Using transport diagnostics to understand chemistry climate model ozone simulations
We use observations of N2O and mean age to identify realistic transport in models in order to explain their ozone predictions. The results are applied to 15 chemistry climate models (CCMs) participating in the 2010 World Meteorological Organization ozone assessment. Comparison of the observed and si...
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Veröffentlicht in: | Journal of Geophysical Research 2011-09, Vol.116 (D17), p.n/a, Article D17302 |
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creator | Strahan, S. E. Douglass, A. R. Stolarski, R. S. Akiyoshi, H. Bekki, S. Braesicke, P. Butchart, N. Chipperfield, M. P. Cugnet, D. Dhomse, S. Frith, S. M. Gettelman, A. Hardiman, S. C. Kinnison, D. E. Lamarque, J.-F. Mancini, E. Marchand, M. Michou, M. Morgenstern, O. Nakamura, T. Olivié, D. Pawson, S. Pitari, G. Plummer, D. A. Pyle, J. A. Scinocca, J. F. Shepherd, T. G. Shibata, K. Smale, D. Teyssèdre, H. Tian, W. Yamashita, Y. |
description | We use observations of N2O and mean age to identify realistic transport in models in order to explain their ozone predictions. The results are applied to 15 chemistry climate models (CCMs) participating in the 2010 World Meteorological Organization ozone assessment. Comparison of the observed and simulated N2O, mean age and their compact correlation identifies models with fast or slow circulations and reveals details of model ascent and tropical isolation. This process‐oriented diagnostic is more useful than mean age alone because it identifies models with compensating transport deficiencies that produce fortuitous agreement with mean age. The diagnosed model transport behavior is related to a model's ability to produce realistic lower stratosphere (LS) O3 profiles. Models with the greatest tropical transport problems compare poorly with O3 observations. Models with the most realistic LS transport agree more closely with LS observations and each other. We incorporate the results of the chemistry evaluations in the Stratospheric Processes and their Role in Climate (SPARC) CCMVal Report to explain the range of CCM predictions for the return‐to‐1980 dates for global (60°S–60°N) and Antarctic column ozone. Antarctic O3 return dates are generally correlated with vortex Cly levels, and vortex Cly is generally correlated with the model's circulation, although model Cl chemistry and conservation problems also have a significant effect on return date. In both regions, models with good LS transport and chemistry produce a smaller range of predictions for the return‐to‐1980 ozone values. This study suggests that the current range of predicted return dates is unnecessarily broad due to identifiable model deficiencies.
Key Points
The trace gas, N2O, is an transport diagnostic
Observations can be used to evaluate model transport
Models with poor transport produce a wide range of ozone predictions |
doi_str_mv | 10.1029/2010JD015360 |
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Key Points
The trace gas, N2O, is an transport diagnostic
Observations can be used to evaluate model transport
Models with poor transport produce a wide range of ozone predictions</description><identifier>ISSN: 0148-0227</identifier><identifier>ISSN: 2169-897X</identifier><identifier>EISSN: 2156-2202</identifier><identifier>EISSN: 2169-8996</identifier><identifier>DOI: 10.1029/2010JD015360</identifier><language>eng</language><publisher>Washington: Blackwell Publishing Ltd</publisher><subject>Atmospheric and Oceanic Physics ; Atmospheric chemistry ; Atmospheric circulation ; Atmospheric sciences ; Climate models ; Climate science ; Climatology ; composition ; Earth Sciences ; General circulation models ; Geophysics ; model evaluation ; Nitrous oxide ; Ozone ; Physics ; Sciences of the Universe ; Stratosphere ; stratospheric transport</subject><ispartof>Journal of Geophysical Research, 2011-09, Vol.116 (D17), p.n/a, Article D17302</ispartof><rights>Copyright 2011 by the American Geophysical Union.