Three-dimensional SF6 data and tropospheric transport simulations : Signals, modeling accuracy, and implications for inverse modeling
Identifieur interne : 000129 ( PascalFrancis/Corpus ); précédent : 000128; suivant : 000130Three-dimensional SF6 data and tropospheric transport simulations : Signals, modeling accuracy, and implications for inverse modeling
Auteurs : M. Gloor ; E. Dlugokencky ; C. Brenninkmeijer ; L. Horowitz ; D. F. Hurst ; G. Dutton ; C. Crevoisier ; T. Machida ; P. TansSource :
- Journal of geophysical research [ 0148-0227 ] ; 2007.
Descripteurs français
- Pascal (Inist)
- Troposphère, Transport, Simulation, Modélisation, Précision, Action anthropique, Modèle, Pertinence prévision, Chimie atmosphérique, Latitude, Zone tropicale, Variation temporelle, Hémisphère Nord, Hauteur, Hémisphère Sud, Atmosphère, Ondulation, Zone convergence intertropicale, Gradient latitudinal, Erreur systématique, Variation saisonnière, Couche limite atmosphérique, Amérique du Nord, Eurasie, Hiver.
English descriptors
- KwdEn :
- Atmospheric boundary layer, Atmospheric chemistry, Bias, Eurasia, Forecast skill, Height, Intertropical convergence zone, Latitudinal gradient, Modeling, North America, Northern Hemisphere, Southern Hemisphere, Winter, accuracy, atmosphere, human activity, latitude, models, seasonal variations, simulation, time variations, transport, tropical zone, troposphere, undulation.
Abstract
Surface emissions of SF6 are closely tied to human activity and thus fairly well known. They therefore can and have been used to evaluate tropospheric transport predicted by models. A range of new atmospheric SF6 data permit us to expand on earlier studies. The purpose of this first of two papers is to characterize known and new transport constraints provided by the data and to use them to quantify predictive skill of the MOZART-2 atmospheric chemistry and transport model. Main noteworthy observational constraints are (1) a well-known steep N-S gradient at the surface confined to an ≃40° wide latitude band in the tropics; (2) a fairly uniform N-S gradient in the upper troposphere; (3) an increase in the temporal variation in upper troposphere Northern Hemisphere records with increasing latitude; (4) a negative SF6 gradient in Northern Hemisphere vertical profiles from the surface to 8 km height, but a positive gradient in the Southern Hemisphere; and (5) a clear reflection in surface records of large-scale seasonal atmosphere movements like the undulations of the Intertropical Convergence Zone (ITCZ). Comparison of observations with simulations reveal excellent modeling skills with regards to (1) large-scale annual mean latitudinal gradients at remote surface sites (relative bias of N-S hemisphere difference < 5%) and aloft (≃10 km, relative bias ≤ 25%); (2) seasonality in signals at remote sites caused by large-scale movements of the atmosphere; (3) time variation in upper troposphere records; (4) "faithfulness" of advective transport on timescales up to ≃1 week; and (5) the general shapes and seasonal variation of vertical profiles. The model (1) underestimates the variation in the vertical of profiles, particularly those from locations close to high emissions regions, and (2) overestimates the difference in SF6 between the planetary boundary layer (PBL) and free troposphere over North America, and thus likely Eurasia, during winter by approximately a factor of 2 (STD ≃ 100%). The comparisons permit estimating lower bounds on representation errors which are large for sites close to continental outflow regions. Given the magnitude of the signals and signal variance, SF6 provides a strong constraint on interhemispheric transport, PBL ventilation, dispersion pathways of northern midlatitude surface emissions through the upper troposphere, and large-scale movements of the atmosphere.
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Pour connaître la documentation sur le format Inist Standard.
