To this regard, climate services do not only create user-relevant climate information, but also stimulate the need to quantify vulnerabilities and come up with appropriate adaptation solutions that can be applied in practice. This session invites contributions from all fields in which climate information is used in decision-making processes, including agriculture, renewable energy, banking, water management, tourism and any other societal sector dependent on climate information.
The operational generation, management and delivery of climate services poses a number of new challenges to the traditional way of accessing and distributing climate data. With a private sector growing and playing an increasingly important role as a service provider, it is important to understand the roles and responsibilities of publicly funded climate data, information and services, as well as the standardisation process for climate services.
This session aims to gather best practices and lessons learnt, for how climate services can successfully facilitate adaptation to climate variability and change by providing climate information that is tailored to the real user need.
Contributions are encouraged from public and private climate services providers, as well as from international efforts (GFCS, CSP, …); European Initiatives (HEU, ERA4CS, C3S, ClimatEurope, ECRA, JPI-Climate…) as well as national, regional and local experiences.
Satellite gravimetry from the GRACE and GRACE Follow-On missions has fundamentally advanced our understanding of the global hydrological cycle. Over the past two decades, these missions have enabled robust scientific assessments of terrestrial water storage and, derived from this, groundwater storage, supporting numerous studies on droughts, floods, and long-term water availability. While the scientific maturity of GRACE-based hydrological products is well established, their systematic translation into operational climate services had yet to happen. Bridging this gap is essential to support climate adaptation and water-related decision-making across societal sectors.
In this contribution, we present the operationalisation of GRACE-based hydrological science into a climate service through the introduction of a new Essential Climate Variable (ECV) Service, “Terrestrial Water Storage and Groundwater”, within the Copernicus Climate Change Service (C3S). The service delivers Climate Data Records (CDRs) for the ECV products Terrestrial Water Storage Anomalies (TWSA) and Groundwater Storage Change (GWSC), designed to meet the requirements of long-term climate monitoring and downstream applications. The datasets, together with a comprehensive Data Documentation Package following C3S standards, are already published or will be made publicly available in the coming weeks.
A central challenge in transforming GRACE-based products into an operational climate service is the assessment and communication of product quality. For global, satellite-derived estimates of TWSA and GWSC, suitable in-situ reference datasets are largely unavailable, particularly at the spatial and temporal scales resolved by GRACE. We therefore developed a dedicated quality assessment framework that combines internal consistency checks, uncertainty characterisation, inter-comparison with independent models and reanalyses, and transparent documentation of limitations and fitness-for-purpose.
The presentation will introduce the new C3S ECV service, describe the delivered datasets and documentation, and focus on the adopted approach to product quality assessment. By doing so, we aim to demonstrate how mature Earth observation science can be translated into an operational climate service that supports adaptation to climate variability and change, while clearly communicating uncertainties to users.
How to cite: Haas, J., Boergens, E., Dahle, C., Dobslaw, H., Dorigo, W., Duissaillant, I., Flechtner, F., Kosmale, M., Lems, J., Luojus, K., Preimersberger, W., Sharifi, E., Zemp, M., and Güntner, A.: A New C3S ECV Service for Terrestrial Water Storage and Groundwater, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2993, https://doi.org/10.5194/egusphere-egu26-2993, 2026.
The C3S2_520_CNR contract improves the evaluation and quality control (EQC) function of the Copernicus Climate Change Service (C3S) by providing efficient and transparent quality assurance of climate datasets in the Climate Data Store (CDS). The main objective is to answer the user question “How, and how well, can I use these data for my purpose?” To this end, the EQC material is organised in a hierarchical structure so that users can find high-level information on fitness for purpose with application examples, detailed requirements that data, metadata and documentation must meet, and scientific assessments with explicit examples of data use. The approach is strongly user-oriented and combines interactive self-assessment tools, stakeholder consultation and continuous feedback to ensure the reliability, usability and long-term sustainability of quality information for climate datasets.
How to cite: Yang, C., Bartucca, C., Serva, F., Obregon, A., Goddard, C., and Martins, J.: Evaluation and Quality Control of Copernicus Climate Data, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13376, https://doi.org/10.5194/egusphere-egu26-13376, 2026.
Methodological approaches for assessing the values and benefits of Climate Services (CS) range from quantitative methods (cost-benefit analyses, simulations) to qualitative ones (case studies, interviews). Leading frameworks stress the importance of holistic, context-sensitive evaluation that integrates stakeholder engagement and covers economic, social, and environmental dimensions. It is necessary to consider both tangible and intangible benefits of CS, as well as continuous stakeholder engagement for a deliberate, structured approach to CS evaluation, rooted in transparent methodology, user-centered design, and explicit articulation of both benefits and limitations.
The contribution from Gonzalez Romero et al. (2025) advances CS evaluation science by empirically grounding these principles in the perspectives of public-sector users and standardization processes. Drawing on in-depth interviews with public authorities across different European countries, the study analyses how municipalities understand, use, and evaluate CS. Results show that climate risks, particularly flooding and heat stress, are increasingly taken into consideration for decision-making, including new urban developments, major infrastructure projects, and changes to zoning and land use decisions, often with explicit focus on vulnerable populations. The interviews expressed the need to better understand the uncertainty associated with climate data and how to best communicate this to various stakeholders.
These findings reveal that municipalities had a preference for in-house provision of CS if possible. Where this was unfeasible, preference was given to public institutions, such as National Meteorological and Hydrological Services or platforms such as Climate Atlas, due to legitimacy, trust and financial reasons. No interviewees reported relying on any standard when selecting providers. The lack of a clear and cohesive national guidance on CS was identified as a common barrier. Clear institutional and financial barriers, including a lack of both staff and capacity to use the data, were also mentioned. Local knowledge was highlighted as an essential asset for developing adaptation plans that feel realistic, actionable, and trusted by the community.
