Decadal variation of heavy rainfall frequency in Kyushu ... · Decadal variation of heavy rainfall...
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Decadal variation of heavy rainfall frequency in Kyushu, Japan and associated synoptic weather patterns 6 th European Conference on Severe Storms (ECSS 2011) 3 - 7 October 2011, Palma de Mallorca, Balearic Islands, Spain Koji Nishiyama and Kenji Wakimizu Kyushu university, Japan
Transcript of Decadal variation of heavy rainfall frequency in Kyushu ... · Decadal variation of heavy rainfall...
Decadal variation of heavy rainfall
frequency in Kyushu, Japan and
associated synoptic weather patterns
6th European Conference on Severe Storms (ECSS 2011)
3 - 7 October 2011, Palma de Mallorca, Balearic Islands, Spain
Koji Nishiyama and Kenji Wakimizu
Kyushu university, Japan
Background
Period A
568 631 821
YEAR
0
40
80
120
160
1979 1989 1999
Fre
qu
ency
2008
Period B Period C
129 130 131 132
LONGITUDE
31
32
33
34
35
LA
TIT
UD
E
Many types of synoptic fields make up
decadal trend of heavy rainfall frequency
Kyushu, Japan All areas in Japan
Recent high frequency
Frequency of R
>= 50mm/h
Year
F
requen
cy
What types of patterns contribute strongly to the formation of
decadal variation of heavy rainfall frequency ??
Complicated !!
Research objective
Pattern recognition using the
Self-Organizing Map(SOM)
Heavy rainfall freq for pattern 1
Heavy rainfall freq for pattern 2
Heavy rainfall freq for pattern N
YEAR
0
40
80
120
160
1979 1989 1999
Fre
quen
cy
2008
What kinds of patterns
cause increasing trend of
heavy rainfall ??
Main topic
Methodology
U16
P
Q
R
Sample 76
Sample 51
Sample 17
Sample 34
Sample 1
Sample 5
Unit9
Unit32
Unit16
U9
U32 Different features
(distant)
Similar features
(close)
High dimensional data assembly
Visually-recognizable patterns in the two dimensional array
Called as
‘unit’, representing ‘pattern’ (1) Reference vector showing a pattern
(2) Samples classified by SOM training
Each unit (pattern)
Self-Organizing Map (SOM) : Kohonen (1995)
are non-linearly classified into
),.....,1())()(),(()( 21 Tttxtxtxt n x
i c (BMU)
i=1 i=6
i=36 i=31
)(tim
)()( tmtx i
P
Q
R
(a) Input of sample vector for
SOM training
(b) Determination of BMU（ Best Matching Unit ）
(c) Modification of reference
vector mi(t) depending on
Neighboring function hci
BMU
smallModifylarge
ttthtt ci iicii mxrrmm ,1
The increase of iteration step smaller modification
ic rr ,thci
Min (i=c(BMU))
SOM training algorithm
x=(PW1~PW16 , U1~U16 , V1~V16)
Input vector for the SOM training
129 130 131 132
LONGITUDE
