In late October 2025, the Norwegian Centre for Climate Services (NCCS) will launch a new national climate assessment report for Norway, commissioned by the Norwegian Environment Agency. Alongside the report, we will release a dataset featuring national daily climate and hydrological projections, including a comprehensive set of climate indicators. These indicators reflect projected changes relative to the current normal period (1991–2020), for both the mid-century (2041–2070) and end-of-century (2071–2100) periods. 

The national projections are based on three emission scenarios: RCP2.6 (low), RCP4.5 (medium) and SSP3-7.0 (high). Due to the unavailability of downscaled ensembles of SSP-scenarios representing low and medium emissions from EURO-CORDEX, these are not included. For climate adaptation, the Norwegian government recommends basing assessments on a high emission scenario. Accordingly, the report places particular emphasis on results from the high emission scenario.

In this presentation, we offer a sneak peek of key findings from the report, including analyses of past and current climate conditions, hydrological normals, and projected future changes in climate, hydrology and effects on natural hazards. Under the high emission scenario, the mean projected temperature increase for mainland Norway is 3.4 °C (2071–2100 relative to 1991–2020). Precipitation is projected to increase by 11 %, and runoff by 10 %. 

Compared to the previous national climate assessment report (Hanssen-Bauer et al., 2015), the current ensemble displays a smaller projected temperature increase. This is due to both the lower radiative forcing in SSP3-7.0 compared to RCP8.5, and a shorter period between the reference and the end-of-century period. While the projected precipitation increase is also more moderate, the increase in runoff exceeds that of the previous report. 

Additionally, we will briefly outline plans for data distribution, outreach, and future work related to this updated national climate knowledge base. Specifically, we will highlight ongoing efforts to tailor climate information for Norwegian municipalities, emphasising co-development and user involvement throughout the process.

References:

Hanssen-Bauer et al., 2015: Klima i Norge 2100. Kunnskapsgrunnlaget for klimatilpasning oppdatert i 2015 (in Norwegian). NCCS report 02/2015.

How to cite: Dyrrdal, A. V., Hygen, H. O., Nilsen, I. B., Mayer, S., Hanssen-Bauer, I., Dobler, A., Wong, W. K., Huang, S., Tunheim, K., Garvin, K., Lutz, J., and Tajet, H. T. T.: New national projections and climate assessment report for Norway, EMS Annual Meeting 2025, Ljubljana, Slovenia, 7–12 Sep 2025, EMS2025-347, https://doi.org/10.5194/ems2025-347, 2025.

Deutscher Wetterdienst provides climate services for Germany, especially in the scope of climate adaption. We will present our processing workflow, including quality assessment, bias-adjustment, statistical downscaling, and our resulting products that will support the introduction of a new climate projection ensemble in 2026.

Current products and consultancy are based on EURO-CORDEX CMIP5 simulations. However, in the last years one challenge has been that national and federal agencies in Germany use different ensembles due to various reasons.

In close coordination with these partners we have developed a workflow to create a new consistent national ensemble based on CMIP6 to provide climate services for climate adaption in Germany. Following a technical data check, a three-step quality assessment, progressing from a global to a regional and finally a local scale. The assessment is based on three pillars: the evaluation of global teleconnections, circulation patterns over Germany and the distribution of temperature and precipitation over Germany and its subregions. Each GCM-RCM combination is assigned a quality index to facilitate the selection of a reference ensemble, omitting simulations with insufficient agreement with observational data. The new ensemble will then be further statistically downscaled and bias-adjusted. We will derive a range of products from this data, including climate indicators and a new web service for visualization and data access.  Since not all partners are equipped to process large volumes of data, we will also provide a smaller ensemble that preserves the full ensemble range by excluding highly similar members. All data, along with a quality assessment for each ensemble member, will be made available to impact modelers and other users.

How to cite: Leps, N., Rybka, H., Mannig, B., Dalelane, C., and Paxian, A.: Strategy for providing climate services for Germany based on SSP EURO-CORDEX simulations, EMS Annual Meeting 2025, Ljubljana, Slovenia, 7–12 Sep 2025, EMS2025-171, https://doi.org/10.5194/ems2025-171, 2025.

