Abstract. The Scenario Model Intercomparison Project (ScenarioMIP) defines and coordinates the primary future climate projections within the Coupled Model Intercomparison Project Phase 6 (CMIP6). This paper presents a range of its outcomes by synthesizing results from the participating global coupled Earth system models for concentration driven simulations. We limit our scope to the analysis of strictly geophysical outcomes: mainly global averages and spatial patterns of change for surface air temperature and precipitation. We also compare CMIP6 projections to CMIP5 results, especially for those scenarios that were designed to provide continuity across the CMIP phases, at the same time highlighting important differences in forcing composition, as well as in results. The range of future temperature and precipitation changes by the end of the century encompassing the Tier 1 experiments (SSP1-2.6, SSP2-4.5, SSP3-7.0 and SSP5-8.5) and SSP1-1.9 spans a larger range of outcomes compared to CMIP5, due to higher warming (by 1.15 °C) reached at the upper end of the 5–95 % envelope of the highest scenario, SSP5-8.5. This is due to both the wider range of radiative forcing that the new scenarios cover and to higher climate sensitivities in some of the new models compared to their CMIP5 predecessors. Spatial patterns of change for temperature and precipitation averaged over models and scenarios have familiar features, and an analysis of their variations confirms model structural differences to be the dominant source of uncertainty. Models also differ with respect to the size and evolution of internal variability as measured by individual models' initial condition ensembles' spread, according to a set of initial condition ensemble simulations available under SSP3-7.0. The same experiments suggest a tendency for internal variability to decrease along the course of the century, a new result that will benefit from further analysis over a larger set of models. Benefits of mitigation, all else being equal in terms of societal drivers, appear clearly when comparing scenarios developed under the same SSP, but to which different degrees of mitigation have been applied. It is also found that a mild overshoot in temperature of a few decades in mid-century, as represented in SSP5-3.4OS, does not affect the end outcome in terms of temperature and precipitation changes by 2100, which return to the same level as those reached by the gradually increasing SSP4-3.4. Central estimates of the time at which the ensemble means of the different scenarios reach a given warming level show all scenarios reaching 1.5 °C of warming compared to the 1850–1900 baseline in the second half of the current decade, with the time span between slow and fast warming covering 20–28 years from present. 2 °C of warming is reached as early as the late '30s by the ensemble mean under SSP5-8.5, but as late as the late '50s under SSP1-2.6. The highest warming level considered, 5 °C, is reached only by the ensemble mean under SSP5-8.5, and not until the mid-90s.

Abstract. For the first time the limited-area mode of the new weather and climate model ICON has been used for a continuous long-term regional climate simulation over Europe. Building upon ICON-LAM, ICON-CLM v.0 (ICON in Climate Limited-area Mode, hereafter ICON-CLM) is an adaptation for climate applications. A first version of ICON-CLM is now available and has already been integrated into a starter package (ICON-CLM_SP). The starter package provides users with a technical infrastructure that facilitates long-term simulations as well as model evaluation and test routines. ICON-CLM and ICON-CLM_SP were successfully installed and tested on two different computing systems. Test with different domain decompositions showed bit-identical results, and no systematic outstanding differences were found in the results with different model time steps. Comparison was done between ICON-CLM and COSMO-CLM (the recommended model configuration by the CLM-Community) performance. For that, an evaluation run with ERA-Interim boundary conditions was carried out with the setups similar to the COSMO-CLM recommended optimal setups. ICON-CLM results showed biases in the same range as those of COSMO-CLM for all evaluated surface variables. This is remarkable because the COSMO-CLM simulation was carried out with the latest model version which has been developed for two decades and was carefully tuned for climate simulations on the European domain. Furthermore, ICON-CLM already showed a better performance for air temperature, its daily extremes, and total cloud cover. Results for precipitation and mean sea level pressure did not show clear advantage from any model. However, as ICON-CLM is still in the early stage of development, there is still much room for improvement.

