Decoding low-frequency climate variations

[pukpr]

Decoding low-frequency climate variations: A case study on ENSO and ocean surface warming
Rameshan Kallummal

https://www.sciencedirect.com/science/article/abs/pii/S0377026524000216

1. The qualitative and quantitative definitions of ENSO, as well as the spatial pattern of secular warming, continue to challenge climate scientists.
2. Commonly held assumptions in climate variability analysis, such as the stationarity of the annual cycle’s amplitude and the independence of ENSO’s origin from that of the annual cycle, are scrutinized in this study.
3. By deviating from these assumptions, the research delves into the nature of low-frequency events and proposes a novel dynamical framework.
4. The findings reported - ENSO essentially involves the interannual modulation of two annual cycles and that multidecadal amplitude modulations of a different annual cycle capture secular sea surface warming - hold direct implications for current scientific and political challenges in the realm of climate.

The qualitative and quantitative definitions of ENSO and the spatial pattern of secular warming continued to challenge climate scientists. The signals pertaining to the secular warming of the sea surface and ENSO, as extracted in preceding studies (refer to Section 1), rely on anomalies relative to a climatological annual cycle.

What are the two annual cycles?
Two annual cycles of the Pacific cold tongue under orbital precession
https://www.nature.com/articles/s41586-022-05240-9

Axial tilt ((seeasonal) plus another annual cycle driven by the variation in Earth–Sun distance (distance effect) from orbital eccentricity

Evolution mechanism of principal modes in climate dynamics
https://iopscience.iop.org/article/10.1088/1367-2630/abb89a/pdf

we found that there exist two largest intra-annual principal modes corresponding to two annual cycles within one year. The temporal
evolution of the intra-annual principal modes is investigated from 1979-01-01 to 2016-12-31 by sliding the one-year time window. We showed that the eigenvalues λ1 and λ2 significantly response to the ENSO variability for the raw data. The Pearson correlation coefficients between the fractions of the first and the second eigenvalues and the ONI are 0.65 and −0.62, which imply that the first (second) principal mode is reinforced during El Nino (La Ni˜na) and weakened during La Ni˜na (El Ni˜no).

Connecting subtropical salinity maxima to tropical salinity minima: Synchronization between ocean dynamics and the water cycle
https://www.sciencedirect.com/science/article/pii/S007966112300215X