Multiple Remotely Sensed Lines of Evidence for a Depleting Seasonal Snowpack in the Near East

Round 1

Reviewer 1 Report

The manuscript conducts an exploratory analysis in order to investigate the role of the snowpack in the observed decrease in water storage of the transboundary basins of the Near East region. The authors analyze several snow-related satellite retrievals (optical, passive microwave and gravimetric) and a new meteorological reanalysis data set for this region. This is an interesting and helpful research on cold regions hydrology. And some important results are concluded in it. it should be published in Remote Sensing. However, it needs some revisions as indicated by my personal reading.

1)       Add a map of spatial distribution of SCD in the study area. It is very helpful for understand the spatial pattern of snow cover. And revised the presentation of Fig.5 (reference Fig.8 of the following article).  I suggest you add this article in the references.

Zhiguang Tang, Xiaoru Wang,Jian Wang，Xin Wang，Hongyi Li，Zongli Jiang. Spatiotemporal Variation of Snow Cover in Tianshan Mountains, Central Asia, Based on Cloud-Free MODIS Fractional Snow Cover Product, 2001–2015, Remote Sensing, 2017, 9 (10): 1045.

2)       There are some uncertainties in the several snow-related satellite retrievals. All these uncertainties will bring errors in your analysis results. So, you should better mention them in the Discussion.

3)       In my view, for the terrestrial water storage anomalies, the role of glacier, lakes changes are more important than the snow cover.  But you have not considered the glacier and lakes.   

Author Response

Reply to Reviewer 1

We are grateful to the reviewer for the thoughtful comments and suggestions to our manuscript. We have com- piled a revised version and in the following provide a point-by-point reply to all issues raised. The reviewer’s comments appear in blue and our replies are in black. Excerpts from and changes to the manuscript are quoted in italics. Page and line numbers refer to positions in the original manuscript.

Reviewer 1 : The manuscript conducts an exploratory analysis in order to investigate the role of the snowpack in the observed decrease in water storage of the transboundary basins of the Near East region. The authors analyze several snow-related satellite retrievals (optical, passive microwave and gravimetric) and a new me- teorological reanalysis data set for this region. This is an interesting and helpful research on cold regions hydrology. And some important results are concluded in it. it should be published in Remote Sensing. How- ever, it needs some revisions as indicated by my personal reading.

Point 1 : Add a map of spatial distribution of SCD in the study area. It is very helpful for understand the spatial pattern of snow cover. And revised the presentation of Fig.5 (reference Fig.8 of the following article). I suggest you add this article in the references.
Zhiguang Tang, Xiaoru Wang, Jian Wang, Xin Wang, Hongyi Li, Zongli Jiang. Spatiotemporal variation of Snow Cover in Tianshan Mountains, Central Asia, Based on Cloud-Free MODIS Fractional Snow Cover Prod- uct, 2001-2015, 2017, 9 (10): 1045.

Response : A map which shows the mean spatial distribution of SCD over the study area is added to Appendix A2. The suggested article was added to the references in Section 3.2 and Section 4.6. In Fig.5, we show two high resolution maps from both the Aqua and Terra satellites. Separating the overlapping layers on the map as suggested (significance, trends, and change percentage) will create 6 maps which can make it difficult to see the details in high resolution. The black contour lines are already very helpful to show the significantly changing grids. We thus kept Fig.5 in original form. In our opinion, the maps with absolute SCD trends (rather than relative changes) are more meaningful especially now that they are (following the reviewer’s suggestion) accompanied by a reference map showing the SCD climatology (Fig. A2).

Point 2 : There are some uncertainties in the several snow-related satellite retrievals. All these uncertainties will bring errors in your analysis results. So, you should better mention them in the Discussion.

Response : A new section (Section 4.6) is added to discuss the limitations of the study. We mentioned the uncertainties in the snow-related satellite retrievals under this section in the revised manuscript.

Point 3 : In my view, for the terrestrial water storage anomalies, the role of glacier, lakes changes are more important than the snow cover. But you have not considered the glacier and lakes.