The perceived importance of CS among municipalities varied and was shaped by a combination of institutional structures, political will, financial considerations, and local priorities. The lack of standardisation, clear national guidance, and data accessibility were universal complaints. Consolidated climate data can strengthen the rationale for climate-smart policies, especially where legal mandates are not yet in place. By linking these user-derived perspectives to existing CS evaluation frameworks, this study contributes to a structured, practice-oriented perspective on how CS generates value in policy and planning contexts.
References:
Gonzalez Romero, C., Ferrari, T., McBride, P. J., Calderaro, C., Taddeo, S., Klose, A., Eckel, F., Hömberg, J., Jaiyeola, A., Jablonski, A., Villwock, A., & Stuparu, D. (2025). Recommended approach to the application of assessment methods and pilot applications case studies. Zenodo. https://doi.org/10.5281/zenodo.16926911
How to cite: Gonzalez Romero, C., Ferrari, T., McBride, P. J., Eckel, F., Calderaro, C., Taddeo, S., biddau, F., Jaiyeola, A., Klose, A., Hömberg, J., Villwock, A., Stuparu, D., and Jabłoński, A.: Assessing the value of climate services for public authorities in Europe, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12230, https://doi.org/10.5194/egusphere-egu26-12230, 2026.
Effective climate adaptation depends on how climate-related information, experience, and expectations are translated into decisions across climate-sensitive sectors. Adaptation decision-making is often implicitly assumed to respond linearly to increasing risk, yet growing evidence indicates the presence of thresholds and lock-in effects. Using survey data from a climate-exposed professional sector as an empirical test case, we apply Bayesian inference and explainable machine-learning methods to uncover non-linear adaptation decision dynamics.
Across respondents, the predicted probability of adaptation advocacy is moderate (0.60, 95% CI: 0.52–0.68), establishing a baseline against which critical decision thresholds are detected. While beliefs in local climate impacts are generally strong, beliefs in personally experienced impacts are weaker, highlighting potential gaps between abstract climate information and experiential knowledge. Model-based predictions reveal that adaptation advocacy increases with expected impacts up to critical thresholds but declines beyond them, reflecting risk- and opportunity-associated tipping behaviour rather than monotonic responses.
These non-linear patterns are partly contingent on both the expected impacts of climate change, arising from the interaction of information, personal experience, and prior knowledge, and reported access to adaptation measures considered effective. Incorporating anticipated risk and opportunity alongside perceived actionability alters predicted decision regimes, producing conditional lock-in, where adaptation behaviour persists at a given level but may fail to increase even as risk rises. This demonstrates that climate information alone is not universally effective; rather, it must be tailored to the needs, experiences, and capacities of recipients, as the timing and magnitude of tipping behaviour, shaped by perceived impacts and available options determines whether information translates into meaningful adaptive action.
Although the empirical analysis focuses on one professional group, the identified decision thresholds and lock-in mechanisms are likely relevant across climate-sensitive sectors. These findings have implications for designing climate services that support actionable, context-sensitive adaptation under uncertainty, bridging the gap between information provision and adaptive decision-making.
How to cite: Blennow, K., Persson, J., and Häggström, C.: Non-linear decision thresholds and adaptation lock-in under climate change: Evidence from a professional decision-making context, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13438, https://doi.org/10.5194/egusphere-egu26-13438, 2026.
The ‘Early Warnings for All’ initiative provides a framework for multi-hazard warning systems that aim to protect people from the negative consequences of environmental events. Due to climate change, we see these events occurring more frequently and with higher magnitudes than before.
One of the main bottlenecks in early warning systems is the lack of high-resolution meteorological information, restricted by the mesoscale resolution of most climate models. This impedes the correct representation of e.g. temperatures and heat stress in cities, which can be significantly higher compared to rural environments (the so-called Urban Heat Island effect). Traditional models require multiple nesting steps and are therefore often not suited for early warning management systems. The UrbClim model partially fills this gap by providing fast and reliable meteorological and climatological information at resolutions of up to 100m. The main bottleneck remains in the limited spatial domains (which are usually limited to the size of a city) at which the UrbClim model operates.
To tackle this issue, an AI-based model is designed, based on a 2D Neural Network, leveraging Copernicus ERA5 reanalysis drained and validated with UrbClim simulations. This model provides instant high-resolution (100m) meteorological information (temperature, humidity and heat stress) at daily and hourly frequencies for spatial domains extending to sizes of full countries. A modular Python package underpins the workflows, enabling automated data retrieval, processing, and integration into operational environments. The data feeds in directly in two operational climate services: i) vector borne disease modelling in Belgium & (ii) heat-health early warnings in the Arabian Peninsula. The added value of high-resolution and urban-resolving physics will be demonstrated on both operational and long-term time scales, showcasing its effectiveness in supporting decision-making by regional and federal (health) authorities on both short-term (e.g. issuing warnings) and long-term time scales (e.g. urban planning).
How to cite: Souverijns, N., Wouters, H., Veldeman, N., Broeckx, J., Takacs, S., Lanssens, B., Hosseinzadehtalaei, P., Schouwenaars, F., and Houdmeyers, R.: From Cities to Countries: High-Resolution (100m) Climate Services Supporting Early Warning Systems , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11909, https://doi.org/10.5194/egusphere-egu26-11909, 2026.
Integrating information from multimodel ensemble hydroclimate projections in adaptation strategies poses significant challenges from an operational point of view. Three of these challenges are addressed here to provide information relevant to local water managers in France: (i) the uncertainty from ensembles derived from multiple Global Climate Models (GCMs), Regional Climate Models (RCMs), and Hydrological Models (HMs), (ii) the conceptual differences from scenario-based projections to Global/Regional Warming Level approach, and (iii) the semantic complexity of hydroclimate modelling chains.
