An Updated Model Providing Long‐Term Data Sets of Energetic Electron Precipitation, Including Zonal Dependence
In this study 30‐ to 1,000‐keV energetic electron precipitation (EEP) data from low Earth orbiting National Oceanic and Atmospheric Administration and MetOp Polar Orbiting Environmental Satellites were processed in two improved ways, compared to previous studies. First, all noise‐affected data were...
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creator | Kamp, M. Rodger, C. J. Seppälä, A. Clilverd, M. A. Verronen, P. T. |
description | In this study 30‐ to 1,000‐keV energetic electron precipitation (EEP) data from low Earth orbiting National Oceanic and Atmospheric Administration and MetOp Polar Orbiting Environmental Satellites were processed in two improved ways, compared to previous studies. First, all noise‐affected data were more carefully removed, to provide more realistic representations of low fluxes during geomagnetically quiet times. Second, the data were analyzed dependent on magnetic local time (MLT), which is an important factor affecting precipitation flux characteristics. We developed a refined zonally averaged EEP model, and a new model dependent on MLT, which both provide better modeling of low fluxes during quiet times. The models provide the EEP spectrum assuming a power law gradient. Using the geomagnetic index Ap with a time resolution of 1 day, the spectral parameters are provided as functions of the L shell value relative to the plasmapause. Results from the models compare well with EEP observations over the period 1998–2012. Analysis of the MLT‐dependent data finds that during magnetically quiet times, the EEP flux concentrates around local midnight. As disturbance levels increase, the flux increases at all MLT. During disturbed times, the flux is strongest in the dawn sector and weakest in the late afternoon sector. The MLT‐dependent model emulates this behavior. The results of the models can be used to produce ionization rate data sets over any time period for which the geomagnetic Ap index is available (recorded or predicted). This ionization rate data set will enable simulations of EEP impacts on the atmosphere and climate with realistic EEP variability.
Key Points
A previously published model for radiation belt energetic electron precipitation has been updated and improved
The model includes dependences on the following: the geomagnetic index Ap, the L shell level relative to the plasmapause, and magnetic local time
It provides the energy spectrum of 30‐ to 1,000‐keV precipitating electron flux for any period of time where the geomagnetic index Ap is supplied |
doi_str_mv | 10.1029/2017JD028253 |
format | Article |
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Key Points
A previously published model for radiation belt energetic electron precipitation has been updated and improved
The model includes dependences on the following: the geomagnetic index Ap, the L shell level relative to the plasmapause, and magnetic local time
It provides the energy spectrum of 30‐ to 1,000‐keV precipitating electron flux for any period of time where the geomagnetic index Ap is supplied</description><identifier>ISSN: 2169-897X</identifier><identifier>EISSN: 2169-8996</identifier><identifier>DOI: 10.1029/2017JD028253</identifier><language>eng</language><publisher>Washington: Blackwell Publishing Ltd</publisher><subject>Atmospheric models ; Computer simulation ; Data ; Data processing ; Datasets ; Earth ; Earth orbits ; Electron precipitation ; energetic electron precipitation ; energetic particle precipitation ; Fluctuations ; Fluxes ; Geomagnetism ; Geophysics ; Ionization ; magnetic local time ; Modelling ; Plasmapause ; Power law ; Precipitation ; Remote sensing ; Satellites ; solar particle forcing ; Spaceborne remote sensing ; synthesized data set ; Time dependence</subject><ispartof>Journal of geophysical research. Atmospheres, 2018-09, Vol.123 (17), p.9891-9915</ispartof><rights>2018. American Geophysical Union. All Rights Reserved.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4116-1bfd1a4bc6d33b0d4c41edc6d9c5abb926ad7604319483627c583ffe2670b9103</citedby><cites>FETCH-LOGICAL-c4116-1bfd1a4bc6d33b0d4c41edc6d9c5abb926ad7604319483627c583ffe2670b9103</cites><orcidid>0000-0002-3479-9071 ; 0000-0002-7388-1529 ; 0000-0002-5028-8220 ; 0000-0001-6648-7921 ; 0000-0002-6770-2707</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%2F2017JD028253$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1029%2F2017JD028253$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>314,780,784,1417,1433,27924,27925,45574,45575,46409,46833</link.rule.ids></links><search><creatorcontrib>Kamp, M.</creatorcontrib><creatorcontrib>Rodger, C. J.</creatorcontrib><creatorcontrib>Seppälä, A.</creatorcontrib><creatorcontrib>Clilverd, M. A.</creatorcontrib><creatorcontrib>Verronen, P. T.</creatorcontrib><title>An Updated Model Providing Long‐Term Data Sets of Energetic Electron Precipitation, Including Zonal Dependence</title><title>Journal of geophysical research. Atmospheres</title><description>In this study 30‐ to 1,000‐keV energetic electron precipitation (EEP) data from low Earth orbiting National Oceanic and Atmospheric Administration and MetOp Polar Orbiting Environmental Satellites were processed in two improved ways, compared to previous studies. First, all noise‐affected data were more carefully removed, to provide more realistic representations of low fluxes during geomagnetically quiet times. Second, the data were analyzed dependent on magnetic local time (MLT), which is an important factor affecting precipitation flux characteristics. We developed a refined zonally averaged EEP model, and a new model dependent on MLT, which both provide better modeling of low fluxes during quiet times. The models provide the EEP spectrum assuming a power law gradient. Using the geomagnetic index Ap with a time resolution of 1 day, the spectral parameters are provided as functions of the L shell value relative to the plasmapause. Results from the models compare well with EEP observations over the period 1998–2012. Analysis of the MLT‐dependent data finds that during magnetically quiet times, the EEP flux concentrates around local midnight. As disturbance levels increase, the flux increases at all MLT. During disturbed times, the flux is strongest in the dawn sector and weakest in the late afternoon sector. The MLT‐dependent model emulates this behavior. The results of the models can be used to produce ionization rate data sets over any time period for which the geomagnetic Ap index is available (recorded or predicted). This ionization rate data set will enable simulations of EEP impacts on the atmosphere and climate with realistic EEP variability.
