European Centre for Medium-Range Weather Forecasts

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European Centre for Medium-Range Weather Forecasts
Ecmwf.png
ECMWF logo.svg
Established1975  OOjs UI icon edit-ltr-progressive.svg (49 years ago)
Headquarters Reading   OOjs UI icon edit-ltr-progressive.svg
CountryUnited Kingdom  OOjs UI icon edit-ltr-progressive.svg
Coordinates 51°25′11″N0°57′03″W / 51.41961°N 0.95081°W / 51.41961; -0.95081 OOjs UI icon edit-ltr-progressive.svg
Chief Executives Florence Rabier   OOjs UI icon edit-ltr-progressive.svg
Directors Florence Rabier
Website www.ecmwf.int   OOjs UI icon edit-ltr-progressive.svg

The European Centre for Medium-Range Weather Forecasts (ECMWF) is an independent intergovernmental organisation supported by most of the nations of Europe. It is based at three sites: Shinfield Park, Reading, United Kingdom; Bologna, Italy; and Bonn, Germany. It operates one of the largest supercomputer complexes in Europe and the world's largest archive of numerical weather prediction data. [1]

Contents

History

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members as of 2015
co-operation agreement European forecasting.svg
  members as of 2015
  co-operation agreement

ECMWF was established in 1975, in recognition of the need to pool the scientific and technical resources of Europe's meteorological services and institutions for the production of weather forecasts for medium-range timescales (up to approximately two weeks) and of the economic and social benefits expected from it. The Centre employs about 350 staff, mostly appointed from across the member states and co-operating states. [1]

In 2017, the centre's member states accepted an offer from the Italian Government to move ECMWF's data centre to Bologna, Italy. [2] The new site, a former tobacco factory, would be redesigned by the architecture firm gmp.

During 2020, the Centre arranged to move its Copernicus operations away from Reading and into European Union territory. [3] Following bids from Toulouse, [3] Italy, [4] Austria, [5] Germany, [6] Spain [7] and Ireland, [8] eventually Bonn (Germany) was chosen. [9] The move has been directly attributed to Brexit. [9] [10]

In August 2023, the centre partnered with Huawei on its cloud, AI-powered Pangu-Weather model for 10-day global weather prediction accuracies. [11]

Objectives

ECMWF aims to provide accurate medium-range global weather forecasts out to 15 days and seasonal forecasts out to 12 months. [12] Its products are provided to the national weather services of its member states and co-operating states as a complement to their national short-range and climatological activities, and those national states use ECMWF's products for their own national duties, in particular to give early warning of potentially damaging severe weather.

ECMWF's core mission is to: [13]

To deliver this core mission, the Centre provides:

The Centre develops and operates global atmospheric models and data assimilation systems for the dynamics, thermodynamics and composition of the Earth's atmosphere and for interacting parts of the Earth-system. It uses numerical weather prediction methods to prepare forecasts and their initial conditions, and it contributes to monitoring the relevant parts of the Earth system.

Work and projects

Forecasting

Numerical weather prediction (NWP) requires input of meteorological data, collected by satellites and earth observation systems such as automatic and crewed weather stations, aircraft (including commercial flights [14] ), ships and weather balloons. Assimilation of this data is used to produce an initial state of a computer model of the atmosphere, from which an atmospheric model is used to forecast the weather. These forecasts are typically:

Over the past three decades ECMWF's wide-ranging programme of research has played a major role in developing such assimilation and modelling systems. This improves the accuracy and reliability of weather forecasting by about a day per decade, so that a seven-day forecast now (2015) is as accurate as a three-day forecast was four decades ago (1975). [15]

Monthly and seasonal forecasts

ECMWF's monthly and seasonal forecasts provide early predictions of events such as heat waves, cold spells and droughts, as well as their impacts on sectors such as agriculture, energy and health. Since ECMWF runs a wave model, there are also predictions of coastal waves and storm surges in European waters which can be used to provide warnings.

