Search NASA⌕ Search

SEARCH · Search NASA

Results for “solar variability”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Long-term spatial and temporal solar resource variability over America using the NSRDB version 3 (1998–2017)

The study assesses the long-term spatial and temporal solar resource variability in America using the 20-year National Renewable Energy Laboratory's (NREL's) National Solar Radiation Database (NSRDB). Specifically, the coefficient of variation (COV) is used to analyze the spatial and temporal (interannual and seasonal) variability. Further, both spatial and temporal long-term variability are analyzed using the Köppen-Geiger climate classification. The temporal variability is found that, on average, the continental United States (CONUS) COV reaches up to 5% for global horizontal irradiance (GHI) and 10% for direct normal irradiance (DNI), and that the NSRDB domain's COV is roughly twice that of CONUS. For the seasonal variability analysis, the winter months are found to exhibit higher COV than the other seasons. In particular, December exhibits the highest variability, reaching on average 30% for DNI and 20% for GHI over various areas. On the other hand, the summer months demonstrate significantly lower variability, reaching only less than 20% for DNI and 10% for GHI, on average. Similarly, the spatial variability is analyzed by comparing each pixel to its neighbors. The long-term spatial variability is found to increase with the number of neighboring pixels being considered, which is equivalent to an increase in distance (within a 100-km x 100-km square grid). As expected, the DNI spatial variability is higher than that of GHI. Moreover, the annual solar irradiance anomalies are found to reach ±25% for both GHI and DNI (and even exceed those value in some instances) during each year of the 20-year period.

14 SOLAR ENERGY↗
NASA NTRS2017

Using Data Assimilation Methods of Prediction of Solar Activity

The variable solar magnetic activity known as the 11-year solar cycle has the longest history of solar observations. These cycles dramatically affect conditions in the heliosphere and the Earth's space environment. Our current understanding of the physical processes that make up global solar dynamics and the dynamo that generates the magnetic fields is sketchy, resulting in unrealistic descriptions in theoretical and numerical models of the solar cycles. The absence of long-term observations of solar interior dynamics and photospheric magnetic fields hinders development of accurate dynamo models and their calibration. In such situations, mathematical data assimilation methods provide an optimal approach for combining the available observational data and their uncertainties with theoretical models in order to estimate the state of the solar dynamo and predict future cycles. In this presentation, we will discuss the implementation and performance of an Ensemble Kalman Filter data assimilation method based on the Parker migratory dynamo model, complemented by the equation of magnetic helicity conservation and long-term sunspot data series. This approach has allowed us to reproduce the general properties of solar cycles and has already demonstrated a good predictive capability for the current cycle, 24. We will discuss further development of this approach, which includes a more sophisticated dynamo model, synoptic magnetogram data, and employs the DART Data Assimilation Research Testbed.

Prediction↗
NASA NTRS1994

Changes in photochemically significant solar UV spectral irradiance as estimated by the composite Mg II index and scale factors

Quantitative assessment of the impact of solar ultraviolet irradiance variations on stratospheric ozone abundances currently requires the use of proxy indicators. The Mg II core-to-wing index has been developed as an indicator of solar UV activity between 175-400 nm that is independent of most instrument artifacts, and measures solar variability on both rotational and solar cycle time scales. Linear regression fits have been used to merge the individual Mg II index data sets from the Nimbus-7, NOAA-9, and NOAA-11 instruments onto a single reference scale. The change in 27-dayrunning average of the composite Mg II index from solar maximum to solar minimum is approximately 8 percent for solar cycle 21, and approximately 9 percent for solar cycle 22 through January 1992. Scaling factors based on the short-term variations in the Mg II index and solar irradiance data sets have been developed to estimate solar variability at mid-UV and near-UV wavelengths. Near 205 nm, where solar irradiance variations are important for stratospheric photo-chemistry and dynamics, the estimated change in irradiance during solar cycle 22 is approximately 10 percent using the composite Mg II index and scale factors.

Deland, Matthew T.↗
NASA NTRS1980

The corona and heliosphere

The eleven-year solar cycle is an especially appropriate period over which to study the solar output and its variation, because during this cycle most of the important types of solar variability (many characterized by periods shorter than eleven years) are manifested. Studies of solar variability over a solar cycle will improve understanding of solar structure and of the generation of the solar wind, and this improved understanding can be useful in the related studies of stellar structure and stellar winds, since stellar observations are necessarily less detailed and sophisticated than are solar observations. A particularly significant benefit that will accrue from a thorough study of the solar atmosphere and its variability over the next solar cycle is a great enhancement in the usefulness of so-called 'proxy' data in studying longer term solar variations and their terrestrial implication.