Key Points
A previously published model for radiation belt energetic electron precipitation has been updated and improved
The model includes dependences on the following: the geomagnetic index Ap, the L shell level relative to the plasmapause, and magnetic local time
It provides the energy spectrum of 30‐ to 1,000‐keV precipitating electron flux for any period of time where the geomagnetic index Ap is supplied</description><subject>Atmospheric models</subject><subject>Computer simulation</subject><subject>Data</subject><subject>Data processing</subject><subject>Datasets</subject><subject>Earth</subject><subject>Earth orbits</subject><subject>Electron precipitation</subject><subject>energetic electron precipitation</subject><subject>energetic particle precipitation</subject><subject>Fluctuations</subject><subject>Fluxes</subject><subject>Geomagnetism</subject><subject>Geophysics</subject><subject>Ionization</subject><subject>magnetic local time</subject><subject>Modelling</subject><subject>Plasmapause</subject><subject>Power law</subject><subject>Precipitation</subject><subject>Remote sensing</subject><subject>Satellites</subject><subject>solar particle forcing</subject><subject>Spaceborne remote sensing</subject><subject>synthesized data set</subject><subject>Time dependence</subject><issn>2169-897X</issn><issn>2169-8996</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><recordid>eNp9kM9Kw0AQxhdRsFRvPsCC10b3XzbJsTS1tlQUbUG8hM3upKSku3GTKr35CD6jT2K0Ip6cy8w3_OZj-BA6o-SCEpZcMkKjWUpYzEJ-gHqMyiSIk0Qe_s7R4zE6bZo16SomXISih-qhxcvaqBYMvnEGKnzn3UtpSrvCc2dXH2_vC_AbnKpW4QdoG-wKPLbgV9CWGo8r0K13trsCXdZlq9rS2QGeWl1tv02enFUVTqEGa8BqOEFHhaoaOP3pfbS8Gi9G18H8djIdDeeBFpTKgOaFoUrkWhrOc2JEtwbTqUSHKs8TJpWJJBGcJiLmkkU6jHlRAJMRyRNKeB-d731r75630LTZ2m1990uTMUoZYxFlvKMGe0p71zQeiqz25Ub5XUZJ9hVr9jfWDud7_LWsYPcvm80m92koYin5J8QTeWg</recordid><startdate>20180916</startdate><enddate>20180916</enddate><creator>Kamp, M.</creator><creator>Rodger, C. J.</creator><creator>Seppälä, A.</creator><creator>Clilverd, M. A.</creator><creator>Verronen, P. T.</creator><general>Blackwell Publishing Ltd</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7TG</scope><scope>7UA</scope><scope>8FD</scope><scope>C1K</scope><scope>F1W</scope><scope>FR3</scope><scope>H8D</scope><scope>H96</scope><scope>KL.</scope><scope>KR7</scope><scope>L.G</scope><scope>L7M</scope><orcidid>https://orcid.org/0000-0002-3479-9071</orcidid><orcidid>https://orcid.org/0000-0002-7388-1529</orcidid><orcidid>https://orcid.org/0000-0002-5028-8220</orcidid><orcidid>https://orcid.org/0000-0001-6648-7921</orcidid><orcidid>https://orcid.org/0000-0002-6770-2707</orcidid></search><sort><creationdate>20180916</creationdate><title>An Updated Model Providing Long‐Term Data Sets of Energetic Electron Precipitation, Including Zonal Dependence</title><author>Kamp, M. ; Rodger, C. J. ; Seppälä, A. ; Clilverd, M. A. ; Verronen, P. T.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4116-1bfd1a4bc6d33b0d4c41edc6d9c5abb926ad7604319483627c583ffe2670b9103</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Atmospheric models</topic><topic>Computer simulation</topic><topic>Data</topic><topic>Data processing</topic><topic>Datasets</topic><topic>Earth</topic><topic>Earth orbits</topic><topic>Electron precipitation</topic><topic>energetic electron precipitation</topic><topic>energetic particle precipitation</topic><topic>Fluctuations</topic><topic>Fluxes</topic><topic>Geomagnetism</topic><topic>Geophysics</topic><topic>Ionization</topic><topic>magnetic local time</topic><topic>Modelling</topic><topic>Plasmapause</topic><topic>Power law</topic><topic>Precipitation</topic><topic>Remote sensing</topic><topic>Satellites</topic><topic>solar particle forcing</topic><topic>Spaceborne remote sensing</topic><topic>synthesized data set</topic><topic>Time dependence</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Kamp, M.</creatorcontrib><creatorcontrib>Rodger, C. J.