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

2. 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

3. 7 Variables: wind v, density , potential temperature  pressure p, temperature T budget equations: momentum, mass, energy

4. P. Lynch, Met Éireann, Dublin 1922

5. European Centre for Medium-Range Weather Forecasts ECMWF Reading, UK Operational models: 10^7 – 10^8 variables

6. - sensitive dependence on i.c. - preferred directions of growth Lorenz 1984 model

7. growing directions: stability of the flow correct for in initial condition zid-cc

8. o3800 NAG

9. ZID-CC French storm 24/12/1999/1200

10. Nonlinear error growth 0.01% tau_d = 12 h

11. o3800 12690^2 Optimized TL error growth data assimilation stability, error dynamics tau_d = 4.9 h

12. SIAM Rev. 2003 Science Case for Large-scale Simulation pnl.gov/scales

13. 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

14. 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)

15. 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

16. boundary conditions analysis or forecast We are using two models Global 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

17. Global Model @ ECMWF (UK) 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) RAMS @ ZID (IBK) ZID-CC compute-cluster 16 servers (Transtec), each with 2 processors (2.2 GHz Intel Xeon) ftp High-Resolution Numerical Modeling of Atmospheric Flows IMGI HPC workshop 2004

18. 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

19. 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 elapsed seconds } 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

20. 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 Adriatic Sea Dinaric Alps flow simulation bora

21. 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)

23. F. Rabier, Météo France Ehrendorfer et al. 1999 80.000^2 iterative Lanczos

24. A. Simmons, ECMWF Heutige 5-Tages Prognose ebenso gut wie 4-Tages Prognose for 6 Jahren

26. Temperatur- Unsicherheit aus Ensemble von 50 Vorhersagen (anfänglich leicht verschieden) ECMWF

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