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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1980

Solar activity prediction of sunspot numbers (verification). Predicted solar radio flux; predicted geomagnetic indices Ap and Kp

Efforts to further verify a previously reported technique for predicting monthly sunspot numbers over a period of years (1979 to 1989) involved the application of the technique over the period for the maximum epoch of solar cycle 19. Results obtained are presented. Methods and results for predicting solar flux (F10.7 cm) based on flux/sunspot number models, ascent and descent, and geomagnetic activity indices as a function of sunspot number and solar cycle phase classes are included.

Newman, S. R.↗
NASA NTRS1980

Shuttle program. Solar activity prediction of sunspot numbers, predicted solar radio flux

A solar activity prediction technique for monthly mean sunspot numbers over a period of approximately ten years from February 1979 to January 1989 is presented. This includes the predicted maximum epoch of solar cycle 21, approximately January 1980, and the predicted minimum epoch of solar cycle 22, approximately March 1987. Additionally, the solar radio flux 10.7 centimeter smooth values are included for the same time frame using a smooth 13 month empirical relationship. The incentive for predicting solar activity values is the requirement of solar flux data as input to upper atmosphere density models utilized in mission planning satellite orbital lifetime studies.

Johnson, G. G.↗
NASA NTRS1992

Solar prediction analysis

Solar Activity prediction is essential to definition of orbital design and operational environments for space flight. This task provides the necessary research to better understand solar predictions being generated by the solar community and to develop improved solar prediction models. The contractor shall provide the necessary manpower and facilities to perform the following tasks: (1) review, evaluate, and assess the time evolution of the solar cycle to provide probable limits of solar cycle behavior near maximum end during the decline of solar cycle 22, and the forecasts being provided by the solar community and the techniques being used to generate these forecasts; and (2) develop and refine prediction techniques for short-term solar behavior flare prediction within solar active regions, with special emphasis on the correlation of magnetic shear with flare occurrence.

Smith, Jesse B.↗
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 NTRS1987

Solar prediction and intelligent machines

The solar prediction program is aimed at reducing or eliminating the need to throughly understand the process previously developed and to still be able to produce a prediction. Substantial progress was made in identifying the procedures to be coded as well as testing some of the presently coded work. Another project involves work on developing ideas and software that should result in a machine capable of learning as well as carrying on an intelligent conversation over a wide range of topics. The underlying idea is to use primitive ideas and construct higher order ideas from these, which can then be easily related one to another.

Johnson, Gordon G.↗
NASA NTRS2012

Solar Cycle Predictions

Solar cycle predictions are needed to plan long-term space missions; just like weather predictions are needed to plan the launch. Fleets of satellites circle the Earth collecting many types of science data, protecting astronauts, and relaying information. All of these satellites are sensitive at some level to solar cycle effects. Predictions of drag on LEO spacecraft are one of the most important. Launching a satellite with less propellant can mean a higher orbit, but unanticipated solar activity and increased drag can make that a Pyrrhic victory as you consume the reduced propellant load more rapidly. Energetic events at the Sun can produce crippling radiation storms that endanger all assets in space. Solar cycle predictions also anticipate the shortwave emissions that cause degradation of solar panels. Testing solar dynamo theories by quantitative predictions of what will happen in 5-20 years is the next arena for solar cycle predictions. A summary and analysis of 75 predictions of the amplitude of the upcoming Solar Cycle 24 is presented. The current state of solar cycle predictions and some anticipations how those predictions could be made more accurate in the future will be discussed.

Pesnell, William Dean↗
NASA NTRS2011

Solar Cycle Prediction

Solar cycle predictions are needed to plan long-term space missions; just like weather predictions are needed to plan your next vacation. Fleets of satellites circle the Earth collecting many types of science data, protecting astronauts, and relaying information. All of these satellites are sensitive at some level to solar cycle effects. Predictions of drag on LEO spacecraft are one of the most important. Launching a satellite with less propellant can mean a higher orbit, but unanticipated solar activity and increased drag can make that a Pyrrhic victory. Energetic events at the Sun can produce crippling radiation storms that endanger all assets in space. Testing solar dynamo theories by quantitative predictions of what will happen in 5-20 years is the next arena for solar cycle predictions. I will describe the current state of solar cycle predictions and anticipate how those predictions could be made more accurate in the future.

Pesnell, William Dean↗
NASA NTRS2014

Predicting Solar Cycle 24 Using a Geomagnetic Precursor Pair

We describe using Ap and F(10.7) as a geomagnetic-precursor pair to predict the amplitude of Solar Cycle 24. The precursor is created by using F(10.7) to remove the direct solar-activity component of Ap. Four peaks are seen in the precursor function during the decline of Solar Cycle 23. A recurrence index that is generated by a local correlation of Ap is then used to determine which peak is the correct precursor. The earliest peak is the most prominent but coincides with high levels of non-recurrent solar activity associated with the intense solar activity of October and November 2003. The second and third peaks coincide with some recurrent activity on the Sun and show that a weak cycle precursor closely following a period of strong solar activity may be difficult to resolve. A fourth peak, which appears in early 2008 and has recurrent activity similar to precursors of earlier solar cycles, appears to be the "true" precursor peak for Solar Cycle 24 and predicts the smallest amplitude for Solar Cycle 24. To determine the timing of peak activity it is noted that the average time between the precursor peak and the following maximum is approximately equal to 6.4 years. Hence, Solar Cycle 24 would peak during 2014. Several effects contribute to the smaller prediction when compared with other geomagnetic-precursor predictions. During Solar Cycle 23 the correlation between sunspot number and F(10.7) shows that F(10.7) is higher than the equivalent sunspot number over most of the cycle, implying that the sunspot number underestimates the solar-activity component described by F(10.7). During 2003 the correlation between aa and Ap shows that aa is 10 % higher than the value predicted from Ap, leading to an overestimate of the aa precursor for that year. However, the most important difference is the lack of recurrent activity in the first three peaks and the presence of significant recurrent activity in the fourth. While the prediction is for an amplitude of Solar Cycle 24 of 65 +/- 20 in smoothed sunspot number, a below-average amplitude for Solar Cycle 24, with maximum at 2014.5+/-0.5, we conclude that Solar Cycle 24 will be no stronger than average and could be much weaker than average.