</creatorcontrib><creatorcontrib>Seppälä, A.</creatorcontrib><creatorcontrib>Clilverd, M. A.</creatorcontrib><creatorcontrib>Verronen, P. 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Atmospheres</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Kamp, M.</au><au>Rodger, C. J.</au><au>Seppälä, A.</au><au>Clilverd, M. A.</au><au>Verronen, P. T.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>An Updated Model Providing Long‐Term Data Sets of Energetic Electron Precipitation, Including Zonal Dependence</atitle><jtitle>Journal of geophysical research. Atmospheres</jtitle><date>2018-09-16</date><risdate>2018</risdate><volume>123</volume><issue>17</issue><spage>9891</spage><epage>9915</epage><pages>9891-9915</pages><issn>2169-897X</issn><eissn>2169-8996</eissn><abstract>In this study 30‐ to 1,000‐keV energetic electron precipitation (EEP) data from low Earth orbiting National Oceanic and Atmospheric Administration and MetOp Polar Orbiting Environmental Satellites were processed in two improved ways, compared to previous studies. First, all noise‐affected data were more carefully removed, to provide more realistic representations of low fluxes during geomagnetically quiet times. Second, the data were analyzed dependent on magnetic local time (MLT), which is an important factor affecting precipitation flux characteristics. We developed a refined zonally averaged EEP model, and a new model dependent on MLT, which both provide better modeling of low fluxes during quiet times. The models provide the EEP spectrum assuming a power law gradient. Using the geomagnetic index Ap with a time resolution of 1 day, the spectral parameters are provided as functions of the L shell value relative to the plasmapause. Results from the models compare well with EEP observations over the period 1998–2012. Analysis of the MLT‐dependent data finds that during magnetically quiet times, the EEP flux concentrates around local midnight. As disturbance levels increase, the flux increases at all MLT. During disturbed times, the flux is strongest in the dawn sector and weakest in the late afternoon sector. The MLT‐dependent model emulates this behavior. The results of the models can be used to produce ionization rate data sets over any time period for which the geomagnetic Ap index is available (recorded or predicted). This ionization rate data set will enable simulations of EEP impacts on the atmosphere and climate with realistic EEP variability.
Key Points
A previously published model for radiation belt energetic electron precipitation has been updated and improved
The model includes dependences on the following: the geomagnetic index Ap, the L shell level relative to the plasmapause, and magnetic local time
It provides the energy spectrum of 30‐ to 1,000‐keV precipitating electron flux for any period of time where the geomagnetic index Ap is supplied</abstract><cop>Washington</cop><pub>Blackwell Publishing Ltd</pub><doi>10.1029/2017JD028253</doi><tpages>25</tpages><orcidid>https://orcid.org/0000-0002-3479-9071</orcidid><orcidid>https://orcid.org/0000-0002-7388-1529</orcidid><orcidid>https://orcid.org/0000-0002-5028-8220</orcidid><orcidid>https://orcid.org/0000-0001-6648-7921</orcidid><orcidid>https://orcid.org/0000-0002-6770-2707</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Atmospheric models Computer simulation Data Data processing Datasets Earth Earth orbits Electron precipitation energetic electron precipitation energetic particle precipitation Fluctuations Fluxes Geomagnetism Geophysics Ionization magnetic local time Modelling Plasmapause Power law Precipitation Remote sensing Satellites solar particle forcing Spaceborne remote sensing synthesized data set Time dependence |
title | An Updated Model Providing Long‐Term Data Sets of Energetic Electron Precipitation, Including Zonal Dependence |
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