Compiling Magnetosheath Statistical Data Sets Under Specific Solar Wind Conditions: Lessons Learnt From the Dayside Kinetic Southward IMF GEM Challenge

dc.contributor.authorDimmock AP
dc.contributor.authorHietala H
dc.contributor.authorZou Y
dc.contributor.organizationfi=fysiikan ja tähtitieteen laitos|en=Department of Physics and Astronomy|
dc.contributor.organization-code1.2.246.10.2458963.20.55477946762
dc.converis.publication-id48798341
dc.converis.urlhttps://research.utu.fi/converis/portal/Publication/48798341
dc.date.accessioned2022-10-27T12:26:28Z
dc.date.available2022-10-27T12:26:28Z
dc.description.abstractThe Geospace Environmental Modelling (GEM) community offers a framework for collaborations between modelers, observers, and theoreticians in the form of regular challenges. In many cases, these challenges involve model-data comparisons to provide wider context to observations or validate model results. To perform meaningful comparisons, a statistical approach is often adopted, which requires the extraction of a large number of measurements from a specific region. However, in complex regions such as the magnetosheath, compiling these data can be difficult. Here, we provide the statistical context of compiling statistical data for the southward IMF GEM challenge initiated by the "Dayside Kinetic Processes in Global Solar Wind-Magnetosphere Interaction" focus group. It is shown that matching very specific upstream conditions can severely impact the statistical data if limits are imposed on several solar wind parameters. We suggest that future studies that wish to compare simulations and/or single events to statistical data should carefully consider at an early stage the availability of data in context with the upstream criteria. We also demonstrate the importance of how specific IMF conditions are defined, the chosen spacecraft, the region of interest, and how regions are identified automatically. The lessons learnt in this study are of wide context to many future studies as well as GEM challenges. The results also highlight the issue where a global statistical perspective has to be balanced with its relevance to more-extreme, less-frequent individual events, which is typically the case in the field of space weather.
dc.format.pagerange1
dc.format.pagerange13
dc.identifier.eissn2333-5084
dc.identifier.jour-issn2333-5084
dc.identifier.olddbid175512
dc.identifier.oldhandle10024/158606
dc.identifier.urihttps://www.utupub.fi/handle/11111/30835
dc.identifier.urlhttps://agupubs.onlinelibrary.wiley.com/doi/full/10.1029/2020EA001095
dc.identifier.urnURN:NBN:fi-fe2021042823780
dc.language.isoen
dc.okm.affiliatedauthorHietala, Heli
dc.okm.discipline115 Astronomy and space scienceen_GB
dc.okm.discipline115 Avaruustieteet ja tähtitiedefi_FI
dc.okm.internationalcopublicationinternational co-publication
dc.okm.internationalityInternational publication
dc.okm.typeA1 ScientificArticle
dc.publisherAMER GEOPHYSICAL UNION
dc.publisher.countryUnited Statesen_GB
dc.publisher.countryYhdysvallat (USA)fi_FI
dc.publisher.country-codeUS
dc.relation.articlenumberUNSP e2020EA001095
dc.relation.doi10.1029/2020EA001095
dc.relation.ispartofjournalEarth and Space Science
dc.relation.issue6
dc.relation.volume7
dc.source.identifierhttps://www.utupub.fi/handle/10024/158606
dc.titleCompiling Magnetosheath Statistical Data Sets Under Specific Solar Wind Conditions: Lessons Learnt From the Dayside Kinetic Southward IMF GEM Challenge
dc.year.issued2020

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