by National Aeronautics and Space Administration, National Technical Information Service, distributor in [Washington, DC, Springfield, Va .
Written in English
|Other titles||High performance computing and four dimensional data assimilation.|
|Statement||Miloje S. Kakivic, project leader; principal investigator, Geoffrey C. Fox.|
|Series||[NASA contractor report] -- 206797., NASA contractor report -- NASA CR-206797.|
|Contributions||Fox, Geoffrey C., United States. National Aeronautics and Space Administration.|
|The Physical Object|
•Four Dimensional Data Assimilation (4D DA) requires having information on the state of the system at many different times •In some approaches, information at different times is achieved by running a model forward (Tangent-Linear) and backward (Adjoint) in time •Optimal results with a . Abstract. The Navy Coastal Ocean Model Four-Dimensional Variational Assimilation (NCOM 4DVAR) system is an analysis software package that is designed to supplement the current capability of the operational analysis/prediction system known as the Relocatable Navy Coupled Ocean Model (Relo NCOM) : Scott Smith, Hans Ngodock, Matthew Carrier, Jay Shriver, Philip Muscarella, Innocent Souopgui. Four-Dimensional Model Assimilation of Data: High Performance Computing and Communications. As the report's summary states: "The HPCC program is driven by the recognition that unprecedented computational power and capability [are] needed to investigate and understand a wide range of scientific and engineering `grand challenge' problems. PDF | Driven by the emerging requirements of High Performance Computing (HPC) architectures, the main focus of this work is the interplay of | Find, read and cite all the research you need on.
The STAR Institute with guidance from the Ohio Supercomputer Center is working on porting the Climate Four Dimensional Data Assimilation (CFDDA) technology developed by the National Center for Atmospheric Research to version 3 of the Weather and Research Forecast (WRF) model for use on systems within the Department of Defense High Performance. A Uniform Memory Model for Distributed Data Objects on Parallel Architectures (V Balaji & R W Numrich) and other papers; Readership: Academics and researchers specializing in high performance computing, especially meteorological scientists, and supercomputer manufacturers. A variety of high-resolution atmospheric-model applications are running on the high performance computer cluster at Dugway Proving Ground (DPG), with the objective of providing accurate weather information to forecasters, test managers and planners, and decision-support staff at ATEC test ranges. The foundation of these applications is the 4D Weather (4DWX) forecasting system, which is built. Benefits: This data assimilation system was designed to take advantage of local High Performance Computing (HPC) Numerical Weather Prediction (NWP) and Data Assimilation. Real-Time Four-Dimensional Data Assimilation (RT-FDDA) > see all products.
The method of four dimensional variational data assimilation (4Dvar) is a widely known technique to enhance forecast skills of CTMs (Chemistry-Transport-Models) by ingesting in-situ and. libROM is a collection of C++ classes that compute reduced order models and hyperreduced order models for systems of ordinary differential equations. libROM includes parallel, adaptive methods for proper orthogonal decomposition, and parallel, non-adaptive methods for hyperreduction using the discrete empirical interpolation method. Nonoscillatory advection schemes contain switches, so that the derivative of the numerical solution at any time step with respect to that at the previous time step may be discontinuous. In consequence, sensitivities calculated using the adjoint of the numerical scheme may be discontinuous or by: Fatode is a Fortran library for the integration of ordinary differential equations with direct and adjoint sensitivity analysis capabilities. The paper describes the capabilities, implementation, code organization, and usage of this package. Fatode implements four families of methods: explicit Runge--Kutta for nonstiff problems, fully implicit Runge--Kutta, singly diagonally implicit Runge Cited by: