the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 07 Apr 2025
Dust radiative forcing in CMIP6 Earth System models: insights from the AerChemMIP piClim-2xdust experiment
Abstract. Mineral dust affects significantly the downwelling and upwelling shortwave (SW) and longwave (LW) radiative fluxes and changes in dust can therefore alter the Earth’s energy balance. This study analyses the dust effective radiative forcing (DuERF) in nine CMIP6 Earth System Models (ESMs) using the piClim-2xdust experiment from AerChemMIP. The piClim-2xdust experiment uses a global dust emission tuning factor to double the emission flux. The DuERF is decomposed into contributions from dust-radiation (direct DuERF) and dust-cloud (cloud DuERF) interactions. The net direct DuERF ranges from −0.56 to 0.05 Wm−2. Models with lower (higher) dust absorption and smaller (larger) fraction of coarse dust show the most negative (positive) direct DuERF. The cloud DuERF is positive in most models, ranging from −0.02 to 0.2 W m−2, however, they differ in their LW and SW flux contribution. Specifically NorESM2-LM shows a positive LW cloud DuERF attributable to the effect of dust on cirrus clouds. The dust forcing efficiency varies tenfold among models, indicating that uncertainty in DuERF is likely underestimated in AerChemMIP. There is a consistent fast precipitation response associated with dust decreasing the atmospheric radiative cooling (ARC). Models with strongly absorbing dust show reduced precipitation, explainable by decreased clear-sky ARC (up to 3.2 mm/year). In NorESM2-LM the decrease is correlated with the cloudy sky ARC due to increase in cirrus clouds (up to 5.6 mm/year). Together, this suggests that the fast precipitation response induced by dust is significant, comparable to that of anthropogenic black carbon.
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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Journal article(s) based on this preprint
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2025-1030', Anonymous Referee #1, 22 May 2025
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2025-1030/egusphere-2025-1030-RC1-supplement.pdfCitation: https://doi.org/
10.5194/egusphere-2025-1030-RC1 -
AC1: 'Reply on RC1', Ove Haugvaldstad, 11 Jul 2025
We thank the reviewer for the insightful comments and suggestions. The reviewer’s comments have meaningfully contributed to elevate the quality of the manuscript. Here, we are attaching the point-by-point response along with details about implemented modifications. Please kindly find the attachment.
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AC1: 'Reply on RC1', Ove Haugvaldstad, 11 Jul 2025
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RC2: 'Comment on egusphere-2025-1030', Anonymous Referee #2, 29 May 2025
The manuscript presents a comprehensive analysis of dust effective radiative forcing (DuERF) using CMIP6 ESMs under the AerChemMIP piClim-2xdust experiment, contrasted with the piClim-control run. The study decomposes DuERF into direct and indirect components, evaluates model uncertainties, and quantifies the impact of dust perturbations on precipitation. While the manuscript is well-structured and provides valuable insights, several key issues need addressing to improve clarity, interpretability, and robustness. Below, I outline major revisions the authors may want to consider to ensure the study meets its full potential.
General comments
1. The introduction is quite lengthy and detailed, and it gives me the impression that the authors aim to constrain the uncertainty in dust forcing estimates by addressing the factors that contribute to this uncertainty. However, this is not the primary goal of their study which I did not realize until the last several sentences of the introduction section. To better align with the study’s goals the introduction could be streamlined by shortening the discussion of factors contributing to uncertainty and focusing more on how those factors are represented in ESMs and how they influence the DuERF.
2. The study analyzes DuERF using the idealized piClim-2xdust experiment, which perturbs dust emissions under preindustrial conditions. While the emission increase (70-105%) is comparable to or larger than estimated historical changes (Kok et al., 2023), the experimental design, fixed SSTs and no anthropogenic forcing, means the results reflect model-specific dust responses rather than real-world historical forcing. The authors should clarify that these findings cannot be directly compared to studies quantifying DuERF over the industrial era, as the mechanisms and climate feedback differ. This distinction is critical to avoid misinterpretation of the DuERF values presented.
3. The authors need to explicitly state whether the ESMs account for LW aerosol scattering, if any, both in the model physics and in the reported LW and NET (SW+LW) forcing estimates. Omitting LW scattering likely biases the NET DuERF, as it can contribute 50% (20-60%) of the dust LW direct radiative effect at the TOA (Dufresne et al., 2002). If LW scattering is not included, please consider estimating the potential bias in the LW and NET DuERF and, if possible, adding this information to the LW and NET forcing estimates.
