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At least 649 records · Page 36
All sourcesNASA NTRSDOE OSTI
NASA NTRS1994

DE 1 and Viking observations associated with electron conical distributions

Data from the electron detectors on board the Swedish Viking satellite launched during a period of low solar activity and from the Dynamic Explorer (DE) 1 satellite launched during active solar coditions have been examined for the occurrence and location of electron conical distributions and several conclusions can be drawn. First, we note that most of the best examples of electron conics observed by the V-3 experiment onboard Viking occurred in the afternoon sector in the range of magneitc local time 14 hours less than Magnetic Local Time (MLT) less than 18 hours, at midaltitudes in the range 10,000 km less than h less than 13,500 km, with few occurring in the nightside auroral region, a region poorly sampled at altitudes greater than 5000 km. For the Viking data there is an association of electron conics with upper hybrid waves. DE 1 observations made by the high-altitude plasma instrument (HAPI) indicate that electron conics were observed in the midmorning sector and the late evening sector, and as has been reported earlier, the correlation with upper hybird waves was good. The HAPI did not sample the afternoon sector. The electon conics observed on both satellites occurred in the presence of at least a modest (several kilovolts) potential difference beneath the satellite with a maximum energy that was usually, but not always, equal to or greater than the maximum energy of the electron conics. Two independent sets of observations by DE 1 suggest two distinct production mechanisms for electron conics. Examiniation of DE 1 electric field measurements from the plasma wave instrument during the observation of electron conics show simultaneous parallel oscillations in the frequency range of 0.2 Hz less than f less than 0.5 Hz during one and perhaps two of four events examined, and upper hybrid waves were observed on all four events. In addition, recent observations of '90-deg' electron conics associated with auroral kilometric radiation source regions suggest a perpendicular heating mechanism produced by wave-particle interaction. Such distributions may be observed as electron conics at higher altitudes. These results suggest more than one possible source mechanism may be responsible for electron conics.

Menietti, J. D.↗
NASA NTRS2016

Automated ISS Flight Utilities

During my internship at NASA Johnson Space Center, I worked in the Space Radiation Analysis Group (SRAG), where I was tasked with a number of projects focused on the automation of tasks and activities related to the operation of the International Space Station (ISS). As I worked on a number of projects, I have written short sections below to give a description for each, followed by more general remarks on the internship experience. My first project is titled "General Exposure Representation EVADOSE", also known as "GEnEVADOSE". This project involved the design and development of a C++/ ROOT framework focused on radiation exposure for extravehicular activity (EVA) planning for the ISS. The utility helps mission managers plan EVAs by displaying information on the cumulative radiation doses that crew will receive during an EVA as a function of the egress time and duration of the activity. SRAG uses a utility called EVADOSE, employing a model of the space radiation environment in low Earth orbit to predict these doses, as while outside the ISS the astronauts will have less shielding from charged particles such as electrons and protons. However, EVADOSE output is cumbersome to work with, and prior to GEnEVADOSE, querying data and producing graphs of ISS trajectories and cumulative doses versus egress time required manual work in Microsoft Excel. GEnEVADOSE automates all this work, reading in EVADOSE output file(s) along with a plaintext file input by the user providing input parameters. GEnEVADOSE will output a text file containing all the necessary dosimetry for each proposed EVA egress time, for each specified EVADOSE file. It also plots cumulative dose versus egress time and the ISS trajectory, and displays all of this information in an auto-generated presentation made in LaTeX. New features have also been added, such as best-case scenarios (egress times corresponding to the least dose), interpolated curves for trajectories, and the ability to query any time in the EVADES output. As mentioned above, GEnEVADOSE makes extensive use of ROOT version 6, the data analysis framework developed at the European Organization for Nuclear Research (CERN), and the code is written to the C++11 standard (as are the other projects). My second project is the Automated Mission Reference Exposure Utility (AMREU).Unlike GEnEVADOSE, AMREU is a combination of three frameworks written in both Python and C++, also making use of ROOT (and PyROOT). Run as a combination of daily and weekly cron jobs, these macros query the SRAG database system to determine the active ISS missions, and query minute-by-minute radiation dose information from ISS-TEPC (Tissue Equivalent Proportional Counter), one of the radiation detectors onboard the ISS. Using this information, AMREU creates a corrected data set of daily radiation doses, addressing situations where TEPC may be offline or locked up by correcting doses for days with less than 95% live time (the total amount time the instrument acquires data) by averaging the past 7 days. As not all errors may be automatically detectable, AMREU also allows for manual corrections, checking an updated plaintext file each time it runs. With the corrected data, AMREU generates cumulative dose plots for each mission, and uses a Python script to generate a flight note file (.docx format) containing these plots, as well as information sections to be filled in and modified by the space weather environment officers with information specific to the week. AMREU is set up to run without requiring any user input, and it automatically archives old flight notes and information files for missions that are no longer active. My other projects involve cleaning up a large data set from the Charged Particle Directional Spectrometer (CPDS), joining together many different data sets in order to clean up information in SRAG SQL databases, and developing other automated utilities for displaying information on active solar regions, that may be used by the space weather environment officers to monitor solar activity. I consulted my mentor Dr. Ryan Rios and Dr. Kerry Lee for project requirements and added features, and ROOT developer Edmond Offermann for advice on using the ROOT library. I also received advice and feedback from Dr. Janet Barzilla of SRAG, who tested my code. Besides these inputs, I worked independently, writing all of the code by myself. The code for all these projects is documented throughout, and I have attempted to write it in a modular format. Assuming that ROOT is updated accordingly, these codes are also Y2038-compliant (and Y10K-compliant). This allows the code to be easily referenced, modified and possibly repurposed for non-ISS missions in the future, should the necessary inputs exist. These projects have taught me a lot about coding and software design - I have become a much more skilled C++ programmer and ROOT user, and I also learned to code in Python and PyROOT (and its advantages and disadvantages compared to C++/ ROOT). Furthermore, I have learned about space radiation and radiation modeling, topics that greatly interest me as I pursue a degree in physics. Working alongside experimental physicists like Dr. Rios, I have developed a greater understanding and appreciation for experimental science, something I have always leaned towards but to which I lacked significant exposure. My work in SRAG has also given me the invaluable opportunity to witness the work environment for physicists at NASA, and what a career in academia may look like at a government laboratory such as NASA Johnson Space Center. As I continue my studies and look forward to graduate school and a future career, this experience at NASA has given me a meaningful and enjoyable opportunity to put my skills to use and see what my future career path might hold.

