Meteo-GRID: Performing Local Weather Forecast Using GRID Computing C.-J. Lenz, D. Majewski Deutscher Wetterdienst (DWD)

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Presentation transcript:

Meteo-GRID: Performing Local Weather Forecast Using GRID Computing C.-J. Lenz, D. Majewski Deutscher Wetterdienst (DWD)

Introduction to Meteo-GRID Tasks of Meteo-GRID, data flow in Meteo-GRID Presentation of the GUI of the LM-Plugin Application example Contents

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 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...)

Behr & Wojcik

Disasters (2)

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

Information and Data Flow (1) 1. Set up of LM-domain User Global topographical data set (GIS), ~ 7 GByte Topographical data set (~ 1 MByte)DWD 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)

Information and Data Flow (2) 2. Define forecast date and range GME data base (Oracle) Hourly initial and lateral boundary data sets on GME grid (~50 Mbyte) User DWD Extraction of GME results covering the LM domain at DWD (SGI Origin O 2000, IBM-RS/6000-SP) ~ 30 min. wallclock time

Information and Data Flow (3) 3. Perform GME2LM interpolation on EUROGRID HPC 1 User DWD Topographical data set Initial and lateral boundary data sets on GME grid HPC 1 GME2LM interpolation of GME results to LM grid ~1 MByte ~50 MByte Initial and hourly lateral boundary data sets on LM grid (50 MByte to 20 GByte)

Information and Data Flow (4) 4. Perform LM-forecast on EUROGRID HPC 2 User HPC 2 LM calculation of weather forecast 50 MByte to 20 GByte LM-forecast data visualization Initial and hourly lateral boundary data sets on LM grid HPC 1 50 MByte to 20 GByte hourly forecast data of LM (50 MByte to 20 GByte)

Information and Data Flow (5) 5. Visualization of LM results User HPC 2 Visualization of model results Graphic files (up to 1 MByte) up to 1 MByte

GUI of the LM Plugin (1)

GUI of the LM Plugin (2)

GUI of the LM Plugin (3)

GUI of the LM Plugin (4)

GUI of the LM Plugin (5)

GUI of the LM Plugin (6)

Application example -Selection of hurricane Isabel /US East Coast, August 2003)