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Format Inist (serveur)
| NO : | PASCAL 07-0424267 INIST |
|---|---|
| ET : | Three-dimensional SF6 data and tropospheric transport simulations : Signals, modeling accuracy, and implications for inverse modeling |
| AU : | GLOOR (M.); DLUGOKENCKY (E.); BRENNINKMEIJER (C.); HOROWITZ (L.); HURST (D. F.); DUTTON (G.); CREVOISIER (C.); MACHIDA (T.); TANS (P.) |
| AF : | Earth and Biosphere Institute and School of Geography, University of Leeds/Leeds/Royaume-Uni (1 aut.); Global Monitoring Division, Earth System Research Laboratory, NOAA/Boulder, Colorado/Etats-Unis (2 aut., 5 aut., 6 aut., 9 aut.); Max-Planck Institute for Chemistry/Mainz/Allemagne (3 aut.); Geophysical Fluid Dynamics Laboratory, NOAA/Princeton, New Jersey/Etats-Unis (4 aut.); Cooperative Institute for Research in Environmental Sciences, University of Colorado/Boulder, Colorado/Etats-Unis (5 aut., 6 aut.); Atmospheric and Oceanic Sciences Program, Princeton University/Princeton, New Jersey/Etats-Unis (7 aut.); National Institute for Environmental Studies/Tsukuba/Japon (8 aut.) |
| DT : | Publication en série; Niveau analytique |
| SO : | Journal of geophysical research; ISSN 0148-0227; Etats-Unis; Da. 2007; Vol. 112; No. D15; D15112.1-D15112.17; Bibl. 1/2 p. |
| LA : | Anglais |
| EA : | Surface emissions of SF6 are closely tied to human activity and thus fairly well known. They therefore can and have been used to evaluate tropospheric transport predicted by models. A range of new atmospheric SF6 data permit us to expand on earlier studies. The purpose of this first of two papers is to characterize known and new transport constraints provided by the data and to use them to quantify predictive skill of the MOZART-2 atmospheric chemistry and transport model. Main noteworthy observational constraints are (1) a well-known steep N-S gradient at the surface confined to an ≃40° wide latitude band in the tropics; (2) a fairly uniform N-S gradient in the upper troposphere; (3) an increase in the temporal variation in upper troposphere Northern Hemisphere records with increasing latitude; (4) a negative SF6 gradient in Northern Hemisphere vertical profiles from the surface to 8 km height, but a positive gradient in the Southern Hemisphere; and (5) a clear reflection in surface records of large-scale seasonal atmosphere movements like the undulations of the Intertropical Convergence Zone (ITCZ). Comparison of observations with simulations reveal excellent modeling skills with regards to (1) large-scale annual mean latitudinal gradients at remote surface sites (relative bias of N-S hemisphere difference < 5%) and aloft (≃10 km, relative bias ≤ 25%); (2) seasonality in signals at remote sites caused by large-scale movements of the atmosphere; (3) time variation in upper troposphere records; (4) "faithfulness" of advective transport on timescales up to ≃1 week; and (5) the general shapes and seasonal variation of vertical profiles. The model (1) underestimates the variation in the vertical of profiles, particularly those from locations close to high emissions regions, and (2) overestimates the difference in SF6 between the planetary boundary layer (PBL) and free troposphere over North America, and thus likely Eurasia, during winter by approximately a factor of 2 (STD ≃ 100%). The comparisons permit estimating lower bounds on representation errors which are large for sites close to continental outflow regions. Given the magnitude of the signals and signal variance, SF6 provides a strong constraint on interhemispheric transport, PBL ventilation, dispersion pathways of northern midlatitude surface emissions through the upper troposphere, and large-scale movements of the atmosphere. |
| CC : | 220; 001E; 001E01 |
| FD : | Troposphère; Transport; Simulation; Modélisation; Précision; Action anthropique; Modèle; Pertinence prévision; Chimie atmosphérique; Latitude; Zone tropicale; Variation temporelle; Hémisphère Nord; Hauteur; Hémisphère Sud; Atmosphère; Ondulation; Zone convergence intertropicale; Gradient latitudinal; Erreur systématique; Variation saisonnière; Couche limite atmosphérique; Amérique du Nord; Eurasie; Hiver |