<p><span>The Destination Earth Climate Adaptation Digital Twin (Climate DT) will design and implement a climate information system running on pre-exascale high-performance computing platforms to support climate adaptation efforts. An overview of the overall Climate DT will be given by Kontkanen et al. (this session).</span></p><p><span>The Climate DT will provide global climate data for both the historical period and the near-term future with unprecedented spatial and temporal resolution. The downstream applications will access the full model state vector (MSV) at runtime. This will </span><span>lead to an interactive system where applications harnessing the MSV can be added, removed, or modified as required by the user. The climate MSV, which contains both the prognostic and a large number of diagnosed variables, will be continuously streamed (understood as all the user-requested variables being available in a federated and curated repository for a limited period of time before being erased) at both high frequency and native resolution. </span><span>The applications will be able to consume this data at runtime as it is streamed. This is equivalent to applications using all the model data they require in a similar manner as one observes a physical system with all the necessary detail to satisfy specific requirements. Additional functionalities will be provided to help the data consumers access relevant statistics, to speed up the data processing and facilitate the data reduction (e.g., on-the-fly bias adjustment). This approach reduces the entry-level requirements for applications to participate in this completely new approach to access climate information data sources. The applications have the possibility of not only interacting with the model to extract the required climate data and indicators on real time, but also iteratively contribute to the design of the experimental set up and request additional variables and indicators.</span></p><p><span>To illustrate the broadest possible applicability of the Climate DT concept, five different pilot use cases were selected for the co-design, implementation, user feedback and evaluation of the Climate DT. The selected use cases focus on wildfires, urban climate, river discharge, wind energy, and hydrometeorological applications. Another consumer of the MSV will be the climate model evaluation. Furthermore, the use cases will present technical recipes for users to access the data and link their applications or impact models to the digital twin.</span></p><p><span>Each use case has identified specific key users. A close exchange with these key users is foreseen to meet the user requirements. To ensure transferability of the work to other users, an exchange with a wider circle of users is foreseen at a more advanced phase at dedicated stakeholder meetings.</span></p><p><span>An overview of the use cases, the technical concepts and the ongoing user engagement and co-design activities will be given to demonstrate the novelty, potential and advantages the digital twin offers. The use cases will illustrate the progress beyond current practices that is possible with these new climate simulation workflow compared to the traditional way of delivering climate simulation.</span></p>

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<p>The structural uncertainty of a climate model is defined as the range of outcomes that can be obtained through different representations of physical processes of the climate system, the selection of different unconstrained parameter values and different choices for the numerical solution of underlying fundamental equations. Exploring the range of these outcomes with the goal of determining a model configuration that produces results in closer agreement with observational data is defined as model calibration or tuning.</p><p>In this study, the preliminary results of the Coordinated Parameter Testing 2 (COPAT2) initiative of the CLM-Community are presented. In COPAT2, volunteer members of the community join forces together, with the objective of testing and providing recommended configurations for the new and final version of COSMO-CLM (6.0), as well as for the newly released regional climate model ICON-CLM, for climate modeling applications over the European CORDEX domain. </p><p>A series of sensitivity tests is performed in which various configurations of the models are explored. The aspects that are tested have been carefully selected, based on expert judgment. In the case of COSMO-CLM 6.0, the primary focus is on newly introduced and recently updated parameterizations and physical schemes. For ICON-CLM, these  tests are the first ever conducted with the climate version of the model and are based on the operational configuration and on information of experiments performed for the development of the NWP mode of ICON.</p><p>The simulations are conducted at a horizontal resolution of approximately 12 km over Europe, using ERA5 reanalysis data as boundary conditions. In a first step, a series of relatively short tests is conducted over a 7-year period, from 1979 to 1985. Successively, depending on the sensitivity of the model to the applied changes in its configuration, a sub-set of simulations is extended over a total period of 12 years. The results are systematically analyzed with an evaluation suite that has been further developed and extended for COPAT2. The standardized analysis and condensation of results in very few indices summarizing the models performance allow for an easy and fast comparison of the quality of the different simulations.  </p><p>Beside introducing preliminary results of the conducted sensitivity tests, an overview of the calibration strategy followed in COPAT2 will be presented, including information on the selected metrics, employed observational data sets and further details inherent to the ranking of the different experiments.  </p><p><br><br></p>