Dust storms from the Taklamakan Desert significantly darken snow surface on surrounding mountains

Xing, Yuxuan; Chen, Yang; Yan, Shirui; Shi, Tenglong; Cao, Xiaoyi; Niu, Xiaoying; Wu, Dongyou; Cui, Jiecan; Wang, Xin; Pu, Wei

doi:https://doi.org/10.5194/egusphere-2023-1443

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https://doi.org/10.5194/egusphere-2023-1443

Preprints

05 Sep 2023

| 05 Sep 2023

Dust storms from the Taklamakan Desert significantly darken snow surface on surrounding mountains

Yuxuan Xing, Yang Chen, Shirui Yan, Tenglong Shi, Xiaoyi Cao, Xiaoying Niu, Dongyou Wu, Jiecan Cui, Xin Wang, and Wei Pu

Abstract. The Taklamakan Desert (TD) is a major source of mineral dust emissions into the atmosphere. These dust particles have the ability to darken the surface of snow on the surrounding high mountains after deposition, significantly impacting the regional radiation balance. However, previous field measurements have been unable to capture the effects of severe dust storms accurately, and their representation on regional scales has been inadequate. In this study, we propose a modified remote-sensing approach that combines data from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite and simulations from the Snow, Ice, and Aerosol Radiative (SNICAR) model. This approach allows us to detect and analyze the substantial snow darkening resulting from dust storm deposition. We focus on three typical dust events originating from the Taklamakan Desert and observe significant snow darkening over an area of >2100, >600, and >630 km² in the Tien Shan, Kunlun, and Qilian Mountains, respectively. Our findings reveal that the impact of dust storms extends beyond the local high mountains, reaching mountains located approximately 1000 km away from the source. Furthermore, we observe that dust storms not only darken the snowpack during the spring but also in the summer and autumn seasons, leading to increased absorption of solar radiation. Specifically, the snow albedo reduction (radiative forcing) triggered by severe dust depositions is up to 0.028–0.079 (11–31.5 W m⁻²), 0.088–0.136 (31–49 W m⁻²), and 0.092–0.153 (22–38 W m⁻²) across the Tien Shan, Kunlun, and Qilian Mountains, respectively. This further contributes to the aging of the snow, as evidenced by the growth of snow grain size. Comparatively, the impact of persistent but relatively slow dust deposition over several months during non-event periods is significantly lower than that of individual dust event. This highlights the necessity of giving more attention to the influence of extreme events on the regional radiation balance. Through this study, we gain a deeper understanding of how a single dust event can affect the extensive snowpack and demonstrates the potential of employing satellite remote-sensing to monitor large-scale snow darkening.

Received: 29 Jun 2023 – Discussion started: 05 Sep 2023

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Yuxuan Xing, Yang Chen, Shirui Yan, Tenglong Shi, Xiaoyi Cao, Xiaoying Niu, Dongyou Wu, Jiecan Cui, Xin Wang, and Wei Pu

Status: closed

RC1:
'Comment on egusphere-2023-1443', Anonymous Referee #1, 27 Sep 2023
Your work is very interesting, but I have a serious concern. You haven't discussed the potential uncertainties and how they might influence your conclusions. Convincing dust-induced snow-darkening within three days using MODIS/CALIOP daily snapshots is quite tricky. Wouldn’t the diurnal variabilities that MODIS misses cause significant biases? Could the dust in the atmosphere introduce biases in the MODIS view of the surface? Considering that CALIOP's track is merely a line over a MODIS granule, might assuming vertical profiles and aerosol types along the CALIOP track for the entire MODIS domain introduce biases in your analysis? It would be helpful if you could add a section summarizing, and if possible, quantifying these uncertainties.

Consider adding a map to indicate the regions you are referring to, especially in the introduction part. You could perhaps zoom out Figure 2(a).

Good job listing a comprehensive set of references.

Since MODIS observes only once or twice per day, are you using simulations to minimize biases due to such sparse observations? (It seems like you're using models to "retrieve the dust content of the snowpack.")

