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1.1.1 Overall objective

The overall objective of CHORALE is to make the representation of the continental water cycle, and of its coupling with energy, vegetation and carbon, a reliable component of Earth system models (ESMs) — reliable enough to establish where water constrains the climate response, and where it limits the land-based mitigation and adaptation options built upon it, with the physical credibility that climate projections, scientific assessments and cross-sectoral decision-making require. Meeting the objective serves all three expected outcomes of the topic: reduced uncertainty in global and regional climate projections, closure of an Earth system science gap identified by IPCC AR6 and subsequent authoritative sources, and new evidence relevant to policy and to inform evidence-based climate policies and implementation (Figure 1.1).

1.1.2 Specific objectives

CHORALE pursues six interlinked objectives, each assigned to work packages, deliverables and milestones. O1–O2 deliver model developments and observational constraints; O3 delivers the coordinated simulations; O4–O5 produce assessment-relevant evidence; and O6 supports uptake by assessment, policy and decision-making communities.

Figure 1.1: CHORALE at a glance. Water-limited regions are shaped by the water–vegetation–carbon, land–atmosphere and water–energy couplings and their feedbacks (top left). CHORALE enhances the structural and scale-aware representation of hydrology in ESMs (O1) and improves and constrains Water–Energy–Carbon feedback (O2). It delivers robust hydroclimate projections over water-limited regions with four ESMs (O3). It assesses the land carbon sink and the sustainability of regreening (O4), and quantifies irrigation needs, adaptation benefits and trade-offs, distinguishing hydrologically feasible pathways from maladaptation (O5). It makes results and model developments accessible to modelling, assessment, risk-management and policy communities (O6).

O1: Enhance structural and scale-aware representation of hydrology in ESMs (WP2, WP4)
Develop and test improved representations of i) shallow groundwater and unconfined-aquifer dynamics, ii) surface–subsurface exchange, iii) lateral water flow, iv) routing and inundation, v) irrigation and human water-balance feedback, and vi) water-table controls on vegetation water access. This will be developed across the land components of four ESM frameworks, through scale-aware parameterisations linking the sub-grid distribution of root-zone storage capacity and of runoff-generation variables to topography, soil and vegetation traits, so that nonlinear behaviour and hydrological connectivity are preserved under aggregation.
Indicators (KPIs)
Means of verification
O2: Improve and constrain the representation of Water–Energy–Carbon feedback (WP1, WP3, WP4)
Develop targeted process improvements in hydrology–vegetation–climate coupling under water-limited conditions: dynamic root allocation and depth; eco-evolutionary optimality formulations of acclimation; diverse plant hydraulic strategies including growth–mortality trade-offs; and updated plant hydraulics applied to crop production and irrigation requirement. These processes will be constrained and evaluated over water-limited and transitional regions using a benchmarking framework that extends current community practice with hydrology-focused Earth observation and process-oriented diagnostics. The framework will also propagate observational uncertainty into development choices — constraining not only individual variables but the process relationships through which models partition, store and transfer water. The regions of interest are comparatively data-poor, so the constraints applied there are satellite-based and global in coverage, while data-rich testbeds will support development.
Indicators (KPIs)
Means of verification
O3: Deliver robust hydroclimate projections over water-limited regions (WP5, WP4)
CHORALE will produce a coordinated suite of historical and scenario simulations with the four ESMs, exploiting the developments validated under O1 and O2 and aligned, where possible, with coupled and land-only CMIP7-related protocols. Targeted regreening and irrigation-sensitivity experiments will be designed and included in the simulations portfolio to probe hydrological constraints, feedback and trade-offs. For cross-scale verification purposes, a bounded set of kilometre-scale regional simulations nested in the global backbone will be performed over two regional domains, EURO-CORDEX and MENA-CORDEX, at approximately 12 km resolution. Within these regional domains, two selected subdomain cases will subsequently be simulated at convection-permitting resolution (< 4 km) by at least two modelling systems. The final cases will be selected based on the sensitivities and feedback identified from the coordinated global and regional analyses, subject to scientific relevance and computational feasibility, and will include priority water-limited environments, such as the Great Green Wall intervention band.
Indicators (KPIs)
Means of verification
O4: Assess future land carbon sink dynamics and the sustainability of regreening actions (WP6, WP7–9)
Determine the long-term sustainability, adaptation potential and carbon-cycle implications of land-based mitigation and regreening in water-limited and transitional regions. This will be done by quantifying the hydrological and ecological feasibility, the potential of sequestration and the associated climate feedback under present and future conditions, identifying thresholds beyond which further expansion of vegetation cover amplifies water stress, groundwater depletion or hydroclimatic extremes, and so compromises the intended benefit.
Indicators (KPIs)
Means of verification
O5: Quantify future irrigation needs, adaptation benefits and trade-offs (WP6, WP7–9)
Represent irrigation demand, driven by climate variability, crop water requirement and socio-economic scenarios in the enhanced models. Based on this, it will assess adaptation benefits, such as reduced heat stress and sustained productivity, alongside unintended consequences, including altered precipitation, water depletion and changes to the surface energy balance. It will explore the observable imprint of irrigation on the surface energy balance in arid, semi-arid and transitional regions to benchmark modelled responses against Earth observation. It will identify where irrigation-supported land-based measures cease to be hydrologically sustainable.
Indicators (KPIs)
Means of verification
O6 – Make project results and model developments accessible to international Earth system modelling, assessment, risk management and policy communities (all WPs, particularly WP4 and WP7–9)
Ensuring project results are accessible to scientific assessment groups, policy- and decision-makers is at the core of CHORALE’s mission. Results will inform cross-sectoral efforts, including climate, food and agriculture policy, water and risk management through targeted dissemination, exploitation and communication measures. Model developments are made accessible to modelling groups beyond the consortium through the public Development and Transferability Matrix (D4.3), which documents for each development the models in which it was tested and whether it proved to be transferable.
Indicators (KPIs)
Means of verification

