On the representation error in data assimilation
Representation, representativity, representativeness error, forward interpolation error, forward model error, observation‐operator error, aggregation error and sampling error are all terms used to refer to components of observation error in the context of data assimilation. This article is an attemp...
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| Veröffentlicht in: | Quarterly journal of the Royal Meteorological Society 2018-04, Vol.144 (713), p.1257-1278 |
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| creator | Janjić, T. Bormann, N. Bocquet, M. Carton, J. A Cohn, S. E. Dance, S. L. Losa, S. N. Nichols, N. K. Potthast, R. Waller, J. A. Weston, P. |
| description | Representation, representativity, representativeness error, forward interpolation error, forward model error, observation‐operator error, aggregation error and sampling error are all terms used to refer to components of observation error in the context of data assimilation. This article is an attempt to consolidate the terminology that has been used in the earth sciences literature and was suggested at a European Space Agency workshop held in Reading in April 2014. We review the state of the art and, through examples, motivate the terminology. In addition to a theoretical framework, examples from application areas of satellite data assimilation, ocean reanalysis and atmospheric chemistry data assimilation are provided. Diagnosing representation‐error statistics as well as their use in state‐of‐the‐art data assimilation systems is discussed within a consistent framework.
Representation, representativity, representativeness error, forward interpolation error, forward model error, observation‐operator error, aggregation error and sampling error are all terms used to refer to components of observation error in the context of data assimilation. This article is an attempt to consolidate the terminology that has been used in the earth sciences literature and was suggested at a European Space Agency workshop held in Reading in April 2014. We review the state of the art and, through examples, motivate the terminology. |
| doi_str_mv | 10.1002/qj.3130 |
| format | Article |
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Representation, representativity, representativeness error, forward interpolation error, forward model error, observation‐operator error, aggregation error and sampling error are all terms used to refer to components of observation error in the context of data assimilation. This article is an attempt to consolidate the terminology that has been used in the earth sciences literature and was suggested at a European Space Agency workshop held in Reading in April 2014. We review the state of the art and, through examples, motivate the terminology.</description><identifier>ISSN: 0035-9009</identifier><identifier>EISSN: 1477-870X</identifier><identifier>DOI: 10.1002/qj.3130</identifier><language>eng</language><publisher>Chichester, UK: John Wiley & Sons, Ltd</publisher><subject>Aggregation ; aggregation error ; Atmospheric chemistry ; Atmospheric data ; Data ; Data assimilation ; Data collection ; Data processing ; Earth ; Earth sciences ; forward interpolation error ; Frameworks ; Interpolation ; observation error ; observation‐ operator error ; representativeness error ; representativity error ; Sampling error ; Satellite data ; Satellites ; Statistical methods ; Terminology ; Weather forecasting</subject><ispartof>Quarterly journal of the Royal Meteorological Society, 2018-04, Vol.144 (713), p.1257-1278</ispartof><rights>2017 The Authors. published by John Wiley & Sons Ltd on behalf of the Royal Meteorological Society.</rights><rights>2018 Royal Meteorological Society</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3880-a09df60e9dadd9b9f97821ec16460723b575e1bb07f6446f7d1897cf1fa161493</citedby><cites>FETCH-LOGICAL-c3880-a09df60e9dadd9b9f97821ec16460723b575e1bb07f6446f7d1897cf1fa161493</cites><orcidid>0000-0003-1690-3338 ; 0000-0003-2675-0347 ; 0000-0002-7783-6434</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1002%2Fqj.3130$$EPDF$$P50$$Gwiley$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1002%2Fqj.3130$$EHTML$$P50$$Gwiley$$Hfree_for_read</linktohtml><link.rule.ids>314,776,780,1411,27901,27902,45550,45551</link.rule.ids></links><search><creatorcontrib>Janjić, T.</creatorcontrib><creatorcontrib>Bormann, N.</creatorcontrib><creatorcontrib>Bocquet, M.</creatorcontrib><creatorcontrib>Carton, J. A</creatorcontrib><creatorcontrib>Cohn, S. E.</creatorcontrib><creatorcontrib>Dance, S. L.</creatorcontrib><creatorcontrib>Losa, S. N.</creatorcontrib><creatorcontrib>Nichols, N. K.</creatorcontrib><creatorcontrib>Potthast, R.</creatorcontrib><creatorcontrib>Waller, J. A.</creatorcontrib><creatorcontrib>Weston, P.</creatorcontrib><title>On the representation error in data assimilation</title><title>Quarterly journal of the Royal Meteorological Society</title><description>Representation, representativity, representativeness error, forward interpolation error, forward model error, observation‐operator error, aggregation error and sampling error are all terms used to refer to components of observation error in the context of data assimilation. This article is an attempt to consolidate the terminology that has been used in the earth sciences literature and was suggested at a European Space Agency workshop held in Reading in April 2014. We review the state of the art and, through examples, motivate the terminology. In addition to a theoretical framework, examples from application areas of satellite data assimilation, ocean reanalysis and atmospheric chemistry data assimilation are provided. Diagnosing representation‐error statistics as well as their use in state‐of‐the‐art data assimilation systems is discussed within a consistent framework.
