Global Assessment of the GNSS Single Point Positioning Biases Produced by the Residual Tropospheric Delay

Round 1

Reviewer 1 Report

This article is a re-submission of a previous contribution. It aims to assess the influences of the residual tropospheric delay on Single Point Positioning (SPP) solutions globally, considering nine conventionally Zenith Tropospheric Delay (ZTD) models.

The English language is quite adequate, and the content is complete even if the topic is not new.

The main question that arises is the same occurred in the previous case: for which reason a user would be interested in exploiting the SPP method instead of other positioning techniques like the NRTK or PPP ones, especially now where even loc-cost and portable devices can apply corrections from networks or local models.

Thus, it is important to highlight what could be the benefit of this approach concerning the classical one, in my opinion.

Besides, some questions arise:

-              what is the benefit of this approach from a positioning point of view?

-              regarding Eq.1: are these equations valid for all GNSS constellations?

-              Why didn’t you use the carrier-phase measurements?

-              Line 105: is the meaning of N the float ambiguity? Are you sure it is float?

-              Line 277: why did you use the GPS-only constellation? And why the cut-off angle is 7°? Please justify these assumptions.

-              why did you use the Bernese 5.2 without adding the proper citation?

-              What’s the benefits of your software concerning some open-source, available today (e.g., RTKLIB)?

The reference section is now adequate.

The paper can not be accepted in the present form but needs a deep revision starting from the previous considerations.

Author Response

Please see the attachment.

Author Response File: Author Response.docx

Reviewer 2 Report

Dear Authors,

Valuable work within your article was done.

Several remarks:

• define every acronym when appeared in text for the first time,
• check the meaning of JPL acronym,
• Table 2 is a bit messy - rows are messed up,
• when writing an equation which is not derived on you own, please cite proper reference,
• in line 346 you've mentioned a MATLAB software - can you please describe it in few word/lines,
• please put units on vertical axis of figures with column diagrams,
• please put units id description row (aside NEU) in Table 5.

Thank you.

Best regards

Author Response

Response to Reviewer 2 Comments

Point 1: define every acronym when appeared in text for the first time

Response 1: Thanks and revised in line 51.

 

Point 2: check the meaning of JPL acronym

Response 2: Thanks and revised in line 252.

 

Point 3: Table 2 is a bit messy - rows are messed up

Point 7: please put units id description row (aside NEU) in Table 5.

Response 3&7: Thanks and revised.

 

Point 4: when writing an equation which is not derived on you own, please cite proper reference

Response 4: Thanks and equation (2), (4), (5) have added reference.

 

Point 5: in line 346 you've mentioned a MATLAB software - can you please describe it in few word/lines

Response 5: Thanks and we add the description in line 355: ‘It counts about data from 400 stations with a time slot of 28 days, and the data sampling rate is 5 minutes. ’

 

Point 6: please put units on vertical axis of figures with column diagrams

Response 6: Thanks and we have modified figure 2,3,4,5,6,9,10,11.

 

At last, great thanks again for spending a great deal of time for reviewing this manuscript. We heartfully appreciate you for the valuable and detailed comments on so many crucial issues, based on which we can have a chance to improve and revise our work.

Round 2

Reviewer 1 Report

The paper has been modified according to my suggestions, and it has been improved.
Despite that, I'm still not convinced about the paper's content: the main doubt is related to this approach's benefits instead of the other positioning techniques.

Author Response

Thanks. The main contribution and novelty of this paper is to answer the question “How much the uncorrected residual tropospheric delay would sway the SPP positioning solutions on a global scale?”.  Unlike PPP and NRTK, residual tropospheric delay after model correction cannot be further compensated by parameter estimation in SPP. Therefore, it is worth to anticipate how much the uncorrected residual ZTD would sway the SPP solution in different locations around the world, so that SPP users can optimally determine which ZTD model is used to seek the highest computation efficiency under required positioning precision. Results of our study can provide references for the refinement and applications of the nine ZTD models for SPP users. For example, in section 5, we briefly give some recommendations about which ZTD model is the better choice for SPP users with different accuracy requirements at different geographical locations.

To clarify the main contribution, we have rewritten the abstract section as “The tropospheric delay is one of the main error sources that degrades the Global Navigation Satellite Systems (GNSS) Single Point Positioning (SPP) accuracy. Although an empirical model is usually applied for correction and therewith to improve the positioning accuracy, the residual tropospheric delay is still drowned in measurement noise, and cannot be further compensated by parameter estimation. How much this type of residual error would sway the SPP positioning solutions on a global scale are still unclear. In this paper, the biases on SPP solutions introduced by the residual tropospheric delay when using nine conventionally Zenith Tropospheric Delay (ZTD) models are analyzed and discussed, including Saastamoinen+norm/GPT/GPT2/GPT2w/GPT3, UNB3, UNB3m, EGNOS and VMF3 model. The accuracies of the nine ZTD models, as well as the SPP biases caused by the residual ZTD (dZTD) after model correction are evaluated using IGS-ZTD products from around 400 globally distrib-uted monitoring stations. The seasonal, latitudinal, and altitudinal discrepancies are analyzed respectively. The results show that the SPP solution biases caused by the dZTD mainly occur on the vertical direction, nearly to decimeter level, and significant discrepancies are observed among different models at different geographical locations. This study provides references for the refinement and applications of the nine ZTD models for SPP users.”