The socioeconomic challenges associated with the effects of global warming are such that there is a clearly expressed need for tailored climate information to support the implementation of mitigation and/or adaptation strategies, as articulated by economic sectors (e.g., agriculture, energy, tourism, land and maritime infrastructure, etc.) and by territories/regions that fully understand their vulnerabilities. In response to these demands, numerous national, European, and international research projects have enabled the funding of “climate services.”Several national and European operational actors are developing and making “climate services” available via platforms that are often freely accessible; finally, consulting firms are emerging on the market whose commercial activity focuses on developing “climate services” tailored to clients’ specific needs.The range of “climate services” is therefore diverse today, both in terms of the information provided (“simple” climate data, indicators, decision-support tools) and in terms of how they are developed. Given this diversity, the challenges lie in documenting and understanding the current landscape of climate services, identifying needs, and equipping ourselves with the means to characterize the success of climate services, to evaluate existing offerings, and to guide the development of new projects. The aim of this presentation has four objectives:i) To document the current landscape of climate services in France and worldwide (as identified by our TRACCS community), presenting them by use and target audience;ii) Identify unmet needs regarding climate services;iii) Identify a set of success criteria for climate services to evaluate them;iv) Propose best practices for meeting these success criteria. This work is based on a combination of collaborative research and the collection of statements from stakeholders in “climate services”. This study has received funding from Agence Nationale de la Recherche - France 2030 as part of the PEPR TRACCS programme under grant number ANR-22-EXTR-0002 and ANR-22-EXTR-0004.

Abstract. This paper describes the experimental protocol for a set of coordinated simulations involving oceanic surface freshwater flux perturbations, conducted as part of the international Tipping Points Modelling Intercomparison Project (TIPMIP). These simulations constitute the first phase of the TIPMIP-OCEAN domain. We propose this protocol for inclusion in the Coupled Model Intercomparison Project Phase 7 (CMIP7), although it can also be implemented within CMIP6+ or other types of coupled or ocean standalone models. This initial phase focuses primarily on the dynamics of the North Atlantic Ocean, particularly the Atlantic Meridional Overturning Circulation (AMOC). The different experiments are designed to (i) evaluate the impacts of a potential major AMOC weakening under a 2 °C global warming scenario, (ii) assess the sensitivity of the AMOC to combined global warming and freshwater forcing, (iii) investigate the potential recovery of the AMOC following the reversal of forcings, and (iv) compare past AMOC variations with available climate observations and reconstructions. Four categories of experiments are included. Experiment group A examines the effect of freshwater release around Greenland under ramp-up, stabilization, and ramp-down scenarios in both CO2 emissions and freshwater input. Experiment group B complements this idealized set by using historical climate simulations and projections for 1850–2100, incorporating realistic estimates of Greenland Ice Sheet melt based on observations for the historical period and ice-sheet model projections for the future. Experiment group C extends the existing North Atlantic Hosing Model Intercomparison Project (NAHosMIP) by applying large freshwater perturbations to both control and 2 °C-warming simulations to assess how global warming influences AMOC reversibility. Finally, experiment group D imposes freshwater inputs, consistent with those inferred for the 8.2 kyr before present event, under pre-industrial conditions, in order to constrain model sensitivity to freshwater forcing using paleoclimate reconstructions. Together, these coordinated experiments will allow systematic evaluation of how different climate models respond to identical freshwater perturbations—an essential step toward better understanding the wide inter-model spread in North Atlantic dynamics and projected future AMOC changes.

