Energy systems across the world are rapidly evolving to meet climate mitigation targets. This requires a rapid transition to electricity systems lower reliance on fossil fuels and greater weather-dependent renewable generation (such as wind power, solar power, and hydropower). This increased weather dependence adds a new set of challenges for balancing supply and demand due to the inherent variability of weather, increasing the need for investment in storage and flexible technologies. The impacts of climate variability and climate change on national energy systems is a topic of current academic interest. Both in terms of security of supply risks from system level challenges (e.g., energy shortfall events, where existing generation is insufficient to meet demand) or from smaller-scale infrastructure challenges (e.g., extreme weather impacting the operability of energy system components).

This talk will discuss a programme of work on energy sector impacts using the UK Climate projections data (UKCP18). This is a suite of state-of-the-art climate model projections available at 60km resolution globally, 12km spatial resolution over Europe, and 2.2km resolution over the UK. Electricity demand, wind power, and solar photovoltaic power timeseries are developed for the period 1980-2080 using the regional climate model outputs. Climate data of this high spatial and temporal resolution is critical for the accurate quantification of meteorological hazards of relevance to the energy sector. The UK energy sector will be used as a case study in this talk due to its large share of variable renewables and commitments to reach net-zero emissions by 2050 and decarbonising the electricity system by 2035.

This talk will highlight weather-driven risks to the energy sector in both a present and future climate, with a particular focus on compound events. At short timescales examples of these risks could be periods of high demand combined with low wind power generation, or weather patterns extending over a very large area of Europe (therefore creating a spatial compound event) or sequences of extreme weather (such as several storms happening in quick succession, which could damage energy infrastructure). At longer timescales these types of compound events could be years with low renewable energy production relative to demand, or as successive years with low production. Future work will use the years containing extreme events highlighted in this talk as inputs within high resolution power system modelling simulations.

How to cite: Bloomfield, H.: Using high resolution climate data to help prepare future energy systems for weather-driven extremes., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8794, https://doi.org/10.5194/egusphere-egu24-8794, 2024.

The correct representation of fine-scale atmospheric processes, like convection, is vital for predicting extreme weather events and CPMs have already shown to provide more reliable representation of extreme precipitation. However, in most cases their validation is limited to the precipitation field and based on sparse in-situ observations or coarser resolution observational gridded dataset. In this study, we first explore whether high-resolution (i.e., grid spacing 2.2km) reanalysis product SPHERA provides a realistic representation of the in-situ observations, thus offering  a comprehensive overview of the atmosphere at fine scale and functioning as a reliable reference dataset for CPMs evaluation. Then the sub-daily precipitation and wind fields of the CPMs ensemble from the CORDEX Flagship Pilot project on Convective Phenomena over Europe and the Mediterranean (FPS Convection) is validated against both in-situ observation and SPHERA. The validation focuses on extreme quantiles, spatial variability and event representation with a quantile based approach (i.e., the event starts when atmospheric variables are above a certain quantile, and ends when it goes below). Results show a general good agreement between in-situ observations and SPHERA, that is found to be a good reference dataset to evaluate the CPM models. When looking at the extreme quantiles, the CPMs well represent  both wind and precipitation fields, although they underestimate heavy precipitation in summer (i.e., June-July-August). Similarly, the spatial distribution of precipitation and wind is well represented for all the season, with a decrease in the spatial variability and spatial correlation for the heavy precipitation in the summer. Finally the CPMs underestimate the number of the events when precipitation and wind are treated singularly, while they substantially overestimate the number of compound events of rainfall and winds. The analysis shows the capability of CPMs to represent the precipitation and wind fields and highlights the possibility of using high-resolution reanalysis into the evaluation of convection-permitting models. Moving from point-based measurements to high-resolution gridded observational datasets opens the path to the use of SPHERA for advanced bias correction methods that could take into account the full 3D dimension of the atmosphere and the processes within it.

How to cite: Cesarini, L. and Fosser, G.: Validation of CPM’s wind and precipitation field against observations and the highresolution reanalysis dataset SPHERA, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17774, https://doi.org/10.5194/egusphere-egu24-17774, 2024.

National Climate Scenarios provide a common basis for national risk assessment and adaptation planning. Recent examples include the UK’s UKCP18, the Netherlands’ KNMI23 and the Australian ‘Climate Change in Australia’ (2015).