Offermann, Jan Tuzlic↗
NASA NTRS2024

Understanding the Variability of Helium Abundance in the Solar Corona Using Three Fluid Modeling and Ultraviolet Observations

The variability of helium abundance in the solar corona and the solar wind is an important signature of solar activity, solar cycle, and solar wind sources, as well as coronal heating processes. Motivated by recently reported remote-sensing UV imaging observations by Helium Resonance Scattering in the Corona and Heliosphere payload sounding rocket of helium abundance in the inner corona on 2009 September 14 near solar minimum, we present the results of the first three-dimensional three-fluid (electrons, protons, and alpha particles) model of tilted coronal streamer belt and slow solar wind that illustrates the various processes leading to helium abundance differentiation and variability. We find good qualitative agreement between the three-fluid model and the coronal helium abundance variability deduced from UV observations of streamers, providing insight on the effects of the physical processes, such as heating, gravitational settling, and interspecies Coulomb friction in the outflowing solar wind that produce the observed features. The study impacts our understanding of the origins of the slow solar wind.

Leon Ofman↗
NASA NTRS2003

Observed Helicity of Active Regions in Solar Cycle 21

We report the results of a study of helicity in solar active regions during the peak of activity in solar cycle 21 from observations with the Marshall Space Flight Center's solar vector magnetograph. Using the force-free parameter alpha as the proxy for helicity, we calculated an average value of alpha for each of 60 active regions from a total of 449 vector magnetograms that were obtained during the period 1980 March to November. The signs of these average values of alpha were correlated with the latitude of the active regions to test the hemispheric rule of helicity that has been proposed for solar magnetic fields: negative helicity predominant in northern latitudes, positive in the southern ones. We have found that of the 60 regions that were observed, 30 obey the hemispheric rule and 30 do not.

Hagyard, M. J.↗
NASA NTRS1986

Solar-geophysical data number 499, March 1986. Part 1: (Prompt reports). Data for February 1986, January 1986 and late data

Solar-Geophysical Data Number 499, March 1986, Part 1 (Prompt Reports); Data for February 1986, January 1986 and Late Data, contains the following: Detailed index for 1985 to 1986; Data for February 1986--(IUWDS alert periods (Advance and worldwide), Solar activity indices, Solar flares, Solar radio emission, Vostok inferred interplanetary magnetic field polarity, Stanford mean solar magnetic field); data for January 1986--(Solar active regions, Sudden ionospheric disturbances, Solar radio spectral observations, Cosmic ray measurements by neutron monitor, Geomagnetic indices, Radio propagation indices); Late data-(Solar active regions, Solar radio spectral observations Culgoora, Cosmic ray measurements by neutron monitor, Calcium plage data).

