Airspace Contamination by Volcanic Ash from Sequences of Etna Paroxysms: Coupling the WRF-Chem Dispersion Model with Near-Source L-Band Radar Observations
, Franck Donnadieu 2, Mauro Morichetti 1, Elenio Avolio 3, Giuseppe Castorina 4, Agostino Semprebello 5,6, Salvatore Magazu 6, Giorgio Passerini 7, Enrico Mancinelli 7 and Clothilde Biensan 2
Round 1
Reviewer 1 Report
The paper was well written and has interesting information for not only the WRF modeling community but to those who work operationally and deal with volcanic ash.
I would be curious to know if you look at only periods of high pressure in 2013 would you get a similar dispersion pattern as that of 2015.
Also, I would like to see some discussion on how things like precipitation during the periods of low pressure influenced the dispersion of ash. And how WRF handled that.
Comments for author File: 
Comments.pdf
Author Response
The paper was well written and has interesting information for not only the WRF modeling community but to those who work operationally and deal with volcanic ash.
1) Earlier you define very fine ash as <30 microns, however, here you say you are modeling very fine ash with particles less than 10 microns. I would recommend rewording to make clearer what is being modeled/what is of most interest in the study.
We agree with the referee, to make things clearer we changed the actual sentence in Introduction section 1.1:
“In our study, we model the dispersion of very fine ash with particles less than 10 μm in size (PM10), as these are also well-known to affect air quality and human health ….. “
with:
“In our study, we model the dispersion of ash particles considering ten bins of volcanic ash particles with a grain diameter range starting from 2 mm down to less than 3.9 μm. Specific interest will be devoted to ash particles less than 10 μm in size (PM10), as these are also well-known to affect air quality and human health ….”
2) I would be curious to know if you look at only periods of high pressure in 2013 would you get a similar dispersion pattern as that of 2015.
Among the whole 2013 sequence, only the eruption denoted by NSE1 (see figure 4a) occurred under high-pressure conditions, we already highlighted this in “result” section :
“Finally, a different (from the previous ones) configuration is noticeable for NSE1 (Figure 4a), characterised by a wide high-pressure area over the whole Italian Peninsula. In this situation, the upper-level currents over Sicily were weaker and mainly directed towards the southwest, also driven by a lower pressure area over North Africa.”
In this context, it is important to point out that although NSE1 occurred under high-pressure conditions the dispersion pattern is quite different from that of 2015. Infact, during NSE1 the prevailing southwestern winds at 500 hPa (figure A2a), with average values around 15 ms-1, dislocated the plume in this direction, as reported in figure 6a.
3) Also, I would like to see some discussion on how things like precipitation during the periods of low pressure influenced the dispersion of ash. And how WRF handled that.
Although a bit beyond the scope of this work, we acknowledge the question of how precipitation may influence ash dispersal is quite relevant and thank the reviewer for having piqued our curiosity. In fact, to evaluate the effect of deposition we should re-run the code by turning-off the deposition routines and compare with present results. Instead, we estimated the cumulated precipitations during the two periods studied, we have added an analysis (toward the end of paragraph 3.2.1) from two new maps obtained by elaborating the Level-3 GPM-IMERG retrievals and reported in Appendix (A4). They allow us to conclude for a negligible effect of precipitation on ash dispersion in the studied cases.
“Additionally, in order to evaluate the influence of precipitation on the dispersion of ash, we have analysed the amount of precipitation in the domain by elaborating the Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM-IMERG Final Precipitation, Level 3 products), for the two periods considered in this work. The WRF-Chem model has specialised routines to calculate dry/wet deposition for aerosol components including volcanic ash. Specifically, the “below cloud” wet deposition is handled by considering the sum of the large-scale rain (from the microphysics scheme) and the convective rain (by cumulus scheme).
