Monitoring Urban Heat Island Intensity with Ground-based GNSS Observations and Space-based Radio Occultation and Radiosonde Historical Data

Xia, Pengfei; Peng, Wei; Ye, Shirong; Guo, Min; Hu, Fangxin

doi:https://doi.org/10.5194/egusphere-2022-589

Preprints

https://doi.org/10.5194/egusphere-2022-589

Preprints

26 Jul 2022

| 26 Jul 2022

Monitoring Urban Heat Island Intensity with Ground-based GNSS Observations and Space-based Radio Occultation and Radiosonde Historical Data

Pengfei Xia, Wei Peng, Shirong Ye, Min Guo, and Fangxin Hu

Abstract. Since Urban Heat Islands (UHI) not only negatively impact human health but consume more energy when cooling buildings, accurate monitoring of its impact is critical. In this study, we propose a ground based GNSS technique to fuse GNSS Radio Occultation (RO) and radiosonde products to monitor the UHI intensity, which described as follows: First, the first and second grid tops are defined using the historical RO and radiosonde products. Then, the wet refractivity between the first and second grid tops is fitted to the higher-order spherical harmonic function based on the RO and radiosonde products, and they are used as the inputs of GNSS tomography, which can reduce the number of unknowns voxels of tomography while increasing the effective number of satellite rays, and improving the accuracy of tomography results. Next, according to the relationships among wet refractivity, temperature, and water vapor partial, as well as the function relationships among temperature, wet pressure, and height in adjacent vertical layers, the temperature and water vapor partial pressure can be obtained using the best search method according to the tomography-derived wet refractivity. Finally, the UHI intensity is monitored by the temperature difference between the urban regions and the surrounding rural regions. The radio occultation and radiosonde products of the Hong Kong region from 2010 to 2019, and the observed GNSS network data of the Hong Kong region for the year of 2020 are employed to evaluate the UHI intensity algorithm. The validation of the algorithm is done by comparing the UHI intensity estimated from the algorithm with the temperature data obtained from weather stations. The result shows that the proposed algorithm can achieve an accuracy of 1.2 K at a 95 % confidence level.

Received: 04 Jul 2022 – Discussion started: 26 Jul 2022

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Pengfei Xia, Wei Peng, Shirong Ye, Min Guo, and Fangxin Hu

Status: closed

CC1:
'Comment on egusphere-2022-589', Zhounan Dong, 05 Aug 2022

I've been working on GNSS meteorological remote sensing for a while now; it's a fascinating subject and offers a fresh way to use GNSS observations for monitoring urban heat islands. It really is a unique thought.

Citation: https://doi.org/10.5194/egusphere-2022-589-CC1
- AC1: 'Reply on CC1', Pengfei Xia, 19 Aug 2022
  
  Thank you very much for your review of the manuscript. At present, we also encounter many difficulties, such as improving the spatial resolution of temperature and how to improve the accuracy of temperature. If you are also interested, we can communicate and discuss more to solve the above problems in the future.
  
  Citation: https://doi.org/10.5194/egusphere-2022-589-AC1
CC2:
'Comment on egusphere-2022-589', xianjie Li, 05 Aug 2022

It is interesting to know from this paper that GNSS tomography could also has the potency on monitoring the Urban Heat Island Intensity (UHII). Since the advent of GNSS meteorology, it has been applied in many meteorological application, like extreme weather monitoring, weather nowcasting and forecasting and so on. As a PhD student working on GNSS meteorology, this paper inspires me that there may be more possibilities when considering data fusion from different data sources, like in this paper, combining ground-based GNSS, Radio Occultation and radiosonde techniques.
Now turn back to the paper itself, one of the key point of this paper is that how to retrieve the temperature based on all these techniques. The authors chose to retrieve the temperature from the wet refractivity field over the region in Hong Kong reconstructed by GNSS tomography. To do so, additional conditions are introduced, like the temperature decreases with height linearly and the pressure decreases with height exponentially. Since both conditions are normally adopted in many researches, is there any other way to retrieve the temperature, either more precise or simpler? And for monitoring UHII, with this validated method, if it is possible to be implemented in a real-time mode? or is it necessary to monitor UHII in real-time?

Citation: https://doi.org/10.5194/egusphere-2022-589-CC2
- AC2: 'Reply on CC2', Pengfei Xia, 19 Aug 2022
  
  Thank you very much for your invaluable time and great efforts toward our manuscript. We respond to your two questions separately.
  