This work builds on a large multimodel ensemble of hydrological projections from the Explore2 French national project (Sauquet et al., 2025), and the National Reference Warming Trajectory for Adaptation (TRACC, Soubeyroux et al., 2024) which defines three Regional Warming Levels (RWLs) : +2°C, +2.7°C, +4°C. The Explore2 hydrological projections consist in up to 153 transient daily streamflow series for over 4,000 locations in France. The approach taken is to select through a dedicated clustering algorithm four individual projections that adequately sample possible changes for time slices defined by the RWLs. Selection is made separately for large basins striking a balance between spatial consistency across local studies, and regional diversity in the hydrological responses ro RWLs. Selection is made based on low-, average- and high-flow indicators to capture contrasting changes across the hydrological regime.
The selected individual projections are called Narratraccs -- short for "TRACC narratives" -- and organised around four families of overall changes represented by one letter (X, E, C, M): eXtrêmes (extremes), Étiages (Low-flows), Crues (floods) and Modérés (Moderate). Each Narratracc belongs to one or more of these families for a given basin and a given RWL. The individual projections originally defined through their GCM/RCM/HM modelling chain (e.g. HadGEM2-ES / CCLM4-8-17 / MORDOR-TS) are renamed and articulated as, for example, "E1: decreased annual streamflow, slightly less severe floods, and much more severe low-flows".
Narratraccs are disseminated via the MEANDRE-TRACC dedicated portal (https://meandre-tracc.explore2.inrae.fr/) which extends the widely-used MEANDRE portal (https://meandre.explore2.inrae.fr/). The latter aimed to synthesise messages from the Explore2 project. MEANDRE-TRACC enables users to visualise and download changes associated with each Narratracc. It also redirects to one-page summary sheets for individual subbasins (Héraut et al., 2025) which are hosted by the Explore2 dataverse (https://entrepot.recherche.data.gouv.fr/dataverse/explore2 .
This work has been funded by the Agence de l'Eau Loire-Bretagne through the EHCLO R&D project.
References
Héraut, L. et al., 2025, Analyse des débits et de la recharge potentielle des aquifères par niveau de réchauffement et par secteur hydrographique — Fiche de synthèse, https://doi.org/10.57745/QDCSBZ, Recherche Data Gouv, V3
Sauquet, E. et al. A large transient multi-scenario multi-model ensemble of future streamflow and groundwater projections in France, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2025-1788, 2025.
Soubeyroux, J.-M. et al. (2024) À quel Climat s’adapter en France selon la TRACC ? Partie 1 —
Concepts et données de base pour les températures et précipitations. Météo-France. https://hal.science/hal-04797481v3
How to cite: Vidal, J.-P., Calmel, B., Héraut, L., and Sauquet, É.: Building and disseminating local hydrological narratives under regional warming levels, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6852, https://doi.org/10.5194/egusphere-egu26-6852, 2026.
The project RETE (Resilience of the Electric Transmission grid to Extreme events) funded by the Italian National Plan for Resilience and Recovery, has demonstrated a prototype service designed to enhance the resilience of critical infrastructures, with a focus on the Italian national transmission grid. The focus of the service is the growing risks posed by climate related geotechnical hazards (e.g. shallow landslides) by integrating climate intelligence with engineering and complex network science.
The concept of RETE originated from the challenges faced by TERNA in planning strategic investments to enhance the resilience of the national transmission grid against changing patterns of intense rainfall events. Such extreme events may affect the frequency of fast landslides with a potential impact on the stability of the infrastructure and related services. To systematically tackle these challenges, RETE was shaped using a climate service development methodology that grounds the service in real user needs, applies advanced scientific models, and iteratively co-designs solutions with stakeholders.
The service architecture is built around several key tools: harmonized climate datasets, high-resolution climate projections generated via deep machine-learning (M-L) approaches, a complex network model to simulate cascading effects across the transmission grid, a geotechnical hazard model interfaced with climate inputs.
We describe the methodology adopted for the consultation and co-development of the service and the resulting multi-scale climate resilience analysis framework tailored to the specific needs of distributed critical infrastructures like the NTG. The co-development methodology has allowed the identification of key decisions and the tailored framework for the resilience analysis at four integrated geographical scale, from national to asset specific.
At the national scale, the framework evaluates dynamically and statistically downscaled precipitation projections to investigate how highly localized extreme rainfall events may evolve under future climate scenarios. These projections are integrated with landslide susceptibility data derived from terrain models, lithology, land cover, and historical landslide inventories to identify areas of heightened risk.
At the sub-system scale, graph theory and complex network modeling are applied to analyze infrastructure resilience. Electrical grid subsets are simulated under disruption scenarios to identify critical components based on their structural and functional roles. Electrical properties are assigned to network links, and tailored topological metrics are used to evaluate system robustness, recovery capacity, and performance.
At the site-specific scale, hydro-mechanical finite element models simulate slope stability under projected climate conditions. The model incorporates slope geometry, stratigraphy, lithology, geo-structural features, and soil hydraulic and mechanical properties critical to climate-induced instability.
While the asset scale is not explicitly addressed, the framework establishes the foundation for more localized risk and cost–benefit analyses.
Finally, we illustrate possible applications of the same co-development methodology in other activities dedicated to the development of sectoral applications such as the project RIVIERADE (Improving modelling methods to produce climate services for resilient European seas and coasts in a decadal to multi-decadal horizon).
How to cite: Calmanti, S. and the Team RETE: A climate service for the Resilience of the Electric Transmission grid to Extreme events, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13614, https://doi.org/10.5194/egusphere-egu26-13614, 2026.
As a national weather and climate service, GeoSphere Austria is responsible for the creation and dissemination of data-driven, factual, and unbiased climate information. The GeoSphere Austria website hosts different types of climate-related content: (a) interactive mapping tools for the visualization of gridded climate variables; (b) homogenized long-term station observations for the Alpine region; (c) graphics that display current observations in historical context; (d) information on extreme events and their impact; (e) tools for the download of a variety of climate datasets such as time series, spatial variables, climate normals, and others; (f) an extensive collection of regularly updated articles on climate change and its impact in Austria; (g) climate information on topics such as phenology and others.
