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At least 253 records · Page 14
All sourcesNASA NTRSDOE OSTI
DOE OSTI2011

SUB-THz AND H{alpha} ACTIVITY DURING THE PREFLARE AND MAIN PHASES OF A GOES CLASS M2 EVENT

Radio and optical observations of the evolution of flare-associated phenomena have shown an initial and rapid burst at 0.4 THz only followed subsequently by a localized chromospheric heating producing an H{alpha} brightening with later heating of the whole active region. A major instability occurred several minutes later producing one impulsive burst at microwaves only, associated with an M2.0 GOES X-ray flare that exhibited the main H{alpha} brightening at the same site as the first flash.The possible association between long-enduring time profiles at soft X-rays, microwaves, H{alpha}, and sub-THz wavelengths is discussed. In the decay phase, the H{alpha} movie shows a disrupting magnetic arch structure ejecting dark, presumably chromospheric, material upward. The time sequence of events suggests genuine interdependent and possibly non-thermal instabilities triggering phenomena, with concurrent active region plasma heating and material ejection.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2013

LONGITUDINAL AND RADIAL DEPENDENCE OF SOLAR ENERGETIC PARTICLE PEAK INTENSITIES: STEREO, ACE, SOHO, GOES, AND MESSENGER OBSERVATIONS

Simultaneous measurements of solar energetic particle (SEP) events by two or more of the spacecraft located near 1 AU during the rising phase of solar cycle 24 (i.e., STEREO-A, STEREO-B, and near-Earth spacecraft such as ACE, SOHO, and GOES) are used to determine the longitudinal dependence of 71-112 keV electron, 0.7-3 MeV electron, 15-40 MeV proton, and 25-53 MeV proton peak intensities measured in the prompt component of SEP events. Distributions of the peak intensities for the selected 35 events with identifiable solar origin are approximated by the form exp [ - ({phi} - {phi}{sub 0}){sup 2}/2{sigma}{sup 2}], where {phi} is the longitudinal separation between the parent active region and the footpoint of the nominal interplanetary magnetic field (IMF) line connecting each spacecraft with the Sun, {phi}{sub 0} is the distribution centroid, and {sigma} determines the longitudinal gradient. The MESSENGER spacecraft, at helioradii R < 1 AU, allows us to determine a lower limit to the radial dependence of the 71-112 keV electron peak intensities measured along IMF lines. We find five events for which the nominal magnetic footpoint of MESSENGER was less than 20 Degree-Sign apart from the nominal footpoint of a spacecraft near 1 AU. Although the expected theoretical radial dependence for the peak intensity of the events observed along the same field line can be approximated by a functional form R {sup -{alpha}} with {alpha} < 3, we find two events for which {alpha} > 3. These two cases correspond to SEP events occurring in a complex interplanetary medium that favored the enhancement of peak intensities near Mercury but hindered the SEP transport to 1 AU.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2019

Conditional Generative Adversarial Networks (cGANs) for Near Real-Time Precipitation Estimation from Multispectral GOES-16 Satellite Imageries—PERSIANN-cGAN

In this paper, we present a state-of-the-art precipitation estimation framework which leverages advances in satellite remote sensing as well as Deep Learning (DL). The framework takes advantage of the improvements in spatial, spectral and temporal resolutions of the Advanced Baseline Imager (ABI) onboard the GOES-16 platform along with elevation information to improve the precipitation estimates. The procedure begins by first deriving a Rain/No Rain (R/NR) binary mask through classification of the pixels and then applying regression to estimate the amount of rainfall for rainy pixels. A Fully Convolutional Network is used as a regressor to predict precipitation estimates. The network is trained using the non-saturating conditional Generative Adversarial Network (cGAN) and Mean Squared Error (MSE) loss terms to generate results that better learn the complex distribution of precipitation in the observed data. Common verification metrics such as Probability Of Detection (POD), False Alarm Ratio (FAR), Critical Success Index (CSI), Bias, Correlation and MSE are used to evaluate the accuracy of both R/NR classification and real-valued precipitation estimates. Statistics and visualizations of the evaluation measures show improvements in the precipitation retrieval accuracy in the proposed framework compared to the baseline models trained using conventional MSE loss terms. This framework is proposed as an augmentation for PERSIANN-CCS (Precipitation Estimation from Remotely Sensed Information using Artificial Neural Network- Cloud Classification System) algorithm for estimating global precipitation.

