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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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18 records
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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 NTRS1999

Performance of Nickel-Cadmium Batteries on the GOES-1 Series of Weather Satellites

This is an errata from an original paper published in the 1997 NASA Aerospace Battery workshop proceedings. A minor change was made to the second equation on page 98 and table 4 was revised during the final preparation of the paper. These changes were inadvertently left out of the final proceedings. These pages are reproduced in their entirety.

Singhal, Sat P.↗
NASA NTRS1977

Potential applications of digital, visible, and infrared data from geostationary environmental satellites

An hourly, digital data base from the Visible/Infrared Spin-Scan Radiometer (VISSR) instrument on the GOES-1 and SMS-2 geostationary satellites is described. Several examples of developmental applications of these quantitative digital data are presented. These include a review of recent attempts to develop products that are of use to meteorologists who provide services to aviation, agriculture, forestry, hydrology, oceanography, and climatology. The sample products include high resolution thermal gradients of land and ocean surfaces, thermal change analyses, fruit frost/freeze application, cloud-top altitude analysis, analysis of hurricane characteristics, and analyses of solar insolation.

Miller, D. B.↗
NASA NTRS1977

The operational processing of wind estimates from cloud motions: Past, present and future

Current NESS winds operations provide approximately 1800 high quality wind estimates per day to about twenty domestic and foreign users. This marked improvement in NESS winds operations was the result of computer techniques development which began in 1969 to streamline and improve operational procedures. In addition, the launch of the SMS-1 satellite in 1974, the first in the second generation of geostationary spacecraft, provided an improved source of visible and infrared scanner data for the extraction of wind estimates. Currently, operational winds processing at NESS is accomplished by the automated and manual analyses of infrared data from two geostationary spacecraft. This system uses data from SMS-2 and GOES-1 to produce wind estimates valid for 00Z, 12Z and 18Z synoptic times.

Novak, C.↗
NASA NTRS1978

NASA to launch NOAA's GOES-C earth monitoring satellite

NASA's launch of the GOES-C geostationary satellite from Kennedy Space Center, Florida is planned for June 16, 1978. The launch vehicle is a three stage Delta 2914. As its contribution, GOES-C will contribute information from a data sparse area of the world centered in the Indian Ocean. GOES-C will replace GOES-1 and will become GOES-3 once it has successfully orbited at 35,750 kilometers (22,300 miles). NASA's Spaceflight Tracking and Data Network (STDN) will provide support for the mission. Included in the article are: (1) Delta launch vehicle statistics, first, second and third stages; (2) Delta/GOES-C major launch events; (3) Launch operations; (4) Delta/GOES-C personnel.

Source record↗
NASA NTRS1978

The benefits of using short interval satellite images to derive winds for tropical cyclones

During the 1975, 1976, and 1977, NOAA's National Environmental Satellite Service and NASA's Goddard Space Flight Center conducted a cooperative program to determine the optimum resolution and frequency of satellite images for deriving winds to study and forecast tropical cyclones. Rapid scan images were obtained at 7.5 minute interval from SMS-2 for hurricane Eloise and cyclone Caroline, and at 3 minute intervals from GOES-1 for tropical storms Belle, Holly, and Anita. Cloud motions were derived from these images using the Atmospheric and Oceanographic Information Processing System. Winds that were derived from the movement of upper and lower tropospheric level clouds using rapid scan data were compared with the 15 and 30 minute interval data. Greater than 10 (5) times as many clouds could be tracked to obtain winds using 3 and 7.5 minute rapid scan images as when using 15 or 30 minute interval images. A few bright areas within the central dense overcast which appeared to be moving with the winds at low levels were tracked.

Rodgers, E.↗
NASA NTRS1978

The operational feasibility of orbit and attitude determination for the Geostationary Operational Environmental Satellite (SMS/GEOS) using only imagery data

Experimental results from three evaluation periods on three geostationary spacecraft (SMS-2, GOES-1, and GOES-2) are presented. It is shown that using existing landmark extraction and identification techniques (1) for east geostationary spacecraft, a high quality orbit and attitude state is maintained with imagery data only, and (2) for west geostationary spacecraft, a high quality orbit and attitude state is recovered with imagery data only in approximately seven days.

