Large-scale data systems at the National Center for Atmospheric Research (NCAR)

Presented at the National data integrity conference: enabling research: new challenges & opportunities held on May 7-8, 2015 at Colorado State University, Fort Collins, Colorado. Researchers, administrators and integrity officers are encountering new challenges regarding research data and integrity. This conference aims to provide attendees with both a high level understanding of these challenges and impart practical tools and skills to deal with them. Topics will include data reproducibility, validity, privacy, security, visualization, reuse, access, preservation, rights and management.Anke Kamrath is the Director of Operations and Services, Computational and Information Systems Laboratory at the National Center for Atmospheric Research.PowerPoint presentation given on May 8, 2015

Position paper on high performance computing needs in earth system prediction

The article of record as published may be found at http://dx.doi.org/10.7289/V5862DH3The United States experiences some of the most severe weather on Earth. Extreme weather or climate events - such as hurricanes, tornadoes, flooding, drought, and heat waves - can devastate communities and businesses, cause loss of life and property, and impact valuable infrastructure and natural resources. The number and severity of extreme weather and climate events in the U.S. has risen since 1980, and is projected to continue rising this century. Growing populations in vulnerable areas create increased risks. If current trends continue, damages from extreme weather and climate events could grow four-fold by 2050. Predictions and projections of weather and extreme events across time scales from weather to climate rely on sophisticated numerical models running on High Performance Computing (HPC) systems, which press the frontier of the Nation’s HPC capability. The Nation’s Earth system modeling community has a unique set of HPC requirements which differ from industry needs. Typically, HPC advances are measured using computational peak performance metrics that are ill-suited to Earth system modeling applications. We advocate for a shift in processor design to increase emphasis on memory bandwidth, so Earth system models run more efficiently and better serve the public need