Early warning of severe weather events

Forecasts of severe weather events allow appropriate mitigating action to be taken and contingency plans to be put into place by the authorities and the public. The increased time gained by issuing accurate warnings can save lives, for instance by evacuating people from a storm surge area. Authorities and businesses can plan to maintain services around threats such as high winds, floods or snow.

In October 2012 the ECMWF model suggested seven days in advance that Hurricane Sandy was likely to make landfall on the East Coast of the United States. [16] It also predicted the intensity and track of the November 2012 nor'easter, which impacted the east coast a week after Sandy. [17]

ECMWF's Extreme Forecast Index (EFI) was developed as a tool to identify where the EPS (Ensemble Prediction System) forecast distribution differs substantially from that of the model climate[ clarification needed ]. It contains information regarding variability of weather parameters, in location and time and can highlight an abnormality of a weather situation without having to define specific space- and time-dependent thresholds.

Satellite data

ECMWF, through its partnerships with EUMETSAT, ESA, the EU and others, exploits satellite data for operational numerical weather prediction and operational seasonal forecasting with coupled atmosphere–ocean–land models. The increasing amount of satellite data and the development of more sophisticated ways of extracting information from that data have made a major contribution to improving the accuracy and utility of NWP forecasts.[ citation needed ] ECMWF continuously endeavours to improve the use of satellite observations for NWP.

Reanalysis

ECMWF supports research on climate variability using an approach known as reanalysis. This involves feeding weather observations collected over decades into a 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. Reanalysis provides a four-dimensional picture of the atmosphere and effectively allows monitoring of the variability and change of global climate, thereby contributing also to the understanding and attribution of climate change.

To date, and with support from Europe's National Meteorological Services and the European Commission, ECMWF has conducted several major reanalyses of the global atmosphere: the first ECMWF re-analysis (ERA-15) project generated reanalyses from December 1978 to February 1994; the ERA-40 project generated reanalyses from September 1957 to August 2002. The ERA-Interim reanalysis [18] covered the period from 1979 onwards. A reanalysis product (ERA5) [19] with higher spatial resolution (31 km) was released by ECMWF in 2019 as part of the Copernicus Climate Change Service. [20]

Operational forecast model

ECMWF's operational forecasts are produced from its "Integrated Forecast System" (sometimes informally known in the United States as the "European model") which is run every twelve hours and forecasts out to ten days.

It includes both a "deterministic forecast" mode and an ensemble. The deterministic forecast is a single model run that is relatively high in resolution as well as in computational expense. The ensemble is relatively low (about half that of the deterministic) in resolution (and in computational expense), so less accurate. But it is run 51 times in parallel, from slightly different initial conditions to give a spread of likelihood over the range of the forecast. [21]

As of 2021, the ECMWF's weather model is generally considered to be the most accurate weather forecasting model. [22]

Copernicus

The centre currently serves as the Entrusted Entity responsible for delivery of two of the Services of the EU's Copernicus Programme. The two services are the Copernicus Atmosphere Monitoring Service (CAMS) [23] and the Copernicus Climate Change Service (C3S). [24]

The Centre arranged to move its Copernicus operations away from Reading and into Bonn (Germany). [3] [9] The move has been directly attributed to Brexit. [9] [10]

Member and co-operating states

ECMWF comprises 23 European countries:

It also has co-operation agreements with other states: Bulgaria, Czech Republic, Georgia, Hungary, Israel, Latvia, Lithuania, North Macedonia, Montenegro, Morocco, Romania and Slovakia.

