The Local Variation of the Indonesian Seas Index Characteristic, Eighteen Years Analysis of Multi Sensor Satellite Remote Sensing Data.
-Second Circular (plan)-
Tomography Lombok Strait Meeting 2015:
A vast challenge to monitor Indonesian Throughflow (ITF)
Date: November 3-7, 2015
Co-conveners: Fadli Syamsudin, Xiaohua Zhu, Chen-Fen Huang and
Arata Kaneko
Sponsored by BPPT, UNRAM, HU and ONR_Global
Purposes-Measurement of Indonesian Throughflow (ITF) is still a key issue of world climate change
research because systematic, long-term measurement of ITF transport is lacked even for major pathways
such as Makassar Strait, Lombok Strait and Ombai Strait. Applicability of Coastal Acoustic Tomography
(CAT), an innovative oceanographic technology, to strait throughflow measurement will be intensively
discussed in this meeting. A new development of CAT (mirror-CAT) by using the mirror reflection of
underwater sound is proposed to monitor the ITF transport in real time and provides a critical material of
discussion. International collaboration with other researchers who advance ongoing or planning projects
on Indonesian sea studies and ITF is also another important issue to be pursued in the meeting.
Providedby Yuji Sakuno (HU)
Agenda:
Date
November 3, 2015
Sessions
Title & Speaker
Opening address
Host: University of Mataram (President)
8:30-9:00
BPPT (Deputy Chairman)
SEACORM KKP (Director)
9:00 – 9.15
Introductory address
Photo session
Target of the meeting (Arata Kaneko, HU)
9:15-9:45
Plenary session (1)
10:00-12:00
Past, present and future of Indonesian Sea studies
(Fadli Syamsudin, BPPT)
Measuring tidal currents and volume transport
through a wide strait by use of the coastal
acoustic tomography system (Xiaohua Zhu,
Plenary session (2)
SIO/SOA)
Innovative application of CAT to Kuroshio
14:00-17:00
measurement (Chen-Fen Huang, NTU)
The observation plan of SITE and TIMIT projects in
the Indonesian Seas (Shujiang Li, FIO/SOA)
The Local Variation of the Indonesian Seas Index
Characteristic: "Eighteen Years Analysis of Multi
Sensor Satellite Remote Sensing Data”
(I Dewa Nyoman Nurweda Putra, Udayana. Univ)
Date
Sessions
Ongoing projects and
November 4, 2015
plan
9:00-12:00
Title & Speaker
JAMSTEC project plan to the Indonesian
Seas (Iwao Ueki, JAMSTEC)
The SIO/SOAITF project (Zhou Lei, SIO/SOA)
One invited speech is reserved here.
Lombok Strait POM model(Hidemi Mutsuda, HU)
Satellite imagery of Lombok Strait and the
Model and Satellite
14:00-17:00
adjacent seas (Yuji Sakuno, HU)
Hiroshima Bay CAT experiment (Chuanzheng
Zhang, HU)
Hiroshima Bay data assimilation (Minmo Chen, HU)
Two regular speeches are reserved here.
Date
Sessions
Reception Dinner
Title & Speaker
All participants are invited.
18:30-20:30
Date
Sessions
Title & Speaker
Bali Strait CAT experiment (Yudi Adityawarman,
BPPT)
November 5, 2015
Dalian Bay CAT experiment (Fan Xiaopeng,
9:00-12:00
SIO/SOA)
CAT
A recent activity to CAT (NaokazuTaniguchi, NTU)
A new system design of CAT (Hong Zheng, ZOU)
Two regular speeches are reserved here.
14:00-15:30
Detailed explanation of projectdesign and
MCAT-ITF project (1)
16:00-17:00
Data distribution and analysis policy (Arata Kaneko,
MCAT-ITF project (2)
HU)
Date
November 6, 2015
deployment (Arata Kaneko, HU)
Sessions
Field survey (1)
Title & Speaker
Tomography site is surveyed.
Discussion is deepened by mutual communication at
10:00-15:00
this event.
Date
November 7, 2015
Sessions
Field survey (2)
10:00-15:00
Title & Speaker
Application of CAT to aquaculture fields is surveyed.
Discussion is deepened by mutual communication at
this event.
