Introduction

Data assimilation (DA) is a cross-disciplinary science to synergize computer simulations and real-world data, based on statistical mathematics and dynamical systems theory. DA has long been playing a crucial role in numerical weather prediction (NWP), and recently, DA started to be applied more widely to numerical model simulations beyond geophysical applications, such as planetary science and biological science. 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 7th International Symposium on Data Assimilation (ISDA2019) will be held at the RIKEN Center for Computational Science (R-CCS) and continues a series of well received events: 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 researches.

The symposium will focus on the cross-cutting issues shared in broad applications of data assimilation from geoscience to various physical and biological sciences. In particular, the symposium will enhance discussions among researchers with various background on, for example, non-Gaussian and nonlinear data assimilation problems, Big Data Assimilation (BDA), high-performance computation (HPC), Uncertainty Quantification (UQ), advanced intelligence (AI) and machine learning, multi-scale and multi-component treatments, observational issues, and mathematical problems.