投到Journal of Mountain Science 的文章"利用气温计算山区裸地地表温度的新方法"（New methods for calculating bare land surface temperature over mountainous terrain） 在第一轮审稿时共收到三份审稿意见, 三份意见均较为详细，所有审稿意见加在一起有四页多，意稿人对这种简单的新方法均表现出浓厚的兴趣并给予了充分的肯定，同时提出了很多具体的建议以便作者进一步修改和完善。三位审稿人分别来位于意大利的欧洲研究院（Academia Europaea）高山研究所， 意大利那不勒斯第二大学,西班牙国家研究委员会比利牛斯生态研究所。在这里贴出这三份审稿意见的目的是希望国内的学者能够从中学习到一些撰写审稿意见的方法, 同时, 给从事相关研究的国内学者提供一些合作交流的线索。

第一位审稿人先对文章进行了总体评价，然后针对文章各章节给出相应评价和具体意见，这样的审稿意见让作者更容易理解，在修改时也更容易操作。

Reviewer 1  

Accademia Europea, Institute for Alpine Environments

The manuscript is well written. However, it proposes a rather simple method compared with the major literature on the field. The method could be useful in data-poor regions.

I would have suggested "reject" in a major journal with very high IF, but I think good works, even if made with a few data and simple approaches, deserve a publication in a good journal as JMS.

General comments:

The article proposes a new methodology to improve the estimation of land surface temperature (LST) over mountainous terrain, on the basis of topographic information and air temperature.

The proposed method is very simple and based on few, easily available data. Performances are relatively poor, compared to other, more complex, methods. Nevertheless, the method improves significantly results, compared to an approach based only on air temperature.  The method could be useful in data-poor regions.

The paper is very well written and results are well supported by observations.

However, there are several aspects in the methodology that can be improved. I understand that the Authors want to keep the method simple and with little data requirements (only T air observations), but several improvements are possible that could, at least, be mentioned as possible future developments in the Discussion. In particular:

•Only bare soil is considered. However, as acknowledged, vegetation strongly influences LST. How vegetation can be considered in the method?

•A better validation of the method could be given by remote sensing data. Why do not validate the model also against such a data?

•Effect of long wave radiation and could cover. Simple methods are available to infer long wave radiation to further improve the method.

I think the paper is in line with the aims and targets of JMS.

To conclude, I suggest a moderate revision for the paper.

Specific comments:

Introduction

Introduction is well written: I suggest underlining the importance of LST estimation in mountain regions for processes as permafrost. I suggest also mentioning the possibility of estimating LST by proximal sensing (thermal cameras).

Site and data

Here I have a major methodological observation. Did you measure LST just below the soil or at the soil surface? In the last case, how has been the instrument sheltered from the Sun? Incorrect solar sheltering and simply the fact that the instrument is made in a different material with respect to the soil, can alter observation of several K. Please explain better the experimental setup.

Methodology

If a temperature lapse rate of -6.5 C/100 m is always assumed, large errors in Ta estimation are possible. In fact, over long time scales this assumption is safe, but locally and at the instantaneous time scale, lapse rate could change a lot (i.e. morning thermal inversion, etc …)

In the methods, the diurnal Ta excursion is used. The method performs also worse for cloudy days. This could be because the effects of incoming long wave radiation from the clouds are not take in account. Way do not consider simple parametrizations as the one of  Brutsaert (1975) and following modifications for clouds?

Brutsaert, W. (1975). On a Derivable Formula for Long-Wave Radiation from Clear Skies. Water Resour. Res., 11(5), 742–744.

Validation

Given the simplicity of the method, it works relatively well, even below pefromances of more complex methods.

A better validation of the method could be given by thermal cameras observations or by MODIS (500 m resolution) LANDSAT LST (60 m resolution) observations. The latter are available for free. Why do not validate the model also against such a data

Reviewer 2

Seconda Università di Napoli, Dipartimento di Ingegneria Civile, Design, Edilizia e Ambiente

The paper proposes a simple method to calculate bare soil surface temperature from air temperature measurements. The topic is of interest for the readership of JMS, as soil surface temperature affects several processes occurring at soil surface, such as soil-atmosphere energy and water exchange, snow melt etc.

