Improving Solar Wind Forecasting Using Data Assimilation

Data Assimilation (DA) has enabled huge improvements in the skill of terrestrial operational weather forecasting. In this study, we use a variational DA scheme with computationally efficient solar wind model and situ observations from STEREO-A, STEREO-B ACE. This enables solar-wind far Sun, such as at 1 AU, to update improve inner boundary conditions (at 30 radii). way, observational information can be used estimates near-Earth wind, even when are not directly downstream Earth. allows improved initial passed into forecasting models. To effect, employ HUXt produce 27-day forecasts during lifetime (01 November 2007 - September 2014). space, compare accuracy these both non-DA simple corotation observations. We find that root mean-square error (RMSE) for comparable significantly lower than forecasts. However, forecast is shown STEREO-B's latitude offset Earth, which an issue And representation whole domain between Sun Earth improved, will enable CME arrival time speed.