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The Design of a Modern Information Technology Infrastructure to Facilitate Research-to-Operations Transition for NCEP’s Modeling Suites

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  • 1 NOAA OAR/ESRL Global Systems Division, and University of Colorado/Cooperative Institute for Research in the Environmental Sciences, and Developmental Testbed Center, Boulder, Colorado
  • | 2 NCAR Research Applications Laboratory, and Developmental Testbed Center, Boulder, Colorado
  • | 3 NOAA NWS/NCEP Environmental Modeling Center, College Park, Maryland
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Abstract

NOAA/NCEP runs a number of numerical weather prediction (NWP) modeling suites to provide operational guidance to the National Weather Service field offices and service centers. A sophisticated infrastructure, which includes a complex set of software tools, is required to facilitate running these NWP suites. This infrastructure needs to be maintained and upgraded so that continued improvements in forecast accuracy can be achieved. This contribution describes the design of a robust NWP Information Technology Environment (NITE) to support and accelerate the transition of innovations to NOAA operational modeling suites.

Through consultation with and at the request of the NOAA NCEP Environmental Modeling Center, a survey of segments of the national NWP community, and a review of selected aspects of the computational infrastructure of several modeling centers was conducted, which led to the following elements being considered as key for NITE: data management, source code management and build systems, suite definition tools, scripts, workflow management, experiment database, and documentation and training.

The design for NITE put forth by the DTC would make model development by NOAA staff and their external collaborators more effective and efficient. It should be noted that NITE was not designed to work exclusively for a certain modeling suite; instead it transcends the current operational suites and is applicable to the expected evolution in NCEP systems. NITE is particularly important for community engagement in the Next-Generation Global Prediction System, which is expected to be an Earth modeling system including several components.

© 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

CORRESPONDING AUTHOR: Ligia Bernardet, ligia.bernardet@noaa.gov

Abstract

NOAA/NCEP runs a number of numerical weather prediction (NWP) modeling suites to provide operational guidance to the National Weather Service field offices and service centers. A sophisticated infrastructure, which includes a complex set of software tools, is required to facilitate running these NWP suites. This infrastructure needs to be maintained and upgraded so that continued improvements in forecast accuracy can be achieved. This contribution describes the design of a robust NWP Information Technology Environment (NITE) to support and accelerate the transition of innovations to NOAA operational modeling suites.

Through consultation with and at the request of the NOAA NCEP Environmental Modeling Center, a survey of segments of the national NWP community, and a review of selected aspects of the computational infrastructure of several modeling centers was conducted, which led to the following elements being considered as key for NITE: data management, source code management and build systems, suite definition tools, scripts, workflow management, experiment database, and documentation and training.

The design for NITE put forth by the DTC would make model development by NOAA staff and their external collaborators more effective and efficient. It should be noted that NITE was not designed to work exclusively for a certain modeling suite; instead it transcends the current operational suites and is applicable to the expected evolution in NCEP systems. NITE is particularly important for community engagement in the Next-Generation Global Prediction System, which is expected to be an Earth modeling system including several components.

© 2017 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

CORRESPONDING AUTHOR: Ligia Bernardet, ligia.bernardet@noaa.gov
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