  Question 1: Since both conditions are normally adopted in many researches, is there any other way to retrieve the temperature, either more precise or simpler?
  
  In subsequent studies, we will attempt to estimate atmospheric temperature and water vapor pressure from the wet refractivity using a one-dimensional variational approach. Compared with the method in this paper, this method is simpler and more accurate in acquiring temperature.
  Question 2: And for monitoring UHII, with this validated method, if it is possible to be implemented in a real-time mode? or is it necessary to monitor UHII in real-time?
  
  The methods presented in the manuscript can be used in a real-time mode, in addition, real-time monitoring of UHII is highly desirable. This is also one of the contents that we will focus on in the next step.
  
  Citation: https://doi.org/10.5194/egusphere-2022-589-AC2
RC1:
'Comment on egusphere-2022-589', Anonymous Referee #1, 19 Aug 2022

The paper by Pengfei Xia et al. is very interesting, but has also very serious shortcomings in the first part (page 1-5).

The methodology section MUST be rewritten IN DEPTH. Basically:

- The correct mathematical setting of eq. 1 is that of the so-called Radon transform. Please have a look at the literature on this tranform (for example X-ray imaging) and mention some theoretical references.

- the decay with respect to altitude of temperature (linear) and water vapor contents (exponential) is not always true.

inversion layers are common,as noted by the authirs themselves...but later in the paper.

- even more important, and I would say a major flaw in the method is that its robustness with respect to small variations

in the beta coefficient (eq. 7) and a and b (eq. 8) is not addressed. This MUST be discussed and robustness established.

- The use of a "Kalman filtering" as a magic word to invert SWD values as Nw values. Kalman filtering is just another word for a least-squares process. In this particular case, the authors are technically doing a least-squares linear inverse problem. I urge them to have a look at the fundamental papers by Tarantola and Valette around 1980, that can be easily found, and especially the paper "inverse problems = Quest for information".

By the way (for the authors), are you doing a linearization of the inversion problem around eqs. 5 and 7? How do you weight a priori information, if any? Please add the relevant equations and do not stay in the vague of "Kalman filtering".

Minor points:

- please add contouring of the topography in Figure 1.

- please describe in a few sentences what is GNSS RO. Are you using COSMIC-2 data?

At this point, my recommendation is to reject and resubmit once these major issues have been fixed, or at minimum major revision, to be sure that the second part of the paper is reliable.

Citation: https://doi.org/10.5194/egusphere-2022-589-RC1
- AC3: 'Reply on RC1', Pengfei Xia, 25 Aug 2022
  
  The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2022/egusphere-2022-589/egusphere-2022-589-AC3-supplement.pdf
  
  Citation: https://doi.org/10.5194/egusphere-2022-589-AC3
RC2:
'Comment on egusphere-2022-589', Anonymous Referee #2, 20 Aug 2022
The evaluation for the manuscript egusphere-2022-589

After the careful review, my conclusion is the study is not accepted. The further comments are as follows for the considerations.

About tomography, the definition of voxels (volumetric pixels) should be the first important thing. I cannot see any clear definition for it. I mean what the size of voxels used in this study. I suggest that the authors put it at the beginning of tomography section.

Slant wet delay (SWD) is the beginning of everything about tomography in this manuscript. The authors just simply only applied Niell Mapping Function and without any parameterised strategy. It is highly risky, especially for water vapour (wet delay). The residual item should be in the equation (13) and the residual should be estimated. Actually, there are at least 3 different kinds of tomography models for 3-D (BIRA, TUW…)and one for 4-D can be used. Applying mapping function only in this manuscript is not enough.

I suggest that more literature review about tomography is necessary. Atmospheric Measurement Techniques (EGU) and ETH Zurich, Switzerland, JoG are good resources.

The authors used wet refractivity from radiosonde and GPS RO to retrieve temperatures as the constrain in the study. GPS RO also provide temperature profiles. Is any reason the authors did not use the GPS RO temperature profiles directly.

Line 328 and 329,

“….ERA5 could provide….., which were selected as the initial values in this study…..”,

GPS RO and radiosondes have already been assimilated into ERA5. However, the authors used ERA5 as the first guest for the wet profiles constrained by GPS RO. Why don’t the authors use ERA5 as the constrain directly for first and second grid tops?

