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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Removing solar artifacts from Geostationary Lightning Mapper data to document lightning extremes

Here, we compare the performance of three different filters that identify solar artifacts in the Geostationary Lightning Mapper (GLM) data. These filters differ in their complexity and intended use. We use the most appropriate filters to document the severity of GLM solar contamination and to compute the frequency of extreme Americas lightning. Solar artifacts occur at an average rate of one every ~8 min. Due to their continuous emissions across a portion of the GLM CCD array, these events disproportionately contribute to the GLM event and group rates. Up to 40% of all events recorded between 10:00 and 12:00 local time during 2018 were solar artifacts. The frequency-domain solar filter also reveals a carrier wave at 50 to 60 Hz in some lightning flashes and solar episodes that appears to be anthropogenic in origin. Removing the relatively frequent solar artifact cases reveals rare cases of extreme lightning flashes. Exceptional flashes on the order of 500+ km in length and 10+ s in duration only occur a few times per year and are produced by storms that are predisposed for exceptional lightning rather than as single random occurrences.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1985

Solar torsional oscillations - A net pattern with wavenumber 2 as artifact

A net solar torsional oscillation pattern is uncovered through a new analysis of Mount Wilson Doppler data. This pattern, found from zonal fits, without subtraction of a global fit, consists of a relative polar spin-up around solar maximum, alternating with a single traveling wave that runs from mid latitude to low latitude during the rest of the cycle. It is suggested that these are separate phenomena, and thus that the previously inferred pole-to-equator traveling pattern with wavenumber 2 per hemisphere may be a mathematical artifact. The new pattern retains aspects of the original pattern's relationship to magnetic activity, and agrees better with model predictions.

Snodgrass, H. B.↗
NASA NTRSDate not supplied

Using AI/ML to Address Satellite Cloud Remote Sensing Challenges

Various AI/ML tools, employed within the Clouds and the Earth's Radiant Energy System (CERES) Satellite Cloud and Radiation Property retrieval System (SatCORPS) project, are being used to mitigate satellite radiance artifacts and thereby yield more accurate cloud and radiation data products. Neural network and K-nearest neighbor approaches have been developed that enable us to better address common passive satellite remote sensing challenges, such as corrupted imagery, day/night cloud property discontinuities, solar terminator artifacts, inadequate knowledge of the land surface emission temperature (i.e., skin temperature), and poor assumptions about vertical cloud structure, that have otherwise proven difficult to solve using more conventional methods. Fixing these problems promotes a more consistent Earth radiation budget record. These efforts demonstrate effective use of AI/ML architecture to exploit complex, multivariate predictor relationships and produce usable output at satellite spatial and temporal resolutions that would otherwise be ignored or have large biases.

Benjamin Scarino↗
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.↗
DOE OSTI2020

Accurate Efficiency Measurements for Emerging PV: A Comparison of NREL's Steady-State Performance Calibration Protocol Between Conventional and Emerging PV Technologies

Emerging PV technologies (e.g. Perovskite, and Quantum Dot) are commonly known to possess challenges for accurate performance measurement under the existing IEC 60904 series of standards, which were developed for conventional Si solar cells. Potential performance artifacts depending on scan rates and directions and light bias exposure history are often seen in those emerging solar cells. To avoid these artifacts and provide an unbiased and reliable efficiency measurement, NREL's Cell and Module Performance (CMP) Group has developed a steady-state performance calibration protocol - the asymptotic P MAX method. In this paper, we applied this procedure to four PV cell technologies, Si, CIGS, perovskite, and Quantum Dot (QD), and compared their performance variations between the transient and the steady-state conditions. By comparison, we found that the performance parameters ( i.e. V OC , I SC , FF, ..eta..) measured between fast I-V scans (and the asymptotic method (steady-state) change significantly for perovskite and QD cells. These changes do not happen for Si and CIGS cells. Furthermore, the statistical performance analysis on nearly 100 emerging cells received globally (including OPV, Perovskite, and QD) shows that over 70 % of the fast I-V scans have a relative performance deviation larger than 1% compared to those determined using the asymptotic P MAX scan. Given the complex dynamic behavior observed in emerging PV devices, the CMP group at NREL thus only certifies their steady steady-state performance using the Asymptotic P MAX method. We highly recommend similar steady-state performance calibration protocol for all researchers in emerging PV because accuracy in reported efficiencies is critical to the long-term success of those promising new PV technologies.

41 EE - Solar Energy Technologies Office (EE-4S)↗
NASA NTRS2018

Reduced Solar-Induced Chlorophyll Fluorescence from GOME-2 During Amazon Drought Caused by Dataset Artifacts

Recently, Yang et al. (2018) reported a decrease in solar‐induced chlorophyll fluorescence (SIF) during 2015/2016 El Nino event albeit the increase in enhanced vegetation index (EVI). They interpreted the reduced SIF as a signal of reduced ecosystem photosynthesis. However, we argue that the reduced SIF during 2015/2016 is caused by a decreasing trend of SIF due to sensor degradation and the satellite overpass time is critical for drought impact assessment.

