The European Centre for Medium-Range Weather Forecasts. European co-operation at its best

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1 The European Centre for Medium-Range Weather Forecasts European co-operation at its best

2 ECMWF a European success story The European Centre for Medium-Range Weather Forecasts (ECMWF) was established in 197, in recognition of the need to pool the scientific and technical resources of Europe s meteorological services and institutions for the production of medium-range weather forecasts and of the economic and social benefits expected from it. ECMWF leads the world in global medium-range Numerical Weather Prediction (NWP), the advanced computer observation-analysis modelling technique used to predict the weather. Our operational activities and wide-ranging programmes of research and development have played a pioneering role in the remarkable advancement of data assimilation and weather forecast systems. In three decades ECMWF has dramatically improved the accuracy and reliability of weather forecasting, working in collaboration with Member and Co-operating States, the European Union and partners such as the World Meteorological Organization (WMO), the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) and the European Space Agency (ESA).

3 A principal player in global weather prediction ECMWF s original goal, as defined by our Convention, was to enhance Europe s medium-range forecasting capabilities by using numerical weather prediction methods to produce forecasts twice daily up to ten days ahead. Since then, our tools, models and supercomputers have evolved to such an extent that we have been able to extend our forecast range and develop techniques which allow us to produce seasonal forecasts up to one year ahead. Our duties encompass: Preparing medium-range forecasts up to 1 days ahead, as well as monthly and seasonal forecasts, for distribution to the National Meteorological Services of our Member and Co-operating States to thereby complement their national forecasting and climatological activities and to weather service providers. Developing numerical methods for medium-range weather forecasting and conducting research to improve the quality and accuracy of our forecasts. Collecting observations obtained globally from land, sea and space, archiving the output and data generated from numerical weather prediction models over time and making the information available to Member and Co-operating States. Making % of our computing facilities available to Member States for their own needs and providing advanced, specialised training to the scientific and technical staff of Member and Co-operating States. Participating in relevant weather, environmental and climate-related programmes led by the European Commission and WMO. Who benefits from our weather forecasts and products? Directly National ydro-meteorological Services Meteorological service providers Scientists monitoring the environment and climate change Indirectly Military and civil defence authorities ocal authorities and emergency services The general public National health services Energy providers, and the offshore oil and gas industry Shipping, commercial fishing and coastal protection agencies Weather-sensitive manufacturing All forms of transport EU, national and regional policy makers

4 Monitoring and predicting the weather The weather is determined to a considerable degree by the initial state of the atmosphere, the behaviour of which is governed by physical laws expressible as mathematical equations. These equations represent how atmospheric conditions such as temperature, humidity, wind speed and direction, and air pressure change from their current states. Solving them provides meteorologists with a prediction of the atmosphere s future state which they can interpret in terms of weather rain, temperature, sunshine and wind, for example. Data are collected round the clock by a variety of Earth observing systems, including automatic and manned stations, aircraft, ships, weather balloons and buoys. In recent years the accuracy of forecasts has been greatly enhanced by data from geostationary and polar-orbiting satellites. The data are analysed and assimilated into ECMWF s advanced NWP models, which produce detailed forecasts up to 1 days ahead and statistical information about monthly and seasonal forecasts. Our current NWP model has evolved from an atmospheric model to an Earthsystem model which takes into account the complex interactions of the planet s other four spheres: living organisms, land, ocean and ice. ECMWF s medium-range forecasts utilise a combination of atmospheric, land and ocean observations, including sea surface temperature, soil moisture and snow cover. Monthly and seasonal forecasts also take into account longer-term influences on the atmosphere, such as the circulation of ocean currents. Climate monitoring makes use of observations of changing sea-ice and vegetation cover. Wave forecasting The state of the sea currents, tides, wave heights, swells and storm surges is an important component of the marine weather forecast, and critical to shipping, fisheries, offshore operations and coastal protection. ECMWF s ocean wave forecasting model provides valuable probabilistic information on sea states to 1 days ahead, and now includes invaluable wave height data from satellites. Geo-stationary satellites Polar-orbiting satellites GPS satellites Atmospheric motion vector Radiances Ozone SCATT Radiances Profiler/ RADAR wind AIRCRAFT Dropsondes TEMP SYNOP Ship Buoys Drifting Moored PIOT SYNOP and METAR Each day more than million observational data elements are collected round the clock by a variety of Earth observing systems, including satellites, automatic and manned stations, aircraft, ships, weather balloons and buoys.

