the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
26 Mar 2021
26 Mar 2021
Shift in seasonal snowpack melt-out date due to light-absorbing particles at a high-altitude site in Central Himalaya
- 1Department of Environmental Science, Stockholm University, Stockholm, Sweden
- 2Atmospheric Composition Research, Finnish Meteorological Institute, Helsinki, Finland
- 3Université Grenoble-Alpes, CNRS, IRD, INP-G, IGE, Grenoble, 38000, France
- 4Institute for Atmospheric and Earth System Research, Faculty of Science, University of Helsinki, Helsinki, Finland
- 5The Energy and Resource Institute, (TERI) New Delhi, India
- 6TERI School of Advanced Studies (TERI SAS), New Delhi, India
- 7Svalbard Integrated Arctic Earth Observing System, Longyearbyen, Norway
- 1Department of Environmental Science, Stockholm University, Stockholm, Sweden
- 2Atmospheric Composition Research, Finnish Meteorological Institute, Helsinki, Finland
- 3Université Grenoble-Alpes, CNRS, IRD, INP-G, IGE, Grenoble, 38000, France
- 4Institute for Atmospheric and Earth System Research, Faculty of Science, University of Helsinki, Helsinki, Finland
- 5The Energy and Resource Institute, (TERI) New Delhi, India
- 6TERI School of Advanced Studies (TERI SAS), New Delhi, India
- 7Svalbard Integrated Arctic Earth Observing System, Longyearbyen, Norway
Abstract. Snow darkening by deposited light-absorbing particles (LAP) has the potential to accelerate snowmelt and shift the snow melt-out date. Here we investigate the sensitivity of the seasonal snow cover duration to changes in LAP at a high altitude valley site in the Central Himalayas, India. First, the variation of the albedo of the seasonal snow was emulated using two seasons of automatic weather station (AWS) data and applying a constant, but realistic deposition of LAP to the snow. Then, the number of days with snowmelt were evaluated based on the estimated net energy budget of the seasonal snow cover and the derived surface temperature. The impact on the energy budget by LAP combined with the melt-day analysis resulted in very simple relations to determine the contribution of LAP to the number of days with snowmelt of the seasonal snow in Himalaya. Above a concentration of 1 ng g-1 (Elemental Carbon equivalent, ECeq, which in this study includes EC and the absorption equivalent EC contribution by other light absorbing particles, such as mineral dust) in new snow, the number of days with snowmelt can be estimated by; days=0.0109(log(〖EC〗_eq )+1)PP±0.0033(log(〖EC〗_eq )+1)PP, where PP is the seasonal precipitation in mm snow water equivalent. A change in ECeq by a factor of two corresponds to about 1/3 of a day per 100 mm precipitation. Although the change in the number of days with melt caused by the changes in ECeq is small, the estimated total change in the snow melt-out date by LAP can be significant. For our realistic base case scenario for the Sunderdhunga Valley, Central Himalayas, India, of ECeq=100 ng g-1 and PP=400 mm, this yields in an advancement of the melt-out date of about 13 days.
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Johan Ström et al.
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RC1: 'Comment on acp-2021-158', Anonymous Referee #1, 26 Apr 2021
This manuscript explores the shift in melt-out date due to deposited LAP at a Central Himalayan site using AWS data. The paper is fairly well written, and the results presented in the article are interesting. However, I have few minor questions before I can recommend it for publishing.
Question 1:
Page 3, Line 104: Authors mentioned that “data was screened for inconsistencies.” However, no clear methodology has been provided on how the inconsistencies were screened. What makes a data point inconsistent?
Question 2:
Page 4, Line 106: Paper uses median for albedo and SD, while a daily average for other data. Why so? Does it create any impact on results if authors use the daily average for albedo and SD as well?
Question 3:
Page 4, Line110: Paper states, “Using a lower emissivity would result in higher Ts, but will not affect the interpretation of the data.” Why so? Some explanation is needed.
Question 4:
Page 11, Line 309-310: “Compared to other reported values for snow these estimates are high, but are close to those reported for ice.” This statement is not entirely clear and needs more explanation on why such a thing will happen if all parameters are used for snow? Also, provide some references for values reported for snow so that a fair comparison can be made.
Question 5:
Page 14, Line 383-385: Authors mentioned “an overestimation of the melting compared to pristine snow.” How much overestimation and compared to which data? Provide some references for comparison and quantify the overestimation.
