Review of Gui et al, ACPD, ‘Record-breaking dust loading during two mega dust storm events over northern China in March 2021: aerosol optical/radiative properties and meteorological drivers’
The authors present a variety of information to characterize two major dust storms in the North China region during March 2021, which were exceptional events. They describe the spatial, temporal and vertical evolution of the dust events using satellite dust optical depths and lidar dust extinction profiles, visibility measurements and RGB Himawari imagery. They analyze the optical and radiative properties of the dust using AERONET data from a site in the Beijing region. They use MERRA-2 reanalysis data to identify dust source locations, and analyse the dynamical driving meteorology predominantly using 700hPa reanalysis data. Finally they put the scale of the month’s dust events into context by analysing the historical record of the dust loading from satellite data and environmental reanalysis data.
The study is of importance since it characterizes these unusual dust events in detail throughout their lifetime from emission, driving meteorology, characteristics in the atmosphere, transport patterns, optical properties, and radiative effects, providing a host of useful information to the aerosol and climate community. The work on classifying the dust events in their historical context is novel and is very important in understanding these properties. Overall the paper is very well written and presented.
The first round of reviewers pointed out several areas of overlap with two previously published papers (Filonchyk (2022) and Liang et al. (2022)). Liang et al. (2022) is a short, bulletin type of publication of 4 pages. Though it touches on some of the areas covered by this publication, the short length of the publication prohibits exploration of the science and data in any detail, as is done in this article. Filonchyk (2022) focuses on ground-based particulate matter concentrations during the 3.15 event, showing some satellite data (mostly different to that used here) to illustrate the links between the ground-based measurements and confirm dust presence. Some analysis of the synoptic situation is presented in Filonchyk (2022), though scope remains for much more detailed analysis and exploration, as aimed for in this article. Thus I think there is ample scope for an article such as this one, fitting for ACP, where the dust properties, evolution and effects, from several data sources, are explored in much detail.
The authors give a very strong justification of why their article is different to Filonchyk (2022) and Liang et al. (2022) in the response to reviewers. In my view these are strongly justified, and there is plenty of scope for exploring the event(s) in much more detail, and with a stronger link between the satellite data, dust transport and emission patterns, and the meteorology. However, given this strong justification I was surprised that this did not come through more strongly in the article – both in terms of setting the scene in the introduction, and in terms of the analysis of certain data elements. The authors certainly need to expand the introduction to include a more detailed summary of the published work on this event, setting out how their aims and approaches expand on what has already been done. They have done this in the response to reviewers, but it feels like it has not really made it through to the article itself. Secondly more could have been made of certain avenues of data analysis which are different to those already published – some even pointed out by the authors themselves. I describe these below, but it is up to the editor whether these is necessary to include. They would enhance the article’s novelty, rather than be critical to its publication.
RGB Himawari imagery - I was surprised to see limited analysis of RGB Himawari imagery, given the response to reviewers. One immense advantage of the RGB imagery is that it’s from geostationary satellites, therefore permitting analysis of dust events at higher temporal resolution than possible with polar-orbiters, providing data once a day. Analysis of hourly RGB data can be highly insightful to dust emission and transport mechanisms, and their interactions and influences by weather systems as a function of time. This simply cannot be determined from single-day overpass satellite data. In my opinion further expansion of the imagery along these lines would be highly beneficial.
Lidar data - The exploration of lidar (both from CALIOP and a ground-based lidar) dust extinction is beneficial, in comparison to the vertical feature dust masking data that has previously been published. However, I found limited discussion of the intensity of the plume at different altitudes – a feature which is identifiable with the extinction data used, rather than discussion of the plume behaviour and altitude in general – which could have been done with the vertical feature mask.
Historical analysis - The historical analysis of the dust event, and setting in into context of the previous years in terms of DOD and also environmental factors, such as soil moisture and precipitation, is extremely useful and important. However, I missed a key point of the analysis which was the question of how unusual the anomalously strong Mongolian cyclones driving the dust emission were. In my opinion this is the missing piece of the puzzle. This is also key to discussing how dust emissions in North China will change in the future.
Introduction – I would like to see an expansion of the discussion of previous work on the 3.15 event (and the 3.27, if it exists), working up to an outline of aims for the article in relation to what has or has not been done before. The authors currently do this in the introduction very briefly, and not in much detail. I have seen the authors detailed and well-justified response to the first round of reviews on this subject, and believe that much of this information and argument should be added to the actual manuscript. The introduction is the fitting part of the manuscript for this to be laid out. For example, new presentation of Himawari data, more detailed analysis of CALIOP data, more thorough analysis of dynamical driving mechanism, etc, and what these additional sources bring to the article. The authors have already explained this in their response to reviewers, but the article would benefit from its inclusion. This would significantly improve the novelty of the paper and make the article stand out from those studies already published.
