The inter-model spread in future West African monsoon rainfall under high-emission scenarios remains large due to climate model biases in large-scale circulation. Here, we develop a physics-guided artificial neural network (ANN) to constrain a subset of CMIP6 precipitation projections using sea-level pressure patterns from the Sahelian monsoon ocean-pressure index (SMOPI). Model-specific ANNs are trained to learn nonlinear SMOPI-related circulation patterns and precipitation relationships under an amplitude-preserving constraint. The physical realism of these learned teleconnections is evaluated against JRA-55 reanalysis to construct a performance-based weighted ensemble. This approach reduces end-of-century inter-model spread by 20% in high-skill models, 33% in lower-skill models, and 30% across the full ensemble. It shifts the spread budget toward models reproducing observed teleconnections by up-weighting physically consistent models and down-weighting less reliable ones without collapsing ensemble diversity. This physics-weighted deep-learning architecture delivers more coherent projections and offers computationally affordable pathways to robust climate information in data-limited regions. This study introduces a physics-guided artificial neural network to constrain CMIP6 inter-model spread in West African monsoon precipitation projections, which is achieved by assigning higher weights to physically consistent models and lower weights to less reliable ones without collapsing ensemble diversity.

In its pursuit of a leadership role in climate service (CS) development and uptake, the European Union (EU) has invested in numerous innovation initiatives that have significantly advanced the field. Still, efforts to promote broader uptake are fragmented, which underscores the need for a more systematic approach to stimulate upscaling. Upscaling CSs—the process of transferring, replicating, extending and/or institutionalising CSs in new contexts, thereby increasing the value of services by enhancing impact and adaptation outcomes— presents both theoretical and practical challenges. This perspective article explores the challenge of upscaling CSs and the benefits of a nuanced understanding of contexts in which such services may be expanded. Collaboration between diverse actors—including developers, intermediaries, and users—is recommended within the upscaling process. Against this backdrop, we propose a framework to orient (1) horizontal upscaling (replication to new audiences), (2) vertical upscaling (institutional changes) and (3) functional upscaling (adding functions and/or content). This framework is structured around four guiding questions: ‘why’—to uncover the rationale for upscaling CS, the specific benefits and opportunities; ‘what’—to consider specific components valued and/or demanded to be upscaled; ‘who’ − to consider those involved in the process; and ‘how’—to explore practices and opportunities. We substantiate the suggested framework with a select few real-life CS examples, as well as illustrating hypothetical examples. We propose that adopting an upscaling framework informed by the viewpoints outlined here can help EU‑sponsored initiatives enhance the strategic impact of climate‑service investments and, in turn, improve long‑term climate resilience and adaptation.This article results from a cross-project Thematic Working Group promoted by the EU Mission on Climate Adaptation, fostering the exchange and discussion between 39 different EU projects involving CSs.

Climate change is often connected to an increase in weather extreme frequencies and severity, demanding an increased necessity in mitigating greenhouse gas emissions, adapting to and building resilience to these changes and impacts. This happens in a background of climate variability that already impacts several climate-sensitive sectors. There is an urgent need for fit-for-purpose climate services and service professionals to support these mitigation and adaptation efforts. Co-development of climate services can enhance their usefulness (context-specific and fit for purpose), usability (easy access and handling), and usage (transfer and upscale) by ensuring appropriate and iterative engagement between climate service providers and users, development of timely, reliable and usable products, and the provision of services to users in a truly accessible manner. Achieving co-development asks for reframing and scaled-up transdisciplinary, sustained, and multidirectional approaches between a diversity of information users and providers. For these processes, it is key to also address and further minimize or overcome barriers of co-production, while supporting enabling and accelerating mechanisms, better preparation of climate services providers including National Meteorological and Hydrological Services, private actors, civil society, and academia for interdisciplinary and transdisciplinary work, enhanced individual and institutional capacity development and governance mechanisms.

