Initial Navigation Alignment of Optical Instruments on GOES-R

NASA Technical Reports Server (NTRS)

Isaacson, Peter J.; DeLuccia, Frank J.; Reth, Alan D.; Igli, David A.; Carter, Delano R.

2016-01-01

Post-launch alignment errors for the Advanced Baseline Imager (ABI) and Geospatial Lightning Mapper (GLM) on GOES-R may be too large for the image navigation and registration (INR) processing algorithms to function without an initial adjustment to calibration parameters. We present an approach that leverages a combination of user-selected image-to-image tie points and image correlation algorithms to estimate this initial launch-induced offset and calculate adjustments to the Line of Sight Motion Compensation (LMC) parameters. We also present an approach to generate synthetic test images, to which shifts and rotations of known magnitude are applied. Results of applying the initial alignment tools to a subset of these synthetic test images are presented. The results for both ABI and GLM are within the specifications established for these tools, and indicate that application of these tools during the post-launch test (PLT) phase of GOES-R operations will enable the automated INR algorithms for both instruments to function as intended.

NASA SPoRT GOES-R Proving Ground Activities

NASA Technical Reports Server (NTRS)

Stano, Geoffrey T.; Fuell, Kevin K.; Jedloec, Gary J.

2010-01-01

The NASA Short-term Prediction Research and Transition (SPoRT) program is a partner with the GOES-R Proving Ground (PG) helping prepare forecasters understand the unique products to come from the GOES-R instrument suite. SPoRT is working collaboratively with other members of the GOES-R PG team and Algorithm Working Group (AWG) scientists to develop and disseminate a suite of proxy products that address specific forecast problems for the WFOs, Regional and National Support Centers, and other NOAA users. These products draw on SPoRT s expertise with the transition and evaluation of products into operations from the MODIS instrument and the North Alabama Lightning Mapping Array (NALMA). The MODIS instrument serves as an excellent proxy for the Advanced Baseline Imager (ABI) that will be aboard GOES-R. SPoRT has transitioned and evaluated several multi-channel MODIS products. The true and false color products are being used in natural hazard detection by several SPoRT partners to provide better observation of land features, such as fires, smoke plumes, and snow cover. Additionally, many of SPoRT s partners are coastal offices and already benefit from the MODIS sea surface temperature composite. This, along with other surface feature observations will be developed into ABI proxy products for diagnostic use in the forecast process as well as assimilation into forecast models. In addition to the MODIS instrument, the NALMA has proven very valuable to WFOs with access to these total lightning data. These data provide situational awareness and enhanced warning decision making to improve lead times for severe thunderstorm and tornado warnings. One effort by SPoRT scientists includes a lightning threat product to create short-term model forecasts of lightning activity. Additionally, SPoRT is working with the AWG to create GLM proxy data from several of the ground based total lightning networks, such as the NALMA. The evaluation will focus on the vastly improved spatial coverage of the GLM, but with the trade-off of lower resolution compared to the NALMA. In addition to the above tasks, SPoRT will make these data available in the NWS next generation display software, AWIPS II. This has already been successfully completed for the two basic GLM proxies. SPoRT will use these products to train forecasters on the capabilities of GOES-R and foster feedback to develop additional products, visualizations, and requirements beneficial to end users needs. These developments and feedback will be made available to the GOES-R Proving Ground for the upcoming 2010 Spring Program in Norman, Oklahoma.

Advancements in the Development of an Operational Lightning Jump Algorithm for GOES-R GLM

NASA Technical Reports Server (NTRS)

Shultz, Chris; Petersen, Walter; Carey, Lawrence

2011-01-01

Rapid increases in total lightning have been shown to precede the manifestation of severe weather at the surface. These rapid increases have been termed lightning jumps, and are the current focus of algorithm development for the GOES-R Geostationary Lightning Mapper (GLM). Recent lightning jump algorithm work has focused on evaluation of algorithms in three additional regions of the country, as well as, markedly increasing the number of thunderstorms in order to evaluate the each algorithm s performance on a larger population of storms. Lightning characteristics of just over 600 thunderstorms have been studied over the past four years. The 2 lightning jump algorithm continues to show the most promise for an operational lightning jump algorithm, with a probability of detection of 82%, a false alarm rate of 35%, a critical success index of 57%, and a Heidke Skill Score of 0.73 on the entire population of thunderstorms. Average lead time for the 2 algorithm on all severe weather is 21.15 minutes, with a standard deviation of +/- 14.68 minutes. Looking at tornadoes alone, the average lead time is 18.71 minutes, with a standard deviation of +/-14.88 minutes. Moreover, removing the 2 lightning jumps that occur after a jump has been detected, and before severe weather is detected at the ground, the 2 lightning jump algorithm s false alarm rate drops from 35% to 21%. Cold season, low topped, and tropical environments cause problems for the 2 lightning jump algorithm, due to their relative dearth in lightning as compared to a supercellular or summertime airmass thunderstorm environment.

Early Transition and Use of VIIRS and GOES-R Products by NWS Forecast Offices

NASA Technical Reports Server (NTRS)

Fuell, Kevin K.; Smith, Mathew; Jedlovec, Gary

2012-01-01

The Visible Infrared Imaging Radiometer Suite (VIIRS) on the NPOESS Preparatory Project (NPP) satellite, part of the Joint Polar Satellite System (JPSS), and the ABI and GLM sensors scheduled for the GOES-R geostationary satellite will bring advanced observing capabilities to the operational weather community. The NASA Short-term Prediction Research and Transition (SPoRT) project at Marshall Space Flight Center has been facilitating the use of real-time experimental and research satellite data by NWS Weather Forecast Offices (WFOs) for a number of years to demonstrate the planned capabilities of future sensors to address particular forecast challenges through improve situational awareness and short-term weather forecasts. For the NOAA GOES-R Proving Ground (PG) activity, SPoRT is developing and disseminating selected GOES-R proxy products to collaborating WFOs and National Centers. SPoRT developed the a pseudo-Geostationary Lightning Mapper product and helped in the transition of the Algorithm Working Group (AWG) Convective Initiation (CI) proxy product for the Hazardous Weather Testbed (HWT) Spring Experiment,. Along with its partner WFOs, SPoRT is evaluating MODIS/GOES Hybrid products, which brings ABI-like data sets from existing NASA instrumentation in front of the forecaster for everyday use. The Hybrid uses near real-time MODIS imagery to demonstrate future ABI capabilities, while utilizing standard GOES imagery to provide the temporal frequency of geostationary imagery expected by operational forecasters. In addition, SPoRT is collaborating with the GOES-R hydrology AWG to transition a baseline proxy product for rainfall rate / quantitative precipitation estimate (QPE) to the OCONUS regions. For VIIRS, SPoRT is demonstrating multispectral observing capabilities and the utility of low-light channels not previously available on operational weather satellites to address a variety of weather forecast challenges. This presentation will discuss the results of transitioning these products to collaborating WFOs throughout the country.

Preliminary assessment of the GOES-R ABI hourly land surface albedo and reflectance products prototyped with Himawari AHI data

NASA Astrophysics Data System (ADS)

He, T.; Liang, S.; Zhang, Y.; Yu, Y.

2016-12-01

Land surface albedo and reflectance are critical geophysical variables used in climate and environmental applications. The multispectral Advanced Baseline Imager (ABI) onboard the next generation geostationary satellites (GOES-R series, set to launch in late 2016) offers high temporal and medium spatial resolution observations, which can be used for monitoring diurnal variation of surface albedo and reflectance. In the GOES-R data processing chain there is no atmospheric correction to generate surface reflectance product, which is usually required for surface albedo estimation. We propose an optimization method to simultaneously retrieve surface bidirectional reflectance distribution function (BRDF) parameters and aerosol optical depth with GOES-R ABI data on a daily-basis, which are used for estimating surface albedo and reflectance. Before the launch of the GOES-R satellite, our algorithm was prototyped with data from the Advanced Himawari Imager (AHI) onboard the Japanese Himawari-8 satellite, which has spectral bands and spatial resolutions similar to GOES-R ABI. Cal/val activities were carried out against ground measurements at the OzFlux sites in Australia and satellite data including albedo/BRDF products from MODIS and Landsat. The preliminary accuracy assessment showed promising results for both the surface albedo and reflectance estimates. The GOES-R surface albedo and reflectance products will serve as critical inputs for downstream GOES-R satellite products and also help improve climate modeling and weather forecasting with a high temporal resolution.

From Data to Knowledge — Faster: GOES Early Fire Detection System to Inform Operational Wildfire Response and Management

NASA Astrophysics Data System (ADS)

Koltunov, A.; Quayle, B.; Prins, E. M.; Ambrosia, V. G.; Ustin, S.

2014-12-01

Fire managers at various levels require near-real-time, low-cost, systematic, and reliable early detection capabilities with minimal latency to effectively respond to wildfire ignitions and minimize the risk of catastrophic development. The GOES satellite images collected for vast territories at high temporal frequencies provide a consistent and reliable source for operational active fire mapping realized by the WF-ABBA algorithm. However, their potential to provide early warning or rapid confirmation of initial fire ignition reports from conventional sources remains underutilized, partly because the operational wildfire detection has been successfully optimized for users and applications for which timeliness of initial detection is a low priority, contrasting to the needs of first responders. We present our progress in developing the GOES Early Fire Detection (GOES-EFD) system, a collaborative effort led by University of California-Davis and USDA Forest Service. The GOES-EFD specifically focuses on first detection timeliness for wildfire incidents. It is automatically trained for a monitored scene and capitalizes on multiyear cross-disciplinary algorithm research. Initial retrospective tests in Western US demonstrate significantly earlier identification detection of new ignitions than existing operational capabilities and a further improvement prospect. The GOES-EFD-β prototype will be initially deployed for the Western US region to process imagery from GOES-NOP and the rapid and 4 times higher spatial resolution imagery from GOES-R — the upcoming next generation of GOES satellites. These and other enhanced capabilities of GOES-R are expected to significantly improve the timeliness of fire ignition information from GOES-EFD.

SPoRT's Participation in the GOES-R Proving Ground Activity

NASA Technical Reports Server (NTRS)

Jedlovec, Gary; Fuell, Kevin; Smith, Matthew; Stano, Geoffrey; Molthan, Andrew

2011-01-01

The next generation geostationary satellite, GOES-R, will carry two new instruments with unique atmospheric and surface observing capabilities, the Advanced Baseline Imager (ABI) and the Geostationary Lightning Mapper (GLM), to study short-term weather processes. The ABI will bring enhanced multispectral observing capabilities with frequent refresh rates for regional and full disk coverage to geostationary orbit to address many existing and new forecast challenges. The GLM will, for the first time, provide the continuous monitoring of total lightning flashes over a hemispherical region from space. NOAA established the GOES-R Proving Ground activity several years ago to demonstrate the new capabilities of these instruments and to prepare forecasters for their day one use. Proving Ground partners work closely with algorithm developers and the end user community to develop and transition proxy data sets representing GOES-R observing capabilities. This close collaboration helps to maximize refine algorithms leading to the delivery of a product that effectively address a forecast challenge. The NASA Short-term Prediction Research and Transition (SPoRT) program has been a participant in the NOAA GOES-R Proving Ground activity by developing and disseminating selected GOES-R proxy products to collaborating WFOs and National Centers. Established in 2002 to demonstrate the weather and forecasting application of real-time EOS measurements, the SPoRT program has grown to be an end-to-end research to operations activity focused on the use of advanced NASA modeling and data assimilation approaches, nowcasting techniques, and unique high-resolution multispectral data from EOS satellites to improve short-term weather forecasts on a regional and local scale. Participation in the Proving Ground activities extends SPoRT s activities and taps its experience and expertise in diagnostic weather analysis, short-term weather forecasting, and the transition of research and experimental data to operational decision support systems like NAWIPS, AWIPS, AWIPS2, and Google Earth. Recent SPoRT Proving Ground activities supporting the development and use of a pseudo GLM total lightning product and the transition of the AWG s Convective Initiation (CI) product, both of which were available in AWIPS and AWIPS II environments, by forecasters during the Hazardous Weather Testbed (HWT) Spring Experiment. SPoRT is also providing a suite of SEVIRI and MODIS RGB image products, and a high resolution composite SST product to several National Centers for use in there ongoing demonstration activities. Additionally, SPoRT has involved numerous WFOs in the evaluation of a GOES-MODIS hybrid product which brings ABI-like data sets in front of the forecaster for everyday use. An overview of this activity will be presented at the conference.

SPoRT's Participation in the GOES-R Proving Ground Activity

NASA Astrophysics Data System (ADS)

Jedlovec, G.; Fuell, K.; Smith, M. R.; Stano, G. T.; Molthan, A.

2011-12-01

The next generation geostationary satellite, GOES-R, will carry two new instruments with unique atmospheric and surface observing capabilities, the Advanced Baseline Imager (ABI) and the Geostationary Lightning Mapper (GLM), to study short-term weather processes. The ABI will bring enhanced multispectral observing capabilities with frequent refresh rates for regional and full disk coverage to geostationary orbit to address many existing and new forecast challenges. The GLM will, for the first time, provide the continuous monitoring of total lightning flashes over a hemispherical region from space. NOAA established the GOES-R Proving Ground activity several years ago to demonstrate the new capabilities of these instruments and to prepare forecasters for their day one use. Proving Ground partners work closely with algorithm developers and the end user community to develop and transition proxy data sets representing GOES-R observing capabilities. This close collaboration helps to maximize refine algorithms leading to the delivery of a product that effectively address a forecast challenge. The NASA Short-term Prediction Research and Transition (SPoRT) program has been a participant in the NOAA GOES-R Proving Ground activity by developing and disseminating selected GOES-R proxy products to collaborating WFOs and National Centers. Established in 2002 to demonstrate the weather and forecasting application of real-time EOS measurements, the SPoRT program has grown to be an end-to-end research to operations activity focused on the use of advanced NASA modeling and data assimilation approaches, nowcasting techniques, and unique high-resolution multispectral data from EOS satellites to improve short-term weather forecasts on a regional and local scale. Participation in the Proving Ground activities extends SPoRT's activities and taps its experience and expertise in diagnostic weather analysis, short-term weather forecasting, and the transition of research and experimental data to operational decision support systems like NAWIPS, AWIPS, AWIPS2, and Google Earth. Recent SPoRT Proving Ground activities supporting the development and use of a pseudo GLM total lightning product and the transition of the AWG's Convective Initiation (CI) product, both of which were available in AWIPS and AWIPS II environments, by forecasters during the Hazardous Weather Testbed (HWT) Spring Experiment. SPoRT is also providing a suite of SEVIRI and MODIS RGB image products, and a high resolution composite SST product to several National Centers for use in there ongoing demonstration activities. Additionally, SPoRT has involved numerous WFOs in the evaluation of a GOES-MODIS hybrid product which brings ABI-like data sets in front of the forecaster for everyday use. An overview of this activity will be presented at the conference.

The GOES-R Geostationary Lightning Mapper (GLM)

NASA Astrophysics Data System (ADS)

Goodman, S. J.; Blakeslee, R. J.; Koshak, W. J.; Mach, D. M.; Bailey, J. C.; Buechler, D. E.; Carey, L. D.; Schultz, C. J.; Bateman, M. G.; McCaul, E., Jr.; Stano, G. T.

2012-12-01

The Geostationary Operational Environmental Satellite (GOES-R) series provides the continuity for the existing GOES system currently operating over the Western Hemisphere. New and improved instrument technology will support expanded detection of environmental phenomena, resulting in more timely and accurate forecasts and warnings. Advancements over current GOES include a new capability for total lightning detection (cloud and cloud-to-ground flashes) from the Geostationary Lightning Mapper (GLM), and improved temporal, spatial, and spectral resolution for the next generation Advanced Baseline Imager (ABI). The GLM will map total lightning activity (in-cloud and cloud-to-ground lightning flashes) continuously day and night with near-uniform spatial resolution of 8 km with a product refresh rate of less than 20 sec over the Americas and adjacent oceanic regions. This will aid in forecasting severe storms and tornado activity, and convective weather impacts on aviation safety and efficiency among a number of potential applications. In parallel with the instrument development, an Algorithm Working Group (AWG) Lightning Detection Science and Applications Team developed the Level 2 (stroke and flash) algorithms from the Level 1 lightning event (pixel level) data. Proxy data sets used to develop the GLM operational algorithms as well as cal/val performance monitoring tools were derived from the NASA Lightning Imaging Sensor (LIS) and Optical Transient Detector (OTD) instruments in low earth orbit, and from ground-based lightning networks and intensive pre-launch field campaigns. GLM will produce the same or similar lightning flash attributes provided by the LIS and OTD, and thus extends their combined climatology over the western hemisphere into the coming decades. Science and application development along with pre-operational product demonstrations and evaluations at NWS forecast offices and NOAA testbeds will prepare the forecasters to use GLM as soon as possible after the planned launch and check-out of GOES-R in late 2015. New applications will use GLM alone, in combination with the ABI, or integrated (fused) with other available tools (weather radar and ground strike networks, nowcasting systems, mesoscale analysis, and numerical weather prediction models) in the hands of the forecaster responsible for issuing more timely and accurate forecasts and warnings. Results from recent field campaigns and forecaster evaluations on the utility of the total lightning products will be presented.

GOES-R Lift to Stand

NASA Image and Video Library

2016-08-23

The GOES-R spacecraft is secured on its work stand inside the Astrotech payload processing facility in Titusville, Florida near NASA’s Kennedy Space Center. GOES-R will be the first satellite in a series of next-generation NOAA Geostationary Operational Environmental Satellites. The spacecraft is to launch aboard a United Launch Alliance Atlas V rocket in November.

The Global Geostationary Wildfire ABBA: Current Implementation and Future Plans

NASA Astrophysics Data System (ADS)

Prins, E.; Schmidt, C. C.; Hoffman, J.; Brunner, J.; Hyer, E. J.; Reid, J. S.

2012-12-01

The Wild Fire Automated Biomass Burning Algorithm (WF_ABBA), developed at the Cooperative Institute for Meteorological Satellite Studies (CIMSS), has a long legacy of operational near real-time wildfire detection and characterization in the Western Hemisphere. The first phase of the global geostationary WF_ABBA was made operational at NOAA NESDIS in 2009 and currently includes diurnal active fire monitoring from GOES-East, GOES-South America, GOES-West, Meteosat-9 and MTSAT-1R/-2. This allows for near global active fire monitoring with coverage of Europe, Africa, Southeast Asia and the Western Pacific utilizing distinct geostationary sensors and a consistent algorithm. Version 6.5.006 of the WF_ABBA was specifically designed to address the capabilities and limitations of diverse geostationary sensors and requests from the global fire monitoring and user community. This presentation will provide an overview of version 6.5.006 of the global WF_ABBA fire product including the new fire and opaque cloud mask and associated metadata. We will demonstrate the WF_ABBA showing examples from around the globe with a focus on the capabilities and plans for integrating new geostationary platforms with coverage of Eastern Europe and Asia (INSAT-3D, Korean COMS, Russian GOMS Elektro-L MSU-GS). We are also preparing for future fire monitoring in the Western Hemisphere, Europe, and Africa utilizing the next generation GOES-R Imager and Meteosat Third Generation Flexible Combined Imager (MTG - FCI). The goal is to create a globally consistent long-term fire product utilizing the capabilities of each of these unique operational systems and a common fire detection algorithm. On an international level, development of a global geostationary fire monitoring system is supported by the IGOS GOFC/GOLD Fire Implementation Team. This work also generally supports Committee on Earth Observation Satellites (CEOS) activities and the Group on Earth Observations (GEO).

Improving precipitation estimates over the western United States using GOES-R precipitation data

NASA Astrophysics Data System (ADS)

Karbalaee, N.; Kirstetter, P. E.; Gourley, J. J.

2017-12-01

Satellite remote sensing data with fine spatial and temporal resolution are widely used for precipitation estimation for different applications such as hydrological modeling, storm prediction, and flash flood monitoring. The Geostationary Operational Environmental Satellites-R series (GOES-R) is the next generation of environmental satellites that provides hydrologic, atmospheric, and climatic information every 30 seconds over the western hemisphere. The high-resolution and low-latency of GOES-R observations is essential for the monitoring and prediction of floods, specifically in the Western United States where the vantage point of space can complement the degraded weather radar coverage of the NEXRAD network. The GOES-R rainfall rate algorithm will yield deterministic quantitative precipitation estimates (QPE). Accounting for inherent uncertainties will further advance the GOES-R QPEs since with quantifiable error bars, the rainfall estimates can be more readily fused with ground radar products. On the ground, the high-resolution NEXRAD-based precipitation estimation from the Multi-Radar/Multi-Sensor (MRMS) system, which is now operational in the National Weather Service (NWS), is challenged due to a lack of suitable coverage of operational weather radars over complex terrain. Distribution of QPE uncertainties associated with the GOES-R deterministic retrievals are derived and analyzed using MRMS over regions with good radar coverage. They will be merged with MRMS-based probabilistic QPEs developed to advance multisensor QPE integration. This research aims at improving precipitation estimation over the CONUS by combining the observations from GOES-R and MRMS to provide consistent, accurate and fine resolution precipitation rates with uncertainties over the CONUS.

GOES-R Lift to Stand

NASA Image and Video Library

2016-08-23

An overhead crane moves the GOES-R spacecraft toward its work stand inside the Astrotech payload processing facility in Titusville, Florida near NASA’s Kennedy Space Center. GOES-R will be the first satellite in a series of next-generation NOAA Geostationary Operational Environmental Satellites. The spacecraft is to launch aboard a United Launch Alliance Atlas V rocket in November.

The GOES-R Product Generation Architecture - Post CDR Update

NASA Astrophysics Data System (ADS)

Dittberner, G.; Kalluri, S.; Weiner, A.

2012-12-01

The GOES-R system will substantially improve the accuracy of information available to users by providing data from significantly enhanced instruments, which will generate an increased number and diversity of products with higher resolution, and much shorter relook times. Considerably greater compute and memory resources are necessary to achieve the necessary latency and availability for these products. Over time, new and updated algorithms are expected to be added and old ones removed as science advances and new products are developed. The GOES-R GS architecture is being planned to maintain functionality so that when such changes are implemented, operational product generation will continue without interruption. The primary parts of the PG infrastructure are the Service Based Architecture (SBA) and the Data Fabric (DF). SBA is the middleware that encapsulates and manages science algorithms that generate products. It is divided into three parts, the Executive, which manages and configures the algorithm as a service, the Dispatcher, which provides data to the algorithm, and the Strategy, which determines when the algorithm can execute with the available data. SBA is a distributed architecture, with services connected to each other over a compute grid and is highly scalable. This plug-and-play architecture allows algorithms to be added, removed, or updated without affecting any other services or software currently running and producing data. Algorithms require product data from other algorithms, so a scalable and reliable messaging is necessary. The SBA uses the DF to provide this data communication layer between algorithms. The DF provides an abstract interface over a distributed and persistent multi-layered storage system (e.g., memory based caching above disk-based storage) and an event management system that allows event-driven algorithm services to know when instrument data are available and where they reside. Together, the SBA and the DF provide a flexible, high performance architecture that can meet the needs of product processing now and as they grow in the future.

GOES-R Lift to Stand

NASA Image and Video Library

2016-08-23

Team members monitor progress as an overhead crane lowers the GOES-R spacecraft into its work stand inside the Astrotech payload processing facility in Titusville, Florida near NASA’s Kennedy Space Center. GOES-R will be the first satellite in a series of next-generation NOAA Geostationary Operational Environmental Satellites. The spacecraft is to launch aboard a United Launch Alliance Atlas V rocket in November.

GOES-R Lift to Stand

NASA Image and Video Library

2016-08-23

Team members monitor progress as an overhead crane lowers the GOES-R spacecraft toward its work stand inside the Astrotech payload processing facility in Titusville, Florida near NASA’s Kennedy Space Center. GOES-R will be the first satellite in a series of next-generation NOAA Geostationary Operational Environmental Satellites. The spacecraft is to launch aboard a United Launch Alliance Atlas V rocket in November.

GOES-R Lift to Stand

NASA Image and Video Library

2016-08-23

An overhead crane lifts the GOES-R spacecraft to move it into its work stand inside the Astrotech payload processing facility in Titusville, Florida near NASA’s Kennedy Space Center. GOES-R will be the first satellite in a series of next-generation NOAA Geostationary Operational Environmental Satellites. The spacecraft is to launch aboard a United Launch Alliance Atlas V rocket in November.

GOES-R Lift to Stand

NASA Image and Video Library

2016-08-23

An overhead crane is positioned to move the GOES-R spacecraft into its work stand inside the Astrotech payload processing facility in Titusville, Florida near NASA’s Kennedy Space Center. GOES-R will be the first satellite in a series of next-generation NOAA Geostationary Operational Environmental Satellites. The spacecraft is to launch aboard a United Launch Alliance Atlas V rocket in November.

Post Launch Calibration and Testing of the Advanced Baseline Imager on the GOES-R Satellite

NASA Technical Reports Server (NTRS)

Lebair, William; Rollins, C.; Kline, John; Todirita, M.; Kronenwetter, J.

