The increasing amount of data from an increasing number of spacecraft in our solar system shouts out for new data analysis strategies. There is a need for frameworks that can rapidly and intelligently extract information from these data sets in a manner useful for scientific analysis. The community is starting to respond to this need. Machine learning, with all of its different facets, provides a viable playground for tackling a wide range of research questions in planetary and heliospheric physics.

We encourage submissions dealing with machine learning approaches of all levels in planetary sciences and heliophysics. The aim of this session is to provide an overview of the current efforts to integrate machine learning technologies into data driven space research, to highlight state-of-the art developments and to generate a wider discussion on further possible applications of machine learning.

Through a wealth of geospatial data, growing computational power, and demonstrated success of application across many fields, artificial intelligence (in particular, machine learning) promises to advance our understanding of natural hazards and our ability to predict and respond to natural disasters. The ITU/WMO/UNEP Focus Group AI for Natural Disaster Management (FG-AI4NDM) is building a community of experts and stakeholders to identify best practices in the use of AI for data processing, improved modeling across spatiotemporal scales, and providing effective communication. This multidisciplinary FG-AI4NDM-session invites contributions addressing challenges related to floods, landslides, earthquakes, volcanic eruptions, tsunamis, among others, as well as multi-hazard. It also welcomes presentations on novel AI methods (including advances in automated annotation, explainability, etc.), which are hazard agnostic.

Unsupervised, supervised, semi-supervised as well as reinforcement learning are now increasingly used to address Earth system related challenges.
Machine learning could help extract information from numerous Earth System data, such as in-situ and satellite observations, as well as improve model fidelity through novel parameterisations or speed-ups. This session invites submissions spanning modelling and observational approaches towards providing an overview of the state-of-the-art of application of these novel methods for predicting and monitoring our earth system. This includes (but it is not restricted to):
- the use of machine learning to improve forecast skill
- generate significant speedups
- design new parameterization schemes
- emulate numerical models.

Please consider submitting abstracts focussed on ML applied to observations and modelling of climate processes to the companion "ML for Climate Science" session.

Recent developments in machine learning (ML) are transforming Earth observation data analysis and modelling of the Earth system and its constituent processes. While statistical models have been used for a long time, state-of-the-art machine and deep learning algorithms allow encoding non-linear, spatio-temporal relationships robustly without sacrificing interpretability. These advances have the potential to accelerate climate science by improving our understanding of the underlying processes, reducing and better quantifying uncertainty, and even making predictions directly from observations across different spatio-temporal scales.

This session aims to provide a venue to present the latest progress in the use of ML applied to all aspects of climate science including, but not limited to:
- Causal discovery and inference
- Learning (causal) process and feature representations in observations
- Hybrid models (physically informed ML)
- Novel detection and attribution approaches
- Probabilistic modelling and uncertainty quantification
- Explainable AI applications to climate science

Please consider submitting abstracts focussed on ML for model improvement, particularly for near-term (including seasonal) forecasting to the companion “ML for Earth System modelling” session.

Citizen science (the involvement of the public in scientific processes) is gaining momentum across multiple disciplines, increasing multi-scale data production on Earth Sciences that is extending the frontiers of knowledge. Successful participatory science enterprises and citizen observatories can potentially be scaled-up in order to contribute to larger policy strategies and actions (e.g. the European Earth Observation monitoring systems), for example to be integrated in GEOSS and Copernicus. Making credible contributions to science can empower citizens to actively participate as citizen stewards in decision making, helping to bridge scientific disciplines and promote vibrant, liveable and sustainable environments for inhabitants across rural and urban localities.
Often, citizen science is seen in the context of Open Science, which is a broad movement embracing Open Data, Open Technology, Open Access, Open Educational Resources, Open Source, Open Methodology, and Open Peer Review. Before 2003, the term Open Access was related only to free access to peer-reviewed literature (e.g., Budapest Open Access Initiative, 2002). In 2003 and during the “Berlin Declaration on Open Access to Knowledge in the Sciences and Humanities”, the definition was considered to have a wider scope that includes raw research data, metadata, source materials, and scholarly multimedia material. Increasingly, access to research data has become a core issue in the advance of science. Both open science and citizen science pose great challenges for researchers to facilitate effective participatory science, yet they are of critical importance to modern research and decision-makers.