42 ENGINEERING↗
DOE OSTI2024

Parallax-corrected VISST-derived pixel-level products from satellite GOES-16

The NASA Langley group led by William Smith produced GOES-16 satellite cloud retrievals over an approximate 10 by 10 degree region over the CACTI field campaign location. These retrievals are described here: https://www.arm.gov/capabilities/vaps/visst and are available for download here . They use algorithms historically called VISST that are now referred to as SatCORPS. More information can be found in Trepte et al. (2019), Minnis et al. (2021), and Yost et al. (2021). If using this dataset, please cite these references, the CACTI VISST dataset DOI found at the download link above, and this dataset’s DOI. The CACTI VISST pixel-level retrievals are on a 2 km spatial grid and available every 15 minutes (every 10 minutes late in the campaign), producing 21,765 files for the entire field campaign between October 2018 and April 2019. They are not corrected for parallax error, which is an offset in the actual geographical location of a cloud above the surface due to the satellite viewing the cloud partly from the side off nadir. This dataset applies a correction for parallax using the location relative to the satellite and the retrieved cloud top height above the surface, which allows the dataset to be geo-located with surface-based observations. The parallax correction for each location depends on the longitude, latitude and cloud top height above ground level (AGL) for that longitude and latitude in the original VISST files. The cloud top height AGL requires first computing the surface elevation at each VISST grid point. Data from the Advanced Spaceborne Thermal Emission and Reflection (ASTER) Global Digital Elevation Map Version 3 at 30-m resolution is projected onto the VISST grid using conservative coarsening (conserving surface elevation) in the xESMF Python package. The surface elevation is then subtracted from the VISST-retrieved cloud top height above mean sea level. These cloud top heights AGL are then combined with longitude and latitude to estimate the latitude and longitude corrections. Due to variability in cloud top height, the parallax shifts produce an irregular grid of values since higher cloud tops are shifted further than lower cloud tops. A ball tree-based neighbor search with Haversine distance is performed using the Python-based scikit-learn library to find the nearest VISST grid point to each parallax correction-shifted point. The data value of the shifted point is then assigned to that VISST grid point. In this manner, the irregular geographical shifts to correct for parallax are projected back to the rectilinear VISST grid. Because relatively higher clouds should obscure lower clouds, the variable values for the highest cloud top are preferentially chosen if two or more values are assigned to a grid point. The parallax correction should be viewed as an improved but still imperfect estimation of the cloud top locations, largely because the cloud top height is an imperfect retrieval. Please see the attached README document for further information. Users are encouraged to contact the authors with any additional questions.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1979

Convective rainfall estimation from digital GOES-1 infrared data

An investigation was conducted to determine the feasibility of developing and objective technique for estimating convective rainfall from digital GOES-1 infrared data. The study area was a 240 km by 240 km box centered on College Station, Texas (Texas A and M University). The Scofield and Oliver (1977) rainfall estimation scheme was adapted and used with the digital geostationary satellite data. The concept of enhancement curves with respect to rainfall approximation is discussed. Raingage rainfall analyses and satellite-derived rainfall estimation analyses were compared. The correlation for the station data pairs (observed versus estimated rainfall amounts) for the convective portion of the storm was 0.92. It was demonstrated that a fairly accurate objective rainfall technique using digital geostationary infrared satellite data is feasible. The rawinsonde and some synoptic data that were used in this investigation came from NASA's Atmospheric Variability Experiment, AVE 7.

Sickler, G. L.↗
NASA NTRS1979

Analysis of NOAA-MSFC GOES X-ray telescope

The general telescope system was assumed to be a paraboloid-hyperboloid in a Wolter Type 1 configuration. The equations which specify the telescope parameters and the resolution as a function of the collecting area are discussed as well as the spot size and point response function for off-axis rays. The measured resolution of the Goddard ATM X-ray telescope (S-056) is compared to the rms blur circle radius and the full width half maximum of the line spread function. An empirical scaling formula, Eq. 26, which transforms the rms blur circle radius into a more accurate measure of resolution, is introduced. The geometrical imaging properties of the proposed NOAA-MSFC GOES X-ray telescope are considered. Conclusions and alternate mirror designs are included.

