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Director of Center for Climate Change and Air Quality – BMKG

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1 Director of Center for Climate Change and Air Quality – BMKG
Factors Influencing the Response of the Maritime Continent Climate to ENSO Dr. Edvin Aldrian Director of Center for Climate Change and Air Quality – BMKG BMKG Presented in XV WMO RA V Bali 30 April – 6 Mei 2010

2 Outline of Presentation
BMKG The theory of El Nino Predictability of the maritime continent El Nino dan climate of the maritime continent ENSO impact episode The role of local sea surface current El Nino and Indian Ocean Dipole Impact of El Nino on the Climate system El Nino and global warming Positive and negative impact of El Nino

3 Theory: What is ENSO BMKG ENSO is the abbreviation of El Niño Southern Oscillation The term El Nino means ‘Christ Child’ and was first used by Peruvian fishermen in the late 1800’s to describe the warm current appearing off the western coast of Peru around Christmas time. Southern oscillation refers to a seesaw shift in surface air pressure at Darwin, Australia and the South Pacific Island of Tahiti. When the pressure is high at Darwin it is low at Tahiti and vice versa. El Nino, and its sister event – La Nina – are the extreme phases of the southern oscillation, with El Nino referring to a warming of the eastern tropical Pacific, and La Nina a cooling.

4 Theory: What is ENSO BMKG The El Nino is indicated by the movement of warm water mass under the surface of ocean from the warm pool region to the central equatorial Pacific What is the warmpool region? Is the most warmest equatorial region located in the north of the Papua island and formed after the accumulation of flowing surface warm water in the Pacific Ocean. Why the surface water in the Pacific flows? Due to the earth rotation Part of the Great Ocean Conveyor Belt The world ventilation system in the ocean Where the water mass in the warmpool ends? The accumulation of that water mass will from geostropically to the Indian Ocean as the Indonesian Throughflow

5 Theory: Why is ENSO Predictable?
BMKG “… the time averages (monthly and seasonal means) for the tropics have more predictability. This is because they are largely determined by fluctuations of the seasonally varying boundary conditions of sea surface temperature and soil moisture. Under favorable conditions, they can contribute to the predictability of middle latitudes also.” Shukla, 1981 Atmospheric weather is IN PRINCIPLE not predictable more than 2 weeks or so; Over the tropical oceans, the STATISTICS of atmospheric weather depends on the sea surface temperature (e.g. Rains over warm water); Sea surface temperature CAN be predicted by a coupled atmosphere-ocean model if the internal state of the upper tropical ocean in known; Skill is likely to be much less in mid-latitudes because the SST determines the statistics in the presence or much variability.

6 Climatology of regional rainfall
BMKG Mainly monsoonal Three distinct rainfall climate regions Aldrian and Susanto, 2003, Intl J Climatol. monsoonal Semi-monsoonal Anti-monsoonal

7 Interannual variability in Region A
BMKG Aldrian et al, 2007, Theo. Appl. Climatol.

8 Interannual variability in Region B
BMKG Aldrian et al, 2007, Theo. Appl. Climatol.

9 Interannual variability in Region C
BMKG Aldrian et al, 2007, Theo. Appl. Climatol.

10 Wide range SST responses to rainfall in region A
BMKG Weak response in spring, no ENSO influence Strong two dipoles in SON (Walker cell) Role of SPCZ in SON Aldrian and Susanto, 2003, Intl J Climatol.

11 Wide range SST responses to rainfall in region B
BMKG Weak response in all season, especially in spring no ENSO influence and walker cell Aldrian and Susanto, 2003, Intl J Climatol.

12 Wide range SST responses to rainfall in region C
BMKG Weak response in spring Strong two dipoles in SON (Walker cell) like region A Role of SPCZ in SON like in region A Aldrian and Susanto, 2003, Intl J Climatol.

13 Skills of monthly rainfall variability
BMKG Response to ENSO Negative responses to NINO3 SST Significant in MJJAS (similar to Hendon, 2003) Variability in comparison to observations (correlation values) Strong responses in Region A and C Spring is the least responsive season ECHAM4 responds well to ENSO Aldrian et al, 2007, Theo. Appl. Climatol.

