Consistent and up-to-date national climate scenarios are an indispensable basis for public and private sectors to plan and design adaptation and mitigation measures. Regional or even local assessments of future climate change are therefore an important climate service. The latest edition of Swiss Climate Scenarios CH2018 was released in 2018 (www.climate-scenarios.ch). Overall, a further increase of mean temperatures is projected, accompanied by four highly impact-relevant facets: more intense and more frequent precipitation extremes, more intense and more frequent hot extremes, drier summers, and snow-scarce winters. Since the release of the CH2018 scenarios, science as well as user needs have evolved. Scientific advances such as those documented in the latest IPCC report (AR6) have been published and new high-resolution convection-permitting climate models have been developed. Thanks to our ongoing user engagement and consultancy, a more detailed landscape of user requirements was established. In the recently launched project Klima CH2025, identified gaps in the existing climate scenarios and additional user requirements will now be addressed. Similar to previous climate scenario generations, the new project is a joint effort involving the Federal Office of Meteorology and Climatology MeteoSwiss, ETH Zurich and further partners from academia and administration. The results of Klima CH2025 will be based on the existing CH2018 scenarios and will extend them with new scientific insights and products. Two main scientific questions will be addressed: 1) How can we better merge observations and model-based climate scenarios in order to provide consistent and temporally seamless information to serve user needs?; 2) What is the projected evolution of impact-relevant climate extremes in Switzerland and what are their underlying processes? Guided by these two questions, we will develop a range of new products, engage with stakeholders, plan active communication and dissemination. In this presentation, the general approach of Klima CH2025 as well as first results will be presented.

How to cite: Muelchi, R., Booth, L., Croci-Maspoli, M., Fischer, E. M., Knutti, R., Kotlarski, S., Rajczak, J., Schär, C., Scherrer, S. C., Schnadt Poberaj, C., Schwierz, C., Seneviratne, S. I., and Zubler, E. M.: Swiss climate scenarios – an ongoing journey, EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-146, https://doi.org/10.5194/ems2023-146, 2023.

Klimaszenarien.AT is an initiative started by 8 scientific and climate service partners in Austria with the aim of developing new national climate scenarios for Austria until 2026 („ÖKS26“).  The main goal is to consider both, a sound scientific basis at the latest state of research and users’ specific requirements concerning climate data and information. Activities of the initiative are, to a large part, carried out in funded research projects.

The workplan of Klimaszenarien.AT roughly defines two stages: The first phase (2021-2025) focuses on the generation of the regional climate scenario data , while the second phase (2023-2026) is dedicated to distillation and communication of climate information for stakeholders and users.

Stage one uses multiple sources of climate projection and reference data from global to regional scales and addresses specific research topics, such as the understanding of atmospheric processes or the linkage of large- and regional-scale impacts of climate change, with a special focus on mountainous areas.

Stage two focuses on the construction of climate information for various user contexts, in terms of main statements and on applicable formats for visualization and provision of the climate information. The initiative aims at serving the principle of use: The derived climate information shall not only be „useful“, i.e. reliable and relevant, but also „useable“, i.e. findable and accessible and, finally, „used“ by public, media, decision-makers and advanced users.  Hence, also the experiences of users with the predecessor, the Austrian „ÖKS15“ scenarios, are gathered within the framework of a comprehensive stakeholder process.

The two phases are closely related to each other and overlap in time. The goal of this concept is that the final outputs, i.e. the generic scenario data as well as the information and products derived therefrom, are understood as the fruit of collaborative efforts by the various actors.

The process of generating „ÖKS26“ is further related to a number of international activities, such as the (EURO-)CORDEX project and the D-A-CH-scenario project. The latter is a cooperation of the national weather services DWD (D), GeoSphere Austria (A) and MeteoSwiss (CH) with the aim to harmonize the new generations of national climate scenarios to the greatest possible extent and to avoid transborder inconsistencies.

How to cite: Schellander-Gorgas, T. and the ÖKS Steering Committee: „Klimaszenarien.AT“ - a strategy to new national climate scenarios in Austria, EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-236, https://doi.org/10.5194/ems2023-236, 2023.

The societal needs for updated and downscaled climate projections for adaptation action are well documented. These needs range from key information and recommendations, such as fact sheets targeted at municipalities, to geographic information and even access to the full datasets of climate projections. 

