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At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRS1981

Global ozone long-term trends from satellite measurements and the response to solar activity variations

Analysis of global ozone variations for the period April 1970 to December 1975 was performed by using the reprocessed Nimbus 4 backscattered ultraviolet (BUV) measurements of total ozone. A correlation coefficient of 0.97 is found between the 6-month running mean of global mean total ozone (filtered for mean semiannual, annual, and quasibiennial variations) and the 10.7-cm solar activity index. Correcting ozone for a time-dependent latitudinal bias relative to Dobson ozone measurements reduces to 2-3% the global mean ozone variation over the solar cycle. The solar ultraviolet variability required in a one-dimensional time-dependent radiative photochemical model to account for the observed ozone variation appears to be consistent with recent solar UV observations.

Keating, G. M.↗
NASA NTRS1980

A three-dimensional spacecraft-charging computer code

A computer code is described which simulates the interaction of the space environment with a satellite at geosynchronous altitude. Employing finite elements, a three-dimensional satellite model has been constructed with more than 1000 surface cells and 15 different surface materials. Free space around the satellite is modeled by nesting grids within grids. Applications of this NASA Spacecraft Charging Analyzer Program (NASCAP) code to the study of a satellite photosheath and the differential charging of the SCATHA (satellite charging at high altitudes) satellite in eclipse and in sunlight are discussed. In order to understand detector response when the satellite is charged, the code is used to trace the trajectories of particles reaching the SCATHA detectors. Particle trajectories from positive and negative emitters on SCATHA also are traced to determine the location of returning particles, to estimate the escaping flux, and to simulate active control of satellite potentials.

Rubin, A. G.↗
NASA NTRS1993

Addendum to the Proceedings of the Third International Mobile Satellite Conference (IMSC 1993)

Satellite-based mobile communications systems provide voice and data communications to users over a vast geographic area. The users may communicate via mobile or hand-held terminals, which may also provide access to terrestrial cellular communications services. This Third IMSC focuses on the increasing worldwide commercial activities in Mobile Satellite Services, along with technical advances in the field. Because of the large service areas provided by such systems, it is important to consider political and regulatory issues in addition to technical and user requirements issues. The official Proceedings presented in 11 sessions include: direct broadcast of audio programming from satellites; spacecraft technology; regulatory and policy considerations; hybrid networks for personal and mobile applications; advanced system concepts and analysis; propagation; and mobile terminal technology; and mobile antenna technology.

Kwan, Robert↗
NASA NTRS2016

Bayesian Methods for Longitudinal Trending in Probabilities of Collision

Satellites have become an integral part of modern life, supporting phone communication, television and radio broadcasting, internet access, and military activities. Indeed, it is difficult to imagine modern society without many of these technologies, especially in an age when the world is increasingly interconnected via long-distance communications. As of 2013, there were over one thousand operational satellites in orbit about Earth. About half of these active satellites are in Low-Earth Orbit (LEO, meaning an orbital period less than 225 minutes), which is where the International Space Station (ISS) conducts operations, along with other commercial missions such as earth observation and satellite telephone communications. An increasing amount of attention is being placed on protecting satellites in LEO, as the frequency of object launches and satellite fragmentation events has contributed to the proliferation of space debris, resulting in increased congestion.

Conjunction↗
NASA NTRS2003

Long-Range Solar Activity Predictions: A Reprieve from Cycle #24's Activity

We discuss the field of long-range solar activity predictions and provide an outlook into future solar activity. Orbital predictions for satellites in Low Earth Orbit (LEO) depend strongly on exospheric densities. Solar activity forecasting is important in this regard, as the solar ultra-violet (UV) and extreme ultraviolet (EUV) radiations inflate the upper atmospheric layers of the Earth, forming the exosphere in which satellites orbit. Rather than concentrate on statistical, or numerical methods, we utilize a class of techniques (precursor methods) which is founded in physical theory. The geomagnetic precursor method was originally developed by the Russian geophysicist, Ohl, using geomagnetic observations to predict future solar activity. It was later extended to solar observations, and placed within the context of physical theory, namely the workings of the Sun s Babcock dynamo. We later expanded the prediction methods with a SOlar Dynamo Amplitude (SODA) index. The SODA index is a measure of the buried solar magnetic flux, using toroidal and poloidal field components. It allows one to predict future solar activity during any phase of the solar cycle, whereas previously, one was restricted to making predictions only at solar minimum. We are encouraged that solar cycle #23's behavior fell closely along our predicted curve, peaking near 192, comparable to the Schatten, Myers and Sofia (1996) forecast of 182+/-30. Cycle #23 extends from 1996 through approximately 2006 or 2007, with cycle #24 starting thereafter. We discuss the current forecast of solar cycle #24, (2006-2016), with a predicted smoothed F10.7 radio flux of 142+/-28 (1-sigma errors). This, we believe, represents a reprieve, in terms of reduced fuel costs, etc., for new satellites to be launched or old satellites (requiring reboosting) which have been placed in LEO. By monitoring the Sun s most deeply rooted magnetic fields; long-range solar activity can be predicted. Although a degree of uncertainty in the long-range predictions remains, requiring future monitoring, we do not expect the next cycle's + 2-sigma value will rise significantly above solar cycle #23's activity level.

