Serveur d'exploration sur les relations entre la France et l'Australie

Attention, ce site est en cours de développement !
Attention, site généré par des moyens informatiques à partir de corpus bruts.
Les informations ne sont donc pas validées.

Optimal representation of source‐sink fluxes for mesoscale carbon dioxide inversion with synthetic data

Identifieur interne : 006364 ( Main/Exploration ); précédent : 006363; suivant : 006365

Optimal representation of source‐sink fluxes for mesoscale carbon dioxide inversion with synthetic data

Auteurs : Lin Wu [France] ; Marc Bocquet [France] ; Thomas Lauvaux [États-Unis] ; Frédéric Chevallier [France] ; Peter Rayner [Australie] ; Kenneth Davis [États-Unis]

Source :

RBID : ISTEX:679DE84C4EA57963368ED1CDF6D16410CC063E92

English descriptors

Abstract

The inversion of CO2 surface fluxes from atmospheric concentration measurements involves discretizing the flux domain in time and space. The resolution choice is usually guided by technical considerations despite its impact on the solution to the inversion problem. In our previous studies, a Bayesian formalism has recently been introduced to describe the discretization of the parameter space over a large dictionary of adaptive multiscale grids. In this paper, we exploit this new framework to construct optimal space‐time representations of carbon fluxes for mesoscale inversions. Inversions are performed using synthetic continuous hourly CO2 concentration data in the context of the Ring 2 experiment in support of the North American Carbon Program Mid Continent Intensive (MCI). Compared with the regular grid at finest scale, optimal representations can have similar inversion performance with far fewer grid cells. These optimal representations are obtained by maximizing the number of degrees of freedom for the signal (DFS) that measures the information gain from observations to resolve the unknown fluxes. Consequently information from observations can be better propagated within the domain through these optimal representations. For the Ring 2 network of eight towers, in most cases, the DFS value is relatively small compared to the number of observations d (DFS/d < 20%). In this multiscale setting, scale‐dependent aggregation errors are identified and explicitly formulated for more reliable inversions. It is recommended that the aggregation errors should be taken into account, especially when the correlations in the errors of a priori fluxes are physically unrealistic. The optimal multiscale grids allow to adaptively mitigate the aggregation errors.

Url:
DOI: 10.1029/2011JD016198


Affiliations:


Links toward previous steps (curation, corpus...)