In an environment of increasing dis- and misinformation, easy access to accurate climate information is crucial for decisionmakers, the general public, and other stakeholders. Therefore, at GeoSphere Austria an effort is underway to modernize not only the look and feel of the climate web pages but also the underlying architecture and how users access information and interact with the content. By integrating the currently scattered topics into one state-of-the-art climate information center, we aim to create a one-stop-shop for accurate climate content in Austria. In this presentation, we will give an overview of the project, the timeline, and lessons learned throughout the process.
How to cite: Romatschke, U., Ganekind, M., and Chimani, B.: Modernization of the distribution of climate information in Austria , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18720, https://doi.org/10.5194/egusphere-egu26-18720, 2026.
Climate services increasingly rely on spatially and temporally consistent meteorological datasets to support climate-aware decision-making across many sectors. In Italy, where complex orography and strong regional climate gradients challenge weather modelling and observational representativeness, meteorological reanalyses represent a key backbone for climate services, enabling monitoring, impact assessment, and adaptation planning in areas such as water resources, renewable energy, civil protection, and urban management.
This contribution summarises a PhD work which assessed the performances of major reanalysis datasets available over Italy through systematic inter-comparison and validation. We focus on 2-m surface air temperature (t2m) and total precipitation (tp) variables. The analysis includes global products (ERA5 at ~31 km grid spacing and ERA5-Land at ~9 km) alongside a comprehensive set of regional dynamical downscalings, namely MERIDA and MERIDA-HRES (developed by RSE), MOLOCH and BOLAM (LaMMA), SPHERA (ARPAE), VHR-REA_IT (CMCC), and MORE (ISAC-CNR), with resolutions ranging from 7 km down to convection-permitting scales (~2 km). Other European products, such as CERRA (Copernicus) and COSMO-REA6 (DWD), are included. Reanalyses are evaluated against high-quality observational references, both gridded and station-based, using validation approaches that explicitly account for scale, resolution, and orography.
Temperature validation (1991–2020) uses observational data elevation-adjusted to each reanalysis grid, eliminating orographic mismatches. Regional products show systematic cold bias (-0.5 to -1°C), strongest in winter over the Alps, where climatological errors dominate. However, daily anomalies and climate indices (e.g., tropical nights) are well captured, demonstrating strong performance in weather variability and impact-relevant metrics. Precipitation validation (1995–2019) uses wavelet spectral analysis to demonstrate the added value of convection-permitting reanalyses in resolving localised (<10 km) phenomena critical for hydrological and risk services. Frequency analyses show that ERA5 underestimates extremes (>20 mm/day), while higher-resolution products better capture intensity distributions but show spatial displacements of convective events. Systematic biases emerge: +30% summer wet bias in northern Italy; -20% winter/fall dry bias in southern regions, and product-specific differences in long-term trends, underscoring the need for bias correction in climate assessments.
The validation effort has resulted in the publication of several papers in international scientific journals (references below), where the full set of methodologies and results is documented and made available to the wider community. Overall, this work highlights how rigorous, scale-aware validation is essential to guide the informed use of reanalysis products in climate services. By identifying strengths and limitations relevant to specific variables, regions, and applications, the study supports transparent and product-specific integration of reanalysis data into operational climate services and adaptation strategies in Italy.
References:
- Cavalleri et al. (2024) Multi-scale assessment of high-resolution reanalyses precipitation fields over Italy. Atmos. Res. 312, 107734.
- Cavalleri et al. (2024) Inter-comparison and validation of high-resolution surface air temperature reanalysis fields over Italy. Int. J. Climatol. 44, 2681–2700.
- Lussana, Cavalleri et al. (2024) Evaluating long-term trends in annual precipitation: a temporal consistency analysis of ERA5 data in the Alps and Italy. Atmos. Sci. Lett. 25, e1239.
How to cite: Cavalleri, F., Stocchi, P., Lussana, C., Viterbo, F., Brunetti, M., Bonanno, R., Manara, V., Lacavalla, M., Maugeri, M., and Davolio, S.: Reanalysis Datasets for Climate Services in Italy: Validation and Inter-Comparison, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4007, https://doi.org/10.5194/egusphere-egu26-4007, 2026.
Mountain regions whose economies depend on winter tourism are particularly vulnerable to climate variability and change, especially through alterations in snow-cover regimes that directly affect local infrastructure and livelihoods. In the Ukrainian Carpathians, Slavsko is one of the most important winter tourism centres, where increasing climate variability and declining snow reliability pose growing challenges to the sustainable operation of ski resorts and related services. This contribution presents the scientific basis and conceptual design for establishing the Slavsko Mountain Living Lab, aimed at developing an operational climate service to support adaptation of winter tourism in the Carpathian region.
The Living Lab is grounded in a comprehensive long-term analysis of snow-cover dynamics at the Slavsko meteorological station (592 m a.s.l.) for the period 1948/49–2019/20. Based on daily observations, snow-cover duration, periods of stable and unstable snow cover, maximum and mean snow depth, daily accumulation and melt processes, as well as synthetic indicators of winter snowiness and severity are analysed. The results indicate a weak but persistent decrease in the number of snow-cover days (approximately one day per decade) and a gradual decline in maximum and mean snow depth, set against pronounced interannual and multi-decadal variability. A statistically significant decrease in winter severity suggests that thermal changes are progressing faster than reductions in snowfall, leading to shorter periods of stable snow cover and a higher frequency of discontinuous snow conditions. At the same time, episodically very snowy winters continue to occur, underlining the importance of variability and extremes for operational planning.
These findings form the empirical foundation of the Slavsko Mountain Living Lab, which is implemented within the framework of the Erasmus+ project “Supporting Ukraine’s Next Generation of Scholars: a project for Raising University Capacity and Improving Doctoral Student Education” (SUNRISE, 2024–2027; https://sunrise.emu.ee/). The Living Lab is conceived as a co-creation platform that brings together ski resort operators, local authorities, tourism businesses, community organisations, and researchers to collaboratively develop climate-informed decision-support tools for mountain regions.