| ED : | troposphere; transport; simulation; Modeling; accuracy; human activity; models; Forecast skill; Atmospheric chemistry; latitude; tropical zone; time variations; Northern Hemisphere; Height; Southern Hemisphere; atmosphere; undulation; Intertropical convergence zone; Latitudinal gradient; Bias; seasonal variations; Atmospheric boundary layer; North America; Eurasia; Winter |
| SD : | Transporte; Simulación; Modelización; Precisión; Acción hombre; Modelo; Pertinencia previsión; Zona tropical; Variación temporal; Hemisferio norte; Altura; Hemisferio sur; Atmósfera; Ondulación; Zona convergencia intertropical; Gradiente latitudinal; Error sistemático; Variación estacional; Capa límite atmosférico; America del norte; Eurasia; Invierno |
| LO : | INIST-3144.354000160826540120 |
| ID : | 07-0424267 |
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Pascal:07-0424267Le document en format XML
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Machida</name><affiliation><inist:fA14 i1="07"><s1>National Institute for Environmental Studies</s1><s2>Tsukuba</s2><s3>JPN</s3><sZ>8 aut.</sZ></inist:fA14></affiliation></author><author><name sortKey="Tans, P" sort="Tans, P" uniqKey="Tans P" first="P." last="Tans">P. Tans</name><affiliation><inist:fA14 i1="02"><s1>Global Monitoring Division, Earth System Research Laboratory, NOAA</s1><s2>Boulder, Colorado</s2><s3>USA</s3><sZ>2 aut.</sZ><sZ>5 aut.</sZ><sZ>6 aut.</sZ><sZ>9 aut.</sZ></inist:fA14></affiliation></author></titleStmt><publicationStmt><idno type="wicri:source">INIST</idno><idno type="inist">07-0424267</idno><date when="2007">2007</date><idno type="stanalyst">PASCAL 07-0424267 INIST</idno><idno type="RBID">Pascal:07-0424267</idno><idno type="wicri:Area/PascalFrancis/Corpus">000129</idno></publicationStmt><sourceDesc><biblStruct><analytic><title xml:lang="en" level="a">Three-dimensional SF<sub>6</sub> data and tropospheric transport simulations : Signals, modeling accuracy, and implications for inverse modeling</title><author><name sortKey="Gloor, M" sort="Gloor, M" uniqKey="Gloor M" first="M." last="Gloor">M. Gloor</name><affiliation><inist:fA14 i1="01"><s1>Earth and Biosphere Institute and School of Geography, University of Leeds</s1><s2>Leeds</s2><s3>GBR</s3><sZ>1 aut.</sZ></inist:fA14></affiliation></author><author><name sortKey="Dlugokencky, E" sort="Dlugokencky, E" uniqKey="Dlugokencky E" first="E." last="Dlugokencky">E. Dlugokencky</name><affiliation><inist:fA14 i1="02"><s1>Global Monitoring Division, Earth System Research Laboratory, NOAA</s1><s2>Boulder, Colorado</s2><s3>USA</s3><sZ>2 aut.</sZ><sZ>5 aut.</sZ><sZ>6 aut.</sZ><sZ>9 aut.</sZ></inist:fA14></affiliation></author><author><name sortKey="Brenninkmeijer, C" sort="Brenninkmeijer, C" uniqKey="Brenninkmeijer C" first="C." last="Brenninkmeijer">C. Brenninkmeijer</name><affiliation><inist:fA14 i1="03"><s1>Max-Planck Institute for Chemistry</s1><s2>Mainz</s2><s3>DEU</s3><sZ>3 aut.</sZ></inist:fA14></affiliation></author><author><name sortKey="Horowitz, L" sort="Horowitz, L" uniqKey="Horowitz L" first="L." last="Horowitz">L. Horowitz</name><affiliation><inist:fA14 i1="04"><s1>Geophysical Fluid Dynamics Laboratory, NOAA</s1><s2>Princeton, New Jersey</s2><s3>USA</s3><sZ>4 aut.</sZ></inist:fA14></affiliation></author><author><name sortKey="Hurst, D F" sort="Hurst, D F" uniqKey="Hurst D" first="D. F." last="Hurst">D. F. Hurst</name><affiliation><inist:fA14 i1="02"><s1>Global Monitoring Division, Earth System Research Laboratory, NOAA</s1><s2>Boulder, Colorado</s2><s3>USA</s3><sZ>2 aut.</sZ><sZ>5 aut.</sZ><sZ>6 aut.</sZ><sZ>9 aut.</sZ></inist:fA14></affiliation><affiliation><inist:fA14 i1="05"><s1>Cooperative Institute for Research in Environmental Sciences, University of Colorado</s1><s2>Boulder, Colorado</s2><s3>USA</s3><sZ>5 aut.</sZ><sZ>6 aut.</sZ></inist:fA14></affiliation></author><author><name sortKey="Dutton, G" sort="Dutton, G" uniqKey="Dutton G" first="G." last="Dutton">G. Dutton</name><affiliation><inist:fA14 i1="02"><s1>Global Monitoring Division, Earth System Research Laboratory, NOAA</s1><s2>Boulder, Colorado</s2><s3>USA</s3><sZ>2 aut.</sZ><sZ>5 aut.