Geospace environment modeling 2008-2009 challenge: Dst index
This paper reports the metrics‐based results of the Dst index part of the 2008–2009 GEM Metrics Challenge. The 2008–2009 GEM Metrics Challenge asked modelers to submit results for four geomagnetic storm events and five different types of observations that can be modeled by statistical, climatologica...
Gespeichert in:
Veröffentlicht in: | Space Weather 2013-04, Vol.11 (4), p.187-205 |
---|---|
Hauptverfasser: | , , , , , , , , , , , , , , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 205 |
---|---|
container_issue | 4 |
container_start_page | 187 |
container_title | Space Weather |
container_volume | 11 |
creator | Rastätter, L. Kuznetsova, M. M. Glocer, A. Welling, D. Meng, X. Raeder, J. Wiltberger, M. Jordanova, V. K. Yu, Y. Zaharia, S. Weigel, R. S. Sazykin, S. Boynton, R. Wei, H. Eccles, V. Horton, W. Mays, M. L. Gannon, J. |
description | This paper reports the metrics‐based results of the Dst index part of the 2008–2009 GEM Metrics Challenge. The 2008–2009 GEM Metrics Challenge asked modelers to submit results for four geomagnetic storm events and five different types of observations that can be modeled by statistical, climatological or physics‐based models of the magnetosphere‐ionosphere system. We present the results of 30 model settings that were run at the Community Coordinated Modeling Center and at the institutions of various modelers for these events. To measure the performance of each of the models against the observations, we use comparisons of 1 hour averaged model data with the Dst index issued by the World Data Center for Geomagnetism, Kyoto, Japan, and direct comparison of 1 minute model data with the 1 minute Dst index calculated by the United States Geological Survey. The latter index can be used to calculate spectral variability of model outputs in comparison to the index. We find that model rankings vary widely by skill score used. None of the models consistently perform best for all events. We find that empirical models perform well in general. Magnetohydrodynamics‐based models of the global magnetosphere with inner magnetosphere physics (ring current model) included and stand‐alone ring current models with properly defined boundary conditions perform well and are able to match or surpass results from empirical models. Unlike in similar studies, the statistical models used in this study found their challenge in the weakest events rather than the strongest events.
Key Points
A large set of models that specify DST have been evaluated
Five skill scores were used to evaluate models
Statistical models perform best but physics-based models can compete |
doi_str_mv | 10.1002/swe.20036 |
format | Article |
fullrecord | <record><control><sourceid>proquest_wiley</sourceid><recordid>TN_cdi_proquest_journals_1638487370</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>3532279091</sourcerecordid><originalsourceid>FETCH-LOGICAL-i2776-c55aa786cccf31bd68b9538f0937b81408e547ac4fd83cb7c9ec45aa1c6e5ec83</originalsourceid><addsrcrecordid>eNpNkFFPwjAUhRujiYg--A-W-Dxo13btjC8GEQ2IiaI8Nl13h8WxwToE_r0VjPHlnvNwvnOTg9AlwR2CcdR1G-hEGNP4CLUIZ1EoaIKP__lTdObc3EcZj1gL3QygckttIIDyy9ZVuYCyCRZVBoUtZ4GvkqE_SWA-dFFAOYPr4M41gS0z2J6jk1wXDi5-tY3e7vuT3kM4eh489m5HoY2EiEPDudZCxsaYnJI0i2WacCpznFCRSsKwBM6ENizPJDWpMAkY5hFiYuBgJG2jq0Pvsq5Wa3CNmlfruvQvFYmpZFJQgX2qe0htbAE7taztQtc7RbD6WUb5ZdR-GfU67e-NJ8IDYV0D2z9C158q9pVcTccD9T4cvwyfJj3F6De0U2Wf</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1638487370</pqid></control><display><type>article</type><title>Geospace environment modeling 2008-2009 challenge: Dst index</title><source>Access via Wiley Online Library</source><source>EZB-FREE-00999 freely available EZB journals</source><creator>Rastätter, L. ; Kuznetsova, M. M. ; Glocer, A. ; Welling, D. ; Meng, X. ; Raeder, J. ; Wiltberger, M. ; Jordanova, V. K. ; Yu, Y. ; Zaharia, S. ; Weigel, R. S. ; Sazykin, S. ; Boynton, R. ; Wei, H. ; Eccles, V. ; Horton, W. ; Mays, M. L. ; Gannon, J.</creator><creatorcontrib>Rastätter, L. ; Kuznetsova, M. M. ; Glocer, A. ; Welling, D. ; Meng, X. ; Raeder, J. ; Wiltberger, M. ; Jordanova, V. K. ; Yu, Y. ; Zaharia, S. ; Weigel, R. S. ; Sazykin, S. ; Boynton, R. ; Wei, H. ; Eccles, V. ; Horton, W. ; Mays, M. L. ; Gannon, J.