the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
The relative importance of wind and hydroclimate drivers in modulating wind-blown dust emissions in Earth system models
Abstract. Windblown dust emissions are subject to large uncertainties in Earth system models (ESMs), yet model discrepancies in dust variability and its physical drivers remain poorly understood. This study evaluates the consistency of 21 ESMs in simulating the climatological distribution and interannual variability of global dust emissions and applies dominance analysis to quantify the relative influence of near-surface wind speed and five hydroclimate variables (precipitation, soil moisture, specific humidity, air temperature, leaf area index) across different climate zones. In hyperarid regions, the models exhibit poor agreement in dust variability, with only 10 % of pairwise comparisons showing significant positive correlations. Most models capture the dominant wind control except GFDL-ESM4 which display dominant hydroclimate influence (wind contributing 42 %) and high spatial variability. In arid and semiarid regions, dust variability is shaped by a dual effect of land surface memory: models with consistent hydroclimate variability converge in dust responses, while those with divergent hydroclimate representations show increased disagreement. While all models capture the expected increase of hydroclimate influence with decreasing aridity, the extent of this transition varies by model, resulting in greater model disagreement regarding the relative importance of wind and hydroclimate drivers in arid/semiarid regions. Implementing the Kok et al. (2014) scheme in CESM reduces the wind contribution from 86 % to 64 % in hyperarid regions and from 56 % to 46 % in arid regions, indicating enhanced hydroclimate influence compared to the Zender et al. (2003) scheme. These findings underscore the importance of improving hydroclimate and land surface representations for reducing uncertainties in dust emission responses to climate variability and change.
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RC1: 'Comment on egusphere-2025-3013', Anonymous Referee #1, 17 Jul 2025
This study investigates the dominant factors contributing to the spatial (regional and aridity-level dependent) and temporal (interannual) variability of dust emission, drawing upon Earth System Model (ESM) results for the present day provided to CMIP6. Similar prior works (not cited in the manuscript) have previously reached comparable conclusions. So the work lacks originality. A key distinction is that previous studies relied on observations, allowing for absolute comparisons. This study, however, does not utilize global long-term observations of dust properties, such as satellite-based Dust Optical Depth (DOD). Consequently, its findings are limited to a model inter-comparison, without the ability to assess potential strengths or weaknesses.
I would suggest to the authors to build upon the work of Zender and Kwon (2005) and Kim et al. (2017), perhaps focusing on long-term variability, given that MODIS offers over 20 years of daily global DOD data. Surface concentration at Barbados has been observed daily since 1965, providing 60 years of data—ample for studying inter-annual variability. Prospero and Lamb (2003) demonstrated that hydroclimate factors control dust long-term variability. By examining the ESM results that best reproduce the interannual variability observed at Barbados and/or in satellite data, we could discern the strengths and weaknesses of their controlling factor(s).
However, when analyzing interannual variations, certain factors influencing these variations should also be considered. These include land-use, which significantly contributes to dust emission (Ginoux et al., 2012; Stanelle et al., 2014), and fires (Yu and Ginoux, 2022; Wagner and Schepanski, 2025).
Some fundamental information regarding the ESMs, crucial for understanding their differences in dust emission, is either incorrect or inadequately explained. Furthermore, the analysis exhibits a bias towards CESM, with minimal or no discussion of other models.
The citations for MPI-ESM-1.2 and GFDL-ESM4 are erroneous. Tegen et al. (2019) described ECHAM6.3-HAM2.3 with constant roughness and vegetation mask. Is Mauritsen et al. (2019) not the correct reference for MPI-ESM-1.2? MPI-ESM-1.2 utilizes MAC-v1 prescribed aerosol distribution (Kinne et al., 2013). For GFDL-ESM4, it would be appropriate to refer to Shevliakova et al. (2024) instead of Evans et al. (2016). The authors are advised to consult these references or contact the lead authors to ensure an accurate description of their models.