2016-01-01

The Geostationary Operational Environmental Satellite R (GOES-R) series is the planned next generation of operational weather satellites for the United State's National Oceanic and Atmospheric Administration. The first launch of the GOES-R series is planned for October 2016. The GOES-R series satellites and instruments are being developed by the National Aeronautics and Space Administration (NASA). One of the key instruments on the GOES-R series is the Advance Baseline Imager (ABI). The ABI is a multi-channel, visible through infrared, passive imaging radiometer. The ABI will provide moderate spatial and spectral resolution at high temporal and radiometric resolution to accurately monitor rapidly changing weather. Initial on-orbit calibration and performance characterization is crucial to establishing baseline used to maintain performance throughout mission life. A series of tests has been planned to establish the post launch performance and establish the parameters needed to process the data in the Ground Processing Algorithm. The large number of detectors for each channel required to provide the needed temporal coverage presents unique challenges for accurately calibrating ABI and minimizing striping. This paper discusses the planned tests to be performed on ABI over the six-month Post Launch Test period and the expected performance as it relates to ground tests.

Post Launch Calibration and Testing of the Advanced Baseline Imager on the GOES-R Satellite

NASA Technical Reports Server (NTRS)

Lebair, William; Rollins, C.; Kline, John; Todirita, M.; Kronenwetter, J.

2016-01-01

The Geostationary Operational Environmental Satellite R (GOES-R) series is the planned next generation of operational weather satellites for the United States National Oceanic and Atmospheric Administration. The first launch of the GOES-R series is planned for October 2016. The GOES-R series satellites and instruments are being developed by the National Aeronautics and Space Administration (NASA). One of the key instruments on the GOES-R series is the Advance Baseline Imager (ABI). The ABI is a multi-channel, visible through infrared, passive imaging radiometer. The ABI will provide moderate spatial and spectral resolution at high temporal and radiometric resolution to accurately monitor rapidly changing weather. Initial on-orbit calibration and performance characterization is crucial to establishing baseline used to maintain performance throughout mission life. A series of tests has been planned to establish the post launch performance and establish the parameters needed to process the data in the Ground Processing Algorithm. The large number of detectors for each channel required to provide the needed temporal coverage presents unique challenges for accurately calibrating ABI and minimizing striping. This paper discusses the planned tests to be performed on ABI over the six-month Post Launch Test period and the expected performance as it relates to ground tests.

Post launch calibration and testing of the Advanced Baseline Imager on the GOES-R satellite

NASA Astrophysics Data System (ADS)

Lebair, William; Rollins, C.; Kline, John; Todirita, M.; Kronenwetter, J.

2016-05-01

The Geostationary Operational Environmental Satellite R (GOES-R) series is the planned next generation of operational weather satellites for the United State's National Oceanic and Atmospheric Administration. The first launch of the GOES-R series is planned for October 2016. The GOES-R series satellites and instruments are being developed by the National Aeronautics and Space Administration (NASA). One of the key instruments on the GOES-R series is the Advance Baseline Imager (ABI). The ABI is a multi-channel, visible through infrared, passive imaging radiometer. The ABI will provide moderate spatial and spectral resolution at high temporal and radiometric resolution to accurately monitor rapidly changing weather. Initial on-orbit calibration and performance characterization is crucial to establishing baseline used to maintain performance throughout mission life. A series of tests has been planned to establish the post launch performance and establish the parameters needed to process the data in the Ground Processing Algorithm. The large number of detectors for each channel required to provide the needed temporal coverage presents unique challenges for accurately calibrating ABI and minimizing striping. This paper discusses the planned tests to be performed on ABI over the six-month Post Launch Test period and the expected performance as it relates to ground tests.

Next Generation of Air Quality Measurements from Geo Orbits: Breaking The Temporal Barrier

NASA Astrophysics Data System (ADS)

Gupta, P.; Levy, R. C.; Mattoo, S.; Remer, L.; Heidinger, A.

2017-12-01

NASA's dark target (DT) aerosol algorithm provides operational retrieval of atmospheric aerosols from multiple polar orbiting satellites. The DT algorithm, initially developed for MODIS observations, has been continuously improved since the first MODIS launch in early 2000. Now, we are adapting the DT algorithm to retrieve on new-generation geostationary (GEO) sensors, including the Advanced Himawari Imager (AHI) on Japan's Himawari-8 (H8) satellite and Advanced Baseline Imager (ABI) on NOAA's GOES-16 (or GOES-R). H8 is a weather geostationary satellite operating since July 2015, and AHI observes earth-atmosphere system over the Asia-Pacific region at spatial resolutions of 1km or less. GOES-R is launched in Nov 2016 and provides high temporal resolution observations over Americas. With 16 spectral channels, including 7 bands that observe similar wavelengths as the MODIS bands used for DT aerosol retrieval. Most exciting, however, is that both ABI and AHI provides full disk observations every 10-15 minutes and zoom mode observations every 30 second to 2.5 minutes. Therefore, spectral, spatial and temporal resolution observations from these GEO satellites provide opportunity to monitor atmospheric aerosols in the region, plus a new capability to monitor aerosol transport and aerosol/cloud diurnal cycles. In this paper, we will introduce retrieval results from AHI using the DT algorithm during the KORUS-AQ field campaign during summer 2016. These results are evaluated against surface measurements (e.g. AERONET). . We will also discuss, its potential applications in monitoring diurnal cycles of urban pollution, smoke and dust in the region. The same DT algorithm will also be adapted to retrieve aerosol properties using GOES-16 over Americas.

New GOES-R Risk Reduction Activities at CIRA

NASA Astrophysics Data System (ADS)

Rogers, M. A.; Miller, S. D.; Grasso, L. D.; Haynes, J. M.; NOH, Y. J.; Forsythe, J.; Zupanski, M.; Lindsey, D. T.

2017-12-01

A team of atmospheric scientists at the Cooperative Institute for Research in the Atmosphere (CIRA) at the Colorado State University has been selected by the National Oceanic and Atmospheric Administration's (NOAA) GOES-R Risk Reduction (GOES-R3) science program to develop applications to enhance the utilization of the GOES-R sensors, including the Advanced Baseline Imager (ABI) and the Geostationary Lightning Mapper (GLM). The selected project topics follow NOAA's Research and Development Objectives listed in its 5-year Strategic Plan. The projects will be carried out over a three-year period which started on 1 July 2017 and will end on 30 June 2019. CIRA is working on five GOES-R3 application developments: 1) Developing an Environmental Awareness Repertoire of ABI Imagery (`DEAR-ABII') to Advise the Operational Weather Forecaster. DEAR-ABII maximizes the vast potential of the new GOES-R/GOES-16 sensor technology. 2) GOES-R ABI channel differencing used to reveal cloud-free zones of `precursors of convective initiation'. This product identifies where convective initiation may occur in cloud free skies. 3) Improving the ABI Cloud Layers Product for Multiple Layer Cloud Systems and Aviation Forecast Applications. This project aims to improve the GOES-16 cloud layer product by providing information on the boundaries of cloud layers even when one layer overlies another. 4) Using the New Capabilities of GOES-R to Improve Blended, Multisensor Water Vapor Products for Forecasters. GOES-R TPW retrievals will be merged with TPW derived from polar orbiter and surface data to improve the operational NOAA blended TPW product. 5) Data assimilation of GLM observations in HWRF/GSI system. Assimilation of GOES-R GLM observations for the NOAA operational hurricane model with the goal to improve operational hurricane forecasting. Examples for each of these applications will be presented.

GOES-R Space Weather Data: Achieving User Ready Products

NASA Astrophysics Data System (ADS)

Rowland, W. F.; Tilton, M.; Redmon, R. J.; Goodman, S. J.; Comerford, M.

2017-12-01

Forecasters and the science community will rely on improved Space Weather products from the next generation of Geostationary Operational Environmental Satellite (GOES-R Series) for decades to come. Many issues must be successfully addressed in order to produce useful products. The instruments themselves and their basic scientific measurements (Level 1b data, i.e. L1b) must be calibrated and validated. Algorithms must be created to transform L1b into the specific environmental parameters that are of interest to forecasters and the community (Level 2+, i.e. L2+). In the case of Space Weather data, because the L2+ products are not generated within the core GOES-R Ground Segment, a separate system had to be developed in order to implement the L2+ products. Finally, the products must be made available to real time and retrospective users, as well as preserved for future generations. We give an overview of the path to production of the GOES-R Space Weather products, and the role of the National Centers for Environmental Information (NCEI) in this process.

Merging Sounder and Imager Data for Improved Cloud Depiction on SNPP and JPSS.

NASA Astrophysics Data System (ADS)

Heidinger, A. K.; Holz, R.; Li, Y.; Platnick, S. E.; Wanzong, S.

2017-12-01

Under the NOAA GOES-R Algorithm Working Group (AWG) Program, NOAA supports the development of an Infrared (IR) Optimal Estimation (OE) Cloud Height Algorithm (ACHA). ACHA is an enterprise solution that supports many geostationary and polar orbiting imager sensors. ACHA is operational at NOAA on SNPP VIIRS and has been adopted as the cloud height algorithm for the NASA NPP Atmospheric Suite of products. Being an OE algorithm, ACHA is flexible and capable of using additional observations and constraints. We have modified ACHA to use sounder (CriS) observations to improve the cloud detection, typing and height estimation. Specifically, these improvements include retrievals in multi-layer scenarios and improved performance in polar regions. This presentation will describe the process for merging VIIRS and CrIS and a demonstration of the improvements.

Toward an Objective Enhanced-V Detection Algorithm

NASA Technical Reports Server (NTRS)

Moses, John F.; Brunner,Jason C.; Feltz, Wayne F.; Ackerman, Steven A.; Moses, John F.; Rabin, Robert M.

2007-01-01

The area of coldest cloud tops above thunderstorms sometimes has a distinct V or U shape. This pattern, often referred to as an "enhanced-V signature, has been observed to occur during and preceding severe weather. This study describes an algorithmic approach to objectively detect overshooting tops, temperature couplets, and enhanced-V features with observations from the Geostationary Operational Environmental Satellite and Low Earth Orbit data. The methodology consists of temperature, temperature difference, and distance thresholds for the overshooting top and temperature couplet detection parts of the algorithm and consists of cross correlation statistics of pixels for the enhanced-V detection part of the algorithm. The effectiveness of the overshooting top and temperature couplet detection components of the algorithm is examined using GOES and MODIS image data for case studies in the 2003-2006 seasons. The main goal is for the algorithm to be useful for operations with future sensors, such as GOES-R.

Atmospheric temporal variations in the pre-landfall environment of typhoon Nangka (2015) observed by the Himawari-8 AHI

NASA Astrophysics Data System (ADS)

Lee, Yong-Keun; Li, Jun; Li, Zhenglong; Schmit, Timothy

2017-11-01

The next generation Geostationary Operational Environmental Satellite-R series (GOES-R) Advanced Baseline Imager (ABI) legacy atmospheric profile (LAP) retrieval algorithm is applied to the Advanced Himawari Imager (AHI) radiance measurements from the Himawari-8 satellite. Derived products included atmospheric temperature/moisture profiles, total precipitable water (TPW), and atmospheric stability indices. Since both AHI and ABI have 9 similar infrared bands, the GOES-R ABI LAP retrieval algorithm can be applied to the AHI measurements with minimal modifications. With the capability of frequent (10-min interval) full disk observations over the East Asia and Western Pacific regions, the AHI measurements are used to investigate the atmospheric temporal variation in the pre-landfall environment for typhoon Nangka (2015). Before its landfall over Japan, heavy rainfalls from Nangka occurred over the southern region of Honshu Island. During the pre-landfall period, the trends of the AHI LAP products indicated the development of the atmospheric environment favorable for heavy rainfall. Even though, the AHI LAP products are generated only in the clear skies, the 10-minute interval AHI measurements provide detailed information on the pre-landfall environment for typhoon Nangka. This study shows the capability of the AHI radiance measurements, together with the derived products, for depicting the detailed temporal features of the pre-landfall environment of a typhoon, which may also be possible for hurricanes and storms with ABI on the GOES-R satellite.

Lightning Jump Algorithm Development for the GOES·R Geostationary Lightning Mapper

NASA Technical Reports Server (NTRS)

Schultz. E.; Schultz. C.; Chronis, T.; Stough, S.; Carey, L.; Calhoun, K.; Ortega, K.; Stano, G.; Cecil, D.; Bateman, M.;

Correcting GOES-R Magnetometer Data for Stray Fields

NASA Technical Reports Server (NTRS)

Carter, Delano; Freesland, Douglas; Tadikonda, Sivakumar; Kronenwetter, Jeffrey; Todirita, Monica; Dahya, Melissa; Chu, Donald

2016-01-01

Time-varying spacecraft magnetic fields, i.e. stray fields, are a problem for magnetometer systems. While constant fields can be removed by calibration, stray fields are difficult to distinguish from ambient field variations. Putting two magnetometers on a long boom and solving for both the ambient and stray fields can help, but this gradiometer solution is more sensitive to noise than a single magnetometer. As shown here for the R-series Geostationary Operational Environmental Satellites (GOES-R), unless the stray fields are larger than the noise, simply averaging the two magnetometer readings gives a more accurate solution. If averaging is used, it may be worthwhile to estimate and remove stray fields explicitly. Models and estimation algorithms to do so are provided for solar array, arcjet and reaction wheel fields.

Initial Navigation Alignment of Optical Instruments on GOES-R

NASA Astrophysics Data System (ADS)

Isaacson, P.; DeLuccia, F.; Reth, A. D.; Igli, D. A.; Carter, D.

2016-12-01

The GOES-R satellite is the first in NOAA's next-generation series of geostationary weather satellites. In addition to a number of space weather sensors, it will carry two principal optical earth-observing instruments, the Advanced Baseline Imager (ABI) and the Geostationary Lightning Mapper (GLM). During launch, currently scheduled for November of 2016, the alignment of these optical instruments is anticipated to shift from that measured during pre-launch characterization. While both instruments have image navigation and registration (INR) processing algorithms to enable automated geolocation of the collected data, the launch-derived misalignment may be too large for these approaches to function without an initial adjustment to calibration parameters. The parameters that may require adjustment are for Line of Sight Motion Compensation (LMC), and the adjustments will be estimated on orbit during the post-launch test (PLT) phase. We have developed approaches to estimate the initial alignment errors for both ABI and GLM image products. Our approaches involve comparison of ABI and GLM images collected during PLT to a set of reference ("truth") images using custom image processing tools and other software (the INR Performance Assessment Tool Set, or "IPATS") being developed for other INR assessments of ABI and GLM data. IPATS is based on image correlation approaches to determine offsets between input and reference images, and these offsets are the fundamental input to our estimate of the initial alignment errors. Initial testing of our alignment algorithms on proxy datasets lends high confidence that their application will determine the initial alignment errors to within sufficient accuracy to enable the operational INR processing approaches to proceed in a nominal fashion. We will report on the algorithms, implementation approach, and status of these initial alignment tools being developed for the GOES-R ABI and GLM instruments.

NASA/SPoRT's GOES-R Activities in Support of Product Development, Management, and Training

NASA Technical Reports Server (NTRS)

Fuell, Kevin K.; Jedlovec, Gary; Molthan, Andrew L.; Stano, Geoffrey T.

2012-01-01

The NASA Short-term Prediction Research and Transition (SPoRT) Center supports many activities within the GOES-R Proving Grounds (PG). These include the development of imagery from existing instrumentation as a proxy to future Advanced Baseline Imager (ABI) capabilities on GOES-R. The Moderate Resolution Imaging Spectroradiometer (MODIS) and the Visible/Infrared Imager/Radiometer Suite (VIIRS) instruments are used to provide a glimpse of the multi-spectral capabilities that will become the norm as the number of channels and data rate dramatically increase with GOES-R. The NOAA/NWS has plans to provide operational users with all ABI channels at the highest resolution. Data fusion of individual channels into composite red, green, and blue imagery products will assist the end user with this future wave of information. While increasing the efficiency in the operational use of ABI channels, these composites provide only qualitative information. Within the GOES-R PG, SPoRT and other partners are exploring ways to include quantitative information as part of the composite imagery. However, limitations in local hardware processing and/or data bandwidth for users of the GOES-R data stream are challenges to overcome. This presentation will discuss the creation of these composite images as well as possible solutions to address these processing challenges. In a similar manner the Geostationary Lightning Mapper (GLM) to be launched on GOES-R presents several data management challenges. The GLM is a pioneering instrument to quantify total lightning from a geostationary platform. The expected data frequency from the GLM is to be at a sub-minute interval. Users of such a data set may have little experience in handling such a rapid update of information. To assist users, SPoRT is working with the NWS to develop tools within the user fs decision support system to allow tracking and analysis of total lightning from a storm-based perspective. This presentation will discuss the challenges and progress of this tool development work. With new data and products comes the need for user Training. Within the GOES-R PG SPoRT is supporting the demonstration of these future products by providing various training materials to end users. A summary of training provided to operational users will be discussed.

NASA/SPoRT's GOES-R Activities in Support of Product Development, Management, and Training

NASA Astrophysics Data System (ADS)

Fuell, K. K.; Jedlovec, G.; Molthan, A.; Stano, G. T.

2012-12-01

The NASA Short-term Prediction Research and Transition (SPoRT) Center supports many activities within the GOES-R Proving Grounds (PG). These include the development of imagery from existing instrumentation as a proxy to future Advanced Baseline Imager (ABI) capabilities on GOES-R. The Moderate Resolution Imaging Spectroradiometer (MODIS) and the Visible/Infrared Imager/Radiometer Suite (VIIRS) instruments are used to provide a glimpse of the multi-spectral capabilities that will become the norm as the number of channels and data rate dramatically increase with GOES-R. The NOAA/NWS has plans to provide operational users with all ABI channels at the highest resolution. Data fusion of individual channels into composite red, green, and blue imagery products will assist the end user with this future wave of information. While increasing the efficiency in the operational use of ABI channels, these composites provide only qualitative information. Within the GOES-R PG, SPoRT and other partners are exploring ways to include quantitative information as part of the composite imagery. However, limitations in local hardware processing and/or data bandwidth for users of the GOES-R data stream are challenges to overcome. This presentation will discuss the creation of these composite images as well as possible solutions to address these processing challenges. In a similar manner the Geostationary Lightning Mapper (GLM) to be launched on GOES-R presents several data management challenges. The GLM is a pioneering instrument to quantify total lightning from a geostationary platform. The expected data frequency from the GLM is to be at a sub-minute interval. Users of such a data set may have little experience in handling such a rapid update of information. To assist users, SPoRT is working with the NWS to develop tools within the user's decision support system to allow tracking and analysis of total lightning from a storm-based perspective. This presentation will discuss the challenges and progress of this tool development work. With new data and products comes the need for user Training. Within the GOES-R PG SPoRT is supporting the demonstration of these future products by providing various training materials to end users. A summary of training provided to operational users will be discussed.

Sao Paulo Lightning Mapping Array (SP-LMA): Network Assessment and Analyses for Intercomparison Studies and GOES-R Proxy Activities

NASA Technical Reports Server (NTRS)

Blakeslee, R. J.; Bailey, J. C.; Carey, L. D.; Goodman, S. J.; Rudlosky, S. D.; Albrecht, R.; Morales, C. A.; Anselmo, E. M.; Neves, J. R.

2013-01-01

A 12 station Lightning Mapping Array (LMA) network was deployed during October 2011in the vicinity of São Paulo, Brazil (SP-LMA) to contribute total lightning measurements to an international field campaign [CHUVA - Cloud processes of tHe main precipitation systems in Brazil: A contribUtion to cloud resolVing modeling and to the GPM (GlobAl Precipitation Measurement)]. The SP-LMA was operational from November 2011 through March 2012. Sensor spacing was on the order of 15-30 km, with a network diameter on the order of 40-50km. The SP-LMA provides good 3-D lightning mapping out to150 km from the network center, with 2-D coverage considerably farther. In addition to supporting CHUVA science/mission objectives, the SP-LMA is supporting the generation of unique proxy data for the Geostationary Lightning Mapper (GLM) and Advanced Baseline Imager (ABI), on NOAA's Geostationary Operational Environmental Satellite-R (GOES-R: scheduled for a 2015 launch). These proxy data will be used to develop and validate operational algorithms so that they will be ready to use on "day1" following the GOES-R launch. The SP-LMA data also will be intercompared with lightning observations from other deployed lightning networks to advance our understanding of the capabilities/contributions of each of these networks toward GLM proxy and validation activities. This paper addresses the network assessment and analyses for intercomparison studies and GOES-R proxy activities

Icing detection from geostationary satellite data using machine learning approaches

NASA Astrophysics Data System (ADS)

Lee, J.; Ha, S.; Sim, S.; Im, J.

2015-12-01

Icing can cause a significant structural damage to aircraft during flight, resulting in various aviation accidents. Icing studies have been typically performed using two approaches: one is a numerical model-based approach and the other is a remote sensing-based approach. The model based approach diagnoses aircraft icing using numerical atmospheric parameters such as temperature, relative humidity, and vertical thermodynamic structure. This approach tends to over-estimate icing according to the literature. The remote sensing-based approach typically uses meteorological satellite/ground sensor data such as Geostationary Operational Environmental Satellite (GOES) and Dual-Polarization radar data. This approach detects icing areas by applying thresholds to parameters such as liquid water path and cloud optical thickness derived from remote sensing data. In this study, we propose an aircraft icing detection approach which optimizes thresholds for L1B bands and/or Cloud Optical Thickness (COT) from Communication, Ocean and Meteorological Satellite-Meteorological Imager (COMS MI) and newly launched Himawari-8 Advanced Himawari Imager (AHI) over East Asia. The proposed approach uses machine learning algorithms including decision trees (DT) and random forest (RF) for optimizing thresholds of L1B data and/or COT. Pilot Reports (PIREPs) from South Korea and Japan were used as icing reference data. Results show that RF produced a lower false alarm rate (1.5%) and a higher overall accuracy (98.8%) than DT (8.5% and 75.3%), respectively. The RF-based approach was also compared with the existing COMS MI and GOES-R icing mask algorithms. The agreements of the proposed approach with the existing two algorithms were 89.2% and 45.5%, respectively. The lower agreement with the GOES-R algorithm was possibly due to the high uncertainty of the cloud phase product from COMS MI.

The GOES-R/JPSS Approach for Identifying Hazardous Low Clouds: Overview and Operational Impacts

NASA Astrophysics Data System (ADS)

Calvert, Corey; Pavolonis, Michael; Lindstrom, Scott; Gravelle, Chad; Terborg, Amanda

2017-04-01

Low ceiling and visibility is a weather hazard that nearly every forecaster, in nearly every National Weather Service (NWS) Weather Forecast Office (WFO), must regularly address. In addition, national forecast centers such as the Aviation Weather Center (AWC), Alaska Aviation Weather Unit (AAWU) and the Ocean Prediction Center (OPC) are responsible for issuing low ceiling and visibility related products. As such, reliable methods for detecting and characterizing hazardous low clouds are needed. Traditionally, hazardous areas of Fog/Low Stratus (FLS) are identified using a simple stand-alone satellite product that is constructed by subtracting the 3.9 and 11 μm brightness temperatures. However, the 3.9-11 μm brightness temperature difference (BTD) has several major limitations. In an effort to address the limitations of the BTD product, the GOES-R Algorithm Working Group (AWG) developed an approach that fuses satellite, Numerical Weather Prediction (NWP) model, Sea Surface Temperature (SST) analyses, and other data sets (e.g. digital surface elevation maps, surface emissivity maps, and surface type maps) to determine the probability that hazardous low clouds are present using a naïve Bayesian classifier. In addition, recent research has focused on blending geostationary (e.g. GOES-R) and low earth orbit (e.g. JPSS) satellite data to further improve the products. The FLS algorithm has adopted an enterprise approach in that it can utilize satellite data from a variety of current and future operational sensors and NWP data from a variety of models. The FLS products are available in AWIPS/N-AWIPS/AWIPS-II and have been evaluated within NWS operations over the last four years as part of the Satellite Proving Ground. Forecaster feedback has been predominantly positive and references to these products within Area Forecast Discussions (AFD's) indicate that the products are influencing operational forecasts. At the request of the NWS, the FLS products are currently being transitioned to NOAA/NESDIS operations, which will ensure that users have long-term access to these products. This paper will provide an overview of the FLS products and illustrate how they are being used to improve transportation safety and efficiency.

Cloud Macro- and Microphysical Properties Derived from GOES over the ARM SGP Domain

NASA Technical Reports Server (NTRS)

Minnis, P.; Smith, W. L., Jr.; Young, D. F.

2001-01-01

Cloud macrophysical properties like fractional coverage and height Z(sub c) and microphysical parameters such as cloud liquid water path (LWP), effective droplet radius r(sub e), and cloud phase, are key factors affecting both the radiation budget and the hydrological cycle. Satellite data have been used to complement surface observations from Atmospheric Radiation Measurements (ARM) by providing additional spatial coverage and top-of-atmosphere boundary conditions of these key parameters. Since 1994, the Geostationary Operational Environmental Satellite (GOES) has been used for deriving at each half-hour over the ARM Southern Great Plains (SGP) domain: cloud amounts, altitudes, temperatures, and optical depths as well as broadband shortwave (SW) albedo and outgoing longwave radiation at the top of the atmosphere. A new operational algorithm has been implemented to increase the number of value-added products to include cloud particle phase and effective size (r(sub e) or effective ice diameter D(sub e)) as well as LWP and ice water path. Similar analyses have been performed on the data from the Visible Infrared Scanner (VIRS) on the Tropical Rainfall Measuring Mission satellite as part of the Clouds and Earth's Radiant Energy System project. This larger suite of cloud properties will enhance our knowledge of cloud processes and further constrain the mesoscale and single column models using ARM data as a validation/initialization resource. This paper presents the results of applying this new algorithm to GOES-8 data taken during 1998 and 2000. The global VIRS results are compared to the GOES SGP results to provide appropriate context and to test consistency.