Le document en format XML

<record>
<TEI wicri:istexFullTextTei="biblStruct">
<teiHeader>
<fileDesc>
<titleStmt>
<title xml:lang="en">Optimal representation of source‐sink fluxes for mesoscale carbon dioxide inversion with synthetic data</title>
<author>
<name sortKey="Wu, Lin" sort="Wu, Lin" uniqKey="Wu L" first="Lin" last="Wu">Lin Wu</name>
</author>
<author>
<name sortKey="Bocquet, Marc" sort="Bocquet, Marc" uniqKey="Bocquet M" first="Marc" last="Bocquet">Marc Bocquet</name>
</author>
<author>
<name sortKey="Lauvaux, Thomas" sort="Lauvaux, Thomas" uniqKey="Lauvaux T" first="Thomas" last="Lauvaux">Thomas Lauvaux</name>
</author>
<author>
<name sortKey="Chevallier, Frederic" sort="Chevallier, Frederic" uniqKey="Chevallier F" first="Frédéric" last="Chevallier">Frédéric Chevallier</name>
</author>
<author>
<name sortKey="Rayner, Peter" sort="Rayner, Peter" uniqKey="Rayner P" first="Peter" last="Rayner">Peter Rayner</name>
</author>
<author>
<name sortKey="Davis, Kenneth" sort="Davis, Kenneth" uniqKey="Davis K" first="Kenneth" last="Davis">Kenneth Davis</name>
</author>
</titleStmt>
<publicationStmt>
<idno type="wicri:source">ISTEX</idno>
<idno type="RBID">ISTEX:679DE84C4EA57963368ED1CDF6D16410CC063E92</idno>
<date when="2011" year="2011">2011</date>
<idno type="doi">10.1029/2011JD016198</idno>
<idno type="url">https://api.istex.fr/document/679DE84C4EA57963368ED1CDF6D16410CC063E92/fulltext/pdf</idno>
<idno type="wicri:Area/Istex/Corpus">001347</idno>
<idno type="wicri:explorRef" wicri:stream="Istex" wicri:step="Corpus" wicri:corpus="ISTEX">001347</idno>
<idno type="wicri:Area/Istex/Curation">001347</idno>
<idno type="wicri:Area/Istex/Checkpoint">000783</idno>
<idno type="wicri:explorRef" wicri:stream="Istex" wicri:step="Checkpoint">000783</idno>
<idno type="wicri:doubleKey">0148-0227:2011:Wu L:optimal:representation:of</idno>
<idno type="wicri:Area/Main/Merge">006740</idno>
<idno type="wicri:Area/Main/Curation">006364</idno>
<idno type="wicri:Area/Main/Exploration">006364</idno>
</publicationStmt>
<sourceDesc>
<biblStruct>
<analytic>
<title level="a" type="main">Optimal representation of source‐sink fluxes for mesoscale carbon dioxide inversion with synthetic data</title>
<author>
<name sortKey="Wu, Lin" sort="Wu, Lin" uniqKey="Wu L" first="Lin" last="Wu">Lin Wu</name>
<affiliation wicri:level="1">
<country wicri:rule="url">France</country>
</affiliation>
<affiliation wicri:level="1">
<country xml:lang="fr">France</country>
<wicri:regionArea>CEREA, Joint Laboratory École des Ponts ParisTech ‐ EDF R&D, Université Paris‐Est, Marne la Vallée</wicri:regionArea>
<wicri:noRegion>Marne la Vallée</wicri:noRegion>
<wicri:noRegion>Marne la Vallée</wicri:noRegion>
</affiliation>
<affiliation wicri:level="3">
<country xml:lang="fr">France</country>
<wicri:regionArea>INRIA, Paris‐Rocquencourt Research Center, Paris</wicri:regionArea>
<placeName>
<region type="region">Île-de-France</region>
<region type="old region">Île-de-France</region>
<settlement type="city">Paris</settlement>
</placeName>
</affiliation>
<affiliation wicri:level="1">
<country wicri:rule="url">France</country>
</affiliation>
</author>
<author>
<name sortKey="Bocquet, Marc" sort="Bocquet, Marc" uniqKey="Bocquet M" first="Marc" last="Bocquet">Marc Bocquet</name>
<affiliation wicri:level="1">
<country xml:lang="fr">France</country>
<wicri:regionArea>CEREA, Joint Laboratory École des Ponts ParisTech ‐ EDF R&D, Université Paris‐Est, Marne la Vallée</wicri:regionArea>
<wicri:noRegion>Marne la Vallée</wicri:noRegion>
<wicri:noRegion>Marne la Vallée</wicri:noRegion>
</affiliation>
<affiliation wicri:level="3">
<country xml:lang="fr">France</country>
<wicri:regionArea>INRIA, Paris‐Rocquencourt Research Center, Paris</wicri:regionArea>
<placeName>
<region type="region">Île-de-France</region>
<region type="old region">Île-de-France</region>
<settlement type="city">Paris</settlement>
</placeName>
</affiliation>
</author>
<author>
<name sortKey="Lauvaux, Thomas" sort="Lauvaux, Thomas" uniqKey="Lauvaux T" first="Thomas" last="Lauvaux">Thomas Lauvaux</name>
<affiliation wicri:level="4">
<country xml:lang="fr">États-Unis</country>
<wicri:regionArea>Department of Meteorology, Pennsylvania State University, Pennsylvania, University Park</wicri:regionArea>
<orgName type="university">Université d'État de Pennsylvanie</orgName>
<placeName>