The Slavsko Mountain Living Lab focuses on integrating long-term climate diagnostics, snow-cover monitoring, and applied climate information into a user-oriented climate service, implemented through an interactive Shiny-based application (R). The application supports the visualisation, exploration, and interpretation of snow and climate indicators, enabling stakeholders to engage directly with climate information in a transparent, accessible, and decision-relevant manner.
Within the SUNRISE framework, the Living Lab also functions as a real-world training and research environment for doctoral students, strengthening their competencies in climate data analysis, climate service co-design, and science–policy–practice communication. In this way, the Slavsko Mountain Living Lab serves both as a pilot framework for climate adaptation in mountain tourism and as a transferable model for other mid-elevation mountain regions seeking to enhance the climate resilience of tourism-dependent local economies under conditions of increasing climatic uncertainty.
ACKNOWLEDGEMENTS
This work was supported by the SUNRISE project (2024-1-IT02-KA220-HED-000256685), co-funded by the Erasmus+ Programme of the European Union.
How to cite: Khomenko, I., Ovcharuk, V., and Marchyshyn, R.: Establishing a Mountain Living Lab for Climate Services in Slavsko (Ukrainian Carpathians), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9986, https://doi.org/10.5194/egusphere-egu26-9986, 2026.
The evolving landscape of climate service provision reveals a fundamental tension between commercial exploitation and equitable public access. This position paper argues for a paradigm shift from purely market-oriented climate services toward a "knowledge commons" approach that balances innovation with universal accessibility. We demonstrate that this approach not only advances climate justice principles but also enhances collective resilience through more democratic governance of climate adaptation.
Current trends in climate services commercialization raise significant concerns about information asymmetry and climate justice. Our experience of climate service provision across multiple national contexts indicates that profit-driven models often result in essential climate information becoming inaccessible to vulnerable stakeholders who lack financial resources. This creates a paradoxical situation where those most exposed to climate risks have the least access to vital adaptation knowledge. Furthermore, the potential privatization of publicly-funded climate research outputs threatens to undermine the social contract between science and society.
We want to clarify that the private sector involvement in climate services brings valuable insider perspectives on market dynamics and incentive structures and enhances the understanding of commercial climate applications. We recognize that innovative applications can flourish alongside equitable data access principles. The private sector creates specialized applications, user interfaces, and sector-specific tools. These specialized products often exceed what government organizations can efficiently produce. Yet such commercial innovations should build upon freely accessible core climate data.
Real-world examples demonstrate the serious consequences of information inequality. The issue of asymmetric information access has been recognized since the early phases of seasonal forecasting distribution (Lemos at al., 2007). In the agricultural insurance sector, research by Carriquiry and Osgood (2012) reveals that farmers with constrained resources and inflexible production systems often cannot adequately adapt their practices when favorable climate conditions arise. Consequently, while premium reductions during favorable seasons appear beneficial on paper, these farmers may lack the capacity to fully capitalize on these opportunities, leaving them in a disadvantaged position overall.
Our analysis suggests that establishing climate services as a tiered system, with guaranteed universal access to core services complemented by specialized commercial offerings, offers a promising approach. Central to our framework is the recognition that climate scientists supported through public funding have an inherent responsibility to ensure their work serves the broader public interest. This does not preclude engagement with private sector applications, but requires thoughtful institutional designs that maintain scientific integrity while preventing exclusive appropriation of knowledge critical for climate adaptation.
By advocating for more equitable climate service provision, this position paper contributes to both theoretical understandings of knowledge of common governance and practical implementations of climate justice principles. The ultimate goal is to ensure that climate service evolution enhances rather than undermines our collective capacity to address the unprecedented challenges posed by climate change, particularly for those communities who face the greatest exposure with the fewest resources.
How to cite: Petitta, M., Calmanti, S., and De Felice, M.: Climate Services as Public Infrastructure: Lessons from European Research Partnerships, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6991, https://doi.org/10.5194/egusphere-egu26-6991, 2026.
Delivering validated climate services for resilient European Seas on a decadal to multi-decadal horizon is a challenge. The recently started HEU RIVIERADE project brings together the scientific communities geared into CORDEX and the Copernicus Marine Service and capitalizes on their unique scientific experience to develop and implement a pre-operational and replicable multi-model framework and protocols to produce, downscale, assess and deliver state-of-the-art decadal predictions and multi-decadal projections of climate change and related impacts on marine ecosystems, covering the basin scale and the coastal areas, up to, and including, development and demonstration of climate services.
RIVIERADE will target three European Seas (Baltic, Black, Mediterranean), to produce data and information for ocean health, sustainable blue economy, and coastal climate risks, downstreaming the data flow from climate ensembles to coastal areas at different spatial resolutions and for selected areas, in a circular process based on users and stakeholders engagement, co-design and assessment of innovative climate services.
The RIVIERADE process of co-design and co-development of regional ocean climate impact/risk services and of regional ocean climate services supporting blue economy will be carried out through engagement of stakeholders and perspective users, in order to foster a continuous interaction between end-users and scientists to identify and prioritise societal needs.