General comments:
Minimal references are provided in many places, especially in the Introduction. Including suitable and more recent references make it easier for comparison and improvement made from previous studies. Some references in the manuscript are quite old and do not reflect the current state of knowledge with associated research. Here are few key references, which authors should consider including in the manuscript (List is not exhaustive):
Bond, T. C., et al., (2013). Bounding the role of black carbon in the climate system: A scientific assessment. Journal of Geophysical Research: Atmospheres, 118(11), 5380–5552. https://doi.org/10.1002/jgrd.50171
Flanner, M. G., Zender, C. S., Hess, P. G., Mahowald, N. M., Painter, T. H., Ramanathan, V., & Rasch, P. J. (2009). Springtime warming and reduced snow cover from carbonaceous particles. Atmospheric Chemistry and Physics, 9(7), 2481–2497. https://doi.org/10.5194/acp-9-2481-2009
He, C., Takano, Y., & Liou, K.-N. (2017). Close packing effects on clean and dirty snow albedo and associated climatic implications. Geophysical Research Letters, 44(8), 3719–3727. https://doi.org/10.1002/2017GL072916
Lee, W.-L., Liou, K. N., He, C., Liang, H.-C., Wang, T.-C., Li, Q., Liu, Z., & Yue, Q. (2017). Impact of absorbing aerosol deposition on snow albedo reduction over the southern Tibetan plateau based on satellite observations. Theoretical and Applied Climatology, 129(3), 1373–1382. https://doi.org/10.1007/s00704-016-1860-4
Singh, D., Flanner, M. G., & Perket, J. (2015). The global land shortwave cryosphere radiative effect during the MODIS era. The Cryosphere, 9(6), 2057–2070. https://doi.org/10.5194/tc-9-2057-2015
Stephens, G. L., O’Brien, D., Webster, P. J., Pilewski, P., Kato, S., & Li, J. (2015). The albedo of Earth. Reviews of Geophysics, 53(1), 141–163. https://doi.org/10.1002/2014RG000449
Ward, J. L., Flanner, M. G., Bergin, M., Dibb, J. E., Polashenski, C. M., Soja, A. J., & Thomas, J. L. (2018). Modeled Response of Greenland Snowmelt to the Presence of Biomass Burning-Based Absorbing Aerosols in the Atmosphere and Snow. Journal of Geophysical Research: Atmospheres, 123(11), 6122–6141. https://doi.org/10.1029/2017JD027878
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RC2: 'Review of "Shift in seasonal snowpack melt-out date due to light absorbing particles at a high-altitude site in Central Himalaya"', Edward Bair, 18 May 2021
In "Shift in seasonal snowpack melt-out date due to light absorbing particles at a high-altitude site in Central Himalaya", empirical relationships are developed to estimate the impact of light absorbing particles (LAPs) on snowmelt over two seasons at a high-altitude glacierized site in the Central Himalaya.
The motivation for the study is convincing as this part of the world suffers from heavily polluted snow and this pollution affects the melt timing and hence downstream water supply. Likewise, the role of snow albedo on global climate and the hydrological cycle is mentioned.
After carefully reviewing this study, I find overwhelming flaws with the methodology that make the results and conclusions unconvincing. At best, the methods used are outdated and inaccurate. At worst, they are unreliable and not supported by previous research.
Simple statistical relationships, sometimes univariate, are employed that do not account for the relevant processes. For example, the air temperature is used as a key predictive measure for both snow albedo and snow melt even though snowmelt in most midlatitude mountains is driven by net radiation (Marks and Dozier 1992) and albedo is related to a number of snow microstructural parameters that do not depend on air temperature (Flanner and Zender 2006).
The methods for modeling snow albedo and degradation from LAP are also lacking. Snow albedo is difficult to measure and subject to a number of pitfalls that are not addressed. For example, any timeseries of snow albedo will show a decreasing albedo throughout the melt season due to a solar zenith effect alone, as albedo decreases with decreasing solar zenith angle due to the forward-scattering nature of snow. However, illumination conditions are not part of the employed relationship between snow albedo and specific surface area in Equation 2. No adjustment is made for the snow surface topography, which is unlikely to be flat and level at this site. Measured snow albedos above 0.90 and below 0.40 show experimental error and are physically impossible.
The assumption of a constant concentration of LAP (100 ng g^-1) on the snow surface is a poor choice. As stated by the authors, LAPs build on the snow surface and are present in higher quantities during melt when the surface is not being refreshed with new snow. Likewise, the assumption that half of the light absorption comes from dust during is also flawed. Svensson et al. (2021) refer to this exposed layer as the "enriched LAP layer" and report much higher LAP concentrations, with mineral dust having up to 80% of the fraction of light absorption. Since this layer is exposed during spring and summer when insolation is highest, it will have a greater effect on snow melt than other layers.
For ablation estimates, decreasing snow depth is assumed to be ablation while settlement of the snowpack due to normal densification is ignored. These decreases in depth are used to erroneously estimate snow melt.