How significant is the diurnal variation of snow albedo for your estimations? It's possible that dust-induced darkening exhibits robust diurnal variability, which could introduce significant biases into your estimations.

Regarding CALIOP, it's important to clarify if you assumed the type of aerosol and its vertical profile to be the same across the entire MODIS image.

In the section discussing the radiative transfer models, you mention two models: one for obtaining contaminated snow and the other for simulating atmospheric radiative transfer. However, you don't explain how these two models are used or combined. This section needs more clarity.

Lines 161-163 mention that the SNICAR model provides spectral albedo, but lines 190-192 suggest you used the same model to derive snow grain size and dust content. This is confusing and should be clarified.

In general, the radiative transfer part of your work lacks clarity and should be improved.

In Section 3.1.1 (Figure 3) (and also in the other 2 examples), you aim to demonstrate dust-induced snow-darkening within three days using MODIS/CALIOP snapshots. It's important to address whether the surface reflectance product in MODIS could be affected by dust aerosols. Consider checking and showing CALIOP feature curtains (similar to your Figure 3j) for all three days to ensure that the darkening isn't due to atmospheric dust particles but rather snow-darkening.

Line 23: Why >2100, >600,… km^2? Why can’t put the approximated area?

Line 35: ‘Through’ -> ‘From’

Line 48: satellite- -> satellite

Line 56: I am not quite sure what ‘imbalance’ you are referring to here
Citation: https://doi.org/10.5194/egusphere-2023-1443-RC1
- AC2: 'Reply on RC1', Yuxuan Xing, 24 Feb 2024
  
  Thank you very much for the positive comments, which will encourage us to do more in-depth research in the future. Moreover, your comments are quite significant that can help us to improve the paper quality substantially. We have addressed all of the comments carefully according to the suggestions. Please see the supplement.
  
  Citation: https://doi.org/10.5194/egusphere-2023-1443-AC2
RC2:
'Comment on egusphere-2023-1443', Anonymous Referee #3, 20 Dec 2023
Review of the manuscript titled “Dust storms from the Taklamakan Desert significantly darken snow surface on surrounding mountains”
The manuscript titled “Dust storms from the Taklamakan Desert significantly darken snow surface on surrounding mountains” by Xing et al. focuses on the dust storm events from the Taklamakan desert and its influence on snow darkening processes over the distinct mountains in the High mountain Asia using the remote sensing techniques and modelling. This work is very interesting and novel. I have some major concerns and comments which can be incorporated during the revision process. First of all, the models and the remote sensing data sets used in this study needs more clarification. The estimated radiative forcing needs more clarity. Several places authors mentioned that the dust content is derived using SNICAR model. It is confusing, and it needs further clarification and explanation. Also, the authors have used only very few cases in this study regarding the dust storm events, and some of the observations are from long ago. I would really recommend the authors to add some more dust storm event cases to this study. Further, I would recommend the authors add in detail about the uncertainties of this study.
Line 41: Appropriate references for this statement. I would also recommend the authors to add the differences in the observations of light absorbing aerosols from the polar regions and HMA in the introduction section ( for eg: Gogoi et al., 2021a, Gogoi et al., 2018, Chaubey et al., 2010 etc.).
M. Gogoi, S. Suresh Babu, Santosh K. Pandey, Vijayakumar S. Nair, et al., Scavenging ratio of black carbon in the Arctic and the Antarctic, Polar Science 16 (2018).

Gogoi, M.M., Pandey, S.K., Arun, B.S., Nair, V.S., Kumar, S., Vaishya, A., Prijith, S.S., Hegde, P., Babu, S.S., 2021b. Long-term changes in aerosol radiative properties over Ny-Ålesund : Results from Indian scientific expeditions to the Arctic. https://doi.org/10.1016/j.polar.2021.100700

Jai Prakash Chaubey, Krishna Moorthy, S. Suresh Babu, Vijayakumar S. Nair et al., Black carbon aerosols over coastal Antarctica and its scavenging by snow during the Southern Hemispheric summer, 2010. https://doi.org/10.1029/2009JD013381

