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the Creative Commons Attribution 4.0 License.
| 17 Jul 2023
Climate Intervention using marine cloud brightening (MCB) compared with stratospheric aerosol injection (SAI) in the UKESM1 climate model
James Matthew Haywood
Andy Jones
Anthony Crawford Jones
Philip J. Rasch
Abstract. The difficulties in using conventional mitigation techniques to maintain global mean temperatures well below 2 °C compared with preindustrial levels have been well documented, leading to so-called ‘climate intervention’ or ‘geoengineering’ research whereby the planetary albedo is increased to counterbalance global warming and ameliorate some impacts of climate change. In the scientific literature, the most prominent climate intervention proposal is that of stratospheric aerosol injection (SAI), although proposals for marine cloud brightening (MCB) have also received considerable attention. In this study, we design a new MCB experiment (G6MCB) for the UKESM1 Earth system model which follows the same baseline and cooling scenarios as the well-documented G6sulfur SAI scenario developed by the Geoengineering Model Intercomparison Project (GeoMIP) and compare the results from G6MCB with those from G6sulfur. The deployment strategy used in G6MCB injects sea-salt aerosol into four cloudy areas of the eastern Pacific. Despite MCB being intended as a technique to modify clouds, much of the radiative effect in G6MCB is found to derive from the direct interaction of the injected sea-salt aerosols with solar radiation. The results show that while G6MCB can achieve its target in terms of reducing high-end global warming to moderate levels, there are several side-effects. Some are common to SAI, including overcooling of the tropics, and residual warming of mid-and high latitudes. Others side effects specific to common choices of MCB regions include changes in monsoon precipitation, year-round increases in precipitation over Australia and the maritime continent and increased sea-level rise around western Australia and the maritime continent; these results are all consistent with a permanent and very strong La Niña-like response being induced in G6MCB. It should be stressed that the results are extremely dependent upon the strategy chosen for MCB deployment. As demonstrated by the development of SAI strategies which can achieve multiple temperature targets and ameliorate some of the residual impacts of climate change, much further work is required in multiple models to obtain a robust understanding of the practical scope, limitations, perils and pitfalls of any proposed MCB deployment.
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James Matthew Haywood et al.
Status: closed
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RC1: 'Comment on egusphere-2023-1611', Michael Diamond, 07 Aug 2023
In this manuscript, the authors devise a new “G6MCB” experiment that parallels the GeoMIP-endorsed G6sulfur experiment but uses sea salt emissions in four regions of the Pacific rather than sulfur emissions in the tropical stratosphere to achieve a reduction in global mean surface temperatures to that of the SSP2-4.5 scenario from a background of SSP5-8.5. For lower levels of spraying with accumulation-mode particles, cloud brightening and the direct effect both produce a substantial cooling effect; at higher levels, cloud forcing saturates and even reverses with all of the cooling coming from the direct effect. The La Niña-like pattern induced by G6MCB produces marked differences in climate response from the warming and SAI scenarios to which it is compared. Perhaps the most striking result is that sea levels over the vulnerable western Pacific basin rise more in G6MCB than in ssp585 due to the La Niña-like dynamic adjustment to eastern Pacific cooling. The paper is well-written and executed and makes an interesting and important contribution to the literature surrounding MCB and SRM more broadly — it merits prompt publication following minor revisions (see specific points below). -Michael Diamond
General point: At low-ish forcings (~1 W m-2), MCB dominates over MSB. The MSB findings may well be a result of pushing the system further than MCB can go. One conclusion may be that MCB is more feasible for a smaller scenario (e.g., sustaining historical peak aerosol cooling) but is infeasible for a more ambitious scenario (multiple degrees of cooling). It may be worth considering this point more explicitly in the discussion.
Specific points:1. Why is the experiment named “G6MCB” instead of “G6sea-salt”, which would be more parallel with the G4 naming system? I appreciate that this experiment is not officially within the GeoMIP umbrella, but it still seems like highlighting the sea-salt aspect may be more appropriate, especially as MSB dominates forcing by the end of the century.