1.1.3 Ambition and Innovation

ESMs urgently need better representation of hydrological processes and feedback, an essential gap this proposal aims to close. The IPCC Sixth Assessment Report (AR6) identifies the continental water cycle as a major source of uncertainty in climate projections, particularly in water-limited and transitional regions that cover about half of the global land surface and are likely to expand under climate change (IPCC, 2021; 2022). Conversely, models currently disagree on whether water-limited regions are expanding (i.e. Gonsamo et al 2021), highlighting both high uncertainty and immediate policy relevance. In these regions, water limits ecosystem functioning, so small changes in its availability can trigger significant responses in vegetation, surface energy fluxes, and carbon uptake.

Improving the representation of continental hydrology and its coupled interactions with land–atmosphere exchange, vegetation and the carbon cycle is therefore critical, as water availability increasingly shapes climate impacts and the effectiveness of adaptation and mitigation options. Yet current ESMs represent continental hydrology in a structurally incomplete, scale-dependent and weakly integrated way.

The Next Frontier for Climate Change Science1 makes clear that water availability is not only an impact variable but an increasingly critical limit on adaptation itself and calls for better representation of continental water-resource dynamics and their feedback in climate models. The consequences are concrete. Regreening can enhance carbon uptake, improve soil-water retention and modify climate through land–atmosphere interactions, but its long-term success depends on water availability and may increase pressure on limited water resources. Irrigation is vital for food security and adaptation, but it can also reshape land–atmosphere interactions, intensify water stress and intensify humid heat stress for populations. In models that do not resolve the hydrology that governs them, both can appear more benign than they actually are.

Three limitations underlie this. Structurally, key processes are missing or incomplete. These include groundwater storage and capillary rise, surface–subsurface exchange, lateral flow, river–groundwater interaction, managed water use, and dynamic root behaviour that controls vegetation access to water (Liao et al 2025; Feng et al 2025; Zampieri et al. 2012; Valmossoi & Keller, 2022; Gao et al 2024). These propagate into errors in Water–Energy–Carbon couplings through which the land system partitions and transfers water, and so into projections of vegetation stress, surface cooling and the land-carbon response (Fisher & Koven, 2020). Institutionally, long-standing separation between hydrology-oriented and climate-oriented land-surface modelling communities (Clark et al 2015) slows co-design of coupled process representations, shared benchmarks and cross-framework evaluation (Mourot et al 2025). Observationally, water-centric datasets that could serve as structural constraints remain under-exploited, leaving water-limited and transitional systems comparatively unconstrained despite their policy relevance (Fawcett et al 2022).

CHORALE's ambition lies in its enhancement of current best practice. Each objective targets an advancement that the present division of labour between the hydrology, land-surface, ecosystem and climate-modelling communities does not deliver, and that the ongoing CMIP7 cycle (Dunne et al 2025) — which will supply the reference projections on which the next assessment cycle rests — is not designed to deliver either2. Table 1.1 states, objective by objective, what the community already does, why that leaves the gap open, and what CHORALE adds.