</sZ><sZ>6 aut.</sZ><sZ>9 aut.</sZ></inist:fA14></affiliation><affiliation><inist:fA14 i1="05"><s1>Cooperative Institute for Research in Environmental Sciences, University of Colorado</s1><s2>Boulder, Colorado</s2><s3>USA</s3><sZ>5 aut.</sZ><sZ>6 aut.</sZ></inist:fA14></affiliation></author><author><name sortKey="Crevoisier, C" sort="Crevoisier, C" uniqKey="Crevoisier C" first="C." last="Crevoisier">C. Crevoisier</name><affiliation><inist:fA14 i1="06"><s1>Atmospheric and Oceanic Sciences Program, Princeton University</s1><s2>Princeton, New Jersey</s2><s3>USA</s3><sZ>7 aut.</sZ></inist:fA14></affiliation></author><author><name sortKey="Machida, T" sort="Machida, T" uniqKey="Machida T" first="T." last="Machida">T. Machida</name><affiliation><inist:fA14 i1="07"><s1>National Institute for Environmental Studies</s1><s2>Tsukuba</s2><s3>JPN</s3><sZ>8 aut.</sZ></inist:fA14></affiliation></author><author><name sortKey="Tans, P" sort="Tans, P" uniqKey="Tans P" first="P." last="Tans">P. Tans</name><affiliation><inist:fA14 i1="02"><s1>Global Monitoring Division, Earth System Research Laboratory, NOAA</s1><s2>Boulder, Colorado</s2><s3>USA</s3><sZ>2 aut.</sZ><sZ>5 aut.</sZ><sZ>6 aut.</sZ><sZ>9 aut.</sZ></inist:fA14></affiliation></author></analytic><series><title level="j" type="main">Journal of geophysical research</title><title level="j" type="abbreviated">J. geophys. res.</title><idno type="ISSN">0148-0227</idno><imprint><date when="2007">2007</date></imprint></series></biblStruct></sourceDesc><seriesStmt><title level="j" type="main">Journal of geophysical research</title><title level="j" type="abbreviated">J. geophys. res.</title><idno type="ISSN">0148-0227</idno></seriesStmt></fileDesc><profileDesc><textClass><keywords scheme="KwdEn" xml:lang="en"><term>Atmospheric boundary layer</term><term>Atmospheric chemistry</term><term>Bias</term><term>Eurasia</term><term>Forecast skill</term><term>Height</term><term>Intertropical convergence zone</term><term>Latitudinal gradient</term><term>Modeling</term><term>North America</term><term>Northern Hemisphere</term><term>Southern Hemisphere</term><term>Winter</term><term>accuracy</term><term>atmosphere</term><term>human activity</term><term>latitude</term><term>models</term><term>seasonal variations</term><term>simulation</term><term>time variations</term><term>transport</term><term>tropical zone</term><term>troposphere</term><term>undulation</term></keywords><keywords scheme="Pascal" xml:lang="fr"><term>Troposphère</term><term>Transport</term><term>Simulation</term><term>Modélisation</term><term>Précision</term><term>Action anthropique</term><term>Modèle</term><term>Pertinence prévision</term><term>Chimie atmosphérique</term><term>Latitude</term><term>Zone tropicale</term><term>Variation temporelle</term><term>Hémisphère Nord</term><term>Hauteur</term><term>Hémisphère Sud</term><term>Atmosphère</term><term>Ondulation</term><term>Zone convergence intertropicale</term><term>Gradient latitudinal</term><term>Erreur systématique</term><term>Variation saisonnière</term><term>Couche limite atmosphérique</term><term>Amérique du Nord</term><term>Eurasie</term><term>Hiver</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">Surface emissions of SF<sub>6</sub> are closely tied to human activity and thus fairly well known. They therefore can and have been used to evaluate tropospheric transport predicted by models. A range of new atmospheric SF<sub>6</sub> data permit us to expand on earlier studies. The purpose of this first of two papers is to characterize known and new transport constraints provided by the data and to use them to quantify predictive skill of the MOZART-2 atmospheric chemistry and transport model. Main noteworthy observational constraints are (1) a well-known steep N-S gradient at the surface confined to an ≃40° wide latitude band in the tropics; (2) a fairly uniform N-S gradient in the upper troposphere; (3) an increase in the temporal variation in upper troposphere Northern Hemisphere records with increasing latitude; (4) a negative SF<sub>6</sub> gradient in Northern Hemisphere vertical profiles from the surface to 8 km height, but a positive gradient