Resort hotel reserved for all participants:
Holiday Resort Lombok (about $46/night in special government discount)
Senggigi Beach Lombok 83355 NTB, Indonesia
Phone: +62-370-693444
Fax: +62-370-693092
http://holidayresort-lombok.com/meeting-banquet.html
Acronyms:
BPPT (Agency for the Assessment and Application of Technology, Indonesia)
UNRAM (University of Mataram, Indonesia)
HU (Hiroshima University, Japan)
UT (University of Tokyo, Japan)
JAMSTEC (Japan Agency for Marine-Earth Science and Technology, Japan)
SIO/SOA (Second Institute of Oceanography
/State Oceanic Administration, China)
FIO/SOA (First Institute of Oceanography
/State Oceanic Administration, China)
ZOU (Zhejiang Ocean University, China)
NTU (National Taiwan University)
CU (Columbia University)
SIO (Scripps Institution of Oceanography)
ONR (Office of Naval Research)
The Local Variation of the Indonesian
Seas Index Characteristic: "Eighteen
Years Analysis of Multi Sensor Satellite
Remote Sensing Data”
I Dewa Nyoman Nurweda Putra
UDAYANA UNIVERSITY
2015
Introduction
Major Characteristics:
SE Asia
Pacific Ocean
ITF
ENSO
IOD
Shallow
Indian Ocean
A semi-closed
marginal sea
Pacific and
Indian
Ocean
Asia and
Australia
continent
Unique
bathymetry
Western
5000 m
Unique
pathway
Indonesian
throughflow
(ITF)
Interannual
Variability
ENSO
Deep
Australia
IOD
(Meter)
Need a relevant information and better understanding on the
features of the characteristics of indices in the Indonesian Sea.
Seasonal Variability
D
C
E
M
N
H
I
J
K
L
F
G
B
A
(Nurweda et al., 2013)
U-WS
SST
The Inner Indonesian Seas
RR
: Strong
: Weak
: Nearly Zero
6-Months Variability
D
C
E
M
N
H
I
J
K
L
F
G
B
A
U-WS
SST
The Inner Indonesian Seas
(Nurweda et al., 2013)
RR
: Very Weak
: Weak
: Zero
Objectives
1. To investigate the cyclical temporal variability
issues on SST index in the several areas of
Indonesian Seas.
2. To improve the detection of the ENSO signal for
the area that show a cyclic temporal variability.
Data Sources
Index
Time Coverage
Unit
Spatial Res.
SST
Dec 97 – Jul 13 And Jan 14 – Aug 15
˚C
0.25˚ ×0.25˚
Temporal Res.
Monthly
Channel(s)
10.65 GHz
Product
Data Center
L3 F10.7 TMI And AMSR 2
REMSS
Index
Time Coverage
Product
Data Center
ONI
1950 – 2014
ENSO Index
NOAA
Data Analysis:
1. Detection of Cyclic Temporal Variability
- Seasonal Variability
- 6-months Variability
2. Detection of the ENSO Signal
Seasonal Variability
Original Data
(Java Sea)
Mode 1
SSA
Mode 2
6-Months Variability
Original Data
(Java Sea)
Mode 3
SSA
Mode 4
Data Analysis:
1. Detection of Cyclic Temporal Variability
- Seasonal Variability
- 6-months Variability
2. Detection of the ENSO Signal
ENSO Phenomenon
Source : NOAA
The El Nino Southern Oscillation (ENSO) Mechanism
ENSO Phenomenon
Index
ONI
Area Boundary
5˚S-5˚N and 190˚E240˚W
Definition
El Nino: The 3 months moving averages of SST is at
least 0.5 warmer than 30-year (1981-2010) average.
La Nina: The 3 months moving averages of SST is at
least 0.5 cooler than 30-year (1981-2010) average.
ENSO Signal Detection
(Proposed Method)
Removing
Seasonal
Variability
Long term
monthly
average data
Area that shows
cyclic temporal
variability
Removing 6
months
variability
Extracted
from 6 month
MA
ENSO Signal
3 months
Moving
Averages
ENSO Signal (Area J)
El Nino
NOAA
Method
Proposed
Method
La Nina
Nino 3.4
Area
ENSO Signal (Java Sea)
3-Months MA
New Proposed Method
El Nino
La Nina
(Nurweda et al., 2013)
Conclusions
The strong cyclical temporal variability exists in the
SST index of Indonesian Seas.
The result of NOAA method could not remove the
strong cyclical temporal variability.
The proposed method significantly improves the
ENSO signal detection for the area that show a cyclic
temporal variability.