Knowledge of the functioning of the climate system, including the physical, dynamical and biogeochemical feedback processes expected to occur in response to anthropogenic climate forcing, has increased substantially over recent decades. Today, climate science is at a crossroads, with new and urgent demands arising from the needs of society to deal with future climate change, and the need for the climate science community to refine its strategic goals to meet these demands rapidly. All possible—but currently unknown—worlds in 2050, with a larger global population, unprecedented climate conditions with higher temperatures, more frequent extreme weather events, sea level rise, disrupted ecosystems, changes in habitability and increased climate-induced displacement and migration, and the emergence of new geopolitical tensions, will require limiting society’s vulnerability both through mitigation measures to minimize further warming and through the implementation of innovative adaptation initiatives. The development of a skillful climate information system, based on the most advanced Earth system science, will be required to inform decision-makers and the public around the world about the local and remote impacts of climate change, and guide them in optimizing their adaptation and mitigation agendas. This information will also help manage renewable resources in a warmer world and strengthen resilience to the expected interconnected impacts of climate change. In this paper, we summarize the major advances needed to understand the multiscale dynamics of the Earth system. We highlight the need to develop an integrated information system accessible to decision-makers and citizens in all parts of the world, and present some of the key scientific questions that need to be addressed to inform decisions on mitigation and adaptation. Finally, we speculate about the values and ethics of climate science and the nature of climate research in a world that will be increasingly affected by global warming in a geopolitical context very different from that of recent decades.

This paper introduces REMO2020, a modernised version of the well-known and widely used REgional climate MOdel (REMO). REMO2020 has undergone fundamental changes in its code structure to provide a more modular, operationally focused design, facilitating the inclusion of new components and updates. Here, we describe the default configuration of REMO2020, which includes the following updates compared to the previous version, REMO2015: (i) the FLake lake model, (ii) a state-of-the-art MACv2-SP aerosol climatology, (iii) a newly developed three-layer snow module, (iv) a prognostic precipitation scheme, (v) an updated time filter, and (vi) a new tuning approach. Additionally, we describe some optional modules that can be activated separately, such as the interactive MOsaic-based VEgetation model iMOVE. REMO2020 outperforms its predecessor REMO2015 with regard to nearly all evaluation metrics used to evaluate simulations of Europe's climate. The persistent warm-temperature bias over central Europe and the cold-temperature bias over northern Europe have been significantly reduced in REMO2020. Similarly, the previously modelled dry bias in central Europe has been nearly eliminated, and the extent of the wet bias in eastern Europe has been reduced. The precipitation distribution in REMO2020 is much more realistic, especially in terms of heavy-precipitation extremes. Statistically, REMO2020 aligns better with long-term measurements than with older versions. Mountainous areas still present a challenge in REMO2020, especially with a higher vertical resolution. In this paper, we demonstrate why REMO2020 will be our new model version for future dynamical downscaling activities.

Monitoring Sahelian rainfall variability is increasingly critical as climate extremes intensify across the region. Here, we develop the Sahelian Monsoon Ocean-Pressure Index (SMOPI), a novel global synthetic indicator constructed from five dynamically coherent sea-level pressure regions statistically linked to June-September Sahel monsoon rainfall. SMOPI captures intra-seasonal and interannual variability, and crucially, reflects the influence of both regional processes and large-scale teleconnections on monsoon dynamics. It aligns with the dominant rainfall variability mode in reanalyses and 29 CMIP6 models. Strong/positive SMOPI phases coincide with wet years and are associated with enhanced convergence, favorable jet configurations, and robust Pacific, Atlantic, and Indian Ocean teleconnections. Conversely, weak/negative SMOPI phases correspond to drought conditions and divergent moisture fluxes. SMOPI exposes model failures in reproducing historical droughts and offers new physical insights into rainfall-driving mechanisms. It stands out as a scalable, potentially transferable diagnostic tool for monitoring/forecasting and evaluating Sahelian monsoon rainfall under global warming.

