Supplementary Materials forThe 2023 coastal El Niño: Atmospheric and air-sea coupling mechanisms
Qihua Peng, Shang-Ping Xie*, Gino A. Passalacqua, Ayumu Miyamoto, and Clara Deser

Correspondence to: sxie@ucsd.edu
This PDF file includes:
Table S1figs. S1 to S13

1

Table S1. Description of the MITgcm experiments
Experiments

CTRLForcing

Description

6-hourly realistic forcing

All processes included

𝝉𝐂𝐨𝐚𝐬𝐭′Time-varying (climatological) wind stress in(outside) the coastal region (75˚ W- 90˚ W, 20˚ S-5˚N). All the other forcings are fixed to their daily
climatological values.

Impacts of coastal windanomalies′
𝝉𝐄𝐄𝐏

Same as 𝝉𝐂𝐨𝐚𝐬𝐭 , but using realistic wind stress in theeastern equatorial Pacific (EEP, 90 ˚ W- 130˚ W, 5˚S-5˚ N ).

′𝝉𝐂𝐖𝐏

Same as 𝝉𝐂𝐨𝐚𝐬𝐭 , but using realistic wind stress in thewestern equatorial Pacific (CWP, 120 ˚ E- 130˚ W,5˚ S-5˚ N ).

′EEP anomalous
effectswind′

CWP wind impacts

2fig. S1. Relationship of basin-scale El Niño with coastal El Niño during 1982-2023. Scatterplot for (A) FMA coastal region of South America (CSA, 85°W–80°W, 10°S–0°) SSTanomalies (℃) and November-January (NDJ) mean Niño 3.4 anomalies; (B) CSA FMA rainfallanomalies (mm/day) and v10 anomalies (m/s). The size of each point represents the amplitude ofSST anomalies in the CSA region.

3

fig. S2. In-situ observed SST anomalies off Peru. Monthly SST anomalies (℃) observed at (A)Paita, (B) Chicama, and (C) Chimbote stations.

4fig. S3. Chl-a anomalies during the 2023 event. (A) Time series of observed Chl-a anomalies(mg/m3) over the southeastern Pacific coastal region (75 ˚W- 85˚ W, 5˚ S-15˚ S). (B) The spatial
pattern of Chl-a anomalies (mg/m3) averaged in March-May 2023.

5fig. S4. Oceanic and atmospheric anomalies as a function of time for the 2023 coastal El Niño.
Time series of daily CSA averaged (A) SST anomalies and SST (grey line, SST>27 ℃ ishighlighted in black), (B) SLA (cm), (C) v10 anomalies (m/s), and (D) rainfall anomalies(mm/day) from January to July 2023.

6

fig. S5. WWV and subsurface perturbations for the 2023 event. March-May (MAM) Observed(A) equatorial and (B) eastern Pacific (zonally averaged in 80oW-85oW) subsurface temperature
anomalies (℃). Black line represents the 23 ℃ isotherm.

7fig. S6. Role of thermodynamics in the 2023 coastal El Niño. (A) Heat budget terms of the 2023
coastal El Niño (10−7 °C/s, averaged in CSA region) (see Materials and Methods). (C) The
decomposition of the vertical advection term into thermocline feedback (TH, blue line), Ekman
feedback (EK, red line), and the nonlinear term (grey line). (E) Changes in each heat flux
component in 2023, where QS represents surface solar radiation, QE denotes latent heat flux, QL
represents longwave radiation, and QH represents sensible heat flux. (Right panels) Spatial patternof the vertical velocity anomalies at the mixed layer bottom (color shading, 10-5 m/s) and mixed
layer horizontal current anomalies (vectors, m/s) averaged during (B) January-February, (D)March- April, and (F) May-June of 2023.
8

fig. S7. Comparison of observed and simulated SSTA for the 2023 coastal El Niño. March-April(MA) averaged (A) observed and (B) MITgcm simulated (CTRL run) SSTA (°C) in 2023.

9fig. S8. The simulated atmospheric responses to the 2023 coastal El Niño. (Left panels) SSTanomalies (℃, color shading), 10-m wind (m/s, vectors; values below 0.5 m/s not shown), andrainfall anomalies (line contours with an interval of 2 mm/day; positive values in green andnegative values in brown) during (A) February, (C) March, and (E) April in AGlobal. (Rightpanels) Same as (Left panels) but for the outputs from the ACoast2023 experiment.

10

fig. S9. Atmospheric Response to Coastal SSTAs of 2023. (a) Anomalies in Vertical Circulation(vectors; m/s; magnified by a factor of 100 for visualization purposes) and Specific Humidity (q',g/kg; represented by color shading) across the Eastern Pacific (zonally averaged between 80°Wand 85°W) as derived from (A) observations, (B) AGlobal, and (C) ACoast2023 experiments.

11

fig. S10. Predictions of the 2023 extreme coastal rainfall from the NMME. CSA anomalous
rainfall (mm/day) forecasts initialized on 1 January 2023 (grey),1 February 2023 (blue), 1 March2023 (magenta), and 1 April 2023 (red). Also plotted in black are observations.

12fig. S11. Hovmöller diagram of 10-m wind anomalies in 2023 at different timescales. (A)Longitude-time evolution of observed equatorial u10 anomalies (m/s). (C), (E), and (G) same as(A) but for the 30-day high pass, 30–90-day band pass, and 90-day low pass filtered u10 anomalies,respectively. (I) Same as (A) but from the AGlobal experiment. (Right panels) Same as (Leftpanels) but for latitude-time evolution of the coastal v10 anomalies (zonally averaged over 80oW85oW).
13

fig. S12. Observed and simulated tropical depressions in 2023. Rainfall (mm/day, colorshading) and 10-m wind (m/s, vectors) averaged during (A) March 8-10, 2023 from observationsand (B) April 8-10, 2023 in the 10th member run with large CSA v10 spread of AGlobal.

14

fig. S13. Atmospheric anomalies associated with internal variability in AGlobal. (A)Regression (sign reversed) of rainfall (shading, mm/day) and 10-m wind (vector, m/s) anomalies
onto 2023 MA CSA v10 ensemble spread variability from AGlobal. (B) Same as (A), but for
regression on the EP u10 ensemble spread variability. Here, the ensemble spread variability is
obtained by subtracting the ensemble mean from each individual member.

15