<settlement type="city">University Park (Pennsylvanie)</settlement>
<region type="state">Pennsylvanie</region>
</placeName>
</affiliation>
</author>
<author>
<name sortKey="Chevallier, Frederic" sort="Chevallier, Frederic" uniqKey="Chevallier F" first="Frédéric" last="Chevallier">Frédéric Chevallier</name>
<affiliation wicri:level="1">
<country xml:lang="fr">France</country>
<wicri:regionArea>Laboratoire des Sciences du Climat et de l'Environnement, CEA‐CNRS‐UVSQ, IPSL, Gif‐sur‐Yvette</wicri:regionArea>
<wicri:noRegion>Gif‐sur‐Yvette</wicri:noRegion>
<wicri:noRegion>Gif‐sur‐Yvette</wicri:noRegion>
</affiliation>
</author>
<author>
<name sortKey="Rayner, Peter" sort="Rayner, Peter" uniqKey="Rayner P" first="Peter" last="Rayner">Peter Rayner</name>
<affiliation wicri:level="4">
<country xml:lang="fr">Australie</country>
<wicri:regionArea>School of Earth Sciences, University of Melbourne, Melbourne, Victoria</wicri:regionArea>
<orgName type="university">Université de Melbourne</orgName>
<placeName>
<settlement type="city">Melbourne</settlement>
<region type="état">Victoria (État)</region>
</placeName>
</affiliation>
</author>
<author>
<name sortKey="Davis, Kenneth" sort="Davis, Kenneth" uniqKey="Davis K" first="Kenneth" last="Davis">Kenneth Davis</name>
<affiliation wicri:level="4">
<country xml:lang="fr">États-Unis</country>
<wicri:regionArea>Department of Meteorology, Pennsylvania State University, Pennsylvania, University Park</wicri:regionArea>
<orgName type="university">Université d'État de Pennsylvanie</orgName>
<placeName>
<settlement type="city">University Park (Pennsylvanie)</settlement>
<region type="state">Pennsylvanie</region>
</placeName>
</affiliation>
</author>
</analytic>
<monogr></monogr>
<series>
<title level="j" type="main">Journal of Geophysical Research: Atmospheres</title>
<title level="j" type="alt">JOURNAL OF GEOPHYSICAL RESEARCH: ATMOSPHERES</title>
<idno type="ISSN">0148-0227</idno>
<idno type="eISSN">2156-2202</idno>
<imprint>
<biblScope unit="vol">116</biblScope>
<biblScope unit="issue">D21</biblScope>
<biblScope unit="page-count">16</biblScope>
<date type="published" when="2011-11-16">2011-11-16</date>
</imprint>
<idno type="ISSN">0148-0227</idno>
</series>
</biblStruct>
</sourceDesc>
<seriesStmt>
<idno type="ISSN">0148-0227</idno>
</seriesStmt>
</fileDesc>
<profileDesc>
<textClass>
<keywords scheme="KwdEn" xml:lang="en">
<term>Adaptive</term>
<term>Aggregation</term>
<term>Aggregation effect</term>
<term>Aggregation error</term>
<term>Aggregation errors</term>
<term>American carbon program</term>
<term>Atmos</term>
<term>Atmospheric transport</term>
<term>Background error</term>
<term>Background error covariance matrix</term>
<term>Background errors</term>
<term>Background fluxes</term>
<term>Balgovind</term>
<term>Balgovind form</term>
<term>Bayesian</term>
<term>Binary trees</term>
<term>Blue analysis</term>
<term>Bocquet</term>
<term>Carbon fluxes</term>
<term>Carbon inversions</term>
<term>Chem</term>
<term>Chevallier</term>
<term>Concentration observations</term>
<term>Correlation length</term>
<term>Covariance</term>
<term>Diagonal</term>
<term>Diagonal case</term>
<term>Different scales</term>
<term>Distant regions</term>
<term>Effective degrees</term>
<term>Finest grid</term>
<term>Finest scale</term>
<term>First guesses</term>
<term>Fisher criterion</term>
<term>Flux representation</term>
<term>Flux variables</term>
<term>Flux variations</term>
<term>Flux vector</term>
<term>Geophys</term>
<term>Gerbig</term>
<term>Grid</term>
<term>Grid cell</term>
<term>Grid cells</term>
<term>Hbht</term>
<term>Inconsistent innovation statistics</term>
<term>Infg</term>
<term>Information gain</term>
<term>Innovation vector</term>
<term>Inversion</term>
<term>Inversion errors</term>
<term>Inversion figure</term>
<term>Inversion performance</term>
<term>Inversion results</term>
<term>Inverted</term>
<term>Inverted fluxes</term>
<term>Lagrangian</term>
<term>Lauvaux</term>
<term>Matrix</term>
<term>Mesoscale</term>
<term>Mesoscale inversions</term>
<term>Meteorological conditions</term>
<term>Multiscale</term>
<term>Multiscale grids</term>
<term>Multiscale representation</term>
<term>Multiscale representations</term>
<term>Observation sites</term>
<term>Observational</term>
<term>Observational error</term>
<term>Observational error covariance matrices</term>