Member state [30] Year of joining
Flag of Austria.svg  Austria 1975
Flag of Belgium (civil).svg  Belgium 1975
Flag of Croatia.svg  Croatia 2011
Flag of Denmark.svg  Denmark 1975
Flag of Estonia.svg  Estonia 2020
Flag of Finland.svg  Finland 1975
Flag of France.svg  France 1975
Flag of Germany.svg  Germany 1975
Flag of Greece.svg  Greece 1976
Flag of Iceland.svg  Iceland 2011
Flag of Ireland.svg  Ireland 1975
Flag of Italy.svg  Italy 1977
Flag of Luxembourg.svg  Luxembourg 2002
Flag of the Netherlands.svg  Netherlands 1975
Flag of Norway.svg  Norway 1989
Flag of Portugal.svg  Portugal 1976
Flag of Serbia.svg  Serbia 2014
Flag of Slovenia.svg  Slovenia 2011
Flag of Spain.svg  Spain 1975
Flag of Sweden.svg  Sweden 1975
Flag of Switzerland (Pantone).svg   Switzerland 1975
Flag of Turkey.svg  Turkey 1976
Flag of the United Kingdom.svg  United Kingdom 1975
Co-operating State [31] Year of joining
Flag of Bulgaria.svg  Bulgaria 12 July 2010
Flag of the Czech Republic.svg  Czech Republic 1 August 2001
Flag of Georgia.svg  Georgia 1 December 2021
Flag of Hungary.svg  Hungary 1 July 1994
Flag of Israel.svg  Israel 28 October 2010
Flag of Latvia.svg  Latvia 30 April 2008
Flag of Lithuania.svg  Lithuania 20 November 2006
Flag of Montenegro.svg  Montenegro 5 November 2007
Flag of Morocco.svg  Morocco 1 December 2006
Flag of North Macedonia.svg  North Macedonia 9 February 2011
Flag of Romania.svg  Romania 22 December 2003
Flag of Slovakia.svg  Slovakia 1 January 2008
Co-operating agreements [32] Year of joining
WMO 1 November 1975
EUMETSAT 18 May 1988
ACMAD 11 May 1995
ALADIN/HIRLAM - Use of IFS/Arpege19 February 1999
JRC 6 May 2003
CTBTO 24 June 2003
CLRTAP 26 January 2005
ESA 31 May 2005
Memorandum of Understanding for Joint Liaison Office with European institutions in Brussels23 April 2010
RIMES8 February 2012
CMA21 January 2014
US NWS23 January 2015 - amended 30 January 2018
US NCAR31 August 2016
INPE Brazil31 August 2017

See also

Related Research Articles

<span class="mw-page-title-main">EUMETSAT</span> European intergovernmental organisation

The European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) is an intergovernmental organisation created through an international convention agreed by a current total of 30 European Member States.

<span class="mw-page-title-main">Weather Prediction Center</span> United States weather agency

The Weather Prediction Center (WPC), located in College Park, Maryland, is one of nine service centers under the umbrella of the National Centers for Environmental Prediction (NCEP), a part of the National Weather Service (NWS), which in turn is part of the National Oceanic and Atmospheric Administration (NOAA) of the U.S. Government. Until March 5, 2013 the Weather Prediction Center was known as the Hydrometeorological Prediction Center (HPC). The Weather Prediction Center serves as a center for quantitative precipitation forecasting, medium range forecasting, and the interpretation of numerical weather prediction computer models.

<span class="mw-page-title-main">Numerical weather prediction</span> Weather prediction using mathematical models of the atmosphere and oceans

Numerical weather prediction (NWP) uses mathematical models of the atmosphere and oceans to predict the weather based on current weather conditions. Though first attempted in the 1920s, it was not until the advent of computer simulation in the 1950s that numerical weather predictions produced realistic results. A number of global and regional forecast models are run in different countries worldwide, using current weather observations relayed from radiosondes, weather satellites and other observing systems as inputs.

The ECMWF reanalysis project is a meteorological reanalysis project carried out by the European Centre for Medium-Range Weather Forecasts (ECMWF). The first reanalysis product, ERA-15, generated reanalyses for approximately 15 years, from December 1978 to February 1994. The second product, ERA-40 begins in 1957 and covers 45 years to 2002. As a precursor to a revised extended reanalysis product to replace ERA-40, ECMWF released ERA-Interim, which covers the period from 1979 to 2019. A new reanalysis product ERA5 has recently been released by ECMWF as part of Copernicus Climate Change Services. This product has higher spatial resolution and covers the period from 1979 to present. Extension up to 1940 became available in 2023.