5 Producing a medium-range weather forecast A medium-range weather forecast predicts the weather up to 1 days ahead and requires four key ingredients: a state-of-the-art data assimilation and analysis system, sophisticated weather prediction models, a constantly updated database of global weather observations and ultra-powerful computers. The starting point for all medium-range forecasts is accurate information about the current state of the weather worldwide, known as initial conditions. Meteorological observations gathered from all around the world e.g. air pressure, temperature, and wind speed and direction are transmitted to ECMWF via specialised telecommunication networks. ECMWF analyses these observations continuously and feeds them into a model representing a -D virtual image of the atmosphere. This analysis is corrected regularly as new observations come in these are used to pull each previous forecast closer to the observations. Every 1 hours ECMWF processes about million observations which are used to correct the million numbers that define the model s virtual atmosphere. Global forecasts, using analysis as a starting point, are distributed twice daily to the National Meteorological Services of our Member and Co-operating States. ECMWF s forecasting system The ECMWF weather forecasting system consists of an atmospheric model coupled with an ocean wave model. The model formulation can be summarised by six basic physical equations, the way the numerical computations are carried out and the resolution in time and space. -day forecast model facts EPS Meteogram Reading 1. N 1. W Deterministic Forecasts and EPS Distribution. - % deg Oper - % - % T179 Number of grid points,1,7 Distance between grid points 1 km Vertical levels 91 Time step s Number of time steps for a ten-day forecast 1 Floating point operations needed. 1 - % EMem T m Wind Speed (m/s) Forecast Day 7 9 Ensemble members of TOTA PRECIPITATION - Accum. rate mm/1h mm m Temperature Reduced to T11 Orography (deg C) 1 9M (T11) 9M (T) MON T CTR TUE WED 9 1 T11 OPS TU 1 FRI SAT SUN Significant wave height. Forecast t+ VT: Sunday 7 November DECEMBER m 1 Day Forecast 7 W W GEOPOTENTIA hpa - Probability for. dam intervals, Range: 7dam 9 W E E E >.m/s 7 N 7 dam W E N ECMWF Seasonal Forecast Mean precipitation anomaly Shaded areas significant at % level Solid contour at 1% level N Forecast Day Ensemble size=, climate size = < No Signal -.. > mm m Wind Speed greater than m/s 7 N N W W%, %, 9% Contours at %, E 7 N E E W 9 E 9 N hpa Temperature Anomaly less than - K hpa Temperature Anomaly less than - K W hpa Temperature Anomaly greater than K N. 9 E 9 hpa Temperature Anomaly greater than K W N E 1 E 9 E E 1 N hr Total Precipitation greater than mm E W W 9 W 1 W W 7 S hr Total Precipitation greater than mm hr Total Precipitation greater than mm N 9 S hr Total Precipitation greater than 1 mm S 1 S S W E 1 N E 99 W E W Tuesday October 7 1UTC ECMWF Forecast t+1 VT: Sunday October 7 1UTC ECMWF FORECAST PROBABIITIES Surface: Mean sea level pressure / 1hr Accumulated precipitation (VT-h/VT+h) Friday November UTC ECMWF Forecast1 VT:Wednesday November UTC N N N N m Wind Speed greater than 1 m/s N max 7% median % min SUN 7 FRI SAT NOVEMBER TEMPERATURE hpa - Probability for 1. deg intervals, Range: deg Total Precipitation (mm/hr) ECMWF ENSEMBE FORECASTS FOR: ECMWF READING AT: 1. ONG: Total Cloud Cover (okta) 7 1 Resolution 9