</rights><rights>Copyright 2011 by American Geophysical Union</rights><rights>Distributed under a Creative Commons Attribution 4.0 International License</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c5152-e5123e7203cdaa0454b89e69bd1adcc730ccaa5b30d4406c1ec68357d24909393</citedby><cites>FETCH-LOGICAL-c5152-e5123e7203cdaa0454b89e69bd1adcc730ccaa5b30d4406c1ec68357d24909393</cites><orcidid>0000-0002-5538-0800 ; 0000-0003-2220-383X ; 0000-0003-3385-0880</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1029%2F2010JD015360$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1029%2F2010JD015360$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>230,314,778,782,883,1414,1430,11497,27907,27908,45557,45558,46392,46451,46816,46875</link.rule.ids><backlink>$$Uhttps://hal.science/hal-00621937$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Strahan, S. E.</creatorcontrib><creatorcontrib>Douglass, A. R.</creatorcontrib><creatorcontrib>Stolarski, R. S.</creatorcontrib><creatorcontrib>Akiyoshi, H.</creatorcontrib><creatorcontrib>Bekki, S.</creatorcontrib><creatorcontrib>Braesicke, P.</creatorcontrib><creatorcontrib>Butchart, N.</creatorcontrib><creatorcontrib>Chipperfield, M. P.</creatorcontrib><creatorcontrib>Cugnet, D.</creatorcontrib><creatorcontrib>Dhomse, S.</creatorcontrib><creatorcontrib>Frith, S. M.</creatorcontrib><creatorcontrib>Gettelman, A.</creatorcontrib><creatorcontrib>Hardiman, S. C.</creatorcontrib><creatorcontrib>Kinnison, D. E.</creatorcontrib><creatorcontrib>Lamarque, J.-F.</creatorcontrib><creatorcontrib>Mancini, E.</creatorcontrib><creatorcontrib>Marchand, M.</creatorcontrib><creatorcontrib>Michou, M.</creatorcontrib><creatorcontrib>Morgenstern, O.</creatorcontrib><creatorcontrib>Nakamura, T.</creatorcontrib><creatorcontrib>Olivié, D.</creatorcontrib><creatorcontrib>Pawson, S.</creatorcontrib><creatorcontrib>Pitari, G.</creatorcontrib><creatorcontrib>Plummer, D. A.</creatorcontrib><creatorcontrib>Pyle, J. A.</creatorcontrib><creatorcontrib>Scinocca, J. F.</creatorcontrib><creatorcontrib>Shepherd, T. G.</creatorcontrib><creatorcontrib>Shibata, K.</creatorcontrib><creatorcontrib>Smale, D.</creatorcontrib><creatorcontrib>Teyssèdre, H.</creatorcontrib><creatorcontrib>Tian, W.</creatorcontrib><creatorcontrib>Yamashita, Y.</creatorcontrib><title>Using transport diagnostics to understand chemistry climate model ozone simulations</title><title>Journal of Geophysical Research</title><addtitle>J. Geophys. Res</addtitle><description>We use observations of N2O and mean age to identify realistic transport in models in order to explain their ozone predictions. The results are applied to 15 chemistry climate models (CCMs) participating in the 2010 World Meteorological Organization ozone assessment. Comparison of the observed and simulated N2O, mean age and their compact correlation identifies models with fast or slow circulations and reveals details of model ascent and tropical isolation. This process‐oriented diagnostic is more useful than mean age alone because it identifies models with compensating transport deficiencies that produce fortuitous agreement with mean age. The diagnosed model transport behavior is related to a model's ability to produce realistic lower stratosphere (LS) O3 profiles. Models with the greatest tropical transport problems compare poorly with O3 observations. Models with the most realistic LS transport agree more closely with LS observations and each other. We incorporate the results of the chemistry evaluations in the Stratospheric Processes and their Role in Climate (SPARC) CCMVal Report to explain the range of CCM predictions for the return‐to‐1980 dates for global (60°S–60°N) and Antarctic column ozone. Antarctic O3 return dates are generally correlated with vortex Cly levels, and vortex Cly is generally correlated with the model's circulation, although model Cl chemistry and conservation problems also have a significant effect on return date. In both regions, models with good LS transport and chemistry produce a smaller range of predictions for the return‐to‐1980 ozone values. This study suggests that the current range of predicted return dates is unnecessarily broad due to identifiable model deficiencies.