Richon, K.↗
NASA NTRS2022

L-Band Microwave Satellite Data and Model Simulations Over the Dry Chaco to Estimate Soil Moisture, Soil Temperature, Vegetation and Soil Salinity

The Dry Chaco in South America is a semi-arid ecoregion prone to dryland salinization. In this region, we investigated coarse-scale surface soil moisture (SM), soil temperature, soil salinity and vegetation, using L-band microwave brightness temperature (TB) observations and retrievals from the Soil Moisture Ocean Salinity (SMOS) and Soil Moisture Active Passive (SMAP) satellite missions, Catchment Land Surface Model (CLSM) simulations, and in situ measurements within 26 sampled satellite pixels. Across these 26 sampled pixels, the satellite-based SM outperformed CLSM SM compared to field data, and forward L-band TB simulations derived from in situ SM and temperature performed better than those derived from CLSM estimates relative to SMOS TB observations. The surface salinity for the sampled pixels was on average only 4 mg/g and only locally influenced the TB simulations, when including salinity in the dielectric mixing model of the forward radiative transfer model (RTM) simulations. To explore the potential of retrieving salinity together with other RTM parameters to optimize TB simulations over the entire Dry Chaco, the RTM was inverted using 10 years of multi-angular SMOS TB data and constraints of CLSM SM and temperature. However, the latter modeled SM was not sufficiently accurate and factors such as open surface water were missing in the background constraints, so that the salinity retrievals effectively represented a bulk correction of the dielectric constant, rather than salinity per se. However, the retrieval of vegetation, scattering albedo and surface roughness resulted in realistic values.

L-Band↗
NASA NTRSDate not supplied

Using Satellite Soil Moisture and Rainfall in the Landslide Hazard Assessment for Situational Awareness System

The Landslide Hazard Assessment for Situational Awareness system(LHASA)gives a global view of landslide hazard in nearly real time. Currently, it is being upgraded from version 1 to version 2, which entails improvements along several dimensions. These include the incorporation of new predictors, machine learning, and new event-based landslide inventories. As a result, LHASA version 2 substantially improves on the prior performanceand introduces a probabilistic element to the global landslide nowcast. Data from the soil moisture active-passive (SMAP) satellite has been assimilated into a globally consistent data product with a latency less than 3 days, known as SMAP Level 4. In LHASA, thesedata representthe antecedent conditions prior to landslide-triggering rainfall. In some cases, soil moisture may have accumulated over aperiod of many months. The model behind SMAP Level 4 also estimates the amount of snow on the ground, which is an important factor in some landslide events. LHASA also incorporates this information as an antecedent condition that modulates the response torainfall. Slope, lithology, and active faults were also used as predictor variables. These factors can have a strong influence on where landslides initiate.LHASA relies on precipitation estimates from the Global Precipitation Measurement mission to identify the locations where landslides are most probable. The low latency and consistent global coverage of these data make them ideal for real-time applications at continental to global scales. LHASA relies primarily on rainfall from the last 24 hours to spothazardous sites, which is rescaled by the local 99thpercentile rainfall.However, the multi-day latency of SMAP requires the use of a 2-day antecedent rainfall variable to represent the accumulation of rain between the antecedent soil moisture and current rainfall. LHASA merges these predictors with XGBoost, a commonly used machine-learning tool, relying on historical landslide inventories to develop the relationship between landslide occurrence and various risk factors. The resulting model relies heavily on current daily rainfall, but other factors also play an important role. LHASA outputsthe probability oflandslide occurrence ona grid of roughly one kilometer over all continents from 60 North to 60 South latitude. Evaluation over the period 2019-2020 showsthat LHASA version 2 doubles the accuracy of the global landslide nowcast without increasing the global false alarm rate. LHASA also identifies the areas where the human exposure to landslide hazard is most intense. Landslide hazard is divided into 4 levels: minimal, low, moderate, and high. Next, the number of persons and the length of major roads (primary and secondary roads)within each of these areas is calculated for every second-level administrative district (county). These results can be viewedthrough a web portal hosted at the Goddard Space Flight Center. In addition, users can download daily hazard and exposure data.LHASAversion 2uses machine learning and satellite data to identify areas of probable landslide hazard within hours of heavy rainfall. Itsglobal maps are significantly more accurate, and it now includes rapid estimates of exposed populations and infrastructure. In addition, a forecast mode will be implemented soon.