Line 108 and 109,

“Though the Gauss weighted method (Song, 2004) can

be used for the horizontal direction,………….”. This strategy is only applied when the horizontal distribution of water vapour is stable. However, the weather (or climate) is the non-linear and complex system. I think the method is only suited for the simulation.

If the GPS RO is applied to this study, the number and the details of RO events happened in Hong Kong should be presented as the table in the manuscript and the types of RO data (used Level) as well.

Both of CDAAC 2.0 (UCAR, USA) and ROM SAF (EUMETSAT) also provide GPS RO profiles. Is it the same with WEGC OPSv5.6 ? If not, I suggest that the authors provide the reason for using WEGC OPSv5.6

The ZTD of ground based GPS stations are retrieved from GAMIT software package. I suggest the authors provide the used strategy in the manuscript for getting ZWD from GAMIT’s ZTD. Theoretically, the in situ weather stations are necessary then you just can get precise ZWD from ZTD.

I suggest the authors do the comparison with MODIS data for heat island topic.

I suggest that the authors put “tomography” in the title of manuscript.
Citation: https://doi.org/10.5194/egusphere-2022-589-RC2
- AC4: 'Reply on RC2', Pengfei Xia, 25 Aug 2022
  
  The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2022/egusphere-2022-589/egusphere-2022-589-AC4-supplement.pdf
  
  Citation: https://doi.org/10.5194/egusphere-2022-589-AC4
CEC1:
'Comment on egusphere-2022-589', Juan Antonio Añel, 23 Aug 2022

Dear authors,
Unfortunately, after checking your manuscript, it has come to our attention that it does not comply with our "Code and Data Policy".

https://www.geoscientific-model-development.net/policies/code_and_data_policy.html
Namely, your manuscript does not contain the Code Availability Section, and the code used for your work is not included in one of the suitable external repositories listed in our policy or as supplementary material. Admittedly, this has been an oversight by the handling Topical Editor, and your manuscript should have never been published in Discussions with this problem. However, given that the manuscript is now in Discussions, we are offering you the possibility to solve it.
Therefore, please, publish your code in one of the appropriate repositories, and reply to this comment with the relevant information (link and DOI) as soon as possible, as it should be available for the Discussions stage. In this way, you must include the modified 'Code and Data Availability' section in a potential reviewed version of your manuscript, the DOI of the code (and another DOI for the dataset if necessary).
Please, note that we can not accept embargoes on the code, such as the need to contact authors to obtain access to it or registration. Also, Also you must include a license for your code/algorithms. If you do not do it, the code continues to be your property and can not be used by others, despite any statement on being free to use. Therefore, when uploading the model's code to the repository, you could want to choose a free software/open-source (FLOSS) license. We recommend the GPLv3. You only need to include the file 'https://www.gnu.org/licenses/gpl-3.0.txt' as LICENSE.txt with your code. Also, you can choose other options that Zenodo provides: GPLv2, Apache License, MIT License, etc.
Please reply as soon as possible to this comment with the link for it so that it is available for peer-review, as it should be.
Moreover, be aware that failing to comply promptly with this request will result in rejecting your manuscript for publication.
Regards,
Juan A. Añel
Geosci. Model Dev. Exec. Editor

Citation: https://doi.org/10.5194/egusphere-2022-589-CEC1
- AC6:
  'Reply on CEC1', Pengfei Xia, 19 Sep 2022
  
  Thank you very much for your commons.
  The code/algorithms of our manuscript can be downloaded from the following website: http://www.showskills.icu/data/Code_and_Data_Availability.tar.gz. Unfortunately, we cannot disclose the code for obtaining atmospheric temperature from the wet refractivity, because according to the requirements of the project contract, we can only disclose it after the project is completed. In addition, we only provide part of the data, because these data take up too much memory space, and these data are public and can be downloaded for free according to the link provided in our manuscript.
  