Solar‐induced chlorophyll fluorescence (SIF) and↗
NASA NTRS2019

Applying the Dark Target Aerosol Algorithm with Advanced Himawari Imager Observations During the KORUS-AQ Field Campaign

For nearly 2 decades we have been quantitatively observing the Earth's aerosol system from space at one or two times of the day by applying the Dark Target family of algorithms to polar-orbiting satellite sensors, particularly MODIS and VIIRS. With the launch of the Advanced Himawari Imager (AHI) and the Advanced Baseline Imagers (ABIs) into geosynchronous orbits, we have the new ability to expand temporal coverage of the traditional aerosol optical depth (AOD) to resolve the diurnal signature of aerosol loading during daylight hours. The Korean–United States Air Quality (KORUS-AQ) campaign taking place in and around the Korean peninsula during May–June 2016 initiated a special processing of full-disk AHI observations that allowed us to make a preliminary adoption of Dark Target aerosol algorithms to the wavelengths and resolutions of AHI. Here,we describe the adaptation and show retrieval results from AHI for this 2-month period. The AHI-retrieved AOD is collocated in time and space with existing AErosol RObotic NETwork stations across Asia and with collocated Terra and Aqua MODIS retrievals. The new AHI AOD product matches AERONET, and the standard MODIS product does as well, and the agreement between AHI and MODIS retrieved AOD is excellent, as can be expected by maintaining consistency in algorithm architecture and most algorithm assumptions. Furthermore, we show that the new product approximates the AERONET-observed diurnal signature. Examining the diurnal patterns of the new AHI AOD product we find specific areas over land where the diurnal signal is spatially cohesive. For example, in Bangladesh the AOD in-creases by 0.50 from morning to evening, and in northeast China the AOD decreases by 0.25. However, over open ocean the observed diurnal cycle is driven by two artifacts, one associated with solar zenith angles greater than 70t hat may be caused by a radiative transfer model that does not properly represent the spherical Earth and the other artifact associated with the fringes of the 40 degree glint angle mask. This opportunity during KORUS-AQ provides encouragement to move towards an operational Dark Target algorithm for AHI. Future work will need to re-examine masking including snow mask, reevaluate assumed aerosol models for geosynchronous geometry, address the artifacts over the ocean, and investigate size parameter retrieval from the over-ocean algorithm.

Gupta, Pawan↗
NASA NTRS2024

Noise Reduction for Solar-Induced Fluorescence Retrievals Using Machine Learning and Principal Component Analysis: Simulations and Applications to GOME-2 Satellite Retrievals

We use a spectral-based approach that employs principal component analysis along with a relatively shallow artificial neural network (NN) to substantially reduce noise and other artifacts in terrestrial chlorophyll solar-induced fluorescence (SIF) retrievals. SIF is a very small emission at red and far-red wavelengths that is difficult to measure and is highly sensitive to random errors and systematic artifacts. Our approach relies upon an assumption that a trained NN can effectively reconstruct the total SIF signal from a relatively small number of leading principal components of the satellite-observed far-red radiance spectra without using information from the trailing modes that contain most of the random errors. We test the approach with simulated reflectance spectra produced with a full atmospheric and surface radiative transfer model using different observing and geophysical parameters and various noise levels. Resulting noisy and noise-reduced retrieved SIF values are compared with true values to assess performance. We then apply our noise reduction approach to SIF derived from two different satellite spectrometers. For evaluation, since the truth in this case is unknown, we compare SIF retrievals from two independent sensors with each other. We also compare the noise-reduced SIF temporal variations with those from an independent gross primary product (GPP) product that should display similar variations. Results show that our noise reduction approach improves capture of SIF seasonal and inter-annual variability. Our approach should be applicable to many noisy data products derived from spectral measurements. Our methodology does not replace the original retrieval algorithms; rather the original noisy retrievals are needed as the target for the NN training process.

noise reduction, solar-induced fluorescence, SIF, ↗
NASA NTRS2022

Decadal and Annual Variations in Meteoric Flux from Ulysses, Wind, and SOFIE Observations