Advances in climate modelling approaches provide the potential for a step change in the quality, and type of national climate scenarios that will likely be produced over coming years. While these advances include improvements in the traditional approaches employed in the provision of future climate projections for adaptation planning (updated global model ensembles, various downscaling approaches including convective permitting regional projections, improvements in constraining model ensembles), developments in a wider range techniques are increasingly being used in the assessment of climate resilience. These include large initial-condition ensembles, event attribution, the exploration of ‘High Impact Low Likelihood’ (HILL) scenarios, as well as the potential to exploit enhanced skill in initialised seasonal and decadal forecasts.

Here we will share what we are learning through parallel activities which seek to (a) develop our understanding of the needs of the diverse user community in the UK through an extensive user consultation to enhance usefulness and usability and (b) scope the opportunities emerging from the climate science community may have to address the gaps in existing information, and their readiness to contribute to a National Climate Information package.

How to cite: McSweeney, C., Lowe, J., and Mittal, N.: From National Climate Scenarios to National Climate Information, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-22471, https://doi.org/10.5194/egusphere-egu24-22471, 2024.

Despite the significant advancements of Integrated Assessment Models [IAMs] in recent years, criticisms underscore their limitations in effectively responding to questions on climate change adaptation and mitigation (4). Such critiques highlight the need for IAMs to be not only technologically advanced but also transparently accessible to both the modeling community and stakeholders (1).

The Horizon Europe project “Delivering the next generation of Open Integrated Assessment Models for net-zero, sustainable development” [DIAMOND] seeks to bridge these gaps. By leveraging participatory and transdisciplinary approaches, DIAMOND aims to enhance, extend, and open up IAMs, aligning them more closely with climate action and sustainable development objectives through open and responsible stakeholder engagement.

Engaging a broad range of stakeholders and working collaboratively with them stands out as pivotal in bolstering the credibility and effectiveness of modeling results (5; 6). Acknowledging policymakers’ inputs further strengthens the potential integration of modeling results into policy-making processes (1). This paper presents co-created comprehensive good practice guidelines for inclusive stakeholder engagement, grounded in a case study of the DIAMOND project. The focus is on establishing an inclusive modeling environment that ensures representation and decision making embody diverse stakeholders’ perspectives, knowledge, and interests, including those of policymakers. Utilizing a transdisciplinary approach facilitates a move towards genuine inclusivity, ensuring all relevant parties, regardless of their background or expertise, are given the opportunity to participate, contribute, and have their voices heard in the decision-making process (2). Employing a mixed-methods approach that combines a literature review, stakeholder elicitation, an online survey, and semi-structured interviews, this study triangulates these methods to comprehensively assess collaborative dynamics, adaptive strategies, and the operational context, providing a nuanced understanding of the complex interactions at play.

This paper endeavors to guide modelers, irrespective of their modeling background, towards producing relevant and actionable results that are aligned with real-world implications and policy needs (3). Through assessing and integrating the dimension of “inclusivity” within participatory modeling processes and demonstrating its integration within a transdisciplinary framework, this study aspires to offer valuable insights to the broader modeling community. The insights derived can empower modelers across disciplines to provide policymakers with evidence-based approaches for designing effective climate change adaptation measures and informing mitigation decisions, paving the way for better-informed policies guiding society towards a sustainable and net-zero future.

References:

(1) Doukas, H., Nikas, A. (2019). European Journal of Operational Research, 280, 1-24. https://doi.org/10.1016/j.ejor.2019.01.017
(2) Ernst, A., Fischer-Hotzel, A., Schumann, D. (2017). Energy Research & Social Science, 29, 23-35. http://dx.doi.org/10.1016/j.erss.2017.04.006
(3) Jordan, R., Gray, S., Zellner, M., Glynn, P. D., Voinov, A., et al. (2018). Earth’s Future, 6, 1046–1057. https://doi.org/10.1029/2018EF000841
(4) Keppo, I., Butnar, I., Bauer, N., Caspani, M., Edelenbosch, O., et al. (2021). Environmental Research Letters, 16, 053006. https://doi.org/10.1088/1748-9326/abe5d8
(5) McGookin C., Gallachóir B., Byrne, E. (2021). Renewable and Sustainable Energy Review, 151, 111504. https://doi.org/10.1016/j.rser.2021.111504
(6) Pisano, U., Lange, L., Lepuschitz, K., Berger, G. (2015). European Sustainable Development Network. ESDN Quarterly Report, 39.

