Nurhayati *, Nelly Florida*, Wahyu Pandoe**

In TPOS 2020, 27-30 January 2014, San Diego US

CURRENT STATUS AND REQUIREMENTS

FOR OCEAN CLIMATE OBSERVATION

IN INDONESIA

Indonesia Agency for Meteorology Climatology and

Geophysics

*)Center for Climate, Agro and Marine Climate, BMKG

**)Agency for The Assesment and Application of Technology (BPPT)

1.NATIONAL POTENCY

2.SEASONAL CLIMATE PREDICTION

3.REQUIREMENT FOR OPERATIONAL

OCEAN OBSERVATION

4.CONCLUSION

OUTLINES

Warm Water Warm Water

Air-Sea Interaction

(IOD)

Indian Ocean Pacific OceanMaritime Continent

Air-Sea Interaction

(ENSO)Air-Land-Sea Interaction

Indonesia as Maritime Continent:

A miniature of the Earth with

coexistence of land and sea

controlling global climate.

Land-sea heat capacity

contrast producing

diurnal/annual cycles.

Latent heating Latent heatingSolarheating

Courtesy: Manabu Yamanaka

Main Driving ForceS

of Indonesian Rainfall

IODSST

11

22

El Nino

La Nina33 MJO 44

55

11

22

33

44

55El Nino, La Nina

Indonesia’s SST

IOD

MJO

Monsoon

- New Indicator(s)?

- We have not taken into account

the ocean sub surface information

-3.5

-3

-2.5

-2

-1.5

-1

-0.5

0

0.5

1

1.5

2

2.5

3

Jan 2009

Mar

May

July

Sep

Nov

Jan 2010

Mar

Mei

Jul

Sep

Nov

Jan 2011

Mar

May

Ind

eks

Nin

o

Current NCEP/NOAA Jamstec BoM BM KG

La Nina Prediction:

Moderate – strong

1. NCEP/NOAA (USA)� Dec10 ���� La Nina Moderate

� Jan-May11 ���� Strong La Nina

2. Jamstec (Japan)� Dec10-Feb11���� La Nina strong

� Mar-May11 ���� La Nina Moderate

3. BoM (Australia)� Dec10-Mar11���� La Nina Moderate

� Apr-May11 ���� La Nina weak

4. BMKG (Indonesia)� Dec10-Mar11 ���� La Nina Moderate

La Nina Prediction:

Moderate – strong

1. NCEP/NOAA (USA)� Dec10 ���� La Nina Moderate

� Jan-May11 ���� Strong La Nina

2. Jamstec (Japan)� Dec10-Feb11���� La Nina strong

� Mar-May11 ���� La Nina Moderate

3. BoM (Australia)� Dec10-Mar11���� La Nina Moderate

� Apr-May11 ���� La Nina weak

4. BMKG (Indonesia)� Dec10-Mar11 ���� La Nina Moderate

NORMAL

El Nino - Strong

El Nino- Moderate

El Nino-Weak

La Nina - Weak

La Nina - Moderate

La Nina -Strong

Air mass flow from

Indonesia � Samudera

Pasifik

Air mass flow from

Samudera Pasifik �

Indonesia

BMKG

ENSO PREDICTION

(UPDATED 27 DECEMBER 2010)

Institusi Dec-10 Jan-11 Feb-11 Mar-11 Apr-11 May-11

NCEP/NOAA -1.55 -2.05 -2.5 -2.9 -2.7 -2.3

Jamstec -2.15 -2.05 -2 -1.8 -1.6 -1.45

BoM -1.65 -1.3 -1.15 -1 -0.75 -0.55

BMKG -1.88 -1.80 -1.80 -1.72 -1.50 -1.29

National Research Vessels Planned for the

Tropical Pacific Ocean

Current and Plan of National Observations in the Tropical Pacific Ocean

Moorings: InaTRITON #2

• Position: 1N, 138E

• Parameters: standard TRITON buoy such as SST, salinity and temperature profiles, surface meteorology, current, etc

• Expected deployment time: June 2014

Opportunities for

TPOS-2020 Resource-Sharing Partnerships

• Bilateral Collaboration:

� Indonesia (BMKG, BPPT, KKP) – USA (NOAA)

� Indonesia (BPPT) – Japan (JAMSTEC)

� Indonesia (KKP, IPB) – France (INDESO Program)

� Others

• Multilateral Collaboration: proposed joint consortium research Tropical Pacific Gateway into ITF (lead by Prof. Arnold Gordon, under intense discussions) focusing in Halmahera Sea and western Pacific-

I

II

III

Regional coverage

x

xx

x

MARINE DATA UTILISATION (of TAO TRITON)

Measured temperatures from Western Pacific

Bouy data can be used to anticipate and

predict the emergence of El Nino and La Nina

(Nino 3.4 SST) to 5-month lag with the

positioning and precise depth location.

126 128 130 132

-4 -2 0 2

126 128 130 132

-4 -2 0 2

--����Propose to installed buoy at North

Halmahera Sea to improve accuracy of

prediction model for anticipation El

Nino and La Nina.