All the while the climate research community is producing global and regional projections of increasingly higher quality. More and more national climate service instances produce further downscaled and bias-adjusted national projections, sometimes even separate hydrological projections, to produce more locally relevant information. 

The sheer amounts of data are enormous and require significant capacity for storage and data transfer. This leads to climate and climate impact scientists spending a significant amount of time handling the data, and this effort is often duplicated even in the office next door.

To alleviate this problem, the Norwegian government has granted MET Norway a project to create an integrated infrastructure for storing, processing, and distribution of downscaled and bias-corrected climate projections. This infrastructure, and the project, is called the Climate Mill, Klimakverna in Norwegian. The project has a 4 year timeframe, starting 2023 with planning and mapping of technologies. One of the keystones in the Climate Mill is FAIR metadata that follows the data through the entire process. This metadata will ensure compatibility with  Geonorge, a national portal for geodata, thus simplifying the distribution. The infrastructure will rely on existing technologies including cloud solutions for storage and processing. With this we aim to make climate projections easier to produce, and ultimately easier to use for adaptation purposes.

How to cite: Tunheim, K., Verpe Dyrrdal, A., and Hygen, H. O.: The Climate Mill, an infrastructure for processing climate data, EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-263, https://doi.org/10.5194/ems2023-263, 2023.

There is a distinct need for climate information and climate projections in society. These needs cover a wide range of use from key information on expected changes to the full range of projections in terms of data.

In climate research the realization that one needs a wide range of projections based on combinations of different models (e.g. combinations ofGCM and RCM) to create a wide ensemble of futures is necessary. This leads to enormous streams of data. In Norway, the new set of national projections will include about 550 simulations with various combinations of emission scenarios, variables, model combinations, bias adjustments methods, hydrological models etc.

As stated above there is a wide range of needs from simple requests to complex impact modelers capable of using the full model output. The Norwegian Centre for Climate Services (NCCS) today serves either end of this spectrum fairly well. NCCS produce Climate fact sheets on a county level, which serve the simpler needs, but also provide the full model ensemble. But the interim users that need more than simple summaries and are incapable of using the full ensemble are not served sufficiently. The result can be, as was shown at EMS 2022, basically to use a single realization for future climate in impact research, despite the access to large ensembles.

Climate services, as e.g. provided by NCCS, should provide user-adapted pre-selection of climate projections; so-called representative projections. To do this in the right way, user needs should be better understood and appropriately grouped. At this stage NCCS do not provide such representative projections, but we would like to raise the discussion on how to go forward.

How to cite: Hygen, H. O. and Dyrrdal, A. V.: User adapted climate projections, EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-214, https://doi.org/10.5194/ems2023-214, 2023.

The climate is continually changing; therefore, making appropriate adaptation and mitigation decisions is essential. Accurate data is paramount for quantifying climate change impacts and performing risk assessments to support decision-making. Nowadays, climate models are the primary tool for understanding and projecting climate variability. However, their outputs systematically differ from observations, especially for climate variables characterized by strong stochasticity (e.g. precipitation). An ongoing problem concerning climate models is the “drizzling” bias. Climate models tend to overestimate the frequency and duration of rainfalls resulting in the underestimation of their intensity and severity. Due to that fact, climate models significantly underestimate consecutive dry days and overestimate wet days. The adjustment of these biases is a critical process that should precede the use of data. This work proposes a novel statistical method, the Q-GAM (quantile generalized additive models), to bias-correct daily precipitation values over Europe. This task is challenging due to the stochasticity that characterizes this variable, especially on high temporal resolution. The Q-GAM method combines Quantile Mapping (QM) and Generalized Additive Models (GAMs). It is an approach that preserves the advantages of the well-established QM and overcomes its limitations using the flexibility of GAMs. Hence, Q-GAM can significantly increase the accuracy of model-simulated rainfall, maintaining its variability and correcting the number of dry days, overcoming the “drizzling” bias. This is critical for robust and reliable impact analysis. The specific aim of this study is to use Q-GAM bias-corrected model projections of precipitation for quantifying future changes in wet and dry spells across Europe. The duration of wet and dry periods is of great importance as dry spells can serve as indicators of drought and affects several aspects of everyday life (e.g. agriculture, health and economy) and builds the intraseasonal structure of water balance. Here, daily rainfall from three EURO-CORDEX climate models is used for the period 1981-2050. The historical period 1981-2005 is for training the bias adjustment method, while the data for 2006-2050 are corrected, and then the projected wet and dry spells are quantified. The future projections are made according to two climate scenarios: the optimistic RCP2.6 and the business-as-usual RCP8.6. The results show that global warming increases rain falling over short periods, likely triggering floods and/or landslides. Additionally, the improvement of dry spell probabilities detection results in an increasing trend of the duration and severity of drought in future. Furthermore, at a seasonal scale, dry spells are enhanced in future summers and are a temporal extension to transitional and moderate seasons.