Geostationary Lightning Mapper for GOES-R

NASA Technical Reports Server (NTRS)

Goodman, Steven; Blakeslee, Richard; Koshak, William

2007-01-01

The Geostationary Lightning Mapper (GLM) is a single channel, near-IR optical detector, used to detect, locate and measure total lightning activity over the full-disk as part of a 3-axis stabilized, geostationary weather satellite system. The next generation NOAA Geostationary Operational Environmental Satellite (GOES-R) series with a planned launch in 2014 will carry a GLM that will provide continuous day and night observations of lightning from the west coast of Africa (GOES-E) to New Zealand (GOES-W) when the constellation is fully operational. The mission objectives for the GLM are to 1) provide continuous, full-disk lightning measurements for storm warning and Nowcasting, 2) provide early warning of tornadic activity, and 3) accumulate a long-term database to track decadal changes of lightning. The GLM owes its heritage to the NASA Lightning Imaging Sensor (1997-Present) and the Optical Transient Detector (1995-2000), which were developed for the Earth Observing System and have produced a combined 11 year data record of global lightning activity. Instrument formulation studies begun in January 2006 will be completed in March 2007, with implementation expected to begin in September 2007. Proxy total lightning data from the NASA Lightning Imaging Sensor on the Tropical Rainfall Measuring Mission (TRMM) satellite, airborne science missions (e.g., African Monsoon Multi-disciplinary Analysis, AMMA), and regional test beds (e.g, Lightning Mapping Arrays) are being used to develop the pre-launch algorithms and applications, and also improve our knowledge of thunderstorm initiation and evolution. Real time lightning mapping data now being provided to selected forecast offices will lead to improved understanding of the application of these data in the severe storm warning process and accelerate the development of the pre-launch algorithms and Nowcasting applications. Proxy data combined with MODIS and Meteosat Second Generation SEVERI observations will also lead to new applications (e.g., multi-sensor precipitation algorithms blending the GLM with the Advanced Baseline Imager, convective cloud initiation and identification, early warnings of lightning threat, storm tracking, and data assimilation).

Image navigation and registration performance assessment tool set for the GOES-R Advanced Baseline Imager and Geostationary Lightning Mapper

NASA Astrophysics Data System (ADS)

De Luccia, Frank J.; Houchin, Scott; Porter, Brian C.; Graybill, Justin; Haas, Evan; Johnson, Patrick D.; Isaacson, Peter J.; Reth, Alan D.

2016-05-01

The GOES-R Flight Project has developed an Image Navigation and Registration (INR) Performance Assessment Tool Set (IPATS) for measuring Advanced Baseline Imager (ABI) and Geostationary Lightning Mapper (GLM) INR performance metrics in the post-launch period for performance evaluation and long term monitoring. For ABI, these metrics are the 3-sigma errors in navigation (NAV), channel-to-channel registration (CCR), frame-to-frame registration (FFR), swath-to-swath registration (SSR), and within frame registration (WIFR) for the Level 1B image products. For GLM, the single metric of interest is the 3-sigma error in the navigation of background images (GLM NAV) used by the system to navigate lightning strikes. 3-sigma errors are estimates of the 99. 73rd percentile of the errors accumulated over a 24 hour data collection period. IPATS utilizes a modular algorithmic design to allow user selection of data processing sequences optimized for generation of each INR metric. This novel modular approach minimizes duplication of common processing elements, thereby maximizing code efficiency and speed. Fast processing is essential given the large number of sub-image registrations required to generate INR metrics for the many images produced over a 24 hour evaluation period. Another aspect of the IPATS design that vastly reduces execution time is the off-line propagation of Landsat based truth images to the fixed grid coordinates system for each of the three GOES-R satellite locations, operational East and West and initial checkout locations. This paper describes the algorithmic design and implementation of IPATS and provides preliminary test results.

Image Navigation and Registration (INR) Performance Assessment Tool Set (IPATS) for the GOES-R Advanced Baseline Imager and Geostationary Lightning Mapper

NASA Technical Reports Server (NTRS)

DeLuccia, Frank J.; Houchin, Scott; Porter, Brian C.; Graybill, Justin; Haas, Evan; Johnson, Patrick D.; Isaacson, Peter J.; Reth, Alan D.

2016-01-01

The GOES-R Flight Project has developed an Image Navigation and Registration (INR) Performance Assessment Tool Set (IPATS) for measuring Advanced Baseline Imager (ABI) and Geostationary Lightning Mapper (GLM) INR performance metrics in the post-launch period for performance evaluation and long term monitoring. For ABI, these metrics are the 3-sigma errors in navigation (NAV), channel-to-channel registration (CCR), frame-to-frame registration (FFR), swath-to-swath registration (SSR), and within frame registration (WIFR) for the Level 1B image products. For GLM, the single metric of interest is the 3-sigma error in the navigation of background images (GLM NAV) used by the system to navigate lightning strikes. 3-sigma errors are estimates of the 99.73rd percentile of the errors accumulated over a 24 hour data collection period. IPATS utilizes a modular algorithmic design to allow user selection of data processing sequences optimized for generation of each INR metric. This novel modular approach minimizes duplication of common processing elements, thereby maximizing code efficiency and speed. Fast processing is essential given the large number of sub-image registrations required to generate INR metrics for the many images produced over a 24 hour evaluation period. Another aspect of the IPATS design that vastly reduces execution time is the off-line propagation of Landsat based truth images to the fixed grid coordinates system for each of the three GOES-R satellite locations, operational East and West and initial checkout locations. This paper describes the algorithmic design and implementation of IPATS and provides preliminary test results.

Image Navigation and Registration Performance Assessment Tool Set for the GOES-R Advanced Baseline Imager and Geostationary Lightning Mapper

NASA Technical Reports Server (NTRS)

De Luccia, Frank J.; Houchin, Scott; Porter, Brian C.; Graybill, Justin; Haas, Evan; Johnson, Patrick D.; Isaacson, Peter J.; Reth, Alan D.

2016-01-01

The GOES-R Flight Project has developed an Image Navigation and Registration (INR) Performance Assessment Tool Set (IPATS) for measuring Advanced Baseline Imager (ABI) and Geostationary Lightning Mapper (GLM) INR performance metrics in the post-launch period for performance evaluation and long term monitoring. For ABI, these metrics are the 3-sigma errors in navigation (NAV), channel-to-channel registration (CCR), frame-to-frame registration (FFR), swath-to-swath registration (SSR), and within frame registration (WIFR) for the Level 1B image products. For GLM, the single metric of interest is the 3-sigma error in the navigation of background images (GLM NAV) used by the system to navigate lightning strikes. 3-sigma errors are estimates of the 99.73rd percentile of the errors accumulated over a 24-hour data collection period. IPATS utilizes a modular algorithmic design to allow user selection of data processing sequences optimized for generation of each INR metric. This novel modular approach minimizes duplication of common processing elements, thereby maximizing code efficiency and speed. Fast processing is essential given the large number of sub-image registrations required to generate INR metrics for the many images produced over a 24-hour evaluation period. Another aspect of the IPATS design that vastly reduces execution time is the off-line propagation of Landsat based truth images to the fixed grid coordinates system for each of the three GOES-R satellite locations, operational East and West and initial checkout locations. This paper describes the algorithmic design and implementation of IPATS and provides preliminary test results.

Image Navigation and Registration Performance Assessment Evaluation Tools for GOES-R ABI and GLM

NASA Technical Reports Server (NTRS)

Houchin, Scott; Porter, Brian; Graybill, Justin; Slingerland, Philip

2017-01-01

The GOES-R Flight Project has developed an Image Navigation and Registration (INR) Performance Assessment Tool Set (IPATS) for measuring Advanced Baseline Imager (ABI) and Geostationary Lightning Mapper (GLM) INR performance metrics in the post-launch period for performance evaluation and long term monitoring. IPATS utilizes a modular algorithmic design to allow user selection of data processing sequences optimized for generation of each INR metric. This novel modular approach minimizes duplication of common processing elements, thereby maximizing code efficiency and speed. Fast processing is essential given the large number of sub-image registrations required to generate INR metrics for the many images produced over a 24 hour evaluation period. This paper describes the software design and implementation of IPATS and provides preliminary test results.

Lossless compression algorithm for multispectral imagers

NASA Astrophysics Data System (ADS)

Gladkova, Irina; Grossberg, Michael; Gottipati, Srikanth

2008-08-01

Multispectral imaging is becoming an increasingly important tool for monitoring the earth and its environment from space borne and airborne platforms. Multispectral imaging data consists of visible and IR measurements from a scene across space and spectrum. Growing data rates resulting from faster scanning and finer spatial and spectral resolution makes compression an increasingly critical tool to reduce data volume for transmission and archiving. Research for NOAA NESDIS has been directed to finding for the characteristics of satellite atmospheric Earth science Imager sensor data what level of Lossless compression ratio can be obtained as well as appropriate types of mathematics and approaches that can lead to approaching this data's entropy level. Conventional lossless do not achieve the theoretical limits for lossless compression on imager data as estimated from the Shannon entropy. In a previous paper, the authors introduce a lossless compression algorithm developed for MODIS as a proxy for future NOAA-NESDIS satellite based Earth science multispectral imagers such as GOES-R. The algorithm is based on capturing spectral correlations using spectral prediction, and spatial correlations with a linear transform encoder. In decompression, the algorithm uses a statistically computed look up table to iteratively predict each channel from a channel decompressed in the previous iteration. In this paper we present a new approach which fundamentally differs from our prior work. In this new approach, instead of having a single predictor for each pair of bands we introduce a piecewise spatially varying predictor which significantly improves the compression results. Our new algorithm also now optimizes the sequence of channels we use for prediction. Our results are evaluated by comparison with a state of the art wavelet based image compression scheme, Jpeg2000. We present results on the 14 channel subset of the MODIS imager, which serves as a proxy for the GOES-R imager. We will also show results of the algorithm for on NOAA AVHRR data and data from SEVIRI. The algorithm is designed to be adapted to the wide range of multispectral imagers and should facilitate distribution of data throughout globally. This compression research is managed by Roger Heymann, PE of OSD NOAA NESDIS Engineering, in collaboration with the NOAA NESDIS STAR Research Office through Mitch Goldberg, Tim Schmit, Walter Wolf.

Future GOES-R global ground receivers

NASA Astrophysics Data System (ADS)

Dafesh, P. A.; Grayver, E.

2006-08-01

The Aerospace Corporation has developed an end-to-end testbed to demonstrate a wide range of modern modulation and coding alternatives for future broadcast by the GOES-R Global Rebroadcast (GRB) system. In particular, this paper describes the development of a compact, low cost, flexible GRB digital receiver that was designed, implemented, fabricated, and tested as part of the development. This receiver demonstrates a 10-fold increase in data rate compared to the rate achievable by the current GOES generation, without a major impact on either cost or size. The digital receiver is integrated on a single PCI card with an FPGA device, and analog-to-digital converters. It supports a wide range of modulations (including 8-PSK and 16-QAM) and turbo coding. With appropriate FPGA firmware and software changes, it can also be configured to receive the current (legacy) GOES signals. The receiver has been validated by sending large image files over a high-fidelity satellite channel emulator, including a space-qualified power amplifier and a white noise source. The receiver is a key component of a future GOES-R weather receiver system (also called user terminal) that includes the antenna, low-noise amplifier, downconverter, filters, digital receiver, and receiver system software. This work describes this receiver proof of concept and its application to providing a very credible estimate of the impact of using modern modulation and coding techniques in the future GOES-R system.

Satellite Proving Ground for the GOES-R Geostationary Lightning Mapper (GLM)

NASA Technical Reports Server (NTRS)

Goodman, Steven J.; Gurka, James; Bruning, E. C.; Blakeslee, J. R.; Rabin, Robert; Buechler, D.

2009-01-01

The key mission of the Satellite Proving Ground is to demonstrate new satellite observing data, products and capabilities in the operational environment to be ready on Day 1 to use the GOES-R suite of measurements. Algorithms, tools, and techniques must be tested, validated, and assessed by end users for their utility before they are finalized and incorporated into forecast operations. The GOES-R Proving Ground for the Geostationary Lightning Mapper (GLM) focuses on evaluating how the infusion of the new technology, algorithms, decision aids, or tailored products integrate with other available tools (weather radar and ground strike networks; nowcasting systems, mesoscale analysis, and numerical weather prediction models) in the hands of the forecaster responsible for issuing forecasts and warning products. Additionally, the testing concept fosters operation and development staff interactions which will improve training materials and support documentation development. Real-time proxy total lightning data from regional VHF lightning mapping arrays (LMA) in Northern Alabama, Central Oklahoma, Cape Canaveral Florida, and the Washington, DC Greater Metropolitan Area are the cornerstone for the GLM Proving Ground. The proxy data will simulate the 8 km Event, Group and Flash data that will be generated by GLM. Tailored products such as total flash density at 1-2 minute intervals will be provided for display in AWIPS-2 to select NWS forecast offices and national centers such as the Storm Prediction Center. Additional temporal / spatial combinations are being investigated in coordination with operational needs and case-study proxy data and prototype visualizations may also be generated from the NASA heritage Lightning Imaging Sensor and Optical Transient Detector data. End users will provide feedback on the utility of products in their operational environment, identify use cases and spatial/temporal scales of interest, and provide feedback to the developers for adjusted or new products.

GOES-R Lift and Mate

NASA Image and Video Library

2016-11-09

A crane begins to lift the payload fairing containing NOAA's Geostationary Operational Environmental Satellite (GOES-R) at the Vertical Integration Facility at Space Launch Complex 41 at Cape Canaveral Air Force Station in Florida. GOES-R will be mated to the United Launch Alliance Atlas V Centaur upper stage in preparation for launch in November. GOES-R is the first satellite in a series of next-generation NOAA GOES Satellites.

Solar Irradiance from GOES Albedo performance in a Hydrologic Model Simulation of Snowmelt Runoff

NASA Astrophysics Data System (ADS)

Sumargo, E.; Cayan, D. R.; McGurk, B. J.

2015-12-01

In many hydrologic modeling applications, solar radiation has been parameterized using commonly available measures, such as the daily temperature range, due to scarce in situ solar radiation measurement network. However, these parameterized estimates often produce significant biases. Here we test hourly solar irradiance derived from the Geostationary Operational Environmental Satellite (GOES) visible albedo product, using several established algorithms. Focusing on the Sierra Nevada and White Mountain in California, we compared the GOES irradiance and that from a traditional temperature-based algorithm with incoming irradiance from pyranometers at 19 stations. The GOES based estimates yielded 21-27% reduction in root-mean-squared error (average over 19 sites). The derived irradiance is then prescribed as an input to Precipitation-Runoff Modeling System (PRMS). We constrain our experiment to the Tuolumne River watershed and focus our attention on the winter and spring of 1996-2014. A root-mean-squared error reduction of 2-6% in daily inflow to Hetch Hetchy at the lower end of the Tuolumne catchment was achieved by incorporating the insolation estimates at only 8 out of 280 Hydrologic Response Units (HRUs) within the basin. Our ongoing work endeavors to apply satellite-derived irradiance at each individual HRU.

The Geostationary Operational Satellite R Series SpaceWire Based Data System Architecture

NASA Technical Reports Server (NTRS)

Krimchansky, Alexander; Anderson, William H.; Bearer, Craig

2010-01-01

The GOES-R program selected SpaceWire as the best solution to satisfy the desire for simple and flexible instrument to spacecraft command and telemetry communications. Data generated by GOES-R instruments is critical for meteorological forecasting, public safety, space weather, and other key applications. In addition, GOES-R instrument data is provided to ground stations on a 24/7 basis. GOES-R requires data errors be detected and corrected from origin to final destination. This paper describes GOES-R developed strategy to satisfy this requirement

GOES-R Lift and Mate

NASA Image and Video Library

2016-11-09

A crane is used to lift the payload fairing containing NOAA's Geostationary Operational Environmental Satellite (GOES-R) at the Vertical Integration Facility at Space Launch Complex 41 at Cape Canaveral Air Force Station in Florida. GOES-R will be mated to the United Launch Alliance Atlas V Centaur upper stage in preparation for launch in November. GOES-R is the first satellite in a series of next-generation NOAA GOES Satellites.

GOES-R Rollout from VIF to Pad 41

NASA Image and Video Library

2016-11-18

A United Launch Alliance Atlas V rocket arrives at Space Launch Complex 41 at Cape Canaveral Air Force Station in Florida. In view is the upper stage and payload fairing containing the Geostationary Operational Environmental Satellite (GOES-R). The launch vehicle will send GOES-R to a geostationary position over the U.S. GOES-R is the first satellite in a series of next-generation NOAA GOES satellites.

GOES-R Lift and Mate

NASA Image and Video Library

2016-11-09

Enclosed in its payload fairing, NOAA's Geostationary Operational Environmental Satellite (GOES-R) is lifted into the Vertical Integration Facility at Space Launch Complex 41 at Cape Canaveral Air Force Station in Florida. GOES-R will be mated to the United Launch Alliance Atlas V Centaur upper stage in preparation for launch aboard the rocket in November. GOES-R is the first satellite in a series of next-generation NOAA GOES Satellites.

GOES-R Lift and Mate

NASA Image and Video Library

2016-11-09

Preparations are underway to lift NOAA's Geostationary Operational Environmental Satellite (GOES-R), enclosed in its payload fairing at the Vertical Integration Facility at Space Launch Complex 41 at Cape Canaveral Air Force Station in Florida. GOES-R will be mated to the United Launch Alliance Atlas V Centaur upper stage in preparation for launch in November. GOES-R is the first satellite in a series of next-generation NOAA GOES Satellites.

GOES-R Lift and Mate

NASA Image and Video Library

2016-11-09

A crane has been attached to the payload fairing containing NOAA's Geostationary Operational Environmental Satellite (GOES-R) at the Vertical Integration Facility at Space Launch Complex 41 at Cape Canaveral Air Force Station in Florida. GOES-R will be mated to the United Launch Alliance Atlas V Centaur upper stage in preparation for launch in November. GOES-R is the first satellite in a series of next-generation NOAA GOES Satellites.

Preliminary GOES-R ABI navigation and registration assessment results

NASA Astrophysics Data System (ADS)

Tan, B.; Dellomo, J.; Wolfe, R. E.; Reth, A. D.

2017-12-01

The US Geostationary Operational Environmental Satellite - R Series (GOES-R) was launched on November 19, 2016, and was designated GOESR-16 upon reaching geostationary orbit ten days later. The Advanced Baseline Imager (ABI) is the primary instrument on the GOES-R series for imaging Earth's surface and atmosphere to aid in weather prediction and climate monitoring. We developed algorithms and software for independent verification of the ABI Image Navigation and Registration (INR). Since late January 2017, four INR metrics have been continuously generated to monitor the ABI INR performance: navigation (NAV) error, channel-to-channel registration (CCR) error, frame-to-frame registration (FFR) error, and within-frame registration (WIFR) error. In this paper, we will describe the fundamental algorithm used for the image registration and briefly discuss the processing flow of INR Performance Assessment Tool Set (IPATS) developed for ABI INR. The assessment of the accuracy shows that IPATS measurements error is about 1/20 of the size of a pixel. Then the GOES-16 NAV assessments results, the primary metric, from January to August 2017, will be presented. The INR has improved over time as post-launch tests were performed and corrections were applied. The mean NAV error of the visible and near infrared (VNIR) channels dropped from 20 μrad in January to around 5 μrad (+/-4 μrad, 1 σ) in June, while the mean NAV error of long wave infrared (LWIR) channels dropped from around 70 μrad in January to around 5 μrad (+/-15 μrad, 1 σ) in June. A full global ABI image is composed with 22 east-west direction swaths. The swath-wise NAV error analysis shows that there was some variation in the mean swath-wise NAV errors. The variations are about as much as 20% of the scene NAV mean errors. As expected, the swaths over the tropical area have far fewer valid assessments (matchups) than those in mid-latitude region due to cloud coverage. It was also found that there was a rotation (clocking) of the focal plane of LWIR that was seen in both the NAV and CCR results. The rotation was corrected by an INR update in June 2017. Through deep-dive examinations of the scenes with large mean and/or variation in INR errors, we validated that IPATS is an excellent tool for assessing and improving the GOES-16 ABI INR and is also useful in INR long-term monitoring.

GOES-R Science Briefing

NASA Image and Video Library

2016-11-17

In the Kennedy Space Center's Press Site auditorium, Steven Goodman, NOAA's GOES-R program scientist, speaks to the media during a mission briefing on the Geostationary Operational Environmental Satellite (GOES-R). GOES-R is the first satellite in a series of next-generation GOES satellites for NOAA, the National Oceanographic and Atmospheric Administration. It will launch to a geostationary orbit over the western hemisphere to provide images of storms and help meteorologists predict severe weather conditionals and develop long-range forecasts.

Pre-Launch GOES-R Risk Reduction Activities for the Geostationary Lightning Mapper

NASA Technical Reports Server (NTRS)

Goodman, S. J.; Blakeslee, R. J.; Boccippio, D. J.; Christian, H. J.; Koshak, W. J.; Petersen, W. A.

2005-01-01

The GOES-R Geostationary Lightning Mapper (GLM) is a new instrument planned for GOES-R that will greatly improve storm hazard nowcasting and increase warning lead time day and night. Daytime detection of lightning is a particularly significant technological advance given the fact that the solar illuminated cloud-top signal can exceed the intensity of the lightning signal by a factor of one hundred. Our approach is detailed across three broad themes which include: Data Processing Algorithm Readiness, Forecast Applications, and Radiance Data Mining. These themes address how the data will be processed and distributed, and the algorithms and models for developing, producing, and using the data products. These pre-launch risk reduction activities will accelerate the operational and research use of the GLM data once GOES-R begins on-orbit operations. The GLM will provide unprecedented capabilities for tracking thunderstorms and earlier warning of impending severe and hazardous weather threats. By providing direct information on lightning initiation, propagation, extent, and rate, the GLM will also capture the updraft dynamics and life cycle of convective storms, as well as internal ice precipitation processes. The GLM provides information directly from the heart of the thunderstorm as opposed to cloud-top only. Nowcasting applications enabled by the GLM data will expedite the warning and response time of emergency management systems, improve the dispatch of electric power utility repair crews, and improve airline routing around thunderstorms thereby improving safety and efficiency, saving fuel and reducing delays. The use of GLM data will assist the Bureau of Land Management (BLM) and the Forest Service in quickly detecting lightning ground strikes that have a high probability of causing fires. Finally, GLM data will help assess the role of thunderstorms and deep convection in global climate, and will improve regional air quality and global chemistry/climate modeling. The GLM has a robust design that benefits and improves upon its strong heritage of NASA-developed LEO predecessors, the Optical Transient Detector (OTD) and the Lightning Imaging Sensor (LIS). GLM will have a substantially larger number of pixels within the focal plane, two lens systems, and multiple Real-Time Event Processors REPS for on-board event detection and data compression to provide continuous observations of the Americas and adjacent oceans.

GOES-R Space Weather Data: Ensuring Access and Usability

NASA Astrophysics Data System (ADS)

Tilton, M.; Rowland, W. F.; Wilkinson, D. C.; Denig, W. F.; Darnel, J.; Kress, B. T.; Loto'aniu, P. T. M.; Machol, J. L.; Redmon, R. J.; Rodriguez, J. V.

2015-12-01

The upcoming Geostationary Operational Environmental Satellite series, GOES-R, will provide critical space weather data. These data are used to prevent communication outages, mitigate the damage solar weather causes to satellites and power grids, and reduce astronaut radiation exposure. The space weather instruments aboard GOES-R will deliver an operational dataset of unprecedented breadth. However, NOAA's National Centers for Environmental Information (NCEI)—the organization that provides access to archived GOES-R data—has faced several challenges in delivering this information to customers in usable form. For instance, the GOES-R ground system was contracted to develop higher-level products for terrestrial data but not space weather data. Variations in GOES-R data file formats and archive locations have also threatened to create an inconsistent user experience. This presentation will examine the ways in which NCEI is making GOES-R space weather data more accessible and actionable for customers. These efforts include NCEI's development of high-level data products to meet the requirements of NOAA's Space Weather Prediction Center—a role NCEI has not previously played. In addition, NCEI is creating a demonstration system to show how these products can be produced in real-time. The organization is also examining customer usage of the GOES-NOP data access system and using these access patterns to drive decisions about the GOES-R user interface.