The development of new generations of climate projections for use in the IPCC assessments is a core part of climate science.  But while new datasets are always welcome, they also present challenges for the operationalisation of climate services. For example, how should the upcoming CORDEX-CMIP6 ensemble be incorporated into an existing climate service based on CORDEX-CMIP5? Should there be a 1:1 replacement of the older data? At what point is the new ensemble sufficiently large to justify the switch? And what do we do with the old dataset? Ideally we would blend the two ensembles into one larger super-ensemble, but this approach is hampered by the use of different generations of emissions scenarios (e.g. RCPs vs SSPs). Here we introduce an approach for blending ensembles from different generations, with differing emissions scenarios, based on global warming levels. We borrow the approaches employed in the statistical attribution community, where a local response variable (e.g. frequency of local extreme temperatures or precipitation) is modelled as a function of the global temperature change: the use of global warming levels is particularly relevant here, as it removes the effect of differing emissions-scenarios. We extend this approach further through the use of a mixed-effects modelling framework, where each individual model is considered as a deviation from a fundamental underlying response. We show using CMIP ensembles that our approach is able to reproduce the characteristics of a single ensemble, to merge multiple ensembles together, and to adequately predict “out-of-sample” ensembles that the model has not been trained against. The use of a statistical framework also allows statistical inference and testing to be performed, and we show how cases where the approach breaks down can be automatically highlighted. Finally, we show how the approach can be applied in a climate-service context, and propose a scheme that blends the existing CORDEX-CMIP5 ensemble with new members from the CORDEX-CMIP6 family to produce a climate service that uses both datasets to the fullest extent.

How to cite: Payne, M. R., Thejll, P., and Christensen, O. B.: Global Warming Levels as a basis for merging different generations of CMIP and CORDEX ensembles, EMS Annual Meeting 2025, Ljubljana, Slovenia, 7–12 Sep 2025, EMS2025-224, https://doi.org/10.5194/ems2025-224, 2025.

Following the catastrophic floods that struck Slovenia in 2023, public awareness of the impacts of climate change has significantly increased. As a result, there is growing demand for information on future climate extremes—particularly changes in extreme precipitation, and to a lesser extent, extreme temperatures. The majority of these requests come from engineers who need to design climate-resilient infrastructure. More recently, municipalities—either individually or as regional consortia—have also begun seeking assessments of their resilience to future climate change.

In 2016, the Slovenian Environment Agency (ARSO) launched the project Assessment of Climate Change by the End of the 21st Century, analysing regional climate model outputs from the Euro-CORDEX project. The analysis included three Representative Concentration Pathways (RCPs): RCP2.6, RCP4.5, and RCP8.5. For each scenario, we evaluated an ensemble of models to calculate projected changes and their statistical robustness for various climate variables, focusing on future 30-year periods relative to the 1981–2010 reference period. For temperature and precipitation, we also assessed trends in extremes using the Generalized Extreme Value (GEV) distribution.

Trends in annual maximum values were used to estimate changes in extreme one-day precipitation and temperature (both maximum and minimum), based on the GEV location parameter. However, we found that one-day precipitation trends tend to underestimate the changes in shorter-duration events (e.g., 5–30 minutes). To better estimate changes in sub-daily extreme rainfall, we now derive trends from mean temperature changes and apply the Clausius–Clapeyron relation. These temperature trends are calculated from annual averages using simple linear regression, rather than from extremes or GEV analysis.

When users request an analysis, they typically provide location coordinates, a future target year, and a preferred RCP scenario. Most analyses are focused on projections to 2050 under RCP4.5, though some users request longer-term assessments under RCP8.5. For temperature, the most common request is the projected change in the 50-year return level of maximum temperature. For precipitation, users frequently request 100-year return levels for one-day and sub-daily extreme rainfall (e.g., 5, 10, 15, 20, 30 minutes). Present-day conditions are derived from meteorological station data interpolated to a ~1 km grid. We then apply model climate trends to these current extremes to estimate future values.

Approximately 90 % of requests involve extreme precipitation projections, followed by 7 % for municipal or regional climate impact assessments, and the remaining 3 % for extreme temperature projections.

How to cite: Medved, A.: Preparation of Tailored Climate Projection Analyses for Climate Change Adaptation in Slovenia, EMS Annual Meeting 2025, Ljubljana, Slovenia, 7–12 Sep 2025, EMS2025-133, https://doi.org/10.5194/ems2025-133, 2025.

We see unprecedented weather causing widespread impacts across the world. In this talk, we provide an overview of methods that help anticipate unprecedented weather hazards that can contribute to stop being surprised. We then discuss disaster management and climate adaptation practices, their gaps, and how the methods to anticipate unprecedented weather may help build resilience. We stimulate thinking about transformative adaptation as a foundation for long-term resilience to unprecedented weather, supported by incremental adaptation through upgrading existing infrastructure, and reactive adaptation through short-term early action and disaster response. Because in the end, we should take responsibility to build resilience rather than being surprised by unprecedented weather.

How to cite: Kelder, T., Heinrich, D., Coughlan de Perez, E., Klok, L., Slater, L., Thompson, V., Dumont Goulart, H. M., Wilby, R. L., Stephens, L., Hawkins, E., de Vries, H., van der Wiel, K., Suárez Gutiérrez, L., Fischer, E., Burt, S., Carmona Baez, A., van Bueren, E., Schipper, L., and van den Hurk, B.: How to stop being surprised by unprecedented weather, EMS Annual Meeting 2025, Ljubljana, Slovenia, 7–12 Sep 2025, EMS2025-728, https://doi.org/10.5194/ems2025-728, 2025.

