... Weather Forecasting. Neil Stringfellow. CSCS Swis

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Alpine Weather Forecasting

• Neil Stringfellow
• CSCS Swiss National Supercomputing Centre

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CSCS Swiss National Supercomputing Centre

• National Supercomputing Centre since 1992
• Provides compute facilities and scientific
  support to Swiss research community
• Federal High Schools, Federal research
  institutes, Universities and University of
  Applied Sciences
• Switzerland is currently planning its national
  strategy in HPC
• CSCS also provides facilities to MeteoSwiss for
  operational weather forecasting

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CSCS User Base

• Scientists drawn from a large number of
  disciplines
• Climate research is a major research field

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Climate Modelling at CSCS

• One of CSCS ALPS projects awarded to model
  hydrological cycle in Alpine Environment
• Various software packages are run at CSCS
• Echam5 Echam5-HAM (Atmosphere Aerosol)
• CCSM CSM with Carbon Cycle
• COSMO climate model (regional and local)
• No non-coupled ocean modelling

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Economic Importance of Climate Modelling

• Tourism
• Important to know long-term effects for planning
  where to locate ski resorts
• Agriculture
• Swiss agriculture is expected to benefit from
  modest temperature increases (up to 2C)
• Electricity generation
• Hydro power requires precipitation
• Nuclear power plants require cooling

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Water and Electricity Generation

• Swiss electricity generation is carbon neutral!
• Approx 60 from hydroelectric power plants
• Most of the rest is Nuclear
• Need to know precipitation levels for electricity
  generation
• Cooling of nuclear power plants relies on water,
  and the temperature of that water
• During the 2003 summer heatwave, electricity
  production from nuclear was reduced by 25

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Future Climate Scenarios

• Current prediction is for higher temperatures and
  lower precipitation
• Glacial melt will increase in near future but
  water available for hydro-generation will reduce
  from present levels by 2050
• Warmer water will reduce cooling capacity for
  nuclear reactors
• There is a need for research, and in particular
  numerical simulation

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MeteoSwiss and CSCS

• MeteoSwiss is the Swiss federal weather office
• MeteoSwiss run operational weather forecast model
  at CSCS
• MeteoSwiss runs the COSMO model from the COSMO
  consortium
• This is a local (not global) model
• CSCS provides compute resources and technical and
  scientific services

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High Resolution Forecasting

• European Windstorms Lothar and Martin caused
  destruction and loss of life in 1999
• Not detected by national weather services
• Demands for improved forecasting
• Additional requirements for accurate forecasting
  from Nuclear Power Plant operators

Destruction in black forest due to Windstorm
Lothar
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European Windstorms - background

• Windstorms occur in Winter, typically December to
  February
• Sometimes called Winter storms or Orkan
• Naming system similar to hurricanes
• Names issued by Free University of Berlin
• Actually all high and low pressures are named
• Historically have caused major loss of life
• Mainly due to dyke breaches in Netherlands
• Occasionally missed by national weather services
• 1987 Storm in United Kingdom
• Lothar in 1990 by Germany (and others inc.
  Switzerland)

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Features of European Windstorms

• Dont dissipate quickly over land
• They sometimes intensify over land
• Often occur in clusters of 2 or more
• Daria Herta (Jan 1990)
• Vivan Wiebke (Feb 1990)
• Désirée, Esther, Fanny, Hetty (Jan 1998)
• Lothar Martin (Dec 1999)
• Wind speeds, insurance losses and fatalities are
  similar to U.S. hurricanes
• No massive loss of life in modern times to
  compare with Hurricanes Jeanne and Katrina

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Swiss Topography

• High mountains and deep valleys lead to extreme
  winds during storms
• 225 km/h on Aetsch Glacier for Kyrill
• 285 km/h at Jungfraujoch for Wiebke

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Insurance Losses

• European Windstorms are the second highest cause
  of insurance losses
• Highest losses are caused by U.S. Hurricanes
• Average annual loss is around 2 Billion
• 5 of top 20 biggest ever insurance losses are due
  to European Windstorms

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Losses of Big Storms
affected Switzerland
Combined Lothar/Martin (25th 27th Dec. 1999)
would be 8th largest loss
Source Swiss Re
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Lothar/Martin December 1999

• Storm Lothar crossed France, Germany and
  Switzerland on 24th 25th December 1999
• Storm Martin followed a similar path on 26th
  27th December
• Many fatalities, billions of dollars of damage
• Not predicted by National Weather Services

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Advances in Prediction

• Study of prediction of Lothar/Martin (Walser et.
  al) looked at 3 aspects
• Moist Singular Vectors
• Different approach to calculate initial
  perturbations for ensemble forecasts
• Increased Resolution
• Ensembles
• Showed great potential for improved forecasts