Holzer, T.↗
NASA NTRS1984

The temporal behavior of upper stratospheric ozone at low latitudes - Evidence from Nimbus 4 BUV data for short-term responses to solar ultraviolet variability

Ozone mixing ratios at pressure levels near 2 mbar are analyzed for the purpose of estimating the average response of the upper stratospheric ozone to solar UV variability on the time scale of the solar rotation period. The data were obtained from observations made with the Nimbus 4 backscattering UV radiometer in 13 latitude zones between 65 degrees N and 65 degrees S. The anaysis showed that temporal variations are negatively correlated with changes in zonally averaged equivalent temperature measured simultaneously by Nimbus 4 radiometer. A linear regression analysis is performed in order to obtain estimates of the average percent change of ozone at low latitudes, on the considered time scale for given changes in 10.7-cm flux, and in the UV flux model developed by Lean et al. (1982). Reproductions of the ozone profiles are provided.

Hood, L. L.↗
NASA NTRS1998

Models of Solar Irradiance Variability and the Instrumental Temperature Record

The effects of decade-to-century (Dec-Cen) variations in total solar irradiance (TSI) on global mean surface temperature Ts during the pre-Pinatubo instrumental era (1854-1991) are studied by using two different proxies for TSI and a simplified version of the IPCC climate model.

solar variability climate change global warming↗
NASA NTRS1989

Time variability of solar active regions at centimeter wavelengths

An analysis is presented of the variability of centimeter wavelength emission originating from the solar transition region and lower corona, and the variability is compared with the sun's quiescent emission. Sequential dual wavelength observations are presented and used to put constraints on a possible model of the variability of active region emissions and to better understand the dynamics of active regions. It is shown that gyroresonance emission contributes significantly to the active region emission at 6 cm, whereas all the quiet-sun emission can be attributed to free-free emission. From comparison of the quiet-sun and active region models, it is shown that the density at the base of the transition region is higher in active regions.

Shevgaonkar, R. K.↗
NASA NTRS2005

Solar Effects on Global Climate Due to Cosmic Rays and Solar Energetic Particles

Although the work reported here does not directly connect solar variability with global climate change, this research establishes a plausible quantitative causative link between observed solar activity and apparently correlated variations in terrestrial climate parameters. Specifically, we have demonstrated that ion-mediated nucleation of atmospheric particles is a likely, and likely widespread, phenomenon that relates solar variability to changes in the microphysical properties of clouds. To investigate this relationship, we have constructed and applied a new model describing the formation and evolution of ionic clusters under a range of atmospheric conditions throughout the lower atmosphere. The activation of large ionic clusters into cloud nuclei is predicted to be favorable in the upper troposphere and mesosphere, and possibly in the lower stratosphere. The model developed under this grant needs to be extended to include additional cluster families, and should be incorporated into microphysical models to further test the cause-and-effect linkages that may ultimately explain key aspects of the connections between solar variability and climate.

Turco, R. P.↗
NASA NTRS1974

Influence of solar wind variability on geomagnetic activity

A statistical study of solar wind data from the Explorer 33 satellite shows that interplanetary magnetic field irregularities are enhanced in the interaction region where a fast solar wind stream overtakes a slower solar wind stream. Comparison with geomagnetic AE and ap indexes further shows that these interplanetary irregularities enhance the level of geomagnetic disturbances. Thus while substorm occurrence is highly correlated with the dawn-dusk component of the solar wind electric field, the amplitude of the substorms is an increasing function of the variance in the interplanetary field. This result can be interpreted as a capacitative effect of the magnetopause that allows a time-varying solar wind electric field to penetrate the magnetosphere more effectively than a static solar wind electric field.

Garrett, H. B.↗
NASA NTRS1998

Validation of 1985-1997 Active Cavity Radiometer Spacecraft Measurements of Total Solar Irradiance Variability