Response : In order to address the role of glaciers and lakes, we need to decompose the total water storage into its components. Previous studies on this issue are cited in the related parts of the manuscript. In our exploratory study, we are only interested in the observational evidence on the relationship between the mountain snowpack and the decrease in water storage. In the analyses, we excluded the grid cells on the biggest lake (the Lake Van) of the study domain. It is worth noting that glaciers make up a very small part of our study domain and are thus do not contribute more to the regional TWS than the seasonal snowpack. We discuss these issues in the limitations part of the revised manuscript (Section 4.6).

Thank you once again for all the helpful comments and suggestions, On behalf of all the co-authors,
Yeliz A. Yılmaz

Author Response File: Author Response.pdf

Reviewer 2 Report

The authors of this study conducted the trend analysis of snowpack over a mountain region using several remote sensing products and, at the same time, carried out the trend analysis of meteorological reanalysis dataset.

Introduction provides sufficient background for the study, however, at first It needs global antecedents of the problem of snow depletion and to explain the role of the remote sensing at monitoring snowpack. Figure 1 must be in the study area section and both images don't have the same scale. Besides, any names in the figure 1 in color black can't well appreciated.

Overall, the methodologies used for the analysis are sound. However, the major issue of this study is the length of the data used for the analysis. For climate change related impact analysis such as trend analysis of environmental variables, data with a length of MODIS and AMSR datasets are too short. By a common consensus, this kind of analysis needs at least 30 years’ data.  A longer period of data for this analysis is indeed needed or should be included in the discussion this topic. In the other hand, it's not clear where was used MODIS monthly product and how was used 8-days composite at postprocessing if this product is the maximun snow extent in 8 days. Finally, It's necessary add what is the overall cloud cover percentage remaining of the MODIS 8 day composites for the trend analysis.

Some additional comments

-Snowfall and sublimation ratio must be explained in the methodoloy previously 

-Figure 10 is from results or conclusion?

Author Response

Reply to Reviewer 2

We are grateful to the reviewer for the thoughtful comments and suggestions to our manuscript. We have com- piled a revised version and in the following provide a point-by-point reply to all issues raised. The reviewer’s comments appear in blue and our replies are in black. Excerpts from and changes to the manuscript are quoted in italics. Page and line numbers refer to positions in the original manuscript.

Reviewer 2 : The authors of this study conducted the trend analysis of snowpack over a mountain region using several remote sensing products and, at the same time, carried out the trend analysis of meteorological reanal- ysis dataset.

Point 1 : Introduction provides sufficient background for the study, however, at first It needs global antecedents of the problem of snow depletion and to explain the role of the remote sensing at monitoring snowpack.

Response : Recent and relevant global snow-cover trend studies, specifically the ones focusing on the role of remote sensing in monitoring snowpack are mentioned in the Introduction part of the revised manuscript. An example sentence is below:

Observations from space play an important role in monitoring changes in the state of the Earth’s surface (Bal- samo et al. (2018); Yang et al. (2013); Guo et al. (2015)) including the global terrestrial water storage Rodell et al. (2018) and the snowpack (Bormann et al. (2018); Hammond et al. (2018)).

Point 2 : Figure 1 must be in the study area section and both images don’t have the same scale. Besides, any names in the figure 1 in color black can’t well appreciated.

Response : In Fig.1, the difference between the scales of the maps was because we wanted to show the en- compassing region in the left panel, and a more zoomed view of the basins on the right panel. According to the reviewer’s suggestion, we have modified Fig.1 by changing the scale, and the colors of the names to white in both panels.

Point 3 : Overall, the methodologies used for the analysis are sound. However, the major issue of this study is the length of the data used for the analysis. For climate change related impact analysis such as trend analysis of environmental variables, data with a length of MODIS and AMSR datasets are too short. By a common consensus, this kind of analysis needs at least 30 years’ data. A longer period of data for this analysis is indeed needed or should be included in the discussion this topic.

Response : Although it’d be great to have longer time series, the MODIS record is now 19 years which is pushing two decades. This should be plenty for trend analysis especially given that 30-year period defined by the World Meteorological Organization (WMO) is rather arbitrary (see discussions in Arguez and Vose (2011)). We discussed this issue as a limitation in the newly added Section 4.6 in the revised version of the manuscript. To support our claim one need only look at the myriad of other recent studies that use the MODIS records for trend analyses (e.g. Akyurek et al., 2011; Gokmen et al., 2013; Gascoin et al., 2015; Swanson, 2017; Tang et al., 2017; Bormann et al., 2018; Hammond et al., 2018).