The manuscript is clearly organized, but the English language must be improved with the help of a native speaker (for instance, there is continuously skipping from present tense to past tense, that should be homogenized throughout the manuscript).

Although the proposed method could be useful for practical applications, the presentation of the results does not allow the reader to judge if the drawn conclusions are actually supported by the data.

In particular, after describing the proposed mathematical relationships allowing calculation of soil temperature from air temperature, solar elevation and land slope and aspect angles, the authors make their discussion by comparing the obtained results only with the naive assumption of considering soil surface temperature equal to air temperature, and conclude that their model is closer to actual measured soil temperature.

I have several concerns about this line of evaluating model performance:

- I wonder if this kind of comparison is enough to draw the conclusion that equations (1) and (2) are suitable for estimating LST. The authors should provide more information about the errors of the model, e.g. at what time of the day, and in what part of the year, the discrepancies between model and measurements are maximum?

- Would it be possible to introduce the effect of cloud cover to further improve the performance of the equation?

- To what extent the errors still present in the modeled LST affect the estimates of water and energy exchanges at soil surface?

- Although the authors state that other existing approaches for estimating soil surface temperature do not provide data at the required spatial resolution, some comparison with the performance of other models should be made.

- The presented data refer to high altitude sites, and the authors, in their introduction, mention permafrost dynamics as one of the possible fields of application of the method; nonetheless, there is no mention to insulation snow effect on the relationship between air temperature and soil temperature (see Wang et al., 2016, for a recent review of existing models).

Given all these issues, me recommendation is that the manuscript is not acceptable in its present form, and major revisions are needed before re-evaluating it for possible publication in JMS.

References

Wang W, et al., 2016 Evaluation of air–soil temperature relationships simulated by land surface models during winter across the permafrost region, The Cryosphere, 10: 1721–173

Reviewer 3

Spanish Research council, CSIC, Pyrenean Institute of Ecology

Dear Editor,

The manuscript deals with a research that is rather simple, but may result useful for other researchers and, hence, to be of interest for JSM. Below I indicate a short number of comments that may facilitate the lecture of the manuscript and also some questions that authors should consider before being accepted the manuscript.

Comments to the Author

The manuscript "New methods for calculating bare land surface temperature over mountainous terrain" test two equation to obtain bare land suface temperature in mountain areas. Analyses are rather simple and the results are depicted very briefly. In general, I think that this topic may be of interest for different field of research in mountain areas (ecology, erosion, etc) and hence of interest for Journal of Mountain Science.

Below I indicate a number of comments that authors should address and/or clarify in a revised version:

1- In the abstract all acronyms should be introduced with the full name for better understanding.

2- Figure captions should be reworked to be self-explanatory. In its current form they do not result very informative if you do not read the full manuscript.

3- The section Validation includes the full results. I would move the first paragraph to methods, and the rest to a "results" section.

4- An important question is that authors are correlating two series (observed and simulated data) with a very strong seasonality, that always will lead to spuriously increase the correlation values. I think that error estimators should be provided to series with the seasonal signal removed, or alternatively present the error estimators for each month, removing in this way the seasonal cycle.

5- In relation with comment 4, I think it would be of interest to show if the equations work better or worse in different times of the year, so providing (and discussing) error estimators for each month would be of interest.

6- It would be of interest stress the RMSE as a percentage of average Temperature to have an idea which % of error are associated to both equations ( a standardized RMSE).

6- What about snowpack? Were the study sites covered by snow? How did it affect the analysis?

7- Perhaps, it would be good to discuss how these equations may work on bare rock instead of bare soils. Probably, it will be necessary to use completely different parameters as differences between air temperature and surface will be much larger.