Defining Radiation Belt Enhancement Events Based on Probability Distributions
We present a methodology to define moderate, strong, and intense space weather events based on probability distributions. We have illustrated this methodology using a long‐duration, uniform data set of 1.8–3.5 MeV electron fluxes from multiple LANL geosynchronous satellite instruments, but a strengt...
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creator | Reeves, Geoffrey D. Vandegriff, Elizabeth M. Niehof, Jonathan T. Morley, Steven K. Cunningham, Gregory S. Henderson, Michael G. Larsen, Brian A. |
description | We present a methodology to define moderate, strong, and intense space weather events based on probability distributions. We have illustrated this methodology using a long‐duration, uniform data set of 1.8–3.5 MeV electron fluxes from multiple LANL geosynchronous satellite instruments, but a strength of this methodology is that it can be applied uniformly to heterogeneous data sets. It allows quantitative comparison of data sets with different energies, units, orbits, and so forth. The methodology identifies a range of times, “events,” using variable flux thresholds to determine average event occurrence in arbitrary 11‐year intervals (“cycles”). We define moderate, strong, and intense events as those that occur 100, 10, and 1 time per cycle and identify the flux thresholds that produce those occurrence frequencies. The methodology does not depend on any ancillary data set (e.g., solar wind or geomagnetic conditions). We show event probabilities using GOES > 2 MeV fluxes and compare them against event probabilities using LANL 1.8–3.5 MeV fluxes. We present some examples of how the methodology picks out moderate, strong, and intense events and how those events are distributed in time: 1989 through 2018, which includes the declining phases of solar cycles 22, 23, and 24. We also provide an illustrative comparison of moderate and strong events identified in the geosynchronous data with Van Allen Probes observations across all L‐shells. We also provide a catalog of start and stop times of moderate, strong, and intense events that can be used for future studies.
Key Points
We present a methodology to identify moderate, strong, and intense space weather events
We illustrate this methodology with radiation belt electron data, but it can be applied to other data sets
We also present an analysis of the events that are identified by this methodology |
doi_str_mv | 10.1029/2020SW002528 |
format | Article |
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Key Points
We present a methodology to identify moderate, strong, and intense space weather events
We illustrate this methodology with radiation belt electron data, but it can be applied to other data sets
We also present an analysis of the events that are identified by this methodology</description><identifier>ISSN: 1542-7390</identifier><identifier>ISSN: 1539-4964</identifier><identifier>EISSN: 1542-7390</identifier><identifier>DOI: 10.1029/2020SW002528</identifier><language>eng</language><publisher>Washington: John Wiley & Sons, Inc</publisher><subject>ASTRONOMY AND ASTROPHYSICS ; Datasets ; Electron density ; Electron flux ; energetic particles ; Geomagnetism ; geosynchronous ; Geosynchronous satellites ; hazards ; Heliospheric and magnetospheric physics ; Methodology ; methods ; Radiation ; Radiation belts ; Satellite instruments ; Satellite-borne instruments ; Satellites ; Solar cycle ; Solar wind ; Space weather ; Thresholds ; Weather</subject><ispartof>Space Weather, 2020-08, Vol.18 (8), p.n/a</ispartof><rights>2020. The Authors.