Matching temporal signatures of solar features to their corresponding solar wind outflows
Diego de Pablos, David M. Long, Christopher J. Owen, Gherardo Valori,, Georgios Nicolaou, Louise K. Harra

TL;DR
This study develops a novel algorithm to link coronal jet activity observed in EUV with corresponding signatures in solar wind measurements, revealing temporal correlations that enhance understanding of solar wind origins.
Contribution
The paper introduces a new method combining signal processing and backmapping to directly compare solar coronal phenomena with in situ solar wind data.
Findings
Identified temporal signatures linking coronal jets to solar wind outflows.
Demonstrated the algorithm's effectiveness with synthetic and real observational data.
Found that solar wind mass flux shows significant correlation with coronal jet activity.
Abstract
The role of small-scale coronal eruptive phenomena in the generation and heating of the solar wind remains an open question. Here, we investigate the role played by coronal jets in forming the solar wind by testing whether temporal variations associated with jetting in EUV intensity can be identified in the outflowing solar wind plasma. This type of comparison is challenging due to inherent differences between remote-sensing observations of the source and in situ observations of the outflowing plasma, as well as travel time and evolution of the solar wind throughout the heliosphere. To overcome these, we propose a novel algorithm combining signal filtering, two-step solar wind ballistic backmapping, window shifting, and Empirical Mode Decomposition. We first validate the method using synthetic data, before applying it to measurements from the Solar Dynamics Observatory, and Wind…
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