Also, while the manuscript notes weak LW direct forcing efficiencies (Figure 2b), it does not clarify whether this is due to missing physics (e.g., neglect of LW aerosol scattering, not only for coarse and super-coarse dust particles, although this is likely the major source), deficiencies in the size distribution (e.g., underrepresentation of super-coarse dust), or a combined effect of the two. I request clarification on these aspects.
4. The outlier behavior of NorESM2-LM is attributed to a known bug (line 400) that largely disables heterogeneous ice nucleation in mixed-phase clouds (lines 171-172). However, it is unclear how the authors handle the indirect forcing results from this model, particularly in relation to the indirect forcing. Was this model excluded from the analysis or given reduced weight in the ensemble mean? The authors should either quantify the impact of this bug on the results or provide a clear justification for including the model and explain how its known bias was accounted for.
5. The manuscript provides a good analysis of dust-cloud interactions and precipitation responses. However, the model descriptions in Table 1, and, in fact, throughout the manuscript, lack critical details about how cloud microphysics and precipitation processes are represented in each ESM. Only limited information is scattered throughout the text. Given that these processes are central to the study’s conclusions, particularly regarding dust indirect forcings and hydrological cycle impacts, a more comprehensive summary of model physics would significantly strengthen the interpretation of results.
6. The manuscript would benefit from greater consistency in its use of aerosol optical metrics to characterize dust impacts. While the study appropriately focuses on dust radiative forcing, there appears to be an inconsistent application of optical depth metrics throughout the analysis. At times, the authors examine total aerosol optical depth (AOD) and absorption aerosol optical depth (AAOD), while at other points they reference dust optical depth (DOD). Unless I missed it, the authors did not provide dust absorption optical depth (DAOD). It is also possible that the authors are using AAOD to refer to what is defined here as DAOD. However, this should be clarified to avoid confusion.
This variation in metrics could potentially lead to confusion when interpreting results, as total AOD/AAOD incorporates contributions from all aerosol species, not just dust. Given that the study specifically investigates dust impacts through the piClim-2xdust experiment, the consistent use of dust-specific metrics (DOD and DAOD) would provide a more direct and unambiguous estimate of dust aerosol effects.
7. The references are not properly cited. I have pointed this out in a few places, but I encourage the authors to check for similar issues elsewhere in the manuscript.
I notice that the authors super frequently cite some frequences, which are undoubtedly very valuable contributions to the research community. However, it is important to also acknowledge and appropriately credit the original studies that underpin key findings.
Minor comments
Line 35-36: What does this "environment changes" specifically refer to?
Line 51-52: This statement is not strictly accurate. Several ESMs are capable of representing dust aerosols as distinct mineral components. A few examples are provided below, although the list is not exhaustive and continues to grow as model development advances.
This list here (and after) is provided for my convenience, as the items are more readily available to me than the others. The authors should feel entirely free to cite any of them or any other sources they find relevant:)
Gómez Maqueo Anaya, S., Althausen, D., Faust, M., Baars, H., Heinold, B., Hofer, J., Tegen, I., Ansmann, A., Engelmann, R., Skupin, A., Heese, B., and Schepanski, K.: The implementation of dust mineralogy in COSMO5.05-MUSCAT, Geosci. Model Dev., 17, 1271–1295, https://doi.org/10.5194/gmd-17-1271-2024, 2024.
Li, L., Mahowald, N. M., Miller, R. L., Pérez García-Pando, C., Klose, M., Hamilton, D. S., Gonçalves Ageitos, M., Ginoux, P., Balkanski, Y., Green, R. O., Kalashnikova, O., Kok, J. F., Obiso, V., Paynter, D., and Thompson, D. R.: Quantifying the range of the dust direct radiative effect due to source mineralogy uncertainty, Atmos. Chem. Phys., 21, 3973–4005, https://doi.org/10.5194/acp-21-3973-2021, 2021.
Gonçalves Ageitos, M., Obiso, V., Miller, R. L., Jorba, O., Klose, M., Dawson, M., Balkanski, Y., Perlwitz, J., Basart, S., Di Tomaso, E., Escribano, J., Macchia, F., Montané, G., Mahowald, N. M., Green, R. O., Thompson, D. R., and Pérez García-Pando, C.: Modeling dust mineralogical composition: sensitivity to soil mineralogy atlases and their expected climate impacts, Atmos. Chem. Phys., 23, 8623–8657, https://doi.org/10.5194/acp-23-8623-2023, 2023.