Adaptation options are being implemented globally to reduce the impacts of current and projected climate change. However, there is still limited information on assessments of the options available, especially related to adaptation research and practice in the Global South. Therefore, we present the local feasibility assessment of climate adaptation options as a methodological advancement, using Puerto Moraz & aacute;n's (Nicaragua) agriculture and livestock sectors as proof of concept. For this case study, we complement current frameworks with participatory approaches and local expert knowledge to contextualize global narratives on adaptation feasibility and overcome information availability challenges. As a result, we assess sixteen options across the agriculture and livestock sectors. We demonstrate that, depending on the context, not all dimensions and criteria are equally relevant. In Puerto Moraz & aacute;n, the environmental and economic dimensions were the most important. We also confirm that the assessment of the options varies when local priorities are considered. Our results highlight the importance of the local context when identifying adaptation options. Our expanded assessment framework helps assess and generate evidence from the local level, where information is usually limited. The advanced assessment can guide local and subnational adaptation processes and inform other policy or scientific assessments by identifying the dimensions where there might be barriers to implementing adaptation.

Against the backdrop of populist attacks on science and sustainable development, the Sustainability Science Summit 2025 focused on advancing sustainability transformations. With over 30 sessions structured around three high-level panel discussions, it addressed global challenges in sustainability science, the transformation of research practices, and the science-policy interface.

We review how the international modelling community, encompassing integrated assessment models, global and regional Earth system and climate models, and impact models, has worked together over the past few decades to advance understanding of Earth system change and its impacts on society and the environment and thereby support international climate policy. We go on to recommend a number of priority research areas for the coming decade, a timescale that encompasses a number of newly starting international modelling activities, as well as the IPCC Seventh Assessment Report (AR7) and the second UNFCCC Global Stocktake. Progress in these priority areas will significantly advance our understanding of Earth system change and its impacts, increasing the quality and utility of science support to climate policy.We emphasize the need for continued improvement in our understanding of, and ability to simulate, the coupled Earth system and the impacts of Earth system change. There is an urgent need to investigate plausible pathways and emission scenarios that realize the Paris climate targets - for example, pathways that overshoot 1.5 or 2 degrees C global warming, before returning to these levels at some later date. Earth system models need to be capable of thoroughly assessing such warming overshoots - in particular, the efficacy of mitigation measures, such as negative CO2 emissions, in reducing atmospheric CO2 and driving global cooling. An improved assessment of the long-term consequences of stabilizing climate at 1.5 or 2 degrees C above pre-industrial temperatures is also required. We recommend Earth system models run overshoot scenarios in CO2-emission mode to more fully represent coupled climate-carbon-cycle feedbacks and, wherever possible, interactively simulate other key Earth system phenomena at risk of rapid change during overshoot. Regional downscaling and impact models should use forcing data from these simulations, so impact and regional climate projections cover a more complete range of potential responses to a warming overshoot. An accurate simulation of the observed, historical record remains a fundamental requirement of models, as does accurate simulation of key metrics, such as the effective climate sensitivity and the transient climate response to cumulative carbon emissions. For adaptation, a key demand is improved guidance on potential changes in climate extremes and the modes of variability these extremes develop within. Such improvements will most likely be realized through a combination of increased model resolution, improvement of key model parameterizations, and enhanced representation of important Earth system processes, combined with targeted use of new artificial intelligence (AI) and machine learning (ML) techniques. We propose a deeper collaboration across such efforts over the coming decade.With respect to sampling future uncertainty, increased collaboration between approaches that emphasize large model ensembles and those focussed on statistical emulation is required. We recommend an increased focus on high-impact-low-likelihood (HILL) outcomes - in particular, the risk and consequences of exceeding critical tipping points during a warming overshoot and the potential impacts arising from this. For a comprehensive assessment of the impacts of Earth system change, including impacts arising directly as a result of climate mitigation actions, it is important that spatially detailed, disaggregated information used to generate future scenarios in integrated assessment models be available for use in impact models. Conversely, there is a need to develop methods that enable potential societal responses to projected Earth system change to be incorporated into scenario development.The new models, simulations, data, and scientific advances proposed in this article will not be possible without long-term development and maintenance of a robust, globally connected infrastructure ecosystem. This system must be easily accessible and useable by modelling communities across the world, allowing the global research community to be fully engaged in developing and delivering new scientific knowledge to support international climate policy.

