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 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.
Since September 2016, RIKEN Advanced Institute for Computational Science (AICS) has launched a project titled “Data assimilation as an innovation hub to connect mathematical science, experimental and observational science, and computational science.” This symposium follows the success of the 2nd International Symposium that was held as the 4th International Symposium on Data Assimilation (ISDA2015) in February 2015 at RIKEN AICS, Kobe, and 6th Japanese Data Assimilation Workshop held in February 2016 at Japan Agency for Marine-Earth Science and Technology, Yokohama, Japan. The symposium will focus on the cross-cutting issues shared in broad applications of data assimilation from geoscience to neuroscience and bioscience. In particular, the symposium will enhance discussions among researchers with various background on, for example, non-Gaussian and nonlinear data assimilation problems, Big Data, high-performance computation (HPC), and advanced intelligence (AI)-related issues, multi-scale and multi-component treatments, and mathematical problems.
[What's new]
Feb. 20, 2017
- You can order lunch boxes for Day 2-4 with a lunch order sheet that you will receive at the registration desk on Day 1.
- We accept cash only.
Feb. 10, 2017
- Registration closed.
Jan. 27, 2017
- The 3rd RIKEN International Symposium on Data Assimilation (RISDA2017) webpage was redesigned.
- Registration opened.