</creatorcontrib><description>This paper reports the metrics‐based results of the Dst index part of the 2008–2009 GEM Metrics Challenge. The 2008–2009 GEM Metrics Challenge asked modelers to submit results for four geomagnetic storm events and five different types of observations that can be modeled by statistical, climatological or physics‐based models of the magnetosphere‐ionosphere system. We present the results of 30 model settings that were run at the Community Coordinated Modeling Center and at the institutions of various modelers for these events. To measure the performance of each of the models against the observations, we use comparisons of 1 hour averaged model data with the Dst index issued by the World Data Center for Geomagnetism, Kyoto, Japan, and direct comparison of 1 minute model data with the 1 minute Dst index calculated by the United States Geological Survey. The latter index can be used to calculate spectral variability of model outputs in comparison to the index. We find that model rankings vary widely by skill score used. None of the models consistently perform best for all events. We find that empirical models perform well in general. Magnetohydrodynamics‐based models of the global magnetosphere with inner magnetosphere physics (ring current model) included and stand‐alone ring current models with properly defined boundary conditions perform well and are able to match or surpass results from empirical models. Unlike in similar studies, the statistical models used in this study found their challenge in the weakest events rather than the strongest events.
Key Points
A large set of models that specify DST have been evaluated
Five skill scores were used to evaluate models
Statistical models perform best but physics-based models can compete</description><identifier>ISSN: 1542-7390</identifier><identifier>ISSN: 1539-4964</identifier><identifier>EISSN: 1542-7390</identifier><identifier>DOI: 10.1002/swe.20036</identifier><language>eng</language><publisher>Washington: Blackwell Publishing Ltd</publisher><subject>GEM 2008 challenge ; model validation ; Physics</subject><ispartof>Space Weather, 2013-04, Vol.11 (4), p.187-205</ispartof><rights>2013. American Geophysical Union. All Rights Reserved.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fswe.20036$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fswe.20036$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,780,784,1417,27924,27925,45574,45575</link.rule.ids></links><search><creatorcontrib>Rastätter, L.</creatorcontrib><creatorcontrib>Kuznetsova, M. M.</creatorcontrib><creatorcontrib>Glocer, A.</creatorcontrib><creatorcontrib>Welling, D.</creatorcontrib><creatorcontrib>Meng, X.</creatorcontrib><creatorcontrib>Raeder, J.</creatorcontrib><creatorcontrib>Wiltberger, M.</creatorcontrib><creatorcontrib>Jordanova, V. K.</creatorcontrib><creatorcontrib>Yu, Y.</creatorcontrib><creatorcontrib>Zaharia, S.</creatorcontrib><creatorcontrib>Weigel, R. S.</creatorcontrib><creatorcontrib>Sazykin, S.</creatorcontrib><creatorcontrib>Boynton, R.</creatorcontrib><creatorcontrib>Wei, H.</creatorcontrib><creatorcontrib>Eccles, V.</creatorcontrib><creatorcontrib>Horton, W.</creatorcontrib><creatorcontrib>Mays, M. L.</creatorcontrib><creatorcontrib>Gannon, J.</creatorcontrib><title>Geospace environment modeling 2008-2009 challenge: Dst index</title><title>Space Weather</title><addtitle>Space Weather</addtitle><description>This paper reports the metrics‐based results of the Dst index part of the 2008–2009 GEM Metrics Challenge. The 2008–2009 GEM Metrics Challenge asked modelers to submit results for four geomagnetic storm events and five different types of observations that can be modeled by statistical, climatological or physics‐based models of the magnetosphere‐ionosphere system. We present the results of 30 model settings that were run at the Community Coordinated Modeling Center and at the institutions of various modelers for these events. To measure the performance of each of the models against the observations, we use comparisons of 1 hour averaged model data with the Dst index issued by the World Data Center for Geomagnetism, Kyoto, Japan, and direct comparison of 1 minute model data with the 1 minute Dst index calculated by the United States Geological Survey. The latter index can be used to calculate spectral variability of model outputs in comparison to the index. We find that model rankings vary widely by skill score used. None of the models consistently perform best for all events. We find that empirical models perform well in general. Magnetohydrodynamics‐based models of the global magnetosphere with inner magnetosphere physics (ring current model) included and stand‐alone ring current models with properly defined boundary conditions perform well and are able to match or surpass results from empirical models. Unlike in similar studies, the statistical models used in this study found their challenge in the weakest events rather than the strongest events.
