the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
| 05 May 2026
Comprehensive validation of MODIS atmospheric temperature profile data across mainland China using sounding observations
Abstract. The vertical profile of atmospheric temperature is crucial for understanding energy transfer within the climate system. The Moderate Resolution Imaging Spectroradiometer (MODIS) atmospheric profile product (MOD07_L2) provides vertical temperature profiles at 5 km spatial resolution. However, comprehensive validation of its absolute accuracy—particularly for lower tropospheric stability (LTS) and temperature inversion layer (TIL) detection—remains limited. Therefore, this study conducted systematic evaluations using sounding data from 74 stations across mainland China spanning 2003–2020, encompassing both daytime and nighttime periods. Results indicated that absolute retrieval accuracy was generally superior at nighttime compared to daytime, with MOD07_L2 demonstrating better performance in upper layers (400–620 hPa) than in lower layers (850–1000 hPa). Nonetheless, retrieval errors at the 700 hPa level exhibited a more pronounced bias (B) relative to other pressure levels. In contrast, LTS accuracy was higher during daytime (r = 0.74, B = 0.04 °C, RMSE = 4.52 °C) than at nighttime (r = 0.57, B = 0.3 °C, RMSE = 6.78 °C).For TIL, MOD07_L2 displayed limited detection capability, achieving an overall detection rate of 6.6 % during daytime and 13.1 % at nighttime. This study provides essential data support for atmospheric science, hydrology, and ecology fields that rely on high-resolution vertical temperature profiles.
Competing interests: At least one of the (co-)authors is a member of the editorial board of Atmospheric Measurement Techniques.
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Status: open (until 06 Jul 2026)
- RC1: 'Comment on egusphere-2026-2290', Anonymous Referee #1, 30 May 2026 reply
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RC2: 'Comment on egusphere-2026-2290', Anonymous Referee #2, 11 Jun 2026
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Manuscript Title: Comprehensive validation of MODIS atmospheric temperature profile data across mainland China using sounding observations
This manuscript presents a comprehensive and valuable validation of the MODIS MOD07_L2 atmospheric temperature profile product over mainland China using long-term (2003–2020) radiosonde observations from 74 stations. The study is well-motivated, addresses an important gap in high-resolution satellite product evaluation (especially for derived variables LTS and TIL), and covers diverse climatic and topographic regions. The analysis is systematic, the results are clearly presented, and the discussion provides useful insights for both data users and algorithm developers. The paper is suitable for Atmospheric Measurement Techniques or a similar journal. Only minor issues in clarity, language, consistency, and presentation need to be addressed. So I suggest accept with minor revisions.
Comments
- Temporal matching window: The choice of |Δt| < 2 hours is justified by sample size vs. accuracy trade-off, but the sensitivity analysis (Fig. 2) shows noticeable degradation in some regions (e.g., HHH daytime bias -1.77°C). Please add a brief sentence in Section 2.3.2 or 3.1 quantifying the overall impact on national-scale statistics and explicitly state why <2 h remains acceptable despite regional variations.
LTS calculation: Clarify whether surface pressure from MOD07_L2 is used directly for potential temperature calculation or if any quality control/filtering is applied (e.g., cloud contamination flags). This is important because LTS is a derived variable sensitive to near-surface values.
- In abstract “absolute retrieval accuracy was generally superior at nighttime” — consistent with results, but specify that this holds mainly for absolute temperature, while LTS performs better daytime. Add one short sentence on the 700 hPa bias, as it is highlighted as noteworthy in the discussion. “For TIL, MOD07_L2 displayed limited detection capability, achieving an overall detection rate of 6.6% during daytime and 13.1% at nighttime.” — Excellent; no change needed.
- Some citations appear slightly outdated or generic (e.g., several 2025 papers). Ensure all are correctly formatted and accessible.
Section 4.1 and 4.2 are strong, but condense repetitive explanations of why lower layers perform worse (surface influence, terrain, clouds). Merge similar sentences.
