Refer to PSP 27th Perihelion Campaign page.
CONSENSUS PREDICTION (CSV, PDF table of coordinates)
The predicted footpoints were kindly provided by the PSP 27th Perihelion modeling team.
Date and arrival time of plasma parcel at PSP, consensus carrington longitude (deg), latitude (deg), error in longitude, error in latitude, on-disk position of predicted source in X and Y (arcseconds) at arrival time, date and emission time of plasma parcel at the source, on-disk position of predicted source at time parcel is emitted. Each row is the updated source location each hour.
The consensus is generated by forming a distribution of footpoint predictions from all modelers for each hour period, and attempting to fit a Kent distribution. If the fitting fails, the median in longitude and latitude are quoted. If the fitting is successful, the quoted errors are formed by drawing random samples from the fitted distribution and computing the standard deviation in longitude and latitude of those samples. If the fitting fails, the quoted errors are the standard deviation in the longitude and latitude from the raw distribution of predictions. The full shape of the distribution is described by black contours in the associated plots on this website. More details about the procedure can be found at the following preprint of Badman et al. (2023) "Prediction and Verification of Parker Solar Probe Solar Wind Sources at 13.3Rs"
Please note the carrington coordinates (lon,lat) are valid from the quoted timestamp (in UTC) until the next timestamp. The helioprojective coordinates quoted (HP-Tx, HP-Ty) are computed from the carrington coordinate at the quoted timestamp (e.g. midnight UTC each day) and so are valid instantaneously at this time but will corotate with the Sun until the next quoted timestamp. For a discussion of the subtle difference in emission and arrival time and why both are included please see the slide deck
Individual model prediction tables of coordinates may be found in a Public DropBox. Files in the Public DropBox have three-letter identifiers indicating the associated model (see below).
Three-letter designation for Public DropBox: UCB. Kindly provided by Sam Badman. The model is a simple ballistic propagation from PSP down to the source surface assuming slow wind 360km/s, and then tracing this sub-PSP trajectory through a PFSS model to get footpoints at the photosphere. The source surface height here is 2.5Rs. The PFSS model is generated using various ADAPT maps with GONG and HMI as input, and the model is run using the open source pfsspy package. A more detailed explanation of the model and comparison to PSP E1 results are given here.
Three-letter designation for Public DropBox: PSI. Kindly provided by Pete Riley. For these predictions, PSI is using a combination of modeling approaches, including PFSS solutions, empirically-based polytropic MHD solutions, and a more sophisticated approach that includes the effects of waves and turbulence to heat the corona and the WKB approximation for wave pressures to accelerate the solar wind. Additionally, boundary conditions are derived from both HMI and ADAPT synoptic magnetograms. Together, these allow us to generate a rich set of ensemble realizations from which to make our optimal prediction, as well as pool them with other teams’ forecasts to derive a hyper-ensemble prediction.
Three-letter designation for Public DropBox: wsa. Kindly provided by Shaela Jones. The Wang-Sheeley-Arge (WSA) model is a combined empirical and physics-based model of the corona and solar wind. The coronal portion of the Wang-Sheeley-Arge (WSA) model is comprised of the Potential Field Source Surface (PFSS) and Schatten Current Sheet (SCS) models, where the output of the PFSS model serves as input to the SCS model. The solar wind portion of WSA consists of a simple 1-D kinematic propagation code that takes stream interactions into account in an ad-hoc fashion. It provides predictions of the solar wind speed and interplanetary magnetic field IMF polarity at any specified point in the inner heliosphere. The WSA model can use global maps of the photospheric magnetic flux measurements from a number of sources as its inner boundary condition; here we are using an ensemble of maps from the Air Force Data Assimilative Photospheric Flux Transport (ADAPT) model, based on input GONG magnetograms.
UAH predictions come from the University of Alabama, Huntsville Multiscale Fluid-Kinetic Simulation Suite (MS-FLUKSS, Pogorelov et al. (2014); Pogorelov (2023); Singh et al. (2022)), which can solve the Reynolds-averaged ideal MHD equations for the mixture of thermal and nonthermal solar wind ions coupled with the kinetic Boltzmann equation describing the transport of neutral atoms. An adaptive mesh refinement technique can be employed for efficient high-resolution calculations. The MS-FLUKSS heliospheric MHD model is coupled with the WSA model (Kim et al., 2020), which uses both ADAPT-GONG and ADAPT-HMI input magnetograms, with the PFSS source surface height and the WSA outer boundary at 2.5 and 10 solar radii, respectively. Hence, field line tracing is performed through the MHD domain down to 10 solar radii instantaneously at approximately 1 hour cadence, where the origin of the field line on the photosphere is already known, as described for WSA.
see Prediction and Verification of Parker Solar Probe Solar Wind Sources at 13.3Rs, Badman et al. (2023)
