This is the revised version. However, I am quite struggle to understand some results partly due to my poor English. Based on the results in the manuscript, it seems to be very tough and challenging to get the clear message of the atmospheric density changes due to the large temperature changes because of SSW.
I would suggest the authors apply similar method for other SSW events occurred in January (for example, 2006, 2009, 2019) if you can get similar results and conclusions. Sorry for the extra works to the authors but It is necessary not only for double check purpose but you will may also see some similarities/differences. Below are the listed comments for the consideration:
1) Lines 37-38. I am not sure where "approximately once every 2 years in the winter stratosphere over North Pole"
comes from. This will cause some confusion and misleading. Note that the frequency event (~ 6 events per decade, the past major SSW events are listed at
https://csl.noaa.gov/groups/csl8/sswcompendium/majorevents.html
does not mean "~ once every 2 years".
2) Line 39. Again not sure which SSW year had 60 K stratospheric temperature increase over a few years as mentioned
"sudden warming of 40–60 K in the polar stratospheric temperature over a few days". I guess it is probably from the model results
because some models have bias cold polar temperature which makes this possible. However, it should be based on observational data for this.
3) Line 52: It is not clear that the cited "O/N2 column density depletion of more than 10% at the onset of SSW"
indicates which altitude range.
4) Lines 56-59. This reads quite weird. What do you mean "atmospheric variations"? The variations of atmosphere have many atmospheric
dynamics/chemistry fields etc including the temperature, total electron content, trace gases mentioned above.
Since the "atmospheric density" can be expressed as a relationship of pressure and temperature based on thermodynamics equation,
so it is understandable how it changes when temperature and pressure change.
Therefore, the sentence "The atmospheric density is always neglected..., resulting in the density evolution during SSW events rarely being reported"
is confusing. Looking at section of Satellite datasets, the satellite don't have direct measures of neutral air density, which is diagnosed based on temperature....
5) Line 66. How Beijing lidar can detect "horizontal distributions of the neutral air density" since it is located at one single location.
6) Line 67. Please add a reference for SD-WACCM when it is first mentioned.
7) Line 85, it looks that the unit for g is wrong, which should be m/s2.
8) Line 91, add a reference for "EGM96 Geopotential Model"
9) Lines 99-100, add some examples/references for the data validation and applications.
10) Lines 105-106, it is vague and unclear how "the reference density" is derived. It seems that the latter results indicate it is climatological mean density.
11) Section 2.2, needs more information about Lidar system. For example, what is the accuracy of lidar temperature and its performance based on the previous publications...
12) Section 2.4. Needs more information about WACCM version. Is it WACCM4 based on CESM1 or WACCM6 based on CESM2?
Has the model simulation carried out in China or did the the authors make the simulations by their own?
If so, how did they implement the required input data (for example, solar, emissions etc) which is current not public available beyond year 2015?
13) Lines 156-158. Not clear why cites Lu et al. (2021) here? Do you want to highlight this is the longest SSW events(?)
Please keep in mind that Lu et al used ERA5. Does MERRA2 show similar results?
14) Line 164. Not sure if the authors describe the results correctly/properly. For example,
It is weird to say something like "colder stratopause", please keep in mind what the definition of stratopause is.
Somehow MLS data did not show clearly the elevated stratopause temperature mid-late January/early Feb after the SSW from the current analysis (because current uses a very narrow latitude band average?).
15) Figure 1(d) and (f). The caption on these Figures is wrong. It is not "zonal mean density" which should be relative density change.
16) Figure 1. "during the SSW event" is not necessary for the description of Figure 1 (d) and (f).
Actually I am concerned the Figure 1 (d) and (f) since it is well known that the atmospheric density decreases exponentially with increases altitude.
Maybe there won't big atmospheric density changes in the stratosphere but I expect some big changes in the stratopause,
especially after the SSW (for example we expect some significant stratopause changes from the past studies for example SSW events in February 2006 and January 2009,
which should show some big effects on the density changes).
However, the current figures won't support my initial thought.