Contact Information
Dr. I Dewa Nyoman Nurweda Putra
Ocean Remote Sensing
Faculty of Marine Science and Fisheries
Centre for Remote Sensing and Ocean Sciences
Udayana University
Email: nurweda14@unud.ac.id
nurweda14@gmail.com
Tomography Lombok Strait Meeting 2015:
A vast challenge to monitor Indonesian Throughflow (ITF)
Date: November 3-7, 2015
Co-conveners: Fadli Syamsudin, Xiaohua Zhu, Chen-Fen Huang and
Arata Kaneko
Sponsored by BPPT, UNRAM, HU and ONR_Global
Purposes-Measurement of Indonesian Throughflow (ITF) is still a key issue of world climate change
research because systematic, long-term measurement of ITF transport is lacked even for major pathways
such as Makassar Strait, Lombok Strait and Ombai Strait. Applicability of Coastal Acoustic Tomography
(CAT), an innovative oceanographic technology, to strait throughflow measurement will be intensively
discussed in this meeting. A new development of CAT (mirror-CAT) by using the mirror reflection of
underwater sound is proposed to monitor the ITF transport in real time and provides a critical material of
discussion. International collaboration with other researchers who advance ongoing or planning projects
on Indonesian sea studies and ITF is also another important issue to be pursued in the meeting.
Providedby Yuji Sakuno (HU)
Agenda:
Date
November 3, 2015
Sessions
Title & Speaker
Opening address
Host: University of Mataram (President)
8:30-9:00
BPPT (Deputy Chairman)
SEACORM KKP (Director)
9:00 – 9.15
Introductory address
Photo session
Target of the meeting (Arata Kaneko, HU)
9:15-9:45
Plenary session (1)
10:00-12:00
Past, present and future of Indonesian Sea studies
(Fadli Syamsudin, BPPT)
Measuring tidal currents and volume transport
through a wide strait by use of the coastal
acoustic tomography system (Xiaohua Zhu,
Plenary session (2)
SIO/SOA)
Innovative application of CAT to Kuroshio
14:00-17:00
measurement (Chen-Fen Huang, NTU)
The observation plan of SITE and TIMIT projects in
the Indonesian Seas (Shujiang Li, FIO/SOA)
The Local Variation of the Indonesian Seas Index
Characteristic: "Eighteen Years Analysis of Multi
Sensor Satellite Remote Sensing Data”
(I Dewa Nyoman Nurweda Putra, Udayana. Univ)
Date
Sessions
Ongoing projects and
November 4, 2015
plan
9:00-12:00
Title & Speaker
JAMSTEC project plan to the Indonesian
Seas (Iwao Ueki, JAMSTEC)
The SIO/SOAITF project (Zhou Lei, SIO/SOA)
One invited speech is reserved here.
Lombok Strait POM model(Hidemi Mutsuda, HU)
Satellite imagery of Lombok Strait and the
Model and Satellite
14:00-17:00
adjacent seas (Yuji Sakuno, HU)
Hiroshima Bay CAT experiment (Chuanzheng
Zhang, HU)
Hiroshima Bay data assimilation (Minmo Chen, HU)
Two regular speeches are reserved here.
Date
Sessions
Reception Dinner
Title & Speaker
All participants are invited.
18:30-20:30
Date
Sessions
Title & Speaker
Bali Strait CAT experiment (Yudi Adityawarman,
BPPT)
November 5, 2015
Dalian Bay CAT experiment (Fan Xiaopeng,
9:00-12:00
SIO/SOA)
CAT
A recent activity to CAT (NaokazuTaniguchi, NTU)
A new system design of CAT (Hong Zheng, ZOU)
Two regular speeches are reserved here.
14:00-15:30
Detailed explanation of projectdesign and
MCAT-ITF project (1)
16:00-17:00
Data distribution and analysis policy (Arata Kaneko,
MCAT-ITF project (2)
HU)
Date
November 6, 2015
deployment (Arata Kaneko, HU)
Sessions
Field survey (1)
Title & Speaker
Tomography site is surveyed.
Discussion is deepened by mutual communication at
10:00-15:00
this event.
Date
November 7, 2015
Sessions
Field survey (2)
10:00-15:00
Title & Speaker
Application of CAT to aquaculture fields is surveyed.
Discussion is deepened by mutual communication at
this event.
