# Contrails and Their Dependence on Meteorological Situations
## 5 Conclusions  
The research question of whether there is a statistically significant dependence between the properties of the contrails, characterized by selected parameters, and the observed meteorological variables was answered in Section 3.2.1. The dependence between contrails and meteorological variables was demonstrated using linear regression for relative humidity with respect to water, relative humidity with respect to ice, and temperature. No significant dependence was shown with statistical analysis for other meteorological variables: wind direction and speed, tropopause height, and atmospheric pressure. These variables carry additional information; they have a minor influence on the contrail lifetime.  
The second question, whether the characteristics of contrails can be estimated from meteorological data based on prediction models, was answered in Section 3.2.2. The selected classification methods were able to classify the contrail lifetime with sufficient quality. The best model was developed using Random Forests, and its classification results in 97% accuracy, with high reliability in predicting both short-lived and long-lived contrails with a resolution of 1 min. Several models have been developed to simulate and predict the properties of a large set of contrails as a function of given air traffic and meteorological conditions using advanced statistical methods (five classification models). The models are intended for the classification and prediction of the occurrence of short-lived and long-lived contrails.  
This study presents specific partial results on how to predict long-lived contrails depending on measured explanatory meteorological variables. The initial condensation properties depend on the aircraft and the relative humidity with respect to water. The evolution of the contrails is monitored based on the ambient meteorological conditions. Of the variables studied, relative humidity with respect to ice and then relative humidity with respect to water were found to have the most significant effect on the contrail lifetime. The results of the study then point to the possibility of classifying the dependence of the contrail lifetime on meteorological conditions using models, and given the uniqueness of the study, they also offer new insights into the issue under investigation. The Random Forests method, which satisfies research question 2, gave the most accurate result for modeling the contrail lifetime. The research results refine the level of scientific knowledge about the occurrence and properties of contrails.  
Conceptualization, I.K.; methodology, I.K., I.N. and J.H.; software, I.K. and I.N.; validation, I.K. and J.H.; formal analysis, I.K. and J.H.; investigation, I.K.; resources, I.K.; data curation, I.K.; writing--original draft preparation, I.K. and J.H.; visualization, I.K. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the CTU research support budget.  
Not applicable.  
The raw data supporting the conclusions of this article will be made available by the authors on request.  
The authors declare no conflicts of interest.