Presentation #301.05 in the session Predicting solar wind properties across the heliosphere with integrated modeling efforts (empirical or first-principles).
We analyze the residual errors for the Wang-Sheeley-Arge (WSA) solar wind speed forecasts as a function of the photospheric magnetic field expansion factor (fp) and the minimum separation angle (d) in the photosphere between the footpoints of open field lines and the nearest coronal hole boundary. We find the map of residual speed errors are systematic when examined as a function of fp and d. We use these residual error maps to apply corrections to the model speeds. We test this correction approach using 3-day lead time speed forecasts for an entire year of observations and model results. In this presentation, we develop empirical formulas that describe the relationships between the solar wind speed and other solar wind, IMF, and geophysical quantities. Plasma properties a solar wind parcel observed near Earth depends on the region of the Sun that emitted it, and how the parcel evolved on its journey to Earth. The slow wind with speeds less than ~450 km/s has more variable plasma properties and associated with coronal streamers and/or the edges of coronal holes. The fast wind emitted from coronal holes is steadier, has a lower density, and has a higher temperature than the slow wind. The large polar coronal holes and their extensions emit wind ranging from 700 to 800 km/s, and smaller equatorial coronal holes emit wind with speeds from 500 to 700 km/s. At a given time a slow wind emitting streamer will align with Earth and then later owing to solar rotation a coronal hole emitting fast wind will align with Earth. The solar wind travels along a radial line from which it was emitted. Therefore, as the fast wind parcels run into slow wind parcels emitted earlier, compression regions are formed with enhanced density, temperature, and field strength. Different types of source regions emit wind with different plasma properties and those properties are altered in systematic ways owing to the interactions between different speed parcels. Therefore, the relationships between the solar wind speed and other solar wind, IMF properties, and geophysical quantities can be combined with the improve WSA speed forecasts to forecast the solar wind temperature, density, field strength, and indices such as Kp.