Quantifying the latitudinal representivity of in situ solar wind observations

Abstract

Advanced space-weather forecasting relies on the ability to accurately predict near-Earth solar wind conditions. For this purpose, physics-based, global numerical models of the solar wind are initialized with photospheric magnetic field and coronagraph observations, but no further observation constraints are imposed between the upper corona and Earth orbit. Data assimilation (DA) of the available in situ solar wind observations into the models could potentially provide additional constraints, improving solar wind reconstructions, and forecasts. However, in order to effectively combine the model and observations, it is necessary to quantify the error introduced by assuming point measurements are representative of the model state. In particular, the range of heliographic latitudes over which in situ solar wind speed measurements are representative is of primary importance, but particularly difficult to assess from observations alone. In this study we use 40+ years of observation-driven solar wind model results to assess two related properties: the latitudinal representivity error introduced by assuming the solar wind speed measured at a given latitude is the same as that at the heliographic equator, and the range of latitudes over which a solar wind measurement should influence the model state, referred to as the observational localisation. These values are quantified for future use in solar wind DA schemes as a function of solar cycle phase, measurement latitude, and error tolerance. In general, we find that in situ solar wind speed measurements near the ecliptic plane at solar minimum are extremely localised, being similar over only 1° or 2° of latitude. In the uniform polar fast wind above approximately 40° latitude at solar minimum, the latitudinal representivity error drops. At solar maximum, the increased variability of the solar wind speed at high latitudes means that the latitudinal representivity error increases at the poles, though becomes greater in the ecliptic, as long as moderate speed errors can be tolerated. The heliospheric magnetic field and solar wind density and temperature show very similar behaviour.

Improving Solar Wind Forecasting Using Data Assimilation

“…The STEREO-B corotation forecasts are seen to be positively correlated, with a gradient of 1.593 kms −1 deg −1 and correlation coefficient of 0.301. This is somewhat expected ([Owens et al, 2020b]) and will be explored in more detail later in the study. (In particular, we note the possibility for aliasing between latitude and longitude separations, as well as with the solar cycle.)…”

Assessment of CESE-HLLD ambient solar wind model results using multipoint observation

“…While these problems can be identified from single-point comparison, the multipoint comparison further confirms that these problems result from the common defects of the near-ecliptic solution. The solution of the ambient solar wind are sensitive to the latitudinal change, especially during the solar minimum (Owens et al, 2020). Some authors exploit this property to generate ensemble forecast to provide the range of uncertainty for the solar wind forecast at the L1 point (Owens & Riley, 2017;Reiss et al, 2019).…”

Improving solar wind forecasts using data assimilation

“…The observation error covariance matrix, R, is also an unknown quantity in solar wind modelling. Properly addressing this is a substantial research topic in its own right [Owens et al, 2020b]. In addition to the measurement uncertainty, y, it also accounts for the uncertainty from the "representativity" error [Janjić et al, 2017], that includes the errors due to approximating a continuous process in discrete space, from representing an observation in the incorrect location, and from representing a single measurement over the (potentially large) volume of a grid-cell (amongst others).…”

“…By comparison, during solar maximum, despite STEREO B reaching a greater latitude offset from ACE, the STEREO B corotation forecast RMSE is uncorrelated with the latitude offset of STEREO B (in fact, the line of best-fit's gradient is −0.013kms −1 deg −1 and is nonsignificantly anti-correlated with latitude). The reason for this almost counter-intuitive result can be explained by looking at the solar wind structure during solar minimum and solar maximum Owens et al [2020b]. During solar minimum, the slow wind band (and heliospheric current sheet) is closely aligned with the heliographic equator (±20 • ), this means that for a relatively small change in latitude, large deviations in solar wind behaviour are observed.…”

“…This means that there are generally smaller gradients of solar wind structure with latitude, hence STEREO B and ACE are more likely to be observing the same solar wind behaviour despite their latitudinal offset. For more details on this phenomena, see Owens et al [2020b].…”