reported value of ΔT for Optim-14 appears to be missing a minus sign. Please check and correct if necessary.

Line 387: For clarity, please consider using a more explicit expression than “NO MCB” such as “MCB in the NO region” to improve readability for non-specialist readers.

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Citation: https://doi.org/10.5194/egusphere-2025-5591-RC1

Alex M. Mason, Matthew Henry, Haruki Hirasawa, Fiona M. O'Connor, and James Haywood

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Short summary

Marine Cloud Brightening (MCB) proposes the spraying of sea salt particles into marine clouds to cool the planet. MCB in midlatitude regions in models gave a relatively even climate response. We use 42 simulations of MCB to target several climate responses. Two optimised combinations are compared to a midlatitude MCB simulation, which improved sea ice restoration and the temperature response pattern, highlighting the importance of high latitude MCB for MCB optimisation in this model.


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