6 Improving weather forecasting techniques ECMWF has played and continues to play a pivotal role in the remarkable advancement of NWP systems. From our earliest days, we have pursued a wideranging programme of research and development directed at improving the scope, accuracy and range of forecast products for the medium range and beyond. The fruits of this research are: The most comprehensive Earth-system and assimilation models in use by NWP centres around the world. Progressively more accurate medium-range forecasts. A constantly expanding range of operational forecasting products for meteorologists and end users. As well as engaging in research and development of our own model, ECMWF collaborates closely with National Meteorological Services, scientists and researchers around the world towards the common goal of improving the accuracy of weather forecasting and severe weather prediction. Observing Earth s weather from space Improvements in the quality and quantity of satellite data over the last decade, and in the ability to process and assimilate information into NWP models, have made spacebased data the most important source of observations for NWP. Satellites deliver regular, highly detailed measurements and images of many of the key variables which influence the weather, including ozone, carbon dioxide, aerosols and other atmospheric constituents, as well as temperature, humidity, cloud conditions, wind speed and direction, vegetation cover, ocean circulation, wave height and sea ice. ECMWF is one of the most advanced users of satellite data for weather prediction and climate monitoring. We collaborate closely with satellite data providers such as the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT), the European Space Agency (ESA), the National Aeronautical Space Administration (NASA), and the National Oceanic and Atmospheric Administration (NOAA). We continually strive to enhance our use of satellite observations to improve the accuracy of our NWP. Recent enhancements in our techniques have led to improvements in our humidity forecasts in the tropics and our analysis and tracking of tropical cyclones. Satellite image courtesy of EUMETSAT Accuracy (%) Anomaly correlation percentage of hpa height forecasts 9 7 Observing System Experiments We participate in Observing System Experiments (OSEs). These OSEs aid in particular the EUMETNET Composite Observing System (EUCOS) programme, which aims to deliver terrestrially based operational observations for the improvement of regional NWP in Europe. To ensure the EUCOS programme evolves and meets customer needs for regional NWP, ECMWF was one of the NWP centres commissioned to carry out OSEs to evaluate and compare the contribution of the components of the in-situ observing system and the satellite-based observing system to numerical weather forecasts. Northern hemisphere Southern hemisphere Day Day Year Day 7 Day Forecasts improved steadily from 19 as a result of improvements in the global observing system, more powerful computers, and advances in the science of the ECMWF s data assimilation system and forecast model. Seven-day forecasts in the northern hemisphere became more accurate than the five-day forecasts of 19, and five-day forecast accuracy reached that of the three-day forecasts made years earlier. In the southern hemisphere, the improvement was even more marked. In the early 19s, because of the lack of observations, the three- and five-day predictions for the southern hemisphere were not much better than those of the northern hemi sphere for five and seven days respectively. Two decades later, forecasts for both hemispheres were of similar accuracy a gain of about four days in the accuracy of southern hemisphere predictions, mainly thanks to the use of satellite data. The shaded area shows the differences in forecast accuracy between the hemispheres.

7 Predicting the uncertainty of forecasts Despite the increasing accuracy of weather forecasts, there is still an element of uncertainty in all predictions. The two main reasons for this are uncertainties in the initial state of the atmosphere and model errors. Advances in utilizing all available observations of the earth system have enabled us to describe the state of the atmosphere better than ever before. owever, the exact state of the atmosphere is never known precisely, and thus there will always be a remaining uncertainty in the initial conditions that are needed to start a forecast. In addition, numerical models cannot fully replicate the laws of physics that govern the behaviour of the atmosphere, resulting in model errors introduced e.g. through the parametrization of sub-gridscale processes. The atmosphere's inherent chaotic nature amplifies these uncertainties, with the result that initially small errors can be magnified over time and profoundly distort the outcome of the forecast. In order to represent this uncertainty in the forecast system and predict its impact on the resulting forecasts, meteoro logists increasingly use forecasting methods which express the weather s likely behaviour as a probability. They use ECMWF s pioneering Ensemble Prediction System (EPS), which provides the tools for estimating the degree of uncertainty and its likely impact on a forecast. Unlike the standard deterministic forecasting method, which runs a single model to produce one possible solution for the weather ahead, EPS runs 1 simulations with a coarser resolution, known as an ensemble, in which the forecast s initial starting conditions vary subtly to provide a range of possible future scenarios. The proportion of ensemble members forecasting a specific weather event indicates the probability of it occurring. End users such as civil protection agencies, health authorities, energy companies, local authorities, transport managers and insurance companies, for example combine this probability with their own information about their sensitivity to certain weather events to manage risk. ow high the probability must be before action is taken depends very much on the potential consequences of the event for the individual user. In the case of severe weather, users who would suffer high losses will take preventive action at much lower probabilities than others who would be less affected by the same weather event. -day forecast 1 Gustav anna 1 Ike Seasonal forecasting As we attempt to predict further into the future, the initial conditions of the atmosphere itself lose impor - tance, while the lower boundary conditions such as sea surface temperature (SST) or soil moisture and snow cover start to exert a significant influence on weather patterns. Ensemble forecasts are used to separate the part of the variability in seasonal weather which can be predicted, from the part which cannot. The future evolution of SST is an important part of the forecast problem, and models of both the atmosphere and ocean are required, together with analyses of the initial state of the ocean. ECMWF s Council approved a programme of involving coupled modelling to address seasonal forecasting in December 199. Experimental seasonal forecasts were issued from December 1997 onwards, and the system became fully operational in. ECMWF also produces EUROSIP multi-model seasonal forecast products, based on input from four forecasting systems (ECMWF, the United Kingdom s Met Office, Météo-France and the US National Centers for Environmental Prediction (NCEP)). Additionally, the European Union is supporting research at ECMWF and a number of other institutes around Europe to establish the predictability of seasonal climate fluctuations using ensemble forecast techniques. -day EPS forecast 7 During an intensive period of the Atlantic hurricane season in, three hurricanes (Gustav, anna and Ike) were active at the same time. On average in this period, the genesis of tropical cyclones was predicted by the model to 7 days before the storms were reported as tropical cyclones. The top panel shows the -day deterministic forecast of mean sea-level pressure verifying at 1 UTC on 1 August. Gustav, anna and Ike can each be clearly identified, even though the forecast was issued before anna and Ike had been officially observed. The bottom panel shows the day- EPS probability forecast for tropical cyclones to be in the region in the -hour period between 1 UTC on 1 August and 1 UTC on 1 September. 7