Last, the data availability section is not compliant with ACP policy.
Because of the shortcomings in the methods employed, I do not find the results convincing, e.g. that the melt out date at this site was decreased by 13 days due to the presence of LAP. The flaws in methodology are extensive enough that I recommend rejection, as I do not believe they can be overcome with revisions. I am sorry that I cannot be more encouraging and suggest the authors employ updated and more sophisticated modeling approaches that account for temporal variability in LAP concentration on the snow surface while addressing all of the pitfalls with in situ measurements of snow albedo.
NB 5/18/21
Works cited
Flanner, M.G., & Zender, C.S. (2006). Linking snowpack microphysics and albedo evolution. Journal of Geophysical Research, 111, D12208
Marks, D., & Dozier, J. (1992). Climate and energy exchange at the snow surface in the alpine region of the Sierra Nevada, 2, Snow cover energy balance. Water Resources Research, 28, 3043-3054
Svensson, J., Ström, J., Honkanen, H., Asmi, E., Dkhar, N.B., Tayal, S., Sharma, V.P., Hooda, R., Leppäranta, M., Jacobi, H.W., Lihavainen, H., & Hyvärinen, A. (2021). Deposition of light-absorbing particles in glacier snow of the Sunderdhunga Valley, the southern forefront of the central Himalayas. Atmos. Chem. Phys., 21, 2931-2943
- AC1: 'Author response on acp-2021-158', Jonas Svensson, 10 Jun 2021
Status: closed
-
RC1: 'Comment on acp-2021-158', Anonymous Referee #1, 26 Apr 2021
This manuscript explores the shift in melt-out date due to deposited LAP at a Central Himalayan site using AWS data. The paper is fairly well written, and the results presented in the article are interesting. However, I have few minor questions before I can recommend it for publishing.
Question 1:
Page 3, Line 104: Authors mentioned that “data was screened for inconsistencies.” However, no clear methodology has been provided on how the inconsistencies were screened. What makes a data point inconsistent?
Question 2:
Page 4, Line 106: Paper uses median for albedo and SD, while a daily average for other data. Why so? Does it create any impact on results if authors use the daily average for albedo and SD as well?
Question 3:
Page 4, Line110: Paper states, “Using a lower emissivity would result in higher Ts, but will not affect the interpretation of the data.” Why so? Some explanation is needed.
Question 4:
Page 11, Line 309-310: “Compared to other reported values for snow these estimates are high, but are close to those reported for ice.” This statement is not entirely clear and needs more explanation on why such a thing will happen if all parameters are used for snow? Also, provide some references for values reported for snow so that a fair comparison can be made.
Question 5:
Page 14, Line 383-385: Authors mentioned “an overestimation of the melting compared to pristine snow.” How much overestimation and compared to which data? Provide some references for comparison and quantify the overestimation.
General comments:
Minimal references are provided in many places, especially in the Introduction. Including suitable and more recent references make it easier for comparison and improvement made from previous studies. Some references in the manuscript are quite old and do not reflect the current state of knowledge with associated research. Here are few key references, which authors should consider including in the manuscript (List is not exhaustive):
Bond, T. C., et al., (2013). Bounding the role of black carbon in the climate system: A scientific assessment. Journal of Geophysical Research: Atmospheres, 118(11), 5380–5552. https://doi.org/10.1002/jgrd.50171
Flanner, M. G., Zender, C. S., Hess, P. G., Mahowald, N. M., Painter, T. H., Ramanathan, V., & Rasch, P. J. (2009). Springtime warming and reduced snow cover from carbonaceous particles. Atmospheric Chemistry and Physics, 9(7), 2481–2497. https://doi.org/10.5194/acp-9-2481-2009
He, C., Takano, Y., & Liou, K.-N. (2017). Close packing effects on clean and dirty snow albedo and associated climatic implications. Geophysical Research Letters, 44(8), 3719–3727. https://doi.org/10.1002/2017GL072916
Lee, W.-L., Liou, K. N., He, C., Liang, H.-C., Wang, T.-C., Li, Q., Liu, Z., & Yue, Q. (2017). Impact of absorbing aerosol deposition on snow albedo reduction over the southern Tibetan plateau based on satellite observations. Theoretical and Applied Climatology, 129(3), 1373–1382. https://doi.org/10.1007/s00704-016-1860-4
Singh, D., Flanner, M. G., & Perket, J. (2015). The global land shortwave cryosphere radiative effect during the MODIS era. The Cryosphere, 9(6), 2057–2070. https://doi.org/10.5194/tc-9-2057-2015
Stephens, G. L., O’Brien, D., Webster, P. J., Pilewski, P., Kato, S., & Li, J. (2015). The albedo of Earth. Reviews of Geophysics, 53(1), 141–163. https://doi.org/10.1002/2014RG000449
Ward, J. L., Flanner, M. G., Bergin, M., Dibb, J. E., Polashenski, C. M., Soja, A. J., & Thomas, J. L. (2018). Modeled Response of Greenland Snowmelt to the Presence of Biomass Burning-Based Absorbing Aerosols in the Atmosphere and Snow. Journal of Geophysical Research: Atmospheres, 123(11), 6122–6141. https://doi.org/10.1029/2017JD027878
-
RC2: 'Review of "Shift in seasonal snowpack melt-out date due to light absorbing particles at a high-altitude site in Central Himalaya"', Edward Bair, 18 May 2021
In "Shift in seasonal snowpack melt-out date due to light absorbing particles at a high-altitude site in Central Himalaya", empirical relationships are developed to estimate the impact of light absorbing particles (LAPs) on snowmelt over two seasons at a high-altitude glacierized site in the Central Himalaya.