Key Points
A large set of models that specify DST have been evaluated
Five skill scores were used to evaluate models
Statistical models perform best but physics-based models can compete</description><subject>GEM 2008 challenge</subject><subject>model validation</subject><subject>Physics</subject><issn>1542-7390</issn><issn>1539-4964</issn><issn>1542-7390</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><recordid>eNpNkFFPwjAUhRujiYg--A-W-Dxo13btjC8GEQ2IiaI8Nl13h8WxwToE_r0VjPHlnvNwvnOTg9AlwR2CcdR1G-hEGNP4CLUIZ1EoaIKP__lTdObc3EcZj1gL3QygckttIIDyy9ZVuYCyCRZVBoUtZ4GvkqE_SWA-dFFAOYPr4M41gS0z2J6jk1wXDi5-tY3e7vuT3kM4eh489m5HoY2EiEPDudZCxsaYnJI0i2WacCpznFCRSsKwBM6ENizPJDWpMAkY5hFiYuBgJG2jq0Pvsq5Wa3CNmlfruvQvFYmpZFJQgX2qe0htbAE7taztQtc7RbD6WUb5ZdR-GfU67e-NJ8IDYV0D2z9C158q9pVcTccD9T4cvwyfJj3F6De0U2Wf</recordid><startdate>201304</startdate><enddate>201304</enddate><creator>Rastätter, L.</creator><creator>Kuznetsova, M. M.</creator><creator>Glocer, A.</creator><creator>Welling, D.</creator><creator>Meng, X.</creator><creator>Raeder, J.</creator><creator>Wiltberger, M.</creator><creator>Jordanova, V. K.</creator><creator>Yu, Y.</creator><creator>Zaharia, S.</creator><creator>Weigel, R. S.</creator><creator>Sazykin, S.</creator><creator>Boynton, R.</creator><creator>Wei, H.</creator><creator>Eccles, V.</creator><creator>Horton, W.</creator><creator>Mays, M. L.</creator><creator>Gannon, J.</creator><general>Blackwell Publishing Ltd</general><general>John Wiley & Sons, Inc</general><scope>BSCLL</scope><scope>7TG</scope><scope>8FD</scope><scope>H8D</scope><scope>KL.</scope><scope>L7M</scope></search><sort><creationdate>201304</creationdate><title>Geospace environment modeling 2008-2009 challenge: Dst index</title><author>Rastätter, L. ; Kuznetsova, M. M. ; Glocer, A. ; Welling, D. ; Meng, X. ; Raeder, J. ; Wiltberger, M. ; Jordanova, V. K. ; Yu, Y. ; Zaharia, S. ; Weigel, R. S. ; Sazykin, S. ; Boynton, R. ; Wei, H. ; Eccles, V. ; Horton, W. ; Mays, M. L. ; Gannon, J.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i2776-c55aa786cccf31bd68b9538f0937b81408e547ac4fd83cb7c9ec45aa1c6e5ec83</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>GEM 2008 challenge</topic><topic>model validation</topic><topic>Physics</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Rastätter, L.</creatorcontrib><creatorcontrib>Kuznetsova, M. M.</creatorcontrib><creatorcontrib>Glocer, A.</creatorcontrib><creatorcontrib>Welling, D.</creatorcontrib><creatorcontrib>Meng, X.</creatorcontrib><creatorcontrib>Raeder, J.</creatorcontrib><creatorcontrib>Wiltberger, M.</creatorcontrib><creatorcontrib>Jordanova, V. K.</creatorcontrib><creatorcontrib>Yu, Y.</creatorcontrib><creatorcontrib>Zaharia, S.</creatorcontrib><creatorcontrib>Weigel, R. S.</creatorcontrib><creatorcontrib>Sazykin, S.</creatorcontrib><creatorcontrib>Boynton, R.</creatorcontrib><creatorcontrib>Wei, H.</creatorcontrib><creatorcontrib>Eccles, V.</creatorcontrib><creatorcontrib>Horton, W.</creatorcontrib><creatorcontrib>Mays, M. L.</creatorcontrib><creatorcontrib>Gannon, J.</creatorcontrib><collection>Istex</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Technology Research Database</collection><collection>Aerospace Database</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>Space Weather</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Rastätter, L.</au><au>Kuznetsova, M. M.</au><au>Glocer, A.</au><au>Welling, D.</au><au>Meng, X.</au><au>Raeder, J.</au><au>Wiltberger, M.</au><au>Jordanova, V. K.</au><au>Yu, Y.