For example, Figure 1(c) and (e) shows stratopause altitude is around 45 km, but why the largest density changes in around 60 km?
I understand there is large annual variability in the high latitude in the Northern hemisphere.
Maybe the best way to add similar results of the relative temperature and pressure changes for double check Figure 1(d) and (f).
Not sure if the authors need to be cautions(to be specified, the SSW events during 2004-2021 should be removed, rather than using the climatology values in the current manuscript).
My understanding is that the current manuscript used the 2021 daily atmospheric density value minus 2004-2021 DJF mean density (Figure 1d) or 2013-2021 DJF mean density (Figure 1f), then divide the mean to obtain the relative density deviation.
17) Lines 181-193. Not clear what the message and key points the authors would like to highlight.
It seems OK to use the global mean density in Figure 2a,b,c assuming the mass is conserved for individual days.
However, these figures only show the relative percentage changes of zonal mean atmospheric density over different latitudes with respect to the global mean density.
18) Lines 184, Figure 2. Which date should be (1 Feb or 7 January). Same comments for Figures 3, 4 and Line 216 etc.
19) Line 206. It is confusing using "standard deviation" in many places, which also makes mean to try very hard to understand Figure 3d and Figure4.
20) I am really sorry that I am total lost in Lines 206-207. The caption in Figure 2d is "DJF Climate mean" and the decription also says "climate winter average", so I thought they are the DJF climate mean of relative percentage change of zonal mean density with respect to the global mean density averaged over the winter DJF during 2004-2021. But standard deviation is different term! I don't see anything in Figure 2d related to the possible explanation based on Smith et al. (2012). This requires further clarification.
21) Lines 222-228: polar vortex. Please bear in mind the low pressure is not the only criteria for the polar vortex!
22) Lidar temperature data. Not sure why the derived temperature from Beijing lidar is only available between ~35-65 km.
As commented for Section 2.2, there are some important information is missing, for example, how temperature and density are retrieved.
What are key parameters are used and where are the from? for example, reference height and reference atmospheric density etc.
23) Lines 237-238. It reads weird. Please note that Beijing is at mid-latitude.
24) Lines 240-241 and Figure 5b, 5d. I understand maybe Lidar did not have enough data to build the climatology.
However, based on Figure 4, there are large temporal variation (though I guess 7 January is a typo in Figure 4) and spatial variation.
So maybe the pattern could be different using climate averaged or Dec 2020-Feb 2021 as a reference.
It is also not clear how you sampled the MLS over Beijing? Do you just simple weight averaged around Beijing location using the processed
every 5 latitude x 20 longitude degree data? Anyway, it will be better to use Dec 2020-Feb 2021 average for MLS.
Another related question is that Beijing lidar temperature was observed during night time, did you also set a time constrain criteria for MLS?
25) Figure 4. Based on the pressure contours in Figure 4 (k) I guess this is the day for 1 Feb 2021. Somehow Figure (c) shows two low pressure centres at 80 km if I read the figure correctly.
26) Lines 261-267. Some discrepancies between MLS and SD-WACCM in the mesosphere should be expected.
Comparing the temperature profiles in Figure 6a and Figure 2a, these differences are not SMALL "excepting some small differences in detail within the topmost altitudes".
I understand the MLS temperature above ~88 km or higher (?) is outside the scientific use, however, somehow the mesopause altitude from MLS is around 80 km (?) (Figure 2a) while WACCM has much higher mesopause altitude (??) than MLS. So this is not only the difference as mentioned "The mesopause temperature is slightly colder than the observations around the onset date."
The result "a decrease in the density appears above 80km" may come from Figure 6b, however, this is the relative percentage density change!
Density is decreasing with increasing altitude is well known!
I am also not convinced by some simple explanations here.
27) Figures 10 versus Figure 1. I am worried about the inconsistent of "density deviation". The results came from the same data and uses different coordinate.
Clearly temperature profiles/evolution/magnitude etc are consistent.However, why don't see similar pattern/magnitude for density change? The results here may cause confusion or may be misleading. |