  Citation: https://doi.org/10.5194/egusphere-2022-589-AC6
  - CEC2: 'Reply on AC6', Juan Antonio Añel, 20 Sep 2022
    
    Dear authors,
    Unfortunately, your manuscript does not comply with our Code and Data Availability Policy yet. First, the repository you have used is not an acceptable one, which should be clear to you if you had paid attention to our policy, as linked in my previous comment. Secondly, the link that you provide does not work. Lastly, although the file was available, the page is not in English, which is the language used by Geosci. Model Dev., making its use difficult by most of the readers of our journal.
    I am not sure we can accept your statement saying that a contract precludes code availability. If the condition is that the code can be available at the end of a project and not before, then the logical thing to do is that you withdraw your manuscript and resubmit it when you can publish the code.
    Also, the statement on limitations for data storage does not seem justified. What amount of data do you say is unfeasible to publish? Some repositories can accept Terabytes, so we need clarification on this.
    Therefore, given that I commented on your manuscript almost one month ago, you did not reply promptly as I requested, and the Discussions stage is closing in a few hours without you having satisfied our requests, I only see the following solutions here:
    Option 1: You reply to this comment before the Discussions stage is closed with all the materials requested. If you can not do it before the Discussions stage closes, you should email us the requested information.
    Option 2: You send to the Topical Editor and me, via email and in a few days, a copy of the contract that you say prevents publication, with a clear indication of its duration and the law that enforces it. If the project is too long (many years), we can study if an exception is of application in this case. And we do not promise that we can make it. Otherwise, if it is a short contract (for example, three years or less), we will reject your manuscript; that said, if this is the case, as said before, I encourage you to withdraw your manuscript and resubmit it when the contract ends. Also, you must send us precise information about what data size is necessary to document your manuscript, preventing you from publishing it. Anyway, we would need that you have issued a DOI for the data and guarantee of internal archival by your institution for several years (usually at least ten years).
    We need to enforce a reply in a short time from you to be sure that we are not wasting the time of reviewers and editors on something that is not publishable.
    Option 3: If you fail to reply and promptly send us the requested information (much faster than your reply to this comment), we will have to reject your manuscript.
    Regards,
    Juan A. Añel
    Geosci. Model Dev. Executive Editor
    
    Citation: https://doi.org/10.5194/egusphere-2022-589-CEC2
    
    AC7: 'Reply on CEC2', Pengfei Xia, 20 Sep 2022
    
    Dear Juan,
    Thank you very much for your reply.
    
    We are very sorry that we were not able to link the Code and Data as you requested. I'm doing this for the first time and I've spent weeks learning how to build Code and Data links. In addition, our server memory is relatively small, and the Code and Data link I established always crashes, causing our established Code and Data link to fail.
    I have communicated with the project partners, and they advised that cannot code for obtaining atmospheric temperature from the wet refractivity can not been disclosed within the past two years. After discussing with other co-authors, we decided to withdraw the manuscript, re-edit the manuscript and wait for the code to be made public before resubmitting it. We greatly appreciate your suggestions and comments on our manuscript, which have greatly improved the quality of our manuscript. Thanks again very much.
    Best Wishes,
    Pengfei Xia
    
    Citation: https://doi.org/10.5194/egusphere-2022-589-AC7
CC3:
'Comment on egusphere-2022-589', qimin he, 09 Sep 2022

Pretty good work, the GNSS has the ability to continuously monitor atmospheric information with high temporal resolution.In future work, the authors can study UHI Intesity with high temporal resolution, especially for real-time GNSS applications. In addition, it can be noted that the UHI intensity of Hong Kong is very small, most regions in Hong Kong are 1-2k, while the author's conclusion is that there is an error of 1.2k (the relative error is too large). In the future, we may try this method in the areas where the temperature varies greatly, and we may be able to get more interesting conclusions.

Citation: https://doi.org/10.5194/egusphere-2022-589-CC3
- AC5: 'Reply on CC3', Pengfei Xia, 16 Sep 2022
  
  Thank you very much for your invaluable time and great efforts toward our manuscript. We respond to your two questions separately.
  1. In future work, the authors can study UHI Intesity with high temporal resolution, especially for real-time GNSS applications
  Response: Thank you very much for your suggestions.
  In the next study, we will increase the time resolution of UHII to 5 minutes utilizing real-time GNSS technology.
  
