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Transportation is a fundamental and service-oriented industry of the national economy, which is significantly influenced by weather and climate factors. Implementing traffic meteorological services effectively improves people’s quality of life and socio-economic benefits. In this study, based on the traffic congestion index and road automatic 〖JP2〗weather station observations from 15 November, 2022, to 14 November,〖JP〗 2024, in Beijing, the temporal characteristics of the traffic congestion index and its meteorological impact are investigated. Firstly, the concept of the meteorological congestion index is proposed, and then the traffic congestion index is decomposed to analyse the distribution characteristics of the total congestion index, basic congestion index, and meteorological congestion index. Subsequently, several major adverse meteorological conditions are discussed for their potential impact on traffic congestion. The results show that the annual average traffic congestion index during the morning and evening peak hours in the Beijing urban area is 1.69 and 1.99, respectively. The maximum congestion index during the morning peak hours of the week occurs on Monday, and that during the evening peak hours occurs on Friday. The adverse meteorological conditions that affect transportation during the morning and evening peak hours account for 32.9% and 26.4% of the total sample, respectively; moreover, the proportion of the meteorological congestion index caused by meteorological conditions during the morning and evening peak hours is 17.2% and 11.1%, respectively, with a maximum of 57.2%. This indicates that the impact of meteorological factors on transportation is greater during the morning peak hours than during the evening peak hours. Additionally, the meteorological congestion index presents seasonal differences, with the maximum value occurring in autumn. It is also found that there is a complex synergistic effect between meteorological factors and traffic congestion. The impact on urban traffic congestion is significant under the following conditions: light or heavy rain, road surface temperature close to freezing or below -10 ℃, wind speed above 10 m/s, and visibility below 1.5 km. Furthermore, the results of variance analysis show that low visibility has the highest contribution rate to the meteorological congestion index, followed by precipitation events, road surface temperature, and wind speed, with contribution rates of 27.6%, 11.7%, 7.2%, and 4.6%, respectively. The research results not only provide a basis for government departments to formulate effective traffic management measures and emergency plans, but also provide a reference for guiding residents to choose reasonable transportation modes.