2. Lines 16-18: This is true at high emissions rates; at lower emissions rates and with smaller particles the cloud effect dominated. This is probably worth clarifying, as the “lower” emission rates still produce forcings that may be policy relevant (e.g., targeting 1 W m-2 of cooling to maintain peak 20th century aerosol forcing).
3. Section 3.1: It may be useful to mention or highlight the likely dependence on activation scheme here. This issue is dealt with nicely in the discussion, so perhaps you could just add an allusion to further information about the activation scheme question that will come later.
4. Figure 3 caption: I don’t understand the caveat about points that don’t meet G6 standards. Could you clarify here or in the text?
5. Figure 4: Could you also plot the net forcing difference and perhaps the zero line? It’s easy enough to eyeball but still could be useful for readers.
6. Line 274: I agree with this point and it’s important to make, but perhaps it should more specifically refer to generalizability when comparing MCB/MSB strategies with substantially different spatial patterns of forcing. The current (on-going) intercomparison seems to suggest that results are more generalizable when using a standardized protocol.
7. La Niña section: A useful figure would be a comparison of G6MCB-SSP585 and the La Niña signal in UKESM1 from interannual variability (e.g., regression on detrended SOI or using some detrended Niño3.4-like index) in terms of variables like temperature, precipitation, sea level pressure, and perhaps circulation anomalies like surface winds.
8. Figure 15a: Put definition of the thin lines (two sigma?) in the figure caption.
9. Lines 371-372: But isn’t mean warming believed to be El Niño-like?
10. Line 377: Is “locking into La Niña” the right description? I’m interpreting the results here as showing a strong mean-state climate change pattern resembling La Niña, but in terms of interannual variability, do the frequency or intensity of El Niño and La Niña events change after adjusting for the changing mean state temperature/pressure?
11. Lines 399-401: This makes sense, but given the inertia in the climate system, I’m not convinced it’s correct. See, e.g., the results in MacMartin et al. (2022) that find a 10-year phase-out doesn’t really differ from sudden termination in CESM2-WACCM.
MacMartin, D. G., Visioni, D., Kravitz, B., Richter, J. H., Felgenhauer, T., Lee, W. R., Morrow, D. R., Parson, E. A., and Sugiyama, M.: Scenarios for modeling solar radiation modification, Proc Natl Acad Sci U S A, 119, e2202230119, 10.1073/pnas.2202230119, 2022.
12. Data availability: I believe that the G6MCB data, minimally that needed to recreate the figures in the paper, need to be posted publicly to a data repository before publication, or “a detailed explanation of why” it is not available must be provided, to be compliant with the stated ACP data policy (https://www.atmospheric-chemistry-and-physics.net/policies/data_policy.html).
Citation: https://doi.org/10.5194/egusphere-2023-1611-RC1 -
RC2: 'Comment on egusphere-2023-1611', Anonymous Referee #2, 24 Aug 2023
Review of “Climate Intervention using marine cloud brightening (MCB) compared with stratospheric aerosol injection (SAI) in the UKESM1 climate model”
Jim Haywood et al., 2023
With the aim of advancing the understanding of climate intervention and assessing climate mitigation techniques, this study performs a set of simulations in the UKESM1 climate model, using sea salt aerosol injection (Marine Cloud Brightening, G6MCB) as compared to stratospheric aerosol injection (SAI, G6sulfur), to reduce global mean temperatures from SSP5-8.5 scenario to SSP2-4.5. The deployment strategy used in G6MCB injects sea-salt aerosol into four cloudy areas of the eastern Pacific. The authors find that much of the radiative effect in G6MCB is derived from the direct interaction of the injected sea-salt aerosols with solar radiation, rather than from aerosol-cloud interaction. The authors discuss the potential side effects of SAI and MCB, including overcooling of the tropics and residual warming of mid- and high latitudes, which are common for both SAI and MCB, and other side effects such as a strong La Nina like condition, that might depend on the choices of MCB emission scenario and the deployment strategy. I find this study very interesting and inspiring, and I believe it would certainly motivate future studies to better understand the complexity of MCB strategies and impact. I recommend acceptance but I do have some comments that I suggest the authors take into consideration.
