Development of a Pixel-Wise Forest Transmissivity Model at Frequencies of 19 GHz and 37 GHz for Snow Depth Inversion in Northeast China

Round 1

Reviewer 1 Report

Comments for author File: Comments.pdf

Author Response

We are grateful to the reviewer for his/her detailed and constructive comments on the manuscript.

Our response to each comment is outlined in the attached file in bold and revised text is in red. The copy of the track changes manuscript is provided following our responses to the reviewers

Author Response File: Author Response.docx

Reviewer 2 Report

The manuscript “Development of a pixel-wise forest transmissivity model at frequencies of 19 GHz and 37 GHz for snow depth inversion in Northeastern China” by Wang et al. appears to be a well-conceived approach to solving a long-standing problem in passive microwave remote sensing of snow – accurate determination of SWE or snow depth in forested environments.  Wang et al attempt to solve this problem by proposing a pixel-level transmissivity estimation model based on time series of brightness temperatures (TBs) from the commonly used SSMI dataset.  Model performance is evaluated in an inversion for Snow Depth (SD) as compared to the forest transmissivity model used in the GlobSnow (v 3.0) product.  They report improvements in both the RMSE and biases compared to this model.

Overall the scope of the work is impressive.  It incorporates the widely used SSMI passive microwave timeseries, a daily land surface temperature producte (ERA5-Land) along with several radiative transfer models required for the modeling effort.  Overall the models are adequately described in an understandable manner making it clear how each of the models (each of which is itself complex) fit together.

The authors validate their output both directly and indirectly. The direct comparison is impressive as their modeled TBs are compared against measured TBs at fourteen sites falling within 8 SSMI pixels.  Such comparisons have all the caveats that go with attempting to compare stand scale measurements to passive microwave pixel scale (> 25 km) measurements.  More importantly, validation is done by incorporating their pixelwise transmissivity model in their snow emission modeling scheme.

I applaud the authors for their diligent comparison efforts which are well described and fairly easy to follow.   However, I do have some concerns over the some of their results which will need to be clarified and explained prior to the manuscript being acceptable for publication.  While they report that the their model provides improved results compared to GlobeSnow for their study area in Northeastern China, there model appears to produce a large number of cases in which their estimated Snow Depth and SWE are zero although the reference snow depth varies from a few to over 30 cm and SWE to over 60 mm.   It appears from Figure 7 that GlobeSnow is substantially less non-zero Snow Depths and SWE estimates than their algorithm.   In a smaller amount of instances it appears to produce considerably higher snow depths than GlobeSnow.

At a minimum this behavior of the algorithm leading to these zero retrievals should be better discussed. This should include at a minimum discussing the conditions under which it appears to predict no snow when snow is present as well has how this behavior impacts the reported comparison metrics (RMSE, Bias, r and p measures in Figure 7 and elsewhere in the manuscript).  I think the manuscript could be improved considerably if the reason for these zero estimates could be explained, and if possible corrected.  As it currently stands, it is unclear to what extent their model represents an improvement over the existing GlobeSnow product.

Overall, the manuscript is well written.  I did not some non-standard English terminology in lines 394-407.  The manuscript refers to plural values, however, I think the authors are meaning to refer to modal values?  On line 406 it is also unclear to me what the authors mean by “polar variations is relatively stable”  I am guessing they mean to say “polarization variations are relatively stable”

Author Response

We are grateful to the reviewer for his/her detailed and constructive comments on the manuscript.

Our response to each comment is outlined in the attached file in bold and revised text is in red. The copy of the track changes manuscript is provided following our responses to the reviewers.

Author Response File: Author Response.docx

Reviewer 3 Report

Line 45: Delete “system itself”

Line 131: “investigated” ---> “investigation” or “study”

Line 131: “until” ---> “to”

Line 131: Please give specific month you used in this study. Throughout this manuscript, you frequently used “winter season” term, but I don’t know the specific time.

Line 134: delete “of”

Section 2.2.1: This study used the brightness temperature data with 25 km spatial resolution, however, the new data with high spatial resolution (3.125 km and 6.25 km) has been issued for several years. Why did not use this new data with high resolution? This data can be accessed from the website (https://nsidc.org/data/nsidc-0630/versions/1).

Line 198-200: The description of Eq. 1 confuses me and it is not clear. Please revised it.

Tb_ac: do you mean it is the upwelling microwave radiation above forest canopy measured by satellite sensor?

Tb_underlying: do you mean it is the upwelling ground surface radiation?

Tb_forest: do you mean it is the upwelling radition of forest canopy?

More clear expression can refer to other published studies, for example, Che et al., 2016; Langlois et al., 2011; Xiao et al. 2022:

Line 213: The variation of emission (E) is related to snow cover property, not only limited snow depth, wetness, but also snow cover fraction (Dai et al., 2018; Shahroudi and Rossow 2014; Xiao et al., 2022). Authors should have a comprehensive concept about the snow cover properties for passive microwave.

 Line 238: how do you identify the “freezing conditions”? Do you used “T_forest <=273.15 K”?

Line 266 and Fig 2: I still don’t understand the so called “autumn priority principle”. Please add more explanations for this method and why you perform this method.

Eq. 6 and Line 281: As you said, this equation can determine the frozen ground with dry snow cover. And you study is to estimate snow depth. My question is how do you confirm the pixel is fully covered with snow or partly cover with snow (Xiao et al., 2022)? If the pixel is covered with patch snow (i.e., mixed pixel), meaning different level snow cover fraction, it could lead to some uncertainties to the snow depth estimations. Fractional snow cover area also has effect on the radiation variation measured by satellite.