We present the methodological charter adopted to codesign and test the RIVIERADE climate services demonstrators. The interaction with stakeholders and end-users firstly includes the setting-up of an Users and Stakeholders Advisory Board (USAB) since the beginning of the activities. USAB will be composed by sectoral coordinating organizations (e.g., territorial decision-makers, regional environmental commissions, national technology clusters, research institutions) who have already expressed interest in joining us or belong to collaboration networks already established by the project partnership. Starting from the prioritised contacts identified by the umbrella organizations present in USAB, a representative sample of specific end-users will be identified and engaged to co-design and co-develop demonstrators for the three regional seas. Scoping workshops will be organised at the early stage of the project to present the innovative tools that will be developed in RIVIERADE, to identify and prioritise the specific needs of users involved in terms of data, information and knowledge required, as well as related spatial and temporal scales. A relevant expected outcome of the USAB workshops will be to build a common terminology, to be adopted in the project and beyond, between users and providers of services to smooth the overall co-design process and the following activities of testing and validation of the services. Subsequently, the effectiveness of the demonstrators will be assessed by analysing their support on critical decisions focusing on critical years/events selected by the users. Finally, the value of demonstrators in supporting decision-making processes for early adopters will be showcased also considering potential enablers and barriers in each case study. Factors influencing the value of a service to the end-user, will be discussed with users in a large showcasing event where the final version of the tools will be presented.
How to cite: Dell'Aquila, A., Calmanti, S., Salon, S., Canu, D., Solidoro, C., Ulses, C., Ranasinghe, R., Meier, M., Magnus, H., Fach, B., and Salihoglu, B.: Co-developing and co-designing climate services for the Baltic, Black, and Mediterranean Seas: the contribution of RIVIERADE project , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12554, https://doi.org/10.5194/egusphere-egu26-12554, 2026.
The wine industry is among the agri-food sectors most strongly influenced by climate variability and climate change across multiple time scales. In particular, the integration of reliable and timely sub-seasonal, seasonal, and decadal climate information into decision-making processes can support the wine sector in better managing climate-related risks, such as spring frost events or water-use restrictions. This has led to growing interest in climate information at these different temporal scales.
Despite this interest, several challenges continue to limit the uptake of climate information by users, including the coarse spatial resolution of climate model outputs and the lack of coherence between climate predictions from different forecast systems operating at different time scales. To address these limitations and produce coherent regional climate information tailored to the wine sector, the suitability of various statistical downscaling methods has been assessed to enhance the spatial resolution of user-relevant climate variables and indicators at specific locations in Catalonia.
In addition, a novel methodology for the temporal merging of seasonal and decadal predictions has been developed to improve the accuracy and consistency of key climate variables. This approach has also been explored for sub-seasonal and seasonal predictions, contributing to a more seamless climate information framework.
This new scientific knowledge has been developed within the EU-funded ASPECT project (Adaptation-oriented Seamless Predictions of European ClimaTe) and the SINFONIA Marie Skłodowska-Curie Postdoctoral Fellowship (Towards Seamless climate INFOrmation: merging sub-seasonal and seasonal predictioNs to better manage climate-related rIsks Affecting the wine sector). In both initiatives, the scientific methods are co-developed in close collaboration with representative stakeholders. Building on these interactions, a climate bulletin has been designed to support key vineyard management decisions by integrating seasonal and decadal predictions, with future versions incorporating seamless and higher-resolution climate information as results become available.
How to cite: Torralba, V., Delgado-Torres, C., Duzenli, E., Pérez-Zanón, N., Doblas-Reyes, F. J., Soret, A., and Terrado, M.: Co-developing seamless climate information for the wine sector, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10087, https://doi.org/10.5194/egusphere-egu26-10087, 2026.
The German Strategy for Adaptation to Climate Change (Deutsche Anpassungsstrategie - DAS) provides the political framework for climate change adaptation in Germany and lays the foundation for a continuous process aimed at preparing for the impacts of climate change and reducing climate-related risks.
The DAS core service „Climate and Water“ provides monitoring and climate projection data to assess adaptation needs related to climate change. The service comprises both tailored advisory support and the ongoing provision of climate projection and observational data. The data is delivered through standardized workflows and are tailored to user-specific requirements.
Here the focus is on data for the North Sea and the Baltic Sea, including their German coastal regions. So far, sea surface temperature observational data for the last 30 years and various climate variables from climate projections are available via the “DAS Climate Data Coast” application (https://das.bsh.de). This data comes from different sources: Global sea level projections from the IPCC 6th Assessment Report (AR6) were adapted to regional vertical land motion conditions for different SSPs decadal until 2150. Extreme sea level, sea surface and bottom temperature and sea surface and bottom salinity are available from a regional climate ocean projection ensemble based on atmospheric forcing from five members of the EURO-CORDEX CMIP5 ensemble. The simulations were calculated for a thirty-year ”historical” period (1971-2000), a thirty-year ”near future” period (2031-2060) and one for the ”far future” (2071-2100) for the RCP8.5 scenario.
The service is designed to respond to the evolving needs of users engaged in climate change adaptation along the German coasts. This is achieved through biennial stakeholder workshops and regular updates of the available climate data. Planning is already underway for the next regionalized model runs based on the EURO-CORDEX CMIP6 climate projections. In addition, the service is continuously expanded with new climate variables and up-to-date observational datasets.
How to cite: Ehlers, B.-M., Janssen, F., Jenssen, C., Ditzinger, G., Su, J., Hovy, C., and Kruschke, T.: Adaptation to climate change: Regional scenarios for the North Sea and the Baltic Sea, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16818, https://doi.org/10.5194/egusphere-egu26-16818, 2026.
Ireland’s National Framework for Climate Services (NFCS), established in 2022, facilitates sustained collaboration between climate information providers and users to deliver decision-relevant climate services. The NFCS promotes knowledge exchange across the science–policy–user interface, integrates scientific advances, and supports Ireland’s climate resilience efforts by signposting authoritative climate information, promoting existing tools, and reducing duplication of effort.
The establishment of the NFCS followed a low-risk “project-first” approach to test national appetite and relevance before formalizing long-term structures. Rather than beginning with a permanent framework without clear demand, this approach allowed Met Éireann (Ireland’s National Meteorological Service) to identify stakeholders, evaluate engagement pathways, and identify potential challenges through time-bound projects. This provided a robust evidence base for transitioning to a sustained national climate services infrastructure.
