arXiv subjects

Rungployphan Kieokaew

Publications and source records attributed to Rungployphan Kieokaew.

7 recordsLinked to original sources

arXiv2026

Direct Measurement of Polar Coronal Hole-like Solar Wind in its Acceleration Phase

The early evolution of fast polar coronal hole (PCH) solar wind remains largely unconstrained by in situ measurements. In March 2025, Parker Solar Probe (Parker) at its closest approach of 9.86 Solar Radii ($R_\odot$) measured outflow from a large equatorial coronal hole (ECH) which was also measured at 1\,au and at intermediate distances by Solar Orbiter (also near its perihelion). At 1\,au the stream properties are consistent with PCH properties established by Ulysses. The stream was measured by Parker substantially below the Alfvén surface, with proton temperatures in excess of 2\,MK and a speed at $\sim$10\,$R_\odot$ which was only $\sim$60\% of its asymptotic value. The Solar Orbiter data indicates that the acceleration is largely complete by 60~$R_{\odot}$. Spherically-polarized fluctuations in the stream are observed to develop from near-transverse and small-angle at Parker to full reversal ``switchbacks'' at Solar Orbiter. Comparison of the implied acceleration profile to historical doppler-dimming measurements suggests that the stream's low coronal acceleration is similar to that of PCH flows. Consistent with previous work, this acceleration requires significantly more energy than can be provided by the observed thermal pressure gradients, with a significant contribution likely from the abundant Alfvénic fluctuation energy observed at Parker. These observations provide unique constraints on models of the radial evolution of the fastest solar wind, and indicate that these wind streams experience gradual, steady acceleration over their first few tens of solar radii of evolution.

astro-ph.SR↗

arXiv2026

Forecasting megaelectron-volt electron flux in the Earth's outer radiation belt using supervised machine learning algorithms and a timeseries foundation model

Accurate forecasting of megaelectron-volt (MeV) electrons in the outer Earth's radiation belt, which can pose significant risks to satellites, is essential for risk mitigation and spacecraft operations. We develop a machine-learning-based pipeline for forecasting 1-MeV electron flux variations, focusing first on a 6-hour forecast horizon. Using precipitating electrons measured by POES NOAA-15, near 1-MeV electron flux measured by GOES, solar wind measurements near L1, and geomagnetic activity indices as inputs in 2013-2023, we train algorithms including linear regression, 1-D convolutional and long short-term memory neural networks, and Transformer-Encoder to forecast 1-MeV electron flux in McIlwain's L-shells between 2.8 and 6.0 with 0.1 bin resolution. Particularly, we exploit the timeseries foundation model TimesFM for (1) a zero-shot prediction and (2) a hybrid application involving the ridge regression on the past dynamic covariates combined with the TimesFM inference on the residuals. Using data from January-June 2024 as an out-of-sample test, we find that the hybrid application of TimesFM, named TimesFM+Cov, yields the best results with an average R2 of 0.9 across L-shells, compared to an average R2 under 0.78 for all other models. The R2 of TimesFM+Cov remains above 0.9 for L-shells between 2.8 and 4.7 and drops to 0.77 at L=6.0, indicating improvements of 12% at the lowest L-shell and 48% at the highest L-shell compared to our second-best models. Our work offers an alternative perspective on how a pretrained foundation model could be adapted for space weather forecasting.

astro-ph.IM↗

arXiv2025

A Tale of Two Shocks

Energetic particles in interplanetary space are normally measured at time scales that are long compared to the ion gyroperiod. Such observations by necessity average out the microphysics associated with the acceleration and transport of 10s - 100s keV particles. We investigate previously unseen non-equilibrium features that only become observable at very high time resolution, and discuss possible explanations of these features. We use unprecedentedly high-time-resolution data that were acquired by the in situ instruments on Solar Orbiter in the vicinity of two interplanetary shocks observed on 2023-11-29 07:51:17 UTC and 2023-11-30 10:47:26 UTC at $\sim 0.83$ astronomical units from the Sun. The solar-wind proton beam population follows the magnetic field instantaneously, on time scales which are significantly shorter than a gyro-period. Energetic particles, despite sampling large volumes of space, vary on remarkably short time scales, typically on the order of the convection time of their gyro-radius. Non-equilibrium features such as bump-on-tail distributions of energetic particles are formed by small-scale magnetic structures in the IMF. High-time-resolution observations show previously unobserved microphysics in the vicinity of two traveling interplanetary shocks, including ion reflection at a current sheet, which may explain where ions are reflected in shock acceleration.

astro-ph.SR↗

arXiv2024

A novel neural network-based approach to derive a geomagnetic baseline for robust characterization of geomagnetic indices at mid-latitude