Climate change is unequivocal and mainly human induced, resulting in increased economic, social, and environmental losses and damages. The climate crisis is existential, paramount, and pervasive, and the negative climate impacts are increasing in frequency and intensity. It is therefore of central importance that all countries now join forces to mitigate climate change and to accelerate action for a comprehensive societal transformation toward a climate-neutral and fair world, globally and locally. This must be done on the basis of the best available science and information. Here, climate services on local levels play a tremendous role in bringing together climate change mitigation and adaptation. Especially at the local level, the involvement of people; local know-how; and the knowledge of respective preconditions, concerns, and needs in the development and implementation of climate adaptation concepts (codesign) are indispensable. Our aim must be a climate-resilient development and holistic transformation of the society as postulated by the Intergovernmental Panel on Climate Change (IPCC).

This study examines the future climate change in the South Asia region during 2070–2099 with respect to the historical period (1975–2004) under RCP8.5 scenario using a high-resolution regional earth system model. We found substantial changes in the key climatic parameters over the South Asia region including ocean biological productivity, however, the magnitude of response varies spatially. A substantial increase (> 2.5 °C) in the projected annual-mean sea surface temperature (SST) was found over the Indian Ocean with the highest increase (~ 3.4 °C) locally in the northern part of the Arabian Sea and in the Persian Gulf, SST changes being significant throughout the study area with 95% confidence level. The changes in the sea surface salinity showed strong spatial variability with the highest freshening over northern Bay of Bengal and highest salinity in the Persian Gulf followed by northern Arabian Sea. The amount of annual-mean precipitation will substantially increase over the eastern coast of the Bay of Bengal (up to 1.5–2.0 mm/day) and along the equator in the band 10° S–10° N (0.5–1.5 mm/day), while it will decrease over the western part of the Bay of Bengal and in the northern states of India (− 0.5 to 1.0 mm/day). The most pronounced increase of precipitation rate in the future climate will occur over India (3–5 mm/day) and the eastern coasts of the Bay of Bengal (> 5 mm/day) during the monsoon period, and over the equatorial band (2–3 mm/day) during the post-monsoon period, with all precipitation changes indicated above being significant at 95% confidence level.

There is an urgent need to enhance climate projections for Central Equatorial Africa (CEA), given the region's high vulnerability to climatic hazards and its economy's heavy dependence on climate-sensitive sectors. This study aims to evaluate the performance of the regional earth system model ROM, composed of the atmosphere-only regional climate model (RCM) REMO coupled with the global Max Planck Institute for Meteorology Ocean Model (MPIOM), in reproducing the precipitation climatology over CEA. ROM results are compared to those of REMO in two sets of experiments, one driven by the ERA-Interim reanalysis and the other by the MPI-ESM-LR earth system model (ESM), both at similar to 25-km horizontal resolution. Results show that ocean coupling improves rainfall climatology thanks to a better representation of the physical processes and mechanisms underlying the rainfall system. In particular, an improved sea surface temperature (SST) results in a more realistic simulation of land-atmosphere-ocean interactions, and subsequently the atmospheric baroclinicity. Specifically, the coupling reduces the positive SST bias inherited by the driving ESM across the entire Guinea Gulf and Benguela-Angola coastal seas. This leads to better simulated land-ocean thermal and pressure contrasts. Improvements in land-ocean contrasts, in turn, enhance the representation of the regional atmospheric circulation, and thus precipitation. Interestingly, the coupling is more beneficial when ROM is driven by the ESM than the reanalysis. This study emphasizes the advantage of dynamically downscaling ESMs using regional earth system models rather than atmosphere-only RCMs, with the potential to enhance confidence in future climate projections. Designing timely and relevant societal responses to climate-related impacts and risks to humans and natural systems requires reliable information about climate variability and projected change, especially at regional scales. For this purpose, considerable efforts were devoted to the improvement of the numerical models used to represent the climate system, including better formulation of the models' physical and dynamical components and the inclusion of feedback between different components of the climate systems, such as those between the ocean and the atmosphere. In this study we aim at investigating whether the use of a regional climate model which includes an explicit representation (coupling) of the ocean is able to better simulate (i.e., adds value) the main mechanisms responsible for precipitation over Central Equatorial Africa. The results show that the coupled model is indeed able to simulate more realistically the complex physical processes and mechanisms underpinning the rainfall system. Our findings advocate for the use of the global ocean-regional atmosphere coupling approach for regional climate change projection analyses. The global ocean-regional atmosphere coupling improves the rainfall climatology compared to its atmosphere-only counterpart model The added value resulting from the coupling is plausible, as associated with improvements in the processes underpinning the rainfall system The added value is modulated by the boundary conditions, with better suitability under the imperfect forcing mode

