Relative occurrence rates and connection of discrete frequency oscillations in the solar wind density and dayside magnetosphere

[1] We present an analysis of the occurrence distributions of statistically significant apparent frequencies of periodic solar wind number density structures and dayside magnetospheric oscillations in the f = 0.5–5.0 mHz range. Using 11 years (1995–2005) of solar wind data, we identified all spectral peaks that passed both an amplitude test and a harmonic F test at the 95% confidence level in 6-hour data segments. We find that certain discrete frequencies, specifically f = 0.7, 1.4, 2.0, and 4.8 mHz, occur more often than do other frequencies over those 11 years. We repeat the analysis on discrete oscillations observed in 10 years (1996–2005) of dayside magnetospheric data. We find that certain frequencies, specifically f = 1.0, 1.5, 1.9, 2.8, 3.3, and 4.4 mHz, occur more often than do other frequencies over those 10 years. Many of the enhancements found in the magnetospheric occurrence distributions are similar to those found in the solar wind. Lastly, we counted the number of times the same discrete frequencies were identified as statistically significant using our two spectral tests on corresponding solar wind and magnetospheric 6-hour time series. We find that in 54% of the solar wind data segments in which we identified a spectral peak, at least one of the same discrete frequencies was statistically significant in the corresponding magnetospheric data segment. Our results argue for the existence of inherent apparent frequencies in the solar wind number density that directly drive global magnetospheric oscillations at the same discrete frequencies, although the magnetosphere also oscillates through other physical mechanisms

Are periodic solar wind number density structures formed in the solar corona?

[1] We present an analysis of the alpha to proton solar wind abundance ratio (AHe) during a period characterized by significant large size scale density fluctuations, focusing on an event in which the proton and alpha enhancements are anti-correlated. In a recent study using 11 years (1995–2005) of solar wind observations from the Wind spacecraft, N. M. Viall et al. [2008] showed that periodic proton density structures occurred at particular radial length-scales more often than others. The source of these periodic density structures is a significant and outstanding question. Are they generated in the interplanetary medium, or are they a relic of coronal activity as the solar wind was formed? We use AHe to answer this question, as solar wind elemental abundance ratios are not expected to change during transit. For this event, the anti-phase nature of the AHe variations strongly suggests that periodic solar wind density structures originate in the solar corona

Inherent length-scales of periodic solar wind number density structures

[1] We present an analysis of the radial length-scales of periodic solar wind number density structures. We converted 11 years (1995–2005) of solar wind number density data into radial length series segments and Fourier analyzed them to identify all spectral peaks with radial wavelengths between 72 (116) and 900 (900) Mm for slow (fast) wind intervals. Our window length for the spectral analysis was 9072 Mm, approximately equivalent to 7 (4) h of data for the slow (fast) solar wind. We required that spectral peaks pass both an amplitude test and a harmonic F-test at the 95% confidence level simultaneously. From the occurrence distributions of these spectral peaks for slow and fast wind, we find that periodic number density structures occur more often at certain radial length-scales than at others, and are consistently observed within each speed range over most of the 11-year interval. For the slow wind, those length-scales are L ∼ 73, 120, 136, and 180 Mm. For the fast wind, those length-scales are L ∼ 187, 270 and 400 Mm. The results argue for the existence of inherent radial length-scales in the solar wind number density

Finding Home After Fallout: The Future of Fukushima\u27s Forests

This long-form journalistic piece is about radioactive forests in Yamakiya, Fukushima Prefecture, Japan, and how locals are dealing with it. Residents of Yamakiya were forced to evacuate their village in April 2011 following an explosion at the Fukushima Daiichi nuclear plant. One Yamakiyan, Hidekatsu Ouchi, stepped into the role of community leader and is the focus of this story. He hopes Yamakiya can use the radiation, rather than condemning it. Ouchi’s devotion to his community is connected to the Japanese concept of furusato, which refers to an individual’s obligation and nostalgia for family, community and place. The story asserts that the forests surrounding the village are just as much furusato as the villages themselves, and it is this connection that drives locals like Ouchi to find ways to deal with the radiation that may not align with science. Research and interviews throughout the story describe how radiation works and its effects on the landscape. Tim Mousseau, a scientist who has been studying radiation and biota in Fukushima and Chernobyl for nearly 20 years, said radiation slows both growth and decay of forest plants. It also causes genetic damage to forest inhabitants. Due to the nature of the radioactive element cesium-137, radiation cycles through forest biota like nutrients, becoming embedded in plants, creatures and detritus. It will take 300 years for the cesium to decay to pre-2011 levels. The area’s local nuclear emergency response manager, Katsushi Miyachi, reveals the government will conduct a test decontamination on a five-acre plot of forest in Yamakiya. Trees will be clear-cut on one half of the plot, and radioactive litter will be removed on both halves. Radiation will be monitored on both portions and in the surrounding areas to determine which method will be most effective. It is unclear how Japanese government will follow up with the results of this test, but Miyachi is determined to decontaminate each hometown mountain. If the test decontamination results align with the science, Fukushima’s forests may have to be entirely clear-cut to save the landscape, or the forest could suffer from hundreds of years of damaging exposure to radiation