Representation, representativity, representativeness error, forward interpolation error, forward model error, observation‐operator error, aggregation error and sampling error are all terms used to refer to components of observation error in the context of data assimilation. This article is an attempt to consolidate the terminology that has been used in the earth sciences literature and was suggested at a European Space Agency workshop held in Reading in April 2014. We review the state of the art and, through examples, motivate the terminology.</description><subject>Aggregation</subject><subject>aggregation error</subject><subject>Atmospheric chemistry</subject><subject>Atmospheric data</subject><subject>Data</subject><subject>Data assimilation</subject><subject>Data collection</subject><subject>Data processing</subject><subject>Earth</subject><subject>Earth sciences</subject><subject>forward interpolation error</subject><subject>Frameworks</subject><subject>Interpolation</subject><subject>observation error</subject><subject>observation‐ operator error</subject><subject>representativeness error</subject><subject>representativity error</subject><subject>Sampling error</subject><subject>Satellite data</subject><subject>Satellites</subject><subject>Statistical methods</subject><subject>Terminology</subject><subject>Weather forecasting</subject><issn>0035-9009</issn><issn>1477-870X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><recordid>eNp10EtLxDAUBeAgCtZR_AsBFy6k471JmzRLGXwyMAgK7kLaJtjS6SPpIPPv7UzdujqL83EvHEKuEZYIwO6HesmRwwmJMJEyziR8nZIIgKexAlDn5CKEGgBSyWREYNPS8dtSb3tvg21HM1ZdS633nadVS0szGmpCqLZVc6wuyZkzTbBXf7kgn0-PH6uXeL15fl09rOOCZxnEBlTpBFhVmrJUuXJKZgxtgSIRIBnPU5lazHOQTiSJcLLETMnCoTMoMFF8QW7mu73vhp0No667nW-nl5ohAhMshXRSt7MqfBeCt073vtoav9cI-jCHHmp9mGOSd7P8qRq7_4_p97ej_gUYLl4i</recordid><startdate>201804</startdate><enddate>201804</enddate><creator>Janjić, T.</creator><creator>Bormann, N.</creator><creator>Bocquet, M.</creator><creator>Carton, J. 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In addition to a theoretical framework, examples from application areas of satellite data assimilation, ocean reanalysis and atmospheric chemistry data assimilation are provided. Diagnosing representation‐error statistics as well as their use in state‐of‐the‐art data assimilation systems is discussed within a consistent framework.
Representation, representativity, representativeness error, forward interpolation error, forward model error, observation‐operator error, aggregation error and sampling error are all terms used to refer to components of observation error in the context of data assimilation. This article is an attempt to consolidate the terminology that has been used in the earth sciences literature and was suggested at a European Space Agency workshop held in Reading in April 2014. We review the state of the art and, through examples, motivate the terminology.</abstract><cop>Chichester, UK</cop><pub>John Wiley & Sons, Ltd</pub><doi>10.1002/qj.3130</doi><tpages>17</tpages><orcidid>https://orcid.org/0000-0003-1690-3338</orcidid><orcidid>https://orcid.org/0000-0003-2675-0347</orcidid><orcidid>https://orcid.org/0000-0002-7783-6434</orcidid><oa>free_for_read</oa></addata></record> |
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| source | Wiley Online Library Journals Frontfile Complete |
| subjects | Aggregation aggregation error Atmospheric chemistry Atmospheric data Data Data assimilation Data collection Data processing Earth Earth sciences forward interpolation error Frameworks Interpolation observation error observation‐ operator error representativeness error representativity error Sampling error Satellite data Satellites Statistical methods Terminology Weather forecasting |
| title | On the representation error in data assimilation |
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