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Remote Sensing Application to Detect and
Idetify the Cimate Change over Indonesia
Eddy Hermawan and Lely Qodrita Avia
Contact : [email protected]
Atmospheric Modeling Divisionof Atmospheric Science and Technology
Center of LAPAN, Jln. Dr. Djundjunan No. 133, Bandung 40173
Absract
This study is mainly concerned to detect and
id
identify
if the
h climate
li
change
h
over Indonesia,
d
i
especially on the hydrometeorological
phenomena
using
space
technology
applications. Firstly, we reviewed the basic
concept of global climate change based on the
trend of surface temperature and precipitation
over several regions over Indonesia. Since the
Indonesia Maritime Continent (IMC) is mostly
effected by the dynamical of Monsoon system,
we mainly focussed on the flood and
drought hazard.
Cont ...
Then, we applied the space technology
applications
li i
to detect
d
and
d identify
id
if the
h trend
d or
tendency of
surface temperature and
precipitation mainly in the Java Island.
precipitation,
Island Since,
Since
both phenomena is related well to agriculture
sector, we need to consider to save the elevent
provinces that has already stated as the rice
production center from the extreme weather
or climate
li t condition.
diti
H
Here,
we promote
t the
th
SADEWA (Satellite Disaster Early Warning
System) and the equatorial atmospheric model
that still developing by LAPAN Bandung.
“Regarding to the statement from the
IPCC experts who stated that as a result of
climate change, more frequent and more
yd o eteo o og ca events
intense hydrometeorological
can be expected, we mainly concerned to
investigate the surface temperature and
precipitation (rainfall) behavior over Java
Island, including their trend or tendency
taken from satellite and in-situ
observation respectively”
observation,
ti l ”
From this figure,
figure we can see,
see at least we have
seven climate hazards over Indonesia. They
are :
1. Earthquake
2 Vulcano
2.
3. Tsunami
4 Tropical Storm
4.
5. Storm Surge
. Flood --- > much water
7 Drought --- > less water
7.
6
We know that both phenomena (flood
and drought) is related well with the
anomaly of Monsoon system, but we
need to consider the other phenomena
that also have severe impact that we call
as the MJO (Madden Julian Oscillation) as
one of the most mode oscillation along
the equatorial region. We can see Jakarta
flood’s in 1996, 2002, 2006, 2007, and
2013 recently as the samples the severe
impacts of MJO event in the Western part
of Indonesia region.
Review
“Floods
Fl d and
dD
Drought”
ht”
Jakarta Floods
g
In Early February 2007
Flooding in Sprawling Mega Cities in Southeast Asia
Philippines
Malaysia
y
Jakarta (Feb 2007)
Bangkok 2011
Singapore 2010
10
Jakarta Floods February 2007
0
Sta. Tanjung Priok
Sta. Halim Perdanakusuma
Sta. Kemayoran
Tanggal
Sta. Cengkareng
Augg-08
Feb
b-08
Augg-07
Feb
b-07
Augg-06
Feb
b-06
Augg-05
Feb
b-05
800
Augg-04
Feb
b-04
Augg-03
Jan, Feb 1996
Feb
b-03
Augg-02
Feb
b-02
Augg-01
Feb
b-01
Augg-00
Feb
b-00
Augg-99
Feb
b-99
Augg-98
Feb
b-98
1000
Augg-97
Feb
b-97
Augg-96
Feb
b-96
Augg-95
Feb
b-95
Curaah Hujan (m
mm/bulan)
Grafik Curah Hujan Bulanan Wilayah Jakarta