8 Delivering consistent and reliable services As the world s leading NWP centre, our reputation rests on our ability to deliver a consistent and reliable service hours a day, 7 days a week. At the core of our operational and research activities lies one of the largest computing centres in Europe. Our extremely powerful supercomputers, supported by the rest of our computing infrastructure, enable ECMWF to: Collect and check approximately million observations daily and actively assimilate some million a day into the NWP models. Produce global forecasts. Perform research experiments to advance NWP techniques and products. Provide Member States with invaluable resources for their own research into NWP. Our computer and ancillary facilities, such as data handling and networking, are regularly upgraded to accommodate the greater computational power demanded by the assimilation of even more observational data and the ongoing evolution of our forecasting models. igh Performance Computing Facility ECMWF s PCF currently comprises two identical IBM supercomputer 1 clusters. Each one is based on 7 IBM pseries p-7 compute servers interconnected by a lowlatency high-speed network. Total number of processors ~17, Peak performance Sustained performance TFlops ~ TFlops igh performance computing infrastructure ECMWF has operated a igh Performance Computing Facility (PCF) for weather forecasting, since the installation of its first CRAY-1 supercomputer in 197. Over time, various supercomputer architectures have been used including vector shared-memory systems, vector distributed memory systems and clusters of scalar shared-memory processing systems. From the very beginning ECMWF has ensured that its codes are portable and has invested considerable resources in ensuring that they remain for most prevailing high performance computing architectures. Data handling The massive amount of data required for and generated by weather forecasting is archived in our Data andling System. Since 197, ECMWF has built up a unique archive of meteorological data for use by researchers as well as for educational and commercial purposes. As of July 1, the archive holds 1 petabytes of data. More than researchers from over different organisations access the meteorological archive for their own work. RMDCN ECMWF s forecast products are disseminated over the Regional Meteorological Data Communications Network (RMDCN). Its primary purpose is to provide a network infrastructure for both the connections between ECMWF and its Member and Co-Operating States and most of the Global Telecommunications System (GTS) connections for WMO Regional Association VI. Operational since March, the network has expanded to encompass countries in many parts of the world with connections to Japan, China, India and South Korea in the Far East as well as the USA and Australia and South Africa and connects 9 sites in countries The network infrastructure is provided by Orange Business Services (OBS), with ECMWF managing the project and monitoring the network on behalf of the sites connected under an agreement concluded with the WMO. Data andling System ECMWF s Data andling System is based on IBM s igh Performance Storage System. About 1 petabytes of data are held on about, tapes, which are stored in Sun S automated tape libraries. RMDCN The RMDCN connects ECMWF, EUMETSAT and the National Meteo - rological Services of many countries in WMO regions I, II, IV, V and VI, providing connectivity based on IPVPN MPS network technology.