Li, L., Mahowald, N. M., Kok, J. F., Liu, X., Wu, M., Leung, D. M., Hamilton, D. S., Emmons, L. K., Huang, Y., Sexton, N., Meng, J., and Wan, J.: Importance of different parameterization changes for the updated dust cycle modeling in the Community Atmosphere Model (version 6.1), Geosci. Model Dev., 15, 8181–8219, https://doi.org/10.5194/gmd-15-8181-2022, 2022.
Perlwitz, J. P., Pérez García-Pando, C., and Miller, R. L.: Predicting the mineral composition of dust aerosols – Part 1: Representing key processes, Atmos. Chem. Phys., 15, 11593–11627, https://doi.org/10.5194/acp-15-11593-2015, 2015.
Scanza, R. A., Mahowald, N., Ghan, S., Zender, C. S., Kok, J. F., Liu, X., Zhang, Y., and Albani, S.: Modeling dust as component minerals in the Community Atmosphere Model: development of framework and impact on radiative forcing, Atmos. Chem. Phys., 15, 537–561, https://doi.org/10.5194/acp-15-537-2015, 2015.
Line 54: The current citation refers to observational data; however, the authors should instead cite modeling studies that have incorporated updated refractive indices consistent with these measurements. Two relevant studies are listed below. The first directly incorporates the measured refractive indices, while the second constrains iron oxide optics to ensure that the modeled dust optical characteristics are consistent with the measurements.
Wang, H., Liu, X., Wu, C., Lin, G., Dai, T., Goto, D., ... & Shi, G. (2024). Larger dust cooling effect estimated from regionally dependent refractive indices. Geophysical Research Letters, 51(9), e2023GL107647.
Li, L., Mahowald, N.M., Gonçalves Ageitos, M. et al. Improved constraints on hematite refractive index for estimating climatic effects of dust aerosols. Commun Earth Environ 5, 295 (2024). https://doi.org/10.1038/s43247-024-01441-4
Line 78-79: The term "pure dust" requires clarification. Do you mean particles composed solely of mineral components (though not limited to a single mineral species)? If so, this should be explicitly stated. Moreover, the claim that "pure dust is insoluble" is not strictly accurate. Some of the mineral components like hematite are indeed largely insoluble in water under ambient atmospheric conditions, but some others like calcite are highly soluble, and these are often present in atmospheric dust in small but non-negligible amounts.
Line 88-89: A reference is needed here, at minimum for K-feldspar. The following is one example that could be cited.
Atkinson, J. D., Murray, B. J., Woodhouse, M. T., Whale, T. F., Baustian, K. J., Carslaw, K. S., ... & Malkin, T. L. (2013). The importance of feldspar for ice nucleation by mineral dust in mixed-phase clouds. Nature, 498(7454), 355-358.
Line 103-105: The two sentences seem to contradict one another: "Furthermore, the net dust effective radiative forcing (DuERF) varies across models…" and "models may appear consistent in DuERF".
The first sentence states that DuERF varies between models, suggesting inconsistency, while the second says models "may appear consistent" which is the opposite.
Line 112: It would be helpful to specify which five models are being referred to.
Line 133-134: "wind dependent dust emission schemes". The current wording is somewhat informal, as dust emission in many ESMs depends on more than just wind speed. Additional factors such as the extent of bare soil, soil texture, and surface aridity also play critical roles in determining dust source regions.
Line 150: Can the authors specify the composition of the mineral mixture used in this calculation?
Line 151: It would be useful to clarify how this model, along with others referenced, treats LW aerosol scattering.
Line 191-192: In addition to the complex refractive index listed in Table 1, which specific optical properties are held fixed, e.g., single scattering albedo, extinction coefficient? Do these properties lack both spatial and temporal variability in the model?
Line 269-271: This sentence should be revised for clarity or just removed. Since surface albedo is consistent across the models, it does not contribute to the spread in forcing efficiencies. This point is already clearly conveyed in the following sentence.
Line 313: Are there any insights into why these two models produce notably different results? Identifying specific parameterizations or assumptions that set them apart would strengthen the analysis.
Line 355: Why focus on AOD and AAOD rather than DOD and ADOD, which are more directly attributable to dust aerosols? Using dust-specific metrics would provide a clearer assessment of dust aerosol impacts, right?
Line 362-363: The uncertainty range reported by Ridley et al. (2016) pertains to present-day DOD. It is unclear why the authors compare this with the modeled change in total AOD under preindustrial conditions.
