the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Atmospheric Forcing of Dust Source Activation across East Asia
Abstract. East Asian dust storms impact the health and livelihoods of millions but the atmospheric processes responsible are far from fully understood because suitable observations are lacking. Here we analyse dust source activation (DSA) frequency data for East Asia (80–130° E, 27–52° N, January 2016 through December 2023, Chen et al., 2025, https://doi.org/10.1088/1748-9326/addee6) to understand atmospheric controls on dust activation. We show that East Asia's two primary dust source regions (Chen et al., 2025) display distinct diurnal and seasonal variations in DSA frequency. A southern region, sandwiched between the Mongolian Plateau and the Tibetan Plateau, chiefly consisting of the Taklimakan Desert and the Alashan Plateau, is active year-round, with 40–60 % of events predominantly occurring during late morning (09:00–12:00 local solar time; LST) under clear-sky conditions. We show that breakdown of the Low-level Jet (LLJ) is a major control on dust activation across this region (not only the Taklimakan Desert), driven by morning heating of the land surface, deepening the convective boundary layer and momentum transfer to the land surface. A northern region, centred on the Mongolian Plateau-Gobi Desert is dust-active from morning to afternoon (08:00–14:00 LST), primarily under cloudy conditions, driven by the passage of low-pressure systems. A third (less active) dust source region, the Tibetan Plateau, is typically active during winter afternoons in response to strong mountain-valley winds. Meso- and local-scale winds are more extensive drivers of dust activation across East Asia than previously documented, adding uncertainty to model predictions of future dust emissions in East Asia under a warming climate.
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Status: open (until 17 Dec 2025)
- RC1: 'Comment on egusphere-2025-3077', Anonymous Referee #2, 23 Nov 2025 reply
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RC2: 'Comment on egusphere-2025-3077', Anonymous Referee #3, 25 Nov 2025
reply
This study performed a systematic analysis of the spatial pattern and time series of the dust source activation frequency in East Asia derived from satellite-based observations. By comparison with the meteorological conditions derived from ERA5, the authors attributed the dust source activation events into three mechanisms, low pressure cyclones, breakdown of low-level jet, and mountain valley winds. The authors further provided statistical results indicating the relative importance of these three mechanisms in different dust source regions. This study provides solid observational evidence of the systems dominating dust emissions in East Asia, and I suggest considering publication after the following comments are addressed.
- When looking at the dust activation frequency data, I’m always confused about the definition of a dust activation event. For example, assuming a single dust emitting event lasts for a few hours within a day, is the ‘dust activation frequency’ the fraction of time with dust emission? The authors should make it clear in the data & method section.
- The authors spend a lot of effort to give a comprehensive review of the mechanisms responsible for dust emissions in East Asia in section 2, and I feel like this should be shorted and put into introduction. Rather than stating the dominant mechanism in each region, I suggest the authors focus more on the limitations of previous studies.
- When analyzing breakdown of low-level jets in Fig. 6, the authors chose to use the wind speed maxima at 3 UTC. Is it more reasonable to use local time because of the diurnal characteristic of these systems? The frequency of the low-level jet is also confusing. Is it the fraction of days that have low-level jets? Also using local time might help identifying low-level jet occurrence.
- It seems that in Fig. 7 the authors tried to compare the wind speed profiles under dusty or non-dusty days. Are they the average wind profiles across all dusty and non-dusty days? Meanwhile the wind share at 0 UTC is compared, why not 3 UTC?
- Attribution of different dust activation events. It seems that the authors tried to attribute each event to different mechanisms by comparing their time series. However, there might be overlaps of different systems, for example the breakdown of low-level jet might occur together with cyclones. In Fig. 8, breakdown of low-level jets could also contribute to an increase in 10-m wind speed.
- I agree with the comments from reviewer #2 that in Fig. 4 you should count in all the regions defined on the left rather than only check a single grid cell.
Citation: https://doi.org/10.5194/egusphere-2025-3077-RC2 -
RC3: 'Comment on egusphere-2025-3077', Yan Yu, 25 Nov 2025
reply
This study analyzes a recently published dust source activation dataset compiled by the same group of authors and tries to attribute the atmospheric forcings responsible for dust activation across East Asia, with an emphasis on the diurnal time scale. Built on the temporal resolution of geostationary satellite, this study examines the resolved details about space and time of dust activation. Therefore, it provides important additions to the existing knowledge about dust emission processes in East Asia. But these new insights could be strengthened upon improved analysis and presentation. Therefore, I recommend a major revision before the manuscript is considered for publication at ACP.
Major questions and suggestions:
- The authors have classified dust source activation events into clear-sky and cloudy situations, and subsequent attribute them to different atmospheric causes. Naturally, one would expect larger uncertainty in the manual identification of dust source activation under clouds. Do you have any uncertainty estimation regarding the time and location of DSA identification in clear-sky and cloudy situations?