</rights><rights>2020. This article is published under http://creativecommons.org/licenses/by-nc/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c5578-2a9fdac66a6f7724882ed25bedeba6eccbc18893282d858a4301a83e98a307963</citedby><cites>FETCH-LOGICAL-c5578-2a9fdac66a6f7724882ed25bedeba6eccbc18893282d858a4301a83e98a307963</cites><orcidid>0000-0001-6286-5809 ; 0000-0003-4515-0208 ; 0000-0001-8520-0199 ; 0000-0002-7985-8098 ; 0000-0001-8851-0301 ; 0000-0003-4975-9029 ; 0000-0001-8819-4345 ; 0000000279858098 ; 0000000188510301 ; 0000000185200199 ; 0000000345150208 ; 0000000188194345 ; 0000000162865809 ; 0000000349759029</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%2F2020SW002528$$EPDF$$P50$$Gwiley$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1029%2F2020SW002528$$EHTML$$P50$$Gwiley$$Hfree_for_read</linktohtml><link.rule.ids>230,314,776,780,881,1411,11541,27901,27902,45550,45551,46027,46451</link.rule.ids><backlink>$$Uhttps://www.osti.gov/biblio/1650392$$D View this record in Osti.gov$$Hfree_for_read</backlink></links><search><creatorcontrib>Reeves, Geoffrey D.</creatorcontrib><creatorcontrib>Vandegriff, Elizabeth M.</creatorcontrib><creatorcontrib>Niehof, Jonathan T.</creatorcontrib><creatorcontrib>Morley, Steven K.</creatorcontrib><creatorcontrib>Cunningham, Gregory S.</creatorcontrib><creatorcontrib>Henderson, Michael G.</creatorcontrib><creatorcontrib>Larsen, Brian A.</creatorcontrib><creatorcontrib>Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)</creatorcontrib><title>Defining Radiation Belt Enhancement Events Based on Probability Distributions</title><title>Space Weather</title><description>We present a methodology to define moderate, strong, and intense space weather events based on probability distributions. We have illustrated this methodology using a long‐duration, uniform data set of 1.8–3.5 MeV electron fluxes from multiple LANL geosynchronous satellite instruments, but a strength of this methodology is that it can be applied uniformly to heterogeneous data sets. It allows quantitative comparison of data sets with different energies, units, orbits, and so forth. The methodology identifies a range of times, “events,” using variable flux thresholds to determine average event occurrence in arbitrary 11‐year intervals (“cycles”). We define moderate, strong, and intense events as those that occur 100, 10, and 1 time per cycle and identify the flux thresholds that produce those occurrence frequencies. The methodology does not depend on any ancillary data set (e.g., solar wind or geomagnetic conditions). We show event probabilities using GOES > 2 MeV fluxes and compare them against event probabilities using LANL 1.8–3.5 MeV fluxes. We present some examples of how the methodology picks out moderate, strong, and intense events and how those events are distributed in time: 1989 through 2018, which includes the declining phases of solar cycles 22, 23, and 24. We also provide an illustrative comparison of moderate and strong events identified in the geosynchronous data with Van Allen Probes observations across all L‐shells. We also provide a catalog of start and stop times of moderate, strong, and intense events that can be used for future studies.
Key Points
We present a methodology to identify moderate, strong, and intense space weather events
We illustrate this methodology with radiation belt electron data, but it can be applied to other data sets
We also present an analysis of the events that are identified by this methodology</description><subject>ASTRONOMY AND ASTROPHYSICS</subject><subject>Datasets</subject><subject>Electron density</subject><subject>Electron flux</subject><subject>energetic particles</subject><subject>Geomagnetism</subject><subject>geosynchronous</subject><subject>Geosynchronous satellites</subject><subject>hazards</subject><subject>Heliospheric and magnetospheric physics</subject><subject>Methodology</subject><subject>methods</subject><subject>Radiation</subject><subject>Radiation belts</subject><subject>Satellite instruments</subject><subject>Satellite-borne instruments</subject><subject>Satellites</subject><subject>Solar cycle</subject><subject>Solar wind</subject><subject>Space