Climate models and theoretical evidence show that the ocean drives climate from sub-decadal to centennial timescales through a variety of processes and their interactions. The range of direct climate observations, arelhowever, is too short to understand the exact role of the ocean in shaping observed and future climate variability on top of anthropogenic climate change. In the present study, we use a large set of paleoclimate records combined with a random forest algorithm to reconstruct a gridded dataset of sea surface temperatures since 850 C.E. to provide a better framework for the study of ocean surface variability. In line with modeling and paleodata studies, our reconstruction suggests that natural climate forcings have importantly influenced the last millennium climate variability. Our reconstruction also suggests that North Atlantic SST multidecadal variability influences Pacific SST on decadal timescales. However, the latter result is shown to be strongly dependent on background climate conditions. This new reconstruction offers a useful resource for testing the capabilities of climate models to reproduce the linkages between Atlantic and Pacific as well as the response to external forcings.

Vertical velocities at large scales are crucial for understanding ocean dynamics, influencing large-scale circulation and associated biochemical processes, yet their rationale is poorly understood, and their three-dimensional mean distribution and temporal variability are mainly known by models. This paper introduces OLIV3 (Observation-based LInear Vorticity Vertical Velocities), a novel observation-based estimation product of vertical velocities over the global thermocline. This product relies on the geostrophic linear vorticity balance (LVB) applied to ARMOR3D observation-based meridional velocities with ERA5 Ekman pumping vertical velocity as surface boundary condition. It covers the water column over 71 isopycnal levels, with 1/4 degrees horizontal resolution at annual frequency during the 1993-2019 period. Since the geostrophic LVB-derived vertical velocities only capture the geostrophic component of the vertical velocity, their performance is tested using ocean general circulation model (OGCM) data against the total vertical flow. In the thermocline, the LVB accurately reproduces the interannual variability and captures the climatology of the large-scale total vertical flow (horizontal scales larger than 5 degrees) with errors below 50 % across the major ocean gyres. Focusing on surface-thermocline exchanges, one of the most common applications that needs vertical velocities, OGCM results indicates that baroclinic geostrophic vertical velocities are largely more accurate than the classic Ekman pumping proxy at estimating the interannual variability of the total vertical flow in the ocean interior. OLIV3 capability to estimate real ocean vertical velocities is assessed against three reference datasets: two reanalyses and the observation-based product OMEGA3D. A strong spatial and temporal correlation is evidenced between OLIV3 and reanalysis datasets, in contrast to the OMEGA3D, demonstrating even higher correlation than within themselves and supporting the dominance of the geostrophic component of interannual variability of vertical movements. OLIV3 also reconstructs a baroclinic vertical velocity field, consistent with the basin oceanographic concept of Sverdrup balance theory. By building on theoretical advances made since the introduction of Sverdrup and Ekman transport theories, OLIV3 provides a simplified yet physically consistent estimate of large-scale vertical transport. The OLIV3 dataset developed in this study is available at 10.5281/zenodo.16962780 .

This study compares two generations of the IPSL-EPOC decadal climate prediction system based on the IPSL-CM6A-LR Earth System Model, focusing on differences in ocean data assimilation. The first configuration (DCP1), developed for CMIP6-DCPP, is carbon concentration-driven, while the second (DCP2), operational since 2023 under the World Meteorological Organization (WMO), incorporates updated observations and a fully interactive carbon cycle. Both systems assimilate sea surface temperature (SST) and salinity (SSS), but differ in data sources and spatial coverage: DCP1 uses the Atlantic-focused Reverdin dataset, whereas DCP2 relies on the global EN4 dataset with climatological filling in data-sparse regions. Over the common 1980–2014 period, DCP2 improves SST and SSS initialization and enhances predictive skill, particularly for ocean temperatures during the first five forecast years. Improvements are most evident in the North Atlantic, tropical Pacific, and Southern Ocean. However, skill declines beyond 5 years, especially for large-scale indices such as the Atlantic Multidecadal Variability (AMV). This loss of skill is partly linked to the use of climatological SSS in EN4 in gridpoints where observations are missing, which appears to damp ocean variability, reduce deep-water variability, and limit fluctuations of the Atlantic Meridional Overturning Circulation (AMOC). These results highlight the need for careful treatment of sparse observational data in decadal prediction systems to preserve the low-frequency variability of ocean circulation.