Here we describe an “all-of-government” approach to building permanent mechanisms for the generation, management, and use of climate services in support of adaptation planning. We outline how the NFCS has moved from coordination and dialogue toward enabling consistent, actionable use of climate information across sectors, and reflect on successes, challenges, and lessons learned that are relevant to climate service providers internationally.
By 2026, notable achievements of Ireland’s operational NFCS include:
- The embedding of the NFCS within national climate policy infrastructure, ensuring that all sectors developing Sectoral Adaptation Plans are using a common, authoritative climate data baseline.
- The development of a semi-quantitative climate risk assessment framework, designed for reuse by sectors and organizations to support structured, transparent risk assessments.
- The organization of national workshops addressing key cross-cutting challenges for climate services, including data rescue, artificial intelligence for climate services, and uncertainty in climate change projections.
- The production of synthesis guidance on sea-level rise for Ireland, translating complex scientific evidence into consistent, decision-ready information for policy and planning.
- The establishment of a permanent NFCS identity through a dedicated webpage, branding, an operational online helpdesk, quarterly newsletters, and thematic hubs that aggregate relevant data, services, and communications.
- Continued support for major national climate initiatives, including the National Adaptation Framework, the National Climate Change Risk Assessment, and sectoral adaptation planning processes.
- International recognition of Ireland’s NFCS as a case study in the WMO State of Climate Services report, highlighting its role in enabling climate-informed decision-making across sectors such as the built environment, transport, water, and agriculture.
This contribution demonstrates how a national climate services framework can evolve from scientific coordination toward operational, policy-embedded climate services, offering transferable lessons on governance, standardization, and the translation of climate science into action.
How to cite: Flattery, P., Coonan, B., Delmar, J., Duffy, C., Griffin, S., Gillman, C., Lambkin, K., and Scannell, C.: From Projections to Policy: Embedding Climate Services in National Decision-Making in Ireland, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18209, https://doi.org/10.5194/egusphere-egu26-18209, 2026.
The Pacific Island Countries Advanced Seasonal Outlook (PICASO) is a climate prediction tool focused on the Pacific Islands, which was launched in 2018. PICASO currently provides 3-month seasonal precipitation forecasts using predictors derived from the APEC Climate Center Multi-Model Ensemble (APCC MME) hindcast dataset for 1983–2005. Under the UNEP CIS-Pac5 project, we have identified new seasonal and monthly predictors for both precipitation and temperature forecasts, based on the updated APCC hindcast dataset (1991–2010). Using these new predictors, we validated the performance of PICASO’s precipitation forecasts at ten observation stations across five countries (Cook Islands, Marshall Islands, Niue, Palau and Tuvalu). The validation period covered 2016–2023, and forecast performance was evaluated using the Heidke Skill Score (HSS). Overall, seasonal forecasts exhibited higher skill than monthly forecasts. When comparing forecasts produced using the old and new hindcast datasets, most stations recorded higher scores. Future work will evaluate the predictive skill of temperature forecasts. In addition, monthly forecasts will be produced on a regular basis and included in an upgraded version of PICASO to be released in the near future.
How to cite: Jeong, D.: Advancing Climate Prediction for the Pacific Islands: Validation of Updates to the PICASO Forecast System, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4686, https://doi.org/10.5194/egusphere-egu26-4686, 2026.
Climate services play a critical role in bridging scientific knowledge and societal needs, enabling informed decision-making for climate adaptation and mitigation. Their effectiveness increasingly depends on their capacity to foster business innovation by translating climate knowledge into scalable solutions, market-ready services, and sustainable value creation. This contribution presents the experience developed within Climateurope2, a Horizon Europe project coordinated by the Barcelona Supercomputing Center, based on an in-depth literature review and on 43 semi-structured interviews conducted with climate service providers, with the aim of analysing how business innovation dynamics can enhance the uptake and impact of climate services.
This contribution examines the business models underpinning climate services and assesses their innovation potential for the future development of the climate services market, with a particular focus on pathways that support transformative and sustainable societies. The analysis shifts attention toward climate services provided by the private sector, complementing existing research that has largely focused on public-sector provision. Building on prior work on climate services business models, this study adopts a comprehensive framework to analyse value creation, delivery, and capture in climate service provision.
Drawing on in-depth, semi-structured interviews with a diverse set of climate service providers across Europe, the study applies a structured and empirically grounded coding approach covering all nine elements of the Business Model Canvas. This enables a more detailed and up-to-date understanding of how providers operationalise and adapt their business models in response to heterogeneous user needs, market fragmentation, and evolving policy contexts. The findings highlight emerging patterns of hybrid business models, key challenges to commercial viability, and innovation strategies that combine public and private value creation. The study provides empirical insights into the mechanisms through which climate services can enhance their market relevance while maintaining their societal function, contributing to the long-term sustainability of the climate services ecosystem.
How to cite: Taddeo, S., Romero Gonzalez, C., Jaiyeola, A., Calderaro, C., Mysiak, J., Villwock, A., and Jabłoński, A.: Strengthening Climate Services through Innovative Business Models, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12283, https://doi.org/10.5194/egusphere-egu26-12283, 2026.
In the context of accelerating climate change and historical land-use degradation, restoring the hydrological functions of small rivers has become a critical Nature-based Solution (NbS) for biodiversity conservation. This study focuses on the Camenca River (Republic of Moldova), a tributary of the Prut River, whose lower course and associated alluvial ecosystems, including the "Pădurea Domnească" Nature Reserve, suffer from severe water deficits and ecological fragmentation.
Our research evaluates the degradation caused by the "barbaric" anthropogenic interventions of the 1960s-1970s, which included riverbed channelization, meadow drainage, and the construction of over 140 ponds/storage lakes. These actions, coupled with shifting precipitation patterns, have disrupted the natural flood-pulse essential for wetland health.
