the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 04 Nov 2024
Measurement report: Can Zenith Wet Delay from GNSS "see" atmospheric turbulence? Insights from case studies across diverse climate zones
Abstract. Global Navigation Satellite Systems (GNSS) microwave signals are almost unaffected by clouds but are delayed as they travel the troposphere. The hydrostatic delay accounts for approximately 90 % of the total delay and can be well modeled as a function of temperature, pressure, and humidity. On the other hand, the wet delay is highly variable with space and time, making it difficult to model accurately. A zenith wet delay (ZWD) can be estimated as part of the GNSS positioning adjustment and is proportional to the specific humidity in the atmospheric boundary layer (ABL). Whereas its average term can describe mesoscale events, its small-scale component is associated with turbulent processes in the ABL and the focus of the present contribution. We introduce a new filtering and estimation strategy to analyze small-scale ZWD variations, addressing questions on daily or periodic variations of some turbulent parameters, and the dependence of these parameters on climate zones. Five GNSS stations were selected for case studies, revealing promising specific daily and seasonal patterns depending on the estimated turbulence at the GNSS station (buoyancy or shear). This research lays the groundwork for more accurate models and prediction strategies for integrated WV turbulence. It has far-reaching applications, from nowcasting uncertainty assessments to the stochastic modeling for Very Large Baseline Interferometry or GNSS.
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Status: open (until 16 Dec 2024)
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RC1: 'Comment on egusphere-2024-2680', Anonymous Referee #2, 19 Nov 2024
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General Comments
The manuscript describes a method to derive turbulence parameters from observations by ground-based GNSS stations. These observations are processed to obtain time series of the equivalent total zenith propagation delay. After a filtering process a time series of estimated variations in the equivalent zenith wet delay are used to characterise turbulence. I find the work interesting and unique, but have some thoughts concerning a critical assessment of the results and the structure and the clarity of presentation.
A first reflection is why the manuscript was submitted to ACP rather than AMT (Atmospheric Measurement Techniques). I find that the method, rather than the estimated turbulence parameters, is the motivation for publishing (and the title also starts with "Measurement Report:". I assume this is a question for the editor.
The time series of the Zenith Wet Delay (ZWD) from the GNSS data processing has a temporal resolution of 30 s. It is stated that no constraint is applied (line 122) but the estimates of the ZWD are averages of the air in the sampled volume. This volume depends on the elevation cutoff angle and which GNSS that were used. I miss information about this. If a frozen flow is assumed (as you do in the manuscript) and an elevation cutoff angle of say 5 or 10 degrees is used, quite a high wind speed is required in order to have independent air volumes with a sample period of 30 s. This issue should be discussed and how the results are affected by this fact. Depending on the conclusions you may want to reduce the temporal resolution.
A related issue is that there is a need to validate the GNSS wet delay time series obtained with the method you describe. One possibility is the use of microwave radiometry. The main advantage of the radiometer is that it samples a much smaller volume and it can measure in the same direction continuously. (Also in this case, however, the temporal resolution for independent samples is limited by the sampled air volume, which in turn is determined by the antenna beam width(s).) Probably none of the sites you study is equipped with a radiometer. However, there are several GNSS/VLBI sites that offer this possibility, see e.g. Teke et al. (2013) (Troposphere delays from space geodetic techniques, water vapor radiometers, and numerical weather models over a series of continuous VLBI campaigns, J. Geod.,87:981–1001, DOI 10.1007/s00190-013-0662-z).
You present results for one summer and one winter day for each GNSS station. I find this to be insufficient. If I may be a bit provokative, but a data point in a climate time series is often an average over 30 years. I have not visited all the sites studied but I have been in similar climates and my experience is that the weather conditions may change considerably from one day to another (possibly excluding the tropical site). I do not argue that you shall use data from several years, but because you spend much effort on comparing the results from the different sites there is a high risk for overinterpretation. One month, or at least one week, of data from each site and season will make more sense. I think it will also be of interest to compare the parameters estimated for adjacent days.