How to cite: Lazoglou, G., Anagnostopoulou, C., Economou, T., Tzyrkalli, A., Zittis, G., and Lelieveld, J.: Calculation of future Wet and Dry spells duration in Europe, using bias corrected data from the Q-GAM method., EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-15, https://doi.org/10.5194/ems2023-15, 2023.

Observed data of extreme rainfall occurrence in Ireland are available from approx. 30 stations over periods ranging from about 30 to 70 years.  They are provided as tables of occurrence dates and magnitudes of 9 different metrics, from “r4in15” (4 mm in 15 minutes) to “r30in24h” (30 mm in 24 hours).  These events are too few and too sparse to be treated with non-parametric statistics.  However, they are all “peak over threshold” (POT) events, and so the well-developed theories of POT statistics applies to them.  In particular, the number of such events in any given time period follow a Poisson distribution (which needs only one parameter, the mean), while the exceedances (i.e., magnitudes above threshold) follow a generalized Pareto distribution (which formally needs 3 parameters, but in practise only 2 need to be determined). 

As climate is projected to change in the future, our basic assumption is that the number of POT events (Poisson distribution) will change, while the exceedances (Pareto distributions) will remain the same, only represented by different numbers of samples.  Since the Poisson distribution is determined by just one parameter (the mean), the only quantity needed to fully characterize the nature of future intense rainfall events are projections of the mean of such events. 

Meanwhile, future climate projections (e.g., from CORDEX) are typically available on daily timescales, so the problem reduces to finding a robust relationship, whether physical  (based e.g., on a Clausius-Clapeyron scaling) or statistical (based, e.g., on the tails of frequency distributions)  between each of the 9 intense rainfall metrics and the daily values of standard surface variables under future climate projections.  Different options are explored, and results are shown based on future projections from the TRANSLATE project, as functions of different future emission scenarios. Typically, large increases in the frequency of all 9 metrics are projected regardless of the exact relationship assumed between the intense rainfall events and the frequency distributions of daily precipitation (or temperature).  Results are best shown as frequency distributions rather than single number percentage changes.

How to cite: O'Brien, E. and Wang, J.: How might the occurrence frequency and intensity of extreme rainfall events in Ireland change in projected future climates?, EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-313, https://doi.org/10.5194/ems2023-313, 2023.

According to the latest IPCC report, under the ongoing climate change, extreme weather events in Western Continental Europe, including heatwaves and droughts, are becoming more prolonged, intense, and frequent, and are set to strengthen in a progressively warmer climate. Total changes observed in these extreme events can be discriminated between the relative contributions of dynamical changes – change in likelihood of weather patterns  – and of thermodynamic changes. While the former remains uncertain in future climate projections, the latter is more certain, with a robust and ubiquitous rise in future land-surface temperatures.

To separate and analyze both contributions, we employ the nudged storyline approach, in which our CMIP6 coupled climate model (AWI-CM1) is nudged towards the observed large-scale free-troposphere dynamics using different climate background conditions and initial states. As a result, the same weather conditions, including jet stream and blockings, are simulated in different climates (pre-industrial, present and future 2, 3 and 4 ºC warmer climates). This methodology provides a very efficient manner of making the consequences of climate change more comprehensible to non-experts and experts alike, as extreme events fresh in people's memory are simulated in different climates with just moderate computational resources.

This configuration reproduces recent extreme events, like the 2019 or 2022 European heatwaves and the ongoing European drought. Our simulations reveal an intensification of these hot and dry extreme events both from preindustrial to present (attribution) and from present to warmer (projection) climates. Moreover, taking advantage of our methodology, observed and projected changes can mainly be attributed to thermodynamic changes, with dynamical changes playing a minor role.

How to cite: Sánchez Benítez, A., Athanase, M., Jung, T., and Goessling, H.: Storylines simulations suggest intensification of recent European droughts in warmer climates., EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-293, https://doi.org/10.5194/ems2023-293, 2023.

Climate change is one of the greatest challenges of our time. Despite all scientific findings on climate change, the current measures to reduce GHG emissions are too small to keep the global warming well below 2 K, preferably at 1.5 K.  “Policies currently in place point to a 2.8°C temperature rise by the end of the century.” [1] Therefore, in addition to measures for climate protection, strategies and measures for adaptation to climate change are needed to mitigate the consequences of climate change and avert damage.

To date, planning decisions, e.g., infrastructure, urban and regional planning, take into account the climate of the past in the relevant standards. In fact, today’s planning often has an impact over several decades and cannot be easily corrected (e.g., railroad embankments, sewage systems). Thus, the climate relevant to the lifetime of the planning realisation must be considered in standards to minimize damage caused by future climate. This is also true for existing infrastructure that has to be adapted to future climate (e.g., depth of water pipes; higher ground temperatures needing more chlorination for sanitary reasons). To facilitate the adjustment to a changing climate for the user of standards and perform adaptation without expert knowledge on climate, the Association of German Engineers (VDI) has decided to review existing standards and standards in progress with regard to climate resilience.[2] The aim is to modify standards, if necessary, by including the climate relevant for the lifetime of the planning realisation. This sounds simple, but a number of questions has to be answered: “To which climate change do we need to adapt?”, “What is the lifetime of a planning realisation?”, “Which climate changes are relevant for this standard?”. The approach followed by VDI and some example answers are given. 

[1] UNEP: Emissions Gap Report 2022.
https://www.unep.org/resources/emissions-gap-report-2022 , last used 10.04.2023

[2] VDI: Strategien und Maßnahmen für eine klimaangepasste Zukunft.
https://www.vdi.de/themen/klima-innovation-anpassung (German only), last used 10.04.2023

How to cite: Schlünzen, K. H., Froehling, C., and Vondran, J.: On the way to adjust standards to future climate, EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-63, https://doi.org/10.5194/ems2023-63, 2023.

To design a building adapted to local climate requires a number of different climate indicators, one of them is design temperatures (DUT) for summer and winter. 

The classic definition of summer design temperature was the maximum temperature exceeded 50 hours a typical year, and for winter the coldest three day average temperature. Looking into different descriptions of the DUT, there are distinct discrepancies. One example is for DUT-winter, where some instances describe the three coldest consecutive days and others the DUT-winter as a return period (e.g. 30 year) based on observations, similar for DUT-summer where some define it as 50 consecutive hours, others as individual hours summed together.

The above uncertainty of definition is combined with the uncertainty of representation. The classic construction of DUT is based on observations from a representative station, interpolated to e.g. the municipality of interest. This method opens for the uncertainty of representation of the observational site and correctness for the interpolation. 

Standards Norway contacted MET Norway to update the values of the DUT summer and winter in Norway to be calculated for the latest normal period, 1991 - 2020. In this work a new method to calculate DUT summer and winter was proposed and accepted:

• Instead of using single observational sites as a base, national climate grids calculated on a daily basis at MET Norway covering the entire country with a 1x1 km resolution is used as a basis
• Instead of a single temperature representing e.g. a single day is a statistical based approach applied. The method that was selected was a Bayesian-GEV approach where the output was calculated for 1 to 5 days average for highest and lowest mean temperature, with return values for 2-200 years. 

This new approach resolves partly the challenge of representativity and interpolation by using robust and well documented spatial interpolation. The statistical approach also provides more well documented and robust statistics than the older approach. This approach creates a challenge since the new datasets represent something different than the older approach, and thus challenges the standard built on these datasets. 

The distribution of the datasets will be renewed. Previously one had to buy the datasets from e.g. Standards Norway or other commercial vendors, the new dataset will be distributed openly from MET Norway, and implemented in e.g. the API frost.met.no 

Besides the DUT, an extended information package containing daily temperature range and absolute humidity is calculated based on representative stations.

How to cite: Hygen, H. O., Grinde, L., Tajet, H. T. T., and Dokka, T. H.: Provision of design temperatures, EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-206, https://doi.org/10.5194/ems2023-206, 2023.