Line 52: There are several studies from the Himalayan region, where higher concentrations of light-absorbing aerosols were reported from the atmosphere and snow. I would recommend using those references here. For eg: these are some of them.
Thakur, R.C., Arun, B.S., Gogoi, M.M., Thamban, M., Thayyen, R.J., Redkar, B.L., Babu, S.S., 2021. Multi-layer distribution of Black Carbon and Inorganic Ions in the Snow-packs of western Himalayas and Snow Albedo Forcing. Atmos Environ 261, 118564. https://doi.org/10.1016/j.atmosenv.2021.118564

Arun, B.S., Aswini, A.R., Gogoi, M.M., Hegde, P., Kumar Kompalli, S., Sharma, P., Suresh Babu, S., 2019. Physico-chemical and optical properties of aerosols at a background site (~4 km a.s.l.) in the western Himalayas. Atmos Environ 218, 117017. https://doi.org/10.1016/j.atmosenv.2019.117017

Arun, B.S., Gogoi, M.M., Borgohain, A., Hegde, P., Kundu, S.S., Babu, S.S., 2021. Role of sulphate and carbonaceous aerosols on the radiative effects of aerosols over a remote high-altitude site Lachung in the Eastern Himalayas. Atmos Res 263. https://doi.org/10.1016/j.atmosres.2021.105799

S. Arun, M. M. Gogoi, P. Hegde, A. Borgohain, Suresh K. R. Boreddy, S. S. Kundu, and S. S. Babu, 2021, Carbonaceous Aerosols over Lachung in the Eastern Himalayas: Primary Sources and Secondary Formation of Organic Aerosols in a Remote High-Altitude Environment, ACS Earth Space Chem. 2021. https://doi.org/10.1021/acsearthspacechem.1c00190

Gogoi, M.M., Babu, S.S., Arun, B.S., Moorthy, K.K., Ajay, A., Ajay, P., Suryavanshi, A., Borgohain, A., Guha, A., Shaikh, A., Pathak, B., Gharai, B., Ramasamy, B., Balakrishnaiah, G., Menon, H.B., Kuniyal, J.C., Srivastava, P., Singh, R.S., Kumar, R., Rastogi, S., 2021a. Response of ambient BC concentration across the Indian region to the nation-wide lockdown : results from the ARFINET measurements of 341–351.

Line 81: I would recommend the authors to add more references for the atmospheric measurements of dust aerosols in the HMA region. For example; Arun et al., 2019 etc.
Line 88: “_” correct it
Line 115: Using SNICAR, is it possible to retrieve the dust content? Needs clarification.
Line 123: Since the authors have used different remote sensing data sets with different spatial resolutions, I would recommend the authors to add the details regarding the uncertainties in this study related to it and add more details about the data products.
Line 163: I recommend the authors also go through the publication by Thakur et al., 2021 since it explains the multilayer distribution of LAP’s in snow and snow albedo reduction.
Line 166: This is not clear to me. And the cited reference seems too old in this case. SNICAR was released after 2000. Explain more about it.
Line 171 : How the authors have identified the clear and cloudy conditions during this study period? How did the authors combine these two data sets for the estimation?
Line 194: How the authors have derived the snow grain size and dust content from the SNICAR model since this model is used to estimate albedo based on the user input of these parameters? Which needs clear clarification and explanation.
Line 195: Explain in detail quantitatively about how the authors coupled the SNICAR and SBDART with all the atmospheric conditions in these two distinct models.
Figure -1: Some of the labels are missing
Line 209: Explain quantitatively about the bias
Line 253: I would not completely agree with this assumption since the absorbing ability of BC is more compared to dust.
Line 287: Since the authors considered only two typical cases in this. I would recommend the authors to have some more multiple dust event cases in this study.
Line 378: Explain the significance of diurnal variation of snow albedo for your estimations biases in your estimations.
Figure -3 , 5, 6 and 7: I would recommend to authors to make a clearer figure instead of keeping everything together.
Line 483: Why the authors have considered an old dust event in this study.
Line 594: Give the references
Line 618: Conclusions in this study need to be concise and clear.
Citation: https://doi.org/10.5194/egusphere-2023-1443-RC2
- AC3: 'Reply on RC2', Yuxuan Xing, 24 Feb 2024
  
  Thank you very much for the positive comments, which will encourage us to do more in-depth research in the future. Moreover, your comments are quite significant that can help us to improve the paper quality substantially. We have addressed all of the comments carefully according to the suggestions. Please see the supplement.
  