Our solar system is filled with meteoric particles, or cosmic dust, which is either interplanetary or interstellar in origin. Interstellar dust (ISD) enters the heliosphere due to the relative motion of the sun and the interstellar flow. Interplanetary dust (IPD) comes primarily from asteroid collisions or comet sublimation, and comprises the bulk of material entering Earth’s atmosphere. This study examines variations in ISD and the IPD flux at Earth using observations from three different satellite techniques. First are size-resolved in situ meteoroid detections by the Ulysses spacecraft, and second are in situ indirect dust observations by Wind. Third are measurements of meteoric smoke in the mesosphere by the Solar Occultation For Ice Experiment (SOFIE). Wind and Ulysses observations are sorted into the interstellar and interplanetary components. Wind ISD show the anticipated correlation to the 22-yr. solar magnetic cycle, and are consistent with model predictions of ISD. Because Wind does not discriminate particle size, the IPD measurements were interpreted using meteoric mass distributions from Ulysses observations and from different models. Wind observations during 2007-2020 indicate a total meteoric influx at Earth of 22 metric tons per day (t d(exp -1)), in reasonable agreement with long-term averages from SOFIE (25 t d(exp -1)) and Ulysses (32 t d(exp -1)). The SOFIE and Wind influx time series both show an unexpected correlation to the 22-yr. solar cycle. This relationship could be an artifact, or may indicate that IPD responds to changes in the solar magnetic field.

Meteoric influx↗
NASA NTRS2019

Calibration Plan for the Ocean Color Instrument (OCI) Engineering Test Unit

The basic product measured by OCI is the top-of atmosphere (TOA) radiance at different wavelengthsThree types of calibration/characterization are necessary for ocean color processing: - Prelaunch calibration/characterization (absolute/spectral calibration and image artifacts) - On-orbit calibration (solar diffuser and lunar measurements) - Vicarious calibration (in-situ measurements of water-leaving radiance)

Meister, Gerhard↗
NASA NTRS2018

Calibration Plan for the Ocean Color Instrument (OCI) on the Plankton, Aerosol, and Cloud ocean Ecosystem (PACE) mission

The basic product measured by OCI is the top-of atmosphere (TOA) radiance at different wavelengths. Three types of calibration/characterization are necessary for ocean color processing: Pre launch calibration/characterization (absolute/spectral calibration and image artifacts), On-orbit calibration (solar diffuser and lunar measurements) and Vicarious calibration (in-situ measurements of water-leaving radiance).

Meister, Gerhard↗
NASA NTRS1982

Are the high-latitude torsional oscillations of the sun real

A numerical test is made to determine if the high-latitude torsional wave is generated from the low-latitude torsional pattern as a result of reduction procedures. The results indicate that the high-latitude motions are not an artifact of the analysis, but are true solar features. It is also demonstrated that the one-wave-per-hemisphere torsional oscillation does not result from the reduction procedure. These results place the observations in conflict with the predictions of alpha-omega models of the solar cycle.

Labonte, B. J.↗
NASA NTRS2012

Filling-in of Near-infrared Solar Lines by Terrestrial Fluorescence and Other Geophysical Effects: Simulations and Space-based Observations from SCIAMACHY and GOSAT

Global mapping of terrestrial vegetation fluorescence from space has recently been accomplished with high spectral resolution (nu/nu greater than 35 000) measurements from the Japanese Greenhouse gases Observing SAellite (GOSAT). These data are of interest because they can potentially provide global information on the functional status of vegetation including light-use efficiency and global primary productivity that can be used for global carbon cycle modeling. Quantifying the impact of fluorescence on the O2-A band is important as this band is used for photon pathlength characterization in cloud- and aerosol-contaminated pixels for trace-gas retrievals including CO2. Here, we examine whether fluorescence information can be derived from space using potentially lower-cost hyperspectral instrumentation, i.e., more than an order of magnitude less spectral resolution (nu/nu approximately 1600) than GOSAT, with a relatively simple algorithm. We discuss laboratory measurements of fluorescence near one of the few wide and deep solar Fraunhofer lines in the long-wave tail of the fluorescence emission region, the calcium (Ca) II line at 866 nm that is observable with a spectral resolution of approximately 0.5 nm. The filling-in of the Ca II line due to additive signals from various atmospheric and terrestrial effects, including fluorescence, is simulated. We then examine filling-in of this line using the SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY (SCIAMACHY) satellite instrument. In order to interpret the satellite measurements, we developed a general approach to correct for various instrumental artifacts that produce false filling-in of solar lines in satellite measurements. The approach is applied to SCIAMACHY at the 866 nm Ca II line and to GOSAT at 758 and 770 nm on the shoulders of the O2-A feature where there are several strong solar Fraunhofer lines that are filled in primarily by vegetation fluorescence. Finally, we compare temporal and spatial variations of SCIAMACHY additive signals with those of GOSAT and the Enhanced Vegetation Index (EVI) from the MODerate-resolution Imaging Spectroradiometer (MODIS). Although the derived additive signals from SCIAMACHY are extremely weak at 866 nm, their spatial and temporal variations are consistent with chlorophyll a fluorescence or another vegetation-related source. We also show that fillingin occurs at 866 nm over some barren areas, possibly originating from luminescent minerals in rock and soil.