Future climate change is likely to cause an increase in climate-related risks across all regions and sectors of society. Quantification and a better understanding of how to adapt to changes are crucial for regions and municipalities to be able to cope with current and future climate risks. However, in many areas of Europe, the capability to perform multi-hazard climate risk assessments is limited due to a lack of resources and knowledge. The EU Horizon Europe project CLIMAAX (CLIMAte risk and vulnerability Assessment framework and toolboX) addresses this by providing financial, analytical and practical support to regions looking to improve their regional Climate Risk Assessment (CRA) and management plans. The project has developed a comprehensive online Handbook comprising a harmonised CRA framework and practical workflows to quantify climate risks from floods, heavy rainfall, drought, extreme heat, wildfire, windstorms and snow. 

The heart of the CLIMAAX Handbook is a Jupyter ecosystem. The Handbook website is implemented as a JupyterBook and risk workflows as Jupyter notebooks, executable in a collaborative JupyterHub cloud environment. All tools are open-source and available for anyone to use. The project participants also have a wide range of support resources available, including video tutorials, documentation, drop-in sessions, and online support, all to create a community of practice where experiences are shared between the participants.

The project currently supports 69 European regions in performing CRAs in separate steps. The first step is screening the most critical climate risks and how they might affect each region, as well as identifying the most important stakeholders and their capability to adapt to climate change. The second step is to conduct more detailed assessments, bringing in local data on hazard, vulnerability and exposure. The final step is to provide an adaptation plan to mitigate the risks for the future. This presentation will summarise the results of the first screening of risks across the European regions and provide lessons learned from implementing the framework and workflows.

How to cite: Wetterhall, F., Polster, C., Vuckovic, M., and Shtivelman, A.: The CLIMAAX handbook - an online tool for regional climate risk assessments, EMS Annual Meeting 2025, Ljubljana, Slovenia, 7–12 Sep 2025, EMS2025-685, https://doi.org/10.5194/ems2025-685, 2025.

The global climate is changing, and Bangladesh is not spared. Bangladesh Meteorological Department (BMD) and Norwegian Meteorological Institute (MET Norway) have collaborated since 2011, and in 2016 we co-published “Climate of Bangladesh”, and in 2024 we published “Changing climate of Bangladesh”. The same cooperation has resulted in a new report that will be published in the June of 2025 named “Future climate of Bangladesh”. The new report goes beyond the baseline of today's climate and detected changes in the Bangladeshi climate, focusing on the future climate of Bangladesh as described in climate projections.

The main objective of this study is to establish a common data set for studies of the potential effects of climate change on Bangladesh in this century, and thus establish a common ground for climate adaptation. To achieve this we analysed the NEX-GDDP-CMIP6 dataset for a region covering Bangladesh. In this we uncovered that some of the models had a clear bias for the region, these models were excluded from the rest of the study, and thus left an ensemble of 23 models for the study. There are two major choices one has to perform before analysing the future climate data: Choice of scenarios and time periods. The chosen scenarios are: SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 thus including both extreme low end scenarios and high end scenarios, with two more interim scenarios. For time periods the following was chosen: Historic reference 1985-2014, Near future 2041 - 2070, and Far future 2071 - 2100.

The NEX-GDDP simulations show a warming in all seasons, with an increase in the daily mean temperature of +1 ℃ to +2 ℃ by the middle of the century (2041 - 2070) and +1.5 ℃ to +4.5 ℃ by the end of the century (2071 - 2100), depending on the season and region, assuming the high emission scenario SSP3-7.0 The number of days of heat waves (daily maximum temperature exceeding 36 ℃) is expected to increase considerably spreading out from the pre-monsson season to all season.  

Besides temperature and precipitation indexes a literature review on sea level rise in the bay of Bengal was included, and some information on impact on e.g. agriculture and health was included. These examples of impact should be considered exactly this, examples on impacts.

How to cite: Hygen, H. O., Parding, K., Rashid, Md. B., Sultana, A., and Hassan, S. M. Q.: Future climate of Bangladesh, EMS Annual Meeting 2025, Ljubljana, Slovenia, 7–12 Sep 2025, EMS2025-413, https://doi.org/10.5194/ems2025-413, 2025.

Due to increasing temperature, the growing season is expanding in Norway, with the exception of glaciers and high mountains.The growing season starts earlier or ends later in the year, when temperatures during night can be low. Therefore, a longer growing season, despite a decreasing number of frost days in a generally warmer climate, may lead to an increased risk of frost early or late in the growing season.