Point 4 : In the other hand, it’s not clear where was used MODIS monthly product and how was used 8-days composite at postprocessing if this product is the maximun snow extent in 8 days. Finally, It’s necessary add what is the overall cloud cover percentage remaining of the MODIS 8 day composites for the trend analysis.

Response : We used monthly MODIS product to show the climatology of fractional snow-cover for each basin in Fig. 4. To describe it explicitly, we extended the the Section 3.2 by adding the following sentences.

We use the monthly MODIS product solely to calculate the climatology of the fractional snow-covered area for each basin (see Fig. 4). For this climatology, merged MODIS retrievals from Terra and Aqua are obtained by combining two data sets to get longer and more accurate time series. For each time step, we selected the higher value from either Aqua (MYD10CM) or Terra (MOD10CM).

The 8-day MODIS product was used to estimate the snow-cover duration (SCD) as described in Section 3.2. The spatial coverage of the cloud cover percentage in the excluded 8-day MODIS data is added as Appendix (Fig. A2).

Point 5 : Some additional comments
-Snowfall and sublimation ratio must be explained in the methodoloy previously

Response : The formula for snowfall and sublimation ratio explained in the Section 3.4 under the Data and Methods part of the revised manuscript.

-Figure 10 is from results or conclusion?

Response : Figure 10 belongs to the Results section. Due to the page limits, it was located in the Conclusions part. After the revision, it is moved to the Results.

Thank you once again for all the helpful comments and suggestions,

On behalf of all the co-authors,
Yeliz A. Yılmaz

References

Akyurek, Z., Surer, S., and Beser, O. (2011). Investigation of the snow-cover dynamics in the upper euphrates basin of turkey using remotely sensed snow-cover products and hydrometeorological data. Hydrological Processes, 25:3637– 3648.

Arguez, A. and Vose, R. S. (2011). The definition of the standard wmo climate normal: The key to deriving alternative climate normals. Bulletin of the American Meteorological Society, 92(6):699–704.

Balsamo, G., Agustì-Parareda, A., Albergel, C., Arduini, G., Beljaars, A., Bidlot, J., Bousserez, N., Boussetta, S., Brown, A., Buizza, R., Buontempo, C., Chevallier, F., Choulga, M., Cloke, H., Cronin, M. F., Dahoui, M., De Rosnay, P., Dirmeyer, P. A., Drusch, M., Dutra, E., Ek, M. B., Gentine, P., Hewitt, H., Keeley, S. P. E., Kerr, Y., Kumar, S., Lupu, C., Mahfouf, J.-F., McNorton, J., Mecklenburg, S., Mogensen, K., Muñoz-Sabater, J., Orth, R., Rabier, F., Reichle, R., Ruston, B., Pappenberger, F., Sandu, I., Seneviratne, S. I., Tietsche, S., Trigo, I. F., Uijlenhoet, R., Wedi, N., Woolway, R. I., and Zeng, X. (2018). Satellite and in situ observations for advancing global earth surface modelling: A review.Remote Sensing, 10(12).

Bormann, K. J., Brown, R. D., Derksen, C., and Painter, T. H. (2018). Estimating snow-cover trends from space. Nature Climate Change, 8:924–928.

Gascoin, S., Hagolle, O., Huc, M., Jarlan, L., Dejoux, J.-F., Szczypta, C., Marti, R., and Sánchez, R. (2015). A snow cover climatology for the pyrenees from modis snow products. Hydrology and Earth System Sciences, 19:2337–2351.

Gokmen, M., Vekerdy, Z., Verhoef, W., and Batelaan, O. (2013). Satellite-based analysis of recent trends in the ecohy- drology of a semi-arid region. Hydrology and Earth System Sciences, 17(10):3779–3794.

Guo, H.-D., Zhang, L., and Zhu, L.-W. (2015). Earth observation big data for climate change research. Advances in Climate Change Research, 6:108–117.

Hammond, J. C., Saavedra, F. A., and Kampf, S. K. (2018). Global snow zone maps and trends in snow persistence 2001–2016. Int J Climatol, 38:4369–4383.