- You have attributed the cloudy situations to cyclone-type of DSA. However, convective storms, especially the cold pools associated with them, can also initiate dust emission (Fiedler et al., 2013; Heinold et al., 2013). These convective dust storms, mostly seen in local summer and afternoon, can at least partially explain the summer, afternoon DSAs in Taklamakan and Alashan.
- On the organization of the contents, I recommend reducing the text about the seasonal cycle and expanding the analysis on shorter time scales, as these are better seen in the currently analyzed geostationary satellite data. To expand on the shorter time scales, I recommend the following additional analysis and/or clarifications: (1) The authors seem to treat wind gusts, Mongolia Cyclone, and break down of LLJ as different atmospheric forcings. But the latter two processes, along with the convective storms I mentioned earlier, could also introduce high wind gusts. Therefore, I don’t like the current framing of section 4.4 that mainly attributes the variations in wind gusts to mountain-valley wind. Indeed, I think a better way to establish the linkage between wind gust (possibly caused by different atmospheric forcings) and DSA is to add the diurnal cycle of wind gust by season on top of the barchart of DSA in Figure 4. It might be helpful to further separate the clear-sky and cloudy cases, dusty and non-dusty cases. From such a figure, we get an overview of the importance of wind gust in driving dust emission. (2) Towards the end of the results section, you can still present the monthly time series (Figure 8). But as a reader I’m curious about at what time of day the temporal variation in wind gust is most closely related to that of DSA. Could provide this information (maybe in a table or heatmap showing correlation coefficients between DSA and wind gusts at different time of day). (3) Attribution of DSA to LLJ could be done in a more specific way. Currently you are inferring the contribution of LLJ by morning DSA over total DSA. But these morning DSA could be partially caused by cyclones too. Could you collocate the DSA with LLJ spatio-temporally and see how much of the DSA in each grid is genuinely caused by LLJ? (4) Figure 3 is a nice summary of the peak hour of DSA. But I believe in some dust sources especially those only active during the overpass of Mongolian Cyclones, there is no distinct pattern of diurnal variation. I recommend the analysis of variance framework, as used in our analysis about diurnal variability in dust optical depth (Yu et al. 2021). Using this framework, you can easily tell if diurnal variability is truly a leading component of DSA’s temporal variability by comparing the variance on the diurnal time scale to that on the seasonal time scale and day-to-day time scale, for each grid.
Minor questions and suggestions:
- On line 111, you state that “dust plumes were identified by manual inspection of daily animations”. Did you specially require that the DSA of each plume has to be tracked within the same day? If so, you are possibly splitting multi-day events into separate daily events and miss-identifying fake sources.
- On line 127, you state that “we used ERA5 monthly averaged data to analyze the monthly variations in wind speed and gusts”. Are you referring only to Section 4.4? It appears that in Figs. 6 and 7, for example, hourly wind speed at different levels is analyzed.
- In Figure 4 and other relevant analysis, rather than picking the grid with highest dust source activation frequency, why don’t aggregate all grids in a specific region to expand the sample?
- You don’t have to say that wind data is from ERA5 every time in the figure captions.
- In Fig. 6, you say that the LLJ is identified based for 9:00 local solar time, but I believe at this time LLJs are starting to break down. Whereas in Fig. 7, it is at 6:00 local solar time. I wonder if it is a typo in the caption of Fig. 6.
- In Fig. 7, the lines are hard to distinguish from each other, maybe consider using a heat map with x-axis for time of day, and y-axis for vertical level, and color representing the wind speed.
Reference:
Fiedler, S., Schepanski, K., Heinold, B., Knippertz, P., and Tegen, I.: Climatology of nocturnal low-level jets over North Africa and implications for modeling mineral dust emission, J. Geophys. Res.-Atmos., 118, 6100–6121, https://doi.org/10.1002/jgrd.50394, 2013.
Heinold, B., Knippertz, P., Marsham, J. H., Fiedler, S., Dixon, N. S., Schepanski, K., Laurent, B., and Tegen, I.: The role of deep convection and nocturnal low-level jets for dust emission in summertime West Africa: Estimates from convection-permitting simulations, J. Geophys. Res.-Atmos., 118, 4385–4400, https://doi.org/10.1002/jgrd.50402, 2013.
Yu, Y., Kalashnikova, O. V., Garay, M. J., Lee, H., Choi, M., Okin, G. S., Yorks, J. E., Campbell, J. R., and Marquis, J.: A global analysis of diurnal variability in dust and dust mixture using CATS observations, Atmos. Chem. Phys., 21, 1427–1447, https://doi.org/10.5194/acp-21-1427-2021, 2021.
Citation: https://doi.org/10.5194/egusphere-2025-3077-RC3
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This study analyzed the spatial distribution and diurnal characteristics of dust source activation frequency in East Asia, with the attribution of the mechanism based on the comparison of dust source activation frequency from Himawari-8/9 satellite imagery and wind fields from EAR5. The scope of the study is important, but I am concerned about the validity of the method and the associated interpretation. The dust source activation frequency and the mechanism attribution need to be strengthened.
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Technical Comments: