High-resolution numerical modelingand predictability of atmospheric flows

M. Ehrendorfer, A. Gohm and G. J. MayrInstitut für Meteorologie und Geophysik

Universität Innsbruck

Vortrag am Zweiter Mini-Workshop

Konsortium Hochleistungsrechnen

Universität Innsbruck, Austria12. März 2004

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

IMGI HPC workshop 2004

Outline

High-Resolution Numerical Modeling and Predictability of Atmospheric Flows

1. Atmospheric models

2. Stability of flows

specific error structures: singular vectors, data assimilation

3. Additional remarks

4. 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

7 Variables: wind v, density , potential temperature pressure p, temperature T

budget equations: momentum, mass, energy

P. Lynch, Met Éireann, Dublin

1922

European Centre for Medium-Range Weather ForecastsECMWFReading, UK

Operational models: 10^7 – 10^8 variables

- sensitive dependence on i.c.- preferred directions of growth

Lorenz1984 model

growing directions:stability of the flowcorrect for in initial condition

zid-cc

o3800NAG

ZID-CC

French storm 24/12/1999/1200

Nonlinear error growth0.01%

tau_d = 12 h

o380012690^2

Optimized TL error growth data assimilationstability, error dynamics

tau_d = 4.9 h

SIAM Rev. 2003

Science Casefor Large-scaleSimulation

pnl.gov/scales

IMGI HPC workshop 2004

Outline

High-Resolution Numerical Modeling and Predictability of Atmospheric Flows

1. Atmospheric models

2. Stability of flows

specific error structures: singular vectors, data assimilation

3. Additional remarks

4. 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

High-Resolution Numerical Modeling of Atmospheric Flows

flow over mountains

orographically induced precipitation

flow around mountains

flow through mountain gaps

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

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

High-Resolution Numerical Modeling of Atmospheric Flows

IMGI HPC workshop 2004

Numerical modeling with

realistic orography• case studies• weather prediction

Flow around the AlpsFlow over the Alps

boundary conditions

analysis or forecast

We are using two modelsGlobal Model (ECMWF*)

* European Centre for Medium-Range Weather Forecasts (Reading, UK)** Regional Atmospheric Modeling System (CSU, Ft. Collins, USA)

• spectral technique• single global domain• x 40 km (TL511)

High-Resolution Numerical Modeling of Atmospheric Flows

IMGI HPC workshop 2004

Limited Area Model (RAMS**)

• finite-difference technique• several nested domains, covering limited areas, centered near the location of interest• x 100 m – 1 km

Global Model @ ECMWF (UK)

IBM supercomputer2 clusters, each with 30 servers (p690), each server having 32 processors (1.3 GHz Power4)

Origin o3800 compute-server48 processors (600 MHz MIPS R14000)

RAMS @ ZID (IBK)

ZID-CC compute-cluster16 servers (Transtec), each with 2 processors (2.2 GHz Intel Xeon)

ftp

High-Resolution Numerical Modeling of Atmospheric Flows

IMGI HPC workshop 2004

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

Parallel computing on ZID-CC cluster• 8 processors• master–slave configuration• domain decomposition technique

High-Resolution Numerical Modeling of Atmospheric Flows

IMGI HPC workshop 2004

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

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

number of time steps

elap

sed

seco

nds

}nodes

}master

Every time step:I/O communication

Every 20 minutes: update with radiative transfer model

Every hour: data I/O from/to hard disk by master node

High-Resolution Numerical Modeling of Atmospheric Flows

IMGI HPC workshop 2004

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

High-Resolution Numerical Modeling of Atmospheric Flows

IMGI HPC workshop 2004

DLR Falcon backscatter lidar

observation

AdriaticSea

DinaricAlps

flow

simulation

bora

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

High-Resolution Numerical Modeling of Atmospheric Flows

IMGI HPC workshop 2004

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)

F. Rabier, Météo France

Ehrendorfer et al. 1999

80.000^2

iterative Lanczos

A. Simmons, ECMWF

Heutige 5-Tages Prognose ebenso gut wie 4-Tages Prognose for 6 Jahren

Temperatur-Unsicherheit

aus Ensemble von 50 Vorhersagen(anfänglichleicht verschieden)ECMWF

A. Simmons, ECMWF amplification of 1-day forecast error