We want to ask and find answers to the following questions:
Which approaches and tools can be used in Earth and planetary observation?
What are the biggest challenges in bridging between scientific disciplines and how to overcome them?
What kind of participatory citizen scientist involvement (e.g. how are citizen scientists involved in research, which kind of groups are involved) and open science strategies exist?
How to ensure transparency in project results and analyses?
What kind of critical perspectives on the limitations, challenges, and ethical considerations exist?
How can citizen science and open science approaches and initiatives be supported on different levels (e.g. institutional, organizational, national)?

Groundwater, the hidden component of the water cycle, traditionally receives less attention than surface water from both the scientific community and policy makers, due to it being "out of sight, out of mind". However, this precious resource is inextricably linked to the maintenance of natural ecosystems and human well-being. Groundwater has always been part of the lives of worldwide communities: irrigated agriculture is primarily sustained by groundwater resources, particularly in arid and semi-arid regions; holy wells and sacred springs are part of our global cultural heritage, while disagreement over groundwater resources have previously resulted in turmoil and national/transboundary conflicts. These obvious interconnections, however, are neglected in favour of the development of sectorial approaches to groundwater resource assessment.
Socio-hydrogeology has recently been proposed as an effective approach to addressing complex groundwater-related issues in an increasingly holistic and integrated manner. By focusing on the reciprocity between humans and groundwater, it aims to explore and understand their dynamic interactions and feedbacks with a final goal of developing transdisciplinary solutions for transdisciplinary problems. Due to the more "personal" (i.e., individual household/community supplies) and local nature of groundwater in many instances, socio-hydrogeology seeks to understand individuals and communities as a primary source, pathway and receptor for potable groundwater supplies, including the role of local knowledge, beliefs, risk perception, tradition/history, and consumption. In essence, the “socio” in socio-hydrogeology embodies sociology, including social, cognitive, behavioural and socio-epidemiological science.

For this session we encourage contributions from diverse fields, including:
• Examples of socio-hydrogeological assessments (e.g., participatory monitoring, stakeholder engagement, public participation, citizen science)
• Integration of “non-expert” knowledge and experience within quantitative and qualitative hydrogeological studies
• Challenges and opportunities arising from the integration of hydrogeology and social sciences
• Social and political approaches to water resources research
• Groundwater geoethics and national/transboundary conflicts
• Attempts to integrate behavioural, experiential or knowledge-based data with hydrogeological/health risk assessment models
• Educational goals for future socio-hydrogeologists

Climate impact and adaptation research has made considerable progress in various fields in the recent years. However, the concrete implementation on the ground needs to be improved.
Local decision makers are facing several challenges with regard to climate adaptation. At the center of this process lies the coupling of climate, impact and risk (incl. vulnerability) models in order to identify future climate risk levels. Finding and correctly using the necessary data in climate impacts and risks assessments and planning for climate action is not without challenges for specialists from other fields.
While climate modelling and technical integration of diverse model data are crucial, social science as well as interdisciplinary perspectives are essential to assess local adaptation capacities, the costs and benefits of adaptive measures and to ensure the usability and transferability of the climate services. Similarly important is capacity building and trainings on properly using, interpreting and communicating climate and impact information.
This session touches upon innovative ways to address theses challenges. It also supports exchange on experiences in impact and adaptation studies, using all kinds of climate data. Former participants from the C3S ULS and IS-ENES3 training events are particularly encouraged to join.
This session discusses approaches and challenges towards the support of climate change adaptation and disaster risk reduction. Central to the discussion is the question how such services can be developed in a stringent co-design process that integrates different natural and social science disciplines as well as users and practitioners. We are therefore seeking for contributions that discuss:
• Actionable services for regional decision-making in regional climate adaptation and disaster risk reduction and challenges in the interaction between researchers and decision makers
• New scientific insights into regional climate and impact modelling (data interfaces and harmonization)
• Assessing local climate adaptation capacities and measures in an integrated way
• New insights into transdisciplinary processes in climate change adaptation
• Data availability for climate impact studies and methods for dealing with limited data availability as well as the opposite, a large number of seemingly similar datasets.
• Experiences with existing tools or newly developed tools for data processing

