General:

This paper is well-written and presents new and interesting results. It relies solely on experimental data to establish positive trends in cold point temperatures for the period 2002-2020, subsequently leading to corresponding positive trends in stratospheric water vapor. The paper explores the seasonality of these trends and their zonal patterns, offering a comprehensive analysis. The abstract effectively summarizes these crucial findings.

One particularly noteworthy discovery is the observed decrease in tape-recorder amplitude over the last two decades. The findings are supported by clear and well-constructed figures. However, a minor improvement could be made regarding the crosses in the figures that mark statistically nonsignificant trends, as it can be challenging to see them. Congratulations on this convincing piece of work.

Here, few detailed comments:

Abstract:

L20 ...on the other hand, seems to be related...

L36: As your introduction is very comprehensive, I would also suggest referencing Riese et al, 2012, doi:10.1029/2012JD017751. See their Figure 1 for insight into the motivation behind the extreme radiative sensitivity of the TTL in relation to its composition.

L97: Concerning your sententce:

"Zonal mean temperature trends from reanalysis over 2002–2020 suggest small but substantial cooling of -0.3 to -0.6 K/decade at 100 hPa and AT the cold point, which are statistically compatible with trends based on the adjusted radiosonde data sets (Tegtmeier et al., 2020a)."

I believe Figure 11 from the cited paper displays results for the 1979-2005 period, not the 2002–2020 period as mentioned in the sentence. Additionally, you later demonstrate that the trends are predominantly positive, not negative, for the 2002–2020 period. Please provide clarification.

L125-135

It would be nice to have 1-2 sentences, how does radio occultation work and how atmospheric temperature can be derived from such observations

L145

I thought, the newest SWOOSH version uses MLS v5.1?

L153

It would be nice to have the explanation of the abbraviation "SAOD" in this sentence and not first in L159.

L171 Please reformulate:

It should be emphasized that substantial residuals (not shown here) indicate a significant portion of variability of around 70%....

You mentioned that only 30% of the variability can be explained by your MLR model. Sometimes, people utilize lagged MLR models, considering that ENSO and SAOD signals take time to propagate from their source regions (ENSO - from the Earth's surface, SAOD -from the maximum of aerosol absorption around 50 hPa) to the region of interest. This might slightly increase the amount of variability that can be explained by the MLR.

Fig 4.

I think, you show mean tropical values (20S-20N). You should mention it both in the caption and in the text.

Review for ‘variability and long-term changes of tropical cold point temperature and water vapor’ by Zolghadrshojaee et al.

This work uses GNSS-RO satellite data, with a very high vertical resolution to study the trend of the tropical tropopause layer (TTL) during the past 20 years, and uses SWOOSH homogenized satellite data and MLS satellite data to study the trend of water vapor. This paper is well structured and almost all points are clearly explained. The trend was studied in terms of different location and seasons, and the authors tried to explore the role of radiation and dynamics in the observed trend. I recommend a minor revision before accepting this paper.

Major comment:

The major comment of this paper is regarding the conclusion ‘overall observed warming of the cold point is due to radiative effects, and seasonal signals and zonal asymmetries are due to dynamics’ in line 383, section 5. I agree with the analysis in section 3, and the conclusion that ‘cold point warming is connected to patterns of enhanced and reduced upper troposphere warming via some regional dynamical or radiative processes’.

However, this does not necessarily lead to the conclusion in line 383. It could only be drawn when the authors analyzed (1) the seasonality and location of the BDC, (2) the overall trend of the BDC, (3) the seasonality and location of the convection, and (4), the overall trend of the convection.

The authors do not provide the location/seasonality/overall trend of the Brewer-Dobson circulation (dynamics), so it is hard to conclude that the BDC are not accounting for the overall trend and instead just the seasonality and location.

The authors also listed previous works that concerning the overall BDC trend in lines 354-369, and this may contribute to the overall trend of the TTL temperature. I don’t understand why the conclusion is ‘it explains the seasonality’, instead of the overall trend.

Minor comments:

1. Line 76: the Brewer-Dobson circulation also plays an important role, see major comments.
2. Line 81: “a very high vertical resolution”: it will be better if the authors provide an estimated number of the vertical resolution.
3. Line 129: 30°x10°: please clarify what is latitude and what is longitude.
4. Line 153: SAOD: this is the first time that the term “SAOD” is used, please define this abbreviation.
5. Line 252: SWOOSH result is very different from MLS, which uses the MLS 4.2 with a drift problem, but it is also a homogenized data and has its strength when comparing with MLS. How much of the difference between SWOOSH is due to MLS 4.2, and how much is from other satellite data? For example, the authors can compare the trend of SWOOSH data, MLS 4.2, and MLS 5.0.
6. Line 309: “due to the influence of other seasonal signals in the middle atmosphere”: like CH4?
7. Line 385: ‘seemed to be’ is too vague. See major comments.