the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 22 Jul 2024
Unseasonal atmospheric river drives anomalous glacier accumulation in the ablation season of the subtropical Andes
Abstract. Climate change is associated with changes in the frequency and intensity of extreme weather events. These changes are impacting the mass balance of Andean glaciers, a phenomenon that requires further detailed investigation. Among these events, atmospheric rivers (ARs) play a significant role in influencing glacier mass balance, potentially leading to either accumulation or melting events. To assess the impact of ARs on Andean glaciers, we analysed an unseasonal event that occurred at the end of January 2021, marked by extreme rainfall, landslides, and flash floods in the lowlands, during the typically dry summer period. Satellite imagery and meteorological observations in the glaciated Maipo River basin and its Olivares River sub-basin (33° S) enabled the characterisation of this event and its basin-scale impacts. Moreover, a glacier mass balance model allows us to quantify the effects on the Olivares Alfa Glacier (4284 to 4988 m a.s.l.) over the context of the preceding six hydrological years. The significant water vapour transport by the AR led to substantial snow accumulation on the Maipo River glaciers, confirmed by the post-event snowline observed at 2463 m a.s.l. In the Olivares River sub-basin, the 0 °C isotherm dropped during the event to an elevation of 3250 m a.s.l., below the frontal zone of all glaciers in this sub-basin. The mass balance model for the Olivares Alfa Glacier during the dry 2020/21 hydrological year showed a trend toward negative values at the beginning of the ablation season, aligning with previous years and the prevailing mega-drought conditions. However, the AR event offset this trend, bringing the mass balance closer to equilibrium. This demonstrates that an unseasonal accumulation event can significantly counteract the broader seasonal trends affecting subtropical Andean glaciers. Our study sheds light on the impacts of extreme and unseasonal snow accumulation events on glacier mass balance in the high Andes, particularly those associated with ARs, a synoptic feature projected to become more common in a warming climate.
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Status: final response (author comments only)
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RC1: 'Comment on egusphere-2024-1958', Anonymous Referee #1, 15 Sep 2024
Summary
In this paper, Bravo and coauthors study an unusual July 2021 atmospheric river (AR) that contributed positively to the mass balance of glaciers in the subtropical Andes during what is normally the ablation season. They use a combination of station observations, atmospheric reanalysis, remote sensing data, and a glacier mass balance model to show that this AR halted the seasonal progression of Olivares Alfa Glacier mass loss, resulting in near-equilibrium mass balance for the year. They conclude that a single major AR event can exert a dominant influence on annual glacier mass balance, even when the large-scale climate conditions would normally be expected to favor mass loss.The paper presents a compelling scientific story and is a novel contribution to the literature, as AR impacts on the cryosphere have not been studied in detail in this region of the subtropical Andes. The paper is generally well-written with sound scientific methods, and the references are comprehensive and appropriate. The main aspect the paper lacks is a more thorough exploration of how this AR event compares to the long-term climate context of this study region, as described in my major comments. I also have a large number of minor comments and technical corrections that do not represent fundamental flaws, but should be addressed before the paper can be of a publishable standard.
Major comments
- Since the ERA5 data are available for a longer time period than 2014–2021, it would enhance this study to see how the January 2021 compares to all summer ARs during the multi-decadal ERA5 record. I understand that running the COSIPY model for this long time period is likely beyond the scope of this analysis, but I don't expect it would be too difficult to extend the record of AR events and their categories to the full time period of the ERA5 data. This would provide some valuable long-term background to determine how unusual the January 2021 AR was. Some of this information may be provided at the regional scale by previous studies (e.g. Valenzuela et al., 2022), but the long-term context that is directly relevant to the glacier mass balance of this study area should be provided and interpreted for the reader in this paper. See also my minor comment on L356–358.