  Citation: https://doi.org/10.5194/egusphere-2023-1443-AC3
AC1: 'Comment on egusphere-2023-1443', Yuxuan Xing, 24 Feb 2024

Thank you very much for the positive comments, which will encourage us to do more in-depth research in the future. Moreover, the referee’s comments are quite significant that can help us to improve the paper quality substantially. We have addressed all of the comments carefully according to the suggestions. Please see our point-by-point responses in the supplement.

Citation: https://doi.org/10.5194/egusphere-2023-1443-AC1

Status: closed

RC1:
'Comment on egusphere-2023-1443', Anonymous Referee #1, 27 Sep 2023
Your work is very interesting, but I have a serious concern. You haven't discussed the potential uncertainties and how they might influence your conclusions. Convincing dust-induced snow-darkening within three days using MODIS/CALIOP daily snapshots is quite tricky. Wouldn’t the diurnal variabilities that MODIS misses cause significant biases? Could the dust in the atmosphere introduce biases in the MODIS view of the surface? Considering that CALIOP's track is merely a line over a MODIS granule, might assuming vertical profiles and aerosol types along the CALIOP track for the entire MODIS domain introduce biases in your analysis? It would be helpful if you could add a section summarizing, and if possible, quantifying these uncertainties.

Consider adding a map to indicate the regions you are referring to, especially in the introduction part. You could perhaps zoom out Figure 2(a).

Good job listing a comprehensive set of references.

Since MODIS observes only once or twice per day, are you using simulations to minimize biases due to such sparse observations? (It seems like you're using models to "retrieve the dust content of the snowpack.")

How significant is the diurnal variation of snow albedo for your estimations? It's possible that dust-induced darkening exhibits robust diurnal variability, which could introduce significant biases into your estimations.

Regarding CALIOP, it's important to clarify if you assumed the type of aerosol and its vertical profile to be the same across the entire MODIS image.

In the section discussing the radiative transfer models, you mention two models: one for obtaining contaminated snow and the other for simulating atmospheric radiative transfer. However, you don't explain how these two models are used or combined. This section needs more clarity.

Lines 161-163 mention that the SNICAR model provides spectral albedo, but lines 190-192 suggest you used the same model to derive snow grain size and dust content. This is confusing and should be clarified.

In general, the radiative transfer part of your work lacks clarity and should be improved.

In Section 3.1.1 (Figure 3) (and also in the other 2 examples), you aim to demonstrate dust-induced snow-darkening within three days using MODIS/CALIOP snapshots. It's important to address whether the surface reflectance product in MODIS could be affected by dust aerosols. Consider checking and showing CALIOP feature curtains (similar to your Figure 3j) for all three days to ensure that the darkening isn't due to atmospheric dust particles but rather snow-darkening.

Line 23: Why >2100, >600,… km^2? Why can’t put the approximated area?

Line 35: ‘Through’ -> ‘From’

Line 48: satellite- -> satellite

Line 56: I am not quite sure what ‘imbalance’ you are referring to here
Citation: https://doi.org/10.5194/egusphere-2023-1443-RC1
- AC2: 'Reply on RC1', Yuxuan Xing, 24 Feb 2024
  
  Thank you very much for the positive comments, which will encourage us to do more in-depth research in the future. Moreover, your comments are quite significant that can help us to improve the paper quality substantially. We have addressed all of the comments carefully according to the suggestions. Please see the supplement.
  
