Abstract

Abstract. The changes in the El Niño–Southern Oscillation (ENSO) phenomenon and its precipitation-related teleconnections over the globe under climate change are investigated in the Community Earth System Model Large Ensemble from 1950 to 2100. For the investigation, a recently developed ensemble-based method, the snapshot empirical orthogonal function (SEOF) analysis, is used. The instantaneous ENSO pattern is defined as the leading mode of the SEOF analysis carried out at a given time instant over the ensemble. The corresponding principal components (PC1s) characterize the ENSO phases. By considering sea surface temperature (SST) regression maps, we find that the largest changes in the typical amplitude of SST fluctuations occur in the June–July–August–September (JJAS) season, in the Niño3–Niño3.4 (5∘ N–5∘ S, 170–90∘ W; NOAA Climate Prediction Center) region, and the western part of the Pacific Ocean; however, the increase is also considerable along the Equator in December–January–February (DJF). The Niño3 amplitude also shows an increase of about 20 % and 10 % in JJAS and DJF, respectively. The strength of the precipitation-related teleconnections of the ENSO is found to be nonstationary, as well. For example, the anticorrelation with precipitation in Australia in JJAS and the positive correlation in central and northern Africa in DJF are predicted to be more pronounced by the end of the 21th century. Half-year-lagged correlations, aiming to predict precipitation conditions from ENSO phases, are also studied. The Australian and Indonesian precipitation and that of the eastern part of Africa in both JJAS and DJF seem to be well predictable based on the ENSO phase, while the southern Indian precipitation relates to the half-year previous ENSO phase only in DJF. The strength of these connections increases, especially from the African region to the Arabian Peninsula.

Highlights

  • The El Niño–Southern Oscillation (ENSO) is recognized as the dominant interannual fluctuation in the climate system

  • Ensemble-based instantaneous regression maps present typical values of the amplitude of the fluctuations directly related to the given empirical orthogonal function (EOF) mode of variability at each grid point, which in the case of EOF1 has the strongest relationship with ENSO

  • The temporal changes in the regression maps are easy to interpret intuitively; they show the changes in the fluctuation amplitudes, i.e., changes in the typical sea surface temperature (SST) anomalies bound to the given mode at each grid point and potential shifting in the pattern during climate change as well

Read more

Summary

Introduction

The El Niño–Southern Oscillation (ENSO) is recognized as the dominant interannual fluctuation in the climate system (see, e.g., Bjerknes, 1969; Rasmusson and Carpenter, 1982; Neelin et al, 1998; Philander, 1990; Timmermann et al, 2018). The SEOF method, computing all relevant quantities at single time instants, via the computed principal components (PC1s) of the leading SEOF mode used as certain ENSO indices to characterize the ENSO phases, allows us to investigate ENSO teleconnections based only on instantaneous ensemble statistics Since this can be done at any time instant, it enables us to monitor the temporal evolution of the strength of the teleconnection during a climate change. It includes a discussion on the capability of snapshot frameworks in general compared to the traditional single time series-based temporal analysis and the interpretation of the meaning of their results.

Data and methods
Studying ENSO and its teleconnections in the snapshot framework
Comparing the capabilities of the snapshot and traditional methods
Changes in the ENSO pattern and amplitude
Changes in ENSO’s teleconnections
Conclusions
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.