- How does the total accumulated precipitation compare to past AR events, both during summer and during all seasons? Is there precedent for this type of summer accumulation event if you look at a longer time period than 9 years? Is there any way for the authors to quantify this with the available data? I expect that the record-high IVT values relative to the Jan/Feb 2013–2021 climatology (L354–361) would translate to precipitation accumulation at the high end of the climatology, but this isn't guaranteed to be the case.
- Figure 3: It's not clear why this figure is included in the paper. The only references to this figure in the text are to mention that the station data exist (L175, 177) and the figure is not used to support any of the paper's main findings. It should either be removed from the paper, or some text should be added to the paper describing how the figure contributes to the study's results. See also my minor comment on L424–425.
Minor comments
- L32–45: This is a long paragraph. I suggest starting a new paragraph at L38 with the sentence starting with "In the subtropical Andes..."
- L38: It would be helpful to give some more detail about what region the term "subtropical Andes" refers to. What countries / areas of countries are considered the subtropical Andes? L42 implies that this mainly refers to Chile and Argentina, but it would be useful to define this region in more detail at its first mention in L38.
- L88 (last paragraph of introduction): This paragraph jumps abruptly to discussing the January 2021 AR event without any transition from previous paragraphs. It would be helpful to at least briefly discuss the seasonal climatology of precipitation and ARs in this region as context for the January 2021 AR studied in this paper. This type of information is provided to some extent later in the paper (e.g. L128–129), but it would be helpful for developing the paper's story for it to be included in the introduction.
- Figure 1: A large-scale map, showing the study region's location within the broader context of southern South America, would be helpful for readers unfamiliar with the region's geography.
- Figure 1: Do the blue areas on the large map show the outlines of glaciers? Please clarify.
- L110–141: I suggest reorganizing this section to cover only the study area. I think the paper will flow better if the description of the January 2021 AR event is refactored into the Introduction and Results sections. Any background information on the January 2021 AR that is based on previous studies (e.g. Valenzuela et al., 2022) should be moved to the Introduction, and any analysis of this event that is a new result of this study should be moved to the Results.
- L122: Is there any way to label the two accumulation zones of the Olivares Alfa Glacier on the large map in Figure 1?
- L131–132: The climatology of AR category 1 events during summer in this region is helpful context for the reader. Is summer defined as December-January-February? Please clarify.
- Figure 2: It would be helpful to mark the location of the Maipo and/or Olivares River basin on either panel A or C.
- Figure 2: It doesn't make sense to me to have a combined y-axis with IVT magnitude on the left axis (units of kg m^-1 s^-1) and IVT direction (angular units) on the right axis. I suggest splitting this into two separate panels with different y axes.
- L152–169: These methods for determining the snowline elevation and freezing level are a nice, creative blending of remote sensing, radiosonde, and station data.
- L153–154: Is this product, which I presume is based on visible imagery, affected by cloud cover? Are there places / times where the snowline elevation can't be determined due to clouds?
- L179–180: From what source(s) are the medium and high resolution imagery?
- L183–184: Do the authors anticipate that initializing the model with a no-snow starting condition for each year will have an influence on the results? It would be helpful to include at least a brief discussion of the implications of this decision.
- L189–195 and L296–299: I like the idea of simulating a hypothetical scenario for seasonal mass balance evolution without the AR's influence, but I'm not sure I completely follow the method and the conclusions that can be drawn from it. How was the detrending of the mass balance time series post-event performed? Am I interpreting L193–195 correctly to mean that this method isn't capable of assessing the influence of the albedo increase during the AR event?
- L208–221: Is this analysis of ARs during 2014–2021 for all seasons? Or summer only? Please clarify.
- L231–232: I'm not sure I agree with the statement that the snowline elevation did not return to its pre-event elevation by the end of the hydrological year. If I am interpreting Figure 4 correctly, it looks like the snowline returned to its pre-event elevation by early March, then another snow event in mid-March decreased the snowline elevation once again.
- L249–251: Do the authors have any hypotheses for why there was a greater discrepancy in the 0 degree isotherm from radiosondes vs in-situ temperature sensors during the post-event days? Is there a physical reason for why this might be the case, or is it just a random occurrence?