Line 379: I expect the authors to further propose, in addition to constraints on DOD, what other specific constraints should be included to reduce the uncertainty in the direct DuERF.
Line 480: Could the authors clarify the distinction between "dusty surface albedo" and the "planetary albedo effect from airborne dust"?
Line 517-518: Are there any references, figures, or tables provided to support this statement?
Citation: https://doi.org/10.5194/egusphere-2025-1030-RC2 -
AC2: 'Reply on RC2', Ove Haugvaldstad, 11 Jul 2025
We thank the reviewer for the valuable comments and suggestions, this has really helped elevate the quality of the manuscript. Here, we are attaching the point-by-point response along with details about implemented modifications. Please kindly find the attachment.
-
AC2: 'Reply on RC2', Ove Haugvaldstad, 11 Jul 2025
Interactive discussion
Status: closed
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RC1: 'Comment on egusphere-2025-1030', Anonymous Referee #1, 22 May 2025
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2025-1030/egusphere-2025-1030-RC1-supplement.pdf
-
AC1: 'Reply on RC1', Ove Haugvaldstad, 11 Jul 2025
We thank the reviewer for the insightful comments and suggestions. The reviewer’s comments have meaningfully contributed to elevate the quality of the manuscript. Here, we are attaching the point-by-point response along with details about implemented modifications. Please kindly find the attachment.
-
AC1: 'Reply on RC1', Ove Haugvaldstad, 11 Jul 2025
-
RC2: 'Comment on egusphere-2025-1030', Anonymous Referee #2, 29 May 2025
The manuscript presents a comprehensive analysis of dust effective radiative forcing (DuERF) using CMIP6 ESMs under the AerChemMIP piClim-2xdust experiment, contrasted with the piClim-control run. The study decomposes DuERF into direct and indirect components, evaluates model uncertainties, and quantifies the impact of dust perturbations on precipitation. While the manuscript is well-structured and provides valuable insights, several key issues need addressing to improve clarity, interpretability, and robustness. Below, I outline major revisions the authors may want to consider to ensure the study meets its full potential.
General comments
1. The introduction is quite lengthy and detailed, and it gives me the impression that the authors aim to constrain the uncertainty in dust forcing estimates by addressing the factors that contribute to this uncertainty. However, this is not the primary goal of their study which I did not realize until the last several sentences of the introduction section. To better align with the study’s goals the introduction could be streamlined by shortening the discussion of factors contributing to uncertainty and focusing more on how those factors are represented in ESMs and how they influence the DuERF.
2. The study analyzes DuERF using the idealized piClim-2xdust experiment, which perturbs dust emissions under preindustrial conditions. While the emission increase (70-105%) is comparable to or larger than estimated historical changes (Kok et al., 2023), the experimental design, fixed SSTs and no anthropogenic forcing, means the results reflect model-specific dust responses rather than real-world historical forcing. The authors should clarify that these findings cannot be directly compared to studies quantifying DuERF over the industrial era, as the mechanisms and climate feedback differ. This distinction is critical to avoid misinterpretation of the DuERF values presented.
3. The authors need to explicitly state whether the ESMs account for LW aerosol scattering, if any, both in the model physics and in the reported LW and NET (SW+LW) forcing estimates. Omitting LW scattering likely biases the NET DuERF, as it can contribute 50% (20-60%) of the dust LW direct radiative effect at the TOA (Dufresne et al., 2002). If LW scattering is not included, please consider estimating the potential bias in the LW and NET DuERF and, if possible, adding this information to the LW and NET forcing estimates.
Also, while the manuscript notes weak LW direct forcing efficiencies (Figure 2b), it does not clarify whether this is due to missing physics (e.g., neglect of LW aerosol scattering, not only for coarse and super-coarse dust particles, although this is likely the major source), deficiencies in the size distribution (e.g., underrepresentation of super-coarse dust), or a combined effect of the two. I request clarification on these aspects.
4. The outlier behavior of NorESM2-LM is attributed to a known bug (line 400) that largely disables heterogeneous ice nucleation in mixed-phase clouds (lines 171-172). However, it is unclear how the authors handle the indirect forcing results from this model, particularly in relation to the indirect forcing. Was this model excluded from the analysis or given reduced weight in the ensemble mean? The authors should either quantify the impact of this bug on the results or provide a clear justification for including the model and explain how its known bias was accounted for.
