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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Coincident Observation of Lightning using Spaceborne Spectrophotometer and Ground-Level Electromagnetic Sensors

The present study aims at assessing a possible new way to reveal the properties of lightning flash, using spectrophotometric data obtained by FORMOSAT-2/ISUAL which is the first spaceborne multicolor lightning detector. The ISUAL data was analyzed in conjunction with ground ]based electromagnetic data obtained by Duke magnetic field sensors, NLDN, North Alabama Lightning Mapping Array (LMA), and Kennedy Space Center (KSC) electric field antennas. We first classified the observed events into cloud ]to ]ground (CG) and intra ]cloud (IC) lightning based on the Duke and NLDN measurements and analyzed ISUAL data to clarify their optical characteristics. It was found that the ISUAL optical waveform of CG lightning was strongly correlated with the current moment waveform, suggesting that it is possible to evaluate the electrical properties of lightning from satellite optical measurement to some extent. The ISUAL data also indicated that the color of CG lightning turned to red at the time of return stroke while the color of IC pulses remained unchanged. Furthermore, in one CG event which was simultaneously detected by ISUAL and LMA, the observed optical emissions slowly turned red as the altitude of optical source gradually decreased. All of these results indicate that the color of lightning flash depends on the source altitude and suggest that spaceborne optical measurement could be a new tool to discriminate CG and IC lightning. In the presentation, we will also show results on the comparison between the ISUAL and KSC electric field data to clarify characteristics of each lightning process such as preliminary breakdown, return stroke, and subsequent upward illumination.

Adachi, Toru↗
NASA NTRS2013

Estimating Ground-Level PM(sub 2.5) Concentrations in the Southeastern United States Using MAIAC AOD Retrievals and a Two-Stage Model

Previous studies showed that fine particulate matter (PM(sub 2.5), particles smaller than 2.5 micrometers in aerodynamic diameter) is associated with various health outcomes. Ground in situ measurements of PM(sub 2.5) concentrations are considered to be the gold standard, but are time-consuming and costly. Satellite-retrieved aerosol optical depth (AOD) products have the potential to supplement the ground monitoring networks to provide spatiotemporally-resolved PM(sub 2.5) exposure estimates. However, the coarse resolutions (e.g., 10 km) of the satellite AOD products used in previous studies make it very difficult to estimate urban-scale PM(sub 2.5) characteristics that are crucial to population-based PM(sub 2.5) health effects research. In this paper, a new aerosol product with 1 km spatial resolution derived by the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm was examined using a two-stage spatial statistical model with meteorological fields (e.g., wind speed) and land use parameters (e.g., forest cover, road length, elevation, and point emissions) as ancillary variables to estimate daily mean PM(sub 2.5) concentrations. The study area is the southeastern U.S., and data for 2003 were collected from various sources. A cross validation approach was implemented for model validation. We obtained R(sup 2) of 0.83, mean prediction error (MPE) of 1.89 micrograms/cu m, and square root of the mean squared prediction errors (RMSPE) of 2.73 micrograms/cu m in model fitting, and R(sup 2) of 0.67, MPE of 2.54 micrograms/cu m, and RMSPE of 3.88 micrograms/cu m in cross validation. Both model fitting and cross validation indicate a good fit between the dependent variable and predictor variables. The results showed that 1 km spatial resolution MAIAC AOD can be used to estimate PM(sub 2.5) concentrations.

aerosol optical depth↗
NASA NTRS1981

Ground level reflectance measurement techniques - An evaluation with emphasis on the importance of spectral calibration

The bandpasses, overflight conditions, and sensor geometry that will provide optimum target discrimination in remote-sensing studies can be determined only from spectral reflectance measurements made for various sun-target-sensor geometries, supplemented by model calculations which can be checked against field data. The accurate measurement of ground reflectance properties is critical to the design of future sensors and to the determination of imaging conditions. The current investigation has the objective to review typical methods of measuring spectral reflectance, to point out some of the problems inherent to reflectance measuring techniques, and to present a method of checking measurement accuracy.