Main comments:
- The authors recognize that the results from their G6MCB maybe an artifact of the model configuration (e.g., the choice of aerosol activation parameterization) that incorrectly represent water vapor competition at very high concentrations of small particles. This is a direct microphysical issue. Another potential issue would be related to the interaction between dynamics and microphysics in the model. E.g., how does the turbulence couple with microphysics in UKESM1? How would the cloud top entrainment change with cloud droplet size in UKESM1? Some discussion in this regard would be helpful.
- The authors show some interesting side effects of MCB experiment including cooler tropics and warmer polar regions, and other regional changes in temperature and precipitation, yet the authors provide no physical explanation/hypothesis regarding the potential mechanisms. It would potentially be more compelling if the authors could connect MCB with large scale circulation change.
- Are the areas of injection regions identical in both hemispheres? Does the quantity of injected aerosols exhibit hemispherical symmetry? Or are there actually more injected aerosols in one hemisphere? The authors talk about potential asymmetry in near-surface air temperature in Fig. 7. They claim the asymmetry might depend on the deployment strategy. I wonder if the authors can make a similar plot for albedo. I wonder how the results are related to the idea of all-sky albedo symmetry where the cloud adjustment would potentially balance the aerosol hemispheric asymmetry.
Specific comments:
- More description of model setup is needed.
The results in Fig. 2 are from 10-year simulations which differ from the other 80-year simulations in the manuscript, but this distinction is not clarified until Section 3. I think all the descriptions of model setup should go to Section 2. To enhance clarity, it would be beneficial if the authors could make a table summarizing the simulation design used in this study. This table could include information such as initial conditions, total simulation time (including spin-up), and the specific time frame used for analysis. The current description appears too simple. E.g., there is no specification as to when the 15-year simulation starts. Could the authors elaborate on their rationale for selecting a 15-year duration, rather than a longer one? I am curious about the potential sensitivity of the results to the start time and duration of the simulations.
- Lines 153-155: The description should go to Section 2.
- Line 159: Is natural sea-salt emission included in the baseline experiment (ssp245)?
- Lines 163-164: What is the typical particle size for G6sulfur? What is the typical aerosol lifetime near the surface and in the stratosphere? More information is needed here.
- Line 170-174: Could the authors explain why temperature respond linearly to aerosol injection over a limited range, but non-linearly over a wider range?
- Line 203: Could the authors elaborate on the dynamical feedbacks that lead to positive CRE_SW?
- Line 229-235: Could the authors explain why G6MCB also leads to cooler tropics and warmer polar regions?
- Line 237-257: Could the authors provide a physical explanation/hypothesis for the disparity observed between G6MCB and G6sulfur, as shown in Figs. 9 and 10?
- Line 259: Please define net primary productivity.
Citation: https://doi.org/10.5194/egusphere-2023-1611-RC2 -
RC3: 'Comment on egusphere-2023-1611', Anonymous Referee #3, 25 Aug 2023
General comments
The manuscript outlines the results from a pair of geoengineering experiments performed using the UKESM1 model. I find that the subject matter to be appropriate for the ACP journal and the results are scientifically interesting. Overall, the results are well documented, and appropriate connections with existing literature are made. However, I find that the following two areas can benefit from a better interpretation or more analysis.
First, the authors appear to suggest in the discussions and conclusions section that the shift from cooling to warming aerosol indirect effect response is due to a strong competition of water vapor by a very large increase in aerosols. However, Figure 5 shows that the large positive response do not occur where the aerosols are injected but in other regions. A clarification of what is behind the positive cloudy-sky effect in Fig 5b is needed. If the authors want to make the case that the positive response is indeed due to a decrease in relative humidity due to water competition, more evidence is necessary.