Results: As you described in above section, you only have 14 sample sites (8 SSMIS pixels), how can you evaluate the forest transmissivity is Ok or reasonable in Fig. 3 and Fig. 4?

Line 423-451: You haven’t verified the accuracy of forest transmissivity; however, you conducted a series of analysis on the variation of transmissivity. I don't think this is making any sense. And also, you didn’t give any more actual explanation for this variation reason during the period 2014-2019. I suggested that you should remove this part.

Section 4.2 should be place at before Section 4.1, i.e., exchange the position of Section 4.1 and section 4.2.

Line 474: “4.4.2 Retrieval of …” ---> “4.2.2 Retrieval of …”

Section 5.1: In vegetation cover region, the influence of land cover types should not be neglected in microwave snow cover study (Xiao et al., 2022; Xiao et al., 2018; Langlois et al., 2011; Kruopis 1999).

Line 519: change the color of red γ letter

 

      

Reference:

1) T. Che, L. Dai, X. Zheng, X. Li, and K. Zhao, “Estimation of snow depth from passive microwave brightness temperature data in forest regions of northeast China,” Remote Sens. Environ., vol. 183, pp. 334–349, Sep. 2016, doi: 10.1016/j.rse.2016.06.005.

2) A. Langlois, A. Royer, F. Dupont, A. Roy, K. Goita, and G. Picard, “Improved corrections of forest effects on passive microwave satellite remote sensing of snow over boreal and subarctic regions,” IEEE Trans. Geosci. Remote Sens., vol. 49, no. 10, pp. 3824–3837, Oct. 2011, doi: 10.1109/TGRS.2011.2138145.

3) N. Shahroudi and W. Rossow, “Using land surface microwave emis- sivities to isolate the signature of snow on different surface types,” Remote Sens. Environ., vol. 152, pp. 638–653, Sep. 2014, doi: 10.1016/j.rse.2014.07.008.

4) L. Dai, T. Che, H. Xie, and X. Wu, “Estimation of snow depth over the Qinghai-Tibetan plateau based on AMSR-E and MODIS data,” Remote Sens., vol. 10, no. 12, p. 1989, Dec. 2018, doi: 10.3390/ rs10121989

5) Xiao, X., He, T., Liang, S., Zhao, T., 2022. Improving fractional snow cover retrieval from passive microwave data using a radiative transfer model and machine learning method. IEEE Trans. Geosci. Remote Sens. 60, 1–15. https://doi.org/10.1109/ TGRS.2021.3128524.

6) N. Kruopis, “Passive microwave measurements of snow-covered forest areas in EMAC’95,” IEEE Trans. Geosci. Remote Sens., vol. 37, no. 6, pp. 2699–2705, Nov. 1999, doi: 10.1109/36.803417.

7) X. Xiao, T. Zhang, X. Zhong, W. Shao, and X. Li, “Support vector regression snow-depth retrieval algorithm using passive microwave remote sensing data,” Remote Sens. Environ., vol. 210, pp. 48–64, Jun. 2018, doi: 10.1016/j.rse.2018.03.008

Author Response

We are grateful to the reviewer for his/her detailed and constructive comments on the manuscript.

Our response to each comment is outlined in the attached file in bold and revised text is in red. The copy of the track changes manuscript is provided following our responses to the reviewers.

Author Response File: Author Response.docx

Reviewer 4 Report

The reviewer would like to thank the authors for this thoughtful manuscript. This work has good potential. The authors are requested to put in some additional efforts to improve the quality of this manuscript. 

 

Introduction

The authors are requested to cite recent articles discussing the role of forests in limiting the accuracy of snow monitoring using optical satellites. Hence, the authors are requested to mention that forests are both crucial in determining the accuracy of snow detection in such environments. Furthermore, the authors are requested to draw the similarities in their findings with the accuracy of retrieving snow cover at different tree forest canopy densities. Please explain how these investigations are beneficial for passive microwave remote sensing of snow cover in forested environments. 

-Kostadinov et al., “Watershed-scale mapping of fractional snow cover under conifer forest canopy using lidar”, RSE, 2019.

-Muhuri et al., “Performance Assessment of Optical Satellite-Based Operational Snow Cover Monitoring Algorithms in Forested Landscapes”, IEEE JSTARS, 2021. 

 

Forest Density Maps

The authors are requested to cite and discuss the forest density map that is widely used and cited. 

     Hansen, M.C., Potapov, P.V., Moore, R., Hancher, M., Turubanova, S.A., Tyukavina, A., Thau, D., Stehman, S.V., Goetz, S.J., Loveland, T.R. and Kommareddy, A., 2013. High-resolution global maps of 21st-century forest cover change. Science, 342(6160), pp.850-853. doi:10.1126/science.1244693.

Can the authors show a relationship between the forest transmittivity estimation model and the tree cover density supplied by the above article?

 

Equations

The equations are not properly visible. Please provide high-resolution versions of all the equations.

 

Fig. and Flowchart

The figures and flowcharts should be redone in better resolution. For now, many aspects like the colorbar and captions within the figure are not properly visible. 

 

Pixel Transmissivity Model

 

The authors are requested to briefly explain if the transmittivity model proposed here can be utilized in optical data for retrieving snow cover.

 

Author Response

We are grateful to the reviewer for his/her detailed and constructive comments on the manuscript.

Our response to each comment is outlined in the attached file in bold and revised text is in red. The copy of the track changes manuscript is provided following our responses to the reviewers.

Author Response File: Author Response.docx