Frost early in the growing season can be a risk for several plant species. There have been incidents in Norway where fruit farmers have had their crops destroyed after an unusually warm period followed by a cold spell.

This is the first study on frost days at the start of the growing season where all of mainland Norway is included. 

To study frost days in the growing season, observation based gridded data at daily resolution is used for two historical normal periods (1961-1990 and 1991-2020) with a 1 km grid resolution  covering mainland Norway. Additionally, bias-adjusted daily climate projections are analysed for the periods 2041-2070 and 2071-2100, following three different future  climate scenarios (RCP2.6, RCP4.5 and SSP3-7.0). 

Frost in the growing season is a risk factor in the lower areas in Southern Norway today, with the highest risk in the southeast. Changes between the historical normal periods show the highest increase of days along the coast in the west of Southern Norway. This is the same area where the growing season has increased the most. Future scenarios show an even higher risk of frost days in the growing season along the coast of Norway except for the northern most areas. Again the increase of the risk is highest in the same areas where the growing season is calculated to increase the most.

This work is done within the Norwegian Centre for Climate Services  (NCCS). NCCS provides information for climate adaptation and helps municipalities to be robust in a changing climate. Information on the changing growing season and risk of frost days in the growing season can be of help to farmers and used as background information for climate adaptation. All authors in this abstract are connected to NCCS.

How to cite: Tajet, H. T. T., Gangstø, R., Hanssen-Bauer, I., Dobler, A., and Hygen, H. O.: Frost days in start of growing season for Norway, EMS Annual Meeting 2025, Ljubljana, Slovenia, 7–12 Sep 2025, EMS2025-629, https://doi.org/10.5194/ems2025-629, 2025.

How to cite: Guerrini, F., Burgues, J., Rubi, P., and Rodriguez-Pinilla, M.: A data-driven methodology for assessing urban runoff pollution risk under climate change scenarios , EMS Annual Meeting 2025, Ljubljana, Slovenia, 7–12 Sep 2025, EMS2025-373, https://doi.org/10.5194/ems2025-373, 2025.

The Restore4Life Web Platform is being developed to support wetland restoration across the Danube Basin by integrating Earth observation, in situ monitoring, stakeholder knowledge, and decision-support tools. Designed under the Restore4Life Horizon Europe project, the platform provides a dynamic interface for data visualization, stakeholder engagement, and evidence-based policy and restoration planning. Building on lessons from eLTER and LifeWatch infrastructures, the platform functions as a centralized hub for identifying, prioritizing, and monitoring potential and ongoing wetland restoration actions. It incorporates historical land use and wetland distribution data, real-time hydrological and climatic inputs, and high-resolution satellite imagery (e.g., Copernicus Sentinel missions), enabling integrated spatial-temporal analysis at multiple scales.

Key components include: a) Stakeholder & Policy Dashboard – Visualizing restoration progress, land use change, and ecosystem service indicators relevant for policy targets (e.g., EU Biodiversity Strategy, Nature Restoration Law); b) Decision Support System (DSS) – Supporting the selection and prioritization of wetland reconstruction areas based on ecological, hydrological, and socio-economic criteria; c) Citizen Science & Community Tools – Enabling participatory mapping, monitoring, and knowledge exchange, with a special focus on local communities and landowners;
d) Business & Finance Tools – Connecting restoration initiatives with ecosystem-based financing, carbon credits, and nature-based enterprise models; e) Learning & Communication Hub – Providing access to case studies, good practices, training modules, and outreach materials;
f) Interoperable Data Integration – Ensuring compatibility with Copernicus, national monitoring systems, and European environmental infrastructures (e.g., LifeWatch, eLTER, ICOS). Designed around FAIR (Findable, Accessible, Interoperable, Reusable) data principles, the Restore4Life platform aims to foster cross-sectoral collaboration, transparent data sharing, and adaptive ecosystem management. It acts as a strategic enabler of large-scale, science-based wetland restoration in line with EU ecological and climate resilience goals.

This article was developed as part of Restoration of wetland complexes as life supporting systems in the Danube Basin (Restore4Life)  funded by the European Commission Horizon Europe programme (101112736). Restore4life is part of the EU Mission: Restore our Ocean and Waters which aims to protect and restore the health of our ocean and waters through research and innovation, citizen engagement and blue investments.

How to cite: Adamescu, M., Cazacu, C., Cheval, S., Craciunescu, V., Dumitrescu, A., Micu, D., and Racoviceanu, T.: Restore4Life Web Platform: A Decision-Support and Engagement System for Wetland Restoration Across the Danube Basin, EMS Annual Meeting 2025, Ljubljana, Slovenia, 7–12 Sep 2025, EMS2025-542, https://doi.org/10.5194/ems2025-542, 2025.