BMKG (land)OBSERVATION NETWORK

BMKG Regional

Center (5)GAW (1) Meteorological

Stations (120)

Geophysics

Stations (31)

Climatology

Stations (21)

NETWORK OF WEATHER RADARS NETWORK OF WEATHER RADARS

To increase the number of observations at Indonesian Sea, BMKG promoted

Voluntary Observing Ship (VOS) program and installed Automatic Weather

Stations (AWS) on 11 commercial ship (PELNI), resulting in real time observational

data. (http://maritim.bmkg.go.id/index.php/aws)

NGL

Zulu

AUTOMATIC WEATHER SYSTEM ON RIG

PLATFORM (AWS RIG)

HF RADAR SYSTEM (Ina-TEWS)

Location:

Teluk Serang, Banten, West Java

Operational Ocean Observing

Requirements

• Numerical Weather Prediction (NWP) models, Air-

Sea Fluxes,

• Monitoring and Prediction of ENSO,

• Variability of Ocean and Surface Atmospheric

Conditions for Weather and Climate Products,

Including Extremes such as Floods and Droughts,

• Development of Applications for Management of

Marine Resources or Protected Species Based on

Operational Ocean Model Outputs,

• Ocean Acidification monitoring,

• Others.

CONCLUSIONSCONCLUSIONS

1. In producing seasonal and sub seasonal climate

predictions, we still seek for appropriate indicators

(ENSO, NINO3.4, SST, IOD, MJO), whereas sub surface

ocean data, SSH have not been taken into account.

2. Global/ regional Forecast models are still in the

development phase, not ready for operational purposes

(sea state, wave height, current prediction)

3. Requirements for Capacity Building and Training

� Technical observation platform (buoy, glider, argo,

cable system)

� Data Assimilation and Modelling

� New Indicators toward better climate prediction for

sectors

Thank You For Your

Attention

INDEKS MJO

Indeks bergerak berlawanan arah

jarum jam menunjukkan

pergeseran MJO ke arah timur.

Selama awal Januari (Das I)

indeks mengalami pelemahan

dan cenderung menghilang.

Memasuki pertangahan Januari

(15 Jan) indeks menunjukkan

penguatan dan muncul pada

Phase 5 di wilayah Maritim

Continent (Indonesia). Indeks

terus menguatn dan bergerak

menuju wilayah Pasifik Barat.

Posisi MJO (22/01) menunjukkan

penguatan dan muncul di wilayah

Pasifik Barat.

Monthly Rainfall Forecast for November 2013

Low

Medium

High/Very High

Category :

13 MARINE METEOROLOGICAL STATION NETWORK

and the RESPONSIBILITY AREA

Needs for Indonesian Ocean Observation

ENSO

Climate Change

Fish Migration

Tsunami

Coastal hazards

IOD

Climate Change

Capture Fisheries

Deep Sea Res.

IOD

Fish Migration

Capture Fisheries

Deep Sea Res.

IUU Fishing

Fisheries

Fisheries

Maritime Security

Sea Transport.

Sea Transport.

Maritime Security

Coastal Pollution

Oil Spills

= ITF = Int’l Sea Lanes

Deep Sea

Expl.

Carrying

Capacity

Fisheries

Sea Transport

No. Instansi Kesepakatan

1. Spatial

Planning

Department,

Jakarta

DEM lidar 2 M FROM DATA 2010.

Contour maps throughout Jakarta with a digital resolution of 25 cm.

Monitoring shorelines around North Jakarta

Bathymetry up to 30 km around Tangerang and Bekasi.

1:1000 digital maps with multiple versions.

Reference point in the northern areas or pillars throughout Jakarta more than 300

points.

2. BIG There are 115 online tide observation stations such as Jakarta and Semarang (locus

CIFDP implementation).

Map of land cover and land system as an input to development of the model.

Inter-agency agreements that have

been achieved include:

3. BPPT •Once there was a review of rob in Pekalongan with MIKE 21.

•Modeling tsunami inundation model to TUNAMI.

•Complete data bathymetry, but still limited T Carta and survey data assimilation.

4. PUSAIR •It has been proposed to apply FEWS and inundation has been already operational

in Jakarta.

5. DISHIDROS •Digital maps ENC (Electronic Navigation Chart) and digital map all ports in

Indonesia.

•Tidal prediction, although not yet online.

6. Public Works,

Jakarta

•There are some data from observation stations automatically using AWRL in some

streams and observations relating to the sea.

7. BPOL KKP •Available HPC for running models in parallel.

8 LAPAN •Have a Quick Unite Respone to support earthquake and flood information.

• Managing & archiving data

(data center)

• Analysis & Dissemination

• Modeling & operational

forecast

• Research

• Climate impact

• Disaster �

Multi Hazard

•Climate

variability

forecasting

•Climate change

analysis

ObservationResearch / Modeling

AnalysisApplication

BMKG

• Infrastructure

• Capacity

Building

Universities

Research

Institutes

KKP

BMKG

LIPI

BIG

DISHIDROS

Indian Ocean RAMA

observation

BPPT

User comunity

could include

other agencies

who provide

tailored

productsNa

tio

na

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lim

ate

Ob

serv

ati

on

s P

lan

Atm

osp

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Oce

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BIGBIG

BPPTBPPTBRKPBRKP

LIPILIPI

BMKGBMKG

DISHIDISHI--DROSDROS

LAPANLAPAN

DASDAS

MIDASMIDAS

DEVELOPMENT COOPERATION for MARINE

OBSERVATION INFORMATION (2013)

CEWS