Although net negative emissions of carbon dioxide (CO2) are essential to meet climate targets, little is known about how declining atmospheric CO2 levels will affect ocean acidification. Here, by analysing the acidity ([H+]) and corrosivity to aragonite (ΩArag) in eight Earth system models that made simulations under rising then falling CO2 levels, we identify the Arctic as a hotspot for delayed reversibility of ocean acidification. Under falling CO2, Arctic surface waters remain comparatively more acidic, and aragonite-corrosive conditions (ΩArag < 1) persist until atmospheric CO2 drops ~120 ppm below the threshold at which they first appeared under rising CO2. This hysteresis arises from the erosion of the natural surface-layer deficit in dissolved inorganic carbon, initially maintained by sea ice limiting air–sea gas exchange and not fully restored as sea ice recovers during CO2 decline. Thus, the Arctic Ocean experiences not only the greatest acidification but also the most delayed benefits from negative emissions. Changes in the Earth system may persist long after atmospheric CO2 levels decline. This study examines ocean acidification and how it will persist in ocean regions globally, with the Arctic identified as the area that experiences relief from acidification the latest under negative emissions.

Attributing atmospheric carbon dioxide (CO2) growth to anthropogenic emissions in the presence of natural climate variability, both in the past and in the near future, is critical for assessing the impact of climate policies on the Earth system toward establishing early warnings for the carbon cycle and climate extremes. Using ensemble simulations from six novel prediction systems based on Earth system models (ESMs), we investigate reconstructions and predictions of the CO2 fluxes and atmospheric CO2 growth. These systems enable predictions of atmospheric CO2 growth variations in response to air-sea and air-land CO2 fluxes via activating the interactive carbon cycle, which is missing in the conventional decadal prediction systems with prescribed atmospheric CO2 concentration. The reconstructions from assimilation runs, integrating physical atmosphere and ocean data products, reproduce the annual mean observed variations in the CO2 fluxes and atmospheric CO2 growth to a large degree. The emission-driven prediction systems show predictive skill for up to 2 years for the air-land CO2 fluxes and atmospheric CO2 growth, while the air-sea CO2 fluxes have higher skill for up to 5 years, indicating that the predictive skill of atmospheric CO2 growth is limited by the air-land CO2 fluxes. While predictions of air-land CO2 fluxes are linearly linked to El Ni & ntilde;o-Southern Oscillation (ENSO), predictions of air-sea CO2 fluxes are less so. The ESMs' ability to predict variations in CO2 fluxes regardless of their linear relationship with ENSO merits further study of the mechanisms regulating the predictive skill toward improving our predictive capability in a closed Earth system. SIGNIFICANCE STATEMENT: This study aims to reconstruct variations in carbon dioxide (CO2) fluxes and atmospheric CO2 growth over the past decades and predict the changes in the next years. This has urgent implications for informing decarbonization and climate mitigation policy, as the global carbon cycle is affected by anthropogenic CO2 emissions and interacts with the changing climate. Six novel prediction systems based on Earth system models (ESMs) provide comprehensive carbon cycle estimates within a closed budget while enabling process-based attribution of the variations. We demonstrate that these initialized ESMs can predict the variations in atmospheric CO2 growth for 2 years. The outcomes have recently contributed to the Global Carbon Budget annual updates and the World Meteorological Organization Lead Centre for Annual-to-Decadal Climate Prediction.

Decadal prediction of the North Atlantic Oscillation (NAO) is essential for developing decadal climate services and improving climate forecasts across the North Atlantic region. However, extracting robust predictive skill at these timescales remains challenging due to internal variability and ensemble limitations. Here, we introduce an innovative postprocessing framework called temporally aligned averaging (TAA) that substantially enhances the prediction skill of the winter NAO, increasing the explained variance from 34 to 69% over 1961-2023, and providing reliable forecasts even for short-term (4 to 5 years) averages. Combined with a subsampling strategy that fully exploits large ensembles from a single model to circumvent inconsistencies and biases arising from multimodel mixtures, the TAA method notably strengthens decadal precipitation forecasts, enhancing its explained variance from 16 to 54% over Scandinavia and from 1 to 58% over the Mediterranean basin. This substantial advancement in decadal forecasting could have broad implications for various sectors by improving climate risk assessments and adaptation strategies.