in the Southern Hemisphere; and (5) a clear reflection in surface records of large-scale seasonal atmosphere movements like the undulations of the Intertropical Convergence Zone (ITCZ). Comparison of observations with simulations reveal excellent modeling skills with regards to (1) large-scale annual mean latitudinal gradients at remote surface sites (relative bias of N-S hemisphere difference < 5%) and aloft (≃10 km, relative bias ≤ 25%); (2) seasonality in signals at remote sites caused by large-scale movements of the atmosphere; (3) time variation in upper troposphere records; (4) "faithfulness" of advective transport on timescales up to ≃1 week; and (5) the general shapes and seasonal variation of vertical profiles. The model (1) underestimates the variation in the vertical of profiles, particularly those from locations close to high emissions regions, and (2) overestimates the difference in SF<sub>6</sub> between the planetary boundary layer (PBL) and free troposphere over North America, and thus likely Eurasia, during winter by approximately a factor of 2 (STD ≃ 100%). The comparisons permit estimating lower bounds on representation errors which are large for sites close to continental outflow regions. Given the magnitude of the signals and signal variance, SF<sub>6</sub> provides a strong constraint on interhemispheric transport, PBL ventilation, dispersion pathways of northern midlatitude surface emissions through the upper troposphere, and large-scale movements of the atmosphere.</div></front></TEI><inist><standard h6="B"><pA><fA01 i1="01" i2="1"><s0>0148-0227</s0></fA01><fA03 i2="1"><s0>J. geophys. res.</s0></fA03><fA05><s2>112</s2></fA05><fA06><s2>D15</s2></fA06><fA08 i1="01" i2="1" l="ENG"><s1>Three-dimensional SF<sub>6</sub> data and tropospheric transport simulations : Signals, modeling accuracy, and implications for inverse modeling</s1></fA08><fA11 i1="01" i2="1"><s1>GLOOR (M.)</s1></fA11><fA11 i1="02" i2="1"><s1>DLUGOKENCKY (E.)</s1></fA11><fA11 i1="03" i2="1"><s1>BRENNINKMEIJER (C.)</s1></fA11><fA11 i1="04" i2="1"><s1>HOROWITZ (L.)</s1></fA11><fA11 i1="05" i2="1"><s1>HURST (D. F.)</s1></fA11><fA11 i1="06" i2="1"><s1>DUTTON (G.)</s1></fA11><fA11 i1="07" i2="1"><s1>CREVOISIER (C.)</s1></fA11><fA11 i1="08" i2="1"><s1>MACHIDA (T.)</s1></fA11><fA11 i1="09" i2="1"><s1>TANS (P.)</s1></fA11><fA14 i1="01"><s1>Earth and Biosphere Institute and School of Geography, University of Leeds</s1><s2>Leeds</s2><s3>GBR</s3><sZ>1 aut.</sZ></fA14><fA14 i1="02"><s1>Global Monitoring Division, Earth System Research Laboratory, NOAA</s1><s2>Boulder, Colorado</s2><s3>USA</s3><sZ>2 aut.</sZ><sZ>5 aut.</sZ><sZ>6 aut.</sZ><sZ>9 aut.</sZ></fA14><fA14 i1="03"><s1>Max-Planck Institute for Chemistry</s1><s2>Mainz</s2><s3>DEU</s3><sZ>3 aut.</sZ></fA14><fA14 i1="04"><s1>Geophysical Fluid Dynamics Laboratory, NOAA</s1><s2>Princeton, New Jersey</s2><s3>USA</s3><sZ>4 aut.</sZ></fA14><fA14 i1="05"><s1>Cooperative Institute for Research in Environmental Sciences, University of Colorado</s1><s2>Boulder, Colorado</s2><s3>USA</s3><sZ>5 aut.</sZ><sZ>6 aut.</sZ></fA14><fA14 i1="06"><s1>Atmospheric and Oceanic Sciences Program, Princeton University</s1><s2>Princeton, New Jersey</s2><s3>USA</s3><sZ>7 aut.</sZ></fA14><fA14 i1="07"><s1>National Institute for Environmental Studies</s1><s2>Tsukuba</s2><s3>JPN</s3><sZ>8 aut.</sZ></fA14><fA20><s2>D15112.1-D15112.17</s2></fA20><fA21><s1>2007</s1></fA21><fA23 i1="01"><s0>ENG</s0></fA23><fA43 i1="01"><s1>INIST</s1><s2>3144</s2><s5>354000160826540120</s5></fA43><fA44><s0>0000</s0><s1>© 2007 INIST-CNRS. All rights reserved.</s1></fA44><fA45><s0>1/2 p.