Satellite Remote Sensing of Tropical Precipitation and Ice Clouds for GCM Verification

NASA Technical Reports Server (NTRS)

Evans, K. Franklin

2001-01-01

This project, supported by the NASA New Investigator Program, has primarily been funding a graduate student, Darren McKague. Since August 1999 Darren has been working part time at Raytheon, while continuing his PhD research. Darren is planning to finish his thesis work in May 2001, thus some of the work described here is ongoing. The proposed research was to use GOES visible and infrared imager data and SSM/I microwave data to obtain joint distributions of cirrus cloud ice mass and precipitation for a study region in the Eastern Tropical Pacific. These joint distributions of cirrus cloud and rainfall were to be compared to those from the CSU general circulation model to evaluate the cloud microphysical amd cumulus parameterizations in the GCM. Existing algorithms were to be used for the retrieval of cloud ice water path from GOES (Minnis) and rainfall from SSM/I (Wilheit). A theoretical study using radiative transfer models and realistic variations in cloud and precipitation profiles was to be used to estimate the retrieval errors. Due to the unavailability of the GOES satellite cloud retrieval algorithm from Dr. Minnis (a co-PI), there was a change in the approach and emphasis of the project. The new approach was to develop a completely new type of remote sensing algorithm - one to directly retrieve joint probability density functions (pdf's) of cloud properties from multi-dimensional histograms of satellite radiances. The usual approach is to retrieve individual pixels of variables (i.e. cloud optical depth), and then aggregate the information. Only statistical information is actually needed, however, and so a more direct method is desirable. We developed forward radiative transfer models for the SSM/I and GOES channels, originally for testing the retrieval algorithms. The visible and near infrared ice scattering information is obtained from geometric ray tracing of fractal ice crystals (Andreas Macke), while the mid-infrared and microwave scattering is computed with Mie scattering. The radiative transfer is performed with the Spherical Harmonic Discrete Ordinate Method (developed by the PI), and infrared molecular absorption is included with the correlated k-distribution method. The SHDOM radiances have been validated by comparison to version 2 of DISORT (the community "standard" discrete-ordinates radiative transfer model), however we use SHDOM since it is computationally more efficient.

GOES-R Science Briefing

NASA Image and Video Library

2016-11-17

In the Kennedy Space Center's Press Site auditorium, members of the media participate in a mission briefing on the Geostationary Operational Environmental Satellite (GOES-R). Briefing participants included Steven Goodman, NOAA's GOES-R program scientist, and Joseph A. Pica, director of the National Weather Service Office of Observations. GOES-R is the first satellite in a series of next-generation GOES satellites for NOAA, the National Oceanographic and Atmospheric Administration. It will launch to a geostationary orbit over the western hemisphere to provide images of storms and help meteorologists predict severe weather conditionals and develop long-range forecasts.

The GOES-R Proving Ground: 2012 Update

NASA Astrophysics Data System (ADS)

Gurka, J.; Goodman, S. J.; Schmit, T.; Demaria, M.; Mostek, A.; Siewert, C.; Reed, B.

2011-12-01

The Geostationary Operational Environmental Satellite (GOES)-R will provide a great leap forward in observing capabilities, but will also offer a significant challenge to ensure that users are ready to exploit the vast improvements in spatial, spectral, and temporal resolutions. To ensure user readiness, forecasters and other users must have access to prototype advanced products well before launch, and have the opportunity to provide feedback to product developers and computing and communications managers. The operational assessment is critical to ensure that the end products and NOAA's computing and communications systems truly meet their needs in a rapidly evolving environment. The GOES-R Proving Ground (PG) engages the National Weather Service (NWS) forecast, watch and warning community and other agency users in pre-operational demonstrations of select products with GOES-R attributes (enhanced spectral, spatial, and temporal resolution). In the PG, developers and forecasters test and apply algorithms for new GOES-R satellite data and products using proxy and simulated data sets, including observations from current and future satellite instruments (MODIS, AIRS, IASI, SEVIRI, NAST-I, NPP/VIIRS/CrIS, LIS), lightning networks, and computer simulated products. The complete list of products to be evaluated in 2012 will be determined after evaluating results from experiments in 2011 at the NWS' Storm Prediction Center, National Hurricane Center, Aviation Weather Center, Ocean Prediction Center, Hydrometeorological Prediction Center, and from the six NWS regions. In 2012 and beyond, the PG will test and validate data processing and distribution systems and the applications of these products in operational settings. Additionally developers and forecasters will test and apply display techniques and decision aid tools in operational environments. The PG is both a recipient and a source of training. Training materials are developed using various distance training tools in close collaboration with NWS Training Division and its partners at COMET, CIMSS, CIRA and other offices. The training is used to prepare the participants of PG activities, such as the Hazardous Weather Testbed's Spring Experiment and other locations listed above. A key component of the proving ground is two-way interaction, where researchers introduce new products and techniques to forecasters and other scientists. The forecasters and other users then provide feedback and ideas for improved or new products and how to best incorporate these into NOAA's integrated observing and analysis operations. This presentation will provide examples of GOES-R proxy products and forecaster evaluations from experiments at the Storm Prediction Center (SPC), the National Hurricane Center (NHC), the Aviation Weather Center (AWC), and the Alaska Region.

Sao Paulo Lightning Mapping Array (SP-LMA): Network Assessment and Analyses for Intercomparison Studies and GOES-R Proxy Activities

NASA Technical Reports Server (NTRS)

Bailey, J. C.; Blakeslee, R. J.; Carey, L. D.; Goodman, S. J.; Rudlosky, S. D.; Albrecht, R.; Morales, C. A.; Anselmo, E. M.; Neves, J. R.; Buechler, D. E.

2014-01-01

A 12 station Lightning Mapping Array (LMA) network was deployed during October 2011 in the vicinity of Sao Paulo, Brazil (SP-LMA) to contribute total lightning measurements to an international field campaign [CHUVA - Cloud processes of tHe main precipitation systems in Brazil: A contribUtion to cloud resolVing modeling and to the GPM (GlobAl Precipitation Measurement)]. The SP-LMA was operational from November 2011 through March 2012 during the Vale do Paraiba campaign. Sensor spacing was on the order of 15-30 km, with a network diameter on the order of 40-50km. The SP-LMA provides good 3-D lightning mapping out to 150 km from the network center, with 2-D coverage considerably farther. In addition to supporting CHUVA science/mission objectives, the SP-LMA is supporting the generation of unique proxy data for the Geostationary Lightning Mapper (GLM) and Advanced Baseline Imager (ABI), on NOAA's Geostationary Operational Environmental Satellite-R (GOES-R: scheduled for a 2015 launch). These proxy data will be used to develop and validate operational algorithms so that they will be ready to use on "day1" following the GOES-R launch. As the CHUVA Vale do Paraiba campaign opportunity was formulated, a broad community-based interest developed for a comprehensive Lightning Location System (LLS) intercomparison and assessment study, leading to the participation and/or deployment of eight other ground-based networks and the space-based Lightning Imaging Sensor (LIS). The SP-LMA data is being intercompared with lightning observations from other deployed lightning networks to advance our understanding of the capabilities/contributions of each of these networks toward GLM proxy and validation activities. This paper addresses the network assessment including noise reduction criteria, detection efficiency estimates, and statistical and climatological (both temporal and spatially) analyses for intercomparison studies and GOES-R proxy activities.

STEM connections to the GOES-R Satellite Series

NASA Astrophysics Data System (ADS)

Mooney, M. E.; Schmit, T.

2015-12-01

GOES-R, a new Geostationary Operational Environmental Satellite (GOES) is scheduled to be launched in October of 2016. Its role is to continue western hemisphere satellite coverage while the existing GOES series winds down its 20-year operation. However, instruments on the next generation GOES-R satellite series will provide major improvements to the current GOES, both in the frequency of images acquired and the spectral and spatial resolution of the images, providing a perfect conduit for STEM education. Most of these improvements will be provided by the Advanced Baseline Imager (ABI). ABI will provide three times more spectral information, four times the spatial resolution, and more than five times faster temporal coverage than the current GOES. Another exciting addition to the GOES-R satellite series will be the Geostationary Lightning Mapper (GLM). The all new GLM on GOES-R will measure total lightning activity continuously over the Americas and adjacent ocean regions with near uniform spatial resolution of approximately 10 km! Due to ABI, GLM and improved spacecraft calibration and navigation, the next generation GOES-R satellite series will usher in an exciting era of satellite applications and opportunities for STEM education. This session will present and demonstrate exciting next-gen imagery advancements and new HTML5 WebApps that demonstrate STEM connections to these improvements. Participants will also be invited to join the GOES-R Education Proving Ground, a national network of educators who will receive stipends to attend 4 webinars during the spring of 2016, pilot a STEM lesson plan, and organize a school-wide launch awareness event.

GOES-R Encapsulation

NASA Image and Video Library

2016-10-21

The two halves of the payload fairing are fully closed around the Geostationary Operational Environmental Satellite (GOES-R) inside the Astrotech payload processing facility in Titusville, Florida near NASA’s Kennedy Space Center. GOES-R will be the first satellite in a series of next-generation NOAA GOES Satellites. The spacecraft is to launch aboard a United Launch Alliance Atlas V rocket in November.

GOES-R Rollout from VIF to Pad 41

NASA Image and Video Library

2016-11-18

A United Launch Alliance Atlas V rocket arrives at Space Launch Complex 41 at Cape Canaveral Air Force Station in Florida. The launch vehicle will send the Geostationary Operational Environmental Satellite (GOES-R) to a geostationary position over the U.S. GOES-R is the first satellite in a series of next-generation NOAA GOES satellites.

The GOES-R Spacecraft Space Weather Instruments and Level 2+ Products

NASA Astrophysics Data System (ADS)

Loto'aniu, Paul; Rodriguez, Juan; Machol, Janet; Kress, Brian; Darnel, Jonathan; Redmon, Robert; Rowland, William; Seation, Daniel; Tilton, Margaret; Denig, William

2016-04-01

Since their inception in the 1970s, the GOES satellites have monitored the sources of space weather on the sun and the effects of space weather at Earth. The space weather instruments on GOES-R will monitor: solar X-rays, UV light, solar energetic particles, magnetospheric energetic particles, galactic cosmic rays, and Earth's magnetic field. These measurements are important for providing alerts and warnings to many customers, including satellite operators, the power utilities, and NASA's human activities in space. This presentation reviews the capabilities of the GOES-R space weather instruments and describes the space weather Level 2+ products that are being developed for GOES-R. These new and continuing data products will be an integral part of NOAA space weather operations in the GOES-R era.

GOES-R ITAR Photos for Media Day

NASA Image and Video Library

2016-09-26

The Geostationary Operational Environmental Satellite (GOES-R) is undergoing final launch preparations prior to fueling inside the Astrotech payload processing facility in Titusville, Florida near NASA’s Kennedy Space Center. GOES-R will be the first satellite in a series of next-generation NOAA GOES Satellites. The spacecraft is to launch aboard a United Launch Alliance Atlas V rocket in November.

GOES-R Rotation to Vertical

NASA Image and Video Library

2016-09-15

The Geostationary Operational Environmental Satellite (GOES-R) is lifted to the vertical position on an “up-ender” inside the Astrotech payload processing facility in Titusville, Florida near NASA’s Kennedy Space Center. GOES-R will be the first satellite in a series of next-generation NOAA GOES Satellites. The spacecraft is to launch aboard a United Launch Alliance Atlas V rocket in November.

GOES-R Encapsulation

NASA Image and Video Library

2016-10-21

Team members with United Launch Alliance (ULA) prepare the Geostationary Operational Environmental Satellite (GOES-R) for encapsulation in the payload fairing inside the Astrotech payload processing facility in Titusville, Florida near NASA’s Kennedy Space Center. GOES-R will be the first satellite in a series of next-generation NOAA GOES Satellites. The spacecraft is to launch aboard a ULA Atlas V rocket in November.

GOES-R Fairing Inspection

NASA Image and Video Library

2016-09-26

Team members with United Launch Alliance (ULA) inspect the first half of the fairing for the Geostationary Operational Environmental Satellite (GOES-R) inside the Astrotech payload processing facility in Titusville, Florida near NASA’s Kennedy Space Center. GOES-R will be the first satellite in a series of next-generation NOAA GOES Satellites. The spacecraft is to launch aboard a ULA Atlas V rocket in November.

GOES-R Rotation to Vertical

NASA Image and Video Library

2016-09-15

The Geostationary Operational Environmental Satellite (GOES-R) is raised to the vertical position on an “up-ender” inside the Astrotech payload processing facility in Titusville, Florida near NASA’s Kennedy Space Center. GOES-R will be the first satellite in a series of next-generation NOAA GOES Satellites. The spacecraft is to launch aboard a United Launch Alliance Atlas V rocket in November.

GOES-R Rotation to Vertical

NASA Image and Video Library

2016-09-15

The Geostationary Operational Environmental Satellite (GOES-R) has been secured in the vertical position on an “up-ender” inside the Astrotech payload processing facility in Titusville, Florida near NASA’s Kennedy Space Center. GOES-R will be the first satellite in a series of next-generation NOAA GOES Satellites. The spacecraft is to launch aboard a United Launch Alliance Atlas V rocket in November.

GOES-R Rotation to Vertical

NASA Image and Video Library

2016-09-15

Team members are securing the Geostationary Operational Environmental Satellite (GOES-R) in the vertical position on an “up-ender” inside the Astrotech payload processing facility in Titusville, Florida near NASA’s Kennedy Space Center. GOES-R will be the first satellite in a series of next-generation NOAA GOES Satellites. The spacecraft is to launch aboard a United Launch Alliance Atlas V rocket in November.

GOES-R Atlas V Centaur Lift and Mate

NASA Image and Video Library

2016-10-31

The United Launch Alliance Atlas V Centaur second stage is lifted up for transfer into the Vertical Integration Facility at Space Launch Complex 41 at Cape Canaveral Air Force Station in Florida. The Geostationary Operational Environmental Satellite (GOES-R) will launch aboard the Atlas V rocket in November. GOES-R is the first satellite in a series of next-generation NOAA GOES Satellites.

GOES-R: Satellite Insight

NASA Technical Reports Server (NTRS)

Fitzpatrick, Austin J.; Leon, Nancy J.; Novati, Alexander; Lincoln, Laura K.; Fisher, Diane K.

2012-01-01

GOES-R: Satellite Insight seeks to bring awareness of the GOES-R (Geostationary Operational Environmental Satellite -- R Series) satellite currently in development to an audience of all ages on the emerging medium of mobile games. The iPhone app (Satellite Insight) was created for the GOES-R Program. The app describes in simple terms the types of data products that can be produced from GOES-R measurements. The game is easy to learn, yet challenging for all audiences. It includes educational content and a path to further information about GOESR, its technology, and the benefits of the data it collects. The game features action-puzzle game play in which the player must prevent an overflow of data by matching falling blocks that represent different types of GOES-R data. The game adds more different types of data blocks over time, as long as the player can prevent a data overflow condition. Points are awarded for matches, and players can compete with themselves to beat their highest score.

GOES-S Rotate to Vertical

NASA Image and Video Library

2017-12-05

At Astrotech Space Operations in Titusville, Florida, technicians and engineers inspect NOAA's Geostationary Operation Environmental Satellite-S (GOES-S) after removal from its shipping container. GOES-S is the second in a series of four advanced geostationary weather satellites. The GOES-R series - consisting of the GOES-R, GOES-S, GOES-T and GOES-U spacecraft - will significantly improve the detection and observation of environmental phenomena that directly affect public safety, protection of property and the nation's economic health and prosperity. GOES-S is slated to launch March 1, 2018 aboard a United Launch Alliance Atlas V rocket from Cape Canaveral Air Force Station in Florida.

GOES-S Uncrating

NASA Image and Video Library

2017-12-05

At Astrotech Space Operations in Titusville, Florida, NOAA's Geostationary Operation Environmental Satellite-S (GOES-S) has been removed from its shipping container. GOES-S is the second in a series of four advanced geostationary weather satellites. The GOES-R series - consisting of the GOES-R, GOES-S, GOES-T and GOES-U spacecraft - will significantly improve the detection and observation of environmental phenomena that directly affect public safety, protection of property and the nation's economic health and prosperity. GOES-S is slated to launch March 1, 2018 aboard a United Launch Alliance Atlas V rocket from Cape Canaveral Air Force Station in Florida.

GOES-S Uncrating

NASA Image and Video Library

2017-12-05

At Astrotech Space Operations in Titusville, Florida, technicians and engineers remove NOAA's Geostationary Operation Environmental Satellite-S (GOES-S) from its shipping container. GOES-S is the second in a series of four advanced geostationary weather satellites. The GOES-R series - consisting of the GOES-R, GOES-S, GOES-T and GOES-U spacecraft - will significantly improve the detection and observation of environmental phenomena that directly affect public safety, protection of property and the nation's economic health and prosperity. GOES-S is slated to launch March 1, 2018 aboard a United Launch Alliance Atlas V rocket from Cape Canaveral Air Force Station in Florida.

GOES-S Uncrating

NASA Image and Video Library

2017-12-05

At Astrotech Space Operations in Titusville, Florida, technicians and engineers inspect NOAA's Geostationary Operation Environmental Satellite-S (GOES-S) after removal from its shipping container. GOES-S is the second in a series of four advanced geostationary weather satellites. The GOES-R series - consisting of the GOES-R, GOES-S, GOES-T and GOES-U spacecraft - will significantly improve the detection and observation of environmental phenomena that directly affect public safety, protection of property and the nation's economic health and prosperity. GOES-S is slated to launch March 1, 2018 aboard a United Launch Alliance Atlas V rocket from Cape Canaveral Air Force Station in Florida.

Long-Term Stability Assessment of Sonoran Desert for Vicarious Calibration of GOES-R

NASA Astrophysics Data System (ADS)

Kim, W.; Liang, S.; Cao, C.

2012-12-01

Vicarious calibration refers to calibration techniques that do not depend on onboard calibration devices. Although sensors and onboard calibration devices undergo rigorous validation processes before launch, performance of sensors often degrades after the launch due to exposure to the harsh space environment and the aging of devices. Such in-flight changes of devices can be identified and adjusted through vicarious calibration activities where the sensor degradation is measured in reference to exterior calibration sources such as the Sun, the Moon, and the Earth surface. Sonoran desert is one of the best calibration sites located in the North America that are available for vicarious calibration of GOES-R satellite. To accurately calibrate sensors onboard GOES-R satellite (e.g. advanced baseline imager (ABI)), the temporal stability of Sonoran desert needs to be assessed precisely. However, short-/mid-term variations in top-of-atmosphere (TOA) reflectance caused by meteorological variables such as water vapor amount and aerosol loading are often difficult to retrieve, making the use of TOA reflectance time series for the stability assessment of the site. In this paper, we address this issue of normalization of TOA reflectance time series using a time series analysis algorithm - seasonal trend decomposition procedure based on LOESS (STL) (Cleveland et al, 1990). The algorithm is basically a collection of smoothing filters which leads to decomposition of a time series into three additive components; seasonal, trend, and remainder. Since this non-linear technique is capable of extracting seasonal patterns in the presence of trend changes, the seasonal variation can be effectively identified in the time series of remote sensing data subject to various environmental changes. The experiment results performed with Landsat 5 TM data show that the decomposition results acquired for the Sonoran Desert area produce normalized series that have much less uncertainty than those of traditional BRDF models, which leads to more accurate stability assessment.

GOES-R Rotation to Vertical

NASA Image and Video Library

2016-09-15

Team members assist as the Geostationary Operational Environmental Satellite (GOES-R) is prepared for lifting to the vertical position on an “up-ender” inside the Astrotech payload processing facility in Titusville, Florida near NASA’s Kennedy Space Center. GOES-R will be the first satellite in a series of next-generation NOAA GOES Satellites. The spacecraft is to launch aboard a United Launch Alliance Atlas V rocket in November.

GOES-R Encapsulation

NASA Image and Video Library

2016-10-21

Team members with United Launch Alliance (ULA) monitor the progress as the two halves of the payload fairing close around the Geostationary Operational Environmental Satellite (GOES-R) inside the Astrotech payload processing facility in Titusville, Florida near NASA’s Kennedy Space Center. GOES-R will be the first satellite in a series of next-generation NOAA GOES Satellites. The spacecraft is to launch aboard a ULA Atlas V rocket in November.

GOES-R Advanced Base Line Imager Installation

NASA Image and Video Library

2016-08-30

Team members prepare the Advanced Base Line Imager, the primary optical instrument, for installation on the Geostationary Operational Environmental Satellite (GOES-R) inside the Astrotech payload processing facility in Titusville, Florida near NASA’s Kennedy Space Center. GOES-R will be the first satellite in a series of next-generation NOAA GOES Satellites. The spacecraft is to launch aboard a United Launch Alliance Atlas V rocket in November.

GOES-R Fairing Inspection

NASA Image and Video Library

2016-09-26

Team members with United Launch Alliance (ULA) inspect an clean the first half of the fairing for the Geostationary Operational Environmental Satellite (GOES-R) inside the Astrotech payload processing facility in Titusville, Florida near NASA’s Kennedy Space Center. GOES-R will be the first satellite in a series of next-generation NOAA GOES Satellites. The spacecraft is to launch aboard a ULA Atlas V rocket in November.

GOES-R Lift and Mate

NASA Image and Video Library

2016-11-09

Enclosed in its payload fairing, NOAA's Geostationary Operational Environmental Satellite (GOES-R) is mated to the United Launch Alliance Atlas V Centaur upper stage in the Vertical Integration Facility at Space Launch Complex 41 at Cape Canaveral Air Force Station in Florida. The satellite will launch aboard the Atlas V rocket in November. GOES-R is the first satellite in a series of next-generation NOAA GOES Satellites.

GOES-R Rotation to Vertical

NASA Image and Video Library

2016-09-15

Team members monitor the progress as the Geostationary Operational Environmental Satellite (GOES-R) is lifted to the vertical position on an “up-ender” inside the Astrotech payload processing facility in Titusville, Florida near NASA’s Kennedy Space Center. GOES-R will be the first satellite in a series of next-generation NOAA GOES Satellites. The spacecraft is to launch aboard a United Launch Alliance Atlas V rocket in November.

GOES-R Advanced Base Line Imager Installation

NASA Image and Video Library

2016-08-30

Team members install the Advanced Base Line Imager, the primary optical instrument, on the Geostationary Operational Environmental Satellite (GOES-R) inside the Astrotech payload processing facility in Titusville, Florida near NASA’s Kennedy Space Center. GOES-R will be the first satellite in a series of next-generation NOAA GOES Satellites. The spacecraft is to launch aboard a United Launch Alliance Atlas V rocket in November.

GOES-R Advanced Base Line Imager Installation

NASA Image and Video Library

2016-08-30

The Advanced Base Line Imager, the primary optical instrument, has been installed on the Geostationary Operational Environmental Satellite (GOES-R) inside the Astrotech payload processing facility in Titusville, Florida near NASA’s Kennedy Space Center. GOES-R will be the first satellite in a series of next-generation NOAA GOES Satellites. The spacecraft is to launch aboard a United Launch Alliance Atlas V rocket in November.

GOES-R Rotation to Vertical

NASA Image and Video Library

2016-09-15

Team members check the Geostationary Operational Environmental Satellite (GOES-R) after it was lifted to the vertical position on an “up-ender” inside the Astrotech payload processing facility in Titusville, Florida near NASA’s Kennedy Space Center. GOES-R will be the first satellite in a series of next-generation NOAA GOES Satellites. The spacecraft is to launch aboard a United Launch Alliance Atlas V rocket in November.

GOES-R Fairing Inspection

NASA Image and Video Library

2016-09-26

Both halves of the fairing for the Geostationary Operational Environmental Satellite (GOES-R) are being inspected and cleaned by United Launch Alliance (ULA) team members inside the Astrotech payload processing facility in Titusville, Florida near NASA’s Kennedy Space Center. GOES-R will be the first satellite in a series of next-generation NOAA GOES Satellites. The spacecraft is to launch aboard a ULA Atlas V rocket in November.

GOES-R Atlas V Centaur Lift and Mate

NASA Image and Video Library

2016-10-31

Operations are underway to stack the United Launch Alliance Atlas V Centaur second stage onto the first stage in the Vertical Integration Facility at Space Launch Complex 41 at Cape Canaveral Air Force Station in Florida. The Geostationary Operational Environmental Satellite (GOES-R) will launch aboard the Atlas V rocket in November. GOES-R is the first satellite in a series of next-generation NOAA GOES Satellites.

GOES-R Atlas V Centaur Lift and Mate

NASA Image and Video Library

2016-10-31

A close-up view of the United Launch Alliance Atlas V Centaur second stage as it travels to the Vertical Integration Facility at Space Launch Complex 41 at Cape Canaveral Air Force Station in Florida. The Geostationary Operational Environmental Satellite (GOES-R) will launch aboard the Atlas V rocket in November. GOES-R is the first satellite in a series of next-generation NOAA GOES Satellites.

GOES-R Atlas V Centaur Lift and Mate

NASA Image and Video Library

2016-10-31

The United Launch Alliance Atlas V Centaur second stage has been lifted up and transferred into the Vertical Integration Facility at Space Launch Complex 41 at Cape Canaveral Air Force Station in Florida. The Geostationary Operational Environmental Satellite (GOES-R) will launch aboard the Atlas V rocket in November. GOES-R is the first satellite in a series of next-generation NOAA GOES Satellites.

GOES-R Atlas V Centaur Lift and Mate

NASA Image and Video Library

2016-10-31

United Launch Alliance team members assist as operation begin to lift the Atlas V Centaur second stage into the Vertical Integration Facility at Space Launch Complex 41 at Cape Canaveral Air Force Station in Florida. The Geostationary Operational Environmental Satellite (GOES-R) will launch aboard the Atlas V rocket in November. GOES-R is the first satellite in a series of next-generation NOAA GOES Satellites.

GOES-R Atlas V Centaur Lift and Mate

NASA Image and Video Library

2016-10-31

The United Launch Alliance Atlas V Centaur second stage is lifted up by crane for transfer into Vertical Integration Facility at Space Launch Complex 41 at Cape Canaveral Air Force Station in Florida. The Geostationary Operational Environmental Satellite (GOES-R) will launch aboard the Atlas V rocket in November. GOES-R is the first satellite in a series of next-generation NOAA GOES Satellites.