Shealy, D. L.↗
NASA NTRS1980

Application of the SRI cloud-tracking technique to rapid-scan GOES observations

An automatic cloud tracking system was applied to multilayer clouds associated with severe storms. The method was tested using rapid scan observations of Hurricane Eloise obtained by the GOES satellite on 22 September 1975. Cloud tracking was performed using clustering based either on visible or infrared data. The clusters were tracked using two different techniques. The data of 4 km and 8 km resolution of the automatic system yielded comparable in accuracy and coverage to those obtained by NASA analysts using the Atmospheric and Oceanographic Information Processing System.

Wolf, D. E.↗
NASA NTRS1980

Orbit/attitude estimation for the GOES spacecraft using VAS landmark data

A software system is described which provides for batch least squares estimation of spacecraft orbit, attitude, and camera bias parameters using image data from the Geostationary Operational Environmental Satellites (GOES). The image data are obtained by the Visible and Infrared Spin Scan Radiometer (VISSR) Atmospheric Sounder (VAS). The resulting estimated parameters are used for absolute image registration. Operating in the Digital Equipment Corporation (DEC) PDP-11/70 computer, the FORTRAN system also includes the capabilities of image display and manipulations. An overview of the system is presented as well as some numerical results obtained from observations taken by the SMS-2 satellite over a 3 day interval in August 1975.

Sielski, H.↗
NASA NTRS1980

Gravity waves and GOES IR data study of an isolated tornadic storm on 29 May 1977

Enhanced convection-initiated gravity waves associated with an isolated tornado in the absence of a squall line are investigated. Ray-tracing computations based on data observed on May 29, 1977 indicated that the wave sources were located in north-central Oklahoma. Comparison with a radar echo map during the time period when the waves were excited showed that the waves were generated by an isolated cloud with enhanced convection. GOES infrared digital data during the time period from wave excitation to tornado touchdown were analyzed. Results showed that the cloud where the gravity waves were excited was characterized by both a very low temperature at the cloud top and a very high expansion rate of the cold cloud-top area. The lead time between the excitation of the gravity waves and the tornado touchdown is discussed in conjunction with the growth rate of the clouds associated with the tornado.

Hung, R. J.↗
NASA NTRS1981

Characteristics, of TIROS, GOES, DMSP and LANDSAT Systems

The characteristics of the TIROS, GOES, DMSP and LANDSAT systems of satellites are described. The data listed for each system are altitude of orbit, inclination/position, orbit type, orbits per day, expected operational lifetime and the sensor systems. The sensor systems are described as to wavelength of each channel, resolution, field of view and other pertinent information. Data information such as availability rate, collection method, primary use/application and how to obtain additional information is also given.

Gray, T. I., Jr.↗
NASA NTRS1980

GOES infrared study of tornadic storms

Enhanced convection-initiated gravity waves associated with an isolated tornado in the absence of a squall line are investigated. Ray tracing computations based on data observed on May 29, 1977 indicated that the wave sources were located in north central Oklahoma. Comparison with a radar echo map during the time period when the waves were excited showed that the waves were generated by an isolated cloud with enhanced convection. GOES infrared digital data during the time period from wave excitation to tornado touchdown were analyzed. Results showed that the cloud where the gravity waves were excited was characterized by both a very low temperature at the cloud top and a very high expansion rate of the cold cloud tops area. The lead time between the excitation of the gravity waves and the tornado touchdown is discussed in conjunction with the growth rate of the clouds associated with the tornado.