  2. In addition, it can be noted that the UHI intensity of Hong Kong is very small, most regions in Hong Kong are 1-2k, while the author's conclusion is that there is an error of 1.2 K (the relative error is too large). In the future, we may try this method in the areas where the temperature varies greatly, and we may be able to get more interesting conclusions.
  Response: Thank you very much for your commons and suggestions.
  At present, the accuracy of diagnosing UHII using single ground-based GNSS is about 1.71K (Jorge et al., 2021) . And the accuracy of diagnosing UHII using GNSS tomography technology is about 1.2K. The accuracy of diagnosing UHII using GNSS technology is limited by the accuracy of GNSS data processing and the accuracy of the retrieval of atmospheric temperature from atmospheric refractivity. In particular, the latter is what we will continue to study in the future, in order to further improve the diagnostic accuracy of UHII.
  Reference.
  Jorge, M.A., Lawrence, L. Tang, Y.T. and Terry, M. 2021. A new global navigation satellite system (GNSS) based method for urban heat island intensity monitoring. International Journal of Applied Earth Observations and Geoinformation. 94: 102222. https://doi.org/10.1016/j.jag.2020.102222
  
  Citation: https://doi.org/10.5194/egusphere-2022-589-AC5

Status: closed

CC1:
'Comment on egusphere-2022-589', Zhounan Dong, 05 Aug 2022

I've been working on GNSS meteorological remote sensing for a while now; it's a fascinating subject and offers a fresh way to use GNSS observations for monitoring urban heat islands. It really is a unique thought.

Citation: https://doi.org/10.5194/egusphere-2022-589-CC1
- AC1: 'Reply on CC1', Pengfei Xia, 19 Aug 2022
  
  Thank you very much for your review of the manuscript. At present, we also encounter many difficulties, such as improving the spatial resolution of temperature and how to improve the accuracy of temperature. If you are also interested, we can communicate and discuss more to solve the above problems in the future.
  
  Citation: https://doi.org/10.5194/egusphere-2022-589-AC1
CC2:
'Comment on egusphere-2022-589', xianjie Li, 05 Aug 2022

It is interesting to know from this paper that GNSS tomography could also has the potency on monitoring the Urban Heat Island Intensity (UHII). Since the advent of GNSS meteorology, it has been applied in many meteorological application, like extreme weather monitoring, weather nowcasting and forecasting and so on. As a PhD student working on GNSS meteorology, this paper inspires me that there may be more possibilities when considering data fusion from different data sources, like in this paper, combining ground-based GNSS, Radio Occultation and radiosonde techniques.
Now turn back to the paper itself, one of the key point of this paper is that how to retrieve the temperature based on all these techniques. The authors chose to retrieve the temperature from the wet refractivity field over the region in Hong Kong reconstructed by GNSS tomography. To do so, additional conditions are introduced, like the temperature decreases with height linearly and the pressure decreases with height exponentially. Since both conditions are normally adopted in many researches, is there any other way to retrieve the temperature, either more precise or simpler? And for monitoring UHII, with this validated method, if it is possible to be implemented in a real-time mode? or is it necessary to monitor UHII in real-time?

Citation: https://doi.org/10.5194/egusphere-2022-589-CC2
- AC2: 'Reply on CC2', Pengfei Xia, 19 Aug 2022
  
  Thank you very much for your invaluable time and great efforts toward our manuscript. We respond to your two questions separately.
  
  Question 1: Since both conditions are normally adopted in many researches, is there any other way to retrieve the temperature, either more precise or simpler?
  
  In subsequent studies, we will attempt to estimate atmospheric temperature and water vapor pressure from the wet refractivity using a one-dimensional variational approach. Compared with the method in this paper, this method is simpler and more accurate in acquiring temperature.
  Question 2: And for monitoring UHII, with this validated method, if it is possible to be implemented in a real-time mode? or is it necessary to monitor UHII in real-time?
  
  The methods presented in the manuscript can be used in a real-time mode, in addition, real-time monitoring of UHII is highly desirable. This is also one of the contents that we will focus on in the next step.
  
  Citation: https://doi.org/10.5194/egusphere-2022-589-AC2
RC1:
'Comment on egusphere-2022-589', Anonymous Referee #1, 19 Aug 2022

The paper by Pengfei Xia et al. is very interesting, but has also very serious shortcomings in the first part (page 1-5).

The methodology section MUST be rewritten IN DEPTH. Basically:

- The correct mathematical setting of eq. 1 is that of the so-called Radon transform. Please have a look at the literature on this tranform (for example X-ray imaging) and mention some theoretical references.

- the decay with respect to altitude of temperature (linear) and water vapor contents (exponential) is not always true.

inversion layers are common,as noted by the authirs themselves...but later in the paper.