How to cite: Herbig, V., Briers, S., and Vienni-Baptista, B.: From Stakeholder Engagement to Inclusivity: Advancing Participatory Modeling for Net-Zero Sustainable Development, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9297, https://doi.org/10.5194/egusphere-egu24-9297, 2024.

How to cite: Sieck, K., Pinto, J., Harrs, J.-A., Tiedje, B., Ziemann, A., Xoplaki, E., Geyer, B., Feldmann, H., Mömken, J., Paeth, H., Trachte, K., Kadow, C., and Dalitz, L.: Bringing high-resolution climate data into action: Experiences from the transdisciplinary funding measure RegIKlim, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8945, https://doi.org/10.5194/egusphere-egu24-8945, 2024.

As the physical processes of our world change, the landscape of risk has changed with it. At Climate X, we provide high-quality data to the financial sector so that evolving risks to global portfolios can be quantified. A crucial element of this is the physical risk from events, including extreme weather events.

Traditionally risk assessments have been carried out at an asset level on small scales, with a dedicated team spending days on tens of assets. The high price and slow turnaround makes this unfeasible for large scale operations. We provide an alternative, leveraging open source datasets and research to estimate the physical risk to over half a billion buildings worldwide. This talk will highlight some challenges of working at this scale, and illustrate our approaches to resolving them.

How to cite: Stables, J., Reverly, G., Brennan, J., Woodhouse, S., Leach, N., Ramsamy, L., Sullivan, P., and Davies, J.: Challenges in quantifying physical risk to assets globally, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19847, https://doi.org/10.5194/egusphere-egu24-19847, 2024.

Climate change requires urgent action. Aggressive actions toward carbon emissions reduction must remain the primary strategy for reversing and addressing climate change. However, increasingly the world is considering technology-based climate intervention approaches—often called climate engineering. There are major practical and ethical questions about the significant risks and potential trade-offs some of these approaches would bring and how they would be measured against the risks of our warming world. Recognizing the need for guiding principles in this fast-moving, dynamic space and building on AGU’s longstanding history of advancing and advocating for strong scientific ethics, AGU is facilitating the development of a draft Ethical Framework for Climate Intervention Research, Experimentation, and Deployment. The ethical framework will be released in 2024 and will serve as a resource to help governments, researchers, NGOs, and the private sector make responsible decisions when engaging in climate intervention research or policy. In 2023, the draft framework completed a rigorous three-month public comment period and consultation process to include more holistic input from other scientists and ethicists, as well as community voices, youth advocates, and many more. This presentation will highlight the ethical principles and how the science community can incorporate and advocate for ethics in climate intervention research.

How to cite: Shimamoto, M., Lachance, J., and Williams, B.: Incorporating Ethics into Climate Intervention Research, Experimentation, and Potential Deployment, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20739, https://doi.org/10.5194/egusphere-egu24-20739, 2024.

Considerable risk is involved in the use of climate models or their products (i.e., simulations and data) when there is a lack of adequacy or fitness for one’s purpose. Of specific concern is the risk of generating information in response to an actionable or applied question or aim that is irrelevant, misleading, inappropriate, inconsistent, or highly inaccurate, as this can lead to downstream harms such as maladaptation. This form of “misuse” is innocent or unintentional, and is largely a function of a user’s misunderstanding or misinterpretation of the intended purposes of a model and/or modeling exercise and the applicability of the model’s products. Ineffective communication and lack of transparency into the intended purposes, assumptions, representational features, adequacies, as well as inadequacies and limitations of a model, can lead to this form of inappropriate and unjustified repurposing. Currently, there is an increase in the demand for open and accessible data, and an increase in the use of climate data, especially data from high-resolution modeling efforts, for applied and actionable purposes (contexts in which derived products are used to inform decision-making). Given both conditions, the reduction and management of possible inappropriate repurposing, i.e., misuse, has become a highly salient consideration for any modeling effort. Producers of models and their products have a moral duty to implement mechanisms to aid users in the identification, understanding, and control of this risk. This can happen by way of the distribution of expert guidance, increase in intentional transparency, and instantiation of systematic norms for clearly and plainly communicating the fitness of purpose and inadequacies of models and their products. This would provide a large step forward toward the reduction of misuse of information in climate science that could lead to harmful consequences, and pave the way for the development of an ethics of scientific practice for the climate science community.

How to cite: Morrison, M.: Towards an Ethics of Modeling and Data Use for Actionable Climate Science, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20838, https://doi.org/10.5194/egusphere-egu24-20838, 2024.