5. The manuscript provides a good analysis of dust-cloud interactions and precipitation responses. However, the model descriptions in Table 1, and, in fact, throughout the manuscript, lack critical details about how cloud microphysics and precipitation processes are represented in each ESM. Only limited information is scattered throughout the text. Given that these processes are central to the study’s conclusions, particularly regarding dust indirect forcings and hydrological cycle impacts, a more comprehensive summary of model physics would significantly strengthen the interpretation of results.
6. The manuscript would benefit from greater consistency in its use of aerosol optical metrics to characterize dust impacts. While the study appropriately focuses on dust radiative forcing, there appears to be an inconsistent application of optical depth metrics throughout the analysis. At times, the authors examine total aerosol optical depth (AOD) and absorption aerosol optical depth (AAOD), while at other points they reference dust optical depth (DOD). Unless I missed it, the authors did not provide dust absorption optical depth (DAOD). It is also possible that the authors are using AAOD to refer to what is defined here as DAOD. However, this should be clarified to avoid confusion.
This variation in metrics could potentially lead to confusion when interpreting results, as total AOD/AAOD incorporates contributions from all aerosol species, not just dust. Given that the study specifically investigates dust impacts through the piClim-2xdust experiment, the consistent use of dust-specific metrics (DOD and DAOD) would provide a more direct and unambiguous estimate of dust aerosol effects.
7. The references are not properly cited. I have pointed this out in a few places, but I encourage the authors to check for similar issues elsewhere in the manuscript.
I notice that the authors super frequently cite some frequences, which are undoubtedly very valuable contributions to the research community. However, it is important to also acknowledge and appropriately credit the original studies that underpin key findings.
Minor comments
Line 35-36: What does this "environment changes" specifically refer to?
Line 51-52: This statement is not strictly accurate. Several ESMs are capable of representing dust aerosols as distinct mineral components. A few examples are provided below, although the list is not exhaustive and continues to grow as model development advances.
This list here (and after) is provided for my convenience, as the items are more readily available to me than the others. The authors should feel entirely free to cite any of them or any other sources they find relevant:)
Gómez Maqueo Anaya, S., Althausen, D., Faust, M., Baars, H., Heinold, B., Hofer, J., Tegen, I., Ansmann, A., Engelmann, R., Skupin, A., Heese, B., and Schepanski, K.: The implementation of dust mineralogy in COSMO5.05-MUSCAT, Geosci. Model Dev., 17, 1271–1295, https://doi.org/10.5194/gmd-17-1271-2024, 2024.
Li, L., Mahowald, N. M., Miller, R. L., Pérez García-Pando, C., Klose, M., Hamilton, D. S., Gonçalves Ageitos, M., Ginoux, P., Balkanski, Y., Green, R. O., Kalashnikova, O., Kok, J. F., Obiso, V., Paynter, D., and Thompson, D. R.: Quantifying the range of the dust direct radiative effect due to source mineralogy uncertainty, Atmos. Chem. Phys., 21, 3973–4005, https://doi.org/10.5194/acp-21-3973-2021, 2021.
Gonçalves Ageitos, M., Obiso, V., Miller, R. L., Jorba, O., Klose, M., Dawson, M., Balkanski, Y., Perlwitz, J., Basart, S., Di Tomaso, E., Escribano, J., Macchia, F., Montané, G., Mahowald, N. M., Green, R. O., Thompson, D. R., and Pérez García-Pando, C.: Modeling dust mineralogical composition: sensitivity to soil mineralogy atlases and their expected climate impacts, Atmos. Chem. Phys., 23, 8623–8657, https://doi.org/10.5194/acp-23-8623-2023, 2023.
Li, L., Mahowald, N. M., Kok, J. F., Liu, X., Wu, M., Leung, D. M., Hamilton, D. S., Emmons, L. K., Huang, Y., Sexton, N., Meng, J., and Wan, J.: Importance of different parameterization changes for the updated dust cycle modeling in the Community Atmosphere Model (version 6.1), Geosci. Model Dev., 15, 8181–8219, https://doi.org/10.5194/gmd-15-8181-2022, 2022.
Perlwitz, J. P., Pérez García-Pando, C., and Miller, R. L.: Predicting the mineral composition of dust aerosols – Part 1: Representing key processes, Atmos. Chem. Phys., 15, 11593–11627, https://doi.org/10.5194/acp-15-11593-2015, 2015.
Scanza, R. A., Mahowald, N., Ghan, S., Zender, C. S., Kok, J. F., Liu, X., Zhang, Y., and Albani, S.: Modeling dust as component minerals in the Community Atmosphere Model: development of framework and impact on radiative forcing, Atmos. Chem. Phys., 15, 537–561, https://doi.org/10.5194/acp-15-537-2015, 2015.