Table 1.1: CHORALE advances beyond the state of the art.

Advance Current situation & gaps What CHORALE adds
A1. Structural hydrology made scale-aware, and made portable (O1) Groundwater, lateral flow, routing and inundation schemes exist, but each is usually developed and tuned inside a single model, and hyper-resolution hydrology has advanced largely offline and apart from climate modelling (Clark et al., 2015; Liao et al., 2025; Feng et al., 2025). Parameterisations are retuned when resolution changes, so threshold behaviour and connectivity are not preserved under aggregation (Vreugdenhil et al., 2022). A fundamentally new approach to scale-aware hydrology: each development implemented in at least one ESM land component and transfer-tested in the others, with every development–model combination evaluated and classified (Figure 1.2), with parameterisations grounded in observable landscape properties rather than calibrated to a target resolution. Paired-resolution experiments quantify the residual resolution dependence of simulated fluxes; the kilometre-scale layer then tests whether the land–atmosphere coupling they support survives the change of scale.
A2. Benchmarking that constrains relationships, not variables (O2) Community suites such as ILAMB and PLUMBER2 score simulated variables against observations. Scoring variables cannot distinguish a model that partitions water correctly from one that compensates errors between processes (Fisher & Koven, 2020; Bonan et al., 2024), and observational uncertainty rarely reaches development decisions. Water-centric datasets remain under-exploited as structural constraints (Dunne et al., 2025). Diagnostics that constrain process relationships rather than individual variables — including the Cooling Efficiency Factor Index (Zampieri et al., 2025) and new observation-constrained diagnostics of runoff generation, water-cycle partitioning and irrigation effects — with observational uncertainty propagated into each metric. Benchmarking acts as a gate: no development enters the coupled stage until it has been evaluated against observations and against its model's own reference configuration.
A3. Experiments the current cycle does not produce (O3) CMIP7 will supply the reference projections underpinning AR7, but its land configurations are fixed early and its value rests on standardisation rather than structural change (Douville et al., 2022; Mourot et al., 2025). IRRMIP has produced multi-model results only for a historical, prescribed-SST protocol (Yao et al., 2025a). Regreening has been studied in single models over single regions (Ingrosso & Pausata, 2024). A four-model global regreening perturbation whose extent is derived from published restoration targets rather than prescribed, where published work is confined to single models and single regions; irrigation experiments extended from the IRRMIP historical protocol to coupled and scenario configurations, for which no multi-model results exist; an attribution experiment separating local from remote response; and a kilometre-scale layer testing whether land–atmosphere coupling survives the change of resolution.
A4. Carbon potential reported with its water cost (O4) Land-based mitigation is assessed predominantly through sequestration potential and biophysical surface effects, with hydrological feasibility treated as a downstream constraint or omitted, so restoration can appear beneficial in models that do not resolve the water limitation governing it in practice (Gao et al., 2024; Fawcett et al., 2022). Sequestration potential reported jointly with the water it consumes and with the resulting change in drought and flood behaviour, in models where the limiting hydrology is explicitly represented — a pairing current assessments do not provide; thresholds beyond which vegetation expansion becomes self-defeating; and maladaptive outcomes treated as a reportable result rather than an exception.
A5. Irrigation as a two-sided, observable signal (O5) Irrigation is represented mainly as a water-demand term, and its effect on the surface energy balance is seldom constrained observationally even though it is among the strongest detectable human imprints on the land surface (Valmossoi & Keller, 2022). Its interaction with restoration is not assessed at all. Irrigation demand and hydrological feasibility quantified together under future scenarios, with the simulated surface-energy response benchmarked directly against Earth observation; and the first assessment of where restoration would require irrigation support that cannot be sustained — an interaction the literature does not address — made possible by running both protocols within one experimental framework.
A6. Accessibility and uptake of model developments and evidence (O6) Developments are typically published in papers, with code and data available only on request; transferability is rarely assessed; policy-relevant evidence is seldom co-produced with users. Uptake beyond the originating group is slow. Open-source model developments (KER1); a public matrix documenting cross-model transferability (KER6); FAIR datasets (KER3); assessment-ready evidence for IPCC, EUCRA and policy actors (KER4); and a knowledge hub providing the entry point to CHORALE outputs.