For the 2013 sequence, Figure A4(a) shows the area around Etna clear from precipitation, and 30 mm of accumulated precipitation in the Ionian and southern Adriatic seas. By comparing with the average p10 map of Figure 6, the amount of ash deposited at ground by wet deposition is arguably quite small. In the second period in December 2015, there was no rain in the domain except in the Tyrennian sea close to the East coast of Sardinia (Figure A4(b)). By comparing with the average p10 map of Figure 7, the amount of ash deposited at ground by wet deposition may be considered negligible.”
Author Response File: Author Response.pdf
Reviewer 2 Report
The presented study elaborates on the dispersion of volcanic ash from unsteady paroxysms at Etna volcano. This is somewhat new as previous studies on ash dispersion (at various other volcanoes) used a more constant input of ash into VATD (Volcanic Ash Transport and Dispersion) models. This study highlights a valuable combination with in-situ estimated mass eruption rate from Doppler radar. I liked reading the manuscript and reccomend it for publication after some minor comments are addressed, listed below.
specific comments and simple text edits (line numbers refer to the submitted pdf):
l.167: ... as input to ...
l.169: ... time-evolving ...
l.190: please format SO2 the same way as e.g. in line 151
l.266: please give a reference to a paper or book describing all processing steps needed to convert raw data to velocities and echo power
l.329: blank missing after reference [37]
l.355-356: The geopotential height and wind vectors derived by WRF-Chem simulations are reported in Figures 4 and 5.
l.363: ... NSE4 and ...
l.408-409 ... the E1 distribution (see Tab. 4) with diameter less than 10 \mum as follows:
l.436: refer to figure 11a,b, where the transect is used
l.440: again, refer to figure 11c-f, where the transect is used
l.476: try to rewrite this. Starting a paragraph with 'Figure x displays...' is not good style
l.526: is this formula important? It does not really show the calculation, which is hidden behind the square bracket operator. The explaining text might be sufficient.
l.588: "transects shown in Figures 6-7": please specify here again, which panel refers to which Figure/transect
l.599: Upon reading this, a question formed: What about Catania airport? Could you give a timeline for ash concentrations there as well? If not in a separate plot, please include a statement on potential hazards at this particular airport. It would also be interesting, if you could issue in-time warnings, if this proposed method would go operational/online.
Figures 6, 7, 8c, 8f, 9c, 9e, 9f, 10c: the most prominent feature in these figures is the patchy or wave-like pattern. A pattern like this sometimes indicates numerical instabilities. Here you give an explanation for them in lines 555-557, but ignore their existance before. I obivously overread the pulsed input of MER (lines 290-291), because I was surprised by this explanation for the pattern. This is my main critique in this manuscript: please make it more clear, that the MER, derived from Doppler radar, is highly variable over time and used as input to WRF-chem. I would repeat this information, in addition to the input height (lines 313-316) as last paragraph of 2.4 (after line 349). In addition, the pattern and its cause should directly be mentioned at the first reference of Figure 6. You could also refer to the discussion and also include a more detailed explanation, because I am not fully convinced. Are the pulses that regular to produce such a regular pattern?
Figures 9 and 10: the titles (flight levels) of the panels looked blurry in the pdf. Maybe enlarge the font size.
no comments
Author Response
The presented study elaborates on the dispersion of volcanic ash from unsteady paroxysms at Etna volcano. This is somewhat new as previous studies on ash dispersion (at various other volcanoes) used a more constant input of ash into VATD (Volcanic Ash Transport and Dispersion) models. This study highlights a valuable combination with in-situ estimated mass eruption rate from Doppler radar. I liked reading the manuscript and reccomend it for publication after some minor comments are addressed, listed below.
specific comments and simple text edits (line numbers refer to the submitted pdf):
l.167: ... as input to ...
OK
l.169: ... time-evolving ...