Line 54: The current citation refers to observational data; however, the authors should instead cite modeling studies that have incorporated updated refractive indices consistent with these measurements. Two relevant studies are listed below. The first directly incorporates the measured refractive indices, while the second constrains iron oxide optics to ensure that the modeled dust optical characteristics are consistent with the measurements.
Wang, H., Liu, X., Wu, C., Lin, G., Dai, T., Goto, D., ... & Shi, G. (2024). Larger dust cooling effect estimated from regionally dependent refractive indices. Geophysical Research Letters, 51(9), e2023GL107647.
Li, L., Mahowald, N.M., Gonçalves Ageitos, M. et al. Improved constraints on hematite refractive index for estimating climatic effects of dust aerosols. Commun Earth Environ 5, 295 (2024). https://doi.org/10.1038/s43247-024-01441-4
Line 78-79: The term "pure dust" requires clarification. Do you mean particles composed solely of mineral components (though not limited to a single mineral species)? If so, this should be explicitly stated. Moreover, the claim that "pure dust is insoluble" is not strictly accurate. Some of the mineral components like hematite are indeed largely insoluble in water under ambient atmospheric conditions, but some others like calcite are highly soluble, and these are often present in atmospheric dust in small but non-negligible amounts.
Line 88-89: A reference is needed here, at minimum for K-feldspar. The following is one example that could be cited.
Atkinson, J. D., Murray, B. J., Woodhouse, M. T., Whale, T. F., Baustian, K. J., Carslaw, K. S., ... & Malkin, T. L. (2013). The importance of feldspar for ice nucleation by mineral dust in mixed-phase clouds. Nature, 498(7454), 355-358.
Line 103-105: The two sentences seem to contradict one another: "Furthermore, the net dust effective radiative forcing (DuERF) varies across models…" and "models may appear consistent in DuERF".
The first sentence states that DuERF varies between models, suggesting inconsistency, while the second says models "may appear consistent" which is the opposite.
Line 112: It would be helpful to specify which five models are being referred to.
Line 133-134: "wind dependent dust emission schemes". The current wording is somewhat informal, as dust emission in many ESMs depends on more than just wind speed. Additional factors such as the extent of bare soil, soil texture, and surface aridity also play critical roles in determining dust source regions.
Line 150: Can the authors specify the composition of the mineral mixture used in this calculation?
Line 151: It would be useful to clarify how this model, along with others referenced, treats LW aerosol scattering.
Line 191-192: In addition to the complex refractive index listed in Table 1, which specific optical properties are held fixed, e.g., single scattering albedo, extinction coefficient? Do these properties lack both spatial and temporal variability in the model?
Line 269-271: This sentence should be revised for clarity or just removed. Since surface albedo is consistent across the models, it does not contribute to the spread in forcing efficiencies. This point is already clearly conveyed in the following sentence.
Line 313: Are there any insights into why these two models produce notably different results? Identifying specific parameterizations or assumptions that set them apart would strengthen the analysis.
Line 355: Why focus on AOD and AAOD rather than DOD and ADOD, which are more directly attributable to dust aerosols? Using dust-specific metrics would provide a clearer assessment of dust aerosol impacts, right?
Line 362-363: The uncertainty range reported by Ridley et al. (2016) pertains to present-day DOD. It is unclear why the authors compare this with the modeled change in total AOD under preindustrial conditions.
Line 379: I expect the authors to further propose, in addition to constraints on DOD, what other specific constraints should be included to reduce the uncertainty in the direct DuERF.
Line 480: Could the authors clarify the distinction between "dusty surface albedo" and the "planetary albedo effect from airborne dust"?
Line 517-518: Are there any references, figures, or tables provided to support this statement?
Citation: https://doi.org/10.5194/egusphere-2025-1030-RC2 -
AC2: 'Reply on RC2', Ove Haugvaldstad, 11 Jul 2025
We thank the reviewer for the valuable comments and suggestions, this has really helped elevate the quality of the manuscript. Here, we are attaching the point-by-point response along with details about implemented modifications. Please kindly find the attachment.
-
AC2: 'Reply on RC2', Ove Haugvaldstad, 11 Jul 2025
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Dirk Olivié
Trude Storelvmo
Michael Schulz
The requested preprint has a corresponding peer-reviewed final revised paper. You are encouraged to refer to the final revised version.
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