</s0></fA45><fA47 i1="01" i2="1"><s0>07-0424267</s0></fA47><fA60><s1>P</s1></fA60><fA61><s0>A</s0></fA61><fA64 i1="01" i2="1"><s0>Journal of geophysical research</s0></fA64><fA66 i1="01"><s0>USA</s0></fA66><fC01 i1="01" l="ENG"><s0>Surface emissions of SF<sub>6</sub> are closely tied to human activity and thus fairly well known. They therefore can and have been used to evaluate tropospheric transport predicted by models. A range of new atmospheric SF<sub>6</sub> data permit us to expand on earlier studies. The purpose of this first of two papers is to characterize known and new transport constraints provided by the data and to use them to quantify predictive skill of the MOZART-2 atmospheric chemistry and transport model. Main noteworthy observational constraints are (1) a well-known steep N-S gradient at the surface confined to an ≃40° wide latitude band in the tropics; (2) a fairly uniform N-S gradient in the upper troposphere; (3) an increase in the temporal variation in upper troposphere Northern Hemisphere records with increasing latitude; (4) a negative SF<sub>6</sub> gradient in Northern Hemisphere vertical profiles from the surface to 8 km height, but a positive gradient in the Southern Hemisphere; and (5) a clear reflection in surface records of large-scale seasonal atmosphere movements like the undulations of the Intertropical Convergence Zone (ITCZ). Comparison of observations with simulations reveal excellent modeling skills with regards to (1) large-scale annual mean latitudinal gradients at remote surface sites (relative bias of N-S hemisphere difference < 5%) and aloft (≃10 km, relative bias ≤ 25%); (2) seasonality in signals at remote sites caused by large-scale movements of the atmosphere; (3) time variation in upper troposphere records; (4) "faithfulness" of advective transport on timescales up to ≃1 week; and (5) the general shapes and seasonal variation of vertical profiles. The model (1) underestimates the variation in the vertical of profiles, particularly those from locations close to high emissions regions, and (2) overestimates the difference in SF<sub>6</sub> between the planetary boundary layer (PBL) and free troposphere over North America, and thus likely Eurasia, during winter by approximately a factor of 2 (STD ≃ 100%). The comparisons permit estimating lower bounds on representation errors which are large for sites close to continental outflow regions. Given the magnitude of the signals and signal variance, SF<sub>6</sub> provides a strong constraint on interhemispheric transport, PBL ventilation, dispersion pathways of northern midlatitude surface emissions through the upper troposphere, and large-scale movements of the atmosphere.</s0></fC01><fC02 i1="01" i2="2"><s0>220</s0></fC02><fC02 i1="02" i2="3"><s0>001E</s0></fC02><fC02 i1="03" i2="2"><s0>001E01</s0></fC02><fC03 i1="01" i2="2" l="FRE"><s0>Troposphère</s0><s5>01</s5></fC03><fC03 i1="01" i2="2" l="ENG"><s0>troposphere</s0><s5>01</s5></fC03><fC03 i1="02" i2="2" l="FRE"><s0>Transport</s0><s5>02</s5></fC03><fC03 i1="02" i2="2" l="ENG"><s0>transport</s0><s5>02</s5></fC03><fC03 i1="02" i2="2" l="SPA"><s0>Transporte</s0><s5>02</s5></fC03><fC03 i1="03" i2="2" l="FRE"><s0>Simulation</s0><s5>03</s5></fC03><fC03 i1="03" i2="2" l="ENG"><s0>simulation</s0><s5>03</s5></fC03><fC03 i1="03" i2="2" l="SPA"><s0>Simulación</s0><s5>03</s5></fC03><fC03 i1="04" i2="X" l="FRE"><s0>Modélisation</s0><s5>04</s5></fC03><fC03 i1="04" i2="X" l="ENG"><s0>Modeling</s0><s5>04</s5></fC03><fC03 i1="04" i2="X" l="SPA"><s0>Modelización</s0><s5>04</s5></fC03><fC03 i1="05" i2="2" l="FRE"><s0>Précision</s0><s5>05</s5></fC03><fC03 i1="05" i2="2" l="ENG"><s0>accuracy</s0><s5>05</s5></fC03><fC03 i1="05" i2="2" l="SPA"><s0>Precisión</s0><s5>05</s5></fC03><fC03 i1="06" i2="2" l="FRE"><s0>Action anthropique</s0><s5>06</s5></fC03><fC03 i1="06" i2="2" l="ENG"><s0>human activity</s0><s5>06</s5></fC03><fC03 i1="06" i2="2" l="SPA"><s0>Acción hombre</s0><s5>06</s5></fC03><fC03 i1="07" i2="2" l="FRE"><s0>Modèle</s0><s5>07</s5></fC03><fC03 i1="07" i2="2" l="ENG"><s0>models</s0><s5>07</s5></fC03><fC03 i1="07" i2="2" l="SPA"><s0>Modelo</s0><s5>07</s5></fC03><fC03 i1="08" i2="X" l="FRE"><s0>Pertinence prévision</s0><s5>08</s5></fC03><fC03 i1="08" i2="X" l="ENG"><s0>Forecast skill</s0><s5>08</s5></fC03><fC03 i1="08" i2="X" l="SPA"><s0>Pertinencia previsión</s0><s5>08</s5></fC03><fC03 i1="09" i2="3" l="FRE"><s0>Chimie atmosphérique</s0><s5>09</s5></fC03><fC03 i1="09" i2="3" l="ENG"><s0>Atmospheric chemistry</s0><s5>09</s5></fC03><fC03 i1="10" i2="2" l="FRE"><s0>Latitude</s0><s5>10</s5></fC03><fC03 i1="10" i2="2" l="ENG"><s0>latitude</s0><s5>10</s5></fC03><fC03 i1="11" i2="2" l="FRE"><s0>Zone