Key Points
The trace gas, N2O, is an transport diagnostic
Observations can be used to evaluate model transport
Models with poor transport produce a wide range of ozone predictions</description><subject>Atmospheric and Oceanic Physics</subject><subject>Atmospheric chemistry</subject><subject>Atmospheric circulation</subject><subject>Atmospheric sciences</subject><subject>Climate models</subject><subject>Climate science</subject><subject>Climatology</subject><subject>composition</subject><subject>Earth Sciences</subject><subject>General circulation models</subject><subject>Geophysics</subject><subject>model evaluation</subject><subject>Nitrous oxide</subject><subject>Ozone</subject><subject>Physics</subject><subject>Sciences of the Universe</subject><subject>Stratosphere</subject><subject>stratospheric transport</subject><issn>0148-0227</issn><issn>2169-897X</issn><issn>2156-2202</issn><issn>2169-8996</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><sourceid>8G5</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNp9kc9rVDEQgIMouLS9-QcETwq-Ovm9OZatbi1Lha3VY8gmaZv6NlmT99T1rzfLkyIenMvA8M3wzQxCLwicEqD6LQUCl-dABJPwBM0oEbKjFOhTNAPC5x1Qqp6jk1ofoAUXkgOZoeubGtMdHopNdZfLgH20dynXIbqKh4zH5EOpg00eu_uwjXUoe-z6uLVDwNvsQ4_zr5wCrnE79naIOdVj9OzW9jWc_MlH6Ob9u0-Li271cflhcbbqnCCCdkEQyoKiwJy3thnxzVwHqTeeWO-cYuCctWLDwHMO0pHg5JwJ5SnXoJlmR-j1NPfe9mZXmlPZm2yjuThbmUMNQFKimfpOGvtqYnclfxtDHUzbxYW-tynksZp2Qi6blqYNffkP-pDHktomRgNVTAFRDXozQa7kWku4fRQgcBimzd__aDib8B-xD_v_suZyuT4nCuBg0k1d7ezh52OXLV-NbB7CfLlamjX_vJ5fXy0MYb8BiiyZkw</recordid><startdate>20110909</startdate><enddate>20110909</enddate><creator>Strahan, S. E.</creator><creator>Douglass, A. R.</creator><creator>Stolarski, R. S.</creator><creator>Akiyoshi, H.</creator><creator>Bekki, S.</creator><creator>Braesicke, P.</creator><creator>Butchart, N.</creator><creator>Chipperfield, M. P.</creator><creator>Cugnet, D.</creator><creator>Dhomse, S.</creator><creator>Frith, S. M.</creator><creator>Gettelman, A.</creator><creator>Hardiman, S. C.</creator><creator>Kinnison, D. E.</creator><creator>Lamarque, J.-F.</creator><creator>Mancini, E.</creator><creator>Marchand, M.</creator><creator>Michou, M.</creator><creator>Morgenstern, O.</creator><creator>Nakamura, T.</creator><creator>Olivié, D.</creator><creator>Pawson, S.</creator><creator>Pitari, G.</creator><creator>Plummer, D. A.</creator><creator>Pyle, J. A.</creator><creator>Scinocca, J. F.</creator><creator>Shepherd, T. G.</creator><creator>Shibata, K.</creator><creator>Smale, D.</creator><creator>Teyssèdre, H.</creator><creator>Tian, W.</creator><creator>Yamashita, Y.</creator><general>Blackwell Publishing Ltd</general><general>American Geophysical Union</general><scope>BSCLL</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7TG</scope><scope>7UA</scope><scope>7XB</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>8G5</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F1W</scope><scope>FR3</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>H8D</scope><scope>H96</scope><scope>HCIFZ</scope><scope>KL.</scope><scope>KR7</scope><scope>L.G</scope><scope>L6V</scope><scope>L7M</scope><scope>M2O</scope><scope>M7S</scope><scope>MBDVC</scope><scope>P5Z</scope><scope>P62</scope><scope>PATMY</scope><scope>PCBAR</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>Q9U</scope><scope>7TV</scope><scope>1XC</scope><scope>VOOES</scope><orcidid>https://orcid.org/0000-0002-5538-0800</orcidid><orcidid>https://orcid.org/0000-0003-2220-383X</orcidid><orcidid>https://orcid.org/0000-0003-3385-0880</orcidid></search><sort><creationdate>20110909</creationdate><title>Using transport diagnostics to understand chemistry climate model ozone simulations</title><author>Strahan, S. E. ; Douglass, A. R. ; Stolarski, R. S. ; Akiyoshi, H. ; Bekki, S. ; Braesicke, P. ; Butchart, N. ; Chipperfield, M. P. ; Cugnet, D. ; Dhomse, S. ; Frith, S. M. ; Gettelman, A. ; Hardiman, S. C. ; Kinnison, D. E. ; Lamarque, J.