Florence Rabier

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Florence Rabier
Florence Rabier at World Meteorological Organization.jpg
Rabier speaks at the World Meteorological Organization in 2019
Born1964 (age 5960)
Alma mater Université Pierre et Marie Curie
École nationale de la météorologie
Toulouse III - Paul Sabatier University
Scientific career
Institutions European Centre for Medium-Range Weather Forecasts
Météo-France
Thesis Assimilation variationnelle de donnees meteorologiques en presence d'instabilite barocline  (1992)

Florence Rabier (born 1964) 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.

Contents

Early life and education

Rabier joined Météo-France as an undergraduate engineer in meteorology from the École nationale de la météorologie. [1] After completing her undergraduate she joined the Toulouse III - Paul Sabatier University, where she earned a master's degree in meteorology. [1] She moved to the University of Paris (Pierre and Marie Curie University) for her doctoral studies, where she researched variations in meteorological data in the presence of barlocline instabilities. [2] She became a senior scientist in 1998.[ citation needed ]

Research and career

Rabier held various positions at Météo-France, where she worked on numerical weather prediction. In 1997, she developed data assimilation methods to optimise the use of satellite observations in weather forecasting. [3] In particular, Rabier worked on four dimensional variation methods. She was appointed Head of the Observation Section of Météo-France in 2001. [4] [5]

In 2003, Rabier was made Chief Engineer of Bridges and Roads. [6] and General Engineer in 2013. She worked on the Infrared Atmospheric Sounding Interferometer (IASI), an instrument for European meteorological satellites. The IASI is an interferometer that permits the measurement of atmospheric and humidity profiles. IASI has been operating since 2007 and considerably improved operational meteorology. [7] During the International Polar Year (2007-2008) Rabier was part of a field campaign over Antarctica. [8]

Rabier moved to the European Centre for Medium-Range Weather Forecasts (ECMWF) in 2013, where she served as Director of Forecasts. In 2016 Rabier was appointed Director-General of ECMWF. [3] She uses supercomputers to better analyse and forecast the weather.[ citation needed ]

She was Chair of the European Space Agency Advisory Committee on Earth Observations from 2021 to 2023. [9]

Awards and honours

Selected publications

Related Research Articles

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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.

<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.

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<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.

Data assimilation is a mathematical discipline that seeks to optimally combine theory with observations. There may be a number of different goals sought – for example, to determine the optimal state estimate of a system, to determine initial conditions for a numerical forecast model, to interpolate sparse observation data using knowledge of the system being observed, to set numerical parameters based on training a model from observed data. Depending on the goal, different solution methods may be used. Data assimilation is distinguished from other forms of machine learning, image analysis, and statistical methods in that it utilizes a dynamical model of the system being analyzed.

<span class="mw-page-title-main">Global Forecast System</span> Global meteorological forecasting mathematical model

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

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<span class="mw-page-title-main">Tim Palmer (physicist)</span> British meteorologist

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The North American Ensemble Forecast System (NAEFS) is a joint project involving the Meteorological Service of Canada (MSC) in Canada, the National Weather Service (NWS) in the United States, and the National Meteorological Service of Mexico (NMSM) in Mexico providing numerical weather prediction ensemble guidance for the 1- to 16-day forecast period. The NAEFS combines the Canadian MSC and the US NWS global ensemble prediction systems, improving probabilistic operational guidance over what can be built from any individual country's ensemble. Model guidance from the NAEFS is incorporated into the forecasts of the respective national agencies.

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References

  1. 1 2 "Florence Rabier". ORCID. 2022. Retrieved 2022-04-06.
  2. Rabier, Florence (1992). ASSIMILATION VARIATIONNELLE DE DONNEES METEOROLOGIQUES EN PRESENCE D'INSTABILITE BAROCLINE (Thesis). S.l.: [s.n.] OCLC   490320856.
  3. 1 2 "FLORENCE RABIER APPOINTED DIRECTOR GENERAL OF ECMWF (European Centre for (...) - MeteoLux - Portail Météo Luxembourg". www.meteolux.lu. Retrieved 2021-12-27.
  4. "METEO FRANCE - Le site institutionnel de Météo-France". meteofrance.fr. Retrieved 2021-12-27.
  5. "L'Europe à la pointe de la prévision météo". Les Echos (in French). 2018-11-17. Retrieved 2021-12-27.
  6. 1 2 "Florence Rabier - Nominations au Journal officiel de la République française". jorfsearch.steinertriples.fr. Retrieved 2021-12-27.
  7. 1 2 "Commission "Prix & Médailles" de l'Académie de l'Air et de l'Espace". www.academie-air-espace.com. Retrieved 2021-12-27.
  8. Rabier, Florence; Cohn, Steve; Cocquerez, Philippe; Hertzog, Albert; Avallone, Linnea; Deshler, Terry; Haase, Jennifer; Hock, Terry; Doerenbecher, Alexis; Wang, Junhong; Guidard, Vincent (2013-03-01). "The Concordiasi Field Experiment over Antarctica: First Results from Innovative Atmospheric Measurements". Bulletin of the American Meteorological Society. 94 (3): ES17–ES20. Bibcode:2013BAMS...94S..17R. doi: 10.1175/BAMS-D-12-00005.1 .
  9. "Copernicus: ECMWF signs agreement with the European Commission for next phase of climate and atmosphere monitoring services | Copernicus". atmosphere.copernicus.eu. Retrieved 2021-12-27.