| Abstract: | The classification of the Northeast China Cold Vortex(NCCV) activity paths is an important way to analyze its characteristics in detail. Based on the daily precipitation data of the northeastern China(NEC) region, and the atmospheric circulation field and temperature field data of ERA-Interim for every six hours, the NCCV processes during the early summer(June) seasons from 1979 to 2018 were objectively identified. Then, the NCCV processes were classified using a machine learning method(k-means) according to the characteristic parameters of the activity path information. The rationality of the classification results was verified from two aspects, as follows:(1) the atmospheric circulation configuration of the NCCV on various paths; and(2) its influences on the climate conditions in the NEC. The obtained results showed that the activity paths of the NCCV could be divided into four types according to such characteristics as the generation origin, movement direction, and movement velocity of the NCCV. These included the generation-eastward movement type in the east of the Mongolia Plateau(eastward movement type or type A); generation-southeast longdistance movement type in the upstream of the Lena River(southeast long-distance movement type or type B); generationeastward less-movement type near Lake Baikal(eastward less-movement type or type C); and the generation-southward less-movement type in eastern Siberia(southward less-movement type or type D). There were obvious differences observed in the atmospheric circulation configuration and the climate impact of the NCCV on the four above-mentioned types of paths, which indicated that the classification results were reasonable. |