<term>Observational error covariance matrix</term>
<term>Optimal grids</term>
<term>Optimal multiscale grids</term>
<term>Optimal multiscale representation</term>
<term>Optimal multiscale representations</term>
<term>Optimal representation</term>
<term>Optimal representations</term>
<term>Optimization</term>
<term>Pennsylvania state university</term>
<term>Perturbation</term>
<term>Peylin</term>
<term>Phys</term>
<term>Preliminary tests</term>
<term>Prolongation</term>
<term>Prolongation operator</term>
<term>Rayner</term>
<term>Realistic correlations</term>
<term>Regular grid</term>
<term>Regular grids</term>
<term>Representation</term>
<term>Representation optimization</term>
<term>Restriction operator</term>
<term>Rmse</term>
<term>Spatial correlations</term>
<term>Spatiotemporal</term>
<term>Standard deviation</term>
<term>Surface fluxes</term>
<term>Synthetic data</term>
<term>Temporal correlations</term>
<term>Time period</term>
<term>Total number</term>
<term>Transport errors</term>
<term>Transport models</term>
<term>True reference fluxes</term>
<term>Unknown fluxes</term>
<term>Variance</term>
</keywords>
<keywords scheme="Teeft" xml:lang="en">
<term>Adaptive</term>
<term>Aggregation</term>
<term>Aggregation effect</term>
<term>Aggregation error</term>
<term>Aggregation errors</term>
<term>American carbon program</term>
<term>Atmos</term>
<term>Atmospheric transport</term>
<term>Background error</term>
<term>Background error covariance matrix</term>
<term>Background errors</term>
<term>Background fluxes</term>
<term>Balgovind</term>
<term>Balgovind form</term>
<term>Bayesian</term>
<term>Binary trees</term>
<term>Blue analysis</term>
<term>Bocquet</term>
<term>Carbon fluxes</term>
<term>Carbon inversions</term>
<term>Chem</term>
<term>Chevallier</term>
<term>Concentration observations</term>
<term>Correlation length</term>
<term>Covariance</term>
<term>Diagonal</term>
<term>Diagonal case</term>
<term>Different scales</term>
<term>Distant regions</term>
<term>Effective degrees</term>
<term>Finest grid</term>
<term>Finest scale</term>
<term>First guesses</term>
<term>Fisher criterion</term>
<term>Flux representation</term>
<term>Flux variables</term>
<term>Flux variations</term>
<term>Flux vector</term>
<term>Geophys</term>
<term>Gerbig</term>
<term>Grid</term>
<term>Grid cell</term>
<term>Grid cells</term>
<term>Hbht</term>
<term>Inconsistent innovation statistics</term>
<term>Infg</term>
<term>Information gain</term>
<term>Innovation vector</term>
<term>Inversion</term>
<term>Inversion errors</term>
<term>Inversion figure</term>
<term>Inversion performance</term>
<term>Inversion results</term>
<term>Inverted</term>
<term>Inverted fluxes</term>
<term>Lagrangian</term>
<term>Lauvaux</term>
<term>Matrix</term>
<term>Mesoscale</term>
<term>Mesoscale inversions</term>
<term>Meteorological conditions</term>
<term>Multiscale</term>
<term>Multiscale grids</term>
<term>Multiscale representation</term>
<term>Multiscale representations</term>
<term>Observation sites</term>
<term>Observational</term>
<term>Observational error</term>
<term>Observational error covariance matrices</term>
<term>Observational error covariance matrix</term>
<term>Optimal grids</term>
<term>Optimal multiscale grids</term>
<term>Optimal multiscale representation</term>
<term>Optimal multiscale representations</term>
<term>Optimal representation</term>
<term>Optimal representations</term>
<term>Optimization</term>
<term>Pennsylvania state university</term>
<term>Perturbation</term>
<term>Peylin</term>
<term>Phys</term>
<term>Preliminary tests</term>
<term>Prolongation</term>
<term>Prolongation operator</term>
<term>Rayner</term>
<term>Realistic correlations</term>
<term>Regular grid</term>
<term>Regular grids</term>
<term>Representation</term>
<term>Representation optimization</term>
<term>Restriction operator</term>
<term>Rmse</term>
<term>Spatial correlations</term>
<term>Spatiotemporal</term>
<term>Standard deviation</term>
<term>Surface fluxes</term>
<term>Synthetic data</term>
<term>Temporal correlations</term>
<term>Time period</term>
<term>Total number</term>
<term>Transport errors</term>
<term>Transport models</term>
<term>True reference fluxes</term>
<term>Unknown fluxes</term>
<term>Variance</term>
</keywords>
</textClass>
</profileDesc>
</teiHeader>
<front>