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Forecast storm Lothar max. wind gusts t(42-66)
(1)
opr SVs, ?x80 km

• Configuration
• opr SVs, 80 km
• opr SVs, 10 km, 80 km topo
• moist SVs, 10 km,80 km topo
• moist SVs, 10 km
• moist SVs, 10 km,10 members

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Forecast storm Lothar max. wind gusts t(42-66)
(2)
opr SVs, ?x10 km, ?x topography 80 km

• Configuration
• opr SVs, 80 km
• opr SVs, 10 km, 80 km topo
• moist SVs, 10 km,80 km topo
• moist SVs, 10 km
• moist SVs, 10 km,10 members

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Forecast storm Lothar max. wind gusts t(42-66)
(3)
moist SVs, ?x10 km, ?x topography 80 km

• Configuration
• opr SVs, 80 km
• opr SVs, 10 km, 80 km topo
• moist SVs, 10 km,80 km topo
• moist SVs, 10 km
• moist SVs, 10 km,10 members

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Forecast storm Lothar max. wind gusts t(42-66)
(4)
moist SVs, ?x10 km

• Configuration
• opr SVs, 80 km
• opr SVs, 10 km, 80 km topo
• moist SVs, 10 km,80 km topo
• moist SVs, 10 km
• moist SVs, 10 km,10 members

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Forecast storm Lothar max. wind gusts t(42-66)
(5)
moist SVs, ?x10 km, 10 members

• Configuration
• opr SVs, 80 km
• opr SVs, 10 km, 80 km topo
• moist SVs, 10 km,80 km topo
• moist SVs, 10 km
• moist SVs, 10 km,10 members

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Going from 80km to 10km
ECMWF EPS (80 km)
COSMO-LEPS (10 km)
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Current Situation of MeteoSwiss

• Forecast runs on a 896 core Cray XT4
• Runs 8 times per day for 30 mins

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Need for High Resolution

• The forecast simulation resolves Switzerland
  using a two-grid refinement
• coarse 6.6km spacing between grid points
• 385 x 325 grid, 60 atmospheric levels over
  Western Europe, 72 second time step with
  numerical leapfrog scheme
• fine simulation uses 2.2km spacing
• 520 x 350 grid, 60 atmospheric levels over
  Alpine Arc, 20 second time step with
  Runge-Kutta numerical scheme
• Many features in Switzerland were not resolved at
  the older 7km resolution
• Few valleys are resolved at this resolution

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Resolution change 6.6km to 2.2km
COSMO-7 (6.6 km)
COSMO-2 (2.2 km)
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Example - Magadino Plain

• Magadino Plain is the lowest part of Switzerland
• Lowest point is on shore of Lago Maggiore
• Plane is surrounded by mountains
• At 6.6km resn it resolves to be a 1km high
  plateau
• At 2.2km resn it has a valley floor at 200m
  height

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Parameterisation v Direct Simulation

• At low resolution many features cannot be
  directly modelled - have to be parameterised
• Higher resolutions allow more physics
• 6.6km -gt 2.2km deep convection is computed
  explicitly
• Higher resolution also allows modelling of valley
  winds

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Full Suite

• 7 components
• Interpolation, assimilation and 24 hour forecast
  on coarse grid
• Interpolation and assimilation on fine grid
• Interpolation and 24 hour forecast on fine grid
• All components have to complete in 20 minutes
• To allow for data post-processing to complete
  within 30 minutes of start
• Suite runs every 3 hours
• Twice per day a 72 hour coarse grid forecast is
  added

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Model Heirarchy
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Full Suite Timeline
Time UTC
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Example of Improvement - Wind

• South of Zurich Lake
• Wind field at 6.6km and 2.2km resolution
• Features only resolved at high resolution

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Other Extreme Events in Switzerland

• Summer Flooding
• Summer floods over central Europe in 2005
• 38th largest insurance loss 1970-2007 (Swiss Re)
• Summer Heatwaves
• European heatwave of 2003 responsible for 35,000
  deaths
• 8th largest number of deaths from natural
  catastrophe 1970-2007
• Others, e.g. hailstorms halted Tour de Suisse in
  2007

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HPC Issues in Climate/Weather

• What is typical high-end Climate HPC work?
• Future Modelling in Climate/Weather
• Higher resolution
• More physics
• Ensembles
• Very complex and large codes
• Not likely to be an early adopter or new
  languages
• No compact kernel for accelerators

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I/O Rate and Storage

• Many codes use proprietary formats
• Grib format in European codes
• No widespread adoption of parallel I/O
• often I/O is done on one or a few processes
• Increasing amounts of data being generated
• reluctance to delete data
• two-thirds of CSCS archive is used for Climate
  and Weather data

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Acknowledgements

• Great many thanks go to Andre Walser and Daniel
  Leuenberger of MeteoSwiss for providing slides
  and answering questions