GOES-R Atlas V Centaur Lift and Mate

NASA Image and Video Library

2016-10-31

The United Launch Alliance Atlas V Centaur second stage has been mated to the first stage in the Vertical Integration Facility at Space Launch Complex 41 at Cape Canaveral Air Force Station in Florida. The Geostationary Operational Environmental Satellite (GOES-R) will launch aboard the Atlas V rocket in November. GOES-R is the first satellite in a series of next-generation NOAA GOES Satellites.

NOAA: Primary GOES-R instrument cleared for installation onto spacecraft

Science.gov Websites

: NOAA-NASA GOES-R Program Office) In early 2014 the ABI will be shipped from its developer, Exelis, in performance of power grids. NOAA manages the GOES-R Series program through an integrated NOAA-NASA office

GOES-R Science Briefing

NASA Image and Video Library

2016-11-17

In the Kennedy Space Center's Press Site auditorium, members of the media participate in a mission briefing on the Geostationary Operational Environmental Satellite (GOES-R). Briefing participants from left are: Steven Goodman, NOAA's GOES-R program scientist; Joseph A. Pica, director of the National Weather Service Office of Observations; and Sandra Cauffman, deputy director of NASA's Earth Science Division. GOES-R is the first satellite in a series of next-generation GOES satellites for NOAA, the National Oceanographic and Atmospheric Administration. It will launch to a geostationary orbit over the western hemisphere to provide images of storms and help meteorologists predict severe weather conditionals and develop long-range forecasts.

GOES-S Arrival to Astrotech

NASA Image and Video Library

2017-12-05

NOAA's Geostationary Operation Environmental Satellite-S (GOES-S) arrives at Astrotech Space Operations in Titusville, Florida, to prepare it for launch. The facility is located near NASA's Kennedy Space Center. GOES-S is the second in a series of four advanced geostationary weather satellites. The GOES-R series - consisting of the GOES-R, GOES-S, GOES-T and GOES-U spacecraft - will significantly improve the detection and observation of environmental phenomena that directly affect public safety, protection of property and the nation's economic health and prosperity. GOES-S is slated to launch March 1, 2018 aboard a United Launch Alliance Atlas V rocket from Cape Canaveral Air Force Station in Florida.

GOES-S Arrival at Astrotech Space Operations

NASA Image and Video Library

2017-12-05

NOAA's Geostationary Operation Environmental Satellite-S (GOES-S) arrives inside Astrotech Space Operations in Titusville, Florida, to prepare it for launch. The facility is located near NASA's Kennedy Space Center. GOES-S is the second in a series of four advanced geostationary weather satellites. The GOES-R series - consisting of the GOES-R, GOES-S, GOES-T and GOES-U spacecraft - will significantly improve the detection and observation of environmental phenomena that directly affect public safety, protection of property and the nation's economic health and prosperity. GOES-S is slated to launch March 1, 2018 aboard a United Launch Alliance Atlas V rocket from Cape Canaveral Air Force Station in Florida.

GOES-S Arrival at Astrotech Space Operations

NASA Image and Video Library

2017-12-05

NOAA's Geostationary Operation Environmental Satellite-S (GOES-S) arrives at Astrotech Space Operations in Titusville, Florida, to prepare it for launch. The facility is located near NASA's Kennedy Space Center. GOES-S is the second in a series of four advanced geostationary weather satellites. The GOES-R series - consisting of the GOES-R, GOES-S, GOES-T and GOES-U spacecraft - will significantly improve the detection and observation of environmental phenomena that directly affect public safety, protection of property and the nation's economic health and prosperity. GOES-S is slated to launch March 1, 2018 aboard a United Launch Alliance Atlas V rocket from Cape Canaveral Air Force Station in Florida.

GOES-S Move to Workstand; Transition into Highbay

NASA Image and Video Library

2017-12-06

At Astrotech Space Operations in Titusville, Florida, technicians and engineers inspect NOAA's Geostationary Operational Environmental Satellite-S (GOES-S). The facility is located near NASA's Kennedy Space Center. GOES-S is the second in a series of four advanced geostationary weather satellites. The GOES-R series - consisting of the GOES-R, GOES-S, GOES-T and GOES-U spacecraft - will significantly improve the detection and observation of environmental phenomena that directly affect public safety, protection of property and the nation's economic health and prosperity. GOES-S is slated to launch March 1, 2018 aboard a United Launch Alliance Atlas V rocket from Cape Canaveral Air Force Station in Florida.

GOES-S Move to Workstand; Transition into Highbay

NASA Image and Video Library

2017-12-06

At Astrotech Space Operations in Titusville, Florida, a technician inspects NOAA's Geostationary Operational Environmental Satellite-S (GOES-S). The facility is located near NASA's Kennedy Space Center. GOES-S is the second in a series of four advanced geostationary weather satellites. The GOES-R series - consisting of the GOES-R, GOES-S, GOES-T and GOES-U spacecraft - will significantly improve the detection and observation of environmental phenomena that directly affect public safety, protection of property and the nation's economic health and prosperity. GOES-S is slated to launch March 1, 2018 aboard a United Launch Alliance Atlas V rocket from Cape Canaveral Air Force Station in Florida.

GOES-S Arrival at Astrotech Space Operations

NASA Image and Video Library

2017-12-05

At Astrotech Space Operations in Titusville, Florida, technicians and engineers prepare to remove NOAA's Geostationary Operation Environmental Satellite-S (GOES-S) from its shipping container. GOES-S is the second in a series of four advanced geostationary weather satellites. The GOES-R series - consisting of the GOES-R, GOES-S, GOES-T and GOES-U spacecraft - will significantly improve the detection and observation of environmental phenomena that directly affect public safety, protection of property and the nation's economic health and prosperity. GOES-S is slated to launch March 1, 2018 aboard a United Launch Alliance Atlas V rocket from Cape Canaveral Air Force Station in Florida.

GOES-S Atlas V Centaur Stage Transport from ASOC to DOC

NASA Image and Video Library

2018-01-24

The Centaur upper stage that will help launch NOAA's Geostationary Operational Environmental Satellite-S, or GOES-S, arrives at the Delta Operations Center at Cape Canaveral Air Force Station for further processing. GOES-S is the second in a series of four advanced geostationary weather satellites. The GOES-R series - consisting of the GOES-R, GOES-S, GOES-T and GOES-U spacecraft - will significantly improve the detection and observation of environmental phenomena that directly affect public safety, protection of property and the nation's economic health and prosperity. GOES-S is slated to launch March 1, 2018 aboard a United Launch Alliance Atlas V rocket.

GOES-S Atlas V Centaur Stage Transport from ASOC to DOC

NASA Image and Video Library

2018-01-24

The Centaur upper stage that will help launch NOAA's Geostationary Operational Environmental Satellite-S, or GOES-S, is being transported to the Delta Operations Center at Cape Canaveral Air Force Station for further processing. GOES-S is the second in a series of four advanced geostationary weather satellites. The GOES-R series - consisting of the GOES-R, GOES-S, GOES-T and GOES-U spacecraft - will significantly improve the detection and observation of environmental phenomena that directly affect public safety, protection of property and the nation's economic health and prosperity. GOES-S is slated to launch March 1, 2018 aboard a United Launch Alliance Atlas V rocket.

GOES-S Atlas V Centaur Stage Transport from ASOC to DOC

NASA Image and Video Library

2018-01-24

The Centaur upper stage that will help launch NOAA's Geostationary Operational Environmental Satellite-S, or GOES-S, arrives inside the Delta Operations Center at Cape Canaveral Air Force Station for further processing. GOES-S is the second in a series of four advanced geostationary weather satellites. The GOES-R series - consisting of the GOES-R, GOES-S, GOES-T and GOES-U spacecraft - will significantly improve the detection and observation of environmental phenomena that directly affect public safety, protection of property and the nation's economic health and prosperity. GOES-S is slated to launch March 1, 2018 aboard a United Launch Alliance Atlas V rocket.

An overview of GOES-8 diurnal fire and smoke results for SCAR-B and 1995 fire season in South America

NASA Astrophysics Data System (ADS)

Prins, Elaine M.; Feltz, Joleen M.; Menzel, W. Paul; Ward, Darold E.

1998-12-01

The launch of the eighth Geostationary Operational Environmental Satellite (GOES-8) in 1994 introduced an improved capability for diurnal fire and smoke monitoring throughout the western hemisphere. In South America the GOES-8 automated biomass burning algorithm (ABBA) and the automated smoke/aerosol detection algorithm (ASADA) are being used to monitor biomass burning. This paper outlines GOES-8 ABBA and ASADA development activities and summarizes results for the Smoke, Clouds, and Radiation in Brazil (SCAR-B) experiment and the 1995 fire season. GOES-8 ABBA results document the diurnal, spatial, and seasonal variability in fire activity throughout South America. A validation exercise compares GOES-8 ABBA results with ground truth measurements for two SCAR-B prescribed burns. GOES-8 ASADA aerosol coverage and derived albedo results provide an overview of the extent of daily and seasonal smoke coverage and relative intensities. Day-to-day variability in smoke extent closely tracks fluctuations in fire activity.

GOES-R Atlas V Solid Rocket Motor (SRM) Lift and Mate

NASA Image and Video Library

2016-10-27

Inside the Vertical Integration Facility at Space Launch Complex 41 at Cape Canaveral Air Force Station in Florida, the solid rocket motor is mated to the United Launch Alliance Atlas V rocket for its upcoming launch. NOAA's Geostationary Operational Environmental Satellite (GOES-R) will launch aboard the Atlas V rocket this month. GOES-R is the first satellite in a series of next-generation NOAA GOES Satellites.

GOES-R Atlas V Solid Rocket Motor (SRM) Lift and Mate

NASA Image and Video Library

2016-10-27

Inside the Vertical Integration Facility at Space Launch Complex 41 at Cape Canaveral Air Force Station in Florida, the solid rocket motor is being mated to the United Launch Alliance Atlas V rocket for its upcoming launch. NOAA's Geostationary Operational Environmental Satellite (GOES-R) will launch aboard the Atlas V rocket this month. GOES-R is the first satellite in a series of next-generation NOAA GOES Satellites.

GOES-R Atlas V Solid Rocket Motor (SRM) Lift and Mate

NASA Image and Video Library

2016-10-27

The solid rocket motor is lifted on its transporter for mating to the United Launch Alliance Atlas V rocket in the Vertical Integration Facility at Space Launch Complex 41 at Cape Canaveral Air Force Station in Florida. NOAA's Geostationary Operational Environmental Satellite (GOES-R) will launch aboard the Atlas V rocket this month. GOES-R is the first satellite in a series of next-generation NOAA GOES Satellites.

GOES-R Encapsulation

NASA Image and Video Library

2016-10-21

Team members with United Launch Alliance (ULA) monitor the progress as the two halves of the payload fairing begin to close around the Geostationary Operational Environmental Satellite (GOES-R) inside the Astrotech payload processing facility in Titusville, Florida near NASA’s Kennedy Space Center. GOES-R will be the first satellite in a series of next-generation NOAA GOES Satellites. The spacecraft is to launch aboard a ULA Atlas V rocket in November.

GOES-R Advanced Base Line Imager Installation

NASA Image and Video Library

2016-08-30

Team members assist as a crane lifts the Advanced Base Line Imager, the primary optical instrument, for installation on the Geostationary Operational Environmental Satellite (GOES-R) inside the Astrotech payload processing facility in Titusville, Florida near NASA’s Kennedy Space Center. GOES-R will be the first satellite in a series of next-generation NOAA GOES Satellites. The spacecraft is to launch aboard a United Launch Alliance Atlas V rocket in November.

GOES-R Science Briefing

NASA Image and Video Library

2016-11-17

In the Kennedy Space Center's Press Site auditorium, Sean Potter of NASA Communications, moderates a mission briefing on the Geostationary Operational Environmental Satellite (GOES-R). GOES-R is the first satellite in a series of next-generation GOES satellites for NOAA, the National Oceanographic and Atmospheric Administration. It will launch to a geostationary orbit over the western hemisphere to provide images of storms and help meteorologists predict severe weather conditionals and develop long-range forecasts.

GOES-R Rotation to Vertical

NASA Image and Video Library

2016-09-15

Team members assist as the Geostationary Operational Environmental Satellite (GOES-R) is raised and prepared for lifting to the vertical position on an “up-ender” inside the Astrotech payload processing facility in Titusville, Florida near NASA’s Kennedy Space Center. GOES-R will be the first satellite in a series of next-generation NOAA GOES Satellites. The spacecraft is to launch aboard a United Launch Alliance Atlas V rocket in November

GOES-R Advanced Base Line Imager Installation

NASA Image and Video Library

2016-08-30

Team members assist as a crane moves the Advanced Base Line Imager, the primary optical instruments, for installation on the Geostationary Operational Environmental Satellite (GOES-R) inside the Astrotech payload processing facility in Titusville, Florida near NASA’s Kennedy Space Center. GOES-R will be the first satellite in a series of next-generation NOAA GOES Satellites. The spacecraft is to launch aboard a United Launch Alliance Atlas V rocket in November.

GOES-R Rotation to Vertical

NASA Image and Video Library

2016-09-15

Team members assist as the Geostationary Operational Environmental Satellite (GOES-R) is raised and prepared for lifting to the vertical position on an “up-ender” inside the Astrotech payload processing facility in Titusville, Florida near NASA’s Kennedy Space Center. GOES-R will be the first satellite in a series of next-generation NOAA GOES Satellites. The spacecraft is to launch aboard a United Launch Alliance Atlas V rocket in November.

Development of IDEA product for GOES-R aerosol data

NASA Astrophysics Data System (ADS)

Zhang, Hai; Hoff, Raymond M.; Kondragunta, Shobha

2009-08-01

The NOAA GOES-R Advanced Baseline Imager (ABI) will have nearly the same capabilities as NASA's Moderate Resolution Imaging Spectroradiometer (MODIS) to generate multi-wavelength retrievals of aerosol optical depth (AOD) with high temporal and spatial resolution, which can be used as a surrogate of surface particulate measurements such as PM2.5 (particulate matter with diameter less than 2.5 μm). To prepare for the launch of GOES-R and its application in the air quality forecasting, we have transferred and enhanced the Infusing satellite Data into Environmental Applications (IDEA) product from University of Wisconsin to NOAA NESDIS. IDEA was created through a NASA/EPA/NOAA cooperative effort. The enhanced IDEA product provides near-real-time imagery of AOD derived from multiple satellite sensors including MODIS Terra, MODIS Aqua, GOES EAST and GOES WEST imager. Air quality forecast guidance is produced through a trajectory model initiated at locations with high AOD retrievals and/or high aerosol index (AI) from OMI (Ozone Monitoring Instrument). The product is currently running at http://www.star.nesdis.noaa.gov/smcd/spb/aq/. The IDEA system will be tested using the GOES-R ABI proxy dataset, and will be ready to operate with GOES-R aerosol data when GOES-R is launched.

Post-Launch Calibration and Testing of Space Weather Instruments on GOES-R Satellite

NASA Technical Reports Server (NTRS)

Tadikonda, S. K.; Merrow, Cynthia S.; Kronenwetter, Jeffrey A.; Comeyne, Gustave J.; Flanagan, Daniel G.; Todrita, Monica

2016-01-01

The Geostationary Operational Environmental Satellite - R (GOES-R) is the first of a series of satellites to be launched, with the first launch scheduled for October 2016. The three instruments Solar UltraViolet Imager (SUVI), Extreme ultraviolet and X-ray Irradiance Sensor (EXIS), and Space Environment In-Situ Suite (SEISS) provide the data needed as inputs for the product updates National Oceanic and Atmospheric Administration (NOAA) provides to the public. SUVI is a full-disk extreme ultraviolet imager enabling Active Region characterization, filament eruption, and flare detection. EXIS provides inputs to solar back-ground-sevents impacting climate models. SEISS provides particle measurements over a wide energy-and-flux range that varies by several orders of magnitude and these data enable updates to spacecraft charge models for electrostatic discharge. EXIS and SEISS have been tested and calibrated end-to-end in ground test facilities around the United States. Due to the complexity of the SUVI design, data from component tests were used in a model to predict on-orbit performance. The ground tests and model updates provided inputs for designing the on-orbit calibration tests. A series of such tests have been planned for the Post-Launch Testing (PLT) of each of these instruments, and specific parameters have been identified that will be updated in the Ground Processing Algorithms, on-orbit parameter tables, or both. Some of SUVI and EXIS calibrations require slewing them off the Sun, while no such maneuvers are needed for SEISS. After a six-month PLT period the GOES-R is expected to be operational. The calibration details are presented in this paper.

Post-Launch Calibration and Testing of Space Weather Instruments on GOES-R Satellite

NASA Technical Reports Server (NTRS)

Tadikonda, Sivakumara S. K.; Merrow, Cynthia S.; Kronenwetter, Jeffrey A.; Comeyne, Gustave J.; Flanagan, Daniel G.; Todirita, Monica

2016-01-01

The Geostationary Operational Environmental Satellite - R (GOES-R) is the first of a series of satellites to be launched, with the first launch scheduled for October 2016. The three instruments - Solar Ultra Violet Imager (SUVI), Extreme ultraviolet and X-ray Irradiance Sensor (EXIS), and Space Environment In-Situ Suite (SEISS) provide the data needed as inputs for the product updates National Oceanic and Atmospheric Administration (NOAA) provides to the public. SUVI is a full-disk extreme ultraviolet imager enabling Active Region characterization, filament eruption, and flare detection. EXIS provides inputs to solar backgrounds/events impacting climate models. SEISS provides particle measurements over a wide energy-and-flux range that varies by several orders of magnitude and these data enable updates to spacecraft charge models for electrostatic discharge. EXIS and SEISS have been tested and calibrated end-to-end in ground test facilities around the United States. Due to the complexity of the SUVI design, data from component tests were used in a model to predict on-orbit performance. The ground tests and model updates provided inputs for designing the on-orbit calibration tests. A series of such tests have been planned for the Post-Launch Testing (PLT) of each of these instruments, and specific parameters have been identified that will be updated in the Ground Processing Algorithms, on-orbit parameter tables, or both. Some of SUVI and EXIS calibrations require slewing them off the Sun, while no such maneuvers are needed for SEISS. After a six-month PLT period the GOES-R is expected to be operational. The calibration details are presented in this paper.

GOES-R Space Weather Data: Products and Data Access

NASA Astrophysics Data System (ADS)

Tilton, M.; Rowland, W. F.; Codrescu, S.; Denig, W. F.; Seaton, D. B.

2016-12-01

In November 2016 NOAA launched the first in the "R" series of Geostationary Operational Environmental Satellites (GOES-R). GOES-R continues a tradition of almost 40 years of continuous space and solar observations at geostationary orbit. Compared to its predecessors, the GOES-R satellite provides improved in situ measurements of charged particle and magnetic field environments. The satellite also offers enhanced remote sensing of the sun through ultraviolet (UV) imagery and X-ray/UV irradiance. After the spacecraft completes early-orbit checkout and calibration, GOES-R space weather data and derived products will be used for operations within NOAA's Space Weather Prediction Center and publicly released through the National Centers for Environmental Information (NCEI). This presentation will provide an overview of GOES-R space weather data ranging from direct measurements (L0 data) to higher level science (L2+) products developed by NCEI scientists. We will also present planned data access and distribution features. We emphasize our strategy to ensure data discoverability and accessibility, including our participation in NOAA's OneStop project and potential partnerships with NASA's Virtual Solar Observatory and projects like Helioviewer.

GOES-R Atlas V Solid Rocket Motor (SRM) Lift and Mate

NASA Image and Video Library

2016-10-27

The solid rocket motor has been lifted to the vertical position and moved into the Vertical Integration Facility at Space Launch Complex 41 at Cape Canaveral Air Force Station in Florida for mating to the United Launch Alliance Atlas V rocket. NOAA's Geostationary Operational Environmental Satellite (GOES-R) will launch aboard the Atlas V rocket this month. GOES-R is the first satellite in a series of next-generation NOAA GOES Satellites.

GOES-R Atlas V Solid Rocket Motor (SRM) Lift and Mate

NASA Image and Video Library

2016-10-27

Preparations are underway to lift the solid rocket motor up from its transporter for mating to the United Launch Alliance Atlas V rocket in the Vertical Integration Facility at Space Launch Complex 41 at Cape Canaveral Air Force Station in Florida. NOAA's Geostationary Operational Environmental Satellite (GOES-R) will launch aboard the Atlas V rocket this month. GOES-R is the first satellite in a series of next-generation NOAA GOES Satellites.

GOES-R Atlas V Solid Rocket Motor (SRM) Lift and Mate

NASA Image and Video Library

2016-10-27

The solid rocket motor has been lifted to the vertical position for mating to the United Launch Alliance Atlas V rocket in the Vertical Integration Facility at Space Launch Complex 41 at Cape Canaveral Air Force Station in Florida. NOAA's Geostationary Operational Environmental Satellite (GOES-R) will launch aboard the Atlas V rocket this month. GOES-R is the first satellite in a series of next-generation NOAA GOES Satellites.

GOES-R Atlas V Solid Rocket Motor (SRM) Lift and Mate

NASA Image and Video Library

2016-10-27

Technicians with United Launch Alliance (ULA) assist as the solid rocket motor is mated to the ULA Atlas V rocket in the Vertical Integration Facility at Space Launch Complex 41 at Cape Canaveral Air Force Station in Florida. NOAA's Geostationary Operational Environmental Satellite (GOES-R) will launch aboard the Atlas V rocket this month. GOES-R is the first satellite in a series of next-generation NOAA GOES Satellites.

GOES-R Atlas V Solid Rocket Motor (SRM) Lift and Mate

NASA Image and Video Library

2016-10-27

Technicians with United Launch Alliance (ULA) monitor the progress as the solid rocket motor is mated to the ULA Atlas V rocket in the Vertical Integration Facility at Space Launch Complex 41 at Cape Canaveral Air Force Station in Florida. NOAA's Geostationary Operational Environmental Satellite (GOES-R) will launch aboard the Atlas V rocket this month. GOES-R is the first satellite in a series of next-generation NOAA GOES Satellites.

GOES-R Lift and Mate

NASA Image and Video Library

2016-11-09

A view from high up inside the Vertical Integration Facility at Space Launch Complex 41 at Cape Canaveral Air Force Station in Florida. A crane lifts the payload fairing containing NOAA's Geostationary Operational Environmental Satellite (GOES-R) for mating to the United Launch Alliance Atlas V Centaur upper stage. The satellite will launch aboard the Atlas V rocket in November. GOES-R is the first satellite in a series of next-generation NOAA GOES Satellites.

GOES-R Prelaunch News Conference

NASA Image and Video Library

2016-11-17

From left, Stephen Volz, assistant administrator for satellite and information services, National Oceanic and Atmospheric Administration (NOAA); and Greg Mandt, GOES-R system program director, NOAA, speak to members of the news media during a Geostationary Operational Environmental Satellite (GOES-R) prelaunch news conference in the Kennedy Space Center's Press Site auditorium.

GOES-S: Removal from Shipping Container

NASA Image and Video Library

2017-12-05

At Astrotech Space Operations in Titusville, Florida, NOAA's Geostationary Operational Environmental Satellite-S (GOES-S) is uncrated from its shipping container and moved into the clean room. The facility is located near NASA's Kennedy Space Center. GOES-S is the second in a series of four advanced geostationary weather satellites. The GOES-R series - consisting of the GOES-R, GOES-S, GOES-T and GOES-U spacecraft - will significantly improve the detection and observation of environmental phenomena that directly affect public safety, protection of property and the nation's economic health and prosperity. GOES-S is slated to launch March 1, 2018 aboard a United Launch Alliance Atlas V rocket from Cape Canaveral Air Force Station in Florida.

GOES-S Atlas V Centaur Stage Transport from ASOC to DOC

NASA Image and Video Library

2018-01-24

Under the watchful eyes of technicians and engineers, the Centaur upper stage that will help launch NOAA's Geostationary Operational Environmental Satellite-S, or GOES-S, arrives inside the Delta Operations Center at Cape Canaveral Air Force Station for further processing. GOES-S is the second in a series of four advanced geostationary weather satellites. The GOES-R series - consisting of the GOES-R, GOES-S, GOES-T and GOES-U spacecraft - will significantly improve the detection and observation of environmental phenomena that directly affect public safety, protection of property and the nation's economic health and prosperity. GOES-S is slated to launch March 1, 2018 aboard a United Launch Alliance Atlas V rocket.

GOES-S Atlas V Centaur Stage Transport from ASOC to DOC

NASA Image and Video Library

2018-01-24

The Centaur upper stage that will help launch NOAA's Geostationary Operational Environmental Satellite-S, or GOES-S, has been lifted from its transporter inside the Delta Operations Center at Cape Canaveral Air Force Station for further processing. GOES-S is the second in a series of four advanced geostationary weather satellites. The GOES-R series - consisting of the GOES-R, GOES-S, GOES-T and GOES-U spacecraft - will significantly improve the detection and observation of environmental phenomena that directly affect public safety, protection of property and the nation's economic health and prosperity. GOES-S is slated to launch March 1, 2018 aboard a United Launch Alliance Atlas V rocket.