weather</subject><subject>Thresholds</subject><subject>Weather</subject><issn>1542-7390</issn><issn>1539-4964</issn><issn>1542-7390</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>24P</sourceid><sourceid>DOA</sourceid><recordid>eNp90UFPFTEQB_CN0UQEb36AjV590J222_Yo8BASiEY0HJtpdxb6smyx7dO8b29hjeHkpZ1Mfv1nmmmadx077BiYI2DArm8YAwn6RbPXSQErxQ17-ax-3bzJeVONkCD2mqtTGsMc5tv2Gw4BS4hze0xTadfzHc6e7mmu9a965vYYMw1tBV9TdOjCFMquPQ25pOC2jy_zQfNqxCnT27_3fvPjbP395Hx1-eXzxcmny5WXUukVoBkH9H2P_agUCK2BBpCOBnLYk_fOd1obDhoGLTUKzjrUnIxGzpTp-X5zseQOETf2IYV7TDsbMdinRky3FlMJfiJLyLXzqJwwIKgTSDCMYw-oJDmDVLPeL1kxl2CzD4X8nY_zTL7YrpeMG6jow4IeUvy5pVzsJm7TXP9oQXAlmORcVfVxUT7FnBON_0brmH3ckH2-ocph4b_DRLv_Wnt9s4ba1fwP_OqRFg</recordid><startdate>202008</startdate><enddate>202008</enddate><creator>Reeves, Geoffrey D.</creator><creator>Vandegriff, Elizabeth M.</creator><creator>Niehof, Jonathan T.</creator><creator>Morley, Steven K.</creator><creator>Cunningham, Gregory S.</creator><creator>Henderson, Michael G.</creator><creator>Larsen, Brian A.</creator><general>John Wiley & Sons, Inc</general><general>American Geophysical Union</general><general>Wiley</general><scope>24P</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7TG</scope><scope>8FD</scope><scope>H8D</scope><scope>KL.</scope><scope>L7M</scope><scope>OTOTI</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0001-6286-5809</orcidid><orcidid>https://orcid.org/0000-0003-4515-0208</orcidid><orcidid>https://orcid.org/0000-0001-8520-0199</orcidid><orcidid>https://orcid.org/0000-0002-7985-8098</orcidid><orcidid>https://orcid.org/0000-0001-8851-0301</orcidid><orcidid>https://orcid.org/0000-0003-4975-9029</orcidid><orcidid>https://orcid.org/0000-0001-8819-4345</orcidid><orcidid>https://orcid.org/0000000279858098</orcidid><orcidid>https://orcid.org/0000000188510301</orcidid><orcidid>https://orcid.org/0000000185200199</orcidid><orcidid>https://orcid.org/0000000345150208</orcidid><orcidid>https://orcid.org/0000000188194345</orcidid><orcidid>https://orcid.org/0000000162865809</orcidid><orcidid>https://orcid.org/0000000349759029</orcidid></search><sort><creationdate>202008</creationdate><title>Defining Radiation Belt Enhancement Events Based on Probability Distributions</title><author>Reeves, Geoffrey D. ; Vandegriff, Elizabeth M. ; Niehof, Jonathan T. ; Morley, Steven K. ; Cunningham, Gregory S. ; Henderson, Michael G. ; Larsen, Brian A.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c5578-2a9fdac66a6f7724882ed25bedeba6eccbc18893282d858a4301a83e98a307963</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>ASTRONOMY AND ASTROPHYSICS</topic><topic>Datasets</topic><topic>Electron density</topic><topic>Electron flux</topic><topic>energetic particles</topic><topic>Geomagnetism</topic><topic>geosynchronous</topic><topic>Geosynchronous satellites</topic><topic>hazards</topic><topic>Heliospheric and magnetospheric physics</topic><topic>Methodology</topic><topic>methods</topic><topic>Radiation</topic><topic>Radiation belts</topic><topic>Satellite instruments</topic><topic>Satellite-borne instruments</topic><topic>Satellites</topic><topic>Solar cycle</topic><topic>Solar wind</topic><topic>Space weather</topic><topic>Thresholds</topic><topic>Weather</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Reeves, Geoffrey D.</creatorcontrib><creatorcontrib>Vandegriff, Elizabeth M.</creatorcontrib><creatorcontrib>Niehof, Jonathan T.</creatorcontrib><creatorcontrib>Morley, Steven K.</creatorcontrib><creatorcontrib>Cunningham, Gregory S.</creatorcontrib><creatorcontrib>Henderson, Michael G.</creatorcontrib><creatorcontrib>Larsen, Brian A.</creatorcontrib><creatorcontrib>Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)</creatorcontrib><collection>Wiley Online Library Open Access</collection><collection>CrossRef</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><collection>OSTI.GOV</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Space Weather</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Reeves, Geoffrey D.