Mathew James Owens

In this study we examine how a deep-learning based forecast of local, ground-based geomagnetic field variations trained on solar wind parameters available in real time might be improved by including information contained in an accurate forecast of solar wind conditions. This is accomplished using a long short-term memory (LSTM) model together with magnetic field measurements made at the Rørvik magnetometer station in Mid-Norway. We use Advanced Composition Explorer (ACE) satellite measurements of solar wind and interplanetary magnetic field (IMF) conditions at the first Sun-Earth Lagrange point, and historical lists of coronal mass ejection (CME) impacts at Earth to train and validate the LSTM model. We find that accurate information about the IMF B _z component and solar wind speed are important for obtaining a reasonably accurate ( r ² ≥0.5) forecast of local geomagnetic activity over forecasting horizons beyond ∼3 h. Information about CME arrival time is only important when accompanied by accurate, relatively high-resolution information about IMF B _z . In the absence of the latter, CME arrival time information does not contribute to model performance. This empirical result amounts to a quantitative demonstration of the widely recognized impact of IMF orientation on CME geoeffectiveness. This result also highlights that new innovations, probably in the form of new prediction capabilities of conditions in interplanetary space, will be required to produce accurate forecasts of local geomagnetic disturbances beyond a forecast horizon of 1 h.

Accurate prediction of the ambient solar wind at Earth is a key requirement for space‐weather forecasting but is limited by uncertainties in coronal boundary conditions and, to a lesser extent, heliospheric transport. We present a quantitative assessment of a solar wind forecast that uses near‐Earth in situ solar wind observations to estimate the inner boundary condition for the Heliospheric Upwind eXtrapolation with Time dependence (HUXt) model. In terms of the accuracy at Earth, this method is very similar to 27‐day recurrence forecasting. However, unlike 27‐day recurrence, it produces a solution throughout the heliosphere that can potentially be used to improve CME propagation estimates and forecasting at a range of near‐ecliptic heliospheric locations. To test this forecast method, daily hindcasts are generated over a 15‐year interval spanning 2008–2022. Performance is directly compared with forecasts generated by the standard operational forecast approach, namely Global Oscillations Network Group (GONG) magnetogram‐based estimates using the Wang–Sheeley–Arge (WSA) coronal model. The InSitu‐HUXt hindcasts achieve mean absolute error (MAE) in solar wind speed of 65 km for lead times up to 27 days. WSA‐HUXt hindcasts are most accurate around 4‐day lead time, with an MAE of around 85 km . More diagnostic metrics show that this is partly because InSitu‐HUXt naturally produces a bias‐free prediction, whereas WSA‐HUXt over‐predicts the occurrence of high‐speed streams in the solar wind by around 30%. Thus InSitu‐HUXt provides a valuable independent method to forecast near‐Earth solar wind conditions and can be used even when magnetogram data is unavailable, providing forecast resilience.

We introduce Space-weather Utilities for Research and Forecasting (SURF), a flexible modelling framework for reconstructing and forecasting large-scale solar wind structure. SURF incorporates both the reduced hydrodynamic “HUXt” model and a newly developed one-dimensional, hydrodynamic solver, “hydro.”. The new solver introduces more physically consistent compression effects, while retaining the computational efficiency required for ensemble forecasting, uncertainty quantification, and large parametric studies. SURF-hydro solves the 1D Euler equations in spherical geometry using finite-volume methods with Riemann solvers and second-order spatial reconstruction. It is shown to accurately reproduce an analytical solution to pressure-driven expansion of a uniform spherical solar wind. Using 30 years of near-Earth OMNI observations, we derive empirical relations between speed, density, and temperature at 1 AU and map these back to 0.1 AU to provide non-equilibrium inner-boundary conditions for SURF-hydro (and for use with other solar wind models). This approach produces more realistic solar wind speed, density and temperature values and variability at 1 AU than simulations based on equilibrium thermodynamic relations at 0.1 AU. While magnetic pressure and tension forces are not included, SURF-hydro is also shown to reproduce the key features of coronal mass ejection (CME) expansion and evolution. For one particular example of a structured solar wind, sensitivity tests demonstrate that CME density and temperature at 0.1 AU alter 1 AU transit times and arrival speeds by 15 – 20%, highlighting a potential under-explored source of forecast uncertainty. SURF-hydro therefore provides a computationally efficient bridge between idealised models and full 3D magnetohydrodynamic simulations, enabling systematic investigation of boundary condition assumptions and CME parameter sensitivity for both research and operational space-weather forecasting.

