the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 08 May 2025
Evaluation of middle atmosphere temperature and wind measurements and and their disturbance characteristics by meteorological rockets
Abstract. It is necessary to carry out the in-situ detection based on the meteorological rocket to deepen the cognitive level of the middle atmosphere environment, though there is still a lack of systematic research on the data accuracy and the physical mechanism affecting the measurement results, which restricts the effective use of rocket data. Based on thermistor and Beidou positioning, combined with temperature correction technology, middle atmosphere temperature and wind measurements from 20–60 km are obtained in northwest China by two meteorological rockets. The detection results are compared with satellite, empirical model and reanalysis data, and the error analysis theory is carried out in combination with the of the drop sounding and atmospheric disturbance characteristics. The results show that the data quality of the rocket detection is ideal, and the variation trend of temperature and wind profile with altitude is consistent with other data. The difference comes from the deviation of the matching data in time and space and the excessive measurement error in the initial fall stage. Also, it is found that the instability of the parachute causes poor positioning data quality and fast falling speed, and eventually cause the measurement error at the corresponding height to be significantly larger. Besides, the profile fluctuation of the first detection is more obvious, which is caused by the fragmentation of the high-altitude gravity wave. Wave dissipation leads to the weakening of atmospheric stability and the generation of denser small-scale layered structures on the profile, making significant wind field changes at the height below through the momentum deposited.
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RC1: 'Comment on egusphere-2024-4172', Anonymous Referee #1, 26 May 2025
The paper represents a rocket-borne technique for measurement of winds and temperature in the middle atmosphere between 20 and approx. 55 km.
The temperature measurement technique uses a thermistor and has been known since the early 1960th and was widely used in the last century.
Wind measurements are made by making use of the GNSS BeiDou.
Additionally, the system measures atmospheric pressure by a "silicon piezoresistive manometer". The measured data is transmitted to the ground by a built-in telemetry system. Authors claim that the density can also be derived from those measurements by using the ideal gas law: p=nkT, where p and T are the measured pressure and temperature, k is the Boltzmann constant and n in the number density of the ambient atmosphere. However, the density measurement results do not appear in the paper.The paper is difficult to read because of a very specific language used alongside not commonly accepted terms. The results are clearly summarized, however not well-supported by the arguments.
After a brief introduction of the measuring instruments in Sec. 2, temperature retrieval including error analysis, is described in detail. Also, measurement error for wind soundings is addressed in this section.
After that, the paper is focused on derivation of small-scale temperature and wind fluctuations and comparison with the satellite-borne SABER measurements and MERRA 2 reanalysis data.
Since the manuscript is submitted to the AMT, I expected to learn more about the measurement technique itself, the instruments and data retrieval. A detailed description of the instrument is not present in the paper. In particular, which kind of sensors (thermistor, pressure sensor) were used. Either these were commercially available parts or self-made sensors. This knowledge will further help to clarify two important questions: resolution and sensitivity of the measurements. The paper by Wagner, 1961 sited in this manuscript, concludes that "Time constant and fall velocity considerations prohibit the measurement of small-scale temperature fluctuations". I accept that the new sensors can be more sensitive and much faster. However, this should be shown in this manuscript, since the main focus is made on the fluctuation measurements. Also, no information on the telemetry requirements (transmitter, receiver, bandwidth, sampling rate, etc.) appears in the manuscript.
The main focus in the entire paper is made on the fluctuation analysis, with an attempt to demonstrate that these measurements are suitable for investigation of small-scale processes like gravity waves and turbulence. This part looks to me neither consistent nor complete.
In Sec. 5 authors focus on deviations of measurements (wind and temperature) from MERRA2, SABER, and MSIS. This makes no sense to me. The general comparison in the left panels of Figs. 5 & 6 looks very convincing and sufficient.
However, the next sections deal with fluctuations. Their extraction method is described in the text: 20-point sliding average, interpolated profile with 50 m interval, and fitted fifth-order polynomial to get the background profile. Additionally, high-pass filtering with a cut-off wavelength of 10 km is applied.
This decomposition into background field and fluctuations needs a demonstration by proper plots, which is not shown in the paper (neither background nor fluctuations). Also, the missing data on resolution and sensitivity of the measurements would help to judge on the quality of the derived fluctuations.Next, spectral analysis is applied to the derived fluctuations. The way it is done looks strange to me. The same time series was analyzed by both the Lomb-Scargle (Fig. 10) and the Fourier (lowest panels of Fig. 11) analyzes. They should demonstrate quite similar picture, which is not the case here. It is not clear to me where such a difference comes from and why authors need the Lomb-Scargle analysis. Why, in particular, the Fourier spectra do not reveal the same dominating wavelengths as shows the Lomb-Scargle. Also, the speculations about dominating slope in the spectra do not look convincing: there are different slopes in those spectra, better pronounced in the right panel. Another question is: what the noise of the instrument itself look like? If the instrument (thermistor) reveals, e.g., red noise, the slopes in spectra demonstrated in the manuscript cannot be interpreted so directly.
It is also quite commonly accepted now, that the gravity waves often propagate as wave packets along very different pathways (directions, inclination angles, etc.). This leads to an observational challenge, that they rather appear in a small part of the measured altitude profile. These wave packets can better be localized by the wavelet analysis.
To my knowledge, the Stokes parameters derived in the Sec. 7.2 yield a relatively coarse description of the gravity waves in comparison with other methods. The measurements described in this paper (zonal and meridional winds and temperature) allow applying a more advance and precise analysis technique, the hodograph method.
To summarize. I suggest improving the description of the instrument by adding more technical details. If authors want to make a fluctuation analysis, important parameters are the resolution and sensitivity of the measurements, as well as the deduction method of fluctuations.
Citation: https://doi.org/10.5194/egusphere-2024-4172-RC1 - RC2: 'Comment on egusphere-2024-4172', Anonymous Referee #2, 19 Aug 2025
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