Second, I found the interpretation that the precipitation and sea-level rise pattern changes are connected to a La Nina-like SST pattern to be quite interesting and compelling. However, this connection was only mentioned in the discussions and lacked the analysis of the other sections. Assuming that the UKESM1 model produces El Nino and La Nina events, I find that an even stronger case can be made if the authors showed the precipitation and sea-level difference patterns composited on La Nina patterns. Given the asymmetric nature of the forcing induced by the MCB strategy, then one might then infer that these precipitation pattern changes would likely be robust across different models.
Specific comments
L159: I assume this is 10% of the global estimate of natural sea-salt emission rate. It would be useful to know what fraction of the ocean is covered by these injection sites – although it might be 10% of the global mean, it might be doubling (or more) the sea-salt mass emissions in these regions.
Figure 5: It would be helpful to see the map of the mean-state shortwave cloud radiative effect in the baseline (maybe the ssp245) to see where the cloud changes are occurring relative to the stratocumulus cloud decks and how large their changes are relative to the background cloud radiative effect.
L202: I am guessing this increase in the cloudy-sky effect is due to remote impacts due to atmospheric dynamics response or more La Nina like conditions with the sea salt injection. If this is the case, this point should be made clearer in the conclusions. At least, it should be noted in the conclusions that the positive cloud radiative effect response is occurring away from the sea-salt injection sites
L204-206: Are the locations of the more positive cloudy sky effect consistent across the simulations? It is suggested that cloud droplet activation scheme might be a reason for the cloud response, but seeing that the positive CRE_SW occurs in the Tropical West Pacific and South Pacific Convergence Zone, away from the injection sites, it seems that the change in SST patterns might be playing a role here.
Figure 6: As in Figure 5, having a map of the PD AOD will help see how the changes in AOD compare with the background.
L315-322: This interpretation and discussion of the negative aerosol indirect effect is misleading, since the forcing change (from negative to positive) does not occur over the region of injection, but on the other side of the Pacific Ocean basin. Instead of an aerosol indirect effect saturation or a swap of signs, it seems that this change in global ACI response is due to a change in the SST pattern that occurs from strongly cooling the Eastern Pacific, relative to the Western Pacific.
L348-353: It is suggested that the La Nina-like conditions that set up in the model are the reason for the changes in the precipitation and sea-level rise response. If that is the case, we should be able to see these patterns show up if the La Nina cases in the model are composited from the UKESM1 model. Such a pattern will lend more support for this argument and also distinguish how much of the precipitation pattern and cloud changes are due to indirect SST influences or direct aerosol increases.
Technical corrections
Figure 15: What do the thin lines represent? Please indicate in the captions.
Citation: https://doi.org/10.5194/egusphere-2023-1611-RC3 -
AC1: 'Comment on egusphere-2023-1611', J.M. Haywood, 06 Oct 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-1611/egusphere-2023-1611-AC1-supplement.pdf
Status: closed
-
RC1: 'Comment on egusphere-2023-1611', Michael Diamond, 07 Aug 2023
In this manuscript, the authors devise a new “G6MCB” experiment that parallels the GeoMIP-endorsed G6sulfur experiment but uses sea salt emissions in four regions of the Pacific rather than sulfur emissions in the tropical stratosphere to achieve a reduction in global mean surface temperatures to that of the SSP2-4.5 scenario from a background of SSP5-8.5. For lower levels of spraying with accumulation-mode particles, cloud brightening and the direct effect both produce a substantial cooling effect; at higher levels, cloud forcing saturates and even reverses with all of the cooling coming from the direct effect. The La Niña-like pattern induced by G6MCB produces marked differences in climate response from the warming and SAI scenarios to which it is compared. Perhaps the most striking result is that sea levels over the vulnerable western Pacific basin rise more in G6MCB than in ssp585 due to the La Niña-like dynamic adjustment to eastern Pacific cooling. The paper is well-written and executed and makes an interesting and important contribution to the literature surrounding MCB and SRM more broadly — it merits prompt publication following minor revisions (see specific points below). -Michael Diamond
General point: At low-ish forcings (~1 W m-2), MCB dominates over MSB. The MSB findings may well be a result of pushing the system further than MCB can go. One conclusion may be that MCB is more feasible for a smaller scenario (e.g., sustaining historical peak aerosol cooling) but is infeasible for a more ambitious scenario (multiple degrees of cooling). It may be worth considering this point more explicitly in the discussion.