14 The Indonesian Throughflow
BMKG The Indonesian Throughflow

15 ENSO and ocean: Climate
BMKG Normal condition El Nino condition La Nina condition

16 Decadal signals of the maritime continent
(Aldrian and Djamil 2008) After monsoon and ENSO signals BMKG

17 El Niño impact episode BMKG Ensemble El Niño events during against climatology

18 La Niña impact episode BMKG Ensemble La Niña events during against climatology

19 ENSO episodes between rainfall and NINO3 SST
BMKG impact starts in April No impacts on the peak of rainfall season in DJF The ocean mechanism prevents the impact during the wet season El Nino is in-phase to the dry season, thus worsen the case La Nina has no impact in the peak of the dry season MJJ because they are out-of-phase

20 Monsoonal climatology of the Maritime Continent

21 Surface sea current (Wyrtki 1962)
BMKG June December

22 Role of ocean circulation in limiting the ENSO impact
BMKG Aldrian, Disertation thesis, 2003

El Nino and other climate characters FACTORS CONTROLLING RAINFALL IN INDONESIA A S I A 1 Ags -Sep Okt - Nov EL NINO / LA NINA DIPOLE MODE POSITIFVE/ DIPOLE MODE NEGATIVE 4 2 A F R I C A 3 INDONESIAN SST 1 4 MONSOONAL WINDS 3 1963 1972 1982 1997 EL NINO (ºC) SEP 09 1.38/ Mod OKT 09 1.95/ Mod NOV 09 2.07/ Kuat DES 09 1.94/ Mod 2 A S I A Ags -Sep Okt - Nov DIPOLE MODE (ºC) SEP 09 (+) 0.38/ Netral OKT 09 (+) 0.40/ Netral NOV 09 (+) 0.32/ Netral DES 09 (+) 0.22/ Netral 4 A F R I C A 1 3 ARAH ANGIN MUSIM AGS – SEP TIMURAN OKT– NOV BARATAN 2

24 Indian Ocean Dipole El Nino and other climate characters
BMKG The Indian Ocean Dipole (IOD) is a coupled ocean-atmosphere phenomenon in the Indian Ocean. It is normally characterized by anomalous cooling of SST in the south eastern equatorial Indian Ocean and anomalous warming of SST in the western equatorial Indian Ocean. Associated with these changes the normal convection situated over the eastern Indian Ocean warm pool shifts to the west and brings heavy rainfall over the east Africa and severe droughts/forest fires over the Indonesian region.

25 Partial correlation between Indian Ocean and ENSO in the maritime continent
BMKG Purwaningtyas and Aldrian 2008 Western pole - rainfall Eastern pole - rainfall

26 Delineation of ENSO and Indian Ocean Dipole impacts
BMKG Purwaningtyas and Aldrian 2008

27 EL NIÑO DAN DIPOLE MODE 1957 – 2007
Update EL NIÑO DAN DIPOLE MODE 1957 – 2007 EL ÑINO PERIOD Anomali Suhu Muka Laut (0 C) Central Pasifik (El Nino) Indonesian water Indian Ocean (Dipole Mode) JAS NDJ 1951/52 + 0.8 -0.38 MAM 1957 – MJJ 1958 + 1.7 -0.40 JJA 1963 – DJF 1963/64 + 1.0 -0.51 + 1.5 MJJ 1965 – MAM 1966 + 1.6 -0.46 + 0.13 OND 1968 – MJJ 1969 -0.16 - 0.12 ASO 1969 – DJF 1969/70 -0.30 + 0.58 AMJ 1972 – FMA 1973 + 2.1 -0.45 (cool) (strg) ASO 1976 – JFM 1977 -0.45 + 0.92 ASO DJF 1977/78 -0.60 + 0.5 AMJ 1982 – MJJ 1983 + 2.3 -0.60 (cool) (strg) JAS 1986 – JFM 1988 + 1.6 -0.05 + 1.88 AMJ 1991 – JJA 1992 + 1.8 -0.23 + 1.56 AMJ 1994 – FMA 1995 + 1.3 -0.52 + 2.73 AMJ 1997 – AMJ 1998 + 2.7 – 3.2 -0.29 (cool) (strg) AMJ 2002 – FMA 2003 + 1.5 0.17 (neutral) + 0.96 MJJ 2004 – JFM 2005 + 0.9 -0.06 - 0.19 JAS DJF 2006/07 + 1.1 -0.25 (cool) + 1.59 Agustus 2009 19 Sept +0.82 +0.65 0.6(warm) +0.63 -0.3 (neutral) -0.33 Sumber : NOAA Level EN & DM EN Kuat > 2.0 0C EN Moderate 1.0 – 2.0 0C EN Lemah 0.5 – 1.0 0C Tahun 1972; 1982; 1997: Pada tahun yang sama, 2 fenomena, El Nino & Dipole Mode terjadi bersama-sama  curah hujan di wilayah Indonesia berkurang banyak karena didorong dari: Pantai barat Sumatera ke Afrika Timur Wilayah perairan Indonesia ke Pasifik Tengah Perhatikan: Kekuatan El Nino dan Suhu perairan 1997: EN Kuat Suhu perairan Indonesia ; dingin 2009; EN Lemah – Moderate Suhu Perariran Indonesia; hangat 27

