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High-resolution numerical modeling and predictability of atmospheric flows. M. Ehrendorfer, A. Gohm and G. J. Mayr Institut für Meteorologie und Geophysik Universität Innsbruck. Vortrag am Zweiter Mini-Workshop Konsortium Hochleistungsrechnen Universität Innsbruck, Austria 12. März 2004.

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high resolution numerical modeling and predictability of atmospheric flows

High-resolution numerical modelingand predictability of atmospheric flows

M. Ehrendorfer, A. Gohm and G. J. Mayr

Institut für Meteorologie und Geophysik

Universität Innsbruck

Vortrag am

Zweiter Mini-Workshop

Konsortium Hochleistungsrechnen

Universität Innsbruck, Austria

12. März 2004

http://www2.uibk.ac.at/meteo

slide2

High-Resolution Numerical Modeling and Predictability of Atmospheric Flows

Outline

  • Atmospheric models
  • Stability of flows
    • specific error structures: singular vectors, data assimilation
  • Additional remarks
  • High-resolution modeling
    • Past research: single-processor computing
    • Current research: multi-processor parallel computing
      • Introducing the numerical models
      • Introducing the computing facilities
      • An example: simulation of bora winds
      • Outlook: numerical weather prediction for the Winter Universiade 2005

IMGI HPC workshop 2004

slide3

7 Variables:wind v, densityr, potentialtemperatureq,

pressure p, temperature T

budget equations: momentum, mass, energy

slide4

1922

P. Lynch, Met Éireann, Dublin

slide5

European Centre for Medium-Range Weather Forecasts

ECMWF

Reading, UK

Operational models: 10^7 – 10^8 variables

slide6

- sensitive dependence on i.c.

- preferred directions of growth

Lorenz

1984

model

slide7

growing directions:

stability of the flow

correct for in initial condition

zid-cc

slide10

Nonlinear error growth

0.01%

tau_d = 12 h

slide11

Optimized TL error growth

data assimilation

stability, error dynamics

tau_d = 4.9 h

o3800

12690^2

slide12

Science Case

for Large-scale

Simulation

pnl.gov/scales

SIAM Rev. 2003

slide13

High-Resolution Numerical Modeling and Predictability of Atmospheric Flows

Outline

  • Atmospheric models
  • Stability of flows
    • specific error structures: singular vectors, data assimilation
  • Additional remarks
  • High-resolution modeling
    • Past research: single-processor computing
    • Current research: multi-processor parallel computing
      • Introducing the numerical models
      • Introducing the computing facilities
      • An example: simulation of bora winds
      • Outlook: numerical weather prediction for the Winter Universiade 2005

IMGI HPC workshop 2004

slide14

flow around mountains

flow through mountain gaps

flow over mountains

orographically induced precipitation

High-Resolution Numerical Modeling of Atmospheric Flows

Past Research – Single-processor computing (Origin XL, o2000)

IMGI HPC workshop 2004

slide15

Numerical modeling with realistic orography

  • case studies
  • weather prediction

Flow around the Alps

Flow over the Alps

High-Resolution Numerical Modeling of Atmospheric Flows

Current Research – Multi-processor parallel computing (Origin o3800, ZID-CC)

IMGI HPC workshop 2004

slide16

Global Model (ECMWF*)

Limited Area Model (RAMS**)

boundary conditions

analysis or forecast

  • spectral technique
  • single global domain
  • x  40 km (TL511)
  • finite-difference technique
  • several nested domains, covering limited areas, centered near the location of interest
  • x  100 m – 1 km

* European Centre for Medium-Range Weather Forecasts (Reading, UK)

** Regional Atmospheric Modeling System (CSU, Ft. Collins, USA)

High-Resolution Numerical Modeling of Atmospheric Flows

We are using two models

IMGI HPC workshop 2004

slide17

Global Model @ ECMWF (UK)

RAMS @ ZID (IBK)

ftp

ZID-CC compute-cluster

16 servers (Transtec), each with 2 processors (2.2 GHz Intel Xeon)

IBM supercomputer

2 clusters, each with 30 servers (p690), each server having 32 processors (1.3 GHz Power4)

Origin o3800 compute-server

48 processors (600 MHz MIPS R14000)

High-Resolution Numerical Modeling of Atmospheric Flows

IMGI HPC workshop 2004

slide18

High-Resolution Numerical Modeling of Atmospheric Flows

An example: Simulation of bora winds to the lee of the Dinaric Alps

  • Parallel computing on ZID-CC cluster
  • 8 processors
  • master–slave configuration
  • domain decomposition technique
  • RAMS model setup
  • 5 nested grids
  • x = 267 m to 65 km
  • 56 vertical levels
  • 6443024 grid points
  • 1440 master time steps for 1-day forecast

IMGI HPC workshop 2004

slide19

Every hour:

data I/O from/to hard disk by master node

}

master

Every time step:

I/O communication

elapsed seconds

}

nodes

Every 20 minutes: update with radiative transfer model

number of time steps

High-Resolution Numerical Modeling of Atmospheric Flows

An example: Simulation of bora winds to the lee of the Dinaric Alps

  • Computing time for RAMS at ZID-CC cluster with 8 CPUs
  • ~180 seconds for a 60-second time step
  • 73.8 hours for a 24-hour simulation

IMGI HPC workshop 2004

slide20

Adriatic

Sea

Dinaric

Alps

DLR Falcon backscatter lidar

flow

bora

simulation

observation

High-Resolution Numerical Modeling of Atmospheric Flows

An example: Simulation of bora winds to the lee of the Dinaric Alps

IMGI HPC workshop 2004

slide21

Goal

  • Set up RAMS as NWP model for the Innsbruck region
  • Compute daily forecast on ZID-CC and/or Origin 3800

Benefit

Resolving various weather phenomena occurring in different spatial scales: between the Alpine scale (L~100 km) and the valley scale (L~1 km)

High-Resolution Numerical Modeling of Atmospheric Flows

Outlook: Numerical Weather Prediction (NWP) @ IMGI/ZID

IMGI HPC workshop 2004

slide23

Ehrendorfer et al. 1999

80.000^2

iterative Lanczos

F. Rabier, Météo France

slide24

A. Simmons, ECMWF

Heutige 5-Tages Prognose ebenso gut

wie 4-Tages Prognose for 6 Jahren

slide26

Temperatur-

Unsicherheit

aus

Ensemble

von

50 Vorhersagen

(anfänglich

leicht

verschieden)

ECMWF

ad