Periode Januari 1995 - Desember 2008
1200
Jan, Feb 2002
Jan, Feb 2007
600
400
200
Please note here almost
every 5-6 gyears, Jakarta is
attacked by the big
flooding and the intense
flooding,
is still increased
MJO animation
Please look at the moving of center
convection over Indonesia both in
850 & 200 mb
Drought
in 1997/98
/
‘82
‘97
(http://www.cpc.ncep.noaa.gov/products/Global_Monsoons/Asian_Monsoons/wind_polrc_anim_asia.gif)
“(MK
(
= Musim Kering)
g)
“(MB = Musim Basah)
(BMKG , 2009)
DEC
JAN
FEB
JUN
JUL
AUG
9/13/2013
Contoh dari kondisi yang tidak neutral,
yakni ekstrim anomali SST yang
menyebabkan El
El-Nino
Nino kuat di tahun
1982 dan 1997
(http://www.bom.gov.au/climate/enso/nov97_ssta-small.png) di download 05.06.2010
Nino 3.4
DMI
~Oct
Oct ‘97
97
+
“long dry”
_
~Oct ‘98
“long wet”
~ Oct ‘97
97
DMI (+)
~ Oct ‘98
DMI (-)
Cross
correlation
b t
between
DMI
vs Nino 3.4
Long dry season along
1997/98
September, October, and
November 1997
Long wet season along
1998/99
September, October, and
November 1998
Cli t Projection
Climate
P j ti
g
Temperature & Precipitation
9/13/2013
The possibility of precipitation change over Java & Bali Island
Early wet
season trends
will be delayed
Future
Naylor et.al.,
2007
Naylor et
et.a
a 2007)
Now
Length
g of wet
season trends
shorter
28
Detecting
Climate Change
g
Temperature
T
28
BANDUNG / WEST
JAVA (1971-2002)
y = 0,0019x + 22,145
23
18
y = 0,0013x
0 0013 + 26
26,925
925
30
28
26
24
22
1
3
30
59
5
88
8
11
17
14
46
17
75
20
04
23
33
26
62
29
91
32
20
34
49
37
78
40
07
43
36
tem
mperature (deg
g C)
1
2
27
53
5
79
7
10
05
13
31
15
57
18
83
20
09
23
35
26
61
28
87
31
13
33
39
36
65
39
91
41
17
tem
mperature (deg C)
30
28
26
24
22
1
24
47
70
93
116
139
162
185
208
231
254
277
300
323
346
369
392
temperatur
re (deg C)
1
28
55
82
109
136
163
190
217
244
271
298
325
352
379
406
433
e (deg C)
temperature
JAKARTA OBS. (19712007)
TEGAL / CENTRAL
JAVA (1971-2008)
30
28
26
24
22
y = 0,0015x + 26,389
SANGKAPURA / EAST
JAVA (1971-2004)
y = 0,0036x + 26,643
RECENT GLOBAL MONTHLY MEAN CO2
BMG
386
Mauna Loa
384
Indonesia GAW Obs.
Linear (Mauna Loa )
380
378
376
374
372
370
368
366
364
362
BMG
2007
2
2006
2
2005
2
2004
2
360
2003
2
CO2 C
CONCENTRAT
TION (ppm)
382
YEAR
Source : NOAA – BMG, September 2007
Detecting
Climate Change
g
Rainfall/Precipitation
PRECIPITATION CHANGE PER
PRECIPITATION CHANGE PER‐‐ CLIMATE PERIOD (30 YEARS) IN DENPASAR BALI
(30 YEARS) IN DENPASAR, BALI
Avia, 2007b
1901
1904
1907
1910
1913
1916
1919
1922
1925
1928
1931
1934
1937
1940
1943
1946
1949
1952
1955
1958
1961
1964
1967
1970
1973
1976
1979
1982
1985
1988
1991
1994
1997
2000
2003
2006
2009
2012
Preccipitation (mm
m)
VARIABILITY AND TREND OF PRECIPITATION
1901‐2012 IN CILACAP, CENTRAL JAVA
IN CILACAP CENTRAL JAVA
6000
5000
y = ‐8,244x + 3854,9
R² = 0,0712
4000
3000
2000
1000
0
year
Definitions of climate change
(IPCC, AR-4, 2007)
Climate change in IPCC usage refers
to a change in the state of the
climate that can be identified (e.g.
using statistical tests) by changes in
the mean and/or the variability of its
properties and that persists for an
properties,
extended period, typically decades
or longer.
