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© Author(s) 2018. This work is distributed under
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© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 02 Nov 2018

Research article | 02 Nov 2018

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This discussion paper is a preprint. It is a manuscript under review for the journal Ocean Science (OS).

Do sun spots influence the onset of ENSO and PDO events in the Pacific Ocean?

Franklin Isaac Ormaza-González and María Esther Espinoza-Celi Franklin Isaac Ormaza-González and María Esther Espinoza-Celi
  • ESPOL Polytechnic University, Escuela Superior Politécnica del Litoral, ESPOL, (Facultad de Ingeniería Marítima, Ciencias Biológicas, Oceánicas y Recursos Naturales), Campus Gustavo Galindo Km. 30.5 Vía Perimetral, P.O. Box 09-01-5863, Guayaquil, Ecuador

Abstract. The sea surface temperature (SST), anomalies (SST), ONI (Oceanographic El Niño Index) and MEI (Multivariate ENSO Index) in regions El Niño 1+2 (80°W–90°W, 0°–10°S) and 3.4 (5°N–5°S, 170°W–120°W) as well as the Pacific Decadal Oscillation (PDO) and Atlantic Multidecadal Oscillation (AMO) indexes were correlated to sun spots number (SS) from cycles (SS#) 19 to 24 (1954–2017). Degree-six polynomial regression functions represented each of the six cycles with an average r2>0.89 (p<0.001). The series of correlations at different lag times (0, 6, 12, 24, 36 and 48 months) gave a response time: 12–36 months. In the 1954–2017 period, the whole series of SS cycles did not show a strong correlation with the variables and SST Anomaly in the El Niño areas 1+2 and 3.4. The highest correlations r2 were up to: 0.043, 0.029, 0.040 and 0.021 for PDO, MEI, ONI and SST Anomaly (in 3.4) respectively, suggesting that there is still a correlation with high confidence (p0.01). Analysing for the period 1990–2016, the correlations improved up to 0.11, 0.12, and 0.17 for ONI, SST (in 3.4) and PDO correspondingly. The SST correlations against individual SS cycles in regions 3.4 and 1+2 were up to 0.219 (SS#23) and <0.0675 (SS#19) correspondingly. SST Anomaly, ONI and MEI correlated with r2 of 0.250, 0.3943 and 0.2510, one-to-one; the lag time was 24–48 months and linear curves had positive slope. In general, in 1+2 there was found a more inconstant and lower correlation than in 3.4 (where also MEI and ONI are measured). On the longer time scales, the PDO (alike AMO) seemed to respond in 36–48 months to SS cycles showing a high degree of correlation coefficient r2 of 0.625 (SS#19) and 0.766 (SS#24); whilst AMO index gave up to 0.490 (SS#20) with similar lag time. Cycles 19 and 24 showed a better correlation in general. During the ascending phases of each cycle the SST in region 1+2 rendered correlation coefficient r2 and p-value from 0.205 and 0.0008 (SS#23) to 0.163 and ≤0.0044 (SS#19). In the region 3.4, r2 were from 0.870 (SS#24), to 0.556 (SS#23). In each SS cycle lag time was around 36 months; all of them occurred at the ascending phase, except in cycles 20 and 24. SST anomaly registered r2 from 0.662 to 0.254 in the ascending phase with a response time 0-48 months and positive linear regression slope (except SS#23). On the other hand, the descending phase showed a predominantly lower r2: <0.14 (p<0.01). The region 3.4 had better r2 than in 1+2, from 0.897 (SS#24) to 0.239 (SS#21) respectively in the ascending phase except cycles 20 and 24. The lag time was consistent at 36 months. The highest r2 of 0.897 at the end of the SS#24 peak, coincided with one of the strongest El Niño (2014–2015) and the second highest r2 (SS# 22 ascending phase) with two consecutive strong El Niño 1991–1995. ONI and MEI also showed strong correlation; the three highest r2 matched dates of strong El Niño 1987–1989, 1955–1957 and 1997–1998 in the ascending phase. During the descending phases, the correlation coefficients were lower, and ranged from 0.6082 to 0.2938; but with a lag time 0–12 months, and positive slope. The index MEI, as with ONI, registered r2 lower during descending phases. The PDOs were linearly correlated from 0.7677 to 0.2855 (12 to 24 months) and 0.3522 during ascending and descending phases respectively. On the other hand, r2 for AMO was up to 0.700. The strength of the linear correlations substantially increased when the ascending and descending phase of each cycle was analysed. During the ascending phase there is a stronger correlation than in the descending phase. These results would indicate that warm events tend to occur in the ascending phase or at the top of the cycle and have a delay time of around 36 months, whilst cold events are associated to a descending phase but with a quicker response time. The sun spot activity should be considered as a factor that could condition and trigger low (PDO and AMO) and high (ONI-El Niño) frequency oceanographic events in the Pacific and Atlantic Oceans. During 2019, the cycle 25 should start, then according to this work probably the next El Niño event would be around 2020–2021 or later.

Franklin Isaac Ormaza-González and María Esther Espinoza-Celi
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Status: open (until 15 Feb 2019)
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Franklin Isaac Ormaza-González and María Esther Espinoza-Celi
Franklin Isaac Ormaza-González and María Esther Espinoza-Celi
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Short summary
Sea surface temperature is affected by sun energy which in turn varies in time due to astronomical factors and sun activity. The activity can be estimated by sun spots (SS). Some oceanographic events like inter-annual El/La Niño/Niña as well as decadal processes should be affected by SS. It was found correlation between SS and various oceanographic indexes in time series from 1954 to 2017. This fact should be considered when dealing and modelling forecasts of such indexes.
Sea surface temperature is affected by sun energy which in turn varies in time due to...