Forecast improvements from solar wind data assimilation

Lead Research Organisation: University of Reading
Department Name: Meteorology

Abstract

Technological infrastructures, such as power grids and telecommunications networks, are vulnerable to space weather. For space-weather forecasting, increased lead time requires accurate representation of the solar wind conditions in near-Earth space. At present, solar wind forecast models are "free running" without an observational constraints beyond the initial conditions. Data assimilation (DA) is the process of merging model and observational data to ensure an optimal estimate for reality. Numerical Weather Prediction has made huge strides in accurate forecast lead time through the expansion of the observational network and the application of DA. The first solar wind DA experiments have used simple 2-dimensional models to reconstruct solar wind speed. This approach shows great promise for improved forecasting, though a number of outstanding issues remain. A method for incorporating the 3-dimensional structure has been proposed, though has yet to be implemented.

Publications

10 25 50

Studentship Projects

Project Reference Relationship Related To Start End Student Name
NE/S007261/1 01/10/2019 30/09/2027
2439627 Studentship NE/S007261/1 01/10/2020 30/09/2023 Harriet Turner