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Abstract. Large-scale interaction between the three tropical ocean basins is an area of intense research that is often conducted through experimentation with numerical models. A common problem is that modeling groups use different experimental setups, which makes it difficult to compare results and delineate the role of model biases from differences in experimental setups. To address this issue, an experimental protocol for examining interaction between the tropical basins is introduced. The Tropical Basin Interaction Model Intercomparison Project (TBIMIP) consists of experiments in which sea surface temperatures (SSTs) are prescribed to follow observed values in selected basins. There are two types of experiments. One type, called standard pacemaker, consists of simulations in which SSTs are restored to observations in selected basins during a historical simulation. The other type, called pacemaker hindcast, consists of seasonal hindcast simulations in which SSTs are restored to observations during 12-month forecast periods. TBIMIP is coordinated by the Climate and Ocean – Variability, Predictability, and Change (CLIVAR) Research Focus on Tropical Basin Interaction. The datasets from the model simulations will be made available to the community to facilitate and stimulate research on tropical basin interaction and its role in seasonal-to-decadal variability and climate change. 

Abstract Understanding the impact of the Indian Ocean Dipole (IOD) on El Niño-Southern Oscillation (ENSO) is important for climate prediction. By analyzing observational data and performing Indian and Pacific Ocean pacemaker experiments using a state-of-the-art climate model, we find that a positive IOD (pIOD) can favor both cold and warm sea surface temperature anomalies (SSTA) in the tropical Pacific, in contrast to the previously identified pIOD-El Niño connection. The diverse impacts of the pIOD on ENSO are related to SSTA in the Seychelles-Chagos thermocline ridge (SCTR; 60°E-85°E and 7°S-15°S) as part of the warm pole of the pIOD. Specifically, a pIOD with SCTR warming can cause warm SSTA in the southeast Indian Ocean, which induces La Niña-like conditions in the tropical Pacific through interbasin interaction processes associated with a recently identified climate phenomenon dubbed the “Warm Pool Dipole”. This study identifies a new pIOD-ENSO relationship and examines the associated mechanisms. 

Abstract The subtropical oceans between 35°-20°S in the Southern Hemisphere (SH) have exhibited prevailingly rapid sea-level rise (SLR) rates since the mid-20^thcentury, amplifying damages of coastal hazards and exerting increasing threats to South America, Africa, and Australia. Yet, mechanisms of the observed SLR have not been firmly established, and its representation in climate models has not been examined. By analyzing observational sea-level estimates, ocean reanalysis products, and ocean model hindcasts, we show that the steric SLR of the SH subtropical oceans between 35°-20°S is faster than the global mean rate by 18.2%±9.9% during 1958-2014. However, present climate models—the fundamental bases for future climate projections—generally fail to reproduce this feature. Further analysis suggests that the rapid SLR in the SH subtropical oceans is primarily attributable to the persistent upward trend of the Southern Annular Mode (SAM). Physically, this trend in SAM leads to the strengthening of the SH subtropical highs, with the strongest signatures observed in the southern Indian Ocean. These changes in atmospheric circulation promote regional SLR in the SH subtropics by driving upper-ocean convergence. Climate models show systematic biases in the simulated structure and trend magnitude of SAM and significantly underestimate the enhancement of subtropical highs. These biases lead to the inability of models to correctly simulate the observed subtropical SLR. This work highlights the paramount necessity of reducing model biases to provide reliable regional sea-level projections. 

Abstract Low-lying island nations like Indonesia are vulnerable to sea level Height EXtremes (HEXs). When compounded by marine heatwaves, HEXs have larger ecological and societal impact. Here we combine observations with model simulations, to investigate the HEXs and Compound Height-Heat Extremes (CHHEXs) along the Indian Ocean coast of Indonesia in recent decades. We find that anthropogenic sea level rise combined with decadal climate variability causes increased occurrence of HEXs during 2010–2017. Both HEXs and CHHEXs are driven by equatorial westerly and longshore northwesterly wind anomalies. For most HEXs, which occur during December-March, downwelling favorable northwest monsoon winds are enhanced but enhanced vertical mixing limits surface warming. For most CHHEXs, wind anomalies associated with a negative Indian Ocean Dipole (IOD) and co-occurring La Niña weaken the southeasterlies and cooling from coastal upwelling during May-June and November-December. Our findings emphasize the important interplay between anthropogenic warming and climate variability in affecting regional extremes. 

Abstract As the greenhouse gas concentrations increase, a warmer climate is expected. However, numerous internal climate processes can modulate the primary radiative warming response of the climate system to rising greenhouse gas forcing. Here the particular internal climate process that we focus on is the Atlantic meridional overturning circulation (AMOC), an important global-scale feature of ocean circulation that serves to transport heat and other scalars, and we address the question of how the mean strength of AMOC can modulate the transient climate response. While the Community Earth System Model version 2 (CESM2) and the Energy Exascale Earth System Model version 1 (E3SM1) have very similar equilibrium/effective climate sensitivity, our analysis suggests that a weaker AMOC contributes in part to the higher transient climate response to a rising greenhouse gas forcing seen in E3SM1 by permitting a faster warming of the upper ocean and a concomitant slower warming of the subsurface ocean. Likewise the stronger AMOC in CESM2 by permitting a slower warming of the upper ocean leads in part to a smaller transient climate response. Thus, while the mean strength of AMOC does not affect the equilibrium/effective climate sensitivity, it is likely to play an important role in determining the transient climate response on the centennial time scale. 

Abstract Scientific and societal interest in the relationship between the Atlantic Meridional Overturning Circulation (AMOC) and U.S. East Coast sea level has intensified over the past decade, largely due to (1) projected, and potentially ongoing, enhancement of sea level rise associated with AMOC weakening and (2) the potential for observations of U.S. East Coast sea level to inform reconstructions of North Atlantic circulation and climate. These implications have inspired a wealth of model‐ and observation‐based analyses. Here, we review this research, finding consistent support in numerical models for an antiphase relationship between AMOC strength and dynamic sea level. However, simulations exhibit substantial along‐coast and intermodel differences in the amplitude of AMOC‐associated dynamic sea level variability. Observational analyses focusing on shorter (generally less than decadal) timescales show robust relationships between some components of the North Atlantic large‐scale circulation and coastal sea level variability, but the causal relationships between different observational metrics, AMOC, and sea level are often unclear. We highlight the importance of existing and future research seeking to understand relationships between AMOC and its component currents, the role of ageostrophic processes near the coast, and the interplay of local and remote forcing. Such research will help reconcile the results of different numerical simulations with each other and with observations, inform the physical origins of covariability, and reveal the sensitivity of scaling relationships to forcing, timescale, and model representation. This information will, in turn, provide a more complete characterization of uncertainty in relevant relationships, leading to more robust reconstructions and projections.