Mark D. Butala

A Semiempirical Magnetohydrodynamical Model of the Solar Wind

We present a new MHD model for simulating the large-scale structure of the solar corona and solar wind under “steady state” conditions stemming from the Wang-Sheeley-Arge empirical model. The processes of turbulent heating in the solar wind are parameterized using a phenomenological, thermodynamical model with a varied polytropic index. We employ the Bernoulli integral to bridge the asymptotic solar wind speed with the assumed distribution of the polytropic index on the solar surface. We successfully reproduce the mass flux from Sun to Earth, the temperature structure, and the large-scale structure of the magnetic field. We reproduce the solar wind speed bimodal structure in the inner heliosphere. However, the solar wind speed is in a quantitative agreement with observations at 1 AU for solar maximum conditions only. The magnetic field comparison demonstrates that the input magnetogram needs to be multiplied by a scaling factor in order to obtain the correct magnitude at 1 AU.

Detecting ionospheric TEC perturbations caused by natural hazards using a global network of GPS receivers: The Tohoku case study

Recent advances in GPS data processing have demonstrated that ground-based GPS receivers are capable of detecting ionospheric TEC perturbations caused by surface-generated Rayleigh, acoustic and gravity waves. There have been a number of publications discussing TEC perturbations immediately following the M 9.0 Tohoku earthquake in Japan on March 11, 2011. Most investigators have focused on the ionospheric responses up to a few hours following the earthquake and tsunami. In our research, in addition to March 11, 2011 we investigate global ionospheric TEC perturbations a day before and after the event. We also compare indices of geomagnetic activity on all three days with perturbations in TEC, revealing strong geomagnetic storm conditions that are also apparent in processed GEONET TEC observations. In addition to the traveling ionospheric disturbances (TIDs) produced by the earthquake and tsunami, we also detect “regular” TIDs across Japan about 5 hours following the Tohoku event, concluding these are likely due to geomagnetic activity. The variety of observed TEC perturbations are consistent with tsunami-generated gravity waves, auroral activity, regular TIDs and equatorial fluctuations induced by increased geomagnetic activity. We demonstrate our capabilities to monitor TEC fluctuations using JPL’s real-time Global Assimilative Ionospheric Model (GAIM) system. We show that a real-time global TEC monitoring network is able to detect the acoustic and gravity waves generated by the earthquake and tsunami. With additional real-time stations deployed, this new capability has the potential to provide real-time monitoring of TEC perturbations that could potentially serve as a plug-in to enhance existing early warning systems.

CEDAR Electrodynamics Thermosphere Ionosphere (ETI) Challenge for systematic assessment of ionosphere/thermosphere models: NmF2, hmF2, and vertical drift using ground‐based observations

[1] Objective quantification of model performance based on metrics helps us evaluate the current state of space physics modeling capability, address differences among various modeling approaches, and track model improvements over time. The Coupling, Energetics, and Dynamics of Atmospheric Regions (CEDAR) Electrodynamics Thermosphere Ionosphere (ETI) Challenge was initiated in 2009 to assess accuracy of various ionosphere/thermosphere models in reproducing ionosphere and thermosphere parameters. A total of nine events and five physical parameters were selected to compare between model outputs and observations. The nine events included two strong and one moderate geomagnetic storm events from GEM Challenge events and three moderate storms and three quiet periods from the first half of the International Polar Year (IPY) campaign, which lasted for 2 years, from March 2007 to March 2009. The five physical parameters selected were NmF2 and hmF2 from ISRs and LEO satellites such as CHAMP and COSMIC, vertical drifts at Jicamarca, and electron and neutral densities along the track of the CHAMP satellite. For this study, four different metrics and up to 10 models were used. In this paper, we focus on preliminary results of the study using ground-based measurements, which include NmF2 and hmF2 from Incoherent Scatter Radars (ISRs), and vertical drifts at Jicamarca. The results show that the model performance strongly depends on the type of metrics used, and thus no model is ranked top for all used metrics. The analysis further indicates that performance of the model also varies with latitude and geomagnetic activity level.

A Robust Null Space Method for Linear Equality Constrained State Estimation

We present a robust null space method for linear equality constrained state space estimation. Exploiting a degeneracy in the estimator statistics, an orthogonal factorization is used to decompose the problem into stochastic and deterministic components, which are then solved separately. The resulting dimension reduction algorithm has enhanced numerical stability, solves the constrained problem completely, and can reduce computational load by reducing the problem size. The new method addresses deficiencies in commonly used pseudo-observation or projection methods, which either do not solve the constrained problem completely or have unstable numerical implementations, due in part to the degeneracy in the estimator statistics. We present a numerical example demonstrating the effectiveness of the new method compared to other current methods.

Time-dependent reconstruction of nonstationary objects with tomographic or interferometric measurements

In a number of astrophysical applications one tries to determine the two-dimensional or three-dimensional structure of an object from a time series of measurements. While most methods used for reconstruction assume that the object is static, the data are often acquired over a time interval during which the object may change significantly. This problem can be addressed with time-dependent reconstruction methods such as Kalman filtering, which models the temporal evolution of the unknown object as a random walk that may or may not have a deterministic component. Time-dependent reconstructions of a hydrodynamic simulation from its line-integral projections are presented. In these examples standard reconstructions based on the static assumption are poor, while good quality reconstructions are obtained from a regularized Kalman estimate. Implications for various astrophysical applications, including tomography of the solar corona and radio aperture synthesis, are discussed.