- Figure 4: This is a nice plot that does a good job of illustrating the radiosonde and station comparisons. However, I have a couple of comments on this plot:
- Similar to my comment on Figure 2, I suggest splitting the plot into 2 separate panels with separate y-axes, rather than having two different scales on the same y-axis
- The two rightmost x-axis tick marks are incorrectly labeled as January. These dates are in February.
- L258–274: Be clear that the energy fluxes reported in this section are based on the COSIPY model simulation rather than observations. This is discussed in Section 5.1 but this point should also be made clear here.
- L282: I don't see the support for the statement that "Typically, ablation in April dominates the mass balance". If I am interpreting Fig. 7 correctly, it looks like the largest mass loss months in the 2014–2021 COSIPY simulations were February and March.
- L288–289: This sentence states that "As expected, the ablation season started in September 2020", but the x-axis label in Fig. 7 labels Oct 1 as the start of the ablation season.
- L337: Nice job compiling the estimates of glacier mass balance from previously published sources and comparing them with the COSIPY simulations. This lends credibility to the study results.
- L356–358: Be clear that the record of historical January-February events, to which the IVT value is being compared, covers only the period from April 2013 to March 2021 (according to Table S1).
- L366–376: This is an interesting discussion of the discrepancy between the observed snowline and the height of the 0 degree isotherm. Do the authors have any hypothesis for why the snowline was anomalously low relative to the 0 degree isotherm during this event?
- L410–429: This is a nice discussion of how one extreme event can counteract the evolution glacier mass balance expected from the large-scale climate state. This is a good story for the reader to take away from the paper.
- L424–425: This appears to be an erroneous reference to Fig. 3. Fig. 3 does not say anything about how the snowline elevation has changed over the past 20 years.
- L424–426: Where is the Lagunitas meteorological station located? This station should be shown on a map in one of the figures, and also described in Section 3 (rather than introducing this dataset for the first time near the end of the paper).
- L463–464: The two papers referenced in this sentence describe projected future changes in global AR conditions. Are there any references that provide projections that are more directly relevant to the study region? Or do the two referenced papers include results that can be used to describe projections more specifically for this study region?
Technical corrections
- L20: "over" --> "in"
- L37: "are" --> "is"
- L39: insert "the" before El Niño
- L50: "role of glaciers" --> "influence on glacier"
- L53: "its" --> "their"
- L60: "mid-latitudes" --> "mid-latitude"
- L64: "ARs" --> "AR"
- L65: "its" --> "their"
- L73: "over" --> "above"
- L90: "and characterized" --> "and was characterized"
- L90: "mountain" --> "mountains"
- L96: "the well-known large-scale glacier mass balance forcing as ENSO" - this does not make grammatical sense, please rephrase
- L136: "fuel" --> "fueled"
- L145: IVT stands for "integrated vapor transport" or "integrated water vapor transport", not "integrated vertical transport"
- L147: "Ralph's scale" - please rephrase
- L147: Remove the word "current"
- L150: "scales" --> "scale"
- L159: "was" --> "were"
- L212: "into" --> "over"
- L226: "glaciers" --> "glacier"
- L227: "at this summertime" - this phrase does not make grammatical sense, please rephrase
- L244: "increases" --> "increase"
- L246: "similar values of" --> "similar values to"
- L257: "Surface fluxes energy" --> "Surface energy fluxes"
- L262: "nigh" --> "night"
- L280: "are" --> "is"
- L285: It is not clear what "particular" means here. Please choose a different word.
- L354: "At synoptic-scale, significant moisture transport." - This sentence is a fragment, please revise.
- L367: Remove the word "up"
- L367: "occurs" --> "occurred"
- L394–395: "heat turbulent" --> "turbulent heat"
- L396: "Glaciers" --> "glaciers"
- L401: "influx longwave radiation" - This phrase does not make grammatical sense, please rephrase.
