Updated on 24 August 2017

Sea-surface temperatures (SSTs) over the equatorial Pacific Ocean is within neutral values (Figure A) and the Nino3.4 index was 0.1 for Jul 2017. The 3-month average (May to July) Nino3.4 value is also within neutral at 0.3 (Figure B). Atmospheric conditions, such as trade winds and cloudiness, over the equatorial Pacific are also at neutral levels.

For the tropical Pacific, most models indicate that the SSTs anomalies will remain neutral in the second half of 2017 (Figure C). For this period, latest experts’ consensus favours neutral conditions over El Niño or La Niña (Figure D).

Impact of El Niño/La Niña on Southeast Asia

Typically the impact from El Niño for Southeast Asia is drier-than-normal rainfall conditions, especially during the Southwest Monsoon period (June – September), including October (Figure E) and especially over the Maritime Continent. During La Niña events the opposite, i.e. wetter-than-normal conditions, normally occurs. Locally-specific impact differs from place to place and for different seasons.

No two El Niño events or two La Niña events are alike in terms of their impact on the region’s rainfall and temperature. Furthermore, the strength of events and the corresponding impact do not always scale. For example, there were years where relatively weaker El Niño/La Niña events induced more significant changes in rainfall than the stronger events.

    Figure A: Sea-surface temperature (SST) anomalies for July 2017 with respect to 1981-2010 climatology. Warm shades show regions of relative warming, while cool shades show regions of relative cooling. The tropical Pacific Ocean Nino3.4 region (solid red box, 120°W-170°W and 5°S-5°N) was at neutral levels in July. Closer to the region, the western Indian Ocean, WTIO (solid black box, 50°E-70°E and 10°S-10°N) was warmer relative to the south-eastern Indian Ocean, SETIO (dotted black box, 90°E-110°E and 10°S-0°N), which made the Indian Ocean Dipole Mode index (WTIO minus SETIO) positive, but still within neutral levels. Data source: ERSSTv4 from NOAA.

 

    Figure B: The Nino3.4 index using three-month running mean of SST anomalies (against 1981-2010 base period) in the Nino3.4 region bounded by 5°N to 5°S and 170°W to 120°W. Warm anomalies (red line) correspond to El Niño conditions while cold anomalies (blue line) correspond to La Niña conditions; otherwise neutral (grey line). The horizontal axis is labelled with the first letters of the 3-month seasons, e.g. JFM refers to January, February and March seasonal average. Data source: ERSSTv4 from NOAA.

 

    Figure C: Forecasts of Nino3.4 index’s strength for second half of 2017 and first half of 2018 from various seasonal prediction models of international climate centres. Values above 0.5°C indicate El Niño conditions, below -0.5°C indicate La Niña conditions, and in between indicate neutral conditions, i.e. neither El Niño nor La Niña. Models predict the Nino3.4 index to remain neutral for the rest of 2017. (image credit: IRI-CPC).

 

    Figure D: Probability of El Niño (red), La Niña (blue) and neutral conditions (green) for 2017. Neutral conditions are favoured over El Niño/La Niña for the rest of 2017 (image credit: IRI-CPC).

 

    Figure E: June to October rainfall anomaly composite for El Niño years minus La Niña years. Brown shades show regions where El Niño induce drier conditions and La Niña induce wetter conditions, while regions in green shades show the opposite effect, i.e. El Niño inducing wetter conditions and La Niña inducing drier conditions (image credit: IRI Data Library). Note that this anomaly composite was generated using limited number El Niño/La Niña occurrences between 1979 and 2016 and therefore should be interpreted with caution (data: NOAA CPC CAMS_OPI).

 

El Niño/La Niña
  • For El Niño/La Niña updates, ASMC assesses information provided by the World Meteorological Organization (WMO) and various international climate centres, such as the Climate Prediction Center (CPC) US, the Bureau of Meteorology (BoM) Australia, as well information from the International Research Institute for Climate and Society (IRI) which contains model outputs from various other centres around the world.