Specific points:1. Why is the experiment named “G6MCB” instead of “G6sea-salt”, which would be more parallel with the G4 naming system? I appreciate that this experiment is not officially within the GeoMIP umbrella, but it still seems like highlighting the sea-salt aspect may be more appropriate, especially as MSB dominates forcing by the end of the century.
2. Lines 16-18: This is true at high emissions rates; at lower emissions rates and with smaller particles the cloud effect dominated. This is probably worth clarifying, as the “lower” emission rates still produce forcings that may be policy relevant (e.g., targeting 1 W m-2 of cooling to maintain peak 20th century aerosol forcing).
3. Section 3.1: It may be useful to mention or highlight the likely dependence on activation scheme here. This issue is dealt with nicely in the discussion, so perhaps you could just add an allusion to further information about the activation scheme question that will come later.
4. Figure 3 caption: I don’t understand the caveat about points that don’t meet G6 standards. Could you clarify here or in the text?
5. Figure 4: Could you also plot the net forcing difference and perhaps the zero line? It’s easy enough to eyeball but still could be useful for readers.
6. Line 274: I agree with this point and it’s important to make, but perhaps it should more specifically refer to generalizability when comparing MCB/MSB strategies with substantially different spatial patterns of forcing. The current (on-going) intercomparison seems to suggest that results are more generalizable when using a standardized protocol.
7. La Niña section: A useful figure would be a comparison of G6MCB-SSP585 and the La Niña signal in UKESM1 from interannual variability (e.g., regression on detrended SOI or using some detrended Niño3.4-like index) in terms of variables like temperature, precipitation, sea level pressure, and perhaps circulation anomalies like surface winds.
8. Figure 15a: Put definition of the thin lines (two sigma?) in the figure caption.
9. Lines 371-372: But isn’t mean warming believed to be El Niño-like?
10. Line 377: Is “locking into La Niña” the right description? I’m interpreting the results here as showing a strong mean-state climate change pattern resembling La Niña, but in terms of interannual variability, do the frequency or intensity of El Niño and La Niña events change after adjusting for the changing mean state temperature/pressure?
11. Lines 399-401: This makes sense, but given the inertia in the climate system, I’m not convinced it’s correct. See, e.g., the results in MacMartin et al. (2022) that find a 10-year phase-out doesn’t really differ from sudden termination in CESM2-WACCM.
MacMartin, D. G., Visioni, D., Kravitz, B., Richter, J. H., Felgenhauer, T., Lee, W. R., Morrow, D. R., Parson, E. A., and Sugiyama, M.: Scenarios for modeling solar radiation modification, Proc Natl Acad Sci U S A, 119, e2202230119, 10.1073/pnas.2202230119, 2022.
12. Data availability: I believe that the G6MCB data, minimally that needed to recreate the figures in the paper, need to be posted publicly to a data repository before publication, or “a detailed explanation of why” it is not available must be provided, to be compliant with the stated ACP data policy (https://www.atmospheric-chemistry-and-physics.net/policies/data_policy.html).