Rodell, M., Famiglietti, J. S., Wiese, D. N., Reager, J. T., Beaudoing, H. K., Landerer, F. W., and Lo, M.-H. (2018). Emerging trends in global freshwater availability. Nature, 557:651–659.

Swanson, D. K. (2017). Trends in greenness and snow cover in alaska’s arctic national parks, 2000–2016. Remote Sensing, 9:514.

Tang, Z., Wang, X., Wang, J., Wang, X., Li, H., and Jiang, Z. (2017). Spatiotemporal variation of snow cover in tianshan mountains, central asia, based on cloud-free modis fractional snow cover product, 2001–2015. Remote Sensing, 9(10).

Yang, J., Gong, P., Fu, R., Zhang, M., Chen, J., Liang, S., Xu, B., Shi, J., and Dickinson, R. (2013). The role of satellite remote sensing in climate change studies. Nature Climate Change, 3:875–883.

Author Response File: Author Response.pdf

Reviewer 3 Report

Introduction general comments:

The introduction part is well written with relevant references but the connection between following paragraphs is somehow missing. Although, there is a brief discussion of change in temperature, the discussion about change in precipitation is missing and must be included. I also feel that comparison of the satellite products for their advantages and disadvantages and their use in other relevant fields is missing in the literature review.

Relevant citations:

Bhardwaj, A., Singh, S., Sam, L., Bhardwaj, A., Martin-Torres, F.J., Singh, A., Kumar, R. (2017). MODIS-based estimates of strong snow surface temperature anomaly related to high altitude earthquakes of 2015. Remote Sensing of Environment, 188, 1-8. DOI: 10.1016/j.rse.2016.11.005

Introduction specific comments:

Line 27: I feel that the term ‘greenhouse forcing’ is not appropriate to be used. Rather, the authors should use the term increased green-house effect or something similar.

Line 62: ‘Observations from space play an important role in monitoring….’ The GRACE product is also observation from space which authors have discussed in previous paragraphs.

Line 75: The magnitude of observed and predicted rise in temperature will be good. The temperature controls the rate of melting of the seasonal snow and also controls the form of precipitation making it the most important meteorological parameter. Also, the changes in annual snow cover area is an important indicator of change in temperature. These points must be discussed in the introduction part.

Relevant citation: Kumar, R., Singh, S., Kumar, R., Singh, A., Bhardwaj, A., Sam, L., Randhawa, S.S., Gupta, A. (2016). Development of a glacio-hydrological model for discharge and mass balance reconstruction. Water Resources Management, 30, 3475–3492. DOI: 10.1007/s11269-016-1364-0.

Study area

The details of the climate regimes in study area in terms of temperature and precipitation has been given here. I would like to suggest authors to discuss it at the relevant places in introduction as this is the background of the study.

Also, I would like to suggest the authors to include a graph showing the hypsometry of the study area (i.e. elevation versus area) and discuss the results with respect to the area falling under each elevation zone for Figure 3.

Data and methods

The description of the data used in the study and their retrieval is very descriptive. But I feel that the description of how they have been used to achieve the objectives of the study is still missing. I would really appreciate if the authors can include a flow diagram showing how these data have been used.

Line 267: What I understand from this sentence is that authors have tried to divide the study area in different elevation zones in order to analyse the results. If yes, then justification of using 500 m gap needs to be included with a detailed description.

Figure 2: The axis for all the figures should have same minimum and maximum value.

Results and discussion

General comments:

I see that the description of the meteorological data used in the section 4.5 has not been well discussed in Introduction or Data and Methods section.

Line 307: The elevation levels must be discussed in methods in detail.

Line 315: The area falling under each elevation zone needs to be included here as well and discussed in reference to the results.

Figure 3: The minimum and maximum value for all the axes in all the figures must be the same for comparison.

Line 329-332: It will be really nice if these findings are supported by monthly mean temperature in the region. The reanalysis temperature data can easily serve the purpose.

Line 445: A detailed description of precipitation data used in the study needs to be included in Data and Methods section. Also, the literature related to use of such precipitation data needs to be discussed in Introduction section.

Author Response

Please see the attached PDF.

Kind regards,

Yeliz A. Yılmaz

Author Response File: Author Response.pdf