Geoscience Reference
In-Depth Information
front, rapid or slow movement can directly influence the temporal and
spatial distribution of the summer rainfall in East China.
3. The Abrupt Changes of EASM in Interdecadal Timescale
From the above discussion, we know that the EASM's movement influenced
the rainfall in East China mainly during the 28th-45th pentad. As EOF
technology develops especially in recent 10 years, it has been one of the
most important climate diagnosis methods. Firstly, the time average EASM
index (Im) (for 28th-45th pentad) is made every year and each data sample
is subtracted from the average for 44 data sample in each grid, getting 44-
year gridded abnormalities of EASM index from 1958 to 2001, then
44 abnormalities of EASM index are analyzed (1958-2001) in area (15
◦
N-
55
◦
N, 105
◦
E-150
◦
E) by EOF method. Essentially, EOF made the evolution
of physical fields divided into a few independent evolutive processes. Based
on the method of North
et al.
,
16
the first three modes cleared the significant
test. The variance contributions of three modes are 28.2%, 18.0%, 12.6%,
respectively. In order to discuss the interdecadal characters of EASM's
movement, the time coecient of the second eigenvector exhibits three
distinct interdecadal shifts in 1965, 1980, and 1994, respectively (Fig. 4(b)),
the second mode is studied mainly in this paper. The second eigenvector
present that the abnormal EASM's index is positive in north of the mid-
lower of Yangtze Valley while it is negative in south of the mid-lower of
Yangtze Valley (Fig. 4(a)). If the time coecient is positive, indicating that
the EASM is stronger (weaker) or stay longer (shorter) than the normal in
north (south) of the mid-lower of Yangtze Valley, and vice versa. During the
period of 1958-1964, 1965-1979, 1980-1993, and 1994-2001, the mean time
(a)
(b)
Fig. 4. (a) The second eigenvector. (b) The 1958-2001 curve for the time coecient of
the second eigenvector.