<div type="abstract">The inversion of CO2 surface fluxes from atmospheric concentration measurements involves discretizing the flux domain in time and space. The resolution choice is usually guided by technical considerations despite its impact on the solution to the inversion problem. In our previous studies, a Bayesian formalism has recently been introduced to describe the discretization of the parameter space over a large dictionary of adaptive multiscale grids. In this paper, we exploit this new framework to construct optimal space‐time representations of carbon fluxes for mesoscale inversions. Inversions are performed using synthetic continuous hourly CO2 concentration data in the context of the Ring 2 experiment in support of the North American Carbon Program Mid Continent Intensive (MCI). Compared with the regular grid at finest scale, optimal representations can have similar inversion performance with far fewer grid cells. These optimal representations are obtained by maximizing the number of degrees of freedom for the signal (DFS) that measures the information gain from observations to resolve the unknown fluxes. Consequently information from observations can be better propagated within the domain through these optimal representations. For the Ring 2 network of eight towers, in most cases, the DFS value is relatively small compared to the number of observations d (DFS/d < 20%). In this multiscale setting, scale‐dependent aggregation errors are identified and explicitly formulated for more reliable inversions. It is recommended that the aggregation errors should be taken into account, especially when the correlations in the errors of a priori fluxes are physically unrealistic. The optimal multiscale grids allow to adaptively mitigate the aggregation errors.</div>
</front>
</TEI>
<affiliations>
<list>
<country>
<li>Australie</li>
<li>France</li>
<li>États-Unis</li>
</country>
<region>
<li>Pennsylvanie</li>
<li>Victoria (État)</li>
<li>Île-de-France</li>
</region>
<settlement>
<li>Melbourne</li>
<li>Paris</li>
<li>University Park (Pennsylvanie)</li>
</settlement>
<orgName>
<li>Université d'État de Pennsylvanie</li>
<li>Université de Melbourne</li>
</orgName>
</list>
<tree>
<country name="France">
<noRegion>
<name sortKey="Wu, Lin" sort="Wu, Lin" uniqKey="Wu L" first="Lin" last="Wu">Lin Wu</name>
</noRegion>
<name sortKey="Bocquet, Marc" sort="Bocquet, Marc" uniqKey="Bocquet M" first="Marc" last="Bocquet">Marc Bocquet</name>
<name sortKey="Bocquet, Marc" sort="Bocquet, Marc" uniqKey="Bocquet M" first="Marc" last="Bocquet">Marc Bocquet</name>
<name sortKey="Chevallier, Frederic" sort="Chevallier, Frederic" uniqKey="Chevallier F" first="Frédéric" last="Chevallier">Frédéric Chevallier</name>
<name sortKey="Wu, Lin" sort="Wu, Lin" uniqKey="Wu L" first="Lin" last="Wu">Lin Wu</name>
<name sortKey="Wu, Lin" sort="Wu, Lin" uniqKey="Wu L" first="Lin" last="Wu">Lin Wu</name>
<name sortKey="Wu, Lin" sort="Wu, Lin" uniqKey="Wu L" first="Lin" last="Wu">Lin Wu</name>
</country>
<country name="États-Unis">
<region name="Pennsylvanie">
<name sortKey="Lauvaux, Thomas" sort="Lauvaux, Thomas" uniqKey="Lauvaux T" first="Thomas" last="Lauvaux">Thomas Lauvaux</name>
</region>
<name sortKey="Davis, Kenneth" sort="Davis, Kenneth" uniqKey="Davis K" first="Kenneth" last="Davis">Kenneth Davis</name>
</country>
<country name="Australie">
<region name="Victoria (État)">
<name sortKey="Rayner, Peter" sort="Rayner, Peter" uniqKey="Rayner P" first="Peter" last="Rayner">Peter Rayner</name>
</region>
</country>
</tree>
</affiliations>
</record>

Pour manipuler ce document sous Unix (Dilib)

EXPLOR_STEP=$WICRI_ROOT/Wicri/Asie/explor/AustralieFrV1/Data/Main/Exploration
HfdSelect -h $EXPLOR_STEP/biblio.hfd -nk 006364 | SxmlIndent | more

Ou

HfdSelect -h $EXPLOR_AREA/Data/Main/Exploration/biblio.hfd -nk 006364 | SxmlIndent | more

Pour mettre un lien sur cette page dans le réseau Wicri

{{Explor lien
   |wiki=    Wicri/Asie
   |area=    AustralieFrV1
   |flux=    Main
   |étape=   Exploration
   |type=    RBID
   |clé=     ISTEX:679DE84C4EA57963368ED1CDF6D16410CC063E92
   |texte=   Optimal representation of source‐sink fluxes for mesoscale carbon dioxide inversion with synthetic data
}}

Wicri

This area was generated with Dilib version V0.6.33.
Data generation: Tue Dec 5 10:43:12 2017. Site generation: Tue Mar 5 14:07:20 2024