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		<title>Assimilation of radar data in AROME (presentation, March 2008)</title>
		<link>http://www.cnrm.meteo.fr/gmapdoc/spip.php?article182</link>
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		<dc:date>2008-03-31T10:30:47Z</dc:date>
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		<dc:language>en</dc:language>
		<dc:creator>Patricia</dc:creator>







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&lt;p&gt;Presentation of Eric Wattrelot during the 2nd AROME training course, Lisbon, 4-7 March 2008 : &#034;Assimilation of radar data in the
&lt;br class='autobr' /&gt;
AROME model AROME model at at M&#195;&#169;t&#195;&#169;o M&#195;&#169;t&#195;&#169;o-France France&#034; by Eric Wattrelot, Olivier Caumont, Thibaut Montmerle, Claudia Faccani, Marian Jurasek and G&#195;&#188;nther Haase. Outlines Context and Introduction. Basic theory of the two measurements: radial wind and reflectivity Sources of measurement errors: need for pre-processing radar data. The specific radar product (&#8230;)&lt;/p&gt;


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&lt;a href="http://www.cnrm.meteo.fr/gmapdoc/spip.php?rubrique47" rel="directory"&gt;Analysis and assimilation&lt;/a&gt;


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		<title>The AROME RUC (presentation, March 2008)</title>
		<link>http://www.cnrm.meteo.fr/gmapdoc/spip.php?article180</link>
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		<dc:date>2008-03-31T10:11:41Z</dc:date>
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		<dc:language>en</dc:language>
		<dc:creator>Patricia</dc:creator>







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&lt;p&gt;Presentation of Pierre Brousseau during the 2nd AROME training course, Lisbon, 4-7 March 2008 : &#034;A mesoscale data assimilation system for operations : the AROME RUC&#034;, PierreBrousseau, Y. Seity, L. Auger, L.Berre, T.Montmerle, E. Wattrelot, C. Faccani &lt;br class='autobr' /&gt;
Outlines General ideas on data assimilation The AROME data assimilation system Background-error Statistics Assimilation experiments &lt;br class='autobr' /&gt;
Conclusion A prototype for the AROME data assimilation system is currently being tested at M&#195;&#169;t&#195;&#169;o-France. (* (&#8230;)&lt;/p&gt;


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&lt;a href="http://www.cnrm.meteo.fr/gmapdoc/spip.php?rubrique47" rel="directory"&gt;Analysis and assimilation&lt;/a&gt;


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		<title>Canari : presentation (in French, Oct 2005)</title>
		<link>http://www.cnrm.meteo.fr/gmapdoc/spip.php?article138</link>
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		<dc:date>2006-02-10T10:37:06Z</dc:date>
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		<dc:creator>Fran&#195;&#167;oise Taillefer</dc:creator>







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&lt;p&gt;CANARI general presentation :
&lt;br class='autobr' /&gt;
&#8211; General Description of CANARI
&lt;br class='autobr' /&gt;
&#8211; Operational use at M&#195;&#169;t&#195;&#169;o-France
&lt;br class='autobr' /&gt;
&#8211; Future plans &lt;br class='autobr' /&gt;
This presentation (in French) gives a general overview of CANARI possibilities.&lt;/p&gt;


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&lt;a href="http://www.cnrm.meteo.fr/gmapdoc/spip.php?rubrique48" rel="directory"&gt;CANARI&lt;/a&gt;


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		<title>Canari : code description - algorithms and data flow (presentation, 2002)</title>
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		<dc:date>2002-12-01T00:00:00Z</dc:date>
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&lt;p&gt;CANARI est the acronym of :
&lt;br class='autobr' /&gt;
&#8211; Code d'Analyse N&#195;&#169;cessaire &#195; Arpege pour ses Rejets et son Initialisation
&lt;br class='autobr' /&gt;
&#8211; Code for the Analysis Necessary for Arpege for its Rejects and its Initiamization &lt;br class='autobr' /&gt;
CANARI is a software which performs an optimum interpolation analysis for any variable of the meteorological forecast model ARPEGE/ALADIN. &lt;br class='autobr' /&gt;
In November 2002, during the 1st ALADIN maintenance and phasing workshop in Budapest, Cornel Soci presented (see the attached .pdf file): &#034;Canari : code (&#8230;)&lt;/p&gt;


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&lt;a href="http://www.cnrm.meteo.fr/gmapdoc/spip.php?rubrique48" rel="directory"&gt;CANARI&lt;/a&gt;


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		<title>Use of satellite data (presentation, 2001)</title>
		<link>http://www.cnrm.meteo.fr/gmapdoc/spip.php?article101</link>
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		<dc:date>2002-06-01T12:19:00Z</dc:date>
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&lt;p&gt;Presentation of Elisabeth G&#195;&#169;rard during the ALATNET training course on Data Assimilation in Gourdon, 11-22 June 2001. &lt;br class='autobr' /&gt;
Contents : 1. Influence of satellite data in NWP TEMP, SATOB, SSM/I, ATOVS ARPEGE grid Illustration of the OSEs Short range in Northern Hemisphere Medium range Principle of remote sensing Active remote sensing Satellite picture Radio occultation geometry Passive remote sensing Solar Backscatter Ultraviolet Spectral Radiometer Information content Radiative transfer (&#8230;)&lt;/p&gt;