l
Lokasi
Jakarta
Surabaya
y
Yogyakarta
Cilacap
41
Tren the amount of wet and dry season per decade (every 10
years) for period of 1953-2002 (~53 years) at Surabaya
9
8
7
6
5
4
3
2
1
0
y = ‐0,2x + 5,4
R² = 0,1429
MH
Linear (MH)
Periode (Tahun)
Panjang Musim
a ja g us Kemarau
e a au
Jumlah
h (bulan)
Jumlah
h (bulan)
Panjang Musim
a ja g us Hujan
uja
9
8
7
6
5
4
3
2
1
0
y = 0,2x + 6,6
R² = 0,1429
R
= 0 1429
MK
Linear (MK)
Periode (Tahun)
42
Tren the amount of wet and dry season per decade (every 10
years) for period of 1901-2012 (~112 years) at Cilacap
Panjang Musim Hujan
a ja g us
uja
Panjang Musim Kemarau
a ja g us
e a au
4
14
y = ‐0,1909x + 11,6
8
6
MH
4
Linear (MH)
2
3
2
2
MK
1
Linear (MK)
1
Dekade
Dekade
2001‐‐2010
1981‐‐1990
1961‐‐1970
1941‐‐1950
1921‐‐1930
0
1901‐‐1910
0
y = 0,1909x + 0,4
3
Jumlaah (bulan)
10
1901‐‐1910
1921‐‐1930
1941‐‐1950
1961‐‐1970
1981‐‐1990
2001‐‐2010
Jumlaah (bulan)
12
Tren the amount of wet and dry season per decade (every 10
years) for period of 1970-2012 (~43 years) at Yogyakarta
9
8
7
6
5
4
3
2
1
0
y = ‐0 6x + 7
y = ‐0,6x + 7
MH
Linear (MH)
Dekade
Panjang Musim Kemarau
a ja g us
e a au
Jumlah
h (bulan)
Jumlah
h (bulan)
Panjang Musim Hujan
a ja g us
uja
9
8
7
6
5
4
3
2
1
0
y = 0 6x + 5
y = 0,6x + 5
MK
Linear (MK)
Dekade
The tren/tendecy of precipitation change over Java & Bali Island
Early wet
season trends
will be delayed
Future
Naylor et.al.,
2007
Naylor et
et.a
a 2007)
Now
Length
g of wet
season trends
shorter
45
What should we do?
We need to save the 11 provinces of
g
our rice production
center from the
extreme climate condition, such as
already happened in 1982/83 and
1997/98 using TRMM data.
How ?
Rainfall at
Surabaya
Period of 1953-2002
(50 Years Observation)
Composite Technique Analysis for Rainfall at
Surabaya for Period of 1953-2002
Januari
Februari
Maret
April
Mei
2001
1999
1997
1995
1993
1991
1989
1987
1985
1983
1981
1979
1977
1975
1973
1971
1969
1967
1965
1963
1961
1959
1957
1955
1953
-150-50 50 150250
Juni
51
-150-50 50 150250
-150
50
250 -150-50 50 150 250 -150-50 50 150 250
-150-50 50 150250
Cont ...
Juli
Agustus
September
Oktober
November
Desember
52
-150-50 50 150250
-150-50 50 150250
-150-50 50 150250
-150-50 50 150250
-150-50 50 150250
-150-50 50150250
The Application of
TRMM Data Analysis to
Investigate the Heavy
Rainfall Potentially over
Indonesia
The Heavy Rainfall Distribution over Indonesia
B
Based
d on th
the TRMM D
Data
t A
Analysis
l i ffor P
Period
i d off
1998-2011 averaged in April
The Heavy Rainfall Distribution over Indonesia
B
Based
d on th
the TRMM D
Data
t A
Analysis
l i ffor P
Period
i d off
1998-2011 averaged in October
Finally
y ...
We need
W
d to
t d
develop
l
an
equatorial atmospheric
model with good time and
spatial high resolution
g
Jakarta
Future Climate Response – Precipitation (%), 2071-2100
Jakarta
Precipitation
2071-2100
WRF/ECHAM A2 Climate Response for Precipitation
(Relative Anomaly in %) relative to 1961-1990, JAKARTA
Climate Signal/Climate Change factor:
= (2071-2100) – (1961-1990)
57
SADEWA
(Satellite Disaster Early Warning System
atau
Sistem Informasi Peringatan Dini Bencana)
http://60.253.114.151/sadewa30
Contact:
[email protected]