-F. ; Mancini, E. ; Marchand, M. ; Michou, M. ; Morgenstern, O. ; Nakamura, T. ; Olivié, D. ; Pawson, S. ; Pitari, G. ; Plummer, D. A. ; Pyle, J. A. ; Scinocca, J. F. ; Shepherd, T. 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E.</creatorcontrib><creatorcontrib>Lamarque, J.-F.</creatorcontrib><creatorcontrib>Mancini, E.</creatorcontrib><creatorcontrib>Marchand, M.</creatorcontrib><creatorcontrib>Michou, M.</creatorcontrib><creatorcontrib>Morgenstern, O.</creatorcontrib><creatorcontrib>Nakamura, T.</creatorcontrib><creatorcontrib>Olivié, D.</creatorcontrib><creatorcontrib>Pawson, S.</creatorcontrib><creatorcontrib>Pitari, G.</creatorcontrib><creatorcontrib>Plummer, D. A.</creatorcontrib><creatorcontrib>Pyle, J. A.</creatorcontrib><creatorcontrib>Scinocca, J. F.</creatorcontrib><creatorcontrib>Shepherd, T. G.</creatorcontrib><creatorcontrib>Shibata, K.</creatorcontrib><creatorcontrib>Smale, D.</creatorcontrib><creatorcontrib>Teyssèdre, H.</creatorcontrib><creatorcontrib>Tian, W.</creatorcontrib><creatorcontrib>Yamashita, Y.</creatorcontrib><collection>Istex</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Water Resources Abstracts</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>Materials Science & Engineering Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>Agricultural & Environmental Science Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Technology Collection</collection><collection>Natural Science Collection</collection><collection>Earth, Atmospheric & Aquatic Science Collection</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Engineering Research Database</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>Aerospace Database</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>SciTech Premium Collection</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Civil Engineering Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>ProQuest Engineering Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Research Library</collection><collection>Engineering Database</collection><collection>Research Library (Corporate)</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>Environmental Science Database</collection><collection>Earth, Atmospheric & Aquatic Science Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>Engineering Collection</collection><collection>Environmental Science Collection</collection><collection>ProQuest Central Basic</collection><collection>Pollution Abstracts</collection><collection>Hyper Article en Ligne (HAL)</collection><collection>Hyper Article en Ligne (HAL) (Open Access)</collection><jtitle>Journal of Geophysical Research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Strahan, S. E.</au><au>Douglass, A. R.</au><au>Stolarski, R. S.</au><au>Akiyoshi, H.</au><au>Bekki, S.</au><au>Braesicke, P.</au><au>Butchart, N.</au><au>Chipperfield, M. P.</au><au>Cugnet, D.</au><au>Dhomse, S.</au><au>Frith, S. M.</au><au>Gettelman, A.</au><au>Hardiman, S. C.</au><au>Kinnison, D. E.</au><au>Lamarque, J.-F.</au><au>Mancini, E.</au><au>Marchand, M.</au><au>Michou, M.</au><au>Morgenstern, O.</au><au>Nakamura, T.</au><au>Olivié, D.</au><au>Pawson, S.</au><au>Pitari, G.</au><au>Plummer, D. A.</au><au>Pyle, J. A.</au><au>Scinocca, J. F.</au><au>Shepherd, T. G.</au><au>Shibata, K.</au><au>Smale, D.</au><au>Teyssèdre, H.</au><au>Tian, W.</au><au>Yamashita, Y.