  Citation: https://doi.org/10.5194/egusphere-2023-1443-AC2
RC2:
'Comment on egusphere-2023-1443', Anonymous Referee #3, 20 Dec 2023
Review of the manuscript titled “Dust storms from the Taklamakan Desert significantly darken snow surface on surrounding mountains”
The manuscript titled “Dust storms from the Taklamakan Desert significantly darken snow surface on surrounding mountains” by Xing et al. focuses on the dust storm events from the Taklamakan desert and its influence on snow darkening processes over the distinct mountains in the High mountain Asia using the remote sensing techniques and modelling. This work is very interesting and novel. I have some major concerns and comments which can be incorporated during the revision process. First of all, the models and the remote sensing data sets used in this study needs more clarification. The estimated radiative forcing needs more clarity. Several places authors mentioned that the dust content is derived using SNICAR model. It is confusing, and it needs further clarification and explanation. Also, the authors have used only very few cases in this study regarding the dust storm events, and some of the observations are from long ago. I would really recommend the authors to add some more dust storm event cases to this study. Further, I would recommend the authors add in detail about the uncertainties of this study.
Line 41: Appropriate references for this statement. I would also recommend the authors to add the differences in the observations of light absorbing aerosols from the polar regions and HMA in the introduction section ( for eg: Gogoi et al., 2021a, Gogoi et al., 2018, Chaubey et al., 2010 etc.).
M. Gogoi, S. Suresh Babu, Santosh K. Pandey, Vijayakumar S. Nair, et al., Scavenging ratio of black carbon in the Arctic and the Antarctic, Polar Science 16 (2018).

Gogoi, M.M., Pandey, S.K., Arun, B.S., Nair, V.S., Kumar, S., Vaishya, A., Prijith, S.S., Hegde, P., Babu, S.S., 2021b. Long-term changes in aerosol radiative properties over Ny-Ålesund : Results from Indian scientific expeditions to the Arctic. https://doi.org/10.1016/j.polar.2021.100700

Jai Prakash Chaubey, Krishna Moorthy, S. Suresh Babu, Vijayakumar S. Nair et al., Black carbon aerosols over coastal Antarctica and its scavenging by snow during the Southern Hemispheric summer, 2010. https://doi.org/10.1029/2009JD013381

Line 52: There are several studies from the Himalayan region, where higher concentrations of light-absorbing aerosols were reported from the atmosphere and snow. I would recommend using those references here. For eg: these are some of them.
Thakur, R.C., Arun, B.S., Gogoi, M.M., Thamban, M., Thayyen, R.J., Redkar, B.L., Babu, S.S., 2021. Multi-layer distribution of Black Carbon and Inorganic Ions in the Snow-packs of western Himalayas and Snow Albedo Forcing. Atmos Environ 261, 118564. https://doi.org/10.1016/j.atmosenv.2021.118564

Arun, B.S., Aswini, A.R., Gogoi, M.M., Hegde, P., Kumar Kompalli, S., Sharma, P., Suresh Babu, S., 2019. Physico-chemical and optical properties of aerosols at a background site (~4 km a.s.l.) in the western Himalayas. Atmos Environ 218, 117017. https://doi.org/10.1016/j.atmosenv.2019.117017

Arun, B.S., Gogoi, M.M., Borgohain, A., Hegde, P., Kundu, S.S., Babu, S.S., 2021. Role of sulphate and carbonaceous aerosols on the radiative effects of aerosols over a remote high-altitude site Lachung in the Eastern Himalayas. Atmos Res 263. https://doi.org/10.1016/j.atmosres.2021.105799

S. Arun, M. M. Gogoi, P. Hegde, A. Borgohain, Suresh K. R. Boreddy, S. S. Kundu, and S. S. Babu, 2021, Carbonaceous Aerosols over Lachung in the Eastern Himalayas: Primary Sources and Secondary Formation of Organic Aerosols in a Remote High-Altitude Environment, ACS Earth Space Chem. 2021. https://doi.org/10.1021/acsearthspacechem.1c00190

Gogoi, M.M., Babu, S.S., Arun, B.S., Moorthy, K.K., Ajay, A., Ajay, P., Suryavanshi, A., Borgohain, A., Guha, A., Shaikh, A., Pathak, B., Gharai, B., Ramasamy, B., Balakrishnaiah, G., Menon, H.B., Kuniyal, J.C., Srivastava, P., Singh, R.S., Kumar, R., Rastogi, S., 2021a. Response of ambient BC concentration across the Indian region to the nation-wide lockdown : results from the ARFINET measurements of 341–351.