The motivation for the study is convincing as this part of the world suffers from heavily polluted snow and this pollution affects the melt timing and hence downstream water supply. Likewise, the role of snow albedo on global climate and the hydrological cycle is mentioned.
After carefully reviewing this study, I find overwhelming flaws with the methodology that make the results and conclusions unconvincing. At best, the methods used are outdated and inaccurate. At worst, they are unreliable and not supported by previous research.
Simple statistical relationships, sometimes univariate, are employed that do not account for the relevant processes. For example, the air temperature is used as a key predictive measure for both snow albedo and snow melt even though snowmelt in most midlatitude mountains is driven by net radiation (Marks and Dozier 1992) and albedo is related to a number of snow microstructural parameters that do not depend on air temperature (Flanner and Zender 2006).
The methods for modeling snow albedo and degradation from LAP are also lacking. Snow albedo is difficult to measure and subject to a number of pitfalls that are not addressed. For example, any timeseries of snow albedo will show a decreasing albedo throughout the melt season due to a solar zenith effect alone, as albedo decreases with decreasing solar zenith angle due to the forward-scattering nature of snow. However, illumination conditions are not part of the employed relationship between snow albedo and specific surface area in Equation 2. No adjustment is made for the snow surface topography, which is unlikely to be flat and level at this site. Measured snow albedos above 0.90 and below 0.40 show experimental error and are physically impossible.
The assumption of a constant concentration of LAP (100 ng g^-1) on the snow surface is a poor choice. As stated by the authors, LAPs build on the snow surface and are present in higher quantities during melt when the surface is not being refreshed with new snow. Likewise, the assumption that half of the light absorption comes from dust during is also flawed. Svensson et al. (2021) refer to this exposed layer as the "enriched LAP layer" and report much higher LAP concentrations, with mineral dust having up to 80% of the fraction of light absorption. Since this layer is exposed during spring and summer when insolation is highest, it will have a greater effect on snow melt than other layers.
For ablation estimates, decreasing snow depth is assumed to be ablation while settlement of the snowpack due to normal densification is ignored. These decreases in depth are used to erroneously estimate snow melt.
Last, the data availability section is not compliant with ACP policy.
Because of the shortcomings in the methods employed, I do not find the results convincing, e.g. that the melt out date at this site was decreased by 13 days due to the presence of LAP. The flaws in methodology are extensive enough that I recommend rejection, as I do not believe they can be overcome with revisions. I am sorry that I cannot be more encouraging and suggest the authors employ updated and more sophisticated modeling approaches that account for temporal variability in LAP concentration on the snow surface while addressing all of the pitfalls with in situ measurements of snow albedo.
NB 5/18/21
Works cited
Flanner, M.G., & Zender, C.S. (2006). Linking snowpack microphysics and albedo evolution. Journal of Geophysical Research, 111, D12208
Marks, D., & Dozier, J. (1992). Climate and energy exchange at the snow surface in the alpine region of the Sierra Nevada, 2, Snow cover energy balance. Water Resources Research, 28, 3043-3054
Svensson, J., Ström, J., Honkanen, H., Asmi, E., Dkhar, N.B., Tayal, S., Sharma, V.P., Hooda, R., Leppäranta, M., Jacobi, H.W., Lihavainen, H., & Hyvärinen, A. (2021). Deposition of light-absorbing particles in glacier snow of the Sunderdhunga Valley, the southern forefront of the central Himalayas. Atmos. Chem. Phys., 21, 2931-2943
- AC1: 'Author response on acp-2021-158', Jonas Svensson, 10 Jun 2021
Johan Ström et al.
Johan Ström et al.
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