Data Serving Platform for HYCOM Ocean Prediction System Outputs
Abstract
Data Serving Platform for HYCOM Ocean Prediction System OutputsPI: Eric P. ChassignetCenter for Ocean-Atmospheric Prediction Studies,, Florida State University, Tallahassee, FLOffice of Naval Research (ONR); Scientific Division: Physical OceanographyONR Program Man,ager: Code 322 / Dr. Scott HarperProject Summary/AbstractFlorida State University (FSU) and the Naval Research Laboratory (NRL) (Ste,nnis Space Center) are presently funded by the Office of Naval research (ONR) to develop, evaluate, and investigate the dynamics of,the data assimilative HYCOM-CICE-NCODA (HYbrid Coordinate Ocean Model - Los Alamos sea ice model - NRL Coupled Ocean Data assimilat,ion) with tides. A specific subgoal of these projects is the public/broad distribution of the ocean prediction system outputs so tha,t the ocean modeling community at large can evaluate the usefulness of the outputs, especially the models ability to provide accura,te boundary conditions for coastal and regional models. For the past ten plus years, we have put in place a comprehensive data manag,ement strategy to make most ocean prediction system forecasts available to general users in near real time, i.e., within 12 hours of, its creation at Department of Defense (DoD) High Performance Computing (HPC) Centers.In order to achieve an efficient dissemination, of the ocean model outputs to the community, it is essential to have a data serving platform that facilitates efficient storage, ma,nagement, analysis, and distribution of the data generated by the HYCOM ocean prediction systems. The proposed acquisition of a stor,age appliance and computing cluster is to replace the current system that has reached its end of life. The new system will provide s,torage capacity of approximately 5 Petabytes (PB) and high-performance compute nodes in support of accelerating data transferring,pr,ocessing, and serving. This proposed system will supersede the existing data processing system with limited storage capacity and leg,acy compute cluster. In addition, this platform will integrate with existing investment/infrastructure of the FSU Research Computing, Center (RCC), enabling educational and research related activities surrounding this data in the Oceanographic, Meteorological, and,Data Science disciplines. The present-day system has been economically serving HYCOM model outputs for more than 8 years and due to,disk media age and partsavailability it will no longer have vendor support nor the spare capacity to store additional data by early,2022. Growing our data serving capacity is central to the continued success of serving high resolution HYCOM outputs. In addition to, making the large multi-terabyte datasets easilyaccessible by students, partners, and the oceanographic community at large, such a s,ystem will allow us to perform highly data intensive diagnostic tests that are needed to evaluate the performance of the Navys ocea,n prediction systems. Publicly releasable
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Apr 01, 2022
- Source ID
- N000142212359
Entities
People
- Eric Chassignet
Organizations
- Florida State University
- Office of Naval Research
- United States Navy