- L453: "mass glacier" --> "glacier mass"
- L461: "202/21" --> "2020/21"Citation: https://doi.org/10.5194/egusphere-2024-1958-RC1 - AC1: 'Reply on RC1', Claudio Bravo, 08 Nov 2024
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RC2: 'Comment on egusphere-2024-1958', Álvaro Ayala, 24 Oct 2024
PAPER SUMMARY AND RECOMMENDATION
Bravo et al. analyse the impact of an unseasonal atmospheric river (AR) on the annual mass balance of Olivares Alfa Glacier, subtropical Andes of Chile. The AR occurred at the end of January 2021and resulted in a strong precipitation event over central Chile, which is very rare to occur during the austral summer. The authors conducted their analyses using remote sensing products, meteorological observations, and energy and mass balance models. They found that the event produced an accumulation of 164 mm w.e. (measured near the glacier tongue) and lowered the 0°C isotherm from typical summer elevations of 4000-4500 m a.s.l. to 3000-3500 m a.s.l., as well as lowering the snowline elevation to about 2500 m a.s.l. Glacier mass and energy balance modelling shows that the annual mass balance of Olivares Alfa Glacier was close to neutral as a consequence of the AR. Synthetic simulations indicate that without the event the annual balance of Olivares Alfa would have been very negative (between -0.5 and -2.5 m w.e., approximately).
The topic of the article is novel and appropriate for The Cryosphere. The analyses seem adequate, and the main message is interesting and useful for future studies. I suggest that the authors add a few more analyses and clarifications to make the article ready for publication.
MAJOR COMMENTS
1. How rare was this event on glaciers?
I agree with the main comment of reviewer 1. I understand that Valuenzuela et al. (2022) showed a detailed analysis on a regional scale, but it would be useful to know how often such an accumulation event occurs on glaciers in the study area. Can you add some more analysis in this direction? Calculate a return period from Lagunitas data? Or maybe add data from ERA5 and El Yeso meteorological station?
2. Mechanisms that explain the mass balance change
The authors state that “… the impact is not solely from the event itself. Feedback mechanisms related to snow accumulation also impact the mass balance. After the event, ablation diminished due to reduced surface temperatures and increased albedo, which lowered net shortwave radiation, which is the main source of energy for melting during summer” (lines 438-440). So, which was more important? It would be good to answer this question very clearly in the abstract and conclusions. I see that the total snow accumulation at the location of AWS was 164 mm w.e. (Fig. 5) and that the expected ablation without the event ranges between -500 to -2500 m w.e. (Fig. 8). Can you conclude that the main effect of the event was to change the energy balance rather than the mass gain during the event? If this is the case, I think it could be stated more clearly.
I have other suggestions along these lines that could help to understand the effect of the storm on the glacier energy and mass balance.
- Figure 6: Can you add two more panels showing i) albedo and ii) surface temperature? It would be interesting to know for how long the albedo remained high.
- Satellite images: Can you show satellite images to better understand how the AR affected the glacier surface during the rest of the summer? For example, I can see from a Sentinel image of 09.03.2021 that the glacier was already quite dark on that date, but a few days later, a small snowfall brought the albedo back to high values again. So, maybe there were other snowfalls that contributed to keeping the mass balance neutral by increasing the albedo?
3. Hypothetical scenario (“no event”)
This is a very interesting and useful exercise, but the description provided by the authors is very brief. What were the main assumptions made? What were the time series of precipitation, temperature and the other variables that you used? The same as those recorded, except for precipitation? Is surface albedo calculated by the model? How low would have been the glacier albedo without the event?
Figure 8: Can you add a panel showing the albedo in the actual and hypothetical scenario? What was the effect of the small events after the AR on surface albedo?
MINOR COMMENTS
Title: I think that the title is not fully accurate. “Glacier accumulation” is not the most common term. Maybe change to “snow accumulation”, “glacier mass accumulation”, “glacier snow accumulation” or “glacier mass gain”? E.g. “Unseasonal atmospheric river drives anomalous summer snow accumulation on glaciers of the subtropical Andes”.