Mack, E.↗
NASA NTRS1979

Satellite-sensed winter nocturnal temperature patterns of the Everglades Agricultural Area

Surface temperature patterns of drained organic soil farmland in the Everglades Agricultural Area south of Lake Okeechobee, Florida, were studied using GOES-1 satellite infrared digital data for the winters of 1976-77 and 1977-78. Local thermal features were explained in terms of soil types, soil depths and climate modification caused by organic soil drainage. A cold-prone area was delineated in the Everglades Agricultural Area with satellite data. The winter nighttime surface temperatures of this area were more characteristic of north central Florida, approximately 370 km further north, than of surrounding areas of mineral soil or undrained organic soil.

Chen, E.↗
NASA NTRS1981

Monitoring tropical cyclone intensity using wind fields derived from short-interval satellite images

Rapid scan visible images from the Visible Infrared Spin Scan Radiometer sensor on board SMS-2 and GOES-1 were used to derive high resolution upper and lower tropospheric environmental wind fields around three western Atlantic tropical cyclones (1975-78). These wind fields were used to derive upper and lower tropospheric areal mean relative vorticity and their differences, the net relative angular momentum balance and upper tropospheric mass outflow. These kinematic parameters were shown by studies using composite rawinsonde data to be strongly related to tropical cyclone formation and intensity changes. Also, the role of forced synoptic scale subsidence in tropical cyclone formation was examined. The studies showed that satellite-derived lower and upper tropospheric wind fields can be used to monitor and possibly predict tropical cyclone formation and intensity changes. These kinematic analyses showed that future changes in tropical cyclone intensity are mainly related to the "spin-up" of the storms by the net horizontal transport of relative angular momentum caused by convergence of cyclonic vorticity in the lower troposphere and to a lesser extent the divergence of anticyclone vorticity in the upper troposphere.

Rodgers, E. B.↗
NASA NTRS1983

Monitoring tropical-cyclone intensity using environmental wind fields derived from short-interval satellite images

The feasibility of predicting changes in tropical storm intensity based on satellite observations of the dynamical relationships between the large-scale upper and lower tropospheric circulations surrounding the cyclone and the characteristics of the storm's inner core is studied. Rapid-scan visible images from the SMS-1 and GOES-1 satellites were used to examine the local change in relative angular momentum (RAM), the lower and upper tropospheric environmental areal mean relative vorticity and transverse circulation on three consecutive days for tropical storms Caroline (August, 1975), Anita (August and September, 1977) and Ella (September, 1978). The three case studies suggest that storm intensification may be predicted from the storm's local change of net RAM, with this quantity best correlated with storm intensification after a time lag of 6 hours. Intensification is also found to be related to the environmental lower and upper tropospheric areal-mean relative vorticity, and to the upper tropospheric environmental circulation, which acts either to hinder or to enhance the storm's anticyclonic outflow channels.

Rodgers, E.↗
NASA NTRS1984

Remote sensing of severe convective storms over Qinghai-Xizang Plateau

The American satellite, GOES-1 was moved to the Indian Ocean at 58 deg E during the First GARP Global Experiment (FGGE). The Qinghai-Xizang Plateau significantly affects the initiation and development of heavy rainfall and severe storms in China, just as the Rocky Mountains influence the local storms in the United States. Satelite remote sensing of short-lived, meso-scale convective storms is particularly important for covering a huge area of a high elevation with a low population density, such as the Qinghai-Xizang Plateau. Results of this study show that a high growth rate of the convective clouds, followed by a rapid collapse of the cloud top, is associated with heavy rainfall in the area. The tops of the convective clouds developed over the Plateau lie between the altitudes of the two tropopauses, while the tops of convective clouds associated with severe storms in the United States usually extend much above the tropopause.

Hung, R. J.↗
NASA NTRS1987

Satellite remote sensing of cloud distribution and amount of rainfall over the Tibet Plateau area of China

The use of images from the GOES-1 satellite to study mesoscale convective clouds over the Tibet Plateau region in China is discussed. The correlation between the quantity of rainfall observed at the ground and the cloud volume dissipation per unit area as determined from satellite IR imagery is examined. It is shown that this relationship is almost linear for the rainfall rate exceeding 8 mm/day.

