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Meteo-GRID: Performing Local Weather Forecast Using GRID Computing C.-J. Lenz, D. Majewski Deutscher Wetterdienst (DWD) e-mail: claus-juergen.lenz@dwd.de detlev.majewski@dwd.de. Contents. Introduction to Meteo-GRID Tasks of Meteo-GRID, data flow in Meteo-GRID
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Meteo-GRID: Performing Local Weather Forecast Using GRID Computing C.-J. Lenz, D. Majewski Deutscher Wetterdienst (DWD) e-mail: claus-juergen.lenz@dwd.de detlev.majewski@dwd.de
Contents • Introduction to Meteo-GRID • Tasks of Meteo-GRID, data flow in Meteo-GRID • Presentation of the GUI of the LM-Plugin • Application example
Goal of Meteo-GRID To provide high-resolution short range weather forecasts with the relocatable nonhydrostatic “Lokal-Modell” (LM) of the Deutscher Wetterdienst (DWD) for any desired region in the world via Internet and EUROGRID
Meteo-GRID - ... is one of the application-specific GRID workpackages of EUROGRID - ...is done by close collaboration of three EUROGRID partners: - Deutscher Wetterdienst (DWD) - Centro Svizzero di Calcolo Scientifico (CSCS) - Centre Nationale de Récherche Scientifique - Institut du Développement et des Ressources en Informatique Scientifique (CNRS-IDRIS)
What`s special about Meteo-GRID ? (1) - Real-time weather forecasting is a time-critical task, a 48-h forecast must be completed in less than 60 minutes - LM is a large MPP code of about 100.000 lines of code, Fortran95, MPI for message passing - Weather forecasting is computationally expensive ~ 4000 Flop/grid point and time step ~ 15 Tflop for a 48-h forecast (160 x 160 x 35 grid points, grid resolution ~ 7 km) ~ 3000 sec at a sustained speed of 5 Gflop/s
What`s special about Meteo-GRID ? (2) - Weather forecasting requires high band width for data transfer Forecast data (at hourly intervals): (48+1) x 20 Mbyte = 1 GByte Transfer in less than 1 hour: 2.4 Mbit/sec - “Weather” has large social and economic impact worldwide (storms, floodings, snow, freezing rain ...)
Disasters (1) @dpa @ Behr & Wojcik
Disasters (2) www.dresden.de www.dresden.de www.dresden.de @dpa
Tasks of Meteo-GRID (1) - Selection of model domain, grid resolution, forecast date and forecast range, forecast products in a Graphical User Interface (GUI)
Tasks of Meteo-GRID (2) - Derivation of topographical data for the selected model domain from high-resolution (1 km x 1 km) data sets at DWD water peat clay loamy clay loam loamy sand sand rock, concrete ice, glacier undefined
Tasks of Meteo-GRID (3) - Extraction of initial data and lateral boundary data sets for LM from result data of the global model GME of DWD from the ORACLE data base
Tasks of Meteo-GRID (4) - Interpolation of GME results to the LM model grid (interpolation program GME2LM) is performed on any supercomputer available in EUROGRID - LM forecast run is performed on any supercomputer available in EUROGRID
Tasks of Meteo-GRID (5) - Forecast data (up to 20 GByte in GRIB code) are returned to the user via the internet and EUROGRID AND/OR - Visualization of LM forecasts ( 1 to 5 dimensional graphics) on a computer within EUROGRID or on the user’s computer - Verification and validation of LM forecasts for any region worldwide
domain corners, resolution Topographical data set (~ 1 MByte) Information and Data Flow (1) 1. Set up of LM-domain User DWD Global topographical data set (GIS), ~ 7 GByte GUI: Selection of - domain corners - grid resolution - forecast date - forecast range - forecast products Calculation at DWD on SGI Origin, IBM RS/6000-SP (~ 15 min. wallclock time)
date (actual, past) Hourly initial and lateral boundary data sets on GME grid (~50 Mbyte) Information and Data Flow (2) 2. Define forecast date and range User DWD GME data base (Oracle) Extraction of GME results covering the LM domain at DWD (SGI Origin O 2000, IBM-RS/6000-SP) ~ 30 min. wallclock time
Initial and hourly lateral boundary data sets on LM grid (50 MByte to 20 GByte) Information and Data Flow (3) 3.Perform GME2LM interpolation on EUROGRID HPC 1 User DWD HPC 1 ~1 MByte Topographical data set GME2LM interpolation of GME results to LM grid Initial and lateral boundary data sets on GME grid ~50 MByte
Initial and hourly lateral boundary data sets on LM grid hourly forecast data of LM (50 MByte to 20 GByte) Information and Data Flow (4) 4.Perform LM-forecast on EUROGRID HPC 2 User HPC 2 HPC 1 50 MByte to 20 GByte LM calculation of weather forecast LM-forecast data visualization 50 MByte to 20 GByte
Graphic files (up to 1 MByte) Information and Data Flow (5) 5. Visualization of LM results HPC 2 forecast products User Visualization of model results up to 1 MByte
Application example • Selection of hurricane Isabel /US East Coast, 18 - 20 August 2003)