the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
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
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.
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Yuxuan Xing et al.
Status: open (until 17 Oct 2023)
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RC1: 'Comment on egusphere-2023-1443', Anonymous Referee #1, 27 Sep 2023
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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
Yuxuan Xing et al.
Yuxuan Xing et al.
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