The core of this paper proposes a strategic framework for Ecosystem Restoration based on: naturalizing the runoff - reassessing the hydrological potential to ensure ecological flows that sustain riparian forests and meadows; hydrological re-connectivity - evaluating the decommissioning or sustainable management of obsolete hydraulic structures to restore the river-floodplain continuum; NbS implementation - utilizing natural flood management and reforestation of riparian buffers to mitigate hydrological extremes (drought and flash floods).
By integrating climate change scenarios with historical hydrological modeling, we provide a technical roadmap for the revitalization of the Camenca's lower course. This approach demonstrates how Nature-based Solutions can shift the management paradigm from "water control" to "ecosystem-based resilience," ensuring the long-term survival of the Prut River's unique biocultural landscapes.
How to cite: Dilan, V. and Bejenaru, G.: Nature-based Solutions for Restoring Hydrological Connectivity in Small River Basins: The Case of the Camenca River and "Pădurea Domnească" Reserve, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19723, https://doi.org/10.5194/egusphere-egu26-19723, 2026.
For a practice oriented field study, a region with the climatic conditions expected in future in the viticultural region of Mainfranken located in Lower Franconia, Germany, is sought. The field study conducted by the Bavarian State Institute for Viticulture and Horticulture (Bayerische Landesanstalt für Weinbau und Gartenbau, LWG) aims to select and test scions of the typically Franconian grapevine variety Silvaner for cultivation under the more difficult conditions caused by climate crisis until the end of the 21st century.
To that end, climate analogs for four vineyards are calculated based on on-site station data as well as gridded observational data for the locations in comparison. The two data sources are each used for bias correction of a multi model ensemble of regional climate projections of CMIP5 based CORDEX runs. Standardized Euclidean distance calculated
For the combination of 30 climate indices selected in cooperation with the experts at LWG is used to derive the analogs. Alternatively, the scores of the major principal components of the indices are utilized for analog search in order to reduce the redundancy between the multitude of indices. The aim is to cover the aspects of the climate relevant to viticulture. The search for analog regions is conducted in the European domain based on E-OBS data.
The results for the indices themselves show three clusters independent of the choice of the vineyard and the data set for adjusting future data: Lot Valley and Lyon in France and Belgrade in Serbia.
Main analog regions for the vineyards’ mesoclimate expected at the end of the 21st century calculated using redundancy reduction with the principal component analysis are located in the region of Belgrade in Serbia, at the Romanian-Bulgarian border in the Region of Vratsa and Krasnodar Krai in the North Caucasus Region of Russia.
The study is part of the project BigData@Geo 2.0 co-funded by the European Regional Development Fund which aims to strengthen and support small and medium-sized enterprises in agriculture and silviculture in the face of the climate crisis.
How to cite: Hofmann, A., Keupp, L., Ziegler, K., and Paeth, H.: Analog climates for Franconian viticulture – Using in depth principal component analysis and a multitude of indicators, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11307, https://doi.org/10.5194/egusphere-egu26-11307, 2026.
Sensitivity to changes in climate conditions is a key component in the Climate Vulnerability and Risk Assessment (CRVA) of economic sectors and other assets. According to the AR6 IPCC Dictionary, Vulnerability is a component of Risk and is defined as: “The propensity or predisposition to be adversely affected. Vulnerability encompasses a variety of concepts and elements, including sensitivity or susceptibility to harm and lack of capacity to cope and adapt.”. Sensitivity is defined as “The degree to which a system or species is affected, either adversely or beneficially, by climate variability or change…”; while the latest can be estimated by change in Climatic Impact-Drivers (CIDs) that are “Physical climate system conditions (e.g., means, events, extremes) that affect an element of society or ecosystems…”
This conceptual framework was applied in the EU-funded APENA3 project ”Strengthening the capacity of regional and local administrations for implementation and enforcement of EU environmental and climate change legislation and development of infrastructure projects”, where Component 3 focused on the development of climate adaptation strategies and implementation plans for three pilot oblasts in Ukraine. As these strategies were intended to serve as guidance for other regions and to contribute to the future National Adaptation Plan, the selection of economic sectors and methodological approach was aligned with EU policy priorities and IPCC definitions.
In total, 12 main economic sectors were assessed (16 including subsectors): agriculture (crop farming and livestock), forestry, biodiversity and ecosystems (terrestrial and freshwater), water management, fisheries and aquaculture, tourism (recreation and travel, ski, and beach), land and water transport, energy infrastructure, health, built environment, disaster management, and cultural heritage. Coastal areas were additionally considered.
Sectoral sensitivity was quantified using weighting coefficients for 32 CIDs grouped into five IPCC categories: heat and cold, wet and dry, snow and ice, wind, and coastal. Weighting coefficients were derived through structured expert workshops involving sectoral specialists and reflect comparative expert judgement on sector susceptibility to changes in each CID. The methodology required that the sum of weighting coefficients for each sector equalled 10 arbitrary units, ensuring internal consistency, comparability across sectors, and the development of unified sensitivity matrices for CRVA applications.
As an example, we will present results based on the obtained sensitivity for CRVA of crop farming and animal husbandry across Ukraine, developed within the EU4ClimateResilience project, co-funded by the EU and the German Federal Ministry for the Environment, Climate Action, Nature Conservation and Nuclear Safety (BMUKN), and implemented by the Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH and the Organisation for Economic Co-operation and Development (OECD). The same sensitivity methodology was also applied to the CRVA of four transport modes: road, railway, aviation, maritime and inland waterway.
By definition, sectoral sensitivity to changes in CIDs is independent of geographical location. Consequently, the obtained sensitivity coefficients are scalable and transferable, allowing application of the methodology to CRVA exercises in other regions and countries with comparable economic sectors.
How to cite: Krakovska, S., Kryshtop, L., and Shum, I.: Sensitivity of economic sectors to changes in climatic impact-drivers on example of the EU-funded project APENA3 for the development of climate adaptation strategies in Ukraine, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14013, https://doi.org/10.5194/egusphere-egu26-14013, 2026.
