Abstract: Based on daily minimum temperature data collected at 70 national weather stations and reconstructed data collected at more than 1300 regional automatic stations during the same period from 1961 to 2020 in Jiangsu province, four variables related to cold waves are selected as the meteorological disaster causing factors of cold wave disasters. The weight of each disaster causing factor is determined by combining the information entropy weighting method and Delphi method. A disaster risk assessment model is established to produce a long-term series of disaster risk index, which is then used to determine the risk level by the percentile method. Based on intelligent grid temperature prediction data, the predicted disaster risk index for the cold wave process is calculated. A risk pre-assessment model for cold wave processes is then constructed by combining the exposure and vulnerability information of the disaster bearing body. The impact of early temperature on wheat growth is also considered to modify the wheat vulnerability index. The results are as follows: (1) The frequency of cold wave events in Jiangsu province generally has shown an upward trend in the last century and a downward trend in the 21 century, and the frequency of occurrence is significantly higher in northern Jiangsu than in southern Jiangsu. The intensities of meteorological disaster causing factors are generally stronger in the west than in the east, and stronger in the north than in the south. (2) Based on the case study of the cold wave event from 28 November to 3 December 2022, it is found that the results of the risk pre-assessment basically are consistent with actual disaster situation.