The 2023 extreme coastal El Niño: Atmospheric and air-sea coupling mechanisms

Abstract

In the boreal spring of 2023, an extreme coastal El Niño struck the coastal regions of Peru and Ecuador, causing devastating rainfalls, flooding, and record dengue outbreaks. Observations and ocean model experiments reveal that northerly alongshore winds and westerly wind anomalies in the eastern equatorial Pacific, initially associated with a record-strong Madden-Julian Oscillation and cyclonic disturbance off Peru in March, drove the coastal warming through suppressed coastal upwelling and downwelling Kelvin waves. Atmospheric model simulations indicate that the coastal warming in turn favors the observed wind anomalies over the far eastern tropical Pacific by triggering atmospheric deep convection. This implies a positive feedback between the coastal warming and the winds, which further amplifies the coastal warming. In May, the seasonal background cooling precludes deep convection and the coastal Bjerknes feedback, leading to the weakening of the coastal El Niño. This coastal El Niño is rare but predictable at 1 month lead, which is useful to protect lives and properties.

Fig. 1.. The spatiotemporal distribution of the 2023 coastal El Niño and associated atmospheric conditions.

Left: Observed SST (°C, color shading), 10-m wind (meters per second, vectors; values below 0.5 m/s not shown), and rainfall anomalies (line contours with an interval of 2 mm/day; positive values in green and negative values in brown) during (A) January, (C) February, (E) March, (G) April, and (I) May. Right: Same as left but for the anomalous wind and rainfall obtained from the AGlobal experiment during (B) January, (D) February, (F) March, (H) April, and (J) May (see Materials and Methods for details).

Fig. 2.. Evolution of the 2023 coastal El Niño.

Longitude-time Hovmöller diagram of u10 anomalies (line contours with an interval of 2 m/s; positive black and negative gray) as well as (A) observed SLA (cm, color shading) and (B) simulated SLA from the OGCM CTRL run (cm, color shading). All meridionally averaged over 2°S to 2°N. Latitude-time evolution of (C) SSTA (°C, color shading) and SLA (line contours with an interval of 2 cm; positive black and negative gray), and (D) rainfall (millimeters per day, color shading) and v10 anomalies (line contours with an interval of 1 m/s, positive black and negative gray) zonally averaged over 80°W to 85°W. The dashed line indicates the approximate time when the coastal rainfall and wind anomaly signals disappear.

Fig. 3.. Latitude-time evolution of the 2023 extreme coastal El Niño in OGCM experiments.

Latitude-time Hovmöller diagrams of coastal (80°W to 85°W) SST anomalies (color shading; degree Celsius) and SLA (contours with an interval of 2 cm; positive black, zero omitted and negative gray) from the OGCM (A) CTRL, (B) ${\mathrm{\tau }}_{\text{Coast}}^{\prime }$, (C) ${\mathrm{\tau }}_{\text{EEP}}^{\prime }$, and (D) ${\mathrm{\tau }}_{\text{CWP}}^{\prime }$ simulations.

Fig. 4.. Weather to intraseasonal timescale perturbations during the 2023 event.

(A) The Wheeler-Hendon phase diagram for June 1974 to July 2023. The 2023 MJO index is highlighted in color, with February in magenta, March in red, and April in blue. (B) Hovmöller diagrams of equatorial (5°S to 5°N) 200 hPa velocity potential (ϕ, color shading, m²/s) and 850-hPa zonal wind anomalies (line contours with an interval of 1 m/s; positive black and negative gray). (C) Observed 30 to 90 band-filtered anomalies of rainfall (millimeters per day; color shading) and 10-m wind (meters per second, vectors), averaged during 5 to 13 March 2023. (D) Correlation (color shading) of observed v10 with eastern Pacific (EP, 85°W to 100°W, 2°S to 2°N) averaged u10; also shown are 10-m wind regressions (vectors) onto EP u10 (30- to 90-day band-filtered anomalies used for 2012–2023).