Abstract. We review how the international modelling community, encompassing Integrated Assessment models, global and regional Earth system and climate models, and impact models, have worked together over the past few decades, to advance understanding of Earth system change and its impacts on society and the environment, and support international climate policy. We then recommend a number of priority research areas for the coming ~6 years (i.e. until ~2030), a timescale that matches a number of newly starting international modelling activities and encompasses the IPCC 7th Assessment Report (AR7) and the 2nd UNFCCC Global Stocktake. Progress in these areas will significantly advance our understanding of Earth system change and its impacts and increase the quality and utility of science support to climate policy. We emphasize the need for continued improvement in our understanding of, and ability to simulate, the coupled Earth system and the impacts of Earth system change. There is an urgent need to investigate plausible pathways and emission scenarios that realize the Paris Climate Targets, including pathways that overshoot the 1.5 °C and 2 °C targets, before later returning to them. Earth System models (ESMs) need to be capable of thoroughly assessing such warming overshoots, in particular, the efficacy of negative CO2 emission actions in reducing atmospheric CO2 and driving global cooling. An improved assessment of the long-term consequences of stabilizing climate at 1.5 °C or 2 °C above pre-industrial temperatures is also required. We recommend ESMs run overshoot scenarios in CO2-emission mode, to more fully represent coupled climate - carbon cycle feedbacks. Regional downscaling and impact models should also use forcing data from these simulations, so impact and regional climate projections are as realistic as possible. An accurate simulation of the observed record remains a key requirement of models, as does accurate simulation of key metrics, such as the Effective Climate Sensitivity. For adaptation, improved guidance on potential changes in climate extremes and the modes of variability these extremes develop in, is a key demand. Such improvements will most likely be realized through a combination of increased model resolution and improvement of key parameterizations. We propose a deeper collaboration across modelling efforts targeting increased process realism and coupling, enhanced model resolution, parameterization improvement, and data-driven Machine Learning methods. With respect to sampling future uncertainty, increased collaboration between approaches that emphasize large model ensembles and those focussed on statistical emulation is required. We recommend increased attention is paid to High Impact Low Likelihood (HILL) outcomes. In particular, the risk and consequences of exceeding critical tipping points during a warming overshoot. For a comprehensive assessment of the impacts of Earth system change, including impacts arising directly from specific mitigation actions, it is important detailed, disaggregated information from the Integrated Assessment Models (IAMs) used to generate future scenarios is available to impact models. Conversely, methods need to be developed to incorporate potential future societal responses to the impacts of Earth system change into scenario development. Finally, the new models, simulations, data, and scientific advances, proposed in this article will not be possible without long-term development and maintenance of a robust, globally connected infrastructure ecosystem. This system must be easily accessible and useable across all modelling communities and across the world, allowing the global research community to be fully engaged in developing and delivering new scientific knowledge to support international climate policy.

