The Recharge Oscillator (RO) is a simple mathematical model of the El Niño Southern Oscillation (ENSO). In its original form, it is based on two ordinary differential equations that describe the evolution of equatorial Pacific sea surface temperature and oceanic heat content. These equations make use of physical principles that operate in nature: (i) the air-sea interaction loop known as the Bjerknes feedback, (ii) a delayed oceanic feedback arising from the slow oceanic response to near-equatorial winds, (iii) state-dependent stochastic forcing from intraseasonal wind variations known as westerly wind bursts (WWBs), and (iv) nonlinearities such as those related to deep atmospheric convection and oceanic advection. These elements can be combined in different levels of RO complexity. The RO reproduces ENSO key properties in observations and climate models: its amplitude, dominant timescale, seasonality, and warm/cold phases amplitude asymmetry. We discuss the RO in the context of timely research questions. First, the RO can be extended to account for ENSO pattern diversity (with events that either peak in the central or eastern Pacific). Second, the core RO hypothesis that ENSO is governed by tropical Pacific dynamics is discussed from the perspective of influences from other basins. Finally, we discuss the RO relevance for studying ENSO response to climate change, and underline that accounting for ENSO diversity, nonlinearities, and better links of RO parameters to the long term mean state are important research avenues. We end by proposing important RO-based research problems.

The Fisheries and Marine Ecosystems Model Intercomparison Project (FishMIP) has dedicated a decade to unravelling the future impacts of climate change on marine animal biomass. FishMIP is now preparing a new simulation protocol to assess the combined effects of both climate and socio-economic changes on marine fisheries and ecosystems. This protocol will be based on the Ocean System Pathways (OSPs), a new set of socio-economic scenarios derived from the Shared Socioeconomic Pathways (SSPs) widely used by the Intergovernmental Panel on Climate Change (IPCC). The OSPs extend the SSPs to the economic, governance, management and socio-cultural contexts of large pelagic, small pelagic, benthic-demersal and emerging fisheries, as well as mariculture. Comprising qualitative storylines, quantitative model driver pathways and a “plug-in-model” framework, the OSPs will enable a heterogeneous suite of ecosystem models to simulate fisheries dynamics in a standardised way. This paper introduces this OSP framework and the simulation protocol that FishMIP will implement to explore future ocean social-ecological systems holistically, with a focus on critical issues such as climate justice, global food security, equitable fisheries, aquaculture development, fisheries management, and biodiversity conservation. Ultimately, the OSP framework is tailored to contribute to the synthesis work of the IPCC. It also aims to inform ongoing policy processes within the United Nations Food and Agriculture Organisation (FAO). Finally, it seeks to support the synthesis work of the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES), with a particular focus on studying pathways relevant for the United Nations Convention on Biological Diversity (CBD).

This paper proposes an ocean-only dynamical framework to mitigate the influence presentday biases of Earth System Models (ESMs) on future regional ocean physical and biogeochemical projections. Initially, a control experiment is conducted using fluxes derived from an atmospheric reanalysis, excluding climate change signals. Subsequently, a climate change simulation is performed by adding historical and future fluxes perturbations from a selected ESM to these background realistic fluxes. Since part of the ESM surface heat fluxes perturbation is a direct feedback to the sea surface temperature (SST) warming, these fluxes perturbations are split into SST-dependent and independent components. The climate change simulation is forced by the independent component, while the SST-dependent component is modeled online as an SST relaxation to the control experiment, accounting for Newtonian cooling and long-wave radiative feedback. This approach demonstrates that ESMs present-day biases can heavily impact the reliability of regional physical and biogeochemical ocean projections. For instance, the strong cold-tongue bias simulated by the IPSL-CM6A-LR model causes greater warming and chlorophyll decrease in the western than in the eastern equatorial Pacific, while our bias-corrected simulation shows opposite projected patterns. Sensitivity experiments applying heat, freshwater and momentum fluxes perturbations separately further indicate that thermodynamical and dynamical processes equally contribute to this warming pattern, highlighting the strong role of the Bjerknes feedback. This cost-effective method can be applied to any ESMs oceanic component to produce more reliable regional oceanic projections and understand the mechanisms driving the projected patterns.

Climate change is anticipated to considerably reduce global marine fish biomass, driving marine ecosystems into unprecedented states with no historical analogues. The Time of Emergence (ToE) marks the pivotal moment when climate conditions (i.e. signal) deviate from pre-industrial norms (i.e. noise). Leveraging ensemble climate-to-fish simulations, this study examines the ToE of epipelagic, migratory and mesopelagic fish biomass, alongside their main environmental drivers, for two contrasted climate-change scenarios. Globally-averaged biomass signals emerge over the historical period. Epipelagic biomass decline emerges earlier (1950) than mesozooplankton decline (2000) due to a stronger signal in the early 20th century, possibly related to trophic amplification induced by an early-emerging surface warming (1915). Trophic amplification is delayed for mesopelagic biomass due to postponed warming in the mesopelagic zone, resulting in a later emergence (2000). ToE displays strong size class dependence, with medium sizes (20 cm) experiencing delays compared to the largest (1 m) and smallest (1 cm) categories. Regional signal emergence lags behind the global average, with median ToE estimates of 2029, 2034 and 2033 for epipelagic, mesopelagic and migrant communities, respectively, due to systematically larger local noise compared to global one. These ToEs are also spatially heterogeneous, driven predominantly by the signal pattern, akin to mesozooplankton. Additionally, our findings underscore that mitigation efforts (i.e. transitioning from SSP5-8.5 to SSP1-2.6 scenario) have a potential to curtail emerging ocean surface signals by 40%.

There is an urgent need for models that can robustly detect past and project future ecosystem changes and risks to the services that they provide to people. The Fisheries and Marine Ecosystem Model Intercomparison Project (FishMIP) was established to develop model ensembles for projecting long-term impacts of climate change on fisheries and marine ecosystems while informing policy at spatio-temporal scales relevant to the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) framework. While contributing FishMIP models have improved over time, large uncertainties in projections remain, particularly in coastal and shelf seas where most of the world’s fisheries occur. Furthermore, previous FishMIP climate impact projections have mostly ignored fishing activity due to a lack of standardized historical and scenario-based human activity forcing and uneven capabilities to dynamically model fisheries across the FishMIP community. This, in addition to underrepresentation of coastal processes, has limited the ability to evaluate the FishMIP ensemble’s ability to adequately capture past states - a crucial step for building confidence in future projections. To address these issues, we have developed two parallel simulation experiments (FishMIP 2.0) on: 1) model evaluation and detection of past changes and 2) future scenarios and projections. Key advances include historical climate forcing, that captures oceanographic features not previously resolved, and standardized fishing forcing to systematically test fishing effects across models. FishMIP 2.0 is a key step towards a detection and attribution framework for marine ecosystem change at regional and global scales, and towards enhanced policy relevance through increased confidence in future ensemble projections.