1. Operational and Research Activities
at ECMWF
Renate Hagedorn
European Centre for Medium-Range Weather Forecasts

2. ECMWF’s… …background and structure …research activities
 Integrated Forecast System (IFS)
…operational activities
 production, delivery, archiving

3. 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
Portugal (76), Turkey (76), Greece (76), Italy (77), Norway (89) and Luxembourg (2002) are the 6 new members adding up to 18 (minus Yugoslavia)

4. Today… 13 co-operating states
…ECMWF is an independent international organization, supported by 18 member states
13 co-operating states
Croatia
Czech
Republic
Co-operating agreements:
Estonia
Hungary
Iceland
Latvia
Lithuania
Montenegro
Morocco
Romania
Serbia
Slovakia
Slovenia

5. 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 ECMWF’s 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)

6. 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)

7. ECMWF Budget 2009 GNI Scale 2009–2011 Main Revenue 2009
Spain 7.95%
Main Revenue 2009
Member States’ contributions £35,593,300
Co-operating States’ contributions £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
Computer Expenditure £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%
Austria 2.16%
Switzerland 2.89%
Portugal
1.29%
GNI Scale 2009–2011

8. Organizational structure
Policy Advisory
Committee
7-18 Members
Scientific Advisory
Committee
12 Members
COUNCIL
18 Member States
Technical Advisory
Committee
18 Members
Finance
Committee
7 Members
DIRECTOR
Dominique Marbouty
(France) (230)
Advisory Committee on Data Policy
8-31 Members
Advisory Committee of Co-operating States
12 Members
Operations
Walter Zwieflhofer
(Austria) (111)
Administration
Ute Dahremöller
(Germany) (25)
Research
Martin Miller
(UK) (90)
Computer Division
Isabella Weger (Austria) (65)
Meteorological Division
Erik Andersson
(Sweden) (42)
Model Division
Martin Miller
(UK) (24)
Data Division
Jean-Noel Thepaut
(France) (37)
Probabilistic Forecasting
and Diagnostics Division
Tim Palmer
(UK) (19)

9. 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.

10. Principal Goal

11. Principal Goal

12. 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

13. 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

14. 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 Centre’s scientific and
technical collaborations

15. Research Department Model Division Probabilistic Forecasting
Martin Miller
(UK) (26)
Probabilistic Forecasting
& Diagnostics Division
Tim Palmer
(UK) (18)
Data Division
Jean-Noel Thepaut
(France) (36)
Physical Aspects
Anton Beljaars
(Netherlands) (12)
Satellite Data
Peter Bauer
(Germany) (14)
Seasonal Forecast
Franco Molteni
(Italy) (9)
Numerical Aspects
Agathe Untch
(Germany) (7)
Data Assimilation
Lars Isaksen
(Denmark) (15)
Predictability & Diagnostics
Tim Palmer
(UK) (7)
Ocean Waves
Peter Janssen
(Netherlands) (3)
Re-Analysis Project
Dick Dee
(Netherlands) (3)

16. ECMWF’s 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

17. Deterministic model grid (T799)

18. EPS model grid (T399)

19. Numerical Methods and Adiabatic Formulation of Models:
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

20. 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

21. Starting a forecast: The initial conditions

22. see next eight days 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

23. What is an ensemble forecast?
Temperature
Forecast time
Initial condition
Forecast
Complete description of weather prediction in terms of a
Probability Density Function (PDF)

24. 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)

25. Why Probabilities? • Open air restaurant scenario:
 open additional tables: £20 extra cost, £100 extra income (if T>24ºC)
 weather forecast: 30% probability for T>24ºC
 what would you do?
• Test the system for 100 days:
 30 x T>24ºC -> 30 x (100 – 20) =
 70 x T<24ºC -> 70 x ( 0 – 20) = -1400
+1000
• Employing extra waiter (spending £20) is beneficial
when probability for T>24 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

26. ECMWF’s 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), 50+1 members
 day 9-15: TL255L62 (0.7°, ~80km), 50+1 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
March 2009

27. 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)

28. Current Computer Configuration

29. RMDCN Network

30. User support for special projects

31. ECMWF model suites
• Deterministic high-resolution global atmospheric model
 TL levels; range=10 days
• Medium-range ensemble prediction system
 TL399 / TL levels; range=15 days
 control + 50 perturbed members
• Monthly forecast system
 TL level (atm.), 1.4 º x º, 29 vertical levels (ocean)
 51-member ensemble; range=32 days
• Seasonal forecast system
 TL level (atm.), 1.4 º x º, 29 vertical levels (ocean)
 41-member ensemble; range=6 months

32. Main operational suites

33. Data Dissemination

34. 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

35. MARS

36. ECMWF Data Server • DEMETER • ERA-40 • ERA-15 • ENACT
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

37. 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

38. Met Ops daily report

39. Monitoring of model performance

40. Product Development

41. Forecast Products: 1979
1 forecast (200 km resolution) issued 5 days a week

42. Forecast Products: 2009 www.ecmwf.int/products/forecasts
wide range of forecast products from deterministic high resolution forecast to probabilistic EPS products

43. Products for end users

44. More Information…