Data availability: Are the meteorological data going to be available?
21: “… led to substantial snow accumulation on the Maipo River glaciers, confirmed by the post-event snowline …” I don’t think that the low snowline confirms a substantial snow accumulation, because a cold event with low precipitation can also produce a low snowline.
58-62: Can you briefly explain how an AR could produce more melt? Is it because it rains on the glaciers? I thought that an AR was always associated with a precipitation event.
112: The 70% number is originally from a DGA report, maybe check if there is a more recent number? Maybe Álvarez-Garretón or CR2 have calculated a more updated number in recent years.
122: I’m not sure if “two accumulation zones” is technically correct. Maybe say that the accumulation zone is divided in two valleys or cirques.
159: Can you show the sensors along the Olivares Basin on a map?
181: Can you briefly explain how the model distributes meteorological variables? Precipitation, winds? How is snow and ice albedo calculated by the model? What value did you use for ice albedo? From observations or the literature?
191: “detrending the mass balance time series post-event” This is not clear, how was this procedure? Can you provide more details about this experiment? Did you remove all the summer precipitation? Is albedo adjusted by the model? See my major comment 3.
192: “The behavior from previous similar years … was derived and applied to the detrended 2020/2021 accumulated mass balance time series” I don’t follow the procedure. I thought that the experiment consisted only of running the model without the AR event, but did you use information from other years? See my major comment 3.
260: The negative latent heat flux means in this context sublimation, not melt. What happened to the snow deposited by the event? Was it sublimated or melted? Can you provide both amounts? Looking at figure 6, I would say that sublimation dominated over melt after the event.
FIGURES
Figure 1: A, please delete the rest of the political boundaries, or explain what they are. The text refers only to the Maipo River Basin.
Figure 3: Please change the red colour of the ERA5 longwave radiation. It is difficult to distinguish from the black lines. Maybe change this plot from hourly to daily time steps? As it is, the hourly data have a lot of noise.
Figure 4: Can you indicate the event period here?
Figure 5: -> “Time series of the 0°C isotherm around the event”
Figure 5: What is AWS DGA? So, you didn’t use the Ta sensors along the valley to calculate the isotherm?
Figure 5: The number 164.6 mm w.e. is only given here, and it is quite important. Please mention it also in the text.
Figure 6: Please see my main comment 2.
Figure 8: Can you add another panel showing accumulation and ablation separately? I think that would be very useful to understand whether the cause of the neutral mass balance was the snow accumulation during the event or its effect on surface albedo.
Table 2: Can you add a new column with the average fluxes in the days or weeks after the event? This would make it easier to understand the changes caused by the AR (instead of looking at Figure 6).
SUGGESTED TECHNICAL CORRECTIONS
18: add “austral” to “summer”
20: -> “the effects of the AR on the…”
21: Replace “significant” by another term, maybe “massive” or “large”.
25: Introduce the current mega-drought before or maybe just say “a severe drought”. As it is, the sentence assumes that all readers know about the prevailing mega-drought conditions.
35: Delete “during specific periods, such as the hydrological year”
36: -> “there is a typically large interannual variability”
138: -> “strong even for winter events”
150: This sentence is quite orphan. Remove or move to the introduction. Or provide here some more general details.
209: “Pacific coastal grid points” Refer to Figure 2c.
211: Please move “Category 1 being the lowest and …” to line 131 when the categories are first mentioned.
213: -> “by the amount of time” or maybe “duration”
231: “an elevation like January 2021”, which one?
239: “Diurnal cycle” is more precise
250: precise here if the direction of the discrepancy, what is higher and what is lower?
383-385: But this is logical, no? It is the ablation season.
415: “Cortés and Margulis”
425: I think it should be Fig. 4, not 3.
Citation: https://doi.org/10.5194/egusphere-2024-1958-RC2 - AC2: 'Reply on RC2', Claudio Bravo, 12 Nov 2024
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