Stratospheric airships，due to their excellent performance，exhibit great potential in flight missions within the aerospace field. However，the complexity of the stratospheric environment presents significant challenges to flight safety. Therefore，conducting environmental forecasts in advance to mitigate flight risks is crucial for the successful completion of airship missions. Although existing thermodynamic models have provided a theoretical foundation for airship design，their analysis remains insufficient. In this paper，two key parameters，cloud top height and cloud top temperature，are introduced to deeply analyze their effects on the airship's thermal balance. Cloud top height determines the relative position between the cloud layer and the airship，while cloud top temperature directly reflects the thermodynamic state of the cloud layer. Both parameters influence the radiative exchange and thermal balance of the airship. Based on this analysis，the importance and urgency of incorporating these factors into thermodynamic models are emphasized，offering new insights for the optimization of future air‐ ship thermodynamic models and revealing the significance of studying cloud layer distribution characteristics. Additionally，the unique advantages of the Qinghai-Xizang（Tibet）Plateau as a natural laboratory are highlight‐ ed，and specific data analysis is conducted. This paper analyzes historical meteorological cloud observation data from 2015 to 2020 in the Qinghai-Xizang（Tibet）Plateau region using the CLARA-A3 dataset，focusing on the spatial distribution characteristics，daily mean and extreme values，cloud area proportions，and the correlation analysis between cloud top height and cloud top temperature. The results show that cloud top height exhibits a spatial distribution pattern of lower in the northwest and higher in the southeast，while cloud top temperature shows a trend of higher in the west and lower in the east. During the period from July to September，cloud top height reaches its highest annual value，and cloud top temperature reaches its lowest. The annual variation pattern of the cloud top parameters is also confirmed. Further analysis indicates the presence of extreme meteorological phenomena，such as ultra-high clouds and extremely low temperatures，with daily cloud top heights exceeding 18 km and cloud top temperatures below -83 ℃，which mostly occur between July and September. A Spearman correlation coefficient analysis reveals a moderate negative correlation between the two variables，with a strong negative correlation during the July-September period. This provides important data support for further quantifying the influence of cloud layers on airship performance. The study shows that the potential threat of cloud layers to air‐ ships cannot be ignored，particularly during the July-September period，when the deployment preparation for stratospheric airships should focus on the changes in local meteorological cloud parameters. Acquiring cloud observation data in advance and implementing meteorological forecasting preparation are key factors in ensuring the safe flight of airships. This research is the first to apply real meteorological data analysis to airship flight environment assessment，verifying the feasibility of data analysis techniques，and emphasizing the critical role of observational data in model validation，providing a new research perspective for improving the thermodynamic models of stratospheric airships. In the future，with the continuous optimization of dynamic prediction models，the safety of airships in complex meteorological environments is expected to be significantly improved.