The imperative to comprehend and forecast global carbon cycle variations in response to climate variability and change over recent decades and in the near future underscores its critical role in informing the global stocktaking process. Our study investigates CO2 fluxes and atmospheric CO2 growth through ensemble decadal prediction simulations using Earth System Models (ESMs) driven by CO2 emissions with an interactive carbon cycle. These prediction systems provide valuable insights into the global carbon cycle and, therefore, the variations in atmospheric CO2. Assimilative ESMs with interactive carbon cycles effectively reconstruct and predict atmospheric CO2 and carbon sink evolution. The emission-driven prediction systems maintain comparable skills to conventional concentration-driven methods, predicting 2-year accuracy for air-land CO2 fluxes and atmospheric CO2 growth, with air-sea CO2 fluxes exhibiting higher skill for up to 5 years. Our multi-model predictions for the next year, along with assimilation reconstructions, for the first time contribute to the Global Carbon Budget 2023 assessment. We plan regular updates and the involvement of more ESMs in future assessments. Ongoing efforts include implementing seasonal-scale predictions for skill improvement. Furthermore, we assess uncertainty contributions to CO2 flux and growth predictions, revealing the comparable impacts of internal climate variability and diverse model responses, particularly at a lead time of 1-2 years. Notably, the effect of CO2 emission forcing rivals internal variability at a 1-year lead time. Large uncertainties in CO2 responses to initial states of ENSO are observed, stemming from both model responses and internal variability. The challenge lies in addressing the scarcity and uncertainty of data for initialization and obtaining precise external forcings to enhance the reliability of predictions. The further advancements involve not only addressing comprehensive bias correction but also implementing statistical methods to enhance dynamical predictions.

The ongoing rapid decline in Arctic sea ice is considered as a tipping element of our climate system. It is exposing a warmer and more acidified ocean directly to the atmosphere, permitting greater light penetration and enhanced exchange of heat, momentum, and gases across the air-sea interface. Earth system models project that these thermal and biogeochemical changes will dramatically perturb Arctic Ocean carbonate chemistry. As one of the consequences, the projections indicate that the seasonal maximum in surface ocean pCO2 generally shifts from winter to summer during this century. Yet, it is unknown whether such biogeochemical changes in the Arctic would be reversible, if we managed to reduce atmospheric carbon dioxide concentrations. Here we analyse the reversibility of Arctic biogeochemistry changes using idealised 1pctCO2-cdr simulations from six earth system models. These model experiments simulate a 140-year period of 1% annual atmospheric CO2 increase (rampup to 4x preindustrial levels), followed by a 140-year period of 1% annual CO2 decrease (rampdown). Our results indicate that the present day pCO2 cycle is largely recovered when atmospheric CO2 returns to preindustrial levels. However, most models exhibit substantial hysteresis, particularly during summer, where surface ocean pCO2 remains more elevated during the rampdown phase relative to the rampup phase (difference in Arctic average up to 60 𝜇atm pCO2 for the same atmospheric CO2 levels). Despite model differences, their projections consistently show pronounced regional variability in the pCO2 hysteresis, with high hysteresis occurring for example in the Nordic Seas and the Barents Sea. Our results indicate that the pCO2 hysteresis is particularly sensitive to sea surface temperature and net primary productivity, both of which show regionally varying hysteresis as well. These findings underscore the complex impacts of Arctic sea ice loss on biogeochemical cycles, emphasising the importance of accounting for hysteresis in CO2 overshoot scenarios and climate mitigation strategies.