Thomas Stanley↗
NASA NTRS1980

Infrared spectrum of Io, 2.8-5.2 microns

The reflectance spectrum of Io is presented from 2.8 to 5.2 microns demonstrating the full extent of the broad and deep spectral absorption between 3.5 and 4.8 microns. Laboratory spectra of nitrates and carbonates diluted with sulfur do not satisfactorily reproduce the Io spectrum, but new information based on recently discovered volcanic activity on the satellite lead to consideration of other classes of compounds reported by Fanale et al. (1979). It is concluded that the variability of the supply of condensible SO2 gas to the surface of Io, its removal by sublimination, and the temporal variations in the strength of the SO2 band may provide an index of volcanic activity on Io that can be monitored from the earth.

Cruikshank, D. P.↗
NASA NTRS1992

Ground Truth Studies - A hands-on environmental science program for students, grades K-12

The paper discusses the background and the objectives of the Ground Truth Studies (GTSs), an activity-based teaching program which integrates local environmental studies with global change topics, utilizing remotely sensed earth imagery. Special attention is given to the five key concepts around which the GTS programs are organized, the pilot program, the initial pilot study evaluation, and the GTS Handbook. The GTS Handbook contains a primer on global change and remote sensing, aerial and satellite images, student activities, glossary, and an appendix of reference material. Also described is a K-12 teacher training model. International participation in the program is to be initiated during the 1992-1993 school year.

Katzenberger, John↗
NASA NTRS1999

Plasma Pressure in the Topside Ionosphere

A previous three year NASA-funded project resulted in the first 2-D maps of magnetotail pressure, density and temperature. A proposal to continue the work was declined, but modest funding was provided for one year to ramp down of the work. During the phase-out year, we used a time when 5 DMSP satellites were simultaneously active to produce the first instantaneous partial image of the magnetotail. The results have been submitted to the proceedings of the 1998 Huntsville Meeting on "The New Millennium Magnetosphere: Integrating Imaging, Discrete Observations and Global Simulations". A method of inferring central plasma sheet (CPS) temperature, density, and pressure from ionospheric observations was developed under a previous 3-year grant. These particles properties are calculated from data taken by particle instruments on DMSP satellites. Ion spectra occurring in conjunction with electron acceleration events are excluded. Because of the variability of magnetotail stretching, mapping to the plasma sheet was done using a modified Tsyganenko 1989 magnetic field model adjusted to agree with the actual magnetotail stretch. On May 25, 1997, five DMSP satellites (F10-F14) passed through the southern hemisphere nightside oval within a 19 minute period. Attached is the first magnetotail image, which results from applying our technique to that data set.

Newell, Patrick T.↗
NASA NTRSDate not supplied

Study of Coronal Heating in Solar Active Regions Using Wide-Field Imaging Spectroscopy: Hinode EIS Slot Observations

Understanding the frequency of heating events that keep the coronal plasma at several million Kelvin above the photospheric temperature of~ 6000K, is one of the most important problems in solar astrophysics. Spectroscopic observations of the Sun in the extreme ultraviolet (EUV) indicate that the coronal plasma reaches temperatures from 1 to 5 MK in active regions. It is also established that temperature in active regions can vary strongly with time and, moreover, contain sub-regions that evolve and develop separately. Tracking the spatio-temporal evolution of temperature requires continuous observation of the entire active region via imaging and spectroscopy. Traditional slit imaging spectroscopy probes plasma heating in solar active regions through observations of diagnostic emission lines and the resulting data are spectrally pure. Here, imaging is performed through rastering process, which severely limits co-temporal observations and often can be slow to miss events that evolve at other portions of the active region. In contrast, wide-field imaging spectroscopy offer simultaneous coverage of a large field of view as well as obtain spectral information in the same direction. This data suffers from spatial-spectral confusion, and are called spectroheliograms. Using the state-of-the-art inversion techniques that are developed recently, now spectroheliogram data can be unfolded to yield spectrally pure maps of large fields over long duration of observations. We use wide slit data, usually referred as ‘slot’, from the EUV Imaging Spectrometer (EIS) onboard Hinode satellite, focusing on active region observations. Here, we present our study of coronal heating in an active region using a long duration Hinode EIS slot observation.