Long-term solar magnetic variability governs the space climate conditions. These variations also modulate the galactic cosmic ray influx reaching Earth and subsequently regulate the production of cosmogenic isotopes in Earth’s atmosphere. By harnessing the multi-millennial records of the abundances of these radio-isotopes stored in natural terrestrial reservoirs, such as tree wood and ice sheets, it is possible to reconstruct past solar magnetic activity predating the telescopic era. However, existing regression-based reconstruction methods using isotope data from time series extracted from the reservoirs are often applied to conditions outside the valid parameter range. This can result in a number of problems, including negative sunspot numbers during low solar activity phases, which correspond to statistically permissible extrapolation artefacts but have no physical meaning. To address this, we developed a Monte-Carlo inversion framework consisting of a sequence of physics-based semi-empirical forward models, supplemented by an Approximate Bayesian Computation-based posterior selection, to infer the most plausible temporal evolution of solar magnetic parameters. Our approach produces physically consistent, uncertainty-quantified reconstructions of annually resolved parameters, including sunspot numbers. We apply the method to two modulation potential datasets, namely geomagnetic record from 1845 – 2020, and an annual ¹⁴ C estimate over the period 971 – 1932. Our new reconstruction method is designed to yield strictly non-negative sunspot numbers and shows close agreement with direct observations within uncertainty during the telescopic era. These results offer valuable insights into long-term solar variability and provide improved constraints for long-term solar dynamo modelling. The annual-scale reconstructions are also directly usable for solar irradiance estimation, terrestrial climate modelling, and studies of long-term Sun-Earth coupling.

Solar wind science and forecasting relies on empirical relations between modeled coronal magnetic‐field structure—particularly flux‐tube expansion and distance to coronal hole boundary—and solar‐wind speed. There is lots of uncertainty in these relations, creating large uncertainties in the inner‐boundary conditions to heliospheric models. This uncertainty could potentially be sampled using ensemble techniques, but current functional forms and numbers of free parameters in empirical relations make this difficult. We present a simplified empirical solar‐wind speed equation that can be readily optimized for different configurations of a Potential Field Source Surface and Schatten Current Sheet (PFSS + SCS) coronal model, in‐lieu of the full Wang–Sheeley–Arge (WSA) equation. Optimization is performed using an 11‐year data set of in situ solar‐wind speed observations, reconstructed at 21.5 rS. We trial several functional forms and explore three linear‐regression techniques, highlighting challenges of fitting empirical relations to noisy data with large class imbalances. To minimize overfitting, we select a regression approach that fits directly to the distributions, rather than time series. Using k‐fold cross validation we find an equation candidate that successfully reproduces the distribution of observed solar‐wind speeds and performs comparably to WSA when coupled with the Heliospheric Upwind eXtrapolation with Time‐dependence (HUXt) model to generate hindcasts at 1AU. The new relation is not intended to replace WSA; the internal complexity remains a key element for WSA. Indeed, the simplified equation produces less variability on average. But this trade‐off is balanced by usability within ensemble frameworks, where now the equation can be easily perturbed to quantify uncertainty in solar‐wind speed.