Since 1978, long-term variations in the total solar irradiance (solar constant) have been monitored using spacecraft radiometers, at the 0.01% precision level. The irradiance measurements were performed from the Earth Radiation Budget Satellite [ERBS], Nimbus-7, Solar Maximum Mission [SMM], Upper Atmosphere Research Satellite [UARS], European Retrievable Carrier (EURECA), Solar and Heliospheric Observatory [SOHO], and the Space Shuttle Atmospheric Laboratory for Applications and Science [ATLAS] spacecraft platforms. Radiometer responses can drift or shift at precision levels of a few hundreds of a percent. In-flight calibration sources are not available to detect radiometer response changes at radiometric accuracy or precision levels near the 0.01% (0.1 W/sq m) level. Inconsistent trends among the sets were used to identify possible instrumental drifts or shifts which may be incorrectly interpreted as solar irradiance changes while consistent trends among the different measurement sets were used to detect long-term irradiance variability components. In this paper, 1991-1998 corresponding ERBS, UARS, SOHO, and ATLAS irradiance measurements are inter-compared with each other as well as with the ERBS empirical irradiance fit. The empirical irradiance fit is based upon 10.7-cm solar radio flux (F10) and photometric sunspot index (PSI), indices of solar magnetic activity. Analyses of recent data sets identified no long-term shifts and drifts in the ERBS, SOHO, or UARS data sets. The typical value of the total solar irradiance is approximately 1365 Watts per meter squared (W/sq m).

Lee, Robert B., III↗
NASA NTRS1995

Studying Solar Irradiance Variability with Wavelet Technique

The detection of variations in solar irradiance by satellite-based experiments during the last 17 years stimulated modelling efforts to help to identify their causes and to provide estimates for irradiance data when no satellite observations exist.

solar irradiance modelling efforst physical origin↗
NASA NTRS2001

Living With a Star, the Geospace Mission Definition Team and Aeronomy

To gain an understanding of the Sun-Earth system, including how and why the sun varies, how the earth responds, and the impacts on humanity, research is needed that has a integrated and systematic approach. The Living With a Star (LWS) program represents an important element in this regard both to continued progress in space science in general and in Aeronomy in particular. A fundamental question in Aeronomy is how the variable sun affects the ionosphere, thermosphere, and mesosphere. The LWS program focuses on those areas of scientific understanding that promote progress in areas that have human impact and can be investigated with space borne instruments. The Geospace Mission Definition Team is charged with investigating the science priorities identified by the LWS Science Architecture Team and developing an approach to making the necessary measurements in concert with other missions and programs. An important aspect of this approach is that all LWS measurement programs are operating simultaneously for several years. We will review some of the areas that the LWS SAT have emphasized in Aeronomy, including understanding the effects of solar variability on ionospheric density and irregularities, the effects of solar variability on the mass density of the atmosphere at LEO altitudes, and the effects of solar variability on near-surface temperatures and on ozone distribution.

Kintner, Paul M., Jr.↗
DOE OSTI2021

Validation of Subhourly Clipping Loss Error Corrections: Preprint

Under-performance of solar PV systems is an important issue that increases risks for stakeholders, including developers, investors and operators. Recently some attention has focused on underestimation of inverter clipping losses as a possible source of over-prediction where sub-hourly solar variability is high. Several models and data sets have been analyzed over the past few years, with the aim of quantifying, predicting, and correcting underestimated clipping loss errors for systems with high DC/AC ratio and solar variability. In this research, we apply a machine learning model developed at NREL to two physical PV systems, to correct for subhourly clipping losses. For each system, we compare overall AC power output for the model taken at 1-minute intervals to AC power output taken at 1-hour intervals with the addition of the subhourly clipping correction. Our findings consistently show that the addition of the clipping loss correction lead to a reduction in mean bias error of 0.6\% and 1.1\% for systems A and B, respectively, with no additional filtering applied. When examining high solar variability periods where clipping is more pronounced, system A and B experienced a 1.4\% and 2.5\% reduction in mean bias error, respectively, when the clipping correction was applied.

machine learning↗
DOE OSTI2021

Validation of Subhourly Clipping Loss Error Corrections

Under-performance of solar PV systems is an important issue that increases risks for stakeholders, including developers, investors and operators. Recently some attention has focused on underestimation of inverter clipping losses as a possible source of over-prediction where sub-hourly solar variability is high. Several models and data sets have been analyzed over the past few years, with the aim of quantifying, predicting, and correcting underestimated clipping loss errors for systems with high DC/AC ratio and solar variability. In this research, we apply a machine learning model developed at NREL to two physical PV systems, to correct for subhourly clipping losses. For each system, we compare overall AC power output for the model taken at 1-minute intervals to AC power output taken at 1-hour intervals with the addition of the subhourly clipping correction. Our findings consistently show that the addition of the clipping loss correction lead to a reduction in mean bias error of 0.8% and 1.2% for systems A and B, respectively, with no additional filtering applied. When examining high solar variability periods where clipping is more pronounced, system A and B experienced a 1.8% and 2.7% reduction in mean bias error, respectively, when the clipping correction was applied.

machine learning↗
NASA NTRS1991

Solar irradiance variability from modern measurements

Direct measurements from satellites of the solar 'constant' (the total irradiance at mean sun-earth distance) during more than ten years show variations over time scales from minutes to years and decades. At high frequencies, solar oscillations contribute to the variance. The most important influences are related to solar activity: during the passage of active regions on the solar disk (sunspots and faculae) changes of a few 0.1 percent lasting for several days are observed. The effects of spots can be well reproduced by the projected sunspot index, whereas the influence of faculae have to be modeled from proxy data like the Ca-K plage index or the He I index. Long-term trends are detected which are connected to the 11-yr solar activity cycle.