</au><au>Zaharia, S.</au><au>Weigel, R. S.</au><au>Sazykin, S.</au><au>Boynton, R.</au><au>Wei, H.</au><au>Eccles, V.</au><au>Horton, W.</au><au>Mays, M. L.</au><au>Gannon, J.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Geospace environment modeling 2008-2009 challenge: Dst index</atitle><jtitle>Space Weather</jtitle><addtitle>Space Weather</addtitle><date>2013-04</date><risdate>2013</risdate><volume>11</volume><issue>4</issue><spage>187</spage><epage>205</epage><pages>187-205</pages><issn>1542-7390</issn><issn>1539-4964</issn><eissn>1542-7390</eissn><abstract>This paper reports the metrics‐based results of the Dst index part of the 2008–2009 GEM Metrics Challenge. The 2008–2009 GEM Metrics Challenge asked modelers to submit results for four geomagnetic storm events and five different types of observations that can be modeled by statistical, climatological or physics‐based models of the magnetosphere‐ionosphere system. We present the results of 30 model settings that were run at the Community Coordinated Modeling Center and at the institutions of various modelers for these events. To measure the performance of each of the models against the observations, we use comparisons of 1 hour averaged model data with the Dst index issued by the World Data Center for Geomagnetism, Kyoto, Japan, and direct comparison of 1 minute model data with the 1 minute Dst index calculated by the United States Geological Survey. The latter index can be used to calculate spectral variability of model outputs in comparison to the index. We find that model rankings vary widely by skill score used. None of the models consistently perform best for all events. We find that empirical models perform well in general. Magnetohydrodynamics‐based models of the global magnetosphere with inner magnetosphere physics (ring current model) included and stand‐alone ring current models with properly defined boundary conditions perform well and are able to match or surpass results from empirical models. Unlike in similar studies, the statistical models used in this study found their challenge in the weakest events rather than the strongest events.
Key Points
A large set of models that specify DST have been evaluated
Five skill scores were used to evaluate models
Statistical models perform best but physics-based models can compete</abstract><cop>Washington</cop><pub>Blackwell Publishing Ltd</pub><doi>10.1002/swe.20036</doi><tpages>19</tpages><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 1542-7390 |
ispartof | Space Weather, 2013-04, Vol.11 (4), p.187-205 |
issn | 1542-7390 1539-4964 1542-7390 |
language | eng |
recordid | cdi_proquest_journals_1638487370 |
source | Access via Wiley Online Library; EZB-FREE-00999 freely available EZB journals |
subjects | GEM 2008 challenge model validation Physics |
title | Geospace environment modeling 2008-2009 challenge: Dst index |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-27T01%3A39%3A21IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_wiley&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Geospace%20environment%20modeling%202008-2009%20challenge:%20Dst%20index&rft.jtitle=Space%20Weather&rft.au=Rast%C3%A4tter,%20L.&rft.date=2013-04&rft.volume=11&rft.issue=4&rft.spage=187&rft.epage=205&rft.pages=187-205&rft.issn=1542-7390&rft.eissn=1542-7390&rft_id=info:doi/10.1002/swe.20036&rft_dat=%3Cproquest_wiley%3E3532279091%3C/proquest_wiley%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1638487370&rft_id=info:pmid/&rfr_iscdi=true |