The increased risk of flooding due to global warming and subsequent heavy rainfall events in the Nordic-Baltic region call for recommendations directed at long-term planning. Climate change allowances are often based on expected changes in design precipitation as given by climate model simulations, and are used as a buffer on top of current design values to avoid a future increased damage potential as a consequence of climate change. We here compute expected changes in precipitation design values, so-called climate factors, for the Nordic-Baltic region, based on convection permitting simulations. These simulations have the advantage of explicitly resolving convection, which has been shown to be the main contributor to increased rainfall, and not explicitly resolving convection is a main source of error in modeled precipitation. We compute climate factors and assess their dependence on rainfall duration, return period, and geographical location, focusing on the summer (convective) season, short durations and the high emission scenario RCP8.5. We also compare these climate factors to those computed from a more conventional (not convection permitting) regional climate model ensemble.

We found higher climate factors for the longer return period, with only few exceptions, and distinctly higher climate factors going from daily to sub-daily durations. However, the different simulations give conflicting results for very short-duration rainfall (< 3 hours). The huge difference in the climate sensitivity of driving GCMs dominates the magnitude of estimated return levels. Our analysis is shaped by the high computational costs of running convection permitting models, resulting in a very limited ensemble representing a single emission scenario. The value lies in a holistic assessment of a combined dataset, with their different strengths and weaknesses, supporting the assessment of robust climate change allowances for heavy precipitation in the Nordic-Baltic region.

Reference: Dyrrdal et al., 2023. Submitted to Weather and Climate Extremes. 

How to cite: Dyrrdal, A. V., Medus, E., Dobler, A., Hodnebrog, Ø., Arnbjerg-Nielsen, K., Olsson, J., Thomassen, E. D., Lind, P., Gaile, D., and Post, P.: Changes in design precipitation over the Nordic-Baltic region as given by convection-permitting climate simulations, EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-322, https://doi.org/10.5194/ems2023-322, 2023.

Snow loads are an important consideration in the design of buildings. Particularly in parts of Norway where heavy snowfall is common, it is important to know the weight from snow on houses to avoid structural damage or collapse. National standards and building regulations have been focusing on snow loads since 1949, and these regulations have been revised several times. 

The Norwegian Meteorological Institute (MET Norway) produces daily interpolated data sets of precipitation and temperature with a 1*1 km resolution as part of our regular service. Data from 1957 - dd are included. These data sets are then used by the Norwegian Water Resources and Energy Directorate (NVE) to generate "Snow Water Equivalent" (SWE) interpolated data sets, grids, using a hydrological model. 

In this study, the SWE grids are  used to produce snow loads with a 50 year return period for Norway, for two different periods 1961-1990 and 1991-2020. Three different methods for calculating the 50-year return period of snow loads are compared. In addition, the old normal period, 1961-1990, is compared with the current normal period, 1991-2020. It is typically shown that the snow load decreases in the lower-lying areas and along the coast of Norway. In higher altitude areas and in parts of Northern Norway, where there still are cold winters, the snow loads have increased. 

Snow loads are also extracted for each municipality center in Norway, to compare to the current national snow loads standard. This method is suggested, and about to be adopted, for future use in the design of buildings in Norway.

How to cite: Tilley Tajet, H. T., Grinde, L., and Hygen, H. O.: Snow Loads in Norway, 1961-2020, EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-220, https://doi.org/10.5194/ems2023-220, 2023.

The DWD climate predictions website www.dwd.de/climatepredictions presents different climate predictions on a common website to support decision-making processes on different time scales: post-processed subseasonal prediction products derived from the IFS forecasts provided by ECMWF for the coming weeks and operational seasonal and decadal predictions of the German climate prediction system for the coming months and years.

The user-oriented evaluation and design of this climate service was developed in cooperation with users from various sectors (e.g. water, energy, agriculture or forestry) and is consistent across all time scales. The website offers maps, time series and tables of ensemble mean and probabilistic predictions in combination with their skill. The products are displayed for weekly, 3-month as well as 1- and 5-year temperature means and precipitation sums for different regions (world, Europe, Germany, German regions).

For Germany, the statistical downscaling EPISODES is used to reach high spatial resolution required by several German climate data users. A lead-time dependent bias correction is applied, and decadal predictions are recalibrated to improve drift and ensemble spread. We use the MSESS and RPSS to evaluate the skill of climate predictions compared to reference predictions (applied by users as an alternative to climate predictions), e.g. the ‘observed climatology’ or ‘uninitialized climate projections’. The significance is tested at a 5% level.