tropicale</s0><s5>11</s5></fC03><fC03 i1="11" i2="2" l="ENG"><s0>tropical zone</s0><s5>11</s5></fC03><fC03 i1="11" i2="2" l="SPA"><s0>Zona tropical</s0><s5>11</s5></fC03><fC03 i1="12" i2="2" l="FRE"><s0>Variation temporelle</s0><s5>12</s5></fC03><fC03 i1="12" i2="2" l="ENG"><s0>time variations</s0><s5>12</s5></fC03><fC03 i1="12" i2="2" l="SPA"><s0>Variación temporal</s0><s5>12</s5></fC03><fC03 i1="13" i2="2" l="FRE"><s0>Hémisphère Nord</s0><s5>13</s5></fC03><fC03 i1="13" i2="2" l="ENG"><s0>Northern Hemisphere</s0><s5>13</s5></fC03><fC03 i1="13" i2="2" l="SPA"><s0>Hemisferio norte</s0><s5>13</s5></fC03><fC03 i1="14" i2="X" l="FRE"><s0>Hauteur</s0><s5>14</s5></fC03><fC03 i1="14" i2="X" l="ENG"><s0>Height</s0><s5>14</s5></fC03><fC03 i1="14" i2="X" l="SPA"><s0>Altura</s0><s5>14</s5></fC03><fC03 i1="15" i2="2" l="FRE"><s0>Hémisphère Sud</s0><s5>15</s5></fC03><fC03 i1="15" i2="2" l="ENG"><s0>Southern Hemisphere</s0><s5>15</s5></fC03><fC03 i1="15" i2="2" l="SPA"><s0>Hemisferio sur</s0><s5>15</s5></fC03><fC03 i1="16" i2="2" l="FRE"><s0>Atmosphère</s0><s5>16</s5></fC03><fC03 i1="16" i2="2" l="ENG"><s0>atmosphere</s0><s5>16</s5></fC03><fC03 i1="16" i2="2" l="SPA"><s0>Atmósfera</s0><s5>16</s5></fC03><fC03 i1="17" i2="2" l="FRE"><s0>Ondulation</s0><s5>17</s5></fC03><fC03 i1="17" i2="2" l="ENG"><s0>undulation</s0><s5>17</s5></fC03><fC03 i1="17" i2="2" l="SPA"><s0>Ondulación</s0><s5>17</s5></fC03><fC03 i1="18" i2="X" l="FRE"><s0>Zone convergence intertropicale</s0><s5>18</s5></fC03><fC03 i1="18" i2="X" l="ENG"><s0>Intertropical convergence zone</s0><s5>18</s5></fC03><fC03 i1="18" i2="X" l="SPA"><s0>Zona convergencia intertropical</s0><s5>18</s5></fC03><fC03 i1="19" i2="X" l="FRE"><s0>Gradient latitudinal</s0><s5>19</s5></fC03><fC03 i1="19" i2="X" l="ENG"><s0>Latitudinal gradient</s0><s5>19</s5></fC03><fC03 i1="19" i2="X" l="SPA"><s0>Gradiente latitudinal</s0><s5>19</s5></fC03><fC03 i1="20" i2="X" l="FRE"><s0>Erreur systématique</s0><s5>20</s5></fC03><fC03 i1="20" i2="X" l="ENG"><s0>Bias</s0><s5>20</s5></fC03><fC03 i1="20" i2="X" l="SPA"><s0>Error sistemático</s0><s5>20</s5></fC03><fC03 i1="21" i2="2" l="FRE"><s0>Variation saisonnière</s0><s5>21</s5></fC03><fC03 i1="21" i2="2" l="ENG"><s0>seasonal variations</s0><s5>21</s5></fC03><fC03 i1="21" i2="2" l="SPA"><s0>Variación estacional</s0><s5>21</s5></fC03><fC03 i1="22" i2="X" l="FRE"><s0>Couche limite atmosphérique</s0><s5>22</s5></fC03><fC03 i1="22" i2="X" l="ENG"><s0>Atmospheric boundary layer</s0><s5>22</s5></fC03><fC03 i1="22" i2="X" l="SPA"><s0>Capa límite atmosférico</s0><s5>22</s5></fC03><fC03 i1="23" i2="2" l="FRE"><s0>Amérique du Nord</s0><s5>23</s5></fC03><fC03 i1="23" i2="2" l="ENG"><s0>North America</s0><s5>23</s5></fC03><fC03 i1="23" i2="2" l="SPA"><s0>America del norte</s0><s5>23</s5></fC03><fC03 i1="24" i2="2" l="FRE"><s0>Eurasie</s0><s5>24</s5></fC03><fC03 i1="24" i2="2" l="ENG"><s0>Eurasia</s0><s5>24</s5></fC03><fC03 i1="24" i2="2" l="SPA"><s0>Eurasia</s0><s5>24</s5></fC03><fC03 i1="25" i2="X" l="FRE"><s0>Hiver</s0><s5>25</s5></fC03><fC03 i1="25" i2="X" l="ENG"><s0>Winter</s0><s5>25</s5></fC03><fC03 i1="25" i2="X" l="SPA"><s0>Invierno</s0><s5>25</s5></fC03><fN21><s1>274</s1></fN21><fN44 i1="01"><s1>OTO</s1></fN44><fN82><s1>OTO</s1></fN82></pA></standard><server><NO>PASCAL 07-0424267 INIST</NO><ET>Three-dimensional SF<sub>6</sub> data and tropospheric transport simulations : Signals, modeling accuracy, and implications for inverse modeling</ET><AU>GLOOR (M.); DLUGOKENCKY (E.); BRENNINKMEIJER (C.); HOROWITZ (L.); HURST (D. F.); DUTTON (G.); CREVOISIER (C.); MACHIDA (T.); TANS (P.)</AU><AF>Earth and Biosphere Institute and School of Geography, University of Leeds/Leeds/Royaume-Uni (1 aut.); Global Monitoring Division, Earth System Research Laboratory, NOAA/Boulder, Colorado/Etats-Unis (2 aut., 5 aut., 6 aut., 9 aut.); Max-Planck Institute for Chemistry/Mainz/Allemagne (3 aut.); Geophysical Fluid Dynamics Laboratory, NOAA/Princeton, New Jersey/Etats-Unis (4 aut.); Cooperative Institute for Research in Environmental Sciences, University of Colorado/Boulder, Colorado/Etats-Unis (5 aut., 6 aut.); Atmospheric and Oceanic Sciences Program, Princeton University/Princeton, New Jersey/Etats-Unis (7 aut.); National Institute for Environmental Studies/Tsukuba/Japon (8 aut.)