{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,14]],"date-time":"2025-05-14T12:51:13Z","timestamp":1747227073822,"version":"3.40.5"},"posted":{"date-parts":[[2020,3,23]]},"group-title":"oral","reference-count":0,"publisher":"Copernicus GmbH","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"abstract":"<jats:p>\n        &amp;lt;p&amp;gt;The El-Ni&amp;amp;#241;o index behaves as a nonlinear and non-Gaussian stochastic process. A well-known characteristic is its positive skewness coming from the occurrence of stronger episodes of El-Ni&amp;amp;#241;o than of La Ni&amp;amp;#241;a. Here, we use the period 1870-2018 of the standardized El-Ni&amp;amp;#241;o index x(t), sampled in trimesters to analyze the spectral origin of the bicorrelation: sk(t1,t2)=E[x(t)x(t+t1)x(t+t2)] and skewness sk(0,0). For that, we estimate the two-dimensional Fourier transform of sk(t1,t2) or bispectrum B(f1,f2). Its sum over bi-frequencies (f1,f2) equals the skewness (0.45 in our case). Positive and negative bispectrum peaks are due to phase locking of frequency triplets: (f1,f2,f1+f2), contributing to extreme El-Ni&amp;amp;#241;os and La Ni&amp;amp;#241;as respectively. Moreover, the most significant positive and\/or negative bispectrum regions are rather well localized in the bispectrum domain. Here, we propose a partition of the El Ni&amp;amp;#241;o signal into a set of band-pass spectrally separated components whose self and cross interactions can explain the broad structure of bispectrum. In the simplest case where the signal is decomposed into a fast and a slow component (with a cutoff frequency of (1\/2.56) cycles\/yr.), we verifty that slow-slow interactions (or phase locking) explain most of La-Ni&amp;amp;#241;as, particularly at the frequency triplet (1\/4.9, 1\/15 and 1\/3.7 cycles\/yr) whereas the fast-slow interactions explain most of El Ni&amp;amp;#241;os, particularly at the frequency triplet (1\/4.9, 1\/4.9 and 1\/2.5 cycles\/yr). In order to simulate this stochastic behavior, we calibrate a set of nonlinearly coupled oscillators (Auto-regressive processes, forced by self and cross quadratic component terms), one for each component. In the case of weak cross-component interactions, and thus weak nonlinearity, the coupling coefficients between spectral-band components are proportional to the corresponding cross-skewnesses, which represent good first guesses in the calibration of the model parameters. The predictability of the model is then assessed, in particular for the anticipation of big El Ni&amp;amp;#241;os and la Ni&amp;amp;#241;as. The authors would like to acknowledge the financial support FCT through project&amp;amp;#160;&amp;lt;strong&amp;gt;UIDB\/50019\/2020 &amp;amp;#8211; IDL.&amp;lt;\/strong&amp;gt;&amp;lt;\/p&amp;gt;\n        <\/jats:p>","DOI":"10.5194\/egusphere-egu2020-10741","type":"posted-content","created":{"date-parts":[[2020,3,9]],"date-time":"2020-03-09T21:42:26Z","timestamp":1583790146000},"source":"Crossref","is-referenced-by-count":0,"title":["Stochastic modeling of extreme El-Ni&amp;#241;o and La Ni&amp;#241;a events by nonlinearly coupled oscillators"],"prefix":"10.5194","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1700-6607","authenticated-orcid":false,"given":"Carlos","family":"Pires","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8255-5186","authenticated-orcid":false,"given":"Abdel","family":"Hannachi","sequence":"additional","affiliation":[]}],"member":"3145","container-title":[],"original-title":[],"deposited":{"date-parts":[[2020,3,23]],"date-time":"2020-03-23T18:33:30Z","timestamp":1584988410000},"score":1,"resource":{"primary":{"URL":"https:\/\/meetingorganizer.copernicus.org\/EGU2020\/EGU2020-10741.html"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,3,23]]},"references-count":0,"URL":"https:\/\/doi.org\/10.5194\/egusphere-egu2020-10741","relation":{},"subject":[],"published":{"date-parts":[[2020,3,23]]},"subtype":"other"}}