南海-海洋大陸之次季節擾動與中緯度-熱帶交互作用

Siberian High is dominant over East Asia during winter. In the scientific literature, its center, domain, and tracking of its split highs are mainly done with subjectively observing the weather maps, such as that in Ding and Krishnamurti (1987). This traditional analysis is subjective, so the same results may not be reproduced by a different researcher even using the same weather charts. The process is particularly painstaking for long-term climate analysis. Besides, past weather charts may not be easy to retrieve and be handy to use. In this study, we develop a series of algorithms for objective analysis that consist of two major steps: 1) Read gridded SLP data and identify high centers; 2) Track the movement of high centers. We apply this objective analysis on the 1948–2017 NCEP reanalysis data and compare our results with those of Ding and Krishnamurti (1987). On the other hand, to verify the reliability of our tracking algorithms (Step 2), we use the CWB SLP charts in 2000/01 and 2001/02 winters to subjectively read out locations of all high centers and feed them into the algorithm for objective tracking. In the meanwhile, we also subjectively track these high centers and compare the results to those of the objective tracking. About 63% of subjectively analyzed tracks can be identified by the objective method, 13% are partially established, and 24% are totally lost. From the results of objective analysis on the 1948–2017 NCEP reanalysis data, movement of high center tracks can be categorized into three: 1) West (W) tracks where high centers move eastward and merge with the Siberian High; 2) Northeast (NE) tracks and 3) Southeast (SE) tracks that are splits of Siberian High that move northeastward and southeastward, respectively. In the long-term mean, frequency of the SE (NE) tracks is negatively (positively) correlated with the strength of Siberian High. In terms of interdecadal variations, frequency of both NE and SE tracks are higher in the latter half (1983–2017) period, while the opposite is true for the W tracks. We also study the cold surge events over Taiwan and their associated pressure patterns. Focusing on years of 2000–2017, we recognize 56 cold surge events and categorized them into three: 25 cold events with fast temperature drop and a high-latitude blocking around date line (Blocking, Cold, with fast temperature Drop, BCD), 6 cold events with pressure blocking but slow temperature drop (Blocking and Cold, BC), and 26 cold events with fast temperature drop but no blocking (Cold and fast temperature Drop, CD).