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&lt;a href="http://www.cnrm.meteo.fr/gmapdoc/spip.php?rubrique47" rel="directory"&gt;Analysis and assimilation&lt;/a&gt;


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		<title>Adjoint technique (presentation, 2001)</title>
		<link>http://www.cnrm.meteo.fr/gmapdoc/spip.php?article100</link>
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		<dc:date>2002-06-01T12:08:00Z</dc:date>
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&lt;p&gt;Presentation of Dominique Giard during the ALATNET training course on Data Assimilation in Gourdon, 11-22 June 2001. &lt;br class='autobr' /&gt;
Contents : ADJOINT TECHNIQUE : GENERAL DESCRIPTION Definitions of tangent linear (TL) and adjoint (AD) operators Case of 3D-Var and 4D-Var assimilation Practical rules for coding TL and AD Different applications of AD models, validation&lt;/p&gt;


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&lt;a href="http://www.cnrm.meteo.fr/gmapdoc/spip.php?rubrique47" rel="directory"&gt;Analysis and assimilation&lt;/a&gt;


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		<title>Variational Data Assimilation (presentation, 2001)</title>
		<link>http://www.cnrm.meteo.fr/gmapdoc/spip.php?article103</link>
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		<dc:date>2001-06-01T15:41:00Z</dc:date>
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		<dc:language>en</dc:language>
		







		<description>
&lt;p&gt;Presentation of Claude Fischer, Andras Horanyi and Wafaa Sadiki during the ALATNET training course on Data Assimilation in Gourdon, 11-22 June 2001. &lt;br class='autobr' /&gt;
Contents : General aspects : motivations history general formulation of the cost function error covariance matrices minimization algorithms Practical implementation : where the problems start and where refinements are needed (multi-)incremental approach quasi-continuous approach the exemple of M&#195;&#169;t&#195;&#169;o-France 4D-Var flow dependant structure (&#8230;)&lt;/p&gt;


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&lt;a href="http://www.cnrm.meteo.fr/gmapdoc/spip.php?rubrique50" rel="directory"&gt;Variational&lt;/a&gt;


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		<title>Observations : use, screening, cost function, control and monitoring (presentation, 2001)</title>
		<link>http://www.cnrm.meteo.fr/gmapdoc/spip.php?article105</link>
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		<dc:date>2001-06-01T14:02:00Z</dc:date>
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		<dc:language>en</dc:language>
		







		<description>
&lt;p&gt;Presentation of Patrick Moll and Elisabeth G&#195;&#169;rard during the ALATNET training course on Data Assimilation in Gourdon, 11-22 June 2001. Observation : General presentation General problematic of data assimilation Problems with the available data Real time available data Production suite The process of data assimilation Operational suite at Meteo-France Summary of the current use of observations at M&#195;&#169;t&#195;&#169;o-France Conventional observations Synops : Details of use Surface : Data coverage Buoys (&#8230;)&lt;/p&gt;


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&lt;a href="http://www.cnrm.meteo.fr/gmapdoc/spip.php?rubrique49" rel="directory"&gt;Observations&lt;/a&gt;


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		<title>Optimal estimation in meteorology (presentation, 2001)</title>
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		<dc:date>2001-06-01T12:14:00Z</dc:date>
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&lt;p&gt;OPTIMAL ESTIMATION IN METEOROLOGY was presented by G&#195;&#169;rald Desroziers during the ALATNET seminar on Data Assimilation, June 11-22, 2001. Introduction estimation theory observations are not perfect, the estimate will also be approximate, the estimate must be an optimal combination of observations, it is better to overdetermine the problem, a model can be used to give a preliminary estimate, model are never perfect, the estimate should fit observations within their errors. 1st approach: (&#8230;)&lt;/p&gt;


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&lt;a href="http://www.cnrm.meteo.fr/gmapdoc/spip.php?rubrique47" rel="directory"&gt;Analysis and assimilation&lt;/a&gt;


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		<title>CANARI-DIAGPACK (presentation, 2001)</title>
		<link>http://www.cnrm.meteo.fr/gmapdoc/spip.php?article99</link>
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		<dc:date>2001-06-01T10:42:00Z</dc:date>
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		<description>
&lt;p&gt;Presentation of Andras Horanyi and Jure Jerman during the ALATNET training course on Data Assimilation in Gourdon, 11-22 June 2001. &lt;br class='autobr' /&gt;
Contents : Diagpack, idea behind Brief history of Canari + Diagpack Objective analysis/data assimilation Applications of CANARI NOWCASTING OI: basic theory Single-observation experiments Canari ==&gt; Diagpack Tuning Practical steps of the analysis CANARI for nowcasting in Hungary Diagnostics for convection Example for CAPE Case studies Assumptions, limitations, (&#8230;)&lt;/p&gt;


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&lt;a href="http://www.cnrm.meteo.fr/gmapdoc/spip.php?rubrique47" rel="directory"&gt;Analysis and assimilation&lt;/a&gt;


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