Coffey, H. E.↗
NASA NTRS1981

Solar wind control of auroral zone geomagnetic activity

Solar wind magnetosphere energy coupling functions are analyzed using linear prediction filtering with 2.5 minute data. The relationship of auroral zone geomagnetic activity to solar wind power input functions are examined, and a least squares prediction filter, or impulse response function is designed from the data. Computed impulse response functions are observed to have characteristics of a low pass filter with time delay. The AL index is found well related to solar wind energy functions, although the AU index shows a poor relationship. High frequency variations of auroral indices and substorm expansions are not predictable with solar wind information alone, suggesting influence by internal magnetospheric processes. Finally, the epsilon parameter shows a poorer relationship with auroral geomagnetic activity than a power parameter, having a VBs solar wind dependency.

Clauer, C. R.↗
NASA NTRS2003

Observed Helicity of Active Regions in Solar Cycle 21

We report the results of a study of magnetic helicity in solar active regions during solar cycles 21 and 22 from observations with the Marshall Space Flight Center's solar vector magnetograph. Using the force-free parameter a as the proxy for helicity, we calculated an average value of a for each of 91 active regions from a total of 683 vector magnetograms that were obtained during the period March 1980 to July 1993. The signs of these average values of a were correlated with the latitude of the active regions to test the hemispherical rule of helicity that has been proposed for solar magnetic fields: negative helicity predominant in northern latitudes, positive in the southern ones. We have found that of the 65 regions that were observed in cycle 21,49% obey the hemispherical rule and 51% do not. On the other hand, for the 26 regions in cycle 22,65% do exhibit this correlation. In addition, our results seem to support the findings of Hagino and Sakurai (2002) which indicate evidence for a time variability in the hemispheric rule.

Hagyard, M. J.↗
DOE OSTI2021

Measurements of the time-dependent cosmic-ray Sun shadow with seven years of IceCube data: Comparison with the Solar cycle and magnetic field models

Observations of the time-dependent cosmic-ray Sun shadow have been proven as a valuable diagnostic for the assessment of solar magnetic field models. Here, seven years of IceCube data are compared to solar activity and solar magnetic field models. A quantitative comparison of solar magnetic field models with IceCube data on the event rate level is performed for the first time. Additionally, a first energy-dependent analysis is presented and compared to recent predictions. We use seven years of IceCube data for the moon and the Sun and compare them to simulations on data rate level. The simulations are performed for the geometrical shadow hypothesis for the moon and the Sun and for a cosmic-ray propagation model governed by the solar magnetic field for the case of the Sun. We find that a linearly decreasing relationship between Sun shadow strength and solar activity is preferred over a constant relationship at the 6.4σ level. We test two commonly used models of the coronal magnetic field, both combined with a Parker spiral, by modeling cosmic-ray propagation in the solar magnetic field. Both models predict a weakening of the shadow in times of high solar activity as it is also visible in the data. We find tensions with the data on the order of 3σ for both models, assuming only statistical uncertainties. The magnetic field model CSSS fits the data slightly better than the PFSS model. This is generally consistent with what is found previously by the Tibet AS-γ Experiment; a deviation of the data from the two models is, however, not significant at this point. Regarding the energy dependence of the Sun shadow, we find indications that the shadowing effect increases with energy during times of high solar activity, in agreement with theoretical predictions.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1984

Solar-geophysical data number 479, July 1984. Part 1: (Prompt reports). Data for June 1984, May 1984 and later data

Solar and geophysical data for May and June 1984 are reported. Topics include: detailed index for 1983/1984; data for June 1984 (solar activity indices, solar flares, solar radio emission, mean solar magnetic field, boulder geomagnetic substorm log); data for May 1984 (solar active regions, sudden ionospheric disturbances, solar radio spectral observations, cosmic ray measurements by neutron monitor, geomagnetic indices, radio propagation indices); and late data (geomagnetic indices March and April 1984 sudden commencements/solar flare effects, cosmic ray measurements by neutron monitor, and solar active regions).