31
32
33
34
35
LA
TIT
UD
E
NCEP/NCAR
Reanalysis
Synoptic field for the SOM Rainfall observation
(AMeDAS)
Synoptic field and rainfall obs area
Linking
1979～2008 (30 years)
（June～September）
14648 samples
(4 times per day)
120E 130E 140E 150E20N
30N
40N
50N
1 2 3 4
5 6 7 8
9 10 11 12
13 14 15 16
Pacific Ocean
Japan
Korea•Peninsula
(1)PW
(2)U850
(3)V850
40mm
50mm
Target area
: Kyushu
NCEP reanalysis grid i
Feature Index
Moisture
inflow into
Japan
PW
(Precipitable
Water)
Low level Jet u, v (850hPa)
3 JST 9 JST 15 JST 21JST
24 JST181260
NCEP/NCAR reanalysis
AMeDAS AMeDAS AMeDAS AMeDAS
Event 1 Event 2 Event 3 Event 4
AMeDAS：Automated Meteorological Data Acquisition System
Field 2 Field 3 Field 4Field 1
Map structure
Unit 1 Unit 30
Unit 871 Unit 900
2000 8/31 06UTC
2000 8/31 12UTC
2002 8 /7 12UTC
:
Heavy rainfall frequency
27N
30N
33N
36N
124E 127E 130E 133E
U871
13 12 15 14
16
10
19 18
11
9
20
6 7 8
17
25 24 23 21
1 3 2 4 5
22
Groups :1~25
All samples for 30
years (14648 fields)
Units : 1~900 dots
900 patterns (25 groups)
Specification of the SOM structure
Heavy rainfall
frequency per each unit
and each group 0
300
600
900
1200
1500
1800
1 2
0
50
100
150
200
250
300
3 4 5
1: 30mm/h =< R < 40mm/h
2: 40mm/h =< R < 50mm/h
3: 50mm/h =< R < 60mm/h
4: 60mm/h =< R < 70mm/h
5: R >= 70mm/h
G01 G03 G05G04G02
G06 G08 G10G09G07
G11 G13 G15G14G12
G16 G18 G20G19G17
G21 G23 G25G24G22
0
300
600
900
1200
1500
1800
1 2
0
50
100
150
200
250
300
3 4 5
0
300
600
900
1200
1500
1800
1 2
0
50
100
150
200
250
300
3 4 5
0
300
600
900
1200
1500
1800
1 2
0
50
100
150
200
250
300
3 4 5
0
300
600
900
1200
1500
1800
1 2
0
50
100
150
200
250
300
3 4 5
0
300
600
900
1200
1500
1800
1 2
0
50
100
150
200
250
300
3 4 5
0
300
600
900
1200
1500
1800
1 2
0
50
100
150
200
250
300
3 4 5
0
300
600
900
1200
1500
1800
1 2
0
50
100
150
200
250
300
3 4 5
0
300
600
900
1200
1500
1800
1 2
0
50
100
150
200
250
300
3 4 5
0
300
600
900
1200
1500
1800
1 2
0
50
100
150
200
250
300
3 4 5
0
300
600
900
1200
1500
1800
1 2
0
50
100
150
200
250
300
3 4 5
0
300
600
900
1200
1500
1800
1 2
0
50
100
150
200
250
300
3 4 5
0
300
600
900
1200
1500
1800
1 2
0
50
100
150
200
250
300
3 4 5
0
300
600
900
1200
1500
1800
1 2
0
50
100
150
200
250
300
3 4 5
0
300
600
900
1200
1500
1800
1 2
0
50
100
150
200
250
300
3 4 5
0
300
600
900
1200
1500
1800
1 2
0
50
100
150
200
250
300
3 4 5
0
300
600
900
1200
1500
1800
1 2
0
50
100
150
200
250
300
3 4 5
0
300
600
900
1200
1500
1800
1 2
0
50
100
150
200
250
300
3 4 5
0
300
600
900
1200
1500
1800
1 2
0
50
100
150
200
250
300
3 4 5
0
300
600
900
1200
1500