vegetation↗
NASA NTRS1994

Mineral identification and mapping of hydrothermal alteration zones using high-spectral resolution images (AVIRIS)

High-spectral resolution images (AVIRIS) of the cuprite mining area were used to evaluate atmospheric calibration algorithms and test several mineral mapping techniques. Four scene normalization techniques were used: (1) the flat-field method, (2) the internal average reflectance method, (3) the empirical line method, and (4) the atmospheric absorption removal method (ATREM). The algorithms were evaluated in terms of their spectral interpret- ability and their ability to remove both solar irradiance and atmospheric absorption features, noise, and artifacts. Noise was quantified by calculating the coefficient of variation of the spectra, and spectral interpretability was quantified by calcu- lating a difference spectrum (eg, laboratory spectrum minus pixel spectrum) for areas with known occurrences of clay minerals. These difference spectra were useful in evaluating the degree of removal of atmospheric features. The empirical line method produced the best calibration results. Mineral mapping as done using (1) color-composites of bands on the shoulders and centers of expected absorption features, (2) color-coded spectra, and (3) spectral angle mapping.

Van Der Meer, Freek D.↗
NASA NTRSDate not supplied

Using AIA Emission Measure Inversion Failures to Track Interesting Flare Physics

EUV channels of the AIA instrument have long been used to characterize the temperature of the plasma, particularly through emission measure inversions. During a solar flare, the instrument can suffer several instrumental artifacts that complicates the analysis. We have performed an analysis of the evolution of two X class flares and find regions where the inversion fails that cannot be easily explained by instrumental artifacts. These failures tend to occur at the top of the flare loop arcade where energy is thought to be released and several non-equilibrium processes may be contributing to the emission of the plasma. In this presentation, I will establish the regions of the emission measure failures and discuss the potential instrumental and physical explanations for these failures.

A R Winebarger↗
NASA NTRS2023

The Trans-Heliospheric Survey - Radial Trends in Plasma Parameters Across the Heliosphere

Context. Though the solar wind is characterized by spatial and temporal variability across a wide range of scales, long-term averages of in situ measurements have revealed clear radial trends: changes in average values of basic plasma parameters (e.g., density, temperature, and speed) and a magnetic field with a distance from the Sun. Aims. To establish our current understanding of the solar wind's average expansion through the heliosphere, data from multiple spacecraft needed to be combined and standardized into a single dataset. Methods. In this study, data from twelve heliospheric and planetary spacecraft - Parker Solar Probe (PSP), Helios 1 and 2, Mariner 2 and 10, Ulysses, Cassini, Pioneer 10 and 11, New Horizons, and Voyager 1 and 2 - were compiled into a dataset spanning over three orders of magnitude in heliocentric distance. To avoid introducing artifacts into this composite dataset, special attention was given to the solar cycle, spacecraft heliocentric elevation, and instrument calibration. Results. The radial trend in each parameter was found to be generally well described by a power-law fit, though up to two break points were identified in each fit. Conclusions. These radial trends are publicly released here to benefit research groups in the validation of global heliospheric simulations and in the development of new deep-space missions such as Interstellar Probe.

Bennett A Maruca↗
NASA NTRS2018

Linking Asteroid Detections from the Large Synoptic Survey Telescope

We have conducted a detailed simulation of the Large Synoptic Survey Telescope (LSST) in order to understand the system’s ability to link detections of asteroids within and across nights in order to populate a catalog of asteroid orbits. We show that LSST, using its baseline survey cadence, should be able to successfully link and catalog asteroids. In our simulation of a single monthly observing cycle, LSST produced 66 million candidate detections of main belt asteroids (MBAs) and near Earth objects (NEOs), of which 77% were spurious detections related to detector noise or image processing. Using the Moving Object Processing System, we were able to assemble single-night “tracklets” with negligible losses, but a purity of only 43%. The next stage of linking led to three-night orbits with data sets no more than 12 days in length, and it is at this stage that the false detections are readily removed from the data stream. Main-belt linkages were essentially complete and 99.8% pure. Similarly, only 0.02% of linked detections involving NEOs were spurious. On the other hand, NEO linking was 93.6% complete, indicating that 6.4% of potentially findable NEOs were not successfully linked. We believe that this rate can be improved with careful tuning of the MOPS linking algorithms. The NEO catalog was affected by main-belt confusion so that mis-linked MBAs appeared as NEOs, and many correctly linked MBAs were consistent with NEO orbits. We show that these cases arise primarily from MBAs detected at lower solar elongations and we postulate that this is an artifact of a one month simulation that will be readily resolved by surveying over many months.

Chesley, Steven R.↗