Dataset associated with "El Niño–Southern Oscillation (ENSO) predictability in equilibrated warmer climates" - Zheng, Yiyu; Rugenstein, Maria; Pieper, Patrick; Beobide-Arsuaga, Goratz; Baehr, Johanna (Colorado State University. Libraries, 2022)
Responses of El Niño-Southern Oscillation (ENSO) to global warming remain uncertain, which challenges ENSO forecasts in a warming climate. We investigate changes in ENSO characteristics and predictability in idealized simulations with quadrupled CO2 forcing from seven general circulation models. Comparing the warmer climate to control simulations, ENSO variability weakens, with the neutral state lasts longer, while active ENSO states last shorter and skew to favor the La Niña state. Six-month persistence-assessed ENSO predictability slightly reduces in five models and increases in two models under the warming condition. While the overall changes in ENSO predictability are insignificant, we find significant relationships between changes in predictability and intensity, duration and skewness of the three individual ENSO states. The maximal contribution to changes in the predictability of El Niño, La Niña and neutral states stems from changes in skewness and events' duration. Our findings show that a robust and significant decrease in ENSO characteristics does not imply a similar change in ENSO predictability in a warmer climate. This could be due to model deficiencies in ENSO dynamics and limitations in persistence model when predicting ENSO.
The Niño 3.4 index calculated from the LongRunMIP outputs of global and annual TAS in seven models (CCSM3, CESM104, CNRMCM61, GISSE2R, HadCM3L, IPSLCM5A, and MPIESM12) with two forcing levels (control and abrupt4x). The LongRunMIP outputs are gained from an archive described in Rugenstein et al. 2019. All simulations used here are millennial-length long. Predictability.txt and characteristics.txt contain the changes of ENSO characteristics (frequency and events' duration) and ENSO predictability (6-month averaged accuracy). The explained variance of ENSO predictability by ENSO characteristics in the observations, control simulations, and changes between control and abrupt4x simulations.
Institute of Oceanography, The Center for Earth System Research and Sustainability, Universität Hamburg, Hamburg, Germany; Department of Atmospheric Science, Colorado State University, Fort Collins, CO, USA.
Department of Atmospheric Science