Froehlich, C.↗
NASA NTRS1986

Application of solar max ACRIM data to analyze solar-driven climatic variability on Earth

Terrestrial climatic effects associated with solar variability have been proposed for at least a century, but could not be assessed quantitatively owing to observational uncertainities in solar flux variations. Measurements from 1980 to 1984 by the Active Cavity Radiometer Irradiance Monitor (ACRIM), capable of resolving fluctuations above the sensible atmosphere less than 0.1% of the solar constant, permit direct albeit preliminary assessments of solar forcing effects on global temperatures during this period. The global temperature response to ACRIM-measured fluctuations was computed from 1980 to 1985 using the NYU transient climate model including thermal inertia effects of the world ocean; and compared the results with observations of recent temperature trends. Monthly mean ACRIM-driven global surface temperature fluctuations computed with the climate model are an order of magnitude smaller, of order 0.01 C. In constrast, global mean surface temperature observations indicate an approx. 0.1 C increase during this period. Solar variability is therefore likely to have been a minor factor in global climate change during this period compared with variations in atmospheric albedo, greenhouse gases and internal self-inducedoscillations. It was not possible to extend the applicability of the measured flux variations to longer periods since a possible correlation of luminosity with solar annual activity is not supported by statistical analysis. The continuous monitoring of solar flux by satellite-based instruments over timescales of 20 years or more comparable to timescales for thermal relaxation of the oceans and of the solar cycle itself is needed to resolve the question of long-term solar variation effects on climate.

Hoffert, M. I.↗
NASA NTRS1990

The ACRIM data in the context of stellar variability

The Active Cavity Radiometer Irradiance Monitor (ACRIM) total-irradiance data from the Solar Maximum Mission have given a first comprehensive view of solar variability in the stellar sense. Five types of solar variability have been identified thus far. These have small amplitudes, less than a few tenths of one percent, and are at levels generally not yet detectable on other stars. The possible stellar analogs are interesting physically, and in particular may help us to understand solar behavior on longer time scales. The ACRIM data is described from the stellar point of view. The present state of stellar time-series photometry is discussed.

Hudson, Hugh S.↗
NASA NTRS2011

Solar UV Variations During the Decline of Cycle 23

Characterization of temporal and spectral variations in solar ultraviolet irradiance over a solar cycle is essential for understanding the forcing of Earth's atmosphere and climate. Satellite measurements of solar UV variability for solar cycles 21, 22, and 23 show consistent solar cycle irradiance changes at key wavelengths (e.g. 205 nm, 250 nm) within instrumental uncertainties. All historical data sets also show the same relative spectral dependence for both short-term (rotational) and long-term (solar cycle) variations. Empirical solar irradiance models also produce long-term solar UV variations that agree well with observational data. Recent UV irradiance data from the Solar Radiation and Climate Experiment (SORCE) Spectral Irradiance Monitor (SIM) and Solar Stellar Irradiance Comparison Experiment (SOLSTICE) instruments covering the declining phase of Cycle 23 present a different picture oflong-term solar variations from previous results. Time series of SIM and SOLSTICE spectral irradiance data between 2003 and 2007 show solar variations that greatly exceed both previous measurements and predicted irradiance changes over this period, and the spectral dependence of the SIM and SOLSTICE variations during these years do not show features expected from solar physics theory. The use of SORCE irradiance variations in atmospheric models yields substantially different middle atmosphere ozone responses in both magnitude and vertical structure. However, short-term solar variability derived from SIM and SOLSTICE UV irradiance data is consistent with concurrent solar UV measurements from other instruments, as well as previous results, suggesting no change in solar physics. Our analysis of short-term solar variability is much less sensitive to residual instrument response changes than the observations of long-term variations. The SORCE long-term UV results can be explained by under-correction of instrument response changes during the first few years of measurements, rather than requiring an unexpected change in the physical behavior of the Sun.

DeLand, Matthew, T.↗