The El Niño Southern Oscillation (ENSO) monitoring system is in “La Niña Conditions” in March 2021. The 1-month Nino3.4 sea surface temperature index continues to indicate La Niña conditions, although it has likely past its peak for this event. Atmospheric indicators (cloudiness and wind anomalies) remain generally consistent with La Niña conditions, although they have weakened slightly in February. The Nino3.4 index was -1.17°C for January 2021 and\xa0 1.40°C for the November 2020 – January 2021 three-month average.
Models are predicting La Niña conditions to gradually weaken during March to June 2021.
Further Information on ENSO
ENSO conditions are monitored by analysing Pacific sea surface temperatures (SSTs), low level winds, cloudiness (using outgoing longwave radiation), and sub-surface temperatures. Special attention is given to SSTs, as they are one of the key indicators used to monitor ENSO. Here, three different datasets are used: HadISST, ERSSTv5, and COBE datasets. As globally, SSTs have gradually warmed over the last century under the influence of climate change, the SST values over the Nino3.4 will increasingly be magnified with time, and hence appear warmer than they should be. Therefore, this background trend is removed from the SST datasets (Turkington, Timbal, & Rahmat, 2018), before calculating SST anomalies using the climatology period 1976-2014. So far, there has been no noticeable background trend in the low-level winds or cloudiness.
El Niño (La Niña) conditions are associated with warmer (colder) SSTs in the central and eastern Pacific. The threshold for an El Niño (La Niña) in the Nino3.4 region is above 0.65°C (below -0.65°C). El Niño (La Niña) conditions also correspond to an increase (decrease) in cloudiness around or to the east of the international dateline (180°), with a decrease (increase) in cloudiness in the west. There is also a decrease (increase) in the trade winds in the eastern Pacific. Sub-surface temperatures in the eastern Pacific should also be warmer (colder) than average, to sustain the El Niño (La Niña) conditions.
For ENSO outlooks, information from the World Meteorological Organization (WMO) and international climate centres are assessed. The centres include the Climate Prediction Center (CPC) USA, the Bureau of Meteorology (BoM) Australia, as well as information from the International Research Institute for Climate and Society (IRI) which consolidates model outputs from other centres around the world. Each centre uses different criteria, including different SST thresholds. Therefore, variations between centres on the current ENSO state should be expected, especially when conditions are borderline.
The sea surface temperatures (SSTs) over the central and eastern tropical Pacific overall represented La Niña conditions in January 2021 (Figure 1). Across the Indian Ocean, no Indian Ocean Dipole was present. Models predict that the La Niña conditions will weaken during March – June. The Indian Ocean Dipole is expected to remain in the neutral state until at least April 2021.
Figure 1: Detrended SST anomalies for January 2021 with respect to 1976-2014 climatology using ERSST v5 data. Red (blue) shades show regions of relative warming (cooling). The tropical Pacific Ocean Nino3.4 Region is outlined in red. The Indian Ocean Dipole index is the difference between average SST anomalies over the western Indian Ocean (black solid box) and the eastern Indian Ocean (black dotted box).
Looking at the Nino3.4 index in \xa0Figure 2, prior to August 2020, the 1-month Nino3.4 values were within the neutral range. Since August 2020, the Nino3.4 index has been within the La Niña range, with the largest 1-month anomalies observed in October and November 2020. La Niña conditions are considered to be present when the 1-month cold SST anomalies (observed or forecast) persist for at least four months below the threshold, along with supporting atmospheric observations.
Figure 2: The Nino3.4 index using the 1-month SST anomalies. Warm anomalies (≥ +0.65; brown) correspond to El Niño conditions while cold anomalies (≤ -0.65; blue) correspond to La Niña conditions; otherwise neutral (> -0.65 and < +0.65; grey).
Model outlooks from Copernicus C3S (Figure 3) indicate Nino3.4 SST index has peaked and that \xa0the La Niña conditions will continue to weaken during March – April. Most models predict continued weakening from May onwards, although a few models predict La Niña conditions to strengthen again in May – July. However, model skill in February for predicting ENSO conditions in the boreal spring (June – August) is low.
Figure 3: Forecasts of Nino3.4 index’s strength until July 2021 from various seasonal prediction models of international climate centres (image credit: Copernicus C3S).
Historical ENSO Variability
To classify a historical El Niño event, the 3-month average Nino3.4 value must be above 0.65°C for 5 or more consecutive months. For La Niña events, the threshold is -0.65°C. Otherwise it is considered neutral. ENSO events with a peak value above 1.5°C (El Niño) or below -1.5°C (La Niña) are considered strong. Otherwise, the events are considered weak to moderate in strength. The following figure (Figure 4) shows the development of the Nino3.4 index in 2015-18 in comparison to other El Niño/La Niña events.
Figure 4: Three-month Nino3.4 index development and retreat of different El Niño (left)/La Niña (right) events since the 1960s. The most recent El Niño and La Niña events are in red and purple, respectively.
Impact of El Niño/La Niña on Southeast Asia
The typical impact of El Niño on Southeast Asia is drier-than-average rainfall conditions, including during March to May (Figure 5, left). Warmer temperature conditions typically follow drier periods. The opposite conditions for rainfall (and consequently temperature) are observed during La Niña years (Figure 5, right).
The impact on the region’s rainfall and temperature from ENSO events is more significantly felt during strong or moderate-intensity events. Also, no two El Niño events or two La Niña events are exactly alike in terms of their impact on the region.
Figure 5: March to May (MAM) season rainfall anomaly composites (mm/day) for El Niño (left) and La Niña (right) years. Brown (green) shades show regions of drier (wetter) conditions. Note that this anomaly composite was generated using a limited number of El Niño and La Niña occurrences between 1979 and 2017 and therefore should be interpreted with caution (data: NOAA CPC CAMS_OPI).
Turkington, T., Timbal, B., & Rahmat, R. (2018). The impact of global warming on sea surface temperature based El Nino Southern Oscillation monitoring indices. International Journal of Climatology, 39(2).
El Niño/La Niña
For El Niño/La Niña updates, information provided by the World Meteorological Organization (WMO) and various international climate centres are assessed. The centres include the Climate Prediction Center (CPC) USA, the Bureau of Meteorology (BoM) Australia, as well as information from the International Research Institute for Climate and Society (IRI) which consolidates model outputs from various other centres around the world.
Frequently Asked Questions
What is El Niño/La Niña and how do they affect weather in South East Asia?
The El Niño phenomenon is a non-regular occurrence in the tropical pacific region where warmer waters develop over the Eastern Tropical Pacific Ocean along the coast of South America. In South East Asia, this brings drier weather and increases the risk of forest fires and smoke haze. The La Niña phenomenon is the reverse of the El Niño where cooler waters develop over the Eastern Tropical Pacific Ocean along the coast of South America.
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.