P

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Operational and Research Activities at ECMWF

Renate Hagedorn European Centre for
Medium-Range Weather Forecasts
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ECMWFs
background and structure research activities
? Integrated Forecast System (IFS) operational
activities ? production, delivery, archiving
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Background

• Convention establishing ECMWF entered in force
  on 1st Nov 1975,
• having been ratified by the following 13
  Member states
• Recognition of importance and potential to
  improve medium-range
• weather forecasts with benefits to the
• ? European economy
• ? Protection and safety of population
• ? Development of meteorology in Europe / post
  university training
• ? Development of European industry in the
  field of data-processing
• Recognition that resources are needed on a
  scale exceeding those
• normally practicable at national level

Denmark Spain
Ireland Netherlands
Switzerland Sweden
Belgium Germany
France Yugoslavia
Austria Finland
United Kingdom
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Today
ECMWF is an independent international
organization, supported by 18 member states
13 co-operating states
Czech Republic
Croatia
Co-operating agreements
Estonia
Hungary
Latvia
Iceland
Lithuania
Montenegro
Romania
Morocco
Slovakia
Serbia
Slovenia
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New Convention
Amendments to the ECMWF Convention were
unanimously adopted by Council at its 62nd
extraordinary session on 22 April 2005
Finalization of the ratification process is
expected by the end of 2009 The adopted
amendments concern mainly ? allowing new
Member States to join ? enlarging ECMWFs
mission to environmental monitoring ?
re-defining some decision making processes
(voting rights) ? widening the possibilities
for externally funded projects (e.g. EU) ?
extending official languages to all official
languages in Member States (on a
request-and-pay basis)
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Objectives

• Operational forecasting up to 15 days ahead
  (including waves)
• R D activities in forecast modelling
• Data archiving and related services
• Operational forecasts for the coming month and
  season
• Advanced NWP training
• Provision of supercomputer resources
• Assistance to WMO programmes
• Management of Regional Meteorological Data
  Communications Network (RMDCN)