GOES-S Atlas V Centaur Stage Transport from ASOC to DOC

NASA Image and Video Library

2018-01-24

The Centaur upper stage that will help launch NOAA's Geostationary Operational Environmental Satellite-S, or GOES-S, is being transported from the Atlas Spaceflight Operations Center at Cape Canaveral Air Force Station to the Delta Operations Center for further processing. GOES-S is the second in a series of four advanced geostationary weather satellites. The GOES-R series - consisting of the GOES-R, GOES-S, GOES-T and GOES-U spacecraft - will significantly improve the detection and observation of environmental phenomena that directly affect public safety, protection of property and the nation's economic health and prosperity. GOES-S is slated to launch March 1, 2018 aboard a United Launch Alliance Atlas V rocket.

GOES-S Atlas V Centaur Stage Transport from ASOC to DOC

NASA Image and Video Library

2018-01-24

The Centaur upper stage that will help launch NOAA's Geostationary Operational Environmental Satellite-S, or GOES-S, has been positioned in at test cell inside the Delta Operations Center at Cape Canaveral Air Force Station for further processing. GOES-S is the second in a series of four advanced geostationary weather satellites. The GOES-R series - consisting of the GOES-R, GOES-S, GOES-T and GOES-U spacecraft - will significantly improve the detection and observation of environmental phenomena that directly affect public safety, protection of property and the nation's economic health and prosperity. GOES-S is slated to launch March 1, 2018 aboard a United Launch Alliance Atlas V rocket.

Evaluation of Skin Temperatures Retrieved from GOES-8

NASA Technical Reports Server (NTRS)

Suggs, Ronnie, J.; Jedlovec, G. J.; Lapenta, W. M.; Haines, S. L.

2000-01-01

Skin temperatures derived from geostationary satellites have the potential of providing the temporal and spatial resolution needed for model assimilation. To adequately assess the potential improvements in numerical model forecasts that can be made by assimilating satellite data, an estimate of the accuracy of the skin temperature product is necessary. A particular skin temperature algorithm, the Physical Split Window Technique, that uses the longwave infrared channels of the GOES Imager has shown promise in recent model assimilation studies to provide land surface temperatures with reasonable accuracy. A comparison of retrieved GOES-8 skin temperatures from this algorithm with in situ measurements is presented. Various retrieval algorithm issues are addressed including surface emissivity

GOES-R Atlas V Solid Rocket Motor (SRM) Lift and Mate

NASA Image and Video Library

2016-10-27

The solid rocket motor has been lifted to the vertical position on its transporter for mating to the United Launch Alliance Atlas V rocket in the Vertical Integration Facility at Space Launch Complex 41 at Cape Canaveral Air Force Station in Florida. NOAA's Geostationary Operational Environmental Satellite (GOES-R) will launch aboard the Atlas V rocket this month. GOES-R is the first satellite in a series of next-generation NOAA GOES Satellites.

GOES-R Liftoff

NASA Image and Video Library

2016-11-19

At Cape Canaveral Air Force Station's Space Launch Complex 41, an Atlas V rocket with NOAA's Geostationary Operational Environmental Satellite, or GOES-R, lifts off at 6:42 p.m. EST. GOES-R is the first satellite in a series of next-generation GOES satellites for NOAA, the National Oceanographic and Atmospheric Administration. It will launch to a geostationary orbit over the western hemisphere to provide images of storms and help meteorologists predict severe weather conditionals and develop long-range forecasts.

GOES-R Science Briefing

NASA Image and Video Library

2016-11-17

In the Kennedy Space Center's Press Site auditorium, Sandra Cauffman, deputy director of NASA's Earth Science Division, speaks to the media during a mission briefing on the Geostationary Operational Environmental Satellite (GOES-R). GOES-R is the first satellite in a series of next-generation GOES satellites for NOAA, the National Oceanographic and Atmospheric Administration. It will launch to a geostationary orbit over the western hemisphere to provide images of storms and help meteorologists predict severe weather conditionals and develop long-range forecasts.

GOES-R Uncrating and Move to Vertical

NASA Image and Video Library

2016-08-23

The GOES-R spacecraft stands vertically inside the Astrotech payload processing facility in Titusville, Florida near NASA’s Kennedy Space Center. GOES-R will be the first satellite in a series of next-generation NOAA Geostationary Operational Environmental Satellites. The spacecraft is to launch aboard a United Launch Alliance Atlas V rocket in November.

GOES-R Atlas V Solid Rocket Motor (SRM) Lift and Mate

NASA Image and Video Library

2016-10-27

A United Launch Alliance (ULA) technician inspects the solid rocket motor for the ULA Atlas V rocket on its transporter near the Vertical Integration Facility at Space Launch Complex 41 at Cape Canaveral Air Force Station in Florida. The solid rocket motor will be lifted and mated to the rocket in preparation for the launch of NOAA's Geostationary Operational Environmental Satellite (GOES-R) this month. GOES-R is the first satellite in a series of next-generation NOAA GOES Satellites.

GOES-R Science Briefing

NASA Image and Video Library

2016-11-17

In the Kennedy Space Center's Press Site auditorium, Joseph A. Pica, director of the National Weather Service Office of Observations, speaks to the media during a mission briefing on the Geostationary Operational Environmental Satellite (GOES-R). GOES-R is the first satellite in a series of next-generation GOES satellites for NOAA, the National Oceanographic and Atmospheric Administration. It will launch to a geostationary orbit over the western hemisphere to provide images of storms and help meteorologists predict severe weather conditionals and develop long-range forecasts.

GOES-R Science Briefing

NASA Image and Video Library

2016-11-17

In the Kennedy Space Center's Press Site auditorium, Damon Penn, assistant administrator for response at the Federal Emergency Management Agency, speaks to the media during a mission briefing on the Geostationary Operational Environmental Satellite (GOES-R). GOES-R is the first satellite in a series of next-generation GOES satellites for NOAA, the National Oceanographic and Atmospheric Administration. It will launch to a geostationary orbit over the western hemisphere to provide images of storms and help meteorologists predict severe weather conditionals and develop long-range forecasts.

GOES-R ABI Optics Test

NASA Image and Video Library

2016-08-31

With the lights out, team members perform an optics test on the Advanced Baseline Imager, the primary optical instrument, on the Geostationary Operational Environmental Satellite (GOES-R) inside the Astrotech payload processing facility in Titusville, Florida near NASA’s Kennedy Space Center. Carbon dioxide is sprayed on the imager to clean it and test its sensitivity. GOES-R will be the first satellite in a series of next-generation NOAA GOES Satellites. The spacecraft is to launch aboard a United Launch Alliance Atlas V rocket in November.

GOES-R ABI Optics Test

NASA Image and Video Library

2016-08-31

Team members prepare for an optics test on the Advanced Baseline Imager, the primary optical instrument, on the Geostationary Operational Environmental Satellite (GOES-R) inside the Astrotech payload processing facility in Titusville, Florida near NASA’s Kennedy Space Center. Carbon dioxide will be sprayed on the imager to clean it and test its sensitivity. GOES-R will be the first satellite in a series of next-generation NOAA GOES Satellites. The spacecraft is to launch aboard a United Launch Alliance Atlas V rocket in November.

Al Roker Interview with NASA for GOES-R Mission

NASA Image and Video Library

2016-11-19

During the countdown for the launch of NOAA's Geostationary Operational Environmental Satellite, or GOES-R, Stephanie Martin of NASA Communications, right, interviews Al Roker, weather forecaster on NBC's "Today Show." GOES-R is the first satellite in a series of next-generation GOES satellites for NOAA, the National Oceanographic and Atmospheric Administration. It will launch to a geostationary orbit over the western hemisphere to provide images of storms and help meteorologists predict severe weather conditionals and develop long-range forecasts.

Al Roker Interview with NASA for GOES-R Mission

NASA Image and Video Library

2016-11-19

During the countdown for the launch of NOAA's Geostationary Operational Environmental Satellite, or GOES-R, Stephanie Martin of NASA Communications, left, interviews Al Roker, weather forecaster on NBC's "Today Show." GOES-R is the first satellite in a series of next-generation GOES satellites for NOAA, the National Oceanographic and Atmospheric Administration. It will launch to a geostationary orbit over the western hemisphere to provide images of storms and help meteorologists predict severe weather conditionals and develop long-range forecasts.

GOES-R Proving Ground Activities at the NASA Short-Term Prediction Research and Transition (SPoRT) Center

NASA Technical Reports Server (NTRS)

Molthan, Andrew

2011-01-01

SPoRT is actively involved in GOES-R Proving Ground activities in a number of ways: (1) Applying the paradigm of product development, user training, and interaction to foster interaction with end users at NOAA forecast offices national centers. (2) Providing unique capabilities in collaboration with other GOES-R Proving Ground partners (a) Hybrid GOES-MODIS imagery (b) Pseudo-GLM via regional lightning mapping arrays (c) Developing new RGB imagery from EUMETSAT guidelines

GOES-R Uncrating and Move to Vertical

NASA Image and Video Library

2016-08-23

Team members remove a protective plastic covering from the GOES-R spacecraft inside the Astrotech payload processing facility in Titusville, Florida near NASA’s Kennedy Space Center. GOES-R will be the first satellite in a series of next-generation NOAA Geostationary Operational Environmental Satellites. The spacecraft is to launch aboard a United Launch Alliance Atlas V rocket in November.

GOES-R Prelaunch News Conference

NASA Image and Video Library

2016-11-17

From left, Stephen Volz, assistant administrator for satellite and information services, National Oceanic and Atmospheric Administration (NOAA); Greg Mandt, GOES-R system program director, NOAA; and Sandra Smalley, director, Joint Agency Satellite Division, NASA Headquarters, speak to members of the news media during a Geostationary Operational Environmental Satellite (GOES-R) prelaunch news conference in the Kennedy Space Center's Press Site auditorium.

GOES-R Uncrating and Move to Vertical

NASA Image and Video Library

2016-08-23

The shipping container is lifted off the GOES-R spacecraft inside the Astrotech payload processing facility in Titusville, Florida near NASA’s Kennedy Space Center. GOES-R will be the first satellite in a series of next-generation NOAA Geostationary Operational Environmental Satellites. The spacecraft is to launch aboard a United Launch Alliance Atlas V rocket in November.

GOES-R Uncrating and Move to Vertical

NASA Image and Video Library

2016-08-23

The GOES-R spacecraft is revealed following its uncrating inside the Astrotech payload processing facility in Titusville, Florida near NASA’s Kennedy Space Center. GOES-R will be the first satellite in a series of next-generation NOAA Geostationary Operational Environmental Satellites. The spacecraft is to launch aboard a United Launch Alliance Atlas V rocket in November.

GOES-S Arrival and Transport

NASA Image and Video Library

2017-12-04

NOAA's Geostationary Operational Environmental Satellite-S (GOES-S) arrives onboard a U.S. Air Force C-5M Super Galaxy cargo aircraft at the Shuttle Landing Facility at NASA's Kennedy Space Center in Florida. The satellite is offloaded and transported to the Astrotech Space Operations facility in Titusville, Florida to prepare it for launch. GOES-S is the second in a series of four advanced geostationary weather satellites. The GOES-R series - consisting of the GOES-R, GOES-S, GOES-T and GOES-U spacecraft - will significantly improve the detection and observation of environmental phenomena that directly affect public safety, protection of property and the nation's economic health and prosperity. GOES-S is slated to launch March 1, 2018 aboard a United Launch Alliance Atlas V rocket from Cape Canaveral Air Force Station in Florida.

Improving Satellite Quantitative Precipitation Estimation Using GOES-Retrieved Cloud Optical Depth

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stenz, Ronald; Dong, Xiquan; Xi, Baike

To address significant gaps in ground-based radar coverage and rain gauge networks in the U.S., geostationary satellite quantitative precipitation estimates (QPEs) such as the Self-Calibrating Multivariate Precipitation Retrievals (SCaMPR) can be used to fill in both the spatial and temporal gaps of ground-based measurements. Additionally, with the launch of GOES-R, the temporal resolution of satellite QPEs may be comparable to that of Weather Service Radar-1988 Doppler (WSR-88D) volume scans as GOES images will be available every five minutes. However, while satellite QPEs have strengths in spatial coverage and temporal resolution, they face limitations particularly during convective events. Deep Convective Systemsmore » (DCSs) have large cloud shields with similar brightness temperatures (BTs) over nearly the entire system, but widely varying precipitation rates beneath these clouds. Geostationary satellite QPEs relying on the indirect relationship between BTs and precipitation rates often suffer from large errors because anvil regions (little/no precipitation) cannot be distinguished from rain-cores (heavy precipitation) using only BTs. However, a combination of BTs and optical depth (τ) has been found to reduce overestimates of precipitation in anvil regions (Stenz et al. 2014). A new rain mask algorithm incorporating both τ and BTs has been developed, and its application to the existing SCaMPR algorithm was evaluated. The performance of the modified SCaMPR was evaluated using traditional skill scores and a more detailed analysis of performance in individual DCS components by utilizing the Feng et al. (2012) classification algorithm. SCaMPR estimates with the new rain mask applied benefited from significantly reduced overestimates of precipitation in anvil regions and overall improvements in skill scores.« less

GOES-R Uncrating and Move to Vertical

NASA Image and Video Library

2016-08-23

The GOES-R spacecraft is inspected after being uncrated and raised to vertical inside the Astrotech payload processing facility in Titusville, Florida near NASA’s Kennedy Space Center. GOES-R will be the first satellite in a series of next-generation NOAA Geostationary Operational Environmental Satellites. The spacecraft is to launch aboard a United Launch Alliance Atlas V rocket in November.

GOES-R Uncrating and Move to Vertical

NASA Image and Video Library

2016-08-23

Team members monitor progress as the GOES-R spacecraft is lifted from horizontal to vertical inside the Astrotech payload processing facility in Titusville, Florida near NASA’s Kennedy Space Center. GOES-R will be the first satellite in a series of next-generation NOAA Geostationary Operational Environmental Satellites. The spacecraft is to launch aboard a United Launch Alliance Atlas V rocket in November.

GOES-R Uncrating and Move to Vertical

NASA Image and Video Library

2016-08-23

Team members monitor progress as the GOES-R spacecraft is raised to vertical inside the Astrotech payload processing facility in Titusville, Florida near NASA’s Kennedy Space Center. GOES-R will be the first satellite in a series of next-generation NOAA Geostationary Operational Environmental Satellites. The spacecraft is to launch aboard a United Launch Alliance Atlas V rocket in November.

GOES EXIS Quadruplets Together in a Clean Room "Nursery"

NASA Image and Video Library

2014-02-10

Four Extreme Ultraviolet and X-ray Irradiance Sensors or EXIS instruments that will fly aboard four of NOAA's Geostationary Operational Environmental Satellite-R or GOES-R Series spacecraft were recently lined up like babies in a nursery. The EXIS Team at NOAA's Laboratory for Atmospheric and Space Physics (LASP) in Boulder, Colorado took a short timeout during the week of January 20, 2014 to take advantage of a rare photo opportunity. Each EXIS instrument will fly aboard one of the GOES-R series of spacecraft that include GOES-R, S, T, and U. All four EXIS instruments happened to be in the clean room at the same time. It is expected that this will probably be the last time that all four siblings will be in one place together as Flight Model 1 (seen on the left) is being shipped on February 3 to begin integration and testing onto the GOES-R spacecraft at a Lockheed Martin facility in Littleton, Colo. The other instruments have already dispersed to other areas at LASP for continued build and test operations. The EXIS instruments on the GOES-R series satellites are critical to understanding and monitoring solar irradiance in the upper atmosphere, that is, the power and effect of the Sun’s electromagnetic radiation per unit of area. EXIS will be able to detect solar flares that could interrupt communications and reduce navigational accuracy, affecting satellites, high altitude airlines and power grids on Earth. On board the EXIS are two main sensors, the Extreme Ultraviolet Sensor (EUVS) and the X-Ray Sensor (XRS), which will help scientists monitor activity on the sun. The GOES-R series is a collaborative development and acquisition effort between the National Oceanic and Atmospheric Administration and NASA. The GOES-R satellites will provide continuous imagery and atmospheric measurements of Earth’s Western Hemisphere and space weather monitoring. For more information about the GOES-R series, visit: www.goes-r.gov Credit: NOAA/NASA NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

The Geostationary Operational Satellite R Series SpaceWire Based Data System

NASA Technical Reports Server (NTRS)

Anderson, William; Birmingham, Michael; Krimchansky, Alexander; Lombardi, Matthew

2016-01-01

The Geostationary Operational Environmental Satellite R-Series Program (GOES-R, S, T, and U) mission is a joint program between National Oceanic & Atmospheric Administration (NOAA) and National Aeronautics & Space Administration (NASA) Goddard Space Flight Center (GSFC). SpaceWire was selected as the science data bus as well as command and telemetry for the GOES instruments. GOES-R, S, T, and U spacecraft have a mission data loss requirement for all data transfers between the instruments and spacecraft requiring error detection and correction at the packet level. The GOES-R Reliable Data Delivery Protocol (GRDDP) [1] was developed in house to provide a means of reliably delivering data among various on board sources and sinks. The GRDDP was presented to and accepted by the European Cooperation for Space Standardization (ECSS) and is part of the ECSS Protocol Identification Standard [2]. GOES-R development and integration is complete and the observatory is scheduled for launch November 2016. Now that instrument to spacecraft integration is complete, GOES-R Project reviewed lessons learned to determine how the GRDDP could be revised to improve the integration process. Based on knowledge gained during the instrument to spacecraft integration process the following is presented to help potential GRDDP users improve their system designs and implementation.

GOES-S Transport to Kennedy Space Center

NASA Image and Video Library

2017-12-04

At Buckley Air Force Base in Aurora, Colorado, NOAA's Geostationary Operational Environmental Satellite-S (GOES-S) is being loaded into the cargo hold of a U.S. Air Force C-5M super Galaxy cargo aircraft. GOES-S will be flown to NASA's Kennedy Space Center in Florida. After it arrives at Kennedy's Shuttle Landing Facility, it will be offloaded and transported to the Astrotech Space Operations facility in Titusville, Florida, to prepare it for launch. GOES-S is the second in a series of four advanced geostationary weather satellites. The GOES-R series - consisting of the GOES-R, GOES-S, GOES-T and GOES-U spacecraft - will significantly improve the detection and observation of environmental phenomena that directly affect public safety, protection of property and the nation's economic health and prosperity. GOES-S is slated to launch March 1, 2018 aboard a United Launch Alliance Atlas V rocket from Cape Canaveral Air Force Station in Florida.

GOES-S Arrival at Kennedy Space Center

NASA Image and Video Library

2017-12-05

NOAA's Geostationary Operation Environmental Satellite-S (GOES-S) is being offloaded from a C-5 transport aircraft onto the flatbed of a heavy-lift truck at the Shuttle Landing Facility at NASA's Kennedy Space Center in Florida. The satellite will be transported to the Astrotech Space Operations facility in Titusville, Florida to prepare it for launch. GOES-S is the second in a series of four advanced geostationary weather satellites. The GOES-R series - consisting of the GOES-R, GOES-S, GOES-T and GOES-U spacecraft - will significantly improve the detection and observation of environmental phenomena that directly affect public safety, protection of property and the nation's economic health and prosperity. GOES-S is slated to launch March 1, 2018 aboard a United Launch Alliance Atlas V rocket from Cape Canaveral Air Force Station in Florida.

GOES-R L1b Readiness Implementation and Management Plan

NASA Technical Reports Server (NTRS)

Kunkee, David; Farley, Robert; Kwan, Betty; Walterscheid, Richard; Hecht, James; Claudepierre, Seth.; De Luccia, Frank

2017-01-01

A complement of Readiness, Implementation and Management Plans (RIMPs) to facilitate management of post-launch product test activities for the official Geostationary Operational Environmental Satellite (GOES-R) Level 1b (L1b) products have been developed and documented. Separate plans have been created for each of the GOES-R sensors including: the Advanced Baseline Imager (ABI), the Extreme ultraviolet and X-ray Irradiance Sensors (EXIS), Geostationary Lightning Mapper (GLM), GOES-R Magnetometer (MAG), the Space Environment In-Situ Suite (SEISS), and the Solar Ultraviolet Imager (SUVI). The GOES-R program has implemented these RIMPs in order to address the full scope of CalVal activities required for a successful demonstration of GOES-R L1b data product quality throughout the three validation stages: Beta, Provisional and Full Validation. For each product maturity level, the RIMPs include specific performance criteria and required artifacts that provide evidence a given validation stage has been reached, the timing when each stage will be complete, a description of every applicable Post-Launch Product Test (PLPT), roles and responsibilities of personnel, upstream dependencies, and analysis methods and tools to be employed during validation. Instrument level Post-Launch Tests (PLTs) are also referenced and apply primarily to functional check-out of the instruments.

Development of Level 1b Calibration and Validation Readiness, Implementation and Management Plans for GOES-R

NASA Technical Reports Server (NTRS)

Kunkee, David B.; Farley, Robert W.; Kwan, Betty P.; Hecht, James H.; Walterscheid, Richard L.; Claudepierre, Seth G.; Bishop, Rebecca L.; Gelinas, Lynette J.; Deluccia, Frank J.

2017-01-01

A complement of Readiness, Implementation and Management Plans (RIMPs) to facilitate management of post-launch product test activities for the official Geostationary Operational Environmental Satellite (GOES-R) Level 1b (L1b) products have been developed and documented. Separate plans have been created for each of the GOES-R sensors including: the Advanced Baseline Imager (ABI), the Extreme ultraviolet and X-ray Irradiance Sensors (EXIS), Geostationary Lightning Mapper (GLM), GOES-R Magnetometer (MAG), the Space Environment In-Situ Suite (SEISS), and the Solar Ultraviolet Imager (SUVI). The GOES-R program has implemented these RIMPs in order to address the full scope of CalVal activities required for a successful demonstration of GOES-R L1b data product quality throughout the three validation stages: Beta, Provisional and Full Validation. For each product maturity level, the RIMPs include specific performance criteria and required artifacts that provide evidence a given validation stage has been reached, the timing when each stage will be complete, a description of every applicable Post-Launch Product Test (PLPT), roles and responsibilities of personnel, upstream dependencies, and analysis methods and tools to be employed during validation. Instrument level Post-Launch Tests (PLTs) are also referenced and apply primarily to functional check-out of the instruments.

Toward an Objective Enhanced-V Detection Algorithm

NASA Technical Reports Server (NTRS)

Brunner, Jason; Feltz, Wayne; Moses, John; Rabin, Robert; Ackerman, Steven

2007-01-01

The area of coldest cloud tops above thunderstorms sometimes has a distinct V or U shape. This pattern, often referred to as an "enhanced-V' signature, has been observed to occur during and preceding severe weather in previous studies. This study describes an algorithmic approach to objectively detect enhanced-V features with observations from the Geostationary Operational Environmental Satellite and Low Earth Orbit data. The methodology consists of cross correlation statistics of pixels and thresholds of enhanced-V quantitative parameters. The effectiveness of the enhanced-V detection method will be examined using Geostationary Operational Environmental Satellite, MODerate-resolution Imaging Spectroradiometer, and Advanced Very High Resolution Radiometer image data from case studies in the 2003-2006 seasons. The main goal of this study is to develop an objective enhanced-V detection algorithm for future implementation into operations with future sensors, such as GOES-R.

Potential Use of a Bayesian Network for Discriminating Flash Type from Future GOES-R Geostationary Lightning Mapper (GLM) data

NASA Technical Reports Server (NTRS)

Solakiewiz, Richard; Koshak, William

2008-01-01

Continuous monitoring of the ratio of cloud flashes to ground flashes may provide a better understanding of thunderstorm dynamics, intensification, and evolution, and it may be useful in severe weather warning. The National Lighting Detection Network TM (NLDN) senses ground flashes with exceptional detection efficiency and accuracy over most of the continental United States. A proposed Geostationary Lightning Mapper (GLM) aboard the Geostationary Operational Environmental Satellite (GOES-R) will look at the western hemisphere, and among the lightning data products to be made available will be the fundamental optical flash parameters for both cloud and ground flashes: radiance, area, duration, number of optical groups, and number of optical events. Previous studies have demonstrated that the optical flash parameter statistics of ground and cloud lightning, which are observable from space, are significantly different. This study investigates a Bayesian network methodology for discriminating lightning flash type (ground or cloud) using the lightning optical data and ancillary GOES-R data. A Directed Acyclic Graph (DAG) is set up with lightning as a "root" and data observed by GLM as the "leaves." This allows for a direct calculation of the joint probability distribution function for the lighting type and radiance, area, etc. Initially, the conditional probabilities that will be required can be estimated from the Lightning Imaging Sensor (LIS) and the Optical Transient Detector (OTD) together with NLDN data. Directly manipulating the joint distribution will yield the conditional probability that a lightning flash is a ground flash given the evidence, which consists of the observed lightning optical data [and possibly cloud data retrieved from the GOES-R Advanced Baseline Imager (ABI) in a more mature Bayesian network configuration]. Later, actual GLM and NLDN data can be used to refine the estimates of the conditional probabilities used in the model; i.e., the Bayesian network is a learning network. Methods for efficient calculation of the conditional probabilities (e.g., an algorithm using junction trees), finding data conflicts, goodness of fit, and dealing with missing data will also be addressed.