1800
1 2
0
50
100
150
200
250
300
3 4 5
0
300
600
900
1200
1500
1800
1 2
0
50
100
150
200
250
300
3 4 5
0
300
600
900
1200
1500
1800
1 2
0
50
100
150
200
250
300
3 4 5
0
300
600
900
1200
1500
1800
1 2
0
50
100
150
200
250
300
3 4 5
0
300
600
900
1200
1500
1800
1 2
0
50
100
150
200
250
300
3 4 5
0
300
600
900
1200
1500
1800
1 2
0
50
100
150
200
250
300
3 4 5
0
300
600
900
1200
1500
1800
1 2
0
50
100
150
200
250
300
3 4 5
R ≥ 30mm/h
f =1
(a)
G1
G16
G21 G22 G23 G24
G17 G19
G18
G3
30 ≤ f < 50
50 ≤ f < 100
100 ≤ f < 200
200 ≤ f
10 ≤ f < 30
5 ≤ f < 10
2 ≤ f < 5
G1
G16
G21 G22 G23 G24
G17 G19
G18
G3
R ≥ 50mm/h(b)
f =1
15 ≤ f < 20
20 ≤ f < 25
25 ≤ f < 30
30 ≤ f
10 ≤ f < 15
5 ≤ f < 10
2 ≤ f < 5
Synoptic field patterns
constructed by the
SOM (25 groups)
plots : Average reference vector in each group
27N
30N
33N
36N
124E 127E 130E 133E
PW ( Precipitable Water)：
・An index of convective activity
・large value ample water vapor
27N
30N
33N
36N
124E 127E 130E 133E
27N
30N
33N
36N
124E 127E 130E 133E
27N
30N
33N
36N
124E 127E 130E 133E
27N
30N
33N
36N
124E 127E 130E 133E
27N
30N
33N
36N
124E 127E 130E 133E
G01 G03 G05G04G02
27N
30N
33N
36N
124E 127E 130E 133E
27N
30N
33N
36N
124E 127E 130E 133E
27N
30N
33N
36N
124E 127E 130E 133E
27N
30N
33N
36N
124E 127E 130E 133E
27N
30N
33N
36N
124E 127E 130E 133E
G06 G08 G10G09G07
27N
30N
33N
36N
124E 127E 130E 133E
27N
30N
33N
36N
124E 127E 130E 133E
27N
30N
33N
36N
124E 127E 130E 133E
27N
30N
33N
36N
124E 127E 130E 133E
27N
30N
33N
36N
124E 127E 130E 133E
G11 G13 G15G14G12
27N
30N
33N
36N
124E 127E 130E 133E
G16 G18 G20G19G17
27N
30N
33N
36N
124E 127E 130E 133E
27N
30N
33N
36N
124E 127E 130E 133E
27N
30N
33N
36N
124E 127E 130E 133E
27N
30N
33N
36N
124E 127E 130E 133E
27N
30N
33N
36N
124E 127E 130E 133E
27N
30N
33N
36N
124E 127E 130E 133E
27N
30N
33N
36N
124E 127E 130E 133E
27N
30N
33N
36N
124E 127E 130E 133E
27N
30N
33N
36N
124E 127E 130E 133E
G21 G23 G25G24G22
PW 60mm 50mm 40mmWIND
850hPa20m/s 10m/s
WIND850 (u, v)：
・Low Level Jet (LLJ)
・Monsoon
G24 G19 G22 G21 G3 G1
Decadal variation in synoptic pattern frequency of 6 HR groups
0
200
400
600
800
1000
1200
1400
0
50
100
150
200
250
1979 1989 1999 2008
Fre
quency
Fre
qu
en
cy
1979
～1988
1989
～1998
1999
～2008
A CB A CB
G24 G19 G22 G21 G3 G1
Decadal variation in heavy rainfall frequency of 6 HR groups
0
20
40
60
80
100
120
140
160
1979 1989 1999 2008
0
200
400
600
800
1000
Fre
qu
en
cy
Fre
qu
en
cy
1000
800
600
400
200
01979
～1988
1989
～1998
1999
～2008
2006
A CB A CB
Synoptic patterns in G22
Heavy rainfall frequency
in G22 (R >= 50 mm/h)
0
10
20
30
40
