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An Integration and Evaluation Framework for ESPC Coupled Models
Author(s) -
Ben P. Kirtman
Publication year - 2014
Language(s) - English
Resource type - Reports
DOI - 10.21236/ada615930
Subject(s) - computer science , systems engineering , engineering
: To realize its potential, a U.S. Earth system modeling and prediction capability must encompass a network of agencies and organizations that contribute model components, infrastructure, and scientific and technical expertise. The model component contributions must be integrated using coupling software, optimized as a whole, and the predictive skill of the resulting models assessed using standard metrics. We propose to provide these integrative functions for the Earth System Prediction Capability (ESPC), using as a reference application a version of the Community Earth System Model (CESM) running an optimized version of the HYbrid Coordinate Ocean Model (HYCOM). We will establish a Coupling Testbed as a resource available to ESPC modelers, with Testbed leads who have developed infrastructure for major modeling systems and can engage and motivate interactions with modelers at NASA, NOAA, and other centers. The Testbed will be used to explore and prototype design and performance challenges related to integration, migrate optimizations to ESPC codes, and advance convergence of coupling interfaces to support knowledge transfer and controlled experimentation. We will work to broaden existing multi-agency computational working groups to address ESPC performance concerns and new application requirements. We will advance and update a coupled CESM-HYCOM system prototyped under other funding with a version of HYCOM optimized for accelerator-based architectures. This HYCOM version will be obtained from a linked proposal, entitled Accelerated Prediction of the Polar Ice and Global Ocean. Performance of the ocean component is of particular interest because we choose to emphasize science applications that are of greatest interest to the Navy, and this is best done at ocean eddy resolving scales. The coupled system will be suitable for data assimilative prediction problems with timescales from one week to up to one year.

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