On the standing wave mode of giant pulsations

Both odd-mode and even-mode standing wave structures have been proposed for giant pulsations. Unless a conclusion is drawn on the field-aligned mode structure, little progress can be made in understanding the excitation mechanism of giant pulsations. In order to determine the standing wave mode, we have made a systematic survey of magnetic field data from the AMPTE CCE spacecraft and from ground stations located near the geomagnetic foot point of CCE. We selected time intervals when CCE was close to the magnetic equator and also magnetically close to Syowa and stations in Iceland, and when either transverse or compressional Pc 4 waves were observed at CCE. Magnetograms from the ground stations were then examined to determine if there was a giant pulsation in a given time interval. One giant pulsation was associated with a compressional wave, while no giant pulsation was observed in association with transverse wave events. The CCE magnetic field record for the giant pulsation exhibited a remarkable similarity to a giant pulsation observed from the ATS 6 geostationary satellite near the magnetic equator (Hillebrand et al., 1982). In agreement with Hillebrand et al., we conclude that the compressional nature of the giant pulsation is due to an odd-mode standing wave structure. This conclusion places a strong constraint on the generation mechanism of giant pulsations. In particular, if giant pulsations are excited through the drift bounce resonance of ions with standing Alfvén waves, ω - mωd = ±Nωb, where ω is the wave frequency, m is the azimuthal wave number, ωd is the ion drift frequency,N is an integer, and ωb is the ion bounce frequency, then the resonance must occur at an even N

Revisiting two-step Forbush decreases

Interplanetary coronal mass ejections (ICMEs) and their shocks can sweep out galactic cosmic rays (GCRs), thus creating Forbush decreases (FDs). The traditional model of FDs predicts that an ICME and its shock decrease the GCR intensity in a two-step profile. This model, however, has been the focus of little testing. Thus, our goal is to discover whether a passing ICME and its shock inevitably lead to a two-step FD, as predicted by the model. We use cosmic ray data from 14 neutron monitors and, when possible, high time resolution GCR data from the spacecraft International Gamma Ray Astrophysical Laboratory (INTEGRAL). We analyze 233 ICMEs that should have created two-step FDs. Of these, only 80 created FDs, and only 13 created two-step FDs. FDs are thus less common than predicted by the model. The majority of events indicates that profiles of FDs are more complicated, particularly within the ICME sheath, than predicted by the model. We conclude that the traditional model of FDs as having one or two steps should be discarded. We also conclude that generally ignored small-scale interplanetary magnetic field structure can contribute to the observed variety of FD profiles

Automatic segmentation of magnetic resonance images of the brain

Magnetic resonance imaging (MRI) is a technique used primarily in medical settings to produce high quality images of the human body’s internal anatomy. Each image is of a thin slice through the body, with the typical distance between slices being a few millimeters. Brain segmentation is the delineation of one or more anatomical structures within images of the brain. It promotes greater understanding of spatial relationships to aid in such tasks as surgical planning and clinical diagnoses, particularly when the segmented outlines from each image slice are displayed together as a surface in three-dimensions. A review of the literature indicates that current brain segmentation methods require a trained human expert to inspect the images and decide appropriate parameters, thresholds, or regions of interest to achieve the proper segmentation. This is a tedious time-consuming task because of the large number of images involved. A truly automatic method is needed to transform brain segmentation into a practical clinical tool. This dissertation describes a novel pattern classification approach to the problem of automatically segmenting magnetic resonance images of the brain. Based on this approach, algorithms were designed and implemented to automatically segment a number of anatomical structures. These algorithms were applied to several standard image data sets of human subjects obtained from the Internet Brain Segmentation Repository (IBSR). The resulting segmentations of the lateral ventricles and the caudate nuclei were compared to reference manual segmentations done by expert radiologists. The Tanimoto similarity coefficient was very good for the lateral ventricles (0.81) and good for the caudate nuclei (0.67)

A quantitative assessment of empirical magnetic field models at geosynchronous orbit during magnetic storms

[1] We evaluate the performance of recent empirical magnetic field models (Tsyganenko, 1996, 2002a, 2002b; Tsyganenko and Sitnov, 2005, hereafter referred to as T96, T02 and TS05, respectively) during magnetic storm times including both pre- and post-storm intervals. The model outputs are compared with GOES observations of the magnetic field at geosynchronous orbit. In the case of a major magnetic storm, the T96 and T02 models predict anomalously strong negative Bz at geostationary orbit on the nightside due to input values exceeding the model limits, whereas a comprehensive magnetic field data survey using GOES does not support that prediction. On the basis of additional comparisons using 52 storm events, we discuss the strengths and limitations of each model. Furthermore, we quantify the performance of individual models at predicting geostationary magnetic fields as a function of local time, Dst, and storm phase. Compared to the earlier models (T96 and T02), the most recent storm-time model (TS05) has the best overall performance across the entire range of local times, storm levels, and storm phases at geostationary orbit. The field residuals between TS05 and GOES are small (≤3 nT) compared to the intrinsic short time-scale magnetic variability of the geostationary environment even during non-storm conditions (∼24 nT). Finally, we demonstrate how field model errors may affect radiation belt studies when estimating electron phase space density

Role of coronal mass ejections in the heliospheric Hale cycle

[1] The 11-year solar cycle variation in the heliospheric magnetic field strength can be explained by the temporary buildup of closed flux released by coronal mass ejections (CMEs). If this explanation is correct, and the total open magnetic flux is conserved, then the interplanetary-CME closed flux must eventually open via reconnection with open flux close to the Sun. In this case each CME will move the reconnected open flux by at least the CME footpoint separation distance. Since the polarity of CME footpoints tends to follow a pattern similar to the Hale cycle of sunspot polarity, repeated CME eruption and subsequent reconnection will naturally result in latitudinal transport of open solar flux. We demonstrate how this process can reverse the coronal and heliospheric fields, and we calculate that the amount of flux involved is sufficient to accomplish the reversal within the 11 years of the solar cycle