Duggin, M. J.↗
NASA NTRS1978

Identification of the nu-2 vibration-rotation band of ammonia in ground level solar spectra

Comparison of infrared solar spectra in the 750 to 950 kayser region obtained during sunrise and sunset shows that a number of features due to the nu-2 NH3 band are present on the sunset spectra but are indicated by only a trace on the sunrise spectra. The sunset path shows approximately 0.007 atm-cm NH3, and the reason for the discrepancy between sunrise and sunset spectra is not known. The ground-based measurements at Denver were obtained with a 0.06 kayser resolution.

Murcray, D. G.↗
DOE OSTI2021

Deep Learning Estimation of Daily Ground–Level NO 2 Concentrations from Remote Sensing Data

The limited number of nitrogen dioxide (NO 2 ) surface measurements calls for the development of highly accurate approaches to estimating surface NO 2 concentrations. In this study, we leverage a new satellite instrument, the TROPOspheric Monitoring Instrument (TROPOMI), along with other predictor variables, to estimate daily surface NO 2 concentrations over Texas in 2019. We use the deep convolutional neural network (Deep-CNN), an advanced deep learning algorithm, to obtain estimates and achieve a correlation coefficient (R) of 0.91, an index of agreement (IOA) of 0.95, and a mean absolute bias (MAB) of 1.75 ppb in surface NO 2 estimation. Additionally, we leverage a novel approach, SHapley Additive exPlanations (SHAP), to describe how Deep-CNN understands each predictor variable. The SHAP results show that the Deep-CNN model has an advanced understanding of the dataset, revealing that TROPOMI closely captures levels of NO 2 . In addition, we show the superiority of our Deep-CNN model at estimating surface NO 2 over other well-known machine learning and regression models in the field, including the support vector machines (SVM), random forest (RF), and multiple linear regression (MLR). Although SVM and RF show strong capabilities at estimating surface NO 2 concentrations, their accuracy is inferior to that of the Deep-CNN model, ranking second and third in model accuracy in this study. The MLR, however, shows a poor ability at NO 2 estimation and ranks last among all models. Furthermore, testing the impact of sample size on model performance, we also show that, compared to other models, Deep-CNN needs more samples to trigger its strength at surface NO 2 estimation.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1975

Comparison between reflectivity statistics at heights of 3 and 6 km and rain rate statistics at ground level

An experiment was conducted to study the relations between the empirical distribution functions of reflectivity at specified locations above the surface and the corresponding functions at the surface. A bistatic radar system was used to measure continuously the scattering cross section per unit volume at heights of 3 and 6 km. A frequency of 3.7 GHz was used in the tests. It was found that the distribution functions for reflectivity may significantly change with height at heights below the level of the melting layer.

Crane, R. K.↗
NASA NTRS1987

Probable detection of solar neutrons by ground-level neutron monitors during STIP interval 16

The third solar neutron event detected by Earth-orbiting spacecraft was observed during STIP Interval XVI. The solar flare beginning at 2356 UT on 24 April l984 produced a variety of emissions including gamma rays and solar neutrons. The neutrons were observed by the SMM satellite and the neutron-decay protons were observed on the ISEE-3 spacecraft. Between 0000 and 0010 UT on 25 April an increase of 0.7 and 1.7 percent was recorded by neutron monitors at Tokyo (Itabashi) and Morioka, Japan. These stations were located about 42 degrees from the sub-solar point, and consequently, these is approximately 1400 grams of atmosphere between the incident neutrons at the top of the atmosphere and their detection on the Earth's surface. Nevertheless, the time coincidence of a small increase in the total counting rate of two independent neutron monitors indicates the presence of solar neutrons with energies greater than 400 MeV at the top of the Earth's atmosphere. The small increases in the counting rate emphasize the difficulty in identifying similar events using historical neutron monitor data.

Shea, M. A.↗
NASA NTRS1989

Ground-level detection of LF and MF high latitude terrestrial emissions

Two brief experimental campaigns have been conducted in Norway and in Alaska, using four commercial comunications receivers, to confirm the suspected existence of auroral phenomena-associated radio noise in the 100 kHz range. While the Alaskan experiment yielded signals attributable to auroral processes on nearly one-half of the nights monitored, the Norway data identified only one such event. A proposed geophysical observatory in Antarctica is noted to furnish an ideal platform for experiments of this type.

Benson, Robert F.↗