9 Analysing climate change Until recently, scientists monitored changes in the Earth s climate by analysing temperature, wind and rainfall observations. They have been particularly interested in looking for evidence of warming and increased frequency of severe weather events. ECMWF was one of the pioneers of an approach known as reanalysis, which involves reprocessing weather observations collected over decades using a modern NWP system to recreate past atmospheric, sea- and land-surface conditions over specific time periods to obtain a clearer picture of how the climate has changed. To date, and with support from Europe s National Meteorological Services and the European Commission, ECMWF has conducted several reanalyses of the global atmosphere. Our work has yielded products of unprecedented scope and quality. Applications of reanalysis The success of reanalysis as a tool for global climate monitoring can be measured by the number, variety and quality of applications of its products. There are few spheres of life that are not touched by weather and climate. Reanalyses have produced applications for sectors such as agriculture, water, air quality, health, ecosystems and biodiversity. Direct applications in the fields of weather and climate include studies of predictability from days to seasons ahead, estimation of the long-range transport of pollutants, investigation of recent climate change and assessment of the capability of climate-prediction models to simulate such change. As reanalysis systems are further refined, their products will increasingly form the backbone of the quantitative information essential for climate related policy and decision making in a changing global environment. Reanalysis data are used extensively by the worldwide scientific community: about, registered users from more than 1 countries have accessed the reanalysis archive. 1. m/s The capability of reanalysis is illustrated well by one of Europe s severest storms of the th century, which occurred on 1 January/1 February 19 and caused the greatest surge on record for the North Sea area as a whole. Flood levels reached.7 m and.97 m in height at Southend and King s ynn in England and. m in the Netherlands. Almost, hectares of Eastern England were flooded and 7 people died. The Netherlands fared worse still, as dykes burst and 1, people drowned. The figure shows the reanalysed near-surface wind (maximum speed about ms -1 ) and ocean-wave height (metres) for UTC, 1 February 19. The strong winds from the north have a long fetch (the distance over which wind blows without changing direction) to develop waves with heights of over nine metres over a large area. The combination of both high tide and waves had a devastating effect. In order to better understand the effects of the storm, the global reanalysed fields have also been used as boundary conditions for high-resolution, limited-area, atmospheric models, which in turn drive detailed storm surge models

10 Monitoring the environment ECMWF contributes actively to the development of the European GMES (Global Monitoring for Environment and Security) initiative, which aims to make environmental information more readily available to scientists, policy makers and industry, and to create a shared European system for exchanging a range of information. As a contribution to GMES, the EU-funded project MACC (Monitoring Atmospheric Composition and Climate) has been established to continue development and pilot operation of an atmospheric monitoring service which is generating valuable new global analysis and forecasts of atmospheric composition, and producing more detailed short- and medium-range forecasts indicating air quality and pollution patterns across Europe. We are co-ordinating the project and are responsible for developing and operating the global system. MACC continues work originally undertaken in a project called GEMS, which was also coordinated by ECMWF. The project is developing state-of-the-art variational estimates of sources and sinks, and estimates of inter-continental transports of many trace gases and aerosols. These estimates, based on both retrospective and near-real-time analyses, will support the science underlying policy makers key information requirements relevant to the Kyoto and Montreal protocols and the UN Convention on ong-range Transboundary Air Pollution (CRTAP). Global warming Monitoring the state of the environment and addressing the challenges of climate change are growing concerns for governments worldwide and all the more pressing as global warming increases the risk and frequency of dangerous weather events. ECMWF, as the leading provider of NWP, is ideally positioned to play an ongoing and increasingly significant role in the timely protection of the Earth and its peoples. Installation New information requirements Policy Kyoto Protocol Montreal Protocol CRTAP Environment agencies Air quality users ealth agencies Science Responds to MACC products Information on atmospheric composition Greenhouse gases Reactive gases Aerosols Regional air quality Monitoring, assessment and prediction Current status Sources, sinks and transport Impact of global change Improved Earth observations Instruments Satellite Ground based Airborne Atmosphere Composition Dynamics and surface Biomass burning Vegetation Ocean Data flow MACC system Global pre-operational assimilation and forecast capability for greenhouse gases, reactive gases and aerosols. Improved forecasts for regional air quality from an ensemble of European air quality models. Delivers Schematic illustrating the objectives and products of the MACC project.