GOES-S Transport to Kennedy Space Center

NASA Image and Video Library

2017-12-04

NOAA's Geostationary Operational Environmental Satellite-S (GOES-S) is prepared for transport at the Lockheed Martin facility in Littleton, Colorado, where it was built and assembled. GOES-S will be loaded into a U.S. Air Force C-5M Super Galaxy cargo aircraft at Buckley Air Force Base in Aurora, Colorado, and flown to NASA's Kennedy Space Center in Florida. After it arrives at Kennedy's Shuttle Landing Facility, it will be offloaded and transported to the Astrotech Space Operations facility in Titusville, Florida, to prepare it for launch. GOES-S is the second in a series of four advanced geostationary weather satellites. The GOES-R series - consisting of the GOES-R, GOES-S, GOES-T and GOES-U spacecraft - will significantly improve the detection and observation of environmental phenomena that directly affect public safety, protection of property and the nation's economic health and prosperity. GOES-S is slated to launch March 1, 2018 aboard a United Launch Alliance Atlas V rocket from Cape Canaveral Air Force Station in Florida.

GOES-R Arrival and Offload

NASA Image and Video Library

2016-08-22

An Air Force C-5 Galaxy transport plane approaches the Shuttle Landing Facility at NASA's Kennedy Space Center in Florida to deliver the GOES-R spacecraft for launch processing. The GOES series are weather satellites operated by NOAA to enhance forecasts. The spacecraft is to launch aboard a United Launch Alliance Atlas V rocket in November.

Oceanic Weather Decision Support for Unmanned Global Hawk Science Missions into Hurricanes with Tailored Satellite Derived Products

NASA Astrophysics Data System (ADS)

Feltz, Wayne; Griffin, Sarah; Velden, Christopher; Zipser, Ed; Cecil, Daniel; Braun, Scott

2017-04-01

The purpose of this presentation is to identify in-flight hazards to high-altitude aircraft, namely the Global Hawk. The Global Hawk was used during Septembers 2012-2016 as part of two NASA funded Hurricane Sentinel-3 field campaigns to over-fly hurricanes in the Atlantic Ocean. This talk identifies the cause of severe turbulence experienced over Hurricane Emily (2005) and how a combination of NOAA funded GOES-R algorithm derived cloud top heights/tropical overshooting tops using GOES-13/SEVIRI imager radiances, and lightning information are used to identify areas of potential turbulence for near real-time navigation decision support. Several examples will demonstrate how the Global Hawk pilots remotely received and used real-time satellite derived cloud and lightning detection information to keep the aircraft safely above clouds and avoid regions of potential turbulence.

Space Weather Monitoring with GOES-16: Instruments and Data Products

NASA Astrophysics Data System (ADS)

Loto'aniu, Paul; Rodriguez, Juan; Redmon, Robert; Machol, Janet; Kress, Brian; Seaton, Daniel; Darnel, Jonathan; Rowland, William; Tilton, Margaret; Denig, William; Boudouridis, Athanasios; Codrescu, Stefan; Claycomb, Abram

2017-04-01

Since their inception in the 1970s, the NOAA GOES satellites have monitored the sources of space weather on the sun and the effects of space weather at Earth. The GOES-16 spacecraft, the first of four satellites as part of the GOES-R spacecraft series mission, was launched in November 2016. The space weather instruments on GOES-16 have significantly improved capabilities over older GOES instruments. They will image the sun's atmosphere in extreme-ultraviolet and monitor solar irradiance in X-rays and UV, solar energetic particles, magnetospheric energetic particles, galactic cosmic rays, and the Earth's magnetic field. These measurements are important for providing alerts and warnings to many worldwide customers, including the NOAA National Weather Service, satellite operators, the power utilities, and NASA's human activities in space. This presentation reviews the capabilities of the GOES-16 space weather instruments and presents initial post launch data along with a discussion of calibration activities and the current status of the instruments. We also describe the space weather Level 2+ products that are being developed for the GOES-R series including solar thematic maps, automated magnetopause crossing detection and spacecraft charging estimates. These new and continuing data products will be an integral part of NOAA space weather operations in the GOES-R era.

Guidance, Navigation, and Control Performance for the GOES-R Spacecraft

NASA Technical Reports Server (NTRS)

Chapel, Jim D.; Stancliffe, Devin; Bevacqua, Tim; Winkler, Stephen; Clapp, Brian; Rood, Tim; Gaylor, David; Freesland, Douglas C.; Krimchansky, Alexander

2014-01-01

The Geostationary Operational Environmental Satellite-R Series (GOES-R) is the first of the next generation geostationary weather satellites, scheduled for delivery in late 2015 and launch in early 2016. Relative to the current generation of GOES satellites, GOES-R represents a dramatic increase in Earth and solar weather observation capabilities, with 4 times the resolution, 5 times the observation rate, and 3 times the number of spectral bands for Earth observations. GOES-R will also provide unprecedented availability, with less than 120 minutes per year of lost observation time. The Guidance Navigation & Control (GN&C) design requirements to achieve these expanded capabilities are extremely demanding. This paper first presents the pointing control, pointing stability, attitude knowledge, and orbit knowledge requirements necessary to realize the ambitious Image Navigation and Registration (INR) objectives of GOES-R. Because the GOES-R suite of instruments is sensitive to disturbances over a broad spectral range, a high fidelity simulation of the vehicle has been created with modal content over 500 Hz to assess the pointing stability requirements. Simulation results are presented showing acceleration, shock response spectrum (SRS), and line of sight responses for various disturbances from 0 Hz to 512 Hz. These disturbances include gimbal motion, reaction wheel disturbances, thruster firings for station keeping and momentum management, and internal instrument disturbances. Simulation results demonstrate excellent performance relative to the pointing and pointing stability requirements, with line of sight jitter of the isolated instrument platform of approximately 1 micro-rad. Low frequency motion of the isolated instrument platform is internally compensated within the primary instrument. Attitude knowledge and rate are provided directly to the instrument with an accuracy defined by the Integrated Rate Error (IRE) requirements. The allowable IRE ranges from 1 to 18.5 micro-rad, depending upon the time window of interest. The final piece of the INR performance is orbit knowledge. Extremely accurate orbital position is achieved by GPS navigation at Geosynchronous Earth Orbit (GEO). Performance results are shown demonstrating compliance with the 50 to 75 m orbit position accuracy requirements of GOES-R, including during station-keeping and momentum management maneuvers. As shown in this paper, the GN&C performance for the GOES-R series of spacecraft supports the challenging mission objectives of the next generation GEO Earth-observation satellites.

GOES-R User Data Types and Structure

NASA Astrophysics Data System (ADS)

Royle, A. W.

2012-12-01

GOES-R meteorological data is provided to the operational and science user community through four main distribution mechanisms. The GOES-R Ground Segment (GS) generates a set of Level 1b (L1b) data from each of the six primary satellite instruments and formats the data into a direct broadcast stream known as GOES Rebroadcast (GRB). Terrestrially, cloud and moisture imagery data is provided to forecasters at the National Weather Service (NWS) through a direct interface to the Advanced Weather Interactive Processing System (AWIPS). A secondary pathway for the user community to receive data terrestrially is via NOAA's Environmental Satellite Processing and Distribution System (ESPDS) Product Distribution and Access (PDA) system. The ESPDS PDA will service the NWS and other meteorological users through a data portal, which provides both a subscription service and an ad hoc query capability. Finally, GOES-R data is made available to NOAA's Comprehensive Large Array-Data Stewardship System (CLASS) for long-term archive. CLASS data includes the L1b and L2+ products sent to PDA, along with the Level 0 data used to create these products, and other data used for product generation and processing. This session will provide a summary description of the data types and formats associated with each of the four primary distribution pathways for user data from GOES-R. It will discuss the resources that are being developed by GOES-R to document the data structures and formats. It will also provide a brief introduction to the types of metadata associated with each of the primary data flows.

Avoiding Stair-Step Artifacts in Image Registration for GOES-R Navigation and Registration Assessment

NASA Technical Reports Server (NTRS)

Grycewicz, Thomas J.; Tan, Bin; Isaacson, Peter J.; De Luccia, Frank J.; Dellomo, John

2016-01-01

In developing software for independent verification and validation (IVV) of the Image Navigation and Registration (INR) capability for the Geostationary Operational Environmental Satellite R Series (GOES-R) Advanced Baseline Imager (ABI), we have encountered an image registration artifact which limits the accuracy of image offset estimation at the subpixel scale using image correlation. Where the two images to be registered have the same pixel size, subpixel image registration preferentially selects registration values where the image pixel boundaries are close to lined up. Because of the shape of a curve plotting input displacement to estimated offset, we call this a stair-step artifact. When one image is at a higher resolution than the other, the stair-step artifact is minimized by correlating at the higher resolution. For validating ABI image navigation, GOES-R images are correlated with Landsat-based ground truth maps. To create the ground truth map, the Landsat image is first transformed to the perspective seen from the GOES-R satellite, and then is scaled to an appropriate pixel size. Minimizing processing time motivates choosing the map pixels to be the same size as the GOES-R pixels. At this pixel size image processing of the shift estimate is efficient, but the stair-step artifact is present. If the map pixel is very small, stair-step is not a problem, but image correlation is computation-intensive. This paper describes simulation-based selection of the scale for truth maps for registering GOES-R ABI images.

An Overview of the Design and Development of the Geostationary Operational Environmental Satellite R-Series (GOES-R) Space Segment

NASA Technical Reports Server (NTRS)

Sullivan, Pamela C.; Krimchansky, Alexander; Walsh, Timothy J.

2017-01-01

The first of the National Oceanic and Atmospheric Administration (NOAA) Geostationary Operational Environmental Satellite R-series (GOES-R) satellites was launched in November 2016. GOES-R has been developed by NOAA in partnership with the National Aeronautics and Space Administration (NASA). The satellite represents a quantum leap in the state of the art for geostationary weather satellites by providing data from a suite of six new instruments. All instruments were developed expressly for this mission, and include two Earth-observing instruments (the Advanced Baseline Imager (ABI) and Geostationary Lightning Mapper (GLM)), two solar-viewing instruments (Solar Ultraviolet Imager (SUVI) and Extreme ultraviolet and X-ray Irradiance Sensors (EXIS)) and two in situ instruments (Space Environment In-Situ Suite (SEISS) and a magnetometer pair). In addition to hosting the instruments, GOES-R also accommodates several communication packages designed to collect and relay data for weather forecasting and emergency management. Accommodating the six instruments and four communication payloads imposed challenging and competing constraints on the satellite, including requirements for extremely stable earth and solar pointing, high-speed and nearly error-free instrument data transmission, and a very quiet electromagnetic background. To meet mission needs, GOES-R employed several technological innovations, including low-thrust rocket engines that allow instrument observations to continue during maneuvers, and the first civilian use of Global Positioning System-based orbit determination in geostationary orbit. This paper will provide a brief overview of the GOES-R satellite and its instruments as well as the developmental challenges involved in accommodating the instruments and communications payloads.

Using NASA's Reference Architecture: Comparing Polar and Geostationary Data Processing Systems

NASA Technical Reports Server (NTRS)

Ullman, Richard; Burnett, Michael

2013-01-01

The JPSS and GOES-R programs are housed at NASA GSFC and jointly implemented by NASA and NOAA to NOAA requirements. NASA's role in the JPSS Ground System is to develop and deploy the system according to NOAA requirements. NASA's role in the GOES-R ground segment is to provide Systems Engineering expertise and oversight for NOAA's development and deployment of the system. NASA's Earth Science Data Systems Reference Architecture is a document developed by NASA's Earth Science Data Systems Standards Process Group that describes a NASA Earth Observing Mission Ground system as a generic abstraction. The authors work within the respective ground segment projects and are also separately contributors to the Reference Architecture document. Opinions expressed are the author's only and are not NOAA, NASA or the Ground Projects' official positions.

Validation of Infrared Azimuthal Model as Applied to GOES Data Over the ARM SGP

NASA Technical Reports Server (NTRS)

Gambheer, Arvind V.; Doelling, David R.; Spangenberg, Douglas A.; Minnis, Patrick

2004-01-01

The goal of this research is to identify and reduce the GOES-8 IR temperature biases, induced by a fixed geostationary position, during the course of a day. In this study, the same CERES LW window channel model is applied to GOES-8 IR temperatures during clear days over the Atmospheric Radiation Measurement-Southern Great Plains Central Facility (SCF). The model-adjusted and observed IR temperatures are compared with topof- the-atmosphere (TOA) estimated temperatures derived from a radiative transfer algorithm based on the atmospheric profile and surface radiometer measurements. This algorithm can then be incorporated to derive more accurate Ts from real-time satellite operational products.

After 10 years of service, NOAA retires GOES-12 satellite

Science.gov Websites

Destinations After 10 years of service, NOAA retires GOES-12 satellite Progress continuing toward launch of next-generation GOES-R satellite August 19, 2013 GOES-12 captured this visible image of Hurricane 10 years of stellar service, NOAA's Geostationary Operational Environmental Satellite (GOES)-12

GOES-R Arrival and Offload

NASA Image and Video Library

2016-08-22

A truck with a specialized transporter drives away from an Air Force C-5 Galaxy transport plane at the Shuttle Landing Facility at NASA's Kennedy Space Center in Florida to deliver the GOES-R spacecraft for launch processing. The GOES series are weather satellites operated by NOAA to enhance forecasts. The spacecraft is to launch aboard a United Launch Alliance Atlas V rocket in November.

A Comparison of Lightning Flashes as Observed by the Lightning Imaging Sensor and the North Alabama Lightning Mapping Array

NASA Technical Reports Server (NTRS)

Bateman, M. G.; Mach, D. M.; McCaul, M. G.; Bailey, J. C.; Christian, H. J.

2008-01-01

The Lightning Imaging Sensor (LIS) aboard the TRMM satellite has been collecting optical lightning data since November 1997. A Lightning Mapping Array (LMA) that senses VHF impulses from lightning was installed in North Alabama in the Fall of 2001. A dataset has been compiled to compare data from both instruments for all times when the LIS was passing over the domain of our LMA. We have algorithms for both instruments to group pixels or point sources into lightning flashes. This study presents the comparison statistics of the flash data output (flash duration, size, and amplitude) from both algorithms. We will present the results of this comparison study and show "point-level" data to explain the differences. AS we head closer to realizing a Global Lightning Mapper (GLM) on GOES-R, better understanding and ground truth of each of these instruments and their respective flash algorithms is needed.

Lightning Jump Algorithm and Relation to Thunderstorm Cell Tracking, GLM Proxy and Other Meteorological Measurements

NASA Technical Reports Server (NTRS)

Schultz, Christopher J.; Carey, Lawrence D.; Cecil, Daniel J.; Bateman, Monte

2012-01-01

The lightning jump algorithm has a robust history in correlating upward trends in lightning to severe and hazardous weather occurrence. The algorithm uses the correlation between the physical principles that govern an updraft's ability to produce microphysical and kinematic conditions conducive for electrification and its role in the development of severe weather conditions. Recent work has demonstrated that the lightning jump algorithm concept holds significant promise in the operational realm, aiding in the identification of thunderstorms that have potential to produce severe or hazardous weather. However, a large amount of work still needs to be completed in spite of these positive results. The total lightning jump algorithm is not a stand-alone concept that can be used independent of other meteorological measurements, parameters, and techniques. For example, the algorithm is highly dependent upon thunderstorm tracking to build lightning histories on convective cells. Current tracking methods show that thunderstorm cell tracking is most reliable and cell histories are most accurate when radar information is incorporated with lightning data. In the absence of radar data, the cell tracking is a bit less reliable but the value added by the lightning information is much greater. For optimal application, the algorithm should be integrated with other measurements that assess storm scale properties (e.g., satellite, radar). Therefore, the recent focus of this research effort has been assessing the lightning jump's relation to thunderstorm tracking, meteorological parameters, and its potential uses in operational meteorology. Furthermore, the algorithm must be tailored for the optically-based GOES-R Geostationary Lightning Mapper (GLM), as what has been observed using Very High Frequency Lightning Mapping Array (VHF LMA) measurements will not exactly translate to what will be observed by GLM due to resolution and other instrument differences. Herein, we present some of the promising aspects and challenges encountered in utilizing objective tracking and GLM proxy data, as well as recent results that demonstrate the value added information gained by combining the lightning jump concept with traditional meteorological measurements.

Guidance, Navigation, and Control Performance for the GOES-R Spacecraft

NASA Technical Reports Server (NTRS)

Chapel, Jim; Stancliffe, Devin; Bevacqua, TIm; Winkler, Stephen; Clapp, Brian; Rood, Tim; Gaylor, David; Freesland, Doug; Krimchansky, Alexander

2014-01-01

The Geostationary Operational Environmental Satellite-R Series (GOES-R) is the first of the next generation geostationary weather satellites. The series represents a dramatic increase in Earth observation capabilities, with 4 times the resolution, 5 times the observation rate, and 3 times the number of spectral bands. GOES-R also provides unprecedented availability, with less than 120 minutes per year of lost observation time. This paper presents the Guidance Navigation & Control (GN&C) requirements necessary to realize the ambitious pointing, knowledge, and Image Navigation and Registration (INR) objectives of GOES-R. Because the suite of instruments is sensitive to disturbances over a broad spectral range, a high fidelity simulation of the vehicle has been created with modal content over 500 Hz to assess the pointing stability requirements. Simulation results are presented showing acceleration, shock response spectra (SRS), and line of sight (LOS) responses for various disturbances from 0 Hz to 512 Hz. Simulation results demonstrate excellent performance relative to the pointing and pointing stability requirements, with LOS jitter for the isolated instrument platform of approximately 1 micro-rad. Attitude and attitude rate knowledge are provided directly to the instrument with an accuracy defined by the Integrated Rate Error (IRE) requirements. The data are used internally for motion compensation. The final piece of the INR performance is orbit knowledge, which GOES-R achieves with GPS navigation. Performance results are shown demonstrating compliance with the 50 to 75 m orbit position accuracy requirements. As presented in this paper, the GN&C performance supports the challenging mission objectives of GOES-R.

An Overview of the Design and Development of the GOES R-Series Space Segment

NASA Technical Reports Server (NTRS)

Sullivan, Pam; Krimchansky, Alexander; Walsh, Timothy

2017-01-01

The first of the National Oceanic and Atmospheric Administration (NOAA) Geostationary Operational Environmental Satellite R-series (GOES-R) satellites was launched in November 2016. GOES-R has been developed by NOAA in partnership with the National Aeronautics and Space Administration (NASA). The satellite represents a quantum leap in the state of the art for geostationary weather satellites by providing data from a suite of six new instruments. All instruments were developed expressly for this mission, and include two Earth-observing instruments (the Advanced Baseline Imager (ABI) and Geostationary Lightning Mapper (GLM)), two solar-viewing instruments (Solar Ultraviolet Imager (SUVI) and Extreme ultraviolet and X-ray Irradiance Sensors (EXIS)) and two in situ instruments (Space Environment In-Situ Suite (SEISS) and a magnetometer pair). In addition to hosting the instruments, GOES-R also accommodates several communication packages designed to collect and relay data for weather forecasting and emergency management. Accommodating the six instruments and four communication payloads imposed challenging and competing constraints on the satellite, including requirements for extremely stable earth and solar pointing, high-speed and nearly error-free instrument data transmission, and a very quiet electromagnetic background. To meet mission needs, GOES-R employed several technological innovations, including low-thrust rocket engines that allow instrument observations to continue during maneuvers, and the first civilian use of Global Positioning System-based orbit determination in geostationary orbit. This paper will provide a brief overview of the GOES-R satellite and its instruments as well as the developmental challenges involved in accommodating the instruments and communications payloads.

An Integrated 0-1 Hour First-Flash Lightning Nowcasting, Lightning Amount and Lightning Jump Warning Capability

NASA Technical Reports Server (NTRS)

Mecikalski, John; Jewett, Chris; Carey, Larry; Zavodsky, Brad; Stano, Geoffrey; Chronis, Themis

2015-01-01

Using satellite-based methods that provide accurate 0-1 hour convective initiation (CI) nowcasts, and rely on proven success coupling satellite and radar fields in the Corridor Integrated Weather System (CIWS; operated and developed at MIT-Lincoln Laboratory), to subsequently monitor for first-flash lightning initiation (LI) and later period lightning trends as storms evolve. Enhance IR-based methods within the GOES-R CI Algorithm (that must meet specific thresholds for a given cumulus cloud before the cloud is considered to have an increased likelihood of producing lightning next 90 min) that forecast LI. Integrate GOES-R CI and LI fields with radar thresholds (e.g., first greater than or equal to 40 dBZ echo at the -10 C altitude) and NWP model data within the WDSS-II system for LI-events from new convective storms. Track ongoing lightning using Lightning Mapping Array (LMA) and pseudo-Geostationary Lightning Mapper (GLM) data to assess per-storm lightning trends (e.g., as tied to lightning jumps) and outline threat regions. Evaluate the ability to produce LI nowcasts through a "lightning threat" product, and obtain feedback from National Weather Service forecasters on its value as a decision support tool.

GOES-R Arrival and Offload

NASA Image and Video Library

2016-08-22

A truck with a specialized transporter drives out of the cargo hold of an Air Force C-5 Galaxy transport plane at the Shuttle Landing Facility at NASA's Kennedy Space Center in Florida to deliver the GOES-R spacecraft for launch processing. The GOES series are weather satellites operated by NOAA to enhance forecasts. The spacecraft is to launch aboard a United Launch Alliance Atlas V rocket in November.

GOES-R Prelaunch News Conference

NASA Image and Video Library

2016-11-17

Scott Messer, program manager, NASA Missions, United Launch Alliance, speak to members of the news media during a Geostationary Operational Environmental Satellite (GOES-R) prelaunch news conference in the Kennedy Space Center's Press Site auditorium in Florida.

GOES-R Prelaunch News Conference

NASA Image and Video Library

2016-11-17

Sandra Smalley, director, Joint Agency Satellite Division, NASA Headquarters, speaks to members of the news media during a Geostationary Operational Environmental Satellite (GOES-R) prelaunch news conference in the Kennedy Space Center's Press Site auditorium in Florida.

GOES-R Prelaunch News Conference

NASA Image and Video Library

2016-11-17

NASA and industry leaders participate in a Geostationary Operational Environmental Satellite (GOES-R), prelaunch news conference in the Kennedy Space Center's Press Site auditorium in Florida. NASA and industry leaders include: Michael Curie, of NASA Communications; Stephen Volz, assistant administrator for satellite and information services, National Oceanic and Atmospheric Administration (NOAA's); Greg Mandt, GOES-R system program director, NOAA; Sandra Smalley, director, Joint Agency Satellite Division, NASA Headquarters; Omar Baez, launch director, NASA Kennedy; Scott Messer, program manager, NASA Missions, United Launch Alliance; and Clay Flinn, launch weather officer, 4th Weather Squadron, Cape Canaveral Air Force Station.

GOES-R Prelaunch News Conference

NASA Image and Video Library

2016-11-17

Members of the news media attend a Geostationary Operational Environmental Satellite (GOES-R) prelaunch news conference in the Kennedy Space Center's Press Site auditorium in Florida. NASA and industry leaders include: Michael Curie, of NASA Communications; Stephen Volz, assistant administrator for satellite and information services, National Oceanic and Atmospheric Administration (NOAA's); Greg Mandt, GOES-R system program director, NOAA; Sandra Smalley, director, Joint Agency Satellite Division, NASA Headquarters; Omar Baez, launch director, NASA Kennedy; Scott Messer, program manager, NASA Missions, United Launch Alliance; and Clay Flinn, launch weather officer, 4th Weather Squadron, Cape Canaveral Air Force Station.

Automated X-ray Flare Detection with GOES, 2003-2017: The Where of the Flare Catalog and Early Statistical Analysis

NASA Astrophysics Data System (ADS)

Loftus, K.; Saar, S. H.

2017-12-01

NOAA's Space Weather Prediction Center publishes the current definitive public soft X-ray flare catalog, derived using data from the X-ray Sensor (XRS) on the Geostationary Operational Environmental Satellites (GOES) series. However, this flare list has shortcomings for use in scientific analysis. Its detection algorithm has drawbacks (missing smaller flux events and poorly characterizing complex ones), and its event timing is imprecise (peak and end times are frequently marked incorrectly, and hence peak fluxes are underestimated). It also lacks explicit and regular spatial location data. We present a new database, "The Where of the Flare" catalog, which improves upon the precision of NOAA's current version, with more consistent and accurate spatial locations, timings, and peak fluxes. Our catalog also offers several new parameters per flare (e.g. background flux, integrated flux). We use data from the GOES Solar X-ray Imager (SXI) for spatial flare locating. Our detection algorithm is more sensitive to smaller flux events close to the background level and more precisely marks flare start/peak/end times so that integrated flux can be accurately calculated. It also decomposes complex events (with multiple overlapping flares) by constituent peaks. The catalog dates from the operation of the first SXI instrument in 2003 until the present. We give an overview of the detection algorithm's design, review the catalog's features, and discuss preliminary statistical analyses of light curve morphology, complex event decomposition, and integrated flux distribution. The Where of the Flare catalog will be useful in studying X-ray flare statistics and correlating X-ray flare properties with other observations. This work was supported by Contract #8100002705 from Lockheed-Martin to SAO in support of the science of NASA's IRIS mission.