<span class="mw-page-title-main">Ensemble forecasting</span> Multiple simulation method for weather forecasting

Ensemble forecasting is a method used in or within numerical weather prediction. Instead of making a single forecast of the most likely weather, a set of forecasts is produced. This set of forecasts aims to give an indication of the range of possible future states of the atmosphere. Ensemble forecasting is a form of Monte Carlo analysis. The multiple simulations are conducted to account for the two usual sources of uncertainty in forecast models: (1) the errors introduced by the use of imperfect initial conditions, amplified by the chaotic nature of the evolution equations of the atmosphere, which is often referred to as sensitive dependence on initial conditions; and (2) errors introduced because of imperfections in the model formulation, such as the approximate mathematical methods to solve the equations. Ideally, the verified future atmospheric state should fall within the predicted ensemble spread, and the amount of spread should be related to the uncertainty (error) of the forecast. In general, this approach can be used to make probabilistic forecasts of any dynamical system, and not just for weather prediction.

<span class="mw-page-title-main">Atmospheric model</span> Mathematical model of atmospheric motions

In atmospheric science, an atmospheric model is a mathematical model constructed around the full set of primitive, dynamical equations which govern atmospheric motions. It can supplement these equations with parameterizations for turbulent diffusion, radiation, moist processes, heat exchange, soil, vegetation, surface water, the kinematic effects of terrain, and convection. Most atmospheric models are numerical, i.e. they discretize equations of motion. They can predict microscale phenomena such as tornadoes and boundary layer eddies, sub-microscale turbulent flow over buildings, as well as synoptic and global flows. The horizontal domain of a model is either global, covering the entire Earth, or regional (limited-area), covering only part of the Earth. The different types of models run are thermotropic, barotropic, hydrostatic, and nonhydrostatic. Some of the model types make assumptions about the atmosphere which lengthens the time steps used and increases computational speed.

In weather forecasting, model output statistics (MOS) is a multiple linear regression technique in which predictands, often near-surface quantities, are related statistically to one or more predictors. The predictors are typically forecasts from a numerical weather prediction (NWP) model, climatic data, and, if applicable, recent surface observations. Thus, output from NWP models can be transformed by the MOS technique into sensible weather parameters that are familiar to a layperson.

The Global Environmental Multiscale Model (GEM), often known as the CMC model in North America, is an integrated forecasting and data assimilation system developed in the Recherche en Prévision Numérique (RPN), Meteorological Research Branch (MRB), and the Canadian Meteorological Centre (CMC). Along with the NWS's Global Forecast System (GFS), which runs out to 16 days, the ECMWF's Integrated Forecast System (IFS), which runs out 10 days, the Naval Research Laboratory Navy Global Environmental Model (NAVGEM), which runs out eight days, the UK Met Office's Unified Model, which runs out to seven days, and Deutscher Wetterdienst's ICON, which runs out to 7.5 days, it is one of the global medium-range models in general use.

The European Flood Awareness System is a European Commission initiative to increase preparedness for riverine floods across Europe.

<span class="mw-page-title-main">Quantitative precipitation forecast</span> Expected amount of melted precipitation

The quantitative precipitation forecast is the expected amount of melted precipitation accumulated over a specified time period over a specified area. A QPF will be created when precipitation amounts reaching a minimum threshold are expected during the forecast's valid period. Valid periods of precipitation forecasts are normally synoptic hours such as 00:00, 06:00, 12:00 and 18:00 GMT. Terrain is considered in QPFs by use of topography or based upon climatological precipitation patterns from observations with fine detail. Starting in the mid-to-late 1990s, QPFs were used within hydrologic forecast models to simulate impact to rivers throughout the United States. Forecast models show significant sensitivity to humidity levels within the planetary boundary layer, or in the lowest levels of the atmosphere, which decreases with height. QPF can be generated on a quantitative, forecasting amounts, or a qualitative, forecasting the probability of a specific amount, basis. Radar imagery forecasting techniques show higher skill than model forecasts within 6 to 7 hours of the time of the radar image. The forecasts can be verified through use of rain gauge measurements, weather radar estimates, or a combination of both. Various skill scores can be determined to measure the value of the rainfall forecast.

