Extracting Inner‐Heliosphere Solar Wind Speed Information From Heliospheric Imager Observations. Issue 6 (24th June 2019)

• Record Type: Journal Article
• Authors: Barnard, L. A.; Owens, M. J.; Scott, C. J.; Jones, S. R.
• Is Part Of: Space weather. Volume 17:Issue 6(2019)
• Page Start: 925
• Page End: 938
• Publication Date: 2019-06-24
• Subjects: solar wind -- Heliospheric Imaging -- statistics -- heliosphere; Space environment -- Periodicals; 551.509992
• DOI: 10.1029/2019SW002226
• Languages: English
• ISSNs: 1542-7390

Abstract

Abstract: We present evidence that variability in the STEREO‐A Heliospheric Imager (HI) data is correlated with in situ solar wind speed estimates from WIND, STEREO‐A, and STEREO‐B. For 2008–2012, we compute the variability in HI differenced images in a plane‐of‐sky shell between 20 to 22.5 solar radii and, for a range of position angles, compare daily means of HI variability and in situ solar wind speed estimates. We show that the HI variability data and in situ solar wind speeds have similar temporal autocorrelation functions. Carrington rotation periodicities are well documented for in situ solar wind speeds, but, to our knowledge, this is the first time they have been presented in statistics computed from HI images. In situ solar wind speeds from STEREO‐A, STEREO‐B, and WIND are all are correlated with the HI variability, with a lag that varies in a manner consistent with the longitudinal separation of the in situ monitor and the HI instrument. Unlike many approaches to processing HI observations, our method requires no manual feature tracking; it is automated, is quick to compute, and does not suffer the subjective biases associated with manual classifications. These results suggest we could possibly estimate solar wind speeds in the low heliosphere directly from HI observations. This motivates further investigation, as this could be a significant asset to the space weather forecasting community; it might provide an independent observational constraint on heliospheric solar wind forecasts, through, for example, data assimilation. Finally, these results are another argument for the potential utility of including a HI on an operational space weather mission. Plain Language Summary: It would be useful for space weather forecasting to have a good estimate of the solar wind speed near the Sun. This could improve space weather forecasting models, and our knowledge of how the solar wind is formed and varies. However, estimating the solar wind speed near the Sun is difficult to do, with either with spacecraft that measure it directly or with cameras observing the solar atmosphere. We have analyzed variations in images of the solar wind taken by the Heliospheric Imagers on the STEREO‐A spacecraft. We show that these variations are well correlated with solar wind speed measurements taken by in situ spacecraft. Furthermore, we show that these correlations evolve in a way that can be explained by the orbits of the spacecraft, which gives us increased confidence that that this statistical relationship is robust. Therefore, these results might be used to develop a relationship between variability in the Heliospheric Imager data and solar wind speed, which would allow us to estimate the solar wind speed near the Sun routinely. Such a technique would be useful for space weather forecasting and would be a good reason to put a Heliospheric Imager on any future space weather monitoring spacecraft. Key Points: Variability in Heliospheric Imager (HI) data is correlated with in situ solar wind speed data This correlations peaks at lags explained by solar rotation and the heliolongitude separation of the instruments This suggests near‐Sun solar wind speeds could be estimated directly from heliospheric imaging