Coffey, H. E.↗
NASA NTRS1987

Activity associated with the solar origin of coronal mass ejections

Solar coronal mass ejections (CMEs) observed in 1980 with the HAO Coronagraph/Polarimeter on the Solar Maximum Mission (SMM) satellite are compared with other forms of solar activity that might be physically related to the ejections. The solar phenomena checked and the method of association used were intentionally patterned after those of Munro et al.'s (1979) analysis of mass ejections observed with the Skylab coronagraph to facilitate comparison of the two epochs. Comparison of the results reveals that the types and degree of CME associations are similar near solar activity minimum and at maximum. For both epochs, most CMEs with associations had associated eruptive prominences, and the proportions of association of all types of activity were similar. A high percentage of association between SMM CMEs and X-ray long duration events is also found, in agreement with Skylab results. It is concluded that most CMEs are the result of the destabilization and eruption of a prominence and its overlying coronal structure, or of a magnetic structure capable of supporting a prominence.

Webb, D. F.↗
DOE OSTI2012

THREE-DIMENSIONAL EVOLUTION OF SOLAR WIND DURING SOLAR CYCLES 22-24

This paper presents an analysis of three-dimensional evolution of solar wind density turbulence and speed at various levels of solar activity between solar cycles 22 and 24. The solar wind data used in this study have been obtained from the interplanetary scintillation (IPS) measurements made at the Ooty Radio Telescope, operating at 327 MHz. Results show that (1) on average, there was a downward trend in density turbulence from the maximum of cycle 22 to the deep minimum phase of cycle 23; (2) the scattering diameter of the corona around the Sun shrunk steadily toward the Sun, starting from 2003 to the smallest size at the deepest minimum, and it corresponded to a reduction of {approx}50% in the density turbulence between the maximum and minimum phases of cycle 23; (3) the latitudinal distribution of the solar wind speed was significantly different between the minima of cycles 22 and 23. At the minimum phase of solar cycle 22, when the underlying solar magnetic field was simple and nearly dipole in nature, the high-speed streams were observed from the poles to {approx}30 Degree-Sign latitudes in both hemispheres. In contrast, in the long-decay phase of cycle 23, the sources of the high-speed wind at both poles, in accordance with the weak polar fields, occupied narrow latitude belts from poles to {approx}60 Degree-Sign latitudes. Moreover, in agreement with the large amplitude of the heliospheric current sheet, the low-speed wind prevailed in the low- and mid-latitude regions of the heliosphere. (4) At the transition phase between cycles 23 and 24, the high levels of density and density turbulence were observed close to the heliospheric equator and the low-speed solar wind extended from the equatorial-to-mid-latitude regions. The above results in comparison with Ulysses and other in situ measurements suggest that the source of the solar wind has changed globally, with the important implication that the supply of mass and energy from the Sun to the interplanetary space has been significantly reduced in the prolonged period of low solar activity. The IPS results are consistent with the onset and growth of the current solar cycle 24, starting from the middle of 2009. However, the width of the high-speed wind at the northern high latitudes has almost disappeared and indicates that the ascending phase of the current cycle has almost reached the maximum phase in the northern hemisphere of the Sun. However, in the southern part of the hemisphere, the solar activity has yet to develop and/or increase.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2008

If We Can't Predict Solar Cycle 24, What About Solar Cycle 34?

Predictions of solar activity in Solar Cycle 24 range from 50% larger than SC 23 to the onset of a Grand Minimum. Because low levels of solar activity are associated with global cooling in paleoclimate and isotopic records, anticipating these extremes is required in any longterm extrapolation of climate variability. Climate models often look forward 100 or more years, which would mean 10 solar cycles into the future. Predictions of solar activity are derived from a number of methods, most of which, such as climatology and physics-based models, will be familiar to atmospheric scientists. More than 50 predictions of the maximum amplitude of SC 24 published before solar minimum will be discussed. Descriptions of several methods that result in the extreme predictions and some anticipation of even longer term predictions will be presented.

Pesnell. William Dean↗
NASA NTRS2000

Status of Cycle 23 Forecasts

A number of techniques for predicting solar activity on a solar cycle time scale are identified, described, and tested with historical data. Some techniques, e.g,, regression and curve-fitting, work well as solar activity approaches maximum and provide a month- by-month description of future activity, while others, e.g., geomagnetic precursors, work well near solar minimum but provide an estimate only of the amplitude of the cycle. A synthesis of different techniques is shown to provide a more accurate and useful forecast of solar cycle activity levels. A combination of two uncorrelated geomagnetic precursor techniques provides the most accurate prediction for the amplitude of a solar activity cycle at a time well before activity minimum. This precursor method gave a smoothed sunspot number maximum of 154+21 for cycle 23. A mathematical function dependent upon the time of cycle initiation and the cycle amplitude then describes the level of solar activity for the complete cycle. As the time of cycle maximum approaches a better estimate of the cycle activity is obtained by including the fit between recent activity levels and this function. This Combined Solar Cycle Activity Forecast now gives a smoothed sunspot maximum of 140+20 for cycle 23. The success of the geomagnetic precursors in predicting future solar activity suggests that solar magnetic phenomena at latitudes above the sunspot activity belts are linked to solar activity, which occurs many years later in the lower latitudes.