50
60
70
1979 1989 1999
Fre
qu
ency
2008
71 64 155
1312 1514
16
10
1918
11
9
20
6 7 8
17
25242321
1 32 4 5
22
2006
Decadal variation in synoptic patterns and HR frequency in G22
0
10
20
30
40
50
60
70
1979 1989 1999
Fre
qu
ency
2008
258 240 217
Period A Period B Period C
27N
30N
33N
36N
124E 127E 130E 133E
U879
G22 U879
Synoptic patterns in G22
(dominant patterns)
Heavy rainfall frequency
in G22 (R >= 50 mm/h)
2006
Decadal variation in synoptic patterns and HR frequency in G22
0
5
10
15
20
25
30
1979 1989 1999
Fre
qu
ency
2008
56 72 56
Period A Period B Period C
21 23 98
0
10
20
30
40
50
60
70
1979 1989 1999
Fre
quen
cy
2008
Heavy rainfall frequency
in each unit
2100JST, July 5, 2006
PATTERN: U879 freq=17 times
G19 U559
Synoptic patterns in G19
(dominant patterns)
Heavy rainfall frequency
in G19 (R >= 50 mm/h)
Decadal variation in synoptic patterns and HR frequency in G19
Heavy rainfall frequency
in each unit
1500JST, Aug 2, 2007
PATTERN: U559 freq=17 times
3 8 1 11 212 1 1 2 3
24 367 4 1
1 2 4 1 1 12 7 5 1
2 17 5 12 2 3 1 9 3 2 1
2 1 2 2 6 2 10 1 1 5 1 1
6 2 1 7 4 5
3 1 5 1 1 2
8 1 7 3 1 2 1
2 2 1
1 2 2 1 4 3 3 1
1 1 2 1 1 2 4 5 1 1
2 1 1 1 2 1 6 1
1 2 2 1 3 1 1 1 1
1 1 1 3 1
1 1 2 1 1 1 1
2 1 1 1 2
1 1 1 2
1 1 2 4 3 3
1 2 2 4 2 2 7 1 1 6
1 1 3 126 17 3 2 4 2
25 333 6 1
20 2 1 4 4 10 1 1 3 1 3 3 18 13 2
7 9 7 4 2 2 2 7 2 1 2 3 1 10 1 3 3 5 2 1
5 2 1 2 1 2 2 2 7 8 1 7
6 2 1 1 1 1 1 1 1 1 3 3 7 4 1 1
2 2 7 3 2 7 1 1 1 2 9 5 5 4 4 6 2 3 1 4
5 1 334
3 9 2 4 16 6 1 1 1 2 3 1 12 4 4 2
3 829 44
20 16 7 8 2 2 5 3 5 5 6 222 1 1 1
2 3 8 20 14 14 13 5 8 2 1 2 2 3 16 6 3 13 10 21 3 2 5 2
4 3 15 9 19 21 11 9 13 2 2 1 1 1 1 4 3 11 12 1 5 1 1 2 1 2
3 6 1 11 14 8 5 9 19 14 9 3 2 2 1 8 322 6 7 5 1 3
15 4 4 19 13 22 829 23 12 27 12 9 4 1
2061
7 22 11 14 1
27N
30N
33N
36N
124E 127E 130E 133E
U559
0
5
10
15
20
25
30
1979 1989 1999
Fre
quen
cy
2008
3 22 46
8 15 19
0
2
4
6
8
10
1979 1989 1999
Fre
qu
ency
2008
Period A Period B Period C
Conclusion
Heavy rainfall frequency during recent 10 years (Period A: 1999-
2008) is higher than during past periods (B, C) in Kyushu Japan
Group characterized by humid region with eastward low-
level jet and a large gradient of PW (the existence of front)
Groups (G19, 22) show higher heavy rainfall frequency
G22
G19 Including the patterns related to Typhoon centers passing
through Kyushu
G21 shows lower heavy rainfall frequency
27N
30N
33N
36N
124E 127E 130E 133E
Group characterized by humid region with northeastward
low-level jet
27N
30N
33N
36N
124E 127E 130E 133E
27N
30N
33N
36N
124E 127E 130E 133E
G21