11 ooking to the future In June 11, the ECMWF Member States unanimously adopted the ECMWF s Strategy for the period 11 to. The vision of this Strategy is for ECMWF to be the acknowledged world leader in global, medium-range numerical weather prediction. This is to provide the best possible forecast products to our members, particularly to national weather services, for the benefit of society. The aims are that by reliable early warnings for severe weather will be routinely received and acted upon by European citizens, and many national weather services will deliver tailored medium-range forecasts using direct ECMWF model output. we will deliver operationally global analyses and forecasts of atmospheric composition. we will continue to support climate monitoring with state-of-the-art reanalyses of the Earth-system. Severe weather Over the last two decades the majority of the victims of natural disasters lost their lives as a result of windstorms, tropical cyclones, floods, cold and heat waves. Our tenyear strategy commits us to improving our capabilities in severe weather prediction. It has already yielded a number of innovative products for mapping lifethreatening severe weather events. Such products include the Extreme Forecast Index, tropical cyclone track and strike probability maps, seasonal tropical cyclone frequency, extreme rainfall and freak waves. To improve our severe weather warning capabilities at extended ranges, we have developed a highly-skilled seasonal forecasting capability and introduced our monthly forecasting system in. We have also developed a multi-model seasonal forecasting system based on our forecasts and those of our project partners, the United Kingdom s Met Office and Météo-France. The potential humanitarian and economic benefits of our work are considerable. We can forecast, for instance, heat waves and cold spells in European countries several weeks in advance; predict the probability of occurrence and likely intensity of El Niño-related effects in the tropics several months before they happen; and help to alleviate human misery in Africa and other vulnerable developing regions by estimating the probability of severe droughts, excessive rainfall and outbreaks of devastating diseases such as malaria. Windy Extreme wind eavy precipitation Extreme precipitation N W An intense winter storm (named Klaus) caused significant destruction across southern France and northern Spain on January, 9. The storm developed in the Atlantic on and January and moved very rapidly in the strong westerly flow, crossing France and continuing to also affect the western Mediterranean. The chart shows areas where there is a high risk of strong winds on January based on the EPS forecast from UTC on 1 January. The shading shows the Extreme Forecast Index (EFI) for wind gusts, which compares the EPS forecast to the distribution of the model climate; higher values indicate a greater risk of extreme weather. The contours show the analysed hpa height field for UTC on January, when the storm struck the French coast

12 About ECMWF ECMWF is an independent inter govern - mental organisation supported by more than States. Its headquarters is located in Reading, km west of ondon, where about 1 staff and consultants are employed. ECMWF s budget is funded almost entirely from annual contributions from Member and Co-operating States according to a scale based on their gross national income. ECMWF s governing body, the Council, is formed of two repre sent - atives from each Member State. Twelve members of the Scientific Advisory Committee are appointed in their personal capacity. Four Committees comprising experts from the Member States advise the Council: the Technical Advisory Committee, the Finance Committee, the Policy Advisory Com - mit tee and the Advisory Committee for Data Policy. In addition, the Advisory Committee of Co-operating States comprises representatives of States with which the organisa tion has co-operation agreements. Computer Division Operations Department Meteorological Division Member States Co-operating States Director-General Administration Department Data Division Model Division Predictability Division Research Department Atmospheric Composition Division ECMWF s Director-General, appointed by the Council, is responsible for implementing the organisa tion s objectives and oversees three departments: Operations, Research and Administration. The Convention establishing ECMWF and its remit came into force on 1 November 197. Amendments made to the Convention were adopted by the Council in April. They came into force on June permitting additional European States to become Member States and formally expanding ECMWF s mission to include environmental and climate monitoring. ECMWF is an intergovernmental organisation supported by more than States. It provides weather services with medium-range forecasts of global weather to 1 days ahead as well as with monthly and seasonal forecasts. ECMWF s computer system at its headquarters in Reading, United Kingdom, is one of the largest for meteorology worldwide and contains the world s largest archive of numerical weather prediction data. It runs a sophisticated medium-range prediction model of the global atmosphere and oceans. The National Meteorological Services of Member States and Co-operating States use ECMWF s products for their own national duties, in particular to give early warning of potentially damaging severe weather. European Centre for Medium-Range Weather Forecasts (ECMWF) Shinfield Park, Reading RG 9AX, United Kingdom Tel: + () Fax: + () Website: 1 ECMWF 1

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