A Verified Estimation of the El Niño Index Niño-3.4 since 1877

Abstract

Decadal and longer time-scale variabilities of the best known El Niñ o-Southern Oscillation (ENSO) indexes are poorly correlated before 1950, and so knowledge of interdecadal variability and trend in ENSO indexes is dubious, especially before 1950. To address this problem, the authors constructed and compared physically related monthly ENSO indexes. The base index was El Niñ o index Niñ o-3.4, the sea surface temperature (SST) anomaly averaged over the equatorial box bounded by 58N, 58S, 1708W, and 1208W; the authors also constructed indexes based on the nighttime marine air temperature over the Niñ o-3.4 region (NMAT3.4) and an equatorial Southern Oscillation index (ESOI). The Niñ o-3.4 index used the ''uninterpolated'' sea surface temperature data from the Second Hadley Centre Sea Surface Temperature dataset (HadSST2), a dataset with smaller uncertainty and better geographical coverage than others. In constructing the index, data at each point for a given month were weighted to take into account the typical considerable spatial variation of the SST anomaly over the Niñ o-3.4 box as well as the number of observations at that point for that month. Missing monthly data were interpolated and ''noise'' was reduced by using the result that Niñ o-3.4 has essentially the same calendar month amplitude structure every year. This 12-point calendar month structure from April to March was obtained by an EOF analysis over the last 58 yr and then was fitted to the entire monthly time series using a least squares approach. Equivalent procedures were followed for NMAT3.4 and ESOI. The new ESOI uses Darwin atmospheric pressure in the west and is based on theory that allows for variations of the atmospheric boundary layer depth across the Pacific.The new Niñ o-3.4 index was compared with NMAT3.4, the new ESOI, and with a record of d 18 O from a coral at Palmyra, an atoll inside the region Niñ o-3.4 (Cobb et al.). Correlation coefficients between Niñ o-3.4 and the three monthly indexes mentioned above before 1950 are 0.84, 0.87, 0.73 and 0.93, 0.86, 0.73 for decadal time scales. These relatively high correlation coefficients between physically related but independent monthly time series suggest that this study has improved knowledge of low-frequency variability. All four indexes are consistent with a rise in Niñ o-3.4 SST and the weakening of the equatorial Pacific winds since about 1970.

A unified proxy for ENSO and PDO variability since 1650

“…Firstly, we note that there is high correspondence between the running variance of the UEP and that of the annual average (July-June) of the verified Niño 3.4 region SSTA of Bunge and Clarke (2009), where the correlation coefficient of 0.7 is statistically significant above the 99% level. As such the 20th century variance of the UEP is realistic.…”

“…Correlation coefficients and root mean squared error (RMSE), in brackets, of the Unified ENSO proxy (UEP) and the original proxy network with the UEP and observations during the overlapping period. Sources: SOI, Ropelewski and Halpert (1987); Kn34, Kaplan et al (1998);Hn34, Rayner et al (2003); and Bn34, Bunge and Clarke (2009). Statistical significance of greater than the 99% level in the correlation coefficients is indicated by bold font.…”

“…While SST anomaly (SSTA) data for the Niño 3.4 region region (5 1856-1977, 1870-1977 and 1873-1977 was obtained respectively from Kaplan et al (1998), Rayner et al (2003) and Bunge and Clarke (2009). These three Niño 3.4 region SSTA time series will hereafter be referred to as Kn34, Hn34 and Bn34.…”

Inferred changes in El Niño–Southern Oscillation variance over the past six centuries

“…3, running variance is calculated in a 30 yr sliding window. The running variance time series are then adjusted by adding a constant, such that their mean running variance over the period 1900-1977 matches that of the observed ENSO over the same period using instrumental data (Kaplan et al, 1998;Rayner et al, 2003;Smith et al, 2008;Bunge and CM2.1 rainfall RVM and ENSO running variance. The black lines indicate those percentiles 5 using data with no introduced dating errors, while the red, yellow, green and blue line 6 respectively represent those percentiles using data with 1/5, 1/4, 1/3, 1/2 of the time series 7 including an introduced dating error.…”

The Asian summer monsoon response to the La Niña event of 2010

“…The climatological mean position of western edge of WPSH was located at 133.5°E (Zhou et al, 2009 Cane et al, 1997;Kumar et al, 2004Kumar et al, , 2010Compo and Sardeshmukh, 2009). It is recognized that there is a debate about the phase of the SST trend in eastern tropical Pacific due to differences in some datasets, particularly when longer period data from the late nineteenth century are used (see Bunge and Clarke, 2009;DiNezio et al, 2009;Deser et al, 2010). Nevertheless, linear SST trends during the postsatellite era seem to suggest a dominant La Niña type of SST pattern in the tropical Pacific (see Ashok et al, 2012).…”