Hung, R. J.↗
NASA NTRS1981

Automatic cloud tracking applied to GOES and Meteosat observations

An improved automatic processing method for the tracking of cloud motions as revealed by satellite imagery is presented and applications of the method to GOES observations of Hurricane Eloise and Meteosat water vapor and infrared data are presented. The method is shown to involve steps of picture smoothing, target selection and the calculation of cloud motion vectors by the matching of a group at a given time with its best likeness at a later time, or by a cross-correlation computation. Cloud motion computations can be made in as many as four separate layers simultaneously. For data of 4 and 8 km resolution in the eye of Hurricane Eloise, the automatic system is found to provide results comparable in accuracy and coverage to those obtained by NASA analysts using the Atmospheric and Oceanographic Information Processing System, with results obtained by the pattern recognition and cross correlation computations differing by only fractions of a pixel. For Meteosat water vapor data from the tropics and midlatitudes, the automatic motion computations are found to be reliable only in areas where the water vapor fields contained small-scale structure, although excellent results are obtained using Meteosat IR data in the same regions. The automatic method thus appears to be competitive in accuracy and coverage with motion determination by human analysts.

Endlich, R. M.↗
NASA NTRS1982

The design and development of GOES

The design and development of the GOES satellites is discussed. The configuration of the satellite and the operation and capabilities of its subsystems are detailed. Spacecraft performance characteristics are given.

Fermelia, L. R.↗
NASA NTRS1977

Visible infrared spin-scan radiometers (VISSR) for the Geostationary Operational Environmental Satellite (GOES) B and C application

Two visible infrared spin scan radiometer (VISSR) instruments provided for the Geostationary Operational Environmental Satellite B and C (GOES B and C) spacecrafts are described. The instruments are identical to those supplied previously are summarized. A significant number of changes primarily involving corrections of drawing errors and omissions were also performed. All electrical changes were breadboarded (where complexity required this), were incorporated into the test module, and subjected to verification of proper operation throughout fall instrument temperature range. Evaluation of the changes also included design operating safety margins to account for component variations and life.

Source record↗
NASA NTRS1983

Case studies using GOES infrared data and a planetary boundary layer model to infer regional scale variations in soil moisture

Modeled temperature data from a one-dimensional, time-dependent, initial value, planetary boundary layer model for 16 separate model runs with varying initial values of moisture availability are applied, by the use of a regression equation, to longwave infrared GOES satellite data to infer moisture availability over a regional area in the central U.S. This was done for several days during the summers of 1978 and 1980 where a large gradient in the antecedent precipitation index (API) represented the boundary between a drought area and a region of near normal precipitation. Correlations between satellite derived moisture availability and API were found to exist. Errors from the presence of clouds, water vapor and other spatial inhomogeneities made the use of the measurement for anything except the relative degree of moisture availability dubious.

Rose, F. G.↗
NASA NTRS1984

Search for solar signals in GOES imagery and cloud climatology analysis

The digitization and analysis of 16mm GOES IR imagery to identify spatial and temporal variation in clouds is discussed, along with a cloud climatology analysis. Recently added to the Interactive Graphics Package was a Computer Image Analysis System. This system allows many new imaging techniques. One of the possibilities is the analysis of overall light intensity variations in six 10 degree square boxes across the intertropical convergence zone. This technique is discussed, as is a preliminary analysis of unnormalized data.

Markson, R. J.↗
NASA NTRS1984

Automated mesoscale winds derived from GOES multispectral imagery

An automated technique for extracting mesoscale winds from sequences of GOES VISSR image pairs was developed, tested and configured for quasi-real time/research applications on a computing system which gives mesoscale wind estimates at the highest spatial/temporal resolution possible from the VISSR imagery down to a wind vector separation of 10 km. Preprocessing of imagery using IR resampling, VIS edge preserving filtering, and reduced VIS resolution averaging improved height assignments and vector extraction for 10, 15, and 30 min imagery. An objective quality control system provides much greater than 99% accuracy in eliminating questionable wind estimates. Automated winds generally have better spatial coverage and density, and have random error estimates half as large as the manual winds. Dynamical analysis of cloud wind divergence revealed temporally consistent convergence centers on the meso beta scale that are highly correlated with on going and future developing convective storms. The entire system of computer codes was successfully vectorized for execution on an array processor resulting in job turnaround in less than one hour.

Wilson, G. S.↗