The NCEP/NCAR Reanalysis is an atmospheric reanalysis produced by the National Centers for Environmental Prediction (NCEP) and the National Center for Atmospheric Research (NCAR). It is a continually updated globally gridded data set that represents the state of the Earth's atmosphere, incorporating observations and numerical weather prediction (NWP) model output from 1948 to present.

<span class="mw-page-title-main">André Robert</span> Canadian meteorologist (1929–1993)

Dr. André Robert was a Canadian meteorologist who pioneered the modelling the Earth's atmospheric circulation.

<span class="mw-page-title-main">Jagadish Shukla</span> Indian meteorologist

Jagadish Shukla is an Indian meteorologist and Distinguished University Professor at George Mason University in the United States.

The Unified Model is a numerical weather prediction and climate modeling software suite originally developed by the United Kingdom Met Office, and now both used and further developed by many weather-forecasting agencies around the world. The Unified Model gets its name because a single model is used across a range of both timescales and spatial scales. The models are grid-point based, rather than wave based, and are run on a variety of supercomputers around the world. The Unified Model atmosphere can be coupled to a number of ocean models. At the Met Office it is used for the main suite of Global Model, North Atlantic and Europe model (NAE) and a high-resolution UK model (UKV), in addition to a variety of Crisis Area Models and other models that can be run on demand. Similar Unified Model suites with global and regional domains are used by many other national or military weather agencies around the world for operational forecasting.

The Integrated Forecasting System (IFS) is a global numerical weather prediction system jointly developed and maintained by the European Centre for Medium-Range Weather Forecasts (ECMWF) based in Reading, England, and Météo-France based in Toulouse. The version of the IFS run at ECMWF is often referred to as the "ECMWF" or the "European model" in North America, to distinguish it from the American Global Forecast System.

An atmospheric reanalysis is a meteorological and climate data assimilation project which aims to assimilate historical atmospheric observational data spanning an extended period, using a single consistent assimilation scheme throughout.

<span class="mw-page-title-main">History of numerical weather prediction</span> Aspect of meteorological history

The history of numerical weather prediction considers how current weather conditions as input into mathematical models of the atmosphere and oceans to predict the weather and future sea state has changed over the years. Though first attempted manually in the 1920s, it was not until the advent of the computer and computer simulation that computation time was reduced to less than the forecast period itself. ENIAC was used to create the first forecasts via computer in 1950, and over the years more powerful computers have been used to increase the size of initial datasets and use more complicated versions of the equations of motion. The development of global forecasting models led to the first climate models. The development of limited area (regional) models facilitated advances in forecasting the tracks of tropical cyclone as well as air quality in the 1970s and 1980s.

The Copernicus Atmosphere Monitoring Service (CAMS) is a service implemented by the European Centre for Medium-Range Weather Forecasts (ECMWF), launched in November 11, 2014, that provides continuous data and information on atmospheric composition. CAMS, which is part of the Copernicus Programme, describes the current situation, forecasts the situation a few days ahead, and analyses consistently retrospective data records for recent years. This service has around 10 years of developments, and its current precursor project, MACC-III, is delivering the pre-operational Copernicus Atmosphere Service. CAMS tracks air pollution, solar energy, greenhouse gases and climate forcing globally.

<span class="mw-page-title-main">Florence Rabier</span> French meteorologist

Florence Rabier is a French meteorologist who is Director-General of the European Centre for Medium-Range Weather Forecasts. She works on numerical weather prediction. She was appointed a Knight of the Legion of Honour in 2014.

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Further reading

"ERA-15". Archived from the original on 11 August 2004.
"ERA-40". Archived from the original on 11 August 2004.