</au><au>Vandegriff, Elizabeth M.</au><au>Niehof, Jonathan T.</au><au>Morley, Steven K.</au><au>Cunningham, Gregory S.</au><au>Henderson, Michael G.</au><au>Larsen, Brian A.</au><aucorp>Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Defining Radiation Belt Enhancement Events Based on Probability Distributions</atitle><jtitle>Space Weather</jtitle><date>2020-08</date><risdate>2020</risdate><volume>18</volume><issue>8</issue><epage>n/a</epage><issn>1542-7390</issn><issn>1539-4964</issn><eissn>1542-7390</eissn><abstract>We present a methodology to define moderate, strong, and intense space weather events based on probability distributions. We have illustrated this methodology using a long‐duration, uniform data set of 1.8–3.5 MeV electron fluxes from multiple LANL geosynchronous satellite instruments, but a strength of this methodology is that it can be applied uniformly to heterogeneous data sets. It allows quantitative comparison of data sets with different energies, units, orbits, and so forth. The methodology identifies a range of times, “events,” using variable flux thresholds to determine average event occurrence in arbitrary 11‐year intervals (“cycles”). We define moderate, strong, and intense events as those that occur 100, 10, and 1 time per cycle and identify the flux thresholds that produce those occurrence frequencies. The methodology does not depend on any ancillary data set (e.g., solar wind or geomagnetic conditions). We show event probabilities using GOES > 2 MeV fluxes and compare them against event probabilities using LANL 1.8–3.5 MeV fluxes. We present some examples of how the methodology picks out moderate, strong, and intense events and how those events are distributed in time: 1989 through 2018, which includes the declining phases of solar cycles 22, 23, and 24. We also provide an illustrative comparison of moderate and strong events identified in the geosynchronous data with Van Allen Probes observations across all L‐shells. We also provide a catalog of start and stop times of moderate, strong, and intense events that can be used for future studies.
Key Points
We present a methodology to identify moderate, strong, and intense space weather events
We illustrate this methodology with radiation belt electron data, but it can be applied to other data sets
We also present an analysis of the events that are identified by this methodology</abstract><cop>Washington</cop><pub>John Wiley & Sons, Inc</pub><doi>10.1029/2020SW002528</doi><tpages>17</tpages><orcidid>https://orcid.org/0000-0001-6286-5809</orcidid><orcidid>https://orcid.org/0000-0003-4515-0208</orcidid><orcidid>https://orcid.org/0000-0001-8520-0199</orcidid><orcidid>https://orcid.org/0000-0002-7985-8098</orcidid><orcidid>https://orcid.org/0000-0001-8851-0301</orcidid><orcidid>https://orcid.org/0000-0003-4975-9029</orcidid><orcidid>https://orcid.org/0000-0001-8819-4345</orcidid><orcidid>https://orcid.org/0000000279858098</orcidid><orcidid>https://orcid.org/0000000188510301</orcidid><orcidid>https://orcid.org/0000000185200199</orcidid><orcidid>https://orcid.org/0000000345150208</orcidid><orcidid>https://orcid.org/0000000188194345</orcidid><orcidid>https://orcid.org/0000000162865809</orcidid><orcidid>https://orcid.org/0000000349759029</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | ASTRONOMY AND ASTROPHYSICS Datasets Electron density Electron flux energetic particles Geomagnetism geosynchronous Geosynchronous satellites hazards Heliospheric and magnetospheric physics Methodology methods Radiation Radiation belts Satellite instruments Satellite-borne instruments Satellites Solar cycle Solar wind Space weather Thresholds Weather |
title | Defining Radiation Belt Enhancement Events Based on Probability Distributions |
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