Abstract Understanding internal variability of the climate system is critical when isolating internal and anthropogenically forced signals. Here, we investigate the modes of Atlantic Meridional Overturning Circulation (AMOC) variability using perturbation experiments with the Institut Pierre‐Simon Laplace's (IPSL) coupled model and compare them to Coupled Model Intercomparison Project Phase 6 (CMIP6) pre‐industrial control simulations. We identify two characteristic modes of variability—decadal‐to‐multidecadal (DMDvar) and centennial (CENvar). The former is driven largely by temperature anomalies in the subpolar North Atlantic, while the latter is driven by salinity in the western subpolar North Atlantic. The amplitude of each mode scales linearly with the mean AMOC strength in the IPSL experiments. The DMDvar amplitude correlates well with the AMOC mean strength across CMIP6 models, while the CENvar mode does not. These findings suggest that the strength of DMDvar depends robustly on the North Atlantic mean state, while the CENvar mode may be model‐dependent.

Abstract The Canary current upwelling System (CCS) is one the most productive marine ecosystems. CMIP5 simulations under the RCP8.5 scenario for the end of the 21st century project a modest upwelling‐favorable wind decrease over the CCS southern outpost, that is, the southern senegalese upwelling center (SSUC). We explore the coastal‐scale physical manifestations of climate change in the SSUC through dynamical downscaling of projected changes from nine CMIP5 models selected for their realistic representation of present‐day thermohaline structure. We find that coastal upwelling reduction due to wind changes is projected to be aggravated by geostrophic/pressure adjustments related, in large part, to changes in upper ocean stratification. The reduction could reach 25% of present‐day upwelling rates. The intensity of the poleward boundary current offshore of the SSUC is projected to decrease. Together with upper ocean warming this opens vast possibilities of ecological evolutions with large impact on neighboring societies.

Atlantic multidecadal variability (AMV) significantly impacts regional and global climate, as evidenced by observations and climate model simulations. Previous sensitivity experiments investigating the AMV were mostly based on climate model simulations in which the North Atlantic sea surface temperatures (NASSTs) were nudged to a fixed AMV pattern. Here, the global influence of AMV is explored using an ensemble of pacemaker experiments where NASSTs are nudged to the time-varying observational records. Ten ensemble members proved sufficient to distinguish forced signals from internal climate variability. Using high-pass-filtered data to inform how the response to the AMV is established, we confirm that the AMV primarily affects the global ocean through its tropical component. The oceanic response to a warm AMV anomaly unfolds in four phases: 1) warming of the western Pacific warm pool and development of anomalous easterlies in the western Indo-Pacific driven by diabatic heating over the tropical Atlantic within the first 6 months, 2) eastward propagation of equatorial thermocline anomalies and establishment of La Ni & ntilde;a-like conditions in the eastern Pacific after 7-10 months, 3) persistence of La Ni & ntilde;a conditions during 11-20 months via Bjerknes feedback and weakening of the Aleutian low through tropical teleconnections, and 4) emergence of a negative Pacific decadal oscillation pattern in the North Pacific after 21-25 months. Our findings highlight the importance of using time-varying SST observations in pacemaker experiments to capture the full complexity of interbasin connections.

The future changes in Sahel precipitation have significant societal implications. Yet, the projections in Sahel precipitation remain highly uncertain, partly due to strong differences across climate models in projected sea surface temperature (SST) and its effects on the atmospheric circulation. This study investigates the effects of North Atlantic and Mediterranean SST changes on future Sahel precipitation through sensitivity experiments conducted with three atmospheric models. We confirm that the warming of the North Atlantic and the Mediterranean SSTs is one of the main reasons for the discrepancies between climate model projections of Sahel precipitation. Warming in the North Atlantic and Mediterranean enhances the monsoon circulation and increases precipitation over the Sahel, primarily through dynamical effects driven by energy gradients. At the same time, we identify non-linear responses to the Atlantic warming and substantial differences between the results of each model. Thus, reducing uncertainty in Sahel precipitation projections calls for improved understanding of two issues: first, Northern Hemisphere SST changes and their representation in climate models, and second, their effects on Sahel precipitation. Additionally, we find that uncertainty in future SST changes contributes to uncertainty in high-impact weather events.