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Using transport diagnostics to understand chemistry climate model ozone simulations</atitle><jtitle>Journal of Geophysical Research</jtitle><addtitle>J. Geophys. Res</addtitle><date>2011-09-09</date><risdate>2011</risdate><volume>116</volume><issue>D17</issue><epage>n/a</epage><artnum>D17302</artnum><issn>0148-0227</issn><issn>2169-897X</issn><eissn>2156-2202</eissn><eissn>2169-8996</eissn><abstract>We use observations of N2O and mean age to identify realistic transport in models in order to explain their ozone predictions. The results are applied to 15 chemistry climate models (CCMs) participating in the 2010 World Meteorological Organization ozone assessment. Comparison of the observed and simulated N2O, mean age and their compact correlation identifies models with fast or slow circulations and reveals details of model ascent and tropical isolation. This process‐oriented diagnostic is more useful than mean age alone because it identifies models with compensating transport deficiencies that produce fortuitous agreement with mean age. The diagnosed model transport behavior is related to a model's ability to produce realistic lower stratosphere (LS) O3 profiles. Models with the greatest tropical transport problems compare poorly with O3 observations. Models with the most realistic LS transport agree more closely with LS observations and each other. We incorporate the results of the chemistry evaluations in the Stratospheric Processes and their Role in Climate (SPARC) CCMVal Report to explain the range of CCM predictions for the return‐to‐1980 dates for global (60°S–60°N) and Antarctic column ozone. Antarctic O3 return dates are generally correlated with vortex Cly levels, and vortex Cly is generally correlated with the model's circulation, although model Cl chemistry and conservation problems also have a significant effect on return date. In both regions, models with good LS transport and chemistry produce a smaller range of predictions for the return‐to‐1980 ozone values. This study suggests that the current range of predicted return dates is unnecessarily broad due to identifiable model deficiencies.
Key Points
The trace gas, N2O, is an transport diagnostic
Observations can be used to evaluate model transport
Models with poor transport produce a wide range of ozone predictions</abstract><cop>Washington</cop><pub>Blackwell Publishing Ltd</pub><doi>10.1029/2010JD015360</doi><tpages>18</tpages><orcidid>https://orcid.org/0000-0002-5538-0800</orcidid><orcidid>https://orcid.org/0000-0003-2220-383X</orcidid><orcidid>https://orcid.org/0000-0003-3385-0880</orcidid><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 0148-0227 |
ispartof | Journal of Geophysical Research, 2011-09, Vol.116 (D17), p.n/a, Article D17302 |
issn | 0148-0227 2169-897X 2156-2202 2169-8996 |
language | eng |
recordid | cdi_hal_primary_oai_HAL_hal_00621937v1 |
source | Wiley Online Library Journals Frontfile Complete; Wiley Free Content; Wiley-Blackwell AGU Digital Library; Alma/SFX Local Collection |
subjects | Atmospheric and Oceanic Physics Atmospheric chemistry Atmospheric circulation Atmospheric sciences Climate models Climate science Climatology composition Earth Sciences General circulation models Geophysics model evaluation Nitrous oxide Ozone Physics Sciences of the Universe Stratosphere stratospheric transport |
title | Using transport diagnostics to understand chemistry climate model ozone simulations |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-16T23%3A33%3A44IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_hal_p&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Using%20transport%20diagnostics%20to%20understand%20chemistry%20climate%20model%20ozone%20simulations&rft.jtitle=Journal%20of%20Geophysical%20Research&rft.au=Strahan,%20S.%20E.&rft.date=2011-09-09&rft.volume=116&rft.issue=D17&rft.epage=n/a&rft.artnum=D17302&rft.issn=0148-0227&rft.eissn=2156-2202&rft_id=info:doi/10.1029/2010JD015360&rft_dat=%3Cproquest_hal_p%3E2506628081%3C/proquest_hal_p%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=902737017&rft_id=info:pmid/&rfr_iscdi=true |