The World Climate Research Programme (WCRP) envisions a future where actionable climate information is universally accessible, supporting decision makers in preparing for and responding to climate change. In this perspective, we advocate for enhancing links between climate science and decision-making through a better and more decision-relevant understanding of climate impacts. The proposed framework comprises three pillars: climate science, impact science, and decision-making, focusing on generating seamless climate information from sub-seasonal, seasonal, decadal to century timescales informed by observed climate events and their impacts. The link between climate science and decision-making has strengthened in recent years, partly owing to undeniable impacts arising from disastrous weather extremes. Enhancing decision-relevant understanding involves utilizing lessons from past extreme events and implementing impact-based early warning systems to improve resilience. Integrated risk assessment and management require a comprehensive approach that encompasses good knowledge about possible impacts, hazard identification, monitoring, and communication of risks while acknowledging uncertainties inherent in climate predictions and projections, but not letting the uncertainty lead to decision paralysis. The importance of data accessibility, especially in the Global South, underscores the need for better coordination and resource allocation. Strategic frameworks should aim to enhance impact-related and open-access climate services around the world. Continuous improvements in predictive modeling and observational data are critical, as is ensuring that climate science remains relevant to decision makers locally and globally. Ultimately, fostering stronger collaborations and dedicated investments to process and tailor climate data will enhance societal preparedness, enabling communities to navigate the complexities of a changing climate effectively.

With the amendment to the German Climate Change Act in 2021, the Federal Government of Germany has set the target to become greenhouse gas neutral by 2045. Reaching this ambitious target requires multisectoral efforts, which in turn calls for interdisciplinary collaboration: the Net-Zero-2050 project of the Helmholtz Climate Initiative serves as an example of successful, interdisciplinary collaboration with the aim of producing valuable recommendations for action to achieve net-zero CO2 emissions in Germany. To this end, we applied an interdisciplinary approach to combining comprehensive research results from ten German national research centers in the context of carbon neutrality in Germany. In this paper, we present our approach and the method behind the interdisciplinary storylines development, which enabled us to create a common framework between different carbon dioxide removal and avoidance methods and the bigger carbon neutrality context. Thus, the research findings are aggregated into narratives: the two complementary storylines focus on technologies for net-zero CO2 emissions and on different framing conditions for implementing net-zero CO2 measures. Moreover, we outline the Net-Zero-2050 results emerging from the two storylines by presenting the resulting narratives in the context of carbon neutrality in Germany. Aiming at creating insights into how complementary and related expertise can be combined in teams across disciplines, we conclude with the project’s lessons learned. This paper sheds light on how to facilitate cooperation between different science disciplines with the purpose of preparing joint research results that can be communicated to a specific audience. Additionally, it provides further evidence that interdisciplinary and diverse research teams are an essential factor for defining solution spaces for complex, interdisciplinary problems.

The Coordinated Regional Downscaling Experiment (CORDEX) is a coordinated international activity that has produced ensembles of regional climate simulations with domains that cover all land areas of the world. These ensembles are used by a wide range of practitioners that include the scientific community, policymakers, and stakeholders from the public and private sectors. They also provide the scientific basis for the Intergovernmental Panel on Climate Change-Assessment Reports. As its next phase now launches, the CMIP6-CORDEX datasets are expected to populate community repositories over the next couple of years, with updated state-of-the-art regional climate data that will further support national and regional communities and inform their climate adaptation and mitigation strategies. The protocol presented here focuses on the European domain (EURO-CORDEX). It takes the international CORDEX protocol covering all 14 global domains as its template. However, it expands on the international protocol in specific areas; incorporates historical and projected aerosol trends into the regional models in a consistent way with CMIP6 global climate models, to allow for a better comparison of global versus regional trends; produces more climate variables to better support sectorial climate impact assessments; and takes into account the recent scientific developments addressed in the CORDEX Flagship Pilot Studies, enabling a better assessment of processes and phenomena relevant to regional climate (e.g., land-use change, aerosol, convection, and urban environment). Here, we summarize the scientific analysis which led to the new simulation protocol and highlight the improvements we expect in the new generation regional climate ensemble. SIGNIFICANCE STATEMENT: As climate change affects all aspects of human life, it is imperative to have access to high-quality state-of-the-art regional climate data in order to serve emergent societal needs. A high level of coordination and a design protocol are required, when large climate model datasets are produced, with the aim to be used by a broader community of scientists and stakeholders. In this work, we present the framework within which the next generation of regional climate model simulations over Europe will be produced. We provide the relevant scientific background, underlying the decisions taken to form the protocol and the improvements we expect in comparison with the previous data repository. This work aims to provide valuable information and guidance to the users of regional climate data produced within the European Coordinated Regional Downscaling Experiment (EURO-CORDEX).