Line 81: I would recommend the authors to add more references for the atmospheric measurements of dust aerosols in the HMA region. For example; Arun et al., 2019 etc.
Line 88: “_” correct it
Line 115: Using SNICAR, is it possible to retrieve the dust content? Needs clarification.
Line 123: Since the authors have used different remote sensing data sets with different spatial resolutions, I would recommend the authors to add the details regarding the uncertainties in this study related to it and add more details about the data products.
Line 163: I recommend the authors also go through the publication by Thakur et al., 2021 since it explains the multilayer distribution of LAP’s in snow and snow albedo reduction.
Line 166: This is not clear to me. And the cited reference seems too old in this case. SNICAR was released after 2000. Explain more about it.
Line 171 : How the authors have identified the clear and cloudy conditions during this study period? How did the authors combine these two data sets for the estimation?
Line 194: How the authors have derived the snow grain size and dust content from the SNICAR model since this model is used to estimate albedo based on the user input of these parameters? Which needs clear clarification and explanation.
Line 195: Explain in detail quantitatively about how the authors coupled the SNICAR and SBDART with all the atmospheric conditions in these two distinct models.
Figure -1: Some of the labels are missing
Line 209: Explain quantitatively about the bias
Line 253: I would not completely agree with this assumption since the absorbing ability of BC is more compared to dust.
Line 287: Since the authors considered only two typical cases in this. I would recommend the authors to have some more multiple dust event cases in this study.
Line 378: Explain the significance of diurnal variation of snow albedo for your estimations biases in your estimations.
Figure -3 , 5, 6 and 7: I would recommend to authors to make a clearer figure instead of keeping everything together.
Line 483: Why the authors have considered an old dust event in this study.
Line 594: Give the references
Line 618: Conclusions in this study need to be concise and clear.
Citation: https://doi.org/10.5194/egusphere-2023-1443-RC2
- AC3: 'Reply on RC2', Yuxuan Xing, 24 Feb 2024
  
  Thank you very much for the positive comments, which will encourage us to do more in-depth research in the future. Moreover, your comments are quite significant that can help us to improve the paper quality substantially. We have addressed all of the comments carefully according to the suggestions. Please see the supplement.
  
  Citation: https://doi.org/10.5194/egusphere-2023-1443-AC3
AC1: 'Comment on egusphere-2023-1443', Yuxuan Xing, 24 Feb 2024

Thank you very much for the positive comments, which will encourage us to do more in-depth research in the future. Moreover, the referee’s comments are quite significant that can help us to improve the paper quality substantially. We have addressed all of the comments carefully according to the suggestions. Please see our point-by-point responses in the supplement.

Citation: https://doi.org/10.5194/egusphere-2023-1443-AC1

Yuxuan Xing, Yang Chen, Shirui Yan, Tenglong Shi, Xiaoyi Cao, Xiaoying Niu, Dongyou Wu, Jiecan Cui, Xin Wang, and Wei Pu

Supplement

https://doi.org/10.5194/egusphere-2023-1443-supplement

Yuxuan Xing, Yang Chen, Shirui Yan, Tenglong Shi, Xiaoyi Cao, Xiaoying Niu, Dongyou Wu, Jiecan Cui, Xin Wang, and Wei Pu

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Short summary

A study investigated the impact of dust storms from the Taklamakan Desert on surrounding high mountains and regional radiation balance. Using satellite data and simulations, researchers found that dust storms significantly darken the snow surface in the Tien Shan, Kunlun, and Qilian Mountains, reaching mountains up to 1000 km away. This darkening occurs not only in spring but also during summer and autumn, leading to increased absorption of solar radiation.


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