4 .Equation (2) and (3): Clearly define all variables the first time they appear (e.g., Γ as lapse rate). In 2.3.3, specify the exact formula used for potential temperature (include the κ = R/Cp value explicitly). TIL detection (Eq. 6): Define “co-detected” more precisely — does it require the same pressure level or just presence in the same profile?
5.Figures 3–6: The density scatter plots are useful, but consider adding a summary table of national-averaged r, B, RMSE for each pressure level (day/night) to improve readability. Fig. 7–10: Legends and color scales should be consistent across day/night panels.
In 3.2 and 3.3, some sentences are repetitive (e.g., “better in upper layers”). Streamline.
6.Several awkward phrasings and minor grammatical issues (common in non-native writing). Examples: can represented key temperature” → “can represent” “20203.3” (typo in Figure 4 caption) “the B in some regions became larger: during daytime...” — improve flow. “no inversion layers were detected on the TP and in the SB” — “were not detected”.
- Consistent terminology: Use “MOD07_L2” uniformly; avoid switching between “retrievals”, “retrieved temperatures”, etc.
8.Fig. 1: The agricultural zoning link is given — ensure the figure clearly labels all nine zones (NEP, NAS, etc.).
All figures: Improve caption completeness (include what “ΔP” exactly means).
Consider moving some detailed spatial maps to supplementary material if the journal has length limits.
9.Check DOIs and formatting consistency. A few recent citations (2025) should be verified for final publication status.
Citation: https://doi.org/10.5194/egusphere-2026-2290-RC2
Data sets
Radiosonde observations from 74 stations in China China Meteorological Administration http://weather.uwyo.edu/upperair/sounding.html
MODIS MOD07_L2 atmospheric temperature profiles NASA MODIS Science Team https://ladsweb.modaps.eosdis.nasa.gov/search/
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- 1
This manuscript addresses a topic of significant scientific importance and novelty. It provides a nationwide, long-term (2003–2020) systematic validation of MODIS atmospheric profile products using radiosonde observations. By extending the evaluation beyond near-surface temperature to include key parameters such as Lower Tropospheric Stability (LTS) and Temperature Inversion Layer (TIL) detection, the study offers a more comprehensive assessment than many previous regional or single-parameter focused works. The scope is substantial, the analytical framework is well-structured, and the conclusions carry considerable reference value for regional climate monitoring, weather analysis, and environmental research. Nevertheless, the manuscript would benefit from improvements in the quality of English expression, the depth of result interpretation, the clarity of figure presentation, and the focus of the literature review. I therefore recommend acceptance after minor revisions.
Minor Comments and Suggestions for Improvement
2.1 Language and Presentation
The most pressing issue is the English language quality. The manuscript contains numerous non-idiomatic expressions, grammatical inaccuracies, and awkward phrasings that reduce its readability and professionalism. I strongly recommend a thorough language polish by a native English speaker or a professional editing service before resubmission.
2.2 Results and Discussion
The discussion section would be strengthened by providing deeper physical interpretations of the observed biases. For example, the pronounced bias at 700 hPa deserves more specific explanation — possibly linked to its role as a key interface for weather systems or the characteristics of the instrument’s weighting functions.
Additionally, all figure titles and axis labels should be reviewed for clarity and precision. For instance, the Y-axis label in Figure 6 (“LTS from MOD07_L2 (K)”) could be more clearly expressed as “MODIS-derived LTS (K)”.
2.4 Literature Review
While the introduction cites relevant background literature, it could be further strengthened by directly referencing studies most closely related to this work. Incorporating specific regional validations of MODIS temperature and water vapor profiles in China (e.g., Ouyang et al., 2015 in the Heihe River Basin) would better contextualize the present contribution and highlight its added value.
Overall Assessment
This study holds high scientific value and rests on a solid methodological foundation. However, the current presentation does not yet meet the standards of high-quality international journals. I encourage the authors to address the above points, particularly through a comprehensive language revision and deeper interpretation of the results. Once these issues are resolved, the manuscript will represent a valuable and publishable contribution to the field.