The pick-up algorithm by the k-th order cluster for the closest distance is used in the fields of weather and climactic events, and the technical terms clustered index and high clustered region are defined to investigate their temporal and spatial distribution characteristics in China during the past 50 years. The results show that the contribution of extreme high-temperature event clusters changed in the period from the 1960s to the 1970s, and its strength was enhanced. On the other hand, the decreasing trend in the clusters of low-temperature extremes can be taken as a signal for warmer winters to follow in the decadal time scale. Torrential rain and heavy rainfall clusters have both been lessened in the past 50 years, and have different cluster characteristics because of their definitions. Regions with high clustered indexes are concentrated in southern China. The spatial evolution of the heavy rainfall clusters reveals that clustered heavy rainfall has played an important role in the rain-belt pattern over China during the last 50 years.

In this paper, we break down sea surface temperature(SST) anomaly field by using the empirical orthogonal function (EOF) to obtain a rebuilding space made up of different patterns which are orthogonal to each other, then we unfold 500 hPa temperature field in this space. Furthermore, with the method of Bayesian analysis, we define the impact index of different patterns on 500 hPa air temperature field and research the variation characteristic of index with the change of spatial pattern of SST. It is found that SST field has a great effect on 500 hPa temperature field between April to June. Besides, after the abrupt climate change, different patterns of SST have different effects on temperature field.