- even more important, and I would say a major flaw in the method is that its robustness with respect to small variations

in the beta coefficient (eq. 7) and a and b (eq. 8) is not addressed. This MUST be discussed and robustness established.

- The use of a "Kalman filtering" as a magic word to invert SWD values as Nw values. Kalman filtering is just another word for a least-squares process. In this particular case, the authors are technically doing a least-squares linear inverse problem. I urge them to have a look at the fundamental papers by Tarantola and Valette around 1980, that can be easily found, and especially the paper "inverse problems = Quest for information".

By the way (for the authors), are you doing a linearization of the inversion problem around eqs. 5 and 7? How do you weight a priori information, if any? Please add the relevant equations and do not stay in the vague of "Kalman filtering".

Minor points:

- please add contouring of the topography in Figure 1.

- please describe in a few sentences what is GNSS RO. Are you using COSMIC-2 data?

At this point, my recommendation is to reject and resubmit once these major issues have been fixed, or at minimum major revision, to be sure that the second part of the paper is reliable.

Citation: https://doi.org/10.5194/egusphere-2022-589-RC1
- AC3: 'Reply on RC1', Pengfei Xia, 25 Aug 2022
  
  The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2022/egusphere-2022-589/egusphere-2022-589-AC3-supplement.pdf
  
  Citation: https://doi.org/10.5194/egusphere-2022-589-AC3
RC2:
'Comment on egusphere-2022-589', Anonymous Referee #2, 20 Aug 2022
The evaluation for the manuscript egusphere-2022-589

After the careful review, my conclusion is the study is not accepted. The further comments are as follows for the considerations.

About tomography, the definition of voxels (volumetric pixels) should be the first important thing. I cannot see any clear definition for it. I mean what the size of voxels used in this study. I suggest that the authors put it at the beginning of tomography section.

Slant wet delay (SWD) is the beginning of everything about tomography in this manuscript. The authors just simply only applied Niell Mapping Function and without any parameterised strategy. It is highly risky, especially for water vapour (wet delay). The residual item should be in the equation (13) and the residual should be estimated. Actually, there are at least 3 different kinds of tomography models for 3-D (BIRA, TUW…)and one for 4-D can be used. Applying mapping function only in this manuscript is not enough.

I suggest that more literature review about tomography is necessary. Atmospheric Measurement Techniques (EGU) and ETH Zurich, Switzerland, JoG are good resources.

The authors used wet refractivity from radiosonde and GPS RO to retrieve temperatures as the constrain in the study. GPS RO also provide temperature profiles. Is any reason the authors did not use the GPS RO temperature profiles directly.

Line 328 and 329,

“….ERA5 could provide….., which were selected as the initial values in this study…..”,

GPS RO and radiosondes have already been assimilated into ERA5. However, the authors used ERA5 as the first guest for the wet profiles constrained by GPS RO. Why don’t the authors use ERA5 as the constrain directly for first and second grid tops?

Line 108 and 109,

“Though the Gauss weighted method (Song, 2004) can

be used for the horizontal direction,………….”. This strategy is only applied when the horizontal distribution of water vapour is stable. However, the weather (or climate) is the non-linear and complex system. I think the method is only suited for the simulation.

If the GPS RO is applied to this study, the number and the details of RO events happened in Hong Kong should be presented as the table in the manuscript and the types of RO data (used Level) as well.

Both of CDAAC 2.0 (UCAR, USA) and ROM SAF (EUMETSAT) also provide GPS RO profiles. Is it the same with WEGC OPSv5.6 ? If not, I suggest that the authors provide the reason for using WEGC OPSv5.6

The ZTD of ground based GPS stations are retrieved from GAMIT software package. I suggest the authors provide the used strategy in the manuscript for getting ZWD from GAMIT’s ZTD. Theoretically, the in situ weather stations are necessary then you just can get precise ZWD from ZTD.

I suggest the authors do the comparison with MODIS data for heat island topic.