28 Detecting El Nino from Indonesian seas
BMKG Data from modeling Indonesian seas from the entrance and exit channel of the throughflow could be used as the precursor of the incoming El Nino up to 5 month in advance with high confidence level During El Nino the climate predictability of the region is high

29 During La Nina (El Nino) the termocline layers will transport more (less) water mass due to ENSO modulations (Meyers, 1996). Large water mass transport is usually associated with a higher density or higher salinity water, thus whenever this layers is modulated, the water composition and density will change accordingly. BMKG

30 El Nino and Indonesian climate
BMKG During El Nino, the Indonesian water will be cooler  high surface pressure in the MC, winds from Australia will be diverted to the southtern coast of MC  create Ekman pumping and upwelling there  good for fishery there and western coast of Sumatera. Ironically cool SST will induce drought especially in the western part of MC or the eastern dipole of the Indian Ocean. Hence, most of El Nino will be associatively related to the positive Dipole Mode. Moreover El Nino usually shutdown the MJO potency in that year.

31 Climate Feedback and forest fire
BMKG Aldrian 2007 annual SST Aug-Dec SST Kalimantan Sumatera 0.94 0.83 0.95 0.93 0.90 0.80 0.77 0.75 0.84 0.85 0.87 1

32 ENSO & Fishery BMKG According to Hendiarti et al (2005) fishery catch in seas around Java is highly seasonal. Catch decrease during El Nino in Sunda Strait, but increase in east Java.

33 Impact of climate change and ENSO over the deep sea
BMKG The global warming will increase surface temperature and its subsurface layer. Changes in temperature will largely occur in the mixing and thermocline layers. Subsequently marine acosystem will change due to comfort zone of living by ocean species.

34 Impact of climate change and ENSO over the deep sea
BMKG Because of global warming or strong La Nina episodes and rising of surface temperature, the ocean species will swim deeper to find the same comfort zone as before global warming happens. As a result the fish catchment must go deeper. The reverse pattern is true during El Nino event when the fish catchment increase because fish swim in shallower layers.

35 Impact of global warming on the evolution of El Nino (higher frequency) (present decade and last 3 decade) BMKG

36 Impact of global warming on the evolution of El Nino (higher intensity)

37 Why El Nino intensifier due to global warming
BMKG The Warm pool is formed due to global thermohaline circulation (the great ocean conveyor belt) and brings surface sea water from north, south and equatorial Pacific. Those surface water is notable warm because direct solar radiation. The warm pool is the main gate of water flow from the Pacific to the Indian Ocean El Nino occurs during the movement of subsurface warm pool from north of Papua to central Pacific because the subsurface temperature gradient over the warm pool and central Pacific exceed the critical threshold. By classic fluid dynamics this condition will allow propagation of water masses, thus creating El Nino Global warming will make faster warmer warm pool With faster and warmer warm pool, the potency to exceed the threshold level will be faster and allowing propagation of water mass  El Nino

38 Competing feature of ENSO and global warming in the region
BMKG As the earth surface temperature warmer, the evaporation rate over the tropics will increase  faster and higher water cycle There is a tendency of wetter dry season over the maritime continent  case 2009 Aldrian and Susanto, 2003, Intl J Climatol.

39 Evidence of wetter climate

40 Negative impacts of El Nino
BMKG Long drought and strong potency of forest fire Surface water deficit and water deficit in the reservoirs, lake, dams and rivers Long drought means harvest failure especially in the paddy field Major El Nino issues: rice import, water pump, irrigation and water resources

41 Positive impact of El Nino
BMKG Fishery sector will be booming as the fish swim nearer to the surface Salt industry will be booming due to longer solar radiation Seaweed industry will be booming with cooler surface sea water

42 Positive impact of El Nino
BMKG Transport sector  no weather extreme Several agriculture commodities will gain better harvest such as onion, tabacco, teakwood, corn etc. Construction sectors will gain better such as building development and the cement industry Tourism sector will gain benefit due to longer solar radiation

43 CONCLUSIONS BMKG The maritime continent has high seasonal predictability from tropical and maritime characters ENSO is the second largest influences of regional climate phenomena, whose influences are confined during the dry season due to monsoonal sea surface pattern.  event and impact are different Indian Ocean dipole, monsoon and global warming are confounding factors affecting the impact of ENSO in the region Global warming has intensifier the frequency and intensity of ENSO but on the other hand warmer and wetter the maritime sea and climate


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