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ECMWF Budget 2009
Spain 7.95
Main Revenue 2009 Member Statescontributions 35
,593,300 Co-operating Statescontributions
847,400 Other Revenue 1,169,500 Total
37,610,200
Germany 20.20
France 15.46
Luxembourg 0.23
Denmark 1.87
Greece 1.74
Belgium 2.71
Ireland 1.23
Main Expenditure 2009 Staff 14,450,100 Leaving
Allowances Pensions 2,965,200 ComputerExpendit
ure 15,690,600 Buildings 3,634,300 Supplies 870
,000 Total 37,610,200
United Kingdom 16.43
Italy 12.66
Turkey 2.38
Netherlands 4.61
Sweden 2.66
Norway 2.13
Finland 1.42
Switzerland 2.89
Austria 2.16
Portugal 1.29
GNI Scale 20092011
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Organizational structure
Scientific Advisory Committee 12 Members
Policy Advisory Committee 7-18 Members
COUNCIL 18 Member States
Finance Committee 7 Members
Technical Advisory Committee 18 Members
DIRECTOR Dominique Marbouty (France) (230)
Advisory Committee of Co-operating States 12
Members
Advisory Committee on Data Policy 8-31 Members
Operations Walter Zwieflhofer (Austria) (111)
Research Martin Miller (UK) (90)
Administration Ute Dahremöller (Germany) (25)
Meteorological Division Erik Andersson (Sweden)
(42)
Computer Division Isabella Weger(Austria) (65)
Data Division Jean-Noel Thepaut (France) (37)
Model Division Martin Miller (UK) (24)
Probabilistic Forecasting and Diagnostics
Division Tim Palmer (UK) (19)
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Principal Goal
Maintain the current, rapid rate of improvement
of its global, medium-range weather
forecasting products, with particular effort on
early warnings of severe weather events.
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Principal Goal
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Principal Goal
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Complimentary Goals
In addition to the principal goal of
maintaining the current, rapid rate of
improvements, the complimentary goals are
?To improve the quality and scope of monthly and
seasonal-to-interannual forecasts
?To enhance support to Member States national
forecasting activities by providing suitable
boundary conditions for limited-area models
?To deliver real-time analysis and forecasts of
atmospheric composition
?To carry out climate monitoring through regular
re-analyses of the Earth-system
?To contribute towards the optimization of the
Global Observing System
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Numerical Weather Prediction
The behaviour of the atmosphere is governed by
a set of physical laws
Equations cannot be solved analytically,
numerical methods are needed Additionally,
knowledge of initial conditions of system
necessary Incomplete picture from observations
can be completed by data assimilation
Interactions between atmosphere and land/ocean
important
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Strategy
Development of a suitably comprehensive
Earth-system assimilation capability to make
best use of all available data
Development of a suitably comprehensive and
integrated high-resolution Earth-system
modelling facility
Development of the methodology of ensemble
forecasting for medium-range and seasonal
forecasting
Operational delivery of an enhanced range of
meteorological and associated products
Maintenance and extension of the Centres
scientific and technical collaborations
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Research Department
Data Division Jean-Noel Thepaut (France) (36)
Model Division Martin Miller (UK) (26)
Probabilistic Forecasting Diagnostics
Division Tim Palmer (UK) (18)
Satellite Data Peter Bauer (Germany) (14)
Physical Aspects Anton Beljaars (Netherlands) (12)
Seasonal Forecast Franco Molteni (Italy) (9)
Data Assimilation Lars Isaksen (Denmark) (15)
Numerical Aspects Agathe Untch (Germany) (7)
Predictability Diagnostics Tim Palmer (UK) (7)
Re-Analysis Project Dick Dee (Netherlands) (3)
Ocean Waves Peter Janssen (Netherlands) (3)
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ECMWFs operational analysis and forecasting
system
The comprehensive earth-system model developed at
ECMWF forms the basis for all the data
assimilation and forecasting activities. All the
main applications required are available through
one integrated computer software system (a set of
computer programs written in Fortran) called the
Integrated Forecast System or IFS
Numerical scheme ? TL799L91 (799 waves
around a great circle on the globe, 91 levels
0-80 km) ? semi-Lagrangian formulation ?
1,630,000,000,000,000 computations required for
each 10-day forecast Time step ? 12 minutes
Prognostic variables ? wind, temperature,
humidity, cloud fraction and water/ice content,
pressure at surface grid-points, ozone
Grid ? Gaussian grid for physical processes,
25 km, 76,757,590 grid points
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Deterministic model grid (T799)
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EPS model grid (T399)
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The wave model

• Coupled ocean wave model (WAM cycle4)
• ? 2 versions global and regional (European
  Shelf Mediterranean)
• ? numerical scheme irregular lat/lon grid,
  40 km spacing
• spectrum with 30 frequencies and 24
  directions
• ? coupling wind forcing of waves every 15
  minutes, two way
• interaction of winds and waves, sea state
  dep. drag coefficient
• ? extreme sea state forecasts freak waves
• ? wave model forecast results can be used as
  a tool to diagnose
• problems in the atmospheric model

Numerical Methods and Adiabatic Formulation of
Models 30 March - 3 April 2009
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Physical aspects, included in IFS
Orography (terrain height and sub-grid-scale
characteristics) Four surface and sub-surface
levels (allowing for vegetation cover,
gravitational drainage, capillarity exchange,
surface / sub-surface runoff) Stratiform and
convective precipitation Carbon dioxide (345
ppmv fixed), aerosol, ozone Solar angle
Diffusion Ground sea roughness Ground and
sea-surface temperature Ground humidity
Snow-fall, snow-cover and snow melt Radiation
(incoming short-wave and out-going long-wave)
Friction (at surface and in free atmosphere)
Sub-grid-scale orographic drag Gravity waves
and blocking effects Evaporation, sensible and
latent heat flux
Parameterization of Diabatic Processes 11 21
May 2009
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Starting a forecast The initial conditions
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Data Assimilation
Observations measure the current state, but
provide an incomplete picture ? Observations
made at irregularly spaced points, often with
large gaps ? Observations made at various
times, not all at analysis time ?
Observations have errors ? Many observations
not directly of model variables
see next eight days

• The forecast model can be used to process the
  observations and produce a
• more complete picture (data assimilation)
• ? start with previous analysis
• ? use model to make short-range forecast for
  current analysis time
• ? correct this background state using the
  new observations