Resort hotel reserved for all participants:
Holiday Resort Lombok (about $46/night in special government discount)
Senggigi Beach Lombok 83355 NTB, Indonesia
Phone: +62-370-693444
Fax: +62-370-693092
http://holidayresort-lombok.com/meeting-banquet.html
Acronyms:
BPPT (Agency for the Assessment and Application of Technology, Indonesia)
UNRAM (University of Mataram, Indonesia)
HU (Hiroshima University, Japan)
UT (University of Tokyo, Japan)
JAMSTEC (Japan Agency for Marine-Earth Science and Technology, Japan)
SIO/SOA (Second Institute of Oceanography
/State Oceanic Administration, China)
FIO/SOA (First Institute of Oceanography
/State Oceanic Administration, China)
ZOU (Zhejiang Ocean University, China)
NTU (National Taiwan University)
CU (Columbia University)
SIO (Scripps Institution of Oceanography)
ONR (Office of Naval Research)
The Local Variation of the Indonesian
Seas Index Characteristic: "Eighteen
Years Analysis of Multi Sensor Satellite
Remote Sensing Data”
I Dewa Nyoman Nurweda Putra
UDAYANA UNIVERSITY
2015
Introduction
Major Characteristics:
SE Asia
Pacific Ocean
ITF
ENSO
IOD
Shallow
Indian Ocean
A semi-closed
marginal sea
Pacific and
Indian
Ocean
Asia and
Australia
continent
Unique
bathymetry
Western
5000 m
Unique
pathway
Indonesian
throughflow
(ITF)
Interannual
Variability
ENSO
Deep
Australia
IOD
(Meter)
Need a relevant information and better understanding on the
features of the characteristics of indices in the Indonesian Sea.
Seasonal Variability
D
C
E
M
N
H
I
J
K
L
F
G
B
A
(Nurweda et al., 2013)
U-WS
SST
The Inner Indonesian Seas
RR
: Strong
: Weak
: Nearly Zero
6-Months Variability
D
C
E
M
N
H
I
J
K
L
F
G
B
A
U-WS
SST
The Inner Indonesian Seas
(Nurweda et al., 2013)
RR
: Very Weak
: Weak
: Zero
Objectives
1. To investigate the cyclical temporal variability
issues on SST index in the several areas of
Indonesian Seas.
2. To improve the detection of the ENSO signal for
the area that show a cyclic temporal variability.
Data Sources
Index
Time Coverage
Unit
Spatial Res.
SST
Dec 97 – Jul 13 And Jan 14 – Aug 15
˚C
0.25˚ ×0.25˚
Temporal Res.
Monthly
Channel(s)
10.65 GHz
Product
Data Center
L3 F10.7 TMI And AMSR 2
REMSS
Index
Time Coverage
Product
Data Center
ONI
1950 – 2014
ENSO Index
NOAA
Data Analysis:
1. Detection of Cyclic Temporal Variability
- Seasonal Variability
- 6-months Variability
2. Detection of the ENSO Signal
Seasonal Variability
Original Data
(Java Sea)
Mode 1
SSA
Mode 2
6-Months Variability
Original Data
(Java Sea)
Mode 3
SSA
Mode 4
Data Analysis:
1. Detection of Cyclic Temporal Variability
- Seasonal Variability
- 6-months Variability
2. Detection of the ENSO Signal
ENSO Phenomenon
Source : NOAA
The El Nino Southern Oscillation (ENSO) Mechanism
ENSO Phenomenon
Index
ONI
Area Boundary
5˚S-5˚N and 190˚E240˚W
Definition
El Nino: The 3 months moving averages of SST is at
least 0.5 warmer than 30-year (1981-2010) average.
La Nina: The 3 months moving averages of SST is at
least 0.5 cooler than 30-year (1981-2010) average.
ENSO Signal Detection
(Proposed Method)
Removing
Seasonal
Variability
Long term
monthly
average data
Area that shows
cyclic temporal
variability
Removing 6
months
variability
Extracted
from 6 month
MA
ENSO Signal
3 months
Moving
Averages
ENSO Signal (Area J)
El Nino
NOAA
Method
Proposed
Method
La Nina
Nino 3.4
Area
ENSO Signal (Java Sea)
3-Months MA
New Proposed Method
El Nino
La Nina
(Nurweda et al., 2013)
Conclusions
The strong cyclical temporal variability exists in the
SST index of Indonesian Seas.
The result of NOAA method could not remove the
strong cyclical temporal variability.
The proposed method significantly improves the
ENSO signal detection for the area that show a cyclic
temporal variability.
Contact Information
Dr. I Dewa Nyoman Nurweda Putra
Ocean Remote Sensing
Faculty of Marine Science and Fisheries
Centre for Remote Sensing and Ocean Sciences
Udayana University
Email: nurweda14@unud.ac.id
nurweda14@gmail.com