Geomagnetic indices derived from ground magnetic measurements characterize the intensity of solar-terrestrial interaction. The \textit{Kp} index derived from multiple magnetic observatories at mid-latitude has commonly been used for space weather operations. Yet, its temporal cadence is low and its intensity scale is crude. To derive a new generation of geomagnetic indices, it is desirable to establish a geomagnetic `baseline' that defines the quiet-level of activity without solar-driven perturbations. We present a new approach for deriving a baseline that represents the time-dependent quiet variations focusing on data from Chambon-la-Forêt, France. Using a filtering technique, the measurements are first decomposed into the above-diurnal variation and the sum of 24h, 12h, 8h, and 6h filters, called the daily variation. Using correlation tools and SHapley Additive exPlanations, we identify parameters that dominantly correlate with the daily variation. Here, we predict the daily `quiet' variation using a long short-term memory neural network trained using at least 11 years of data at 1h cadence. This predicted daily quiet variation is combined with linear extrapolation of the secular trend associated with the intrinsic geomagnetic variability, which dominates the above-diurnal variation, to yield a new geomagnetic baseline. Unlike the existing baselines, our baseline is insensitive to geomagnetic storms. It is thus suitable for defining geomagnetic indices that accurately reflect the intensity of solar-driven perturbations. Our methodology is quick to implement and scalable, making it suitable for real-time operation. Strategies for operational forecasting of our geomagnetic baseline 1 day and 27 days in advance are presented.

physics.space-ph↗

arXiv2023

Scale and Time Dependence of Alfvénicity in the Solar Wind as Observed by {\it Parker Solar Probe}

Alfvénicity is a well-known property, common in the solar wind, characterized by a high correlation between magnetic and velocity fluctuations. Data from the Parker Solar Probe (PSP) enable the study of this property closer to the Sun than ever before, as well as in sub-Alfvénic solar wind. We consider scale-dependent measures of Alfvénicity based on second-order functions of the magnetic and velocity increments as a function of time lag, including the normalized cross-helicity $σ_c$ and residual energy $σ_r$. Scale-dependent Alfvénicity is strongest for lags near the correlation scale and increases when moving closer to the Sun. We find that $σ_r$ typically remains close to the maximally negative value compatible with $σ_c$. We did not observe significant changes in measures of Alfvénicity between sub-Alfvénic and super-Alfvénic wind. During most times, the solar wind was highly Alfvénic; however, lower Alfvénicity was observed when PSP approached the heliospheric current sheet or other magnetic structures with sudden changes in the radial magnetic field, non-unidirectional strahl electron pitch angle distributions, and strong electron density contrasts. These results are consistent with a picture in which Alfvénic fluctuations generated near the photosphere transport outward forming highly Alfvénic states in the young solar wind and subsequent interactions with large scale structures and gradients leads to weaker Alfvénicity, as commonly observed at larger heliocentric distances.

astro-ph.SR↗

arXiv2022

The Dynamic Time Warping as a Means to Assess Solar Wind Time Series

During the last decades, international attempts have been made to develop realistic space weather prediction tools aiming to forecast the conditions on the Sun and in the interplanetary environment. These efforts have led to the development of appropriate metrics in order to assess the performance of those tools. Metrics are necessary to validate models, compare different models and monitor improvements of a certain model over time. In this work, we introduce the Dynamic Time Warping (DTW) as an alternative way to evaluate the performance of models and, in particular, to quantify differences between observed and modeled solar wind time series. We present the advantages and drawbacks of this method as well as applications to WIND observations and EUHFORIA predictions at Earth. We show that DTW can warp sequences in time, aiming to align them with the minimum cost by using dynamic programming. It can be applied in two ways for the evaluation of modeled solar wind time series. The first, calculates the sequence similarity factor (SSF), a number that provides a quantification of how good the forecast is, compared to an ideal and a non-ideal prediction scenarios. The second way quantifies the time and amplitude differences between the points that are best matched between the two sequences. As a result, DTW can serve as a hybrid metric between continuous measurements (e.g., the correlation coefficient), and point-by-point comparisons. It is a promising technique for the assessment of solar wind profiles providing at once the most complete evaluation portrait of a model.

astro-ph.SR↗

arXiv2018

The Reduction of Magnetic Reconnection Outflow Jets to Sub-Alfvénic Speeds

The outflow velocity of jets produced by collisionless magnetic reconnection is shown to be reduced by the ion exhaust temperature in simulations and observations. We derive a scaling relationship for the outflow velocity based on the upstream Alfvén speed and the parallel ion exhaust temperature, which is verified in kinetic simulations and observations. The outflow speed reduction is shown to be due to the firehose instability criterion, and so for large enough guide fields this effect is suppressed and the outflow speed reaches the upstream Alfvén speed based on the reconnecting component of the magnetic field.

physics.plasm-ph↗