Context. Constraining the long-term variations in total solar irradiance (TSI) is important for assessing the Sun’s influence on Earth’s climate. Most current irradiance reconstructions suggest only a modest secular increase in TSI between the 1700 and 1986 activity minima (−2 ), while two models suggest substantially larger changes of 2.1–5.9 W m ⁻² . One of these models is the semi-empirical Code for the High spectral ResolutiOn recoNstructiOn of Solar irradiance (CHRONOS), while the other is an independent empirical reconstruction. Although the two models differ substantially in architecture, both use cosmogenic isotope records combined with neutron monitor data to describe the long-term irradiance variability. However, cross-calibrating modulation potential reconstructions from cosmogenic isotopes against neutron monitor data remains highly uncertain. Aims. We reassess the origin and magnitude of the secular trends inferred by the two current TSI reconstructions exhibiting the largest secular variability. Methods. We update both reconstructions using recent heliospheric modulation potential and open solar flux reconstructions based on geomagnetic data and neutron monitor measurements, which provide a more reliable connection between cosmogenic isotope and neutron monitor records. We further apply a more robust smoothing methodology for the long-term series. These allow the secular component of the reconstructions to be extended consistently to the satellite era and for comparison of the resulting TSI reconstructions with direct TSI measurements. Results. We find that both original reconstructions substantially overestimate the secular variability in irradiance. When constrained by direct TSI measurements, CHRONOS yields a TSI increase of about 0.1±0.17 W m ⁻² between the 1700 and 1986 minima, while the second reconstruction returns about 0.2–0.25 W m ⁻² . Our analysis indicates that the previously inferred large secular trends arose primarily from improper linking of cosmogenic isotope and neutron monitor records as well as issues in the adopted smoothing approach. Conclusions. The updated reconstructions presented here point towards a relatively modest secular increase in TSI since the Maunder minimum, likely below 1 W m ⁻² , consistent with the majority of current irradiance models.

The terrestrial production of cosmogenic radionuclides such as 10Be, 14C and 36Cl is triggered by spallation reactions of high-energy particles with atmospheric constituents such as oxygen, nitrogen and argon. After being produced and transported within the atmosphere, these radionuclides are deposited in natural archives, storing, for example, solar information over thousands of years. Therefore, records of 10Be, 14C and 36Cl can be used to reconstruct solar activity back in time. However, to understand the underlying physical processes that dominate production and interpret the observations, numerical modelling is crucial. Here, we shall discuss the dependencies of the numerically derived production rates on a variety of factors that include the effects of the choice of the local interstellar spectrum (LIS), the geomagnetic field and the production cross-sections available in the literature. We show that the investigated factors have modest to significant impacts on the modelled production rates of cosmogenic radionuclides and identify the discrepancies in the available cross-sections as the most crucial factor. This article is part of the Theo Murphy meeting issue ‘Radiocarbon and cosmic radiation events’.

Ions and electrons accelerated to high energies during flares and coronal mass ejections at the Sun may escape the solar atmosphere and, guided by the interplanetary magnetic fields, propagate through space to near-Earth locations. These Solar Energetic Particles (SEPs) can be detected directly by spacecraft instrumentation. The highest energy SEPs may also propagate through the geomagnetic field and precipitate to low atmospheric heights, producing secondary particles including neutrons and protons that trigger the formation of cosmogenic radionuclides. The space weather effects associated with the SEP ion population (for the most part protons) consist principally of radiation risk to aviation, humans in space and spacecraft. This paper focuses on the risks to aviation and astronauts and emphasizes how the parameters of the SEP event, including fluence and spectrum, affect radiation doses. Space weather effects for events that took place in recent decades, for which a large body of measurements and models exist, are discussed. SEP events of extreme magnitudes, such as those extrapolated from radionuclide data from the distant past are then considered and first estimates of the associated radiation at aviation altitudes and in space presented. These are worst-case estimates derived within the assumption that the radionuclide spike was caused by a single SEP event and that the particle spectrum and geomagnetic conditions were the same during all events. This article is part of the Theo Murphy meeting issue ‘Radiocarbon and cosmic radiation events’.

Magnetic switchbacks are large-amplitude fluctuations in the interplanetary magnetic field, and appear frequently in the near-Sun solar wind explored recently by Parker Solar Probe: these new observations have prompted many new studies into their properties and origins. Here, we first review what is known about how switchbacks evolve as they travel away from the Sun: both in terms of their expansion-driven growth and their decay due to various processes like turbulence, reconnection, dispersion, parametric instability, and interaction with interplanetary shocks. We then review the current state of knowledge on how switchbacks impact the physics of the solar wind as a whole: in terms of the turbulent cascade, acceleration and heating of the wind, modification of the open solar flux and scattering of energetic particles. Finally, we suggest future studies to further our understanding of switchback evolution and impacts on the heliosphere.