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Horel, John
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English
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- Description:
- Weather-related research often requires synthesizing vast amounts of data that need archival solutions that are both economical and viable during and past the lifetime of the project. Public cloud computing services (e.g., from Amazon, Microsoft, or Google) or private clouds managed by research institutions are providing object data storage systems potentially appropriate for long-term archives of such large geophysical data sets. We illustrate the use of a private cloud object store developed by the Center for High Performance Computing (CHPC) at the University of Utah. Since early 2015, we have been archiving thousands of two-dimensional gridded fields (each one containing over 1.9 million values over the contiguous United States) from the High-Resolution Rapid Refresh (HRRR) data assimilation and forecast modeling system. The archive is being used for retrospective analyses of meteorological conditions during high-impact weather events, assessing the accuracy of the HRRR forecasts, and providing initial and boundary conditions for research simulations. The archive is accessible interactively and through automated download procedures for researchers at other institutions that can be tailored by the user to extract individual two-dimensional grids from within the highly compressed files. Characteristics of the CHPC object storage system are summarized relative to network file system storage or tape storage solutions. The CHPC storage system is proving to be a scalable, reliable, extensible, affordable, and usable archive solution for our research.
- Keyword:
- weather, analyses, forecasts, atmospheric science, numerical weather prediction, and data assimilation
- Subject:
- atmospheric science and numerical weather prediction
- Creator:
- Horel, John and Blaylock, Brian
- Contributor:
- University of Utah Center for High Performance Computing, NOAA Earth Systems Research Laboratory, and NOAA Environmental Modeling Center
- Owner:
- BRIAN MCBRIDE
- Based Near Label Tesim:
- Alaska and United States
- Language:
- English and binary
- Date Uploaded:
- 07/10/2019
- Date Modified:
- 07/30/2019
- Date Created:
- April 18, 2015 to present
- License:
- CC BY – Allows others to use and share your data, even commercially, with attribution.
- Resource Type:
- Dataset
- Identifier:
- https://doi.org/10.7278/S5JQ0Z5B