I suggest that the authors put “tomography” in the title of manuscript.
Citation: https://doi.org/10.5194/egusphere-2022-589-RC2
- AC4: 'Reply on RC2', Pengfei Xia, 25 Aug 2022
  
  The comment was uploaded in the form of a supplement: https://egusphere.copernicus.org/preprints/2022/egusphere-2022-589/egusphere-2022-589-AC4-supplement.pdf
  
  Citation: https://doi.org/10.5194/egusphere-2022-589-AC4
CEC1:
'Comment on egusphere-2022-589', Juan Antonio Añel, 23 Aug 2022

Dear authors,
Unfortunately, after checking your manuscript, it has come to our attention that it does not comply with our "Code and Data Policy".

https://www.geoscientific-model-development.net/policies/code_and_data_policy.html
Namely, your manuscript does not contain the Code Availability Section, and the code used for your work is not included in one of the suitable external repositories listed in our policy or as supplementary material. Admittedly, this has been an oversight by the handling Topical Editor, and your manuscript should have never been published in Discussions with this problem. However, given that the manuscript is now in Discussions, we are offering you the possibility to solve it.
Therefore, please, publish your code in one of the appropriate repositories, and reply to this comment with the relevant information (link and DOI) as soon as possible, as it should be available for the Discussions stage. In this way, you must include the modified 'Code and Data Availability' section in a potential reviewed version of your manuscript, the DOI of the code (and another DOI for the dataset if necessary).
Please, note that we can not accept embargoes on the code, such as the need to contact authors to obtain access to it or registration. Also, Also you must include a license for your code/algorithms. If you do not do it, the code continues to be your property and can not be used by others, despite any statement on being free to use. Therefore, when uploading the model's code to the repository, you could want to choose a free software/open-source (FLOSS) license. We recommend the GPLv3. You only need to include the file 'https://www.gnu.org/licenses/gpl-3.0.txt' as LICENSE.txt with your code. Also, you can choose other options that Zenodo provides: GPLv2, Apache License, MIT License, etc.
Please reply as soon as possible to this comment with the link for it so that it is available for peer-review, as it should be.
Moreover, be aware that failing to comply promptly with this request will result in rejecting your manuscript for publication.
Regards,
Juan A. Añel
Geosci. Model Dev. Exec. Editor

Citation: https://doi.org/10.5194/egusphere-2022-589-CEC1
- AC6:
  'Reply on CEC1', Pengfei Xia, 19 Sep 2022
  
  Thank you very much for your commons.
  The code/algorithms of our manuscript can be downloaded from the following website: http://www.showskills.icu/data/Code_and_Data_Availability.tar.gz. Unfortunately, we cannot disclose the code for obtaining atmospheric temperature from the wet refractivity, because according to the requirements of the project contract, we can only disclose it after the project is completed. In addition, we only provide part of the data, because these data take up too much memory space, and these data are public and can be downloaded for free according to the link provided in our manuscript.
  
  Citation: https://doi.org/10.5194/egusphere-2022-589-AC6
  - CEC2: 'Reply on AC6', Juan Antonio Añel, 20 Sep 2022
    
    Dear authors,
    Unfortunately, your manuscript does not comply with our Code and Data Availability Policy yet. First, the repository you have used is not an acceptable one, which should be clear to you if you had paid attention to our policy, as linked in my previous comment. Secondly, the link that you provide does not work. Lastly, although the file was available, the page is not in English, which is the language used by Geosci. Model Dev., making its use difficult by most of the readers of our journal.
    I am not sure we can accept your statement saying that a contract precludes code availability. If the condition is that the code can be available at the end of a project and not before, then the logical thing to do is that you withdraw your manuscript and resubmit it when you can publish the code.
    Also, the statement on limitations for data storage does not seem justified. What amount of data do you say is unfeasible to publish? Some repositories can accept Terabytes, so we need clarification on this.
    Therefore, given that I commented on your manuscript almost one month ago, you did not reply promptly as I requested, and the Discussions stage is closing in a few hours without you having satisfied our requests, I only see the following solutions here:
    Option 1: You reply to this comment before the Discussions stage is closed with all the materials requested. If you can not do it before the Discussions stage closes, you should email us the requested information.
    Option 2: You send to the Topical Editor and me, via email and in a few days, a copy of the contract that you say prevents publication, with a clear indication of its duration and the law that enforces it. If the project is too long (many years), we can study if an exception is of application in this case. And we do not promise that we can make it. Otherwise, if it is a short contract (for example, three years or less), we will reject your manuscript; that said, if this is the case, as said before, I encourage you to withdraw your manuscript and resubmit it when the contract ends. Also, you must send us precise information about what data size is necessary to document your manuscript, preventing you from publishing it. Anyway, we would need that you have issued a DOI for the data and guarantee of internal archival by your institution for several years (usually at least ten years).
    We need to enforce a reply in a short time from you to be sure that we are not wasting the time of reviewers and editors on something that is not publishable.
    Option 3: If you fail to reply and promptly send us the requested information (much faster than your reply to this comment), we will have to reject your manuscript.
    Regards,
    Juan A. Añel
    Geosci. Model Dev. Executive Editor
    