Tomographic Imaging of Dynamic Objects With the Ensemble Kalman Filter

We address the image formation of a dynamic object from projections by formulating it as a state estimation problem. The problem is solved with the ensemble Kalman filter (EnKF), a Monte Carlo algorithm that is computationally tractable when the state dimension is large. In this paper, we first rigorously address the convergence of the EnKF. Then, the effectiveness of the EnKF is demonstrated in a numerical experiment where a highly variable object is reconstructed from its projections, an imaging modality not yet explored with the EnKF. The results show that the EnKF can yield estimates of almost equal quality as the optimal Kalman filter but at a fraction of the computational effort. Further experiments explore the rate of convergence of the EnKF, its performance relative to an idealized particle filter, and implications of modeling the system dynamics as a random walk.

The 2013 Chelyabinsk meteor ionospheric impact studied using GPS measurements

On 15 February 2013, the Chelyabinsk meteor event (the largest in size since 1908) provided a unique opportunity to observe ionospheric perturbations associated with the ablation and ionospheric impact of the meteor using GPS measurements. The hypersonic bolide generated powerful shock waves while acoustic perturbations in the atmosphere led to the upward propagation of acoustic and gravity waves into the ionosphere. In our research, we applied two different techniques to detect ionospheric disturbances in dual-frequency global positioning system (GPS) measurements during the meteor impact event. The data were collected from near-field GPS networks in Russia, GPS Earth Observation Network (GEONET) in Japan, and Plate Boundary Observatory (PBO) stations in the coterminous U.S. Using a novel wavelet coherence detection technique, we were able to identify three different wave trains in the measurements collected from the nearest GPS station to the meteor impact site, with frequencies of approximately 4.0–7.8 mHz, 1.0 −2.5 mHz, and 2.7–11 mHz at 03:30 UTC. We estimated the speed and direction of arrival of the total electron content (TEC) disturbances by cross-correlating TEC time series for every pair of stations in several areas of the GEONET and PBO networks. The results may be characterized as three different types of traveling ionospheric disturbances (TIDs). First, the higher-frequency (4.0–7.8 mHz) disturbances were observed around the station ARTU in Arti, Russia (56.43°N, 58.56°E), with an estimated mean propagation speed of about 862 ± 65 m/s (with 95% confidence interval). Another type of TID disturbance related to the wave trains was identified in the lower frequency band (1.0–2.5 mHz), propagating with a mean speed of 362 ± 23 m/s. The lower frequency ionospheric perturbations were observed at distances of 300–1500 km away from Chelyabinsk. The third type of TID wave train was identified using the PBO stations in the relative short-period range of 1.5–6 min (2.7–11 mHz) with a mean propagation speed of 733 ± 36 m/s. The observed short-period ionospheric perturbations in the U.S. region is, to the best of our knowledge, the first observational evidence of the coincident the long-range meteor-generated infrasound signals propagating in the ionosphere.

Intermediate‐scale plasma irregularities in the polar ionosphere inferred from GPS radio occultation

We report intermediate-scale plasma irregularities in the polar ionosphere inferred from high-resolution radio occultation (RO) measurements using GPS (Global Positioning System) to CASSIOPE (CAScade Smallsat and IOnospheric Polar Explorer) satellite radio links. The high inclination of CASSIOPE and the high rate of signal reception by the GPS Attitude, Positioning, and Profiling RO receiver on CASSIOPE enable a high-resolution investigation of the dynamics of the polar ionosphere with unprecedented detail. Intermediate-scale, scintillation-producing irregularities, which correspond to 1 to 40 km scales, were inferred by applying multiscale spectral analysis on the RO phase measurements. Using our multiscale spectral analysis approach and satellite data (Polar Operational Environmental Satellites and Defense Meteorological Satellite Program), we discovered that the irregularity scales and phase scintillations have distinct features in the auroral oval and polar cap. We found that large length scales and more intense phase scintillations are prevalent in the auroral oval compared to the polar cap implying that the irregularity scales and phase scintillation characteristics are a function of the solar wind and magnetospheric forcings.

Asymptotic convergence of the ensemble Kalman filter

This paper formally addresses the asymptotic convergence of the ensemble Kalman filter (EnKF), a state estimation procedure that, when combined with a technique called localization, provides computationally tractable solutions to large-dimensional state estimation problems. The proof presented in this paper shows that the estimates given by the EnKF converge to the optimal estimates given by the Kalman filter (KF) and provides a formal justification for the use of the EnKF in dynamic remote sensing image formation. The implications of the proof are twofold: it shows that the EnKF converges to a well-defined limit and provides a formal argument that the EnKF is in fact a Monte Carlo algorithm that converges to the KF.

Dynamic Tomographic Imaging of the Solar Corona

Three-dimensional (3-D) maps of the electron density and temperature in the solar atmosphere can be tomographically reconstructed from two-dimensional images that are measured by a variety of ground-based and space-based instruments. The electron density and temperature of the solar corona are fundamental parameters for understanding the physical mechanisms that contribute to space weather, or physical phenomena that can, in extreme cases, have adverse effects on Earth and the near-Earth space environment. New signal processing methods are required to take full advantage of the rich and complex suite of observations that are available from the current generation of Sun-observing spacecraft. In particular, this paper provides signal models and corresponding optimal state estimation methods for reconstructing the dynamic 3-D electron density and temperature structures in the solar corona with focus on the many challenges associated with solar tomography.