S. Nitti, J. A. Carter, S. F. Sembay, S. E. Milan, L. Zhao, S. T. Lepri, K. D. Kuntz
{"title":"Can XMM-Newton Be Used to Track Compositional Changes in the Solar Wind?","authors":"S. Nitti, J. A. Carter, S. F. Sembay, S. E. Milan, L. Zhao, S. T. Lepri, K. D. Kuntz","doi":"10.1029/2024JA033323","DOIUrl":null,"url":null,"abstract":"<p>Geocoronal Solar Wind Charge Exchange (SWCX) is the process by which heavy ions from the solar wind undergo charge exchange with neutral hydrogen atoms from the Earth's exosphere, releasing photons at discrete energies characteristic of the solar wind ions. This paper investigates the solar wind types driving geocoronal SWCX. We find that during periods of time-variable SWCX, higher fractions of every ion species are recorded by ACE compared to the averages. Notably, a subset of the slow solar wind characterized by a systematic lower temperature and higher proton flux is surprisingly effective for producing SWCX. Given the degradation of the solar wind composition spectrometer on ACE in 2011, we explore the capabilities of XMM-Newton as an alternative sensor to monitor heavy ion composition in the solar wind. Unlike the distributions of other ion line fluxes analyzed, only OVIII, extracted via spectral analysis of XMM-Newton observations, display patterns similar to the corresponding parent ion abundances from ACE <span></span><math>\n <semantics>\n <mrow>\n <mfenced>\n <mrow>\n <msup>\n <mi>O</mi>\n <mrow>\n <mn>8</mn>\n <mo>+</mo>\n </mrow>\n </msup>\n <mo>/</mo>\n <mi>p</mi>\n </mrow>\n </mfenced>\n </mrow>\n <annotation> $\\left({\\mathrm{O}}^{\\mathrm{8}+}/\\mathrm{p}\\right)$</annotation>\n </semantics></math>. Finally, we employ a Random Forest Classifier model to predict solar wind types based on literature results. When combining proton data with XMM-Newton features, the model performance improves significantly, achieving a macro-averaged F1 score of 0.80 (with a standard deviation of 0.06).</p>","PeriodicalId":15894,"journal":{"name":"Journal of Geophysical Research: Space Physics","volume":"129 12","pages":""},"PeriodicalIF":2.6000,"publicationDate":"2024-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1029/2024JA033323","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Geophysical Research: Space Physics","FirstCategoryId":"89","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1029/2024JA033323","RegionNum":2,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ASTRONOMY & ASTROPHYSICS","Score":null,"Total":0}
引用次数: 0
Abstract
Geocoronal Solar Wind Charge Exchange (SWCX) is the process by which heavy ions from the solar wind undergo charge exchange with neutral hydrogen atoms from the Earth's exosphere, releasing photons at discrete energies characteristic of the solar wind ions. This paper investigates the solar wind types driving geocoronal SWCX. We find that during periods of time-variable SWCX, higher fractions of every ion species are recorded by ACE compared to the averages. Notably, a subset of the slow solar wind characterized by a systematic lower temperature and higher proton flux is surprisingly effective for producing SWCX. Given the degradation of the solar wind composition spectrometer on ACE in 2011, we explore the capabilities of XMM-Newton as an alternative sensor to monitor heavy ion composition in the solar wind. Unlike the distributions of other ion line fluxes analyzed, only OVIII, extracted via spectral analysis of XMM-Newton observations, display patterns similar to the corresponding parent ion abundances from ACE . Finally, we employ a Random Forest Classifier model to predict solar wind types based on literature results. When combining proton data with XMM-Newton features, the model performance improves significantly, achieving a macro-averaged F1 score of 0.80 (with a standard deviation of 0.06).