    Citation: https://doi.org/10.5194/egusphere-2022-589-CEC2
    
    AC7: 'Reply on CEC2', Pengfei Xia, 20 Sep 2022
    
    Dear Juan,
    Thank you very much for your reply.
    
    We are very sorry that we were not able to link the Code and Data as you requested. I'm doing this for the first time and I've spent weeks learning how to build Code and Data links. In addition, our server memory is relatively small, and the Code and Data link I established always crashes, causing our established Code and Data link to fail.
    I have communicated with the project partners, and they advised that cannot code for obtaining atmospheric temperature from the wet refractivity can not been disclosed within the past two years. After discussing with other co-authors, we decided to withdraw the manuscript, re-edit the manuscript and wait for the code to be made public before resubmitting it. We greatly appreciate your suggestions and comments on our manuscript, which have greatly improved the quality of our manuscript. Thanks again very much.
    Best Wishes,
    Pengfei Xia
    
    Citation: https://doi.org/10.5194/egusphere-2022-589-AC7
CC3:
'Comment on egusphere-2022-589', qimin he, 09 Sep 2022

Pretty good work, the GNSS has the ability to continuously monitor atmospheric information with high temporal resolution.In future work, the authors can study UHI Intesity with high temporal resolution, especially for real-time GNSS applications. In addition, it can be noted that the UHI intensity of Hong Kong is very small, most regions in Hong Kong are 1-2k, while the author's conclusion is that there is an error of 1.2k (the relative error is too large). In the future, we may try this method in the areas where the temperature varies greatly, and we may be able to get more interesting conclusions.

Citation: https://doi.org/10.5194/egusphere-2022-589-CC3
- AC5: 'Reply on CC3', Pengfei Xia, 16 Sep 2022
  
  Thank you very much for your invaluable time and great efforts toward our manuscript. We respond to your two questions separately.
  1. In future work, the authors can study UHI Intesity with high temporal resolution, especially for real-time GNSS applications
  Response: Thank you very much for your suggestions.
  In the next study, we will increase the time resolution of UHII to 5 minutes utilizing real-time GNSS technology.
  
  2. In addition, it can be noted that the UHI intensity of Hong Kong is very small, most regions in Hong Kong are 1-2k, while the author's conclusion is that there is an error of 1.2 K (the relative error is too large). In the future, we may try this method in the areas where the temperature varies greatly, and we may be able to get more interesting conclusions.
  Response: Thank you very much for your commons and suggestions.
  At present, the accuracy of diagnosing UHII using single ground-based GNSS is about 1.71K (Jorge et al., 2021) . And the accuracy of diagnosing UHII using GNSS tomography technology is about 1.2K. The accuracy of diagnosing UHII using GNSS technology is limited by the accuracy of GNSS data processing and the accuracy of the retrieval of atmospheric temperature from atmospheric refractivity. In particular, the latter is what we will continue to study in the future, in order to further improve the diagnostic accuracy of UHII.
  Reference.
  Jorge, M.A., Lawrence, L. Tang, Y.T. and Terry, M. 2021. A new global navigation satellite system (GNSS) based method for urban heat island intensity monitoring. International Journal of Applied Earth Observations and Geoinformation. 94: 102222. https://doi.org/10.1016/j.jag.2020.102222
  
  Citation: https://doi.org/10.5194/egusphere-2022-589-AC5

Pengfei Xia, Wei Peng, Shirong Ye, Min Guo, and Fangxin Hu

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Short summary

We first present a novel method of monitoring the UHI intensity using GNSS data. We overcomes two major challenges in the algorithm development. The first challenge is the determination of the GNSS tomographic top grid height, and the second challenge is the estimation of temperature from wet refractivity. The result shows that the proposed algorithm can achieve an accuracy of 1.2 K at a 95 % confidence level.


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