Hathaway, D. H.↗
NASA NTRS1999

A Survey and Synthesis of Solar Cycle Prediction Techniques

A number of techniques for predicting solar activity on a solar cycle time scale are identified, described, and tested with historical data. Some techniques, e.g. regression and curve-fitting, work well as solar activity approaches maximum and provide a complete description of future activity, while others, e.g. geomagnetic precursors, work well near solar minimum but only provide an estimate of the amplitude of the cycle. A synthesis of different techniques is shown to provide a more accurate and useful forecast of solar cycle activity levels. A combination of two uncorrelated geomagnetic precursor techniques provides the most accurate prediction for the amplitude of a solar activity cycle at a time well before activity minimum. This Combined Precursor Method gives a smoothed sunspot number maximum of 154+/-21 at the 95% level of confidence for the next cycle maximum. A mathematical function dependent upon the time of cycle initiation and the cycle amplitude then describes the level of solar activity for the next complete cycle. As the time of cycle maximum approaches a better estimate of the cycle activity is obtained by including the fit between previous activity levels and this function. This Combined Solar Cycle Activity Forecast gives, as of January 1999, a smoothed sunspot maximum of 146+/-20 at the 95% level of confidence for the next cycle maximum. The success of the geomagnetic precursors in predicting future solar activity suggests that solar magnetic phenomena at latitudes above the sunspot activity belts are linked to solar activity which occurs many years later in the lower latitudes.

Hathaway, David H.↗
NASA NTRS1993

How active was solar cycle 22?

Solar EUV observations from the Langmuir probe on Pioneer Venus Orbiter suggest that at EUV wavelengths solar cycle 22 was more active than solar cycle 21. The Langmuir probe, acting as a photodiode, measured the integrated solar EUV flux over a 13 1/2 year period from January 1979 to June 1992, the longest continuous solar EUV measurement. The Ipe EUV flux correlated very well with the SME measurement of L-alpha during the lifetime of SME and with the UARS SOLSTICE L-alpha from October 1991 to June 1992 when the Ipe measurement ceased. Starting with the peak of solar cycle 21, there was good general agreement of Ipe EUV with the 10.7 cm, Ca K, and He 10830 solar indices, until the onset of solar cycle 22. From 1989 to the start of 1992, the 10.7 cm flux exhibited a broad maximum consisting of two peaks of nearly equal magnitude, whereas Ipe EUV exhibited a strong increase during this time period making the second peak significantly higher than the first. The only solar index that exhibits the same increase in solar activity as Ipe EUV and L-alpha during the cycle 22 peak is the total magnetic flux. The case for high activity during this peak is also supported by the presence of very high solar flare intensity.

Hoegy, W. R.↗
NASA NTRS1985

Solar-geophysical data number 490, June 1985. Part 1: (Prompt reports). Data for May 1985, April 1985 and late data

Contents include: detailed index for 1984 to 1985; data for May 1985--(IUWDS alert periods (Advance and Worldwide) solar activity indices, solar flares, solar radio emission, Stanford mean solar magnetic field); data for April 1985--(solar active regions, sudden ionospheric disturbances, solar radio spectral observations, cosmic ray measurements by neutron monitor, geomagnetic indices, radio propagation indices); and late data--(geomagnetic indices, cosmic rays, calcium plage data).

Coffey, H. E.↗
NASA NTRS1985

Solar-geophysical data number 493, September 1985. Part 1: (Prompt reports). Data for August 1985, July 1985 and late data

Topics covered include: detailed index for 1985; data for August 1985--(IUWDS alert periods (Advanced and Worldwide), solar activity indices, solar flares, solar radio emission, Stanford mean solar magnetic field); (solar active regions, sudden ionospheric disturbances, solar radio spectral observations, cosmic ray measurements by neutron monitor, geomagnetic indices, radio propagation indices); and late data--calcium plage data.

Coffey, H. E.↗