arXiv subjects

Matthew Lang

Publications and source records attributed to Matthew Lang.

4 recordsLinked to original sources

arXiv2023

Causal Analysis of Influence of the Solar Cycle and Latitudinal Solar-Wind Structure on Corotation Forecasts

Studying solar wind conditions is central to forecasting impact of space weather on Earth. Under the assumption that the structure of this wind is constant in time and corotates with the Sun, solar wind and thereby space weather forecasts have been made quite effectively. Such corotation forecasts are well studied with decades of observations from STEREO and near-Earth spacecrafts. Forecast accuracy depends upon the latitudinal separation (or offset $\Delta \theta$) between source and spacecraft, forecast lead time ($\Delta t$) and the solar cycle via the sunspot number (SSN). The precise dependencies factoring in uncertain- ties however, are a mixture of influences from each of these factors. And for high precision forecasts, it is important to understand what drives the forecast accuracy and its uncertainty. Here we present a causal inference approach based on information theoretic measures to do this. Our framework can compute not only the direct (linear and non-linear) dependencies of the forecast mean absolute error (MAE) on SSN, $\Delta t$ and $\Delta t$, but also how these individual variables combine to enhance or diminish the MAE. We provide an initial assessment of this with potential of aiding data assimilation in the future.

astro-ph.SR↗

arXiv2022

SIR-HUXt -- a particle filter data assimilation scheme for assimilating CME time-elongation profiles

We present the development of SIR-HUXt, the integration of a sequential importance resampling (SIR) data assimilation scheme with the HUXt solar wind model. SIR-HUXt is designed to assimilate the time-elongation profiles of CME fronts in the low heliosphere, such as those typically extracted from heliospheric imager data returned by the STEREO, Parker Solar Probe, and Solar Orbiter missions. We use Observing System Simulation Experiments to explore the performance of SIR-HUXt for a simple synthetic CME scenario of a fully Earth directed CME flowing through a uniform ambient solar wind, where the CME is initialised with the average observed CME speed and width. These experiments are performed for a range of observer locations, from 20 deg to 90 deg behind Earth, spanning the L5 point where ESA's future Vigil space weather monitor will return heliospheric imager data for operational space weather forecasting. We show that SIR-HUXt performs well at constraining the CME speed, and has some success at constraining the CME longitude. The CME width is largely unconstrained by the SIR-HUXt assimilations, and more experiments are required to determine if this is due to this specific CME scenario, or is a general feature of assimilating time-elongation profiles. Rank-histograms suggest that the SIR-HUXt ensembles are well calibrated, with no clear indications of bias or under/over dispersion. Improved constraints on the initial CME speed lead directly to improvements in the CME transit time to Earth and arrival speed. For an observer in the L5 region, SIR-HUXt returned a 69% reduction in the CME transit time uncertainty, and a 63% reduction in the arrival speed uncertainty. This suggests SIR-HUXt has potential to improve the real-world representivity of HUXt simulations, and therefore has potential to reduce the uncertainty of CME arrival time hindcasts and forecasts.

astro-ph.SR↗

arXiv2020

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

physics.space-ph↗

arXiv2018

A variational approach to Data Assimilation in the Solar Wind

Variational Data Assimilation (DA) has enabled huge improvements in the skill of operational weather forecasting. In this study, we use a simple solar-wind propagation model to develop the first solar-wind variational DA scheme. This scheme enables solar-wind observations far from the Sun, such as at 1 AU, to update and improve the inner boundary conditions of the solar wind model (at $30$ solar radii). In this way, observational information can be used to improve estimates of the near-Earth solar wind, even when the observations are not directly downstream of the Earth. Using controlled experiments with synthetic observations we demonstrate this method's potential to improve solar wind forecasts, though the best results are achieved in conjunction with accurate initial estimates of the solar wind. The variational DA scheme is also applied to STEREO in-situ observations using initial solar wind conditions supplied by a coronal model of the observed photospheric magnetic field. We consider the period Oct 2010-Oct 2011, when the STEREO spacecraft were approximately $80^{\circ}$ ahead/behind Earth in its orbit. For 12 of 13 Carrington Rotations, assimilation of STEREO data improves the near-Earth solar wind estimate over the non-assimilated state, with a $18.4\%$ reduction in the root-mean-squared-error. The largest gains are made by the DA during times when the steady-state assumption of the coronal models breaks down. While applying this pure variational approach to complex solar-wind models is technically challenging, we discuss hybrid DA approaches which are simpler to implement and may retain many of the advantages demonstrated here.

physics.space-ph↗