Citation: https://doi.org/10.5194/egusphere-2023-1611-RC1 -
RC2: 'Comment on egusphere-2023-1611', Anonymous Referee #2, 24 Aug 2023
Review of “Climate Intervention using marine cloud brightening (MCB) compared with stratospheric aerosol injection (SAI) in the UKESM1 climate model”
Jim Haywood et al., 2023
With the aim of advancing the understanding of climate intervention and assessing climate mitigation techniques, this study performs a set of simulations in the UKESM1 climate model, using sea salt aerosol injection (Marine Cloud Brightening, G6MCB) as compared to stratospheric aerosol injection (SAI, G6sulfur), to reduce global mean temperatures from SSP5-8.5 scenario to SSP2-4.5. The deployment strategy used in G6MCB injects sea-salt aerosol into four cloudy areas of the eastern Pacific. The authors find that much of the radiative effect in G6MCB is derived from the direct interaction of the injected sea-salt aerosols with solar radiation, rather than from aerosol-cloud interaction. The authors discuss the potential side effects of SAI and MCB, including overcooling of the tropics and residual warming of mid- and high latitudes, which are common for both SAI and MCB, and other side effects such as a strong La Nina like condition, that might depend on the choices of MCB emission scenario and the deployment strategy. I find this study very interesting and inspiring, and I believe it would certainly motivate future studies to better understand the complexity of MCB strategies and impact. I recommend acceptance but I do have some comments that I suggest the authors take into consideration.
Main comments:
- The authors recognize that the results from their G6MCB maybe an artifact of the model configuration (e.g., the choice of aerosol activation parameterization) that incorrectly represent water vapor competition at very high concentrations of small particles. This is a direct microphysical issue. Another potential issue would be related to the interaction between dynamics and microphysics in the model. E.g., how does the turbulence couple with microphysics in UKESM1? How would the cloud top entrainment change with cloud droplet size in UKESM1? Some discussion in this regard would be helpful.
- The authors show some interesting side effects of MCB experiment including cooler tropics and warmer polar regions, and other regional changes in temperature and precipitation, yet the authors provide no physical explanation/hypothesis regarding the potential mechanisms. It would potentially be more compelling if the authors could connect MCB with large scale circulation change.
- Are the areas of injection regions identical in both hemispheres? Does the quantity of injected aerosols exhibit hemispherical symmetry? Or are there actually more injected aerosols in one hemisphere? The authors talk about potential asymmetry in near-surface air temperature in Fig. 7. They claim the asymmetry might depend on the deployment strategy. I wonder if the authors can make a similar plot for albedo. I wonder how the results are related to the idea of all-sky albedo symmetry where the cloud adjustment would potentially balance the aerosol hemispheric asymmetry.
Specific comments:
- More description of model setup is needed.
The results in Fig. 2 are from 10-year simulations which differ from the other 80-year simulations in the manuscript, but this distinction is not clarified until Section 3. I think all the descriptions of model setup should go to Section 2. To enhance clarity, it would be beneficial if the authors could make a table summarizing the simulation design used in this study. This table could include information such as initial conditions, total simulation time (including spin-up), and the specific time frame used for analysis. The current description appears too simple. E.g., there is no specification as to when the 15-year simulation starts. Could the authors elaborate on their rationale for selecting a 15-year duration, rather than a longer one? I am curious about the potential sensitivity of the results to the start time and duration of the simulations.
- Lines 153-155: The description should go to Section 2.
- Line 159: Is natural sea-salt emission included in the baseline experiment (ssp245)?
- Lines 163-164: What is the typical particle size for G6sulfur? What is the typical aerosol lifetime near the surface and in the stratosphere? More information is needed here.
- Line 170-174: Could the authors explain why temperature respond linearly to aerosol injection over a limited range, but non-linearly over a wider range?
- Line 203: Could the authors elaborate on the dynamical feedbacks that lead to positive CRE_SW?
- Line 229-235: Could the authors explain why G6MCB also leads to cooler tropics and warmer polar regions?
- Line 237-257: Could the authors provide a physical explanation/hypothesis for the disparity observed between G6MCB and G6sulfur, as shown in Figs. 9 and 10?
- Line 259: Please define net primary productivity.