predictions↗
NASA NTRS1992

The role of predicted solar activity in TOPEX/Poseidon orbit maintenance maneuver design

Following launch in June 1992, the TOPEX/Poseidon satellite will be placed in a near-circular frozen orbit at an altitude of about 1336 km. Orbit maintenance maneuvers are planned to assure all nodes of the 127-orbit 10-day repeat ground track remain within a 2 km equatorial longitude bandwidth. Orbit determination, maneuver execution, and atmospheric drag prediction errors limit overall targeting performance. This paper focuses on the effects of drag modeling errors, with primary emphasis on the role of SESC solar activity predictions, especially the 27-day outlook of the 10.7 cm solar flux and geomagnetic index used by a simplified version of the Jacchia-Roberts density model developed for this TOPEX/Poseidon application. For data evaluated from 1983-90, the SESC outlook performed better than a simpler persistence strategy, especially during the first 7-10 days. A targeting example illustrates the use of ground track biasing to compensate for expected orbit predictions errors, emphasizing the role of solar activity prediction errors.

Frauenholz, Raymond B.↗
NASA NTRS1979

Solar weather/climate predictions

Solar variability influences upon terrestrial weather and climate are addressed. Both the positive and negative findings are included and specific predictions, areas of further study, and recommendations listed.

Schatten, K. H.↗
NASA NTRSDate not supplied

Using Long-Short Term Memory Models to Predict Solar Active Regions Emergence

We train Long Short-Term Memory (LSTM) models that predict the formation of active regions (ARs), the main source of eruptive solar activity. Using the Doppler shift velocity, the continuum intensity and the magnetic field full-disk maps from SDO/HMI we have created time-series datasets of acoustic power and magnetic flux which are used to train Long Short-Term Memory (LSTM) models on predicting decreases in continuum intensity 12 hours in advance. Testing of the models' performance was done on data from 5 ARs, unseen from the model during training. The model predicted the emergence of AR11726, AR13165 and AR13179, 10, 29 and 5 hours in advance, and variations of this model achieved average RMSE values of 0.11 for both active and quiet parts of the solar disc, showing the ability of the model to capture acoustic power anomalies and predict continuum intensity variations. This work sets the foundations for the very first ML-aided prediction of solar ARs.

SMD↗
NASA NTRS1984

Predicting Solar Deficits

Statistical method uses available long term solar irradiance data at selected sites in United States to predict probable deviations from long term monthly averages. Technique useful in sizing solar collectors and backup storage systems to cover solar deficits.

Ross, R. G., Jr.↗
NASA NTRS2018

Helioseismic Observations of Torsional Oscillations Inside the Sun and Their Potential for Predicting Solar Cycles

The helioseismic analysis of torsional oscillations of the Sun, obtained in 1996-2018 from SOHO (Solar and Heliospheric Observatory) and SDO (Solar Dynamics Observatory), reveals the spatio-temporal dynamics associated with the dynamo process. The data reveal new relationships between the migrating magnetic field patterns observed in synoptic magnetograms and the dynamics of torsional oscillations near the surface and in the interior. In particular, it is found that the evolution of torsional oscillations in the deep convection zone is ahead of the surface magnetic evolution by several years, and that it is related to the extended solar cycle phenomenon previously observed in the solar corona. The data show substantial differences in the torsional oscillation properties between Cycles 23 and 24 indicating fundamental changes in the dynamo regime, and also reveal initiation of Cycle 25. The helioseismology observations of the torsional oscillations open new perspectives for understanding the global dynamo processes inside the Sun, and for predicting the next solar cycle.

Oscillations↗
NASA NTRS2023

Using Random Hiveminds to Predict Solar Energetic Particles (SEPs)

The Problem: The use of conventional neural networks (CoNNs) to predict SEPs has become popular, but neural network models do not follow one-size-fits-all approaches and their chaotic natures can yield completely different results on identical data sets. Committees of neural networks identical in input features have been used to solve this problem by (Aminalragia et al., 2021), but they have the possibility of all agreeing together in lockstep and missing crucial information. The Solution: (O’Keefe et al., 2023) propose a solution consisting of neural network estimators in an ensemble, but with features randomly removed from them in a layout known as a random hivemind (RH). The decision weight, learning rate, and epoch count of each member in this ensemble are boosted in relation to how well its individual features perform in a chi-square test.

SMD↗
NASA NTRS1974

Uncertainties in predicting solar panel power output

The problem of calculating solar panel power output at launch and during a space mission is considered. The major sources of uncertainty and error in predicting the post launch electrical performance of the panel are considered. A general discussion of error analysis is given. Examples of uncertainty calculations are included. A general method of calculating the effect on the panel of various degrading environments is presented, with references supplied for specific methods. A technique for sizing a solar panel for a required mission power profile is developed.

Anspaugh, B.↗