This study explores the added value (AV) of a regional Earth system model (ESM) compared to an atmosphere- only regional climate model (RCM) in simulating West African monsoon (WAM) rainfall. The primary goals are to foster discussions on the suitability of coupled RCMs for WAM projections and deepen our understanding of ocean- atmosphere coupling's influence fl uence on the WAM system. The study employs results from dynamical downscaling of the ERA-Interim reanalysis and Max Plank Institute ESM, low resolution (MPI-ESM-LR), by two RCMs, atmosphere only (REMO) and REMO coupled with Max Planck Institute Ocean Model (MPIOM) (ROM), at ; 25-km horizontal resolution. Results show that in regions distant from coupling domain boundaries such as West Africa (WA), constraint conditions from ERA-Interim are more beneficial fi cial than coupling effects. REMO, reliant on oceanic sea surface temperatures (SSTs) from observations and influenced fl uenced by ERA-Interim, is biased under coupling conditions, although coupling offers potential advantages in representing heat and mass fl uxes. Contrastingly, as intended, coupling improves SSTs and monsoon fl uxes' relationships under ESM-forced conditions. In this latter case, the coupling features a dipole-like spatial structure of AV, improving precipitation over the Guinea Coast but degrading precipitation over half of the Sahel. Our extensive examination of physical processes and mechanisms underpinning the WAM system supports the plausibility of AV. Additionally, we found that the monsoonal dynamics over the ocean respond to convective activity, with the Sahara- Sahel surface temperature gradient serving as the maintenance mechanism. While further efforts are needed to enhance the coupled RCM, we advocate for its use in the context of WAM rainfall forecasts and projections.

Climate change risk assessment is a major topic of current research, with an increasing number of publications appearing annually that project changes in indicators of climate risk to particular sectors of the economy or elements of the natural world, at a wide range of scales ranging from global to local.The increase in risk-related research is also aligned with the need created by the Paris Agreement (PA) (UNFCCC 2015), which aims to constrain global temperature rise to 'well below 2 °C' and to 'pursue efforts' to limit this warming to 1.5 °C above pre-industrial levels.The Intergovernmental Panel on Climate Change (IPCC) highlighted the need for more research aligned to the PA and the related risks in its Special Report on the 1.5 °C of global warming (IPCC 2018).However, typically, each study utilises its own selected climate change and socioeconomic scenarios to describe the future.It may apply its own selected method of downscaling socioeconomic and/or climate change scenarios to the appropriate scale for the assessment in question, and may, or may not, encapsulate the implications of uncertainties in regional climate projection.Finally, risks are usually projected using a single model that is deemed most appropriate for the risk in question, and such models may be either processbased or empirical.Owing to the diversity of approaches, the research community organised model inter-comparison projects (MIPS) in order to assess global-scale indicators of various climate-related risks in a consistent manner.These include AgMIP (Rosenzweig et al. 2013), WaterMIP (Haddeland et al. 2014), and ISIMIP (Frieler et al. 2017), which conduct regular organised harmonised assessments of future risk which have standard procedures for exploration of uncertainties associated with climate projections.However, at the national scale, countries tend to conduct their own independent risk assessments (e.g.,

To manage Earth in the Anthropocene, new tools, new institutions, and new forms of international cooperation will be required. Earth Virtualization Engines is proposed as an international federation of centers of excellence to empower all people to respond to the immense and urgent challenges posed by climate change.