Active region heating↗
NASA NTRS1985

NASA scatterometer oceanic wind measurement system

Satellite scatterometers are active microwave radars designed to yield measurements of near surface horizontal wind velocity over the ocean. Scatterometers are unique in that they are the only existing microwave remote sensing instruments that allow measurements of both wind speed and wind direction. NASA will fly a scatterometer, NSCAT, aboard the Navy Ocean Remote Sensing System (N-ROSS) mission starting in late 1990. N-ROSS is a spaceborne ocean remote sensing system with a planned mission life of three years. In addition to the NSCAT, N-ROSS will have three other microwave instruments mounted on a single satellite flying in a near polar orbit: an altimeter; a special sensor microwave/imager (SSM/I); and a low frequency microwave radiometer. The NSCAT to be flown on N-ROSS is described.

Freilich, M.↗
NASA NTRS2006

The Art and Science of Long-Range Space Weather Forecasting

Long-range space weather forecasts are akin to seasonal forecasts of terrestrial weather. We don t expect to forecast individual events but we do hope to forecast the underlying level of activity important for satellite operations and mission pl&g. Forecasting space weather conditions years or decades into the future has traditionally been based on empirical models of the solar cycle. Models for the shape of the cycle as a function of its amplitude become reliable once the amplitude is well determined - usually two to three years after minimum. Forecasting the amplitude of a cycle well before that time has been more of an art than a science - usually based on cycle statistics and trends. Recent developments in dynamo theory -the theory explaining the generation of the Sun s magnetic field and the solar activity cycle - have now produced models with predictive capabilities. Testing these models with historical sunspot cycle data indicates that these predictions may be highly reliable one, or even two, cycles into the future.

Hathaway, David H.↗
DOE OSTI2017

Solar Flare Prediction Model with Three Machine-learning Algorithms using Ultraviolet Brightening and Vector Magnetograms

We developed a flare prediction model using machine learning, which is optimized to predict the maximum class of flares occurring in the following 24 hr. Machine learning is used to devise algorithms that can learn from and make decisions on a huge amount of data. We used solar observation data during the period 2010–2015, such as vector magnetograms, ultraviolet (UV) emission, and soft X-ray emission taken by the Solar Dynamics Observatory and the Geostationary Operational Environmental Satellite . We detected active regions (ARs) from the full-disk magnetogram, from which ∼60 features were extracted with their time differentials, including magnetic neutral lines, the current helicity, the UV brightening, and the flare history. After standardizing the feature database, we fully shuffled and randomly separated it into two for training and testing. To investigate which algorithm is best for flare prediction, we compared three machine-learning algorithms: the support vector machine, k-nearest neighbors (k-NN), and extremely randomized trees. The prediction score, the true skill statistic, was higher than 0.9 with a fully shuffled data set, which is higher than that for human forecasts. It was found that k-NN has the highest performance among the three algorithms. The ranking of the feature importance showed that previous flare activity is most effective, followed by the length of magnetic neutral lines, the unsigned magnetic flux, the area of UV brightening, and the time differentials of features over 24 hr, all of which are strongly correlated with the flux emergence dynamics in an AR.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRSDate not supplied

The Benefit of NASA's Atmosphere Observing System (AOS) Mission Lidar and Polarimeter Observations for Health and Air Quality Applications

The Atmosphere Observing System (AOS) seeks to explore fundamental questions of how interconnections between aerosols, clouds and precipitation impact our weather and climate, addressing real-world challenges to benefit society. AOS will provide key information to enhance the communities’ ability to improve weather and air quality forecasting today, seasonal to sub-seasonal changes in the near future, and societal challenges resulting from climate change in the decades to come. A fundamental component of the AOS mission is ensuring that health and air quality applications are considered to the greatest extent possible in mission design. As a result, the Applications Impact Team (AIT) was implemented to address this objective. The overarching goal of the AIT is to help improve the capacity for transitioning science to applications to make it possible to more quickly and effectively inform decisions that will directly benefit society. We seek to maximize AOS benefit to impact decisions through early engagement in the mission development phase in order to prepare stakeholders to apply observations as soon as AOS mission data becomes available. To support these efforts, we leverage existing and near future mission applications activities and initiatives, such as the NASA CALIPSO, MAIA, TEMPO, and PACE missions to form a framework to enhance health and air quality applications for AOS. The unique synergy between lidar and polarimeter instruments onboard the AOS constellation, as well as diurnally varying observations of aerosol profiles, will provide new opportunities to engage health and air quality stakeholders for forecasting, monitoring, and warning of hazardous events (e.g., wildfire smoke, volcanic ash) that impact human health. Engaging with existing missions helps identify and understand data needs, gaps and opportunities for current and future stakeholders, determine what aerosol data products are of highest value and use, and helps connect stakeholders with current mission data that can serve as AOS proxy data, among others. In this presentation, we provide an overview of AOS aerosol observations relevant for health and air quality applications, AIT activities and initiatives and how existing aerosol satellite missions and their applications activities can play a critical role in AOS applications development during mission design.

Melanie Follette-Cook↗