Environmental Engineering Reference
In-Depth Information
sensor is about 40-50 km. For ship observations, the field of view varies with the
weather condition and can be as large as tens of kilometers for a clear day down to a
few kilometers under misty or hazy conditions to less than a few 100 m in severe
weather conditions. The probability of observing rain increases as the FOV
increases. For GATE rainfall, the rain frequency increases from around 10% at a
resolution of 4 km to 40% at a resolution of 40 km (Kedem and Chiu 1987b ).
15.4 Applications
15.4.1 GPCP Merging
This product serves as input to GPCP rain maps (Huffman et al. 1997 ). This data set
and derived products (Adler et al. 2003 ; Huffman et al. 2001 ; Xie et al. 2003 ) have
been utilized rather extensively in climate and weather analyses.
15.4.2 Climate “Trend” and Variations
Trends in the data set have been examined. A trend is dependent on the length of the
time record. The version 6 data showed a smaller trend than the version 4 data.
Overall, the trends are consistent with the GPCP estimates and are generally lower
than the other estimates (Chiu and Chokngamwong 2010 ). No significant trend in
global oceanic rainfall is observed. The only significant trend in zonal mean is
observed at the tropical Pacific between 0 and 10ºN. Figure 15.9 shows the linear
trend pattern of global rainfall. The monthly rainfall data have been deseasonalized,
i.e., monthly climatology removed.
An empirical orthogonal function (EOF) analysis was performed on the nonsea-
sonal time series. Only the first two EOFs are judged to be significant and distinct
according to the criteria of North et al. ( 1982 ) (see also Chiu et al. 2008 ).
Figure 15.10 shows the first two EOF patterns (with variance explained) and the
associated time series (principal component, or PCs). A Southern Oscillation Index
(SOI), scaled to match the time series, is also included in the figure. The first PC
shows a correlation coefficient of 0.8, significant at the 95% level, while the
contemporaneous correlation with the second PC (at
0.11) is insignificant. The
major mode of nonseasonal rainfall variations is associated with the El Nino
Southern Oscillation (ENSO) phenomena. This rather
robust
result
is well
established (Chang et al. 1993 ; Kafatos et al. 2001 ).
The second mode (EOF2) is similar to the first mode (EOF1). This pattern is
characterized by an equatorial dipole. The overall wedge pattern is hinged in the
central Pacific instead of the maritime continents as demonstrated in EOF1. There
are recognitions of an ENSO pattern that has its origin in the central Pacific. This is
termed the ENSO Modoki (Weng et al. 2007 ). Others have coined the canonical
Search WWH ::




Custom Search