Previous studies agree on an impact of the Atlantic multidecadal variability (AMV) on the total seasonal rainfall amounts over the Sahel. However, whether and how the AMV affects the distribution of rainfall or the timing of the West African monsoon is not well known. Here we seek to explore these impacts by analyzing daily rainfall outputs from climate model simulations with an idealized AMV forcing imposed in the North Atlantic, which is representative of the observed one. The setup follows a protocol largely consistent with the one proposed by the Component C of the Decadal Climate Prediction Project (DCPP-C). We start by evaluating model's performance in simulating precipitation, showing that models underestimate it over the Sahel, where the mean intensity is consistently smaller than observations. Conversely, models overestimate precipitation over the Guinea coast, where too many rainy days are simulated. In addition, most models underestimate the average length of the rainy season over the Sahel; some are due to a monsoon onset that is too late and others due to a cessation that is too early. In response to a persistent positive AMV pattern, models show an enhancement in total summer rainfall over continental West Africa, including the Sahel. Under a positive AMV phase, the number of wet days and the intensity of daily rainfall events are also enhanced over the Sahel. The former explains most of the changes in seasonal rainfall in the northern fringe, while the latter is more relevant in the southern region, where higher rainfall anomalies occur. This dominance is connected to the changes in the number of days per type of event; the frequency of both moderate and heavy events increases over the Sahel's northern fringe. Conversely, over the southern limit, it is mostly the frequency of heavy events which is enhanced, thus affecting the mean rainfall intensity there. Extreme rainfall events are also enhanced over the whole Sahel in response to a positive phase of the AMV. Over the Sahel, models with stronger negative biases in rainfall amounts compared to observations show weaker changes in response to AMV, suggesting that systematic biases could affect the simulated responses. The monsoon onset over the Sahel shows no clear response to AMV, while the demise tends to be delayed, and the overall length of the monsoon season enhanced between 2 and 5 d with the positive AMV pattern. The effect of AMV on the seasonality of the monsoon is more consistent to the west of 10∘ W, with all models showing a statistically significant earlier onset, later demise, and enhanced monsoon season with the positive phase of the AMV. Our results suggest a potential for the decadal prediction of changes in the intraseasonal characteristics of rainfall over the Sahel, including the occurrence of extreme events.

The Sahel is one of the most vulnerable regions to climate change. Robust estimation of future changes in the Sahel monsoon is therefore essential for effective climate change adaptation. Unfortunately, state-of-the-art climate models show large uncertainties in their projections of Sahel rainfall. In this study, we use 32 models from CMIP6 to iden-tify the sources of this large intermodel spread of Sahel rainfall. By using maximum covariance analysis, we first highlight two new key drivers of this spread during boreal summer: the interhemispheric temperature gradient and equatorial Pacific sea surface temperature (SST) changes. This contrasts with previous studies, which have focused mainly on the Northern Hemisphere rather than the global scale, and in which the Pacific Ocean has been neglected in favor of the Atlantic. Next, we unravel the physical mechanisms behind these statistical relationships. First, the modulation of the interhemispheric temperature gradient across the models leads to varying latitudinal positions of the intertropical convergence zone and, consequently, varying Sahel rainfall intensity. Second, models that exhibit less warming than the multimodel mean in the equatorial Pacific, thereby projecting a less "El Nino-like" mean state, simulate enhanced precipitation over the central Sahel in the future through modulations of the Walker circulation, the tropical easterly jet, the meridional tropospheric temperature gradient, and hence regional zonal wind shear. Finally, we show that these two indices collectively explain 62% of Sahel rainfall change uncertainty: 40% due to the interhemispheric temperature gradient and 22% through equato-rial Pacific SST.