The forecast model is very sensitive to small
differences in initial conditions ? accurate
analysis crucial for accurate forecast ? EPS
used to represent the remaining analysis
uncertainty
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What is an ensemble forecast?
Temperature
Forecast time
Initial condition
Forecast
Complete description of weather prediction in
terms of a Probability Density Function (PDF)
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Flow dependence of forecast errors
26th June 1995
26th June 1994
If the forecasts are coherent (small spread) the
atmosphere is in a more predictable state than if
the forecasts diverge (large spread)
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Why Probabilities?
Open air restaurant scenario ? open
additional tables 20 extra cost, 100 extra
income (if Tgt24ºC) ? weather forecast 30
probability for Tgt24ºC ? what would you do?
Employing extra waiter (spending 20) is
beneficial when probability for Tgt24 ºC is
greater 20 The higher/lower the cost loss
ratio, the higher/lower probabilities are
needed in order to benefit from action on forecast
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ECMWFs Ensemble Prediction Systems
Account for initial uncertainties by running
ensemble of forecasts from slightly different
initial conditions ? singular vector approach
to sample perturbations Model uncertainties are
represented by stochastic physics
Medium-range VarEPS (15-day lead) runs twice
daily (00 and 12 UTC) ? day 0-10 TL399L62
(0.45, 50km), 501 members ? day 9-15
TL255L62 (0.7, 80km), 501 members Extended
time-range EPS systems monthly and seasonal
forecasts ? coupled atmosphere-ocean model
(IFS HOPE) ? monthly forecast (4 weeks lead)
runs once a week ? seasonal forecast (6 months
lead) runs once a month
Predictability, Diagnostics and Extended Range
Forecasting 16 - 25 March 2009
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Operations Department
Computer Division Isabella Weger (Austria) (68)
Meteorological Division Erik Andersson (Sweden)
(37)
Computer Operations Sylvia Baylis (UK) (32)
Meteorological Applications Alfred
Hofstadler (Austria) (9)
Network and Computer Security Rémy
Giraud (France) (12)
Meteorological Operations David Richardson (UK)
(13)
Servers Desktops Richard Fisker (Denmark) (9)
Data Services Baudouin Raoult (France) (8)
Systems Software Neil Storer (UK) (8)
Graphics Stefan Siemen (Germany) (6)
User Support Umberto Modigliani (Italy) (6)
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Current Computer Configuration
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RMDCN Network
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User support for special projects
http//www.ecmwf.int/about/computer_access_registr
ation/Special_Projects.html
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ECMWF model suites
Deterministic high-resolution global
atmospheric model ? TL799 91 levels range10
days Medium-range ensemble prediction system
? TL399 / TL255 62 levels range15 days ?
control 50 perturbed members Monthly forecast
system ? TL255 62 level (atm.), 1.4 º x
0.3-1.4º, 29 vertical levels (ocean) ?
51-member ensemble range32 days Seasonal
forecast system ? TL159 62 level (atm.), 1.4 º
x 0.3-1.4º, 29 vertical levels (ocean) ?
41-member ensemble range6 months
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Main operational suites
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Data Dissemination
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The ECMWF archive

• The largest NWP archive worldwide
• Built since ECMWF operations started in 1979
• Holds more than 5 petabytes today
• 6 terabytes added daily
• Contains
• All data used
• All analyses
• All forecasts
• Reanalyses
• Fully accessible on-line to Member States users

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MARS
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ECMWF Data Server
A new service that gives researchers immediate
and free access to datasets from ECMWF.
DEMETER ERA-40 ERA-15 ENACT ENSEMBLES /
GEMS - Monthly and daily data - Select area -
GRIB or NetCDF - Plotting facility
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Meteorological Operations
Daily report (data and forecast monitoring,
unusual events,) Forecast verification
Development of new products (EFI, tropical
cyclones,) Data and satellite monitoring
User guides / meetings
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Met Ops daily report
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Monitoring of model performance
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Product Development
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Forecast Products 1979
1 forecast (200 km resolution) issued 5 days a
week
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Forecast Products 2009
wide range of forecast products from
deterministic high resolution forecast to
probabilistic EPS products
www.ecmwf.int/products/forecasts
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Products for end users
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More Information