Minor/Technical Points
Fig 1 – the chosen color scheme makes it nearly impossible to identify the dust plume in this imagery, both on my screen and on print-out. The authors have added the notation ‘dust’ in several locations to aid this, though it’s still nearly impossible to differentiate this from other land areas, forcing the reader to take their word for dust presence. It’s impossible to identify the spatial extent and intensity described in lines 68-75. The authors should strive to present this more clearly. If the color scheme cannot be altered, perhaps a ‘dust’ contour could be drawn, with information in the caption to state what that definition is based on.
L79-82, “To date, several studies (e.g., Liang et al., 2021; Filonchyk, 2022; Filonchyk and Peterson, 2022) have been conducted to characterize the severe SDS event in March 2021. Most of these studies have focused on investigating the evolution and transport processes of the dust plume during the 3.15 event and assess its impact on the air quality by using particulate matter (PM10) concentration observations and individual satellite retrieval products.” – The authors should separate these studies rather than generalizing (‘most of these studies..’), and for each describe what has previously been done, leading up to the main differences in this article.
L105 – do you mean they agree well as demonstrated by those studies, or do you mean specifically for your case study?
Section 2.1.3 – CALIOP – was there a reason you did not use the dust extinction profile provided directly by NASA? What are the differences between your algorithm and the standard NASA CALIOP retrievals for dust-only extinction?
Section 2.1.4 – Himawari – An assessment of the advantages and assumptions/limitations of using the Himawari RGB data should be given here – e.g. high time resolution diurnal sampling ability, assumption of aerosol properties/altitude, interference from clouds. Much of this is covered in Brindley et al. (2012).
L200-210 – Are you using the DARF using fluxes at the TOA and BOA as given by the AERONET algorithm (rather than applying the aerosol properties in a radiative transfer code of your own)? This should be clearly stated.
2.2.2 Visibility – Why are the effects of RH discounted? RH is an important contributor to visibility, and is a relative unknown in terms of how much it affects dust-induced decreases in visibility. On reading section 3.1 perhaps this is done to avoid spatial variations in visibility due to relative humidity. In this case it would be useful to include the uncorrected visibility map in the supplement.
L264 – ‘Clearly, the dust RGB composite images are able to provide a more spatially continuous evolution of the dust plume than the satellite inversion of aerosol-related variables, as it does not need to rely on various retrieval assumptions.’ – this is not clear, since other satellite aerosol products have not been presented at this point. Himawari RGB data does require other assumptions and have other limitations (see comment for section 2.1.4).
L268 – ‘pulled’ > ‘uplifted’
L274-280 – This paragraph is a bit disappointing in that it points out differences in cyclone intensity, extent and location, yet does not really provide the evidence to explain these.
Fig 3 – a better color bar should be used, with fixed thresholds for different visibility levels (rather than a graduated color bar), so that readers can easily pick out the actual visibility values.
All map figures – it would be useful to distinguish between the outlines of national boundaries vs regional boundaries within China to aid interpretation from figures. Perhaps the authors could use a bold outline for national boundaries to make them more distinct?
Fig 5 – figure quality is poor – markers very light and blurred.
L331-2 = “Notably, an enhancement of DOD at the dust source on March 28 was not captured, which implies that the intensity of dust emissions was significantly lower on March 28 than on March 27.” – if it was not captured, how do you know there was an enhancement? Which source?
L336 – “the AOD in Beijing increased significantly during the period from 8 to 12 h (CST) on March 17” – fig 5 shows that the AOD mostly increased on March 16th – by 17th March the AOD is already ~2. Similarly, this means that the event lasted longer than ~ 4 hours, as stated.
L339-341 – ‘On March 17, EAE values between 0.1 and 0.3 and FMF values between 0.2 and 0.3 together reveal that the enhanced aerosol loading is dominated by 340 coarse-mode particles, with a smaller contribution from fine-mode particles.’ – The FMF does not seem to relate to the dust-related AOD – FMF drops somewhat at the end of 16th March, drops very slightly on 17th March, but the differences are not exceptional.
Fig 7 – has cloud-screening been performed in constructing this figure?
L358 and next 2 paragraphs – the authors should consider the point-nature of the lidar site in their description of the vertical distribution of the dust. This data is great for fully describing the temporal evolution of the dust, but it is only a single point. Thus when a plume at upper levels mostly dissipates and one appears at lower levels, this does not necessarily mean the plume has descended to the surface (as described for 26th March). It’s more likely that the upper plume dissipated or was transported away from the point observation, and the lower plume entered the observing region due to transport.
