Data assimilation across scales and disciplines 
Data assimilation (DA) is an interdisciplinary science that integrates model simulations with real-world observations in a harmonious way, leveraging statistical mathematics, dynamical systems theory, and more recently, machine learning (ML). DA has long been a cornerstone of numerical weather prediction. DA has rapidly evolved into a unifying scientific methodology that spans multiple scales — from short-term weather forecasting to long-term paleoclimate reconstruction — and diverse disciplines, including data science, geoscience, biology, and engineering. Recent advances in observation, computation, and ML are transforming the landscape of DA. With the growing integration of ML, DA techniques are being refined to improve predictive capabilities and enhance data-driven modeling, and combined with system control theory, create a powerful framework for improving system performance by integrating real-time observations to refine models and control strategies. 

Key contemporary challenges include advancing the treatment of nonlinear and multi-scale system dynamics, addressing complex observation operators, and managing variables with non-Gaussian characteristics. Thus, this symposium aims to review latest developments and address issues of common interest to DA. The main following topics will be covered during the symposium:

Methodology
Contributions could for example address: DA theory and mathematics, ensemble approaches, non-linear and non-Gaussian DA, convective-scale and ultra-rapid DA, innovative approaches to reanalysis

Observations
Contributions could for example address: assimilation of remotely sensed observations (satellite, radar, GNSS, and unconventional observations), observations and impacts, OSSE, OSE

Hybrid DA and ML
Contributions could for example address: integration of ML to DA, hybrid DA and ML techniques, fully data-driven DA frameworks, predictability and uncertainty quantification for ML-based models, feedback from DA to ML

DA infrastructure and center updates
Contributions could for example address: developments in DA infrastructures (e.g., DART, JEDI, PDEF), updates from operational centers on DA, updates from global and regional reanalysis producers

DA for the Earth system
Contributions could for example address: atmosphere-land/ocean/sea ice coupled DA, atmospheric composition DA, seamless approaches - from minutes to seasons / multi-scale aspects, paleoclimate DA

Broad Applications, Perspectives and Predictive Sciences
Contributions could for example address: digital twin and controllability, extreme events and high-impact weather in forecasting and reanalysis, renewable energy, hydrology, socio economic applications

By bringing together scientists from diverse backgrounds, this symposium aims to promote dialogue, share emerging methodologies, and foster collaboration toward the next generation of cross-scale and cross-disciplinary data assimilation science.

The 8th WMO Symposium on Data Assimilation & 12th International Symposium on Data Assimilation is organized by Nanjing University and will be held, for the first time, in China, at the University's Xianlin Campus – Nanjing University International Conference Center. The WMO symposia on data assimilation have been held in Clermont-Ferrand, France (1990); Tokyo, Japan (1995); Quebec City, Canada (1999); Prague, Czech Republic (2005); Melbourne, Australia (2009); Washington, D.C., USA (2013); Florianópolis, Brazil (2017); and virtually in 2021.

The ISDA continues a series of well-received events: the first two symposia at DWD in Offenbach, ISDA2014 in Munich, ISDA2015 in Kobe, ISDA2016 in Reading, ISDA2018 in Munich, ISDA2019 in Kobe, ISDA2022 in Fort Collins, ISDA2023 in Bologna, ISDA2024 in Kobe, and ISDA2025 in Melbourne.

Scientific organizing committee

Lehmann Volker, Daryl Kleist, Sarah Dance, Lili Lei, Rossella Arcucci, Phil Browne, Maria Eugenia Dillon, Clara Draper, Sean Healy, Katia Lamer, Peter Jan van Leeuwen, Takemasa Miyoshi, Andrew Moore, Lars Nerger, Roland Potthast, Nahidul Samrat, Martin Weissman

Local organizing committee

Lili Lei, Zhu Zhang, Jian-Feng Gu, Yi-Peng Guo, Yan-Liu, Yuanlong Li, Ang Zhou, Jian Sun, Lin Zhang, Xin Li

Keynote Speakers

TBD