Citation: https://doi.org/10.5194/egusphere-2023-1611-RC2 -
RC3: 'Comment on egusphere-2023-1611', Anonymous Referee #3, 25 Aug 2023
General comments
The manuscript outlines the results from a pair of geoengineering experiments performed using the UKESM1 model. I find that the subject matter to be appropriate for the ACP journal and the results are scientifically interesting. Overall, the results are well documented, and appropriate connections with existing literature are made. However, I find that the following two areas can benefit from a better interpretation or more analysis.
First, the authors appear to suggest in the discussions and conclusions section that the shift from cooling to warming aerosol indirect effect response is due to a strong competition of water vapor by a very large increase in aerosols. However, Figure 5 shows that the large positive response do not occur where the aerosols are injected but in other regions. A clarification of what is behind the positive cloudy-sky effect in Fig 5b is needed. If the authors want to make the case that the positive response is indeed due to a decrease in relative humidity due to water competition, more evidence is necessary.
Second, I found the interpretation that the precipitation and sea-level rise pattern changes are connected to a La Nina-like SST pattern to be quite interesting and compelling. However, this connection was only mentioned in the discussions and lacked the analysis of the other sections. Assuming that the UKESM1 model produces El Nino and La Nina events, I find that an even stronger case can be made if the authors showed the precipitation and sea-level difference patterns composited on La Nina patterns. Given the asymmetric nature of the forcing induced by the MCB strategy, then one might then infer that these precipitation pattern changes would likely be robust across different models.
Specific comments
L159: I assume this is 10% of the global estimate of natural sea-salt emission rate. It would be useful to know what fraction of the ocean is covered by these injection sites – although it might be 10% of the global mean, it might be doubling (or more) the sea-salt mass emissions in these regions.
Figure 5: It would be helpful to see the map of the mean-state shortwave cloud radiative effect in the baseline (maybe the ssp245) to see where the cloud changes are occurring relative to the stratocumulus cloud decks and how large their changes are relative to the background cloud radiative effect.
L202: I am guessing this increase in the cloudy-sky effect is due to remote impacts due to atmospheric dynamics response or more La Nina like conditions with the sea salt injection. If this is the case, this point should be made clearer in the conclusions. At least, it should be noted in the conclusions that the positive cloud radiative effect response is occurring away from the sea-salt injection sites
L204-206: Are the locations of the more positive cloudy sky effect consistent across the simulations? It is suggested that cloud droplet activation scheme might be a reason for the cloud response, but seeing that the positive CRE_SW occurs in the Tropical West Pacific and South Pacific Convergence Zone, away from the injection sites, it seems that the change in SST patterns might be playing a role here.
Figure 6: As in Figure 5, having a map of the PD AOD will help see how the changes in AOD compare with the background.
L315-322: This interpretation and discussion of the negative aerosol indirect effect is misleading, since the forcing change (from negative to positive) does not occur over the region of injection, but on the other side of the Pacific Ocean basin. Instead of an aerosol indirect effect saturation or a swap of signs, it seems that this change in global ACI response is due to a change in the SST pattern that occurs from strongly cooling the Eastern Pacific, relative to the Western Pacific.
L348-353: It is suggested that the La Nina-like conditions that set up in the model are the reason for the changes in the precipitation and sea-level rise response. If that is the case, we should be able to see these patterns show up if the La Nina cases in the model are composited from the UKESM1 model. Such a pattern will lend more support for this argument and also distinguish how much of the precipitation pattern and cloud changes are due to indirect SST influences or direct aerosol increases.
Technical corrections
Figure 15: What do the thin lines represent? Please indicate in the captions.
Citation: https://doi.org/10.5194/egusphere-2023-1611-RC3 -
AC1: 'Comment on egusphere-2023-1611', J.M. Haywood, 06 Oct 2023
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2023/egusphere-2023-1611/egusphere-2023-1611-AC1-supplement.pdf
James Matthew Haywood et al.
James Matthew Haywood et al.
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