Held every three years, ESA’s Living Planet Symposia are among the world’s premier events on Earth observation. The symposia continue to expand in both size and scope. With the climate crisis intensifying, the Living Planet Symposium 2025 (LPS25) emphasises transitioning from ‘observation to climate action and sustainability for Earth’.

The event provides a forum to present and discuss the latest scientific findings and applications based on satellite data, and to review the contribution that data and technologies have made and could further make in addressing environmental and societal challenges. The symposium will showcase innovative products, services, missions and initiatives, with the overarching goal of demonstrating how science, society, policy-making, businesses and the economy can all benefit from observations made from space.

During the five-day event, diverse communities united by a common interest in exploiting Earth observation data will gather together, creating a unique opportunity to meet and network with space enthusiasts from a wide range of sectors.

CMIP at LPS25

CMIP will have a strong presence at LPS25, with ESA as the host of the CMIP IPO. CMIP have organised the following sessions.

Advances in Benchmarking and Evaluation of Earth System Models (A.05.03)

Earth System Models (ESMs) have evolved considerably in complexity, capability and scale as evidenced in projects such as the Coupled Model Intercomparison Project (CMIP), NextGEMs, and ESM2025. ESMs are also key tools in understanding how our climate may evolve in the future. Therefore, there is a need to assess the credibility and accuracy of model developments and capabilities to maximise earth system science research, for which Earth Observations are a vital tool. This session aims to share evaluation approaches and advances, highlight avenues for future development, and identify gaps which could be filled by ESM and observational improvements.
This session seeks to feature work relating to any of:

1. innovative evaluation and benchmarking strategies, tools, and techniques,
2. new and informative diagnostics,
3. science performance metrics,
4. development of evaluation tools and methods,
5. model and observational uncertainties,
6. observational requirements to enable the next generation of CMIP model benchmarking and
7. the role of emerging technologies, including machine learning and artificial intelligence, in advancing the assessment of ESMs.

Climate forcing: quantifying the roles and responses of anthropogenic and natural climate drivers (A.05.04)

Climate forcings play a key role in the definition of drivers of ongoing climate change. As such, they are an integral component of historical, future scenario and idealised simulations in climate models. Perturbations in atmospheric chemistry, or land-use affecting the surface albedo are just two examples of natural or anthropogenic climate forcings. These “climate forcing” agents cause an energy imbalance at the top of the atmosphere, driving changes in Earth’s surface temperature and the wider climate system. Historical climate forcing datasets are often partially derived from earth observations. Therefore, for accurate, timely, and accessible climate information, collaboration across the Earth Observation and climate modelling communities is essential.

This session invites research contributions assessing the climate responses to forcing and uncertainties in the evolution of different forcing agents. Contributions on all aspects of climate-forcing research are welcome. These may include, but are not limited to, the development of historical and future forcing, studies that use idealized, single- or multi-Earth System Model approaches, observational methods to evaluate climate responses, as well as works accounting for multiple climate system realms, i.e., the ocean, atmosphere, cryosphere, land surface/subsurface, and biosphere, their linkages, and feedbacks in the system. In addition, we welcome submissions from those interested in the development of regular and sustained delivery of forcing datasets, and also those seeking to utilising such potential “operational” outputs.