</AF><DT>Publication en série; Niveau analytique</DT><SO>Journal of geophysical research; ISSN 0148-0227; Etats-Unis; Da. 2007; Vol. 112; No. D15; D15112.1-D15112.17; Bibl. 1/2 p.</SO><LA>Anglais</LA><EA>Surface emissions of SF<sub>6</sub> are closely tied to human activity and thus fairly well known. They therefore can and have been used to evaluate tropospheric transport predicted by models. A range of new atmospheric SF<sub>6</sub> data permit us to expand on earlier studies. The purpose of this first of two papers is to characterize known and new transport constraints provided by the data and to use them to quantify predictive skill of the MOZART-2 atmospheric chemistry and transport model. Main noteworthy observational constraints are (1) a well-known steep N-S gradient at the surface confined to an ≃40° wide latitude band in the tropics; (2) a fairly uniform N-S gradient in the upper troposphere; (3) an increase in the temporal variation in upper troposphere Northern Hemisphere records with increasing latitude; (4) a negative SF<sub>6</sub> gradient in Northern Hemisphere vertical profiles from the surface to 8 km height, but a positive gradient in the Southern Hemisphere; and (5) a clear reflection in surface records of large-scale seasonal atmosphere movements like the undulations of the Intertropical Convergence Zone (ITCZ). Comparison of observations with simulations reveal excellent modeling skills with regards to (1) large-scale annual mean latitudinal gradients at remote surface sites (relative bias of N-S hemisphere difference < 5%) and aloft (≃10 km, relative bias ≤ 25%); (2) seasonality in signals at remote sites caused by large-scale movements of the atmosphere; (3) time variation in upper troposphere records; (4) "faithfulness" of advective transport on timescales up to ≃1 week; and (5) the general shapes and seasonal variation of vertical profiles. The model (1) underestimates the variation in the vertical of profiles, particularly those from locations close to high emissions regions, and (2) overestimates the difference in SF<sub>6</sub> between the planetary boundary layer (PBL) and free troposphere over North America, and thus likely Eurasia, during winter by approximately a factor of 2 (STD ≃ 100%). The comparisons permit estimating lower bounds on representation errors which are large for sites close to continental outflow regions. Given the magnitude of the signals and signal variance, SF<sub>6</sub> provides a strong constraint on interhemispheric transport, PBL ventilation, dispersion pathways of northern midlatitude surface emissions through the upper troposphere, and large-scale movements of the atmosphere.</EA><CC>220; 001E; 001E01</CC><FD>Troposphère; Transport; Simulation; Modélisation; Précision; Action anthropique; Modèle; Pertinence prévision; Chimie atmosphérique; Latitude; Zone tropicale; Variation temporelle; Hémisphère Nord; Hauteur; Hémisphère Sud; Atmosphère; Ondulation; Zone convergence intertropicale; Gradient latitudinal; Erreur systématique; Variation saisonnière; Couche limite atmosphérique; Amérique du Nord; Eurasie; Hiver</FD><ED>troposphere; transport; simulation; Modeling; accuracy; human activity; models; Forecast skill; Atmospheric chemistry; latitude; tropical zone; time variations; Northern Hemisphere; Height; Southern Hemisphere; atmosphere; undulation; Intertropical convergence zone; Latitudinal gradient; Bias; seasonal variations; Atmospheric boundary layer; North America; Eurasia; Winter</ED><SD>Transporte; Simulación; Modelización; Precisión; Acción hombre; Modelo; Pertinencia previsión; Zona tropical; Variación temporal; Hemisferio norte; Altura; Hemisferio sur; Atmósfera; Ondulación; Zona convergencia intertropical; Gradiente latitudinal; Error sistemático; Variación estacional; Capa límite atmosférico; America del norte; Eurasia; Invierno</SD><LO>INIST-3144.354000160826540120</LO><ID>07-0424267</ID></server></inist></record>Pour manipuler ce document sous Unix (Dilib)
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