Science Highlights

Multiyear La Niña does not increase the likelihood of transitioning to a strong El Niño

Figure 1. More persistent cold conditions in boreal spring and early summer after a multiyear La Niña, compared to those before a strong El Niño (left, a, c), inhibit an eastward movement and enhancement of atmosphere deep convection (right, b, d), leading to a decoupled ocean and atmosphere that delay the growth of a subsequent El Niño.

The Influence of Contrasting La Niña Evolutions on Indian Monsoon Rainfall Dynamics

Our CLIVAR member Satyaban Bishoyi Ratna from Climate Dynamics Panel and Monsoons Panel recently published the article which explored two distinct types of evolution in La Niña and the associated asymmetry in the response of the ISMR. It was observed that India receives significantly more and less rainfall during ELLA and LALA events, respectively, and ISMR has a spatial diversity with a northeast-southwest dipole pattern. 

Coupling is key for the tropical Indian and Atlantic Oceans to boost super El Niño

A member of the CLIVAR Tropical Basin Interaction Research Foci (TBI RF) recently published a paper that highlights the importance of coupled dynamics between the tropical Atlantic and Indian Oceans in shaping and intensifying super El Niño events. Their study, which utilizes a series of global climate model experiments, demonstrates that super El Niño events are driven by a complex interaction among the tropical Atlantic, Indian, and Pacific Oceans. It was observed that while individual effects were weaker and more uncertain, the combined effects were significantly stronger and more reliable. Specifically, the joint influence of the Atlantic and Indian Oceans was found to more effectively drive tropical Pacific warming. This process is linked to the nonlinear characteristics of convective sensitivity: when both oceans impact the Pacific simultaneously, they more effectively promote the eastward expansion of the Pacific warm pool, enhancing tropical Pacific convection and strengthening the Bjerknes feedback loop, ultimately leading to the formation of a super El Niño event.

Tropical Pacific Decadal Variability Mechanisms

The Tropical Pacific Decadal Variability (TPDV) Working Group of the CLIVAR Pacific Region Panel recently published a review paper that evaluates our understanding of the mechanisms behind TPDV.  No final consensus exists on the relative importance and efficacy of the mechanisms, but the tropical ocean adjustment to varying wind forcing likely plays a key role in the origin of decadal timescales.  These processes are elucidated in this review paper which is a product of rigorous discussions at several virtual meetings over the span of two years since the working group’s establishment in May 2021. 

Advection-driven marine heatwaves and co-occurring extremes in the Mozambique Channel

Marine heatwaves (MHWs) are events characterized by prolonged and extremely warm ocean conditions, and have been detected in recent decades over many regions of the global ocean. Some recent studies led by D. Mawren and with the contribution from J. Hermes (co-chair of IORP), provide an improved understanding of the important role of horizontal advection, associated with anticyclonic eddies on the evolution of MHWs, as well as the co-occurring extremes in the Mozambique Channel.

Towards Regional Marine Ecological Forecasting Using Global Climate Mode Predictions From Subseasonal to Decadal Time Scales: Bottlenecks and Recommendations

A perspective paper discussing how the research community can promote the enhancement of marine ecosystem forecasting using physical ocean conditions predicted by the GCMs has recently been published in Frontiers in Marine Science by scientists from CLIVAR and PICES communities. 

Intercomparison of submesoscale-permitting realistic ocean models are implemented under cloud-based framework

A cloud-based analysis framework proposed by the Pangeo project was used to systematically assess the realism of the kilometer-scale resolution models, aiming to tackle the existed distribution and analysis challenges of the model output.

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