Fig 8 – please zoom the map plots in more to make them more readable. Lat/lon values on the map would be useful to relate them to the extinction figure.
L384-388 (wrt fig 8) – This is rather underwhelming. The figure (8b) seems to show onlyk a small amount of data, which may be due to the lidar signal being extinguished by the heavy dust loadings. If this is so, the authors should discuss this. This section of writing does not add much to the manuscript.
Fig 9 – presumably this is shortwave DARF. This should be clearly added to the figure caption and methodology section, as well as the results section of the text.
L 403 – SSA of 0.915 is actually fairly low as far as dust is concerned. For example, climate models tend to use values of ~0.95-0.97 at 550nm
L435 – ‘It is worth noting that on March 15 the dust emissions from the GD located in northwestern Inner Mongolia were significantly higher than the intensity of dust emissions from the GD located in southern Mongolia, which raises the question as to whether the GD in China was the original source of the 3.15 SDS event.’ – this is rather unclear. It’s difficult to make out from the maps exactly what is meant by this.
Fig 10 – it would be useful to add the preceding dates of 14 Mar (as in fig 11) and 26 Mar. Fig 11 and associated analysis in the paper show that the emissions peak the day before peak dust concentrations and load are experienced across China. Therefore it would be relevant to include emissions from the preceding day for each event, as these are most useful to illustrate the evolution of the dust event. Although 14 Mar is shown in fig 11, it would be useful to add it to fig 9 to complete the temporal evolution shown.
L443-444 – what do your results of emission here add to the description of this event, in addition to confirming those of Jin and Liang? Backward trajectory analysis for dust can often be inaccurate due to poorly represented meteorology at low resolution driving the back trajectories, and the fact that the trajectories do not include dust being deposited out of the air mass tracked.
L481 – ‘This configuration of synoptic systems established an unfavorable atmospheric circulation condition for dust emissions from the GD and transported along the direction of cyclone movement, which directly led to visibility reaching the minimum of this process on March 15.’ – unclear. Do the authors mean an unfavorable situation for strong transport and dispersion of dust in the atmosphere? I.e. the airmass was relatively stagnant after the cyclone moved away, leading to the build up of the emitted dust?
L488-491 – what about difference in location (and therefore availability of erodible surface material) in addition to cyclone intensity?
Section 3.5 – I was surprised not to find more analysis of the surface pressure distribution and evolution presented here, given the arguments in the response to reviewers about the surface pressure being the missing link between what has previously been published.
L529-536 – this is a fairly substantial section discussing material only in the supplement. I urge the authors to include important information and figures in the manuscript itself, and if not crucial, do not discuss the` detail in the text.
Fig 16 caption – is the data in the figure instantaneous at 2d preceding the 3.15 event, or averaged over a fixed time period? I.e. averaged over days -14 to day zero preceding the event? This should be clarified in the caption.
Fig 16 – why does fig b show approximately zero snow depth anomaly, yet fig f shows a negative anomaly compared to the mean?
L558-563 – “Yin et al. (2021) utilized site observations, reanalysis data, and historical simulation outputs from CMIP 6 to analyse the dynamical mechanisms of Mongolian cyclones influencing dust occurrence and development, and revealed that the climate variabilities at different latitudes and synoptic disturbances jointly facilitated the strongest SDS event in NC over the past decade.” – this is not a very useful statement – it doesn’t allow the reader to learn anything new. The authors should make their statement clearer, and in addition explain how their own analysis here adds understanding/information to previously published studies.
Section 3.7 – how anomalous were the 2 Mongolian cyclones in March 2021 which drove the dust events? The authors have identified the record breaking nature of March 2021 dust, and identified that the environment was effectively ‘pre-loaded’ via reduced precipitation, surface temperature and soil moisture to be ready for a massive dust storm. But the key missing factor appears to be how unusual was the dynamical situation? Or was the surface so dry that the typical average Mongolian cyclone would result in a massive dust storm? This is also key to discussing how dust emissions in North China will change in the future.
Section 3.7 – snow melt – how does this relate to the soil moisture? To what extent does earlier/more snow melt lead to a moister soil due to the meltwater?
Conclusions – the authors may also like to add Pu and Ginoux (2018) to their discussion of future dust changes, as these authors provided some valuable contributions. (Manuscript already in references of main article).
Throughout manuscript: ‘blown up’ > ‘uplifted’
References
Brindley, H.. et al., A critical evaluation of the ability of the Spinning Enhanced Visible and Infrared Imager (SEVIRI) thermal infrared red-green-blue rendering to identify dust events: Theoretical analysis, J. Geophys. Res., 2012, doi: 10.1029/2011JD017326 |
