The next generation of numerical models used to simulate the Earth's climate and global weather represent a significant advancement in humanity's ability to realistically and accurately model the Earth System. These new models solve complex mathematical equations that describe the motion, chemistry, and energy transfer of the planet's oceans and atmosphere at spatial scales fine enough to capture individual storms. As a result, these so-called 'Global Storm Resolving Models' (GSRMs) generate tremendous amounts of numerical data. Moreover, the structure of these data is far more complex than it is for current models. The goal of this work, Project Raijin, is to develop and provide the global weather and climate modeling communities with the software tools they need to make sense of these massive and complex data sets. Without the ability to effectively explore and interrogate GSRM outputs the value of these new models will be greatly limited. The tools created by Project Raijin will be developed under an open source license and made freely available to anyone in the world who wants to use, or even improve, them.
The transition by the global weather and climate modeling communities to kilometer-scale resolutions enabled by unstructured grid 'dynamical cores' comes with a two-fold cost. First, the increased model resolution results in the output of massive volumes of data, further exacerbating the 'Big Data' problem. Second, the existing, general purpose software tools commonly used for analyzing, post-processing, and visualizing geoscience model outputs primarily operate on structured grid data, providing little or no support for unstructured meshes. The goal of this project, called Raijin, is to enhance the analysis and visualization tool landscape by developing community-owned, sustainable, scalable tools that facilitate operating on unstructured climate and global weather data. Working in close collaboration with atmospheric modelers the researchers plan to: 1. develop extensible, scalable, open source tools supporting fundamental analysis and visualization methods capable of operating directly (without resampling) on unstructured grid model outputs at global storm resolving resolutions; and 2. establish an active, vibrant community of user-contributors, committed to extending our work beyond the scope of this project, and helping ensure the long term sustainability of the project. The primary environment for this effort will be the Scientific Python Ecosystem. The researchers will leverage, in particular, the NSF-supported, open development Xarray and Dask packages, and the Pangeo community. To better support both of our primary goals, our work will be conducted under an open development model that encourages participation in all aspects of the project's development.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
|Effective start/end date||9/1/21 → 8/31/24|
- National Science Foundation: $281,960.00