the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A global dust emission dataset for estimating dust radiative forcings in climate models
Abstract. Sedimentary records indicate that atmospheric dust has increased substantially since preindustrial times. However, state-of-the-art global Earth system models (ESMs) are unable to capture this historical increase, posing challenges in assessing the impacts of desert dust on Earth’s climate. To address this issue, we construct a globally gridded dust emission dataset (DustCOMMv1) spanning 1841–2000. We do so by combining 19 sedimentary records of dust deposition with observational and modeling constraints on the modern-day dust cycle. The derived emission dataset contains interdecadal variability of dust emissions as forced by the deposition flux records, which increased by approximately 50 % from the 1850s to the 1990s. We further provide future dust emission datasets for 2000–2100 by assuming three possible scenarios for how future dust emissions will evolve. We evaluate the dust emission dataset and illustrate its effectiveness in enforcing a historical dust increase in ESMs by implementing conducting a long-term (1851–2000) dust cycle simulation with the Community Earth System Model (CESM2). The simulated dust deposition is in reasonable agreement with the long-term increase in most sedimentary dust deposition records and with measured long-term trends in dust concentration at sites in Miami and Barbados. This contrasts with the CESM2 simulations using a process-based dust emission scheme and with simulations from the Coupled Model Intercomparison Project (CMIP6), which show little to no secular trends in dust deposition, concentration, and optical depth. The DustCOMM emissions thus enables ESMs to account for the historical radiative forcings (RFs), including due to dust direct interactions with radiation (direct RF). Our CESM2 simulations estimate a 1981–2000 minus 1851–1870 direct RF of –0.10 W m-2 from dust particles up to 10 μm in diameter (PM10).
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RC1: 'Comment on egusphere-2024-1124', Anonymous Referee #1, 08 Jun 2024
Review of the manuscript entitled “A global dust emission dataset for estimating dust radiative forcings in climate models”by Danny M. Leung, Jasper F. Kok et al.
General comments:
This paper constructed a globally gridded dust emission dataset spanning 1841-2000 according to combining 19 sedimentary records of dust deposition. Their results are interesting and important for improving GCM simulations at historical and future dust change. Several points of the manuscript still need to be improved before accepted. Specifically, the dust radiative forcing can lead to non-uniform feedbacks on dust emissions from dust radiative effect, e.g., dust direct and dust-in-snow forcing, which will affect the results from CESM2-DustCOMM. Therefore, the manuscript needs to make several revisions before their paper is considered acceptable. Please see the following comments.
Specific comments:
1, Previous studies have shown that the dust emission fluxes can significantly be influenced by dust direct effect and dust-in-snow effect (e.g., Miller et al., 2004; Xie et al., 2018b), which can affect the regional dust cycle including dust emissions, depositions, and dust AOD, in turn lead to positive or negative feedbacks. The dust radiative forcing can lead to non-uniform feedbacks on dust emissions from dust direct effect (positive feedback over North Africa and negative feedback over East Asia in Xie et al., 2018a) and from dust-in-snow effect (only positive feedback over East Asia in Xie et al., 2018b). These non-uniform feedbacks induced by dust radiative forcing may result in inconsistency between simulations from dust reconstructed gridded dust emission dataset (red line) and observation (black line) in Figs 4, 6, and 7. I think the authors should discuss this point about these radiative feedbacks on dust emission. Dust-ice cloud interaction (DeMott et al., 2010; Sagoo and Storelvmo, 2017) maybe also have important influence on dust cycle?
3, In Figure 1, it shows the source region contributes the greatest deposition flux in the present day at a given grid. These dust deposition fluxes in Figure 1 are from the previous study (Ron L. Miller)? If the dust deposition flux data is from the previous study (Ron L. Miller) in Figure 1, your new results from DustCOMMv1 will show different pattern of the fractional contribution of that dominant source region. I think the authors should clarify this point.
4, To directly compare to other GCM results (or CMIP6), the authors should show the global mean value as one table for CESM2-L23 and CESM2-DustCOMM about dust emissions (Tg/yr), dust dry/wet deposition (Tg/yr), dust burden (Tg), lifetime (days), and Dust AOD,…
5, In Figure 5 caption, the authors should point out what the box and the error bar represent?
References
DeMott P J et al 2010 Predicting global atmospheric ice nuclei distributions and their impacts on climate Proc. Natl. Acad. Sci. U.S.A. 107(25) 11,217-11,222
Miller, R. L., Perlwitz, J., and Tegen, I.: Feedback upon dust emission by dust radiative forcing through the planetary boundary layer, J. Geophys. Res., 109, D24209, https://doi.org/10.1029/2004JD004912, 2004.
Sagoo N and Storelvmo T 2017 Testing the sensitivity of past climates to the indirect effects of dust Geophys. Res. Lett. 44 5807-5817
Xie, X.N., X.D. Liu, H.Z. Che, X.X. Xie, H.L. Wang, J.D. Li, Z.G. Shi, and Y.G. Liu, 2018a, Modeling East Asian dust and its radiative feedbacks in CAM4-BAM, Journal of Geophysical Research–Atmospheres, 123, 1079-1096, https://doi.org/10.1002/2017JD027343.
Xie, X.N., X.D. Liu, H.Z. Che, X.X. Xie, X.Z. Li, Z.G. Shi, H.L. Wang, T.L. Zhao, Y.G. Liu, 2018b: Radiative feedbacks of dust-in-snow over eastern Asia in CAM4-BAM, Atmospheric Chemistry and Physics, 18, 12683–12698, https://doi.org/10.5194/acp-18-12683-2018.
Citation: https://doi.org/10.5194/egusphere-2024-1124-RC1 -
RC2: 'Comment on egusphere-2024-1124', I. Pérez, 23 Jul 2024
This is a quite complete paper where dust emissions and deposition are considered. It may be divided in several parts. The first one is devoted to obtain a global gridded dust emission dataset. This dataset is extended into the future under three emission scenarios: enhancement, constant, and reduction. The second part is focused on the modelling, and comparison with experimental values at two sites (Miami and Barbados), ice cores, or marine sediments, is presented. Finally, optical properties are analysed and a negative radiative forcing is obtained. Both the study extension and depth of this paper are noticeable. Paper information is extremely dense. However, this study can be published in Atmospheric Chemistry and Physics after the inclusion of the following minor changes.
In its current form, this paper is oriented towards a specialised community, which could be small. To increase and attract possible readers, some simple sentences should be introduced to highlight the main results, strengths and weaknesses of this paper.
Figure 2 presents three possible scenarios, taking into account that the past trend presented increasing emissions, do the authors think that a reduction scenario is possible?
Figure 5. Perhaps modelling results should be considered with caution due to the box ranges and even the negative values that are obtained.
Figure 7. Is there any special reason to justify the good agreement between the CESM2-DustCOMM and reconstruction? Why is a 68% confidence level selected?
Since deserts are major dust sources, is it possible to select the main sources against the minor contributors? Is the contribution of both groups quantified?
Minor remarks.
These is a version of the Wilks title published in 2019. Is it possible to update this reference?
Citation: https://doi.org/10.5194/egusphere-2024-1124-RC2 - AC1: 'Comment on egusphere-2024-1124', Danny Leung, 03 Sep 2024
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