Transferability is a project result, not an assumption. Demonstrating a development in a single model shows only that it works in that model: it does not separate a genuine improvement in the physics from compensation between that model's own errors. CHORALE therefore implements and evaluates every development in more than one framework, against each framework's own reference, and classifies each development–model combination as directly transferable, transferable with model-specific adaptation or as concept or constraint, or not transferable, recording the reason in every case. No systematic multi-model assessment of the transferability of hydrological developments across ESM land components is available today, which makes the resulting classification a result in its own right: applicability limits and negative outcomes are reported alongside successful transfers, across models, scales and regions, because knowing which representations do not carry across architectures is as useful as knowing which do.

1.1.4 Positioning and expected maturity

CHORALE turns existing process knowledge, isolated implementations and observational datasets into reusable modelling capability: developments implemented in production environments, evaluated against model-specific references, exercised in coordinated experiments and released with the diagnostics and protocols needed for reuse. CHORALE does not operate a service: operational use belongs with the modelling centres, intercomparison activities and climate services that take up these outputs.

Because Earth system model components are improved within systems already used operationally and scientifically, maturity is stated per capability rather than through a single Technology Readiness Level (Table 1.2).

Table 1.2: Maturity of CHORALE capabilities at project start and at project end.

Capability At project start At project end
Structural hydrology and scale-aware parameterisation in ESM land components Mature as isolated components: developed in offline hydrological codes apart from climate modelling and implemented one model at a time, with parameterisations recalibrated at each resolution rather than derived from landscape properties. Implemented in at least one ESM land component per development and transfer-tested across the four ESM frameworks (Figure 1.2), each evaluated against its own reference, verified in paired-resolution and kilometre-scale experiments, with transferability classified and documented.
Plant hydraulics, optimality-based acclimation and process-oriented benchmarking Theory is mature and demographic land models can represent mortality thresholds, but the two remain separate implementations; hydrology-focused observational diagnostics exist in the literature and are not yet used to constrain model structure. Combined formulations constrained on data-rich testbeds and carried into the coupled configurations, supported by a benchmarking capability that constrains process relationships and is released under an open licence.
Coordinated multi-model experimentation The four modelling systems and the shared infrastructure are operational; no common protocol yet covers hydrologically enhanced historical, scenario, regreening and irrigation experiments. Defined protocol, agreed and executed by all four models, with output published on ESGF and the experimental design available for reuse.
Assessment-oriented evidence on land-based options Assessed in models that do not resolve the limiting hydrology, and rarely against a common baseline, so feasibility cannot currently be stated with its water cost. Assessment-grade evidence — quantified, uncertainty-bounded, traceable to a documented protocol and expressed against a current assessment baseline — on feasibility, thresholds, trade-offs and maladaptive outcomes.

According to current IPCC planning, the AR7 Working Group contributions are expected to begin appearing from mid-2028, with the Synthesis Report approved by late 20293. CHORALE's coordinated simulations therefore become available after the literature window of the AR7 Working Group I assessment, and the project does not claim to contribute to it. CHORALE instead builds on the knowledge produced by CMIP7 and by the AR7 cycle and is designed for the assessment cycle that follows, with diagnostics, benchmarking tools, validated developments and experiment protocols released throughout the project, and the full evidence base reaching the community in time for the information collection phase of the third Global Stocktake under the Paris Agreement (GST3, concluding in 2033). Scenario selection is anchored accordingly to policy relevance at the time of production (MS5.1, M29; MS5.2, M39), including the option of adopting post-CMIP7 scenarios should these become available. Within Destination 1, CHORALE complements rather than duplicates the other 2025–2027 topics: it addresses one specific assessment gap that no previous or ongoing EU project has tackled across multiple ESMs, the continental water cycle and its coupling with energy, vegetation and carbon in water-limited regions, rather than the broad model development and CMIP7/AR7 simulation support of HORIZON-CL5-2025-06-D1-01 and D1-02, and it supplies the process understanding and modelling capability on which the topics on extremes (HORIZON-CL5-2027-01-D1-07), land carbon sinks (D1-12) and maladaptation (D1-10) can build.

1 European Commission: Directorate-General for Research and Innovation, https://data.europa.eu/doi/10.2777/34601

2 European Commission, 2024. Horizon Europe Work Programme 2026–2027, Climate, Energy and Mobility

3 IPCC, AR7 programme agreed at IPCC-60, https://www.ipcc.ch/assessment-report/ar7/; IPCC press release, 18 Aug 2025. At the time of writing the detailed schedule of the Working Group contributions remains under consideration by the Panel; the argument below holds under all schedules discussed. Global Stocktake: Paris Agreement, Art. 14.

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