Observations: In February 2017, the cool anomalies of the equatorial Pacific Ocean’s sea-surface temperature (SST) further weakened towards neutral values (Figure A). The Nino3.4 index for February 2017 was -0.2 (Figure B) and the latest 3-month average (Dec-Feb) was -0.5. Most of the atmospheric indicators over the equatorial Pacific are at neutral values since mid-February.
Outlook: Most models indicate the tropical Pacific will continue warming gradually for the next 6 months. Given the observations and outlook, there is an increasing chance for El Niño development (Figure D) in the second half of the year, with a majority of the models indicating weak El Niño strength (Figure E). However, model outlooks made at this time of the year are not as accurate as those made during the second half of the year and furthermore their Nino3.4 anomaly predictions may contain a tropical warming component leading to an overestimation of the effective Nino3.4 values. More confident assessment of El Niño risk will be available from May onwards.
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 F). 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 February 2017 with respect to 1981-2010 climatology. Warm shades show regions of relative warming, while cool shades show regions of relative cooling. On average, the tropical Pacific Ocean Nino3.4 region (red box, 120°W-170°W and 5°S-5°N) was still slightly cooler than normal but is weakening to neutral (image credit: IRI Map Room).
- Figure B: The Nino3.4 index based on raw (full line) data, 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 an El Niño event (above 0.65°C) while cold anomalies (blue line) correspond to a La Niña event (below -0.65°C); 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: Spatial rainfall anomaly patterns in the region for February 2017 showing large scale, wetter-than-normal conditions for the region (image credit: IRI Map Room). Brown (green) shades show drier (wetter) than the average climatological rainfall for February (1970 – 2009). Quantitative anomaly values are only indicative due to limitations in the data source (data: NOAA CPC CAMS_OPI).
- Figure D: Probability of El Niño (red), La Niña (blue) and neutral conditions (green) for 2017. Neutral conditions are favoured up to mid-2017 and following that increasing chance of El Niño developing. However, model outlooks made at this time of the year are not as accurate as those made during the second half of the year and furthermore their Nino3.4 anomaly predictions may contain a tropical warming component leading to an overestimation of the effective Nino3.4 values (image credit: IRI-CPC).
- Figure E: Forecasts of Nino3.4 index’s strength for 2017 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 warming to continue and for El Niño conditions to emerge from mid-2017. However, model outlooks made at this time of the year are not as accurate as those made during the second half of the year and furthermore their Nino3.4 anomaly predictions may contain a tropical warming component leading to an overestimation of the effective Nino3.4 values (image credit: IRI-CPC).
- Figure F: 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
 From February 2017 onwards, ASMC has adopted a new dataset for calculation of the Nino3.4 index which is the latest ERSST v4 (Extended Reconstructed Sea Surface Temperature) version 4 product from US NOAA NCDC.
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.
Frequently Asked Question
What is El Niño/La Niña and how do they affect weather in South East Asia?
In South East Asia, higher than normal rainfall tends to occur during a La Niña episode which may result in an increased occurrence of floods.
The correlation between El Niño/La Niña and its associated weather impacts on South East Asia differ from one place to another and for different seasons.
The image above shows the precipitation anomalies averaged over the El Niño and La Niña years. For instance, the impact of El Niño is typically stronger over the southern and eastern part of South East Asia during the months of Jun – Oct.