GOES-S satellite in thermal vacuum testing

NASA Image and Video Library

2017-12-08

In March, NOAA's Geostationary Operational Environmental Satellite-S (GOES-S) satellite was lifted into a thermal vacuum chamber to test its ability to function in the cold void of space in its orbit 22,300 miles above the Earth. The most complicated and challenging test is thermal vacuum where a satellite experiences four cycles of extreme cold to extreme heat in a giant vacuum chamber. To simulate the environment of space, the chamber is cooled to below minus 100 degrees Celsius or minus 148 degrees Fahrenheit and air is pumped out. The test simulates the temperature changes GOES-S will encounter in space, as well as worst case scenarios of whether the instruments can come back to life in case of a shut down that exposes them to even colder temperatures. In this photo from March 8, the GOES-S satellite was lowered into the giant vacuum chamber at Lockheed Martin Space Systems, Denver, Colorado. GOES-S will be in the thermal vacuum chamber for 45 days. As of March 30, two of four thermal cycles were complete. GOES-S is the second in the GOES-R series. The GOES-R program is a collaborative development and acquisition effort between the National Oceanic and Atmospheric Administration and NASA. The GOES-R series of satellites will help meteorologists observe and predict local weather events, including thunderstorms, tornadoes, fog, flash floods, and other severe weather. In addition, GOES-R will monitor hazards such as aerosols, dust storms, volcanic eruptions, and forest fires and will also be used for space weather, oceanography, climate monitoring, in-situ data collection, and for search and rescue. Credit: Lockheed Martin NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Development of Level 2 Calibration and Validation Plans for GOES-R; What is a RIMP?

NASA Technical Reports Server (NTRS)

Kopp, Thomas J.; Belsma, Leslie O.; Mollner, Andrew K.; Sun, Ziping; Deluccia, Frank

2017-01-01

Calibration and Validation (CalVal) plans for Geostationary Operational Environmental Satellite version R (GOES-R) Level 2 (L2) products were documented via Resource, Implementation, and Management Plans (RIMPs) for all of the official L2 products required from the GOES-R Advanced Baseline Imager (ABI). In 2015 the GOES-R program decided to replace the typical CalVal plans with RIMPs that covered, for a given L2 product, what was required from that product, how it would be validated, and what tools would be used to do so. Similar to Level 1b products, the intent was to cover the full spectrum of planning required for the CalVal of L2 ABI products. Instead of focusing on step-by-step procedures, the RIMPs concentrated on the criteria for each stage of the validation process (Beta, Provisional, and Full Validation) and the many elements required to prove when each stage was reached.

Geostationary Operational Environmental Satellites (GOES): R series hyperspectral environmental suite (HES) overview

NASA Astrophysics Data System (ADS)

Martin, Gene; Criscione, Joseph C.; Cauffman, Sandra A.; Davis, Martin A.

2004-11-01

The Hyperspectral Environmental Suite (HES) instrument is currently under development by the NASA GOES-R Project team within the framework of the GOES Program to fulfill the future needs and requirements of the National Environmental Satellite, Data, and Information Service (NESDIS) Office. As part of the GOES-R instrument complement, HES will provide measurements of the traditional temperature and water vapor vertical profiles with higher accuracy and vertical resolution than obtained through current sounder technologies. HES will provide measurements of the properties of the shelf and coastal waters and back up imaging (at in-situ resolution) for the GOES-R Advanced Baseline Imager (ABI). The HES team is forging the future of remote environmental monitoring with the development of an operational instrument with high temporal, spatial and spectral-resolution and broad hemispheric coverage. The HES development vision includes threshold and goal requirements that encompass potential system solutions. The HES team has defined tasks for the instrument(s) that include a threshold functional complement of Disk Sounding (DS), Severe Weather/Mesoscale Sounding (SW/M), and Shelf and Coastal Waters imaging (CW) and a goal functional complement of Open Ocean (OO) imaging, and back up imaging (at in-situ resolution) for the GOES-R Advanced Baseline Imager (ABI). To achieve the best-value procurement, the GOES-R Project has base-lined a two-phase procurement approach to the HES design and development; a Formulation/study phase and an instrument Implementation phase. During Formulation, currently slated for the FY04-05 timeframe, the developing team(s) will perform Systems Requirements Analysis and evaluation, System Trade and Requirements Baseline Studies, Risk Assessment and Mitigation Strategy and complete a Preliminary Conceptual Design of the HES instrument. The results of the formulation phase will be leveraged to achieve an effective and efficient system solution during the Implementation Phase scheduled to begin FY05 for a resultant FY12 launch. The magnitude of complexity of the HES development requires an appreciation of the technologies required to achieve the functional objectives. To this end, the GOES-R project team is making available all NASA developed technologies to potential HES vendors, including, the NASA New Millennium Program"s (NMP) Earth Observing-3, Geostationary Imaging Fourier Transform Spectrometer (GIFTS) instrument developed technologies, as applicable. It is anticipated that the instrument(s) meeting the HES requirements will be either a dispersive spectrometer or an interferometric spectrometer or perhaps a combination. No instrument configuration is preferred or favored by the Government. This paper outlines the HES development plan; including an overview of current requirements, existing partnerships and the GOES-R project methodologies to achieve the advanced functional objectives of the GOES Program partnership.

GOES-R Prelaunch News Conference

NASA Image and Video Library

2016-11-17

Clay Flinn, launch weather officer, 4th Weather Squadron, Cape Canaveral Air Force Station, speaks to members of the news media during a Geostationary Operational Environmental Satellite (GOES-R) prelaunch news conference in the Kennedy Space Center's Press Site auditorium in Florida.

In-Flight Guidance, Navigation, and Control Performance Results for the GOES-16 Spacecraft

NASA Technical Reports Server (NTRS)

Chapel, Jim; Stancliffe, Devin; Bevacqua, Tim; Winkler, Stephen; Clapp, Brian; Rood, Tim; Freesland, Doug; Reth, Alan; Early, Derrick; Walsh, Tim;

Preparing the Direct Broadcast Community for GOES-R

NASA Astrophysics Data System (ADS)

Dubey, K. F.; Baptiste, E.; Prasad, K.; Shin, H.

2012-12-01

The first satellite in the United States next generation weather satellite program, GOES-R, will be launched in 2015. SeaSpace Corporation is using our recent experience and lessons learned from bringing Suomi NPP-capable direct reception systems online, to similarly bring direct reception solutions to future GOES-R users. This includes earlier outreach to customers, due to the advance budgeting deadline for procurement in many agencies. With the cancellation of eGRB, all current GOES gvar customer will need a new direct readout system, with a new receiver, high powered processing subsystem, and a larger antenna in some locations. SeaSpace's preparations have also included communicating with program leaders in NOAA and NASA regarding direct readout specifications and the development of the borrowing process for the government-procured GRB emulator. At the request of NASA, SeaSpace has offered input towards the emulator check-out process, which is expected to begin in spring 2013. After the launch of Suomi NPP, SeaSpace found a need by non-traditional customers (such as customers with non-SeaSpace ground stations or those getting data via the NOAA archive), for a processing-only subsystem. In response to this need, SeaSpace developed such a solution for Suomi NPP users, and plans to do similar for GOES-R. This presentation will cover the steps that SeaSpace is undertaking to prepare the members of the direct reception community for reception and processing of GOES-R satellite data, and detail the solutions offered.

GOES-R active vibration damping controller design, implementation, and on-orbit performance

NASA Astrophysics Data System (ADS)

Clapp, Brian R.; Weigl, Harald J.; Goodzeit, Neil E.; Carter, Delano R.; Rood, Timothy J.

2018-01-01

GOES-R series spacecraft feature a number of flexible appendages with modal frequencies below 3.0 Hz which, if excited by spacecraft disturbances, can be sources of undesirable jitter perturbing spacecraft pointing. To meet GOES-R pointing stability requirements, the spacecraft flight software implements an Active Vibration Damping (AVD) rate control law which acts in parallel with the nadir point attitude control law. The AVD controller commands spacecraft reaction wheel actuators based upon Inertial Measurement Unit (IMU) inputs to provide additional damping for spacecraft structural modes below 3.0 Hz which vary with solar wing angle. A GOES-R spacecraft dynamics and attitude control system identified model is constructed from pseudo-random reaction wheel torque commands and IMU angular rate response measurements occurring over a single orbit during spacecraft post-deployment activities. The identified Fourier model is computed on the ground, uplinked to the spacecraft flight computer, and the AVD controller filter coefficients are periodically computed on-board from the Fourier model. Consequently, the AVD controller formulation is based not upon pre-launch simulation model estimates but upon on-orbit nadir point attitude control and time-varying spacecraft dynamics. GOES-R high-fidelity time domain simulation results herein demonstrate the accuracy of the AVD identified Fourier model relative to the pre-launch spacecraft dynamics and control truth model. The AVD controller on-board the GOES-16 spacecraft achieves more than a ten-fold increase in structural mode damping for the fundamental solar wing mode while maintaining controller stability margins and ensuring that the nadir point attitude control bandwidth does not fall below 0.02 Hz. On-orbit GOES-16 spacecraft appendage modal frequencies and damping ratios are quantified based upon the AVD system identification, and the increase in modal damping provided by the AVD controller for each structural mode is presented. The GOES-16 spacecraft AVD controller frequency domain stability margins and nadir point attitude control bandwidth are presented along with on-orbit time domain disturbance response performance.

GOES-R Active Vibration Damping Controller Design, Implementation, and On-Orbit Performance

NASA Technical Reports Server (NTRS)

Clapp, Brian R.; Weigl, Harald J.; Goodzeit, Neil E.; Carter, Delano R.; Rood, Timothy J.

2017-01-01

GOES-R series spacecraft feature a number of flexible appendages with modal frequencies below 3.0 Hz which, if excited by spacecraft disturbances, can be sources of undesirable jitter perturbing spacecraft pointing. In order to meet GOES-R pointing stability requirements, the spacecraft flight software implements an Active Vibration Damping (AVD) rate control law which acts in parallel with the nadir point attitude control law. The AVD controller commands spacecraft reaction wheel actuators based upon Inertial Measurement Unit (IMU) inputs to provide additional damping for spacecraft structural modes below 3.0 Hz which vary with solar wing angle. A GOES-R spacecraft dynamics and attitude control system identified model is constructed from pseudo-random reaction wheel torque commands and IMU angular rate response measurements occurring over a single orbit during spacecraft post-deployment activities. The identified Fourier model is computed on the ground, uplinked to the spacecraft flight computer, and the AVD controller filter coefficients are periodically computed on-board from the Fourier model. Consequently, the AVD controller formulation is based not upon pre-launch simulation model estimates but upon on-orbit nadir point attitude control and time-varying spacecraft dynamics. GOES-R high-fidelity time domain simulation results herein demonstrate the accuracy of the AVD identified Fourier model relative to the pre-launch spacecraft dynamics and control truth model. The AVD controller on-board the GOES-16 spacecraft achieves more than a ten-fold increase in structural mode damping of the fundamental solar wing mode while maintaining controller stability margins and ensuring that the nadir point attitude control bandwidth does not fall below 0.02 Hz. On-orbit GOES-16 spacecraft appendage modal frequencies and damping ratios are quantified based upon the AVD system identification, and the increase in modal damping provided by the AVD controller for each structural mode is presented. The GOES-16 spacecraft AVD controller frequency domain stability margins and nadir point attitude control bandwidth are presented along with on-orbit time domain disturbance response performance.

27 CFR 9.178 - Columbia Gorge.

Code of Federal Regulations, 2013 CFR

2013-04-01

... Columbia River. From this point, the boundary line— (1) Goes 1.5 miles straight north along the R9E-R10E line to the northwest corner of section 19, T3N, R10E (Hood River Quadrangle); (2) Continues 2 miles... Quadrangle); (3) Goes 4.1 miles straight north along the section line, crossing onto the Northwestern Lake...

27 CFR 9.178 - Columbia Gorge.

Code of Federal Regulations, 2011 CFR

2011-04-01

... Columbia River. From this point, the boundary line— (1) Goes 1.5 miles straight north along the R9E-R10E line to the northwest corner of section 19, T3N, R10E (Hood River Quadrangle); (2) Continues 2 miles... Quadrangle); (3) Goes 4.1 miles straight north along the section line, crossing onto the Northwestern Lake...

27 CFR 9.178 - Columbia Gorge.

Code of Federal Regulations, 2014 CFR

2014-04-01

... Columbia River. From this point, the boundary line— (1) Goes 1.5 miles straight north along the R9E-R10E line to the northwest corner of section 19, T3N, R10E (Hood River Quadrangle); (2) Continues 2 miles... Quadrangle); (3) Goes 4.1 miles straight north along the section line, crossing onto the Northwestern Lake...

27 CFR 9.178 - Columbia Gorge.

Code of Federal Regulations, 2012 CFR

2012-04-01

... Columbia River. From this point, the boundary line— (1) Goes 1.5 miles straight north along the R9E-R10E line to the northwest corner of section 19, T3N, R10E (Hood River Quadrangle); (2) Continues 2 miles... Quadrangle); (3) Goes 4.1 miles straight north along the section line, crossing onto the Northwestern Lake...

Characterizing the GOES-R (GOES-16) Geostationary Lightning Mapper (GLM) On-Orbit Performance

NASA Technical Reports Server (NTRS)

Rudlosky, Scott D.; Goodman, Steven J.; Koshak, William J.; Blakeslee, Richard J.; Buechler, Dennis E.; Mach, Douglas M.; Bateman, Monte

2017-01-01

Two overlapping efforts help to characterize the GLM performance, the Post Launch Test (PLT) phase to validate the predicted pre-launch instrument performance and the Post Launch Product Test (PLPT) phase to validate the lightning detection product used in forecast and warning decision-making. This paper documents the calibration and validation plans and activities for the first 6 months of GLM on-orbit testing and validation commencing with first light on 4 January 2017. The PLT phase addresses image quality, on-orbit calibration, RTEP threshold tuning, image navigation, noise filtering, and solar intrusion assessment, resulting in a GLM calibration parameter file. The PLPT includes four main activities, the Reference Data Comparisons (RDC), Algorithm Testing (AT), Instrument Navigation and Registration Testing (INRT), and Long Term Baseline Testing (LTBT). Field campaigns are also designed to contribute valuable insights into the GLM performance capabilities. The PLPT tests each contribute to the beta, provisional, and fully validated GLM data.

GOES-S NASA Social

NASA Image and Video Library

2018-02-28

Pam Sullivan, NASA's GOES-R flight director, left, and A.J. Sandora, Lockheed Martin's GOES-R Series Mechanical Operations Assembly, Test and Launch Operations (ATLO) manager, speak to members of social media in the Kennedy Space Center’s Press Site auditorium. The briefing focused on the National Oceanic and Atmospheric Administration's, or NOAA's, Geostationary Operational Environmental Satellite, or GOES-S. The spacecraft is the second satellite in a series of next-generation NOAA weather satellites. It will launch to a geostationary position over the U.S. to provide images of storms and help predict weather forecasts, severe weather outlooks, watches, warnings, lightning conditions and longer-term forecasting. GOES-S is slated to lift off at 5:02 p.m. EST on March 1, 2018 aboard a United Launch Alliance Atlas V rocket.

Mapping high-resolution incident photosynthetically active radiation over land surfaces from MODIS and GOES satellite data

NASA Astrophysics Data System (ADS)

Liang, S.; Wang, K.; Wang, D.; Townshend, J.; Running, S.; Tsay, S.

2008-05-01

Incident photosynthetically active radiation (PAR) is a key variable required by almost all terrestrial ecosystem models. Many radiation efficiency models are linearly related canopy productivity to the absorbed PAR. Unfortunately, the current incident PAR products estimated from remotely sensed data or calculated by radiation models at spatial and temporal resolutions are not sufficient for carbon cycle modeling and various applications. In this study, we aim to develop incident PAR products at one kilometer scale from multiple satellite sensors, such as Moderate Resolution Imaging Spectrometer (MODIS) and Geostationary Operational Environmental Satellite (GOES) sensor. We first developed a look-up table approach to estimate instantanerous incident PAR product from MODIS (Liang et al., 2006). The temporal observations of each pixel are used to estimate land surface reflectance and look-up tables of both aerosol and cloud are searched, based on the top-of-atmosphere reflectance and surface reflectance for determining incident PAR. The incident PAR product includes both the direct and diffuse components. The calculation of a daily integrated PAR using two different methods has also been developed (Wang, et al., 2008a). The similar algorithm has been further extended to GOES data (Wang, et al., 2008b, Zheng, et al., 2008). Extensive validation activities are conducted to evaluate the algorithms and products using the ground measurements from FLUXNET and other networks. They are also compared with other satellite products. The results indicate that our approaches can produce reasonable PAR product at 1km resolution. We have generated 1km incident PAR products over North America for several years, which are freely available to the science community. Liang, S., T. Zheng, R. Liu, H. Fang, S. C. Tsay, S. Running, (2006), Estimation of incident Photosynthetically Active Radiation from MODIS Data, Journal of Geophysical Research ¡§CAtmosphere. 111, D15208,doi:10.1029/2005JD006730. Wang, D., S. Liang, and Zheng, T., (2008a), Integrated daily PAR from MODIS. International Journal of Remote Sensing, revised. Wang, K., S. Liang, T. Zheng and D. Wang, (2008b), Simultaneous estimation of surface photosynthetically active radiation and albedo from GOES, Remote Sensing of Environment, revised. Zheng, T., S. Liang, K. Wang, (2008), Estimation of incident PAR from GOES imagery, Journal of Applied Meteorology and Climatology. in press.

GEO-LEO reflectance band inter-comparison with BRDF and atmospheric scattering corrections

NASA Astrophysics Data System (ADS)

Chang, Tiejun; Xiong, Xiaoxiong Jack; Keller, Graziela; Wu, Xiangqian

2017-09-01

The inter-comparison of the reflective solar bands between the instruments onboard a geostationary orbit satellite and onboard a low Earth orbit satellite is very helpful to assess their calibration consistency. GOES-R was launched on November 19, 2016 and Himawari 8 was launched October 7, 2014. Unlike the previous GOES instruments, the Advanced Baseline Imager on GOES-16 (GOES-R became GOES-16 after November 29 when it reached orbit) and the Advanced Himawari Imager (AHI) on Himawari 8 have onboard calibrators for the reflective solar bands. The assessment of calibration is important for their product quality enhancement. MODIS and VIIRS, with their stringent calibration requirements and excellent on-orbit calibration performance, provide good references. The simultaneous nadir overpass (SNO) and ray-matching are widely used inter-comparison methods for reflective solar bands. In this work, the inter-comparisons are performed over a pseudo-invariant target. The use of stable and uniform calibration sites provides comparison with appropriate reflectance level, accurate adjustment for band spectral coverage difference, reduction of impact from pixel mismatching, and consistency of BRDF and atmospheric correction. The site in this work is a desert site in Australia (latitude -29.0 South; longitude 139.8 East). Due to the difference in solar and view angles, two corrections are applied to have comparable measurements. The first is the atmospheric scattering correction. The satellite sensor measurements are top of atmosphere reflectance. The scattering, especially Rayleigh scattering, should be removed allowing the ground reflectance to be derived. Secondly, the angle differences magnify the BRDF effect. The ground reflectance should be corrected to have comparable measurements. The atmospheric correction is performed using a vector version of the Second Simulation of a Satellite Signal in the Solar Spectrum modeling and BRDF correction is performed using a semi-empirical model. AHI band 1 (0.47μm) shows good matching with VIIRS band M3 with difference of 0.15%. AHI band 5 (1.69μm) shows largest difference in comparison with VIIRS M10.

Two Exceptions in the Large SEP Events of Solar Cycles 23 and 24

NASA Technical Reports Server (NTRS)

Thakur, N.; Gopalswamy, N.; Makela, P.; Akiyama, S.; Yashiro, S.; Xie, H.

2016-01-01

We discuss our findings from a survey of all large solar energetic particle (SEP) events of Solar Cycles 23 and 24, i.e. the SEP events where the intensity of greater than 10 megaelectronvolts protons observed by GOES (Geostationary Operational Environmental Satellite) was greater than 10 proton flux units. In our previous work (Gopalswamy et al. in Geophys.Res.Lett. 41, 2673, 2014) we suggested that ground level enhancements (GLEs) in Cycles 23 and 24 also produce an intensity increase in the GOES greater than 700 megaelectronvolts proton channel. Our survey, now extended to include all large SEP events of Cycle 23, confirms this to be true for all but two events: i) the GLE of 6 May 1998 (GLE57) for which GOES did not observe enhancement in greater than 700 megaelectronvolts protons intensities and ii) a high-energy SEP event of 8 November 2000, for which GOES observed greater than 700 megaelectronvolts protons but no GLE was recorded. Here we discuss these two exceptions. We compare GLE57 with other small GLEs, and the 8 November 2000 SEP event with those that showed similar intensity increases in the GOES greater than 700 megaelectronvolts protons but produced GLEs. We find that, because GOES greater than 700 megaelectronvolts proton intensity enhancements are typically small for small GLEs, they are difficult to discern near solar minima due to higher background. Our results also support that GLEs are generally observed when shocks of the associated coronal mass ejections (CMEs) form at heights 1.2-1.93 solar radii [R (sub solar)] and when the solar particle release occurs between 2-6 solar radii [R (sub solar)]. Our secondary findings support the view that the nose region of the CME-shock may be accelerating the first-arriving GLE particles and the observation of a GLE is also dependent on the latitudinal connectivity of the observer to the CME-shock nose. We conclude that the GOES greater than 700 megaelectronvolts proton channel can be used as an indicator of GLEs excluding some rare exceptions, such as those discussed here.

GPS Receiver On-Orbit Performance for the GOES-R Spacecraft

NASA Technical Reports Server (NTRS)

Winkler, Stephen; Ramsey, Graeme; Frey, Charles; Chapel, Jim; Chu, Donald; Freesland, Douglas; Krimchansky, Alexander; Concha, Marco

2017-01-01

This paper evaluates the on-orbit performance of the first civilian operational use of a Global Positioning System Receiver (GPSR) at a geostationary orbit (GEO). The GPSR is on-board the newly launched Geostationary Operational Environmental Satellite (GOES-R). GOES-R is the first of four next generation GEO weather satellites for NOAA, now in orbit GOES-R is formally identified as GOES-16. Among the pioneering technologies required to support its improved spatial, spectral and temporal resolution is a GPSR. The GOES-16 GPSR system is a new design that was mission critical and therefore received appropriate scrutiny. As ground testing of a GPSR for GEO can only be done by simulations with numerous assumptions and approximations regarding the current GPS constellation, this paper reveals what performance can be achieved in using on orbit data. Extremely accurate orbital position is achieved using GPS navigation at GEO. Performance results are shown demonstrating compliance with the1007575 meter and 6 cms radial/in-track/cross-track orbital position and velocity accuracy requirements of GOES-16. The aforementioned compliance includes station-keeping and momentum management maneuvers, contributing to no observational outages. This performance is achieved by a completely new system design consisting of a unique L1 GEOantenna, low-noise amplifier (LNA) assembly and a 12 channel GPSR capable of tracking the edge of the main beam and the side lobes of the GPS L1 signals. This paper presents the definitive answer that the GOES-16 GPSR solution exceeds all performance requirements tracking up to 12 satellites and achieving excellent carrier-to-noise density (C/N0). Additionally, these performance results show the practicality of this approach. This paper makes it clear that all future GEO Satellites should consider the addition of a GPSR in their spacecraft design, otherwise they may be sacrificing spacecraft capabilities and accuracy along with incurring increased and continual demand on ground support.

A near real time regional JPSS and GOES-R data assimilation system for high impact weather research and applications

NASA Astrophysics Data System (ADS)

Li, J.; Wang, P.; Han, H.; Schmit, T. J.

2014-12-01

JPSS and GOES-R observations play important role in numerical weather prediction (NWP). However, how to best represent the information from satellite observations and how to get value added information from these satellite data into regional NWP models, including both radiance and derived products, still need investigations. In order to enhance the applications of JPSS and GOES-R data in regional NWP for high impact weather forecasts, scientists from Cooperative Institute of Meteorological Satellite Studies (CIMSS) at University of Wisconsin-Madison have recently developed a near realtime regional Satellite Data Assimilation system for Tropical storm forecasts (SDAT) (http://cimss.ssec.wisc.edu/sdat). The system consists of the community Gridpoint Statistical Interpolation (GSI) assimilation system and the advanced Weather Research Forecast (WRF) model. In addition to assimilate GOES, AMSUA/AMSUB, HIRS, MHS, ATMS (Suomi-NPP), AIRS and IASI radiances, the SDAT is also able to assimilate satellite-derived products such as hyperspectral IR retrieved temperature and moisture profiles, total precipitable water (TPW), GOES Sounder (and future GOES-R) layer precipitable water (LPW) and GOES Imager atmospheric motion vector (AMV) products into the system. Real time forecasted GOES infrared (IR) images simulated from SDAT output have also been part of the SDAT system for applications and forecast evaluations. To set up the system parameters, a series of experiments have been carried out to test the impacts of different initialization schemes, including different background error matrix, different NCEP global model date sets, and different WRF model horizontal resolutions. Using SDAT as a research testbed, researches have been conducted for different satellite data impacts study, as well as different techniques for handling clouds in radiance assimilation. Since the fall of 2013, the SDAT system has been running in near real time. The results from historical cases and 2014 hurricane season cases will be compared with the operational GFS and HWRF, and presented at the meeting.

Data Products From Particle Detectors On-Board NOAA's Newest Space Weather Monitor

NASA Astrophysics Data System (ADS)

Kress, B. T.; Rodriguez, J. V.; Onsager, T. G.

2017-12-01

NOAA's newest Geostationary Operational Environmental Satellite, GOES-16, was launched on 19 November 2016. Instrumentation on-board GOES-16 includes the new Space Environment In-Situ Suite (SEISS), which has been collecting data since 8 January 2017. SEISS is composed of five magnetospheric particle sensor units: an electrostatic analyzer for measuring 30 eV - 30 keV ions and electrons (MPS