Table 1 lacks critical information, such as LAI. Is it calculated online? Is it static or dynamic? Does it incorporate land-use? Is brown vegetation included? For 10-meter wind-speed derived from the first model level, the robustness of the derivation diminishes with increasing altitude of this level. Horizontal resolution is paramount for all fields. How can models be compared without knowledge of their spatial resolution?
Given these significant issues, I cannot recommend the publication of the present manuscript.
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References:
Evans, S., P. Ginoux, S. Malyshev, and E. Shevliakova (2016). Climate-vegetation interaction and amplification of Australian dust variability, Geophys. Res. Lett., 43, 11,823–11,830, doi:10.1002/2016GL071016.
Ginoux, P., J. M. Prospero, T. E. Gill, N. C. Hsu, and M. Zhao (2012), Global-scale attribution of anthropogenic and natural dust sources and their emission rates based on MODIS Deep Blue aerosol products, Rev. Geophys., 50, RG3005, doi:10.1029/2012RG000388.
Kim, D., Chin, M., Remer, L. A., Diehl, T., Bian, H., Yu, H., ... and Stockwell, W. R. (2017). Role of surface wind and vegetation cover in multi-decadal variations of dust emission in the Sahara and Sahel. Atmos. Environm., 148, 282-296.
Kinne, S., D. O'Donnel, P. Stier, S. Kloster, K. Zhang, H. Schmidt, S. Rast, M. Giorgetta, T. F. Eck, and B. Stevens (2013). MAC-v1: A new global aerosol climatology for climate studies, J. Adv. Model. Earth Syst., 5, 704–740, doi:10.1002/jame.20035.
Mauritsen, T., Bader, J., Becker, T., Behrens, J., Bittner, M., Brokopf, R., et al. (2019). Developments in the MPI-M Earth System Model version 1.2 (MPI-ESM1.2) and its response to increasing CO2. Journal of Advances in Modeling Earth Systems, 11, 998–1038. https://doi.org/10.1029/2018MS001400
Prospero, J. M., and Lamb, P. J. (2003). African droughts and dust transport to the Caribbean: Climate change implications. Science, 302(5647), 1024-1027.
Stanelle, T., I. Bey, T. Raddatz, C. Reick, and I. Tegen (2014), Anthropogenically induced changes in twentieth century mineral dust burden and the associated impact on radiative forcing, J. Geophys. Res. Atmos., 119, 13,526–13,546, doi:10.1002/2014JD022062.
Tegen, I., Neubauer, D., Ferrachat, S., Siegenthaler-Le Drian, C., Bey, I., Schutgens, N., Stier, P., Watson-Parris, D., Stanelle, T., Schmidt, H., Rast, S., Kokkola, H., Schultz, M., Schroeder, S., Daskalakis, N., Barthel, S., Heinold, B., and Lohmann, U. (2019). The global aerosol–climate model ECHAM6.3–HAM2.3 – Part 1: Aerosol evaluation, Geosci. Model Dev., 12, 1643–1677, https://doi.org/10.5194/gmd-12-1643-2019.
Wagner, R., and Schepanski, K. (2025). Quantifying fire-driven dust emissions using a global aerosol model. Journal of Advances in Modeling Earth Systems, 17, e2024MS004466. https://doi.org/10.1029/2024MS004466
Yu, Y., and Ginoux, P. (2022). Enhanced dust emission following large wildfires due to vegetation disturbance. Nature Geoscience, 15(11), 878-884.
Zender, C. S., and E. Y. Kwon (2005). Regional contrasts in dust emission responses to climate, J. Geophys. Res., 110, D13201, doi:10.1029/2004JD005501.
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Citation: https://doi.org/10.5194/egusphere-2025-3013-RC1 -
AC1: 'Reply on RC1', Xin Xi, 21 Jul 2025
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2025-3013/egusphere-2025-3013-AC1-supplement.pdf
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AC1: 'Reply on RC1', Xin Xi, 21 Jul 2025
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RC2: 'Comment on egusphere-2025-3013', Anonymous Referee #2, 04 Aug 2025
The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2025/egusphere-2025-3013/egusphere-2025-3013-RC2-supplement.pdf
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