Different layers of complexity are presented: Within the ‘basic climate predictions’ section, a traffic light indicates if regional-mean predictions are significantly better (green), not significantly different (yellow) or significantly worse (red) than a reference prediction. Within the ‘expert climate predictions’ section, prediction maps show per grid box the prediction (via the color of dots) and its skill (via the size of dots). The co-development of this climate service with users from different sectors improves its comprehensibility and usability. Outlooks are regularly communicated, and user feedback loops are continuously performed to evaluate and improve this climate service.

Drought-related variables and indices such as the climatic water balance (precipitation minus potential evapotranspiration), SPI (standardized precipitation index) or SPEI (standardized precipitation evaporation index) are evaluated and will soon be included in the climate outlook. Cooperation work is ongoing to use climate predictions to forecast soil moisture and groundwater levels. Plans for future extensions of this climate service include multi-year seasonal predictions, multi-model predictions, large-scale and extreme indices (e.g. for ENSO, NAO, heat), and tools to further clarify the presented information (e.g. video clips or interactivity). Finally, we work on a time series combining observations, subseasonal, seasonal and decadal climate predictions and climate projections, the next step towards a seamless climate service for Germany.

How to cite: Paxian, A., Mannig, B., Tivig, M., Stanley, K., Ziese, M., Pasternack, A., Pankatz, K., Wehring, S., Lorenz, P., Fröhlich, K., Kreienkamp, F., and Früh, B.: The DWD climate predictions website: towards a user-oriented seamless climate service based on subseasonal, seasonal and decadal predictions, EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-38, https://doi.org/10.5194/ems2023-38, 2023.

How to cite: Trefalt, S., Klein, G., Ramshorn, C., Schlögl, S., and Gutbrod, K.: Physical climate risk assessments - how to meet clients’ requirements for non-financial reporting in a standardised process, EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-424, https://doi.org/10.5194/ems2023-424, 2023.

Recent European Commission-funded projects Destination Earth and EERIE aim to provide state-of-the-art climate change projections with a strong emphasis on increasing spatial resolution and user interactivity, which is possible due to the significant advancements in high-performance computing. However, rather than just focusing on improvements in climate outputs following traditional modelling exercises, these projects also aim to communicate the potential consequences of climate change in a way that is relevant for particular regional and local decision-makers. In this regard, both projects will apply alternative approaches to represent uncertainty in the future climate, so-called physical climate storylines (PCS). Defined in Shepherd & Lloyd (2021) as ‘physically self-consistent unfoldings of past events, or of plausible future events or pathways’, PCS have many overlaps with the methodology behind surrogate climate change and the likelihood estimations of the IPCC’s extreme weather and climate events. This complementary approach to conventional risk assessment can be applied to simulate historic extreme events in a warmer climate to identify adaptation options (Destination Earth) and tipping points with associated consequences for the global and regional climate (EERIE).

The study aims to find usability gaps in the PCS approaches of Destination Earth and EERIE. Social science can play an important role in filling the gaps by analyzing the user’s discourse on scientific uncertainty and its implications for decision-making. Given that the PCS approach is advantageous on smaller scales with high uncertainty about future changes in climate variability, it should be receptive to an environment accentuated by value judgements and where perspectives, evidence, risk preferences and errors are continuously redefined. Discourse-analytical approaches can help uncover these aspects. Moreover, for adaptive decision-making using a bottom-up approach, climate change is just another factor to consider among a wide range of potentially competing issues and demands. Becoming part of an extensive risk assessment which includes many non-climatic components, implies that PCS should be tailored to the user’s socioeconomic setting, which explains system vulnerabilities, resilience and coping capacities towards the future climate based on conditional statements. Transparent and rigorous insights into creating and managing co-produced climate information are critical for PCS’s objective to fit the local decision context. Therefore, a storyline should include climate analysis anchored in physical knowledge, which can be translated into robust and actionable climate adaptation output. The two European projects will be evaluated on their uptake of PCS as a tool to guide adaptive decision-making. Especially an effort will be made to discover the advantages and limitations of applying PCS of future climates in a co-developmental way.

How to cite: Versteeg, G. B.: Co-produced storyline approaches for adaptive climate management and the role of discourse analysis., EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-306, https://doi.org/10.5194/ems2023-306, 2023.