The virus is still with us, with more potent variants. It remains the most immediate challenge for geosciences and health, including its impacts on geoscience development (data collection, training, dissemination) and the achievement of the UN Sustainable Development Goals, in particular that urban systems should increase well-being and health.

Long-term visions based on transdisciplinary scientific advances are therefore essential. As a consequence, this session, like the ITS1.1 session in 2021, calls for contributions based on data-driven and theory-based approaches to health in the context of global change. This includes :
- main lessons from lockdowns?
- how to get the best scientific results during a corona pandemic?
- how to manage field works, geophysical monitoring and planetary missions?
- qualitative improvements in epidemic modelling, with nonlinear, stochastic, and complex system science approaches;
- eventual interactions between weather and/or climate factors and epidemic/health problems
- new surveillance capabilities (including contact tracing), data access, assimilation and multidimensional analysis techniques;
- a fundamental revision of our urban systems, their greening and their need for mobility;
- a special focus on urban biodiversity, especially to better manage virus vectors;
- urban resilience must include resilience to epidemics, and therefore requires revisions of urban governance.

The 2021-2022 Hunga Tonga-Hunga Ha'apai eruption in Tonga was among the largest of recent decades. The event was notable for its high intensity, generating a convective column that rapidly ascended well into the stratosphere; for the atmospheric pressure wave generated by the explosion, which was detected globally; and for generating a tsunami that was observable across Pacific Ocean shorelines. Following a series of preceding seismic and explosive events since December 2021, the sustained phase of the eruption on 15th January was relatively short lived, but the associated pressure wave and tsunami impacts were the most far-reaching since the eruption of Krakatau volcano in 1883. Tsunamis were recorded both locally and in the far-field, but their mechanism(s) remains uncertain; in the near field being from either (or both of) the collapsing eruption column or a phreatomagmatic explosion as the erupting mass mixed with sea water. In the far-field the tsunamis are possibly best explained by the massive atmospheric pressure wave, that is the first instrumentally recorded eruption-generated event of its type, which affected the entire global atmosphere and ionosphere, causing the observed infrasound waves and unusual long-period seismic resonances.
This interdisciplinary late-breaking session welcomes contributions from all disciplines involved in local and global observations of this eruption and its effects, including remote sensing observations and modeling as well as hazard assessment and estimation of damage and long-term consequences.

In a fast-changing environment, earth’s ecosystems are facing multiple stressors compromising the provision of essential services for mankind, and the resiliency of the natural environment itself.
Climate change, water pollution and scarcity affect biodiversity, socio-economic and climate related vulnerabilities and as a consequence, water and food security and human health.
The recent European Green Deal aims at Europe becoming the world’s first climate-neutral continent by 2050 and it does so by setting climate, energy, transport and taxation policies fit for reducing net greenhouse gas emissions by at least 55% by 2030. This program sets ambitious yet realistic targets for the next decades, auspicating the transformation of European Countries into a modern resource-efficient economy and society in line with the Sustainable Development Goals.
However, to address both the impacts as well as the causes of climate change, it is fundamental to create conditions where ecosystem services are optimized for both the local population and global objectives. Yet, the use of ecosystem services assessment in decision making might prove challenging when it comes to economic and social domains, as well as the perception and concept of natural environment may differ across disciplines. Such transdisciplinary approach plays a key role in Nature Based Solutions and opens up to the participation of multiple stakeholders in local governance, thus offering a multitude of co-benefits for the environment and for communities.
This session aims at opening a common ground between the natural, physical, social and economic sciences towards a resilient planet, by providing examples of challenges and opportunities and harmonizing best practices in this field.
We welcome transdisciplinary contributions on terrestrial, marine, and urban ecosystem services assessment that take into account the natural and the human dimension, advance in modelling complex spatio-temporal and social dynamics and transdisciplinary approaches towards nature inspired and supported solutions for social benefits and ecosystems’ resilience.

