Introduction

Data assimilation (DA) is a cross-disciplinary science to bring together computer simulations and real-world data in a synergistic manner based on statistical mathematics and dynamical systems theory. DA has long been playing a crucial role in numerical weather prediction (NWP), and recently, DA has been applied more widely to numerical model simulations beyond geophysical applications, such as planetary and biological sciences as well as engineering applications. Contemporary fundamental challenges include better treatment of nonlinear and multi-scale system evolution, complex observation operators, and variables with non-Gaussian properties. Developing efficient computational algorithms has also been a major issue.

The 10th International Symposium on Data Assimilation (ISDA2024) is organized by RIKEN and will be held at the Convention Hall of Integrated Research Center of Kobe University, continuing a series of well-received events: ISDA2023 in Bologna, ISDA2022 in Fort Collins, ISDA2019 in Kobe, ISDA2018 in Munich, ISDA2016 in Reading, ISDA2015 in Kobe, ISDA2014 in Munich and the first two symposia at DWD in Offenbach. The symposium is open for oral and poster contributions in various fields of DA research.

The symposium will focus on the cross-cutting issues shared in broad applications of DA from geoscience to various physical and biological sciences and engineering. In particular, the symposium will enhance discussions among researchers with various backgrounds on, for example, nonlinear and non-Gaussian DA, Uncertainty Quantification (UQ), Artificial Intelligence (AI) and Machine Learning (ML), observational issues, mathematical problems, and predictability and controllability. DA is at the core of more general predictive sciences, and the symposium celebrates the final year of the 5-year RIKEN Pioneering Project "Prediction for Science" and the launch of "RIKEN Prediction Science", a theme of "Transformative Research Innovation Platform of RIKEN platforms (TRIP)".