Hung, R. J.↗
NASA NTRS1992

Geostationary Operational Environmental Satellite (GOES-N report). Volume 2: Technical appendix

The contents include: operation with inclinations up to 3.5 deg to extend life; earth sensor improvements to reduce noise; sensor configurations studied; momentum management system design; reaction wheel induced dynamic interaction; controller design; spacecraft motion compensation; analog filtering; GFRP servo design - modern control approach; feedforward compensation as applied to GOES-1 sounder; discussion of allocation of navigation, inframe registration and image-to-image error budget overview; and spatial response and cloud smearing study.

Source record↗
NASA NTRS1994

Control structure interaction/optimized design

The objective of this study is to apply the integrated design methodology to the mature GOES-1 spacecraft design, and to assess the possible advantages to be gained using this approach over the conventional sequential design approach used for the current design. In the process, the development of this technology into a tool that can be utilized for future near-term spacecraft designs is emphasized.

Mclaren, Mark↗
NASA NTRS2004

Next Generation Geostationary Operational Environmental Satellite (GOES-R Series): A Space Segment Overview

The next-generation National Oceanic and Atmospheric Administration (NOAA) Geostationary Operational Environmental Satellite (GOES-R series) is currently being developed by NOAA in cooperation with the National Aeronautics and Space Administration (NASA). The GOES-R series satellites represents a significant improvement in spatial, temporal, and spectral observations (several orders of magnitude) over the capabilities of the currently operational GOES-1 series and the about to be launched GOES-N series satellite. The GOES-R series will incorporate technically advanced third-generation instruments and spacecraft enhancements to meet evolving observational requirements of forecasting for the era 2012-2025. The GOES-R instrument complement being developed includes a Advanced Baseline Imager (ABI), a Hyperspectral Environmental Suite (HES), a GEO Lighting Mapper (GLM), a Solar Imaging Suite (SIS) and a Space Environment In-Situ Suite (SEISS). Also, candidates for a number of GOES-R Pre-Planned Product Improvements (P(sup 3)Is) includes a Geo microwave Sounder, a Coronograph, a Hyperspectral Imager, and a Solar Irradiance Sensor. Currently, the GOES-R Space Segment architecture is being evaluated as part of a GOES-R system end-to-end architecture study. The GOES-R notional baseline architecture is a constellation of two satellites (A-sat and B-sat) each nominally located at 75 degrees west longitude and at 135 degrees west longitude at geostationary altitude, 0 degrees inclination. The primary mission of the A-sat is to provide imaging from the ABI. The A-sat will also contain the SIS and the GLM. The primary mission of the B-sat is to provide sounding of the hemispherical disk of the earth from the HES. The B-sat also contains the SEISS. Both satellites have mesoscale capabilities for severe weather sounding or imaging. This paper overviews the GOES-R Space Segment development including satellite constellation trade-off, improvements and differences between the current and future instrument and spacecraft capabilities, and technology infusion.

Krimchansky, Alexander↗
NASA NTRS2017

H31G-1596: DeepSAT's CloudCNN: A Deep Neural Network for Rapid Cloud Detection from Geostationary Satellites

Cloud and cloud shadow detection has important applications in weather and climate studies. It is even more crucial when we introduce geostationary satellites into the field of terrestrial remote sensing. With the challenges associated with data acquired in very high frequency (10-15 mins per scan), the ability to derive an accurate cloud shadow mask from geostationary satellite data is critical. The key to the success for most of the existing algorithms depends on spatially and temporally varying thresholds,which better capture local atmospheric and surface effects.However, the selection of proper threshold is difficult and may lead to erroneous results. In this work, we propose a deep neural network based approach called CloudCNN to classify cloudshadow from Himawari-8 AHI and GOES-16 ABI multispectral data. DeepSAT's CloudCNN consists of an encoderdecoder based architecture for binary-class pixel wise segmentation. We train CloudCNN on multi-GPU Nvidia Devbox cluster, and deploy the prediction pipeline on NASA Earth Exchange (NEX) Pleiades supercomputer. We achieved an overall accuracy of 93.29% on test samples. Since, the predictions take only a few seconds to segment a full multispectral GOES-16 or Himawari-8 Full Disk image, the developed framework can be used for real-time cloud detection, cyclone detection, or extreme weather event predictions.

GOES-1↗