Continued advancement in weather and climate prediction models depend on (1) increasing spatial resolution, (2) increasing the number of ensemble members, (3) additional physical processes (eg. ocean, land, chemistry, etc) that were unaffordable decades ago, and (4) increasing the scale and accuracy of data assimilation to incorporate billions of observations collected by next-generation, high-resolution satellites, radars, and a myriad of in situ sensors worldwide. It will also require next generation exascale systems with at least 1000 times more computing power than used currently.

    However, massive increases in computing power will not be sufficient to overcome significant obstacles in running such models on exascale systems.  Issues include under- or unexposed parallelism, load-imbalance, and critical dependence on scarce memory bandwidth (low computational intensity).  Most weather prediction models use less than 5 percent of the peak computational capabilities of today’s CPU chips, and less than 2 percent of the latest generation GPU and MIC chips. Future chips are expected to continue this downward trend of diminishing computational benefit.  Growing awareness of these problems led to formation of a multi-agency (NOAA, NASA, NCAR, DoE, DoD) working group in the Earth System Prediction Capability (ESPC), and spawned meetings on the topic with industry.

    While hardware improvements will help, effective utilization of next generation systems with millions of compute cores will require adapting and rewriting applications to better prepare them for exascale. Weather and climate models are complex, multi-component models often designed separately, and then coupled or linked together. Lack of overall system design can limit parallelism, and make it difficult to understand, modify, test, and maintain them.  In addition, the scientific algorithms, grids, and formulations used are motivated by ease of development and scientific accuracy of the solution at the expense of computational efficiency, portability and maintainability. In the exascale era, a balance between accuracy and computational efficiency may be needed to further advance capabilities of our earth system models.

    To address these challenges requires cooperation and collaboration between modeling teams, computational experts and software designers. We invite your submissions in a wide range of topics including model and assimilation development, algorithms, software design, languages, high performance I/O, performance portability, and computing hardware.