Nature-Based Solutions and Climate Engineering in Climate Governance

As reaching the Paris agreement goal of limiting the global mean surface warming even below 2ºC becomes increasingly difficult with only emission reduction, additional measures complementing greenhouse gas (GHG) emission reductions to limit global warming gain more attention: Nature-based Solutions and Climate Engineering.
Nature-based solutions (NbS) have gained popularity as a set of integrated approaches that contribute to climate change adaptation, slowing further global warming, supporting ecosystem services and biodiversity, while promoting sustainable development. To achieve the full potential of NbS to address climate change, there is an urgent need for multidisciplinary teams of scientists to articulate solutions that engage policy makers and enable NbS interventions to reduce carbon emissions while benefiting human well-being. This will require systemic change in the way we conduct research, promote collaboration between institutions and with policy makers.

Climate Engineering (CE) is much more controversial. Carbon Dioxide Removal (CDR) aims at removing CO2 from the atmosphere through techniques such as ocean fertilization, artificial upwelling or enhanced weathering. CE has been criticized for creating potentially dangerous side effects, distracting from the root cause of climate change (GHG emissions), and being difficult to govern. So what, if any, should be the future role of CDR and SRM in the climate governance toolbox and to what extent should CE research have high priority? which knowledge gaps must be addressed before a decision for or against these techniques can be taken?
This session aims to advance knowledge of innovative NbS approaches for more inclusive and resilient communities from inter-disciplinary perspectives.

Specific topics include, but are not limited to:
— Benefits: The potential of NbS and CE to help achieving climate goals
— Feasibility: Tools and best practices enabling successful implementation and upscaling of NbS; impact assessment of real-life NbS projects, especially for the Global South and developing countries; and technical feasibility and risks in implementing CE
— Viability: Cost-benefit analysis of NbS and CE to multiple Sustainable Development Goals
— Governance: New NBS governance models and co-creation approaches and tools; and regional and global challenges and solutions for fair and inclusive governance of CE.

Perhaps the most dramatic demonstration of the impact of global environmental change has been the rapid change in fire regimes, from the Amazon to suburban Athens. However, the observed disruption in global wildfire regimes has not yet been directly attributed to climate – but only to weather patterns that make wildfires more likely.

At the heart of this issue is a lack of understanding of the diverse socio-ecological feedbacks that are driving Anthropocene wildfires. For example, in response to damaging fire events, common policy responses such as increased suppression and fire use bans may ultimately exacerbate fire risk by leading to large build-ups of flammable and connected fuels. Meanwhile a combination of global-scale trade conflict, national-scale political change and regional drought have all contributed to a surge in wildfires in the Amazon basin. These examples highlight the urgent need for new transdisciplinary approaches to wildfire research that account for feedbacks between land use and wider environmental change.

In this session we welcome a broad range of contributions that explore the interactions between socio-economic and biophysical drivers of wildfires, encompassing disciplines including: anthropology, earth observation, ecology, economics, land surface and climate modelling, and political science. Example topics might include how agricultural intensification, land degradation and CO2 fertilisation effects combine to alter fire regimes in grassland ecosystems, through to how rural and urban populations’ contrasting perceptions of risk can influence land management policies.

We particularly encourage contributions that demonstrate how methods from different disciplines may inform each other. Holistic advances in our understanding can lead to better adaptation policies and strategies, and will be vital to improved wildfire modelling and attribution of fire regime changes to climate change.