A related matter is that the argument that the spring and the autumn may be slightly different for the tropical station (SEY2) is definitely valid for all the stations. Consequently I recommend to handle all the stations in the same way. Furthermore, to me it does not make sense to present the "extra" results for RIO2 and SEY2 in appendices. It will be easier for the reader to follow if all the results for each station are presented together. (See more details in the section with specific comments below)
Specific comments
In the abstract (and in line 30) you state that "microwave signals are almost unaffected by clouds but are delayed as they travel the troposphere". In many geodesy applications the induced effect on the delay by clouds are ignored because thy are comparable to the uncertainties. In your case however, you surpress the large variations in the estimated propagation delay by filtering and the question is then how the small scale variability in the delay caused by clouds affect your interpretations of the turbulence parameters. For example, cumulus clouds may cause delays of several millimetres. Solheim et al. (1999)( Propagation delays induced in GPS signals by dry air, water vapor, hydrometeors, and other particulates, J. Geophys. Res., 104, 9663–9670) state that "A cloud droplet concentration of 1 g/m^3 for a distance of 1 km has an integrated liquid value of 1 mm and would therefore induce a radio path delay of 1.45 mm." In Line 36 it is stated that the topic is on WV turbulence. Perhaps it will be more correct to refer to turbulence due to WV and liquid water clouds?
In Section 2.1 you mention briefly that the ZTD can be estimated from GNSS observation. I think this is the appropriate place to give the details on how this is done rather than in the paragraph starting on Line 120.
Line (L) 219: It is not clear to me why satellite orbit and clock errors can be ignored. Do you mean that the products from GFZ are free of error? This cannot be true. If you believe that these errors are small enough to be ignored, it needs to be motivated.
Table 1: "Gravity waves" is not a type of climate. You may instead call it characterisation of GNSS station. Additionally, it is not really needed to present this in a table (with only one line as an entry). Each site can be described/characterised in the running text.
L 238-240: When checking the supplementary material I find that there is only one additional day for each site and season. From just reading the information available one cannot conclude that this material support your conclusions. As mentioned above you need more than one day of data to characterise the turbulence at a site.
Another question related to the supplementary material is that when I randomly checked some of the data files I find that the ground pressure is constant over the entire day in all cases. Does that mean that when you subtract the hydrostatic delay from the ZTD it has a constant value and that any variations in the hydrostatic delay will alias with the wet delay variability? This needs to be explained / discussed.
L 400-404: You have not presented any results for the PAYN station, so there is no need to discuss such results. If it is of relevance for this study I think it shall be included rather than referring to the "next contribution".
L 420: Also here the "next contribution" is mentioned. It is sufficient say that confirmation is needed because the reader will not know where the next contribution is to be found.
Technical CorrectionsA general comment: At many places you use the wording "in this contribution" (or something similar). In most cases these words should be deleted. It is obvious, e.g. L 8, 55, 178, 184, 215-216, 240, and 380.
L 3: 90% --> 90 % (Also at many other places: insert a "space" between the value and the unit (SI recommendation). Also there shall be no dash between the value and the unit.)
L 32: You probably mean hydrostatic delay (not dry), which is the term you use elsewhere?
L 48: Why is the slope not mentioned here?
Figure 1: Correct the labels on the y axis in the ZWD' graph (too close for a good readability).
L 104: Better to write the mathematical expression in one line, or make it a numbered equation.
L 106: Units shall not be in italics.
L 109: 1 hour --> 1 h
L 121: 30-second rate --> 30 s rate
L 126: 4h --> 4 h UT
L 170: Better to write the mathematical expression in one line, or make it a numbered equation.
Figure 2: The time series graphs are too small, make them bigger or delete them (they are not really needed)?
L 220, 221, 222, 223, 226: shall read 30 s, 1 h, 24 h
L 284: Do not start a sentence with a symbol.
L 318 & 326. RIA2 --> RIO2
L 411: 375 unit?
L 422: automn --> autumnCitation: https://doi.org/10.5194/egusphere-2024-2680-RC1
Data sets
Zenithwetdelay Gael Kermarrec and Zhiguo Deng https://doi.org/10.25835/HCC01FRE
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