OK
l.190: please format SO2 the same way as e.g. in line 151
we changed using the same format: SO2
l.266: please give a reference to a paper or book describing all processing steps needed to convert raw data to velocities and echo power
reference [29] Dubosclard et al. 2004 was added
l.329: blank missing after reference [37]
OK
l.355-356: The geopotential height and wind vectors derived by WRF-Chem simulations are reported in Figures 4 and 5.
OK
l.363: ... NSE4 and ...
OK
l.408-409 ... the E1 distribution (see Tab. 4) with diameter less than 10 \mum as follows:
OK
l.436: refer to figure 11a,b, where the transect is used
OK
l.440: again, refer to figure 11c-f, where the transect is used
OK
l.476: try to rewrite this. Starting a paragraph with 'Figure x displays...' is not good style
OK
l.526: is this formula important? It does not really show the calculation, which is hidden behind the square bracket operator. The explaining text might be sufficient.
OK
l.588: "transects shown in Figures 6-7": please specify here again, which panel refers to which Figure/transect
OK
l.599: Upon reading this, a question formed: What about Catania airport? Could you give a timeline for ash concentrations there as well? If not in a separate plot, please include a statement on potential hazards at this particular airport. It would also be interesting, if you could issue in-time warnings, if this proposed method would go operational/online.
We thank the reviewer for this insightful remark! We added the following statement (after line 599, and a sentence in last bullet point of conclusive section):
“The timeline of ash contamination at the nearby Catania airport (CTA), or a given city, may be obtained by extrapolating the proximal ash at a given time after the onset; this would allow in-time warnings to be issued at CTA or any specified point of the numerical domain. This may be very important in the case the proposed procedure would go online with an operational forecast.“
Figures 6, 7, 8c, 8f, 9c, 9e, 9f, 10c: the most prominent feature in these figures is the patchy or wave-like pattern. A pattern like this sometimes indicates numerical instabilities. Here you give an explanation for them in lines 555-557, but ignore their existance before. I obivously overread the pulsed input of MER (lines 290-291), because I was surprised by this explanation for the pattern. This is my main critique in this manuscript: please make it more clear, that the MER, derived from Doppler radar, is highly variable over time and used as input to WRF-chem. I would repeat this information, in addition to the input height (lines 313-316) as last paragraph of 2.4 (after line 349). In addition, the pattern and its cause should directly be mentioned at the first reference of Figure 6. You could also refer to the discussion and also include a more detailed explanation, because I am not fully convinced. Are the pulses that regular to produce such a regular pattern?
The wave-like pattern results from the combined effect of time-varying MER of particularly strong and rapid eruptions and the averaging (daily) of the pulsed ash plumes.
This may be seen in our previous paper (Remote Sens. 2021, 13, 4037. https://doi.org/10.3390/rs13204037) in particular in the figure 10 it may be seen the effects of time-varying MER, resulting in a pulsed map distribution (figure 10b) if compared with a constant MER (figure 10a). That figure is relative to a snapshot (12:00 UTC of November 2013) and when averaging over time you obtain the wave-like pattern.
As suggested, we have changed the text and added the following:
“The MER, derived from Doppler radar, is highly variable over time and used as input to WRF-Chem.”
In the points mentioned by the referee, that is in the lines 313-316, at the end of 2.4.
In particular when commenting figure 6 we added the following:
“Another feature that is evident in figure 6 is the wave-like pattern, caused by NSE4 in the northward direction. This happened because NSE4 was very rapid (3 hours, see table 1) and the most intense of the whole sequence (figure 1d). The wave-like pattern results from the combined effect of time-varying MER, of particularly strong eruptions, and the averaging (daily) of the pulsed ash plumes.”
when commenting figure 7 we added:
“Again, the wave-like pattern is evident in the eastward direction caused by the VOR1 paroxysm, which is the most intense of the whole sequence.”
Figures 9 and 10: the titles (flight levels) of the panels looked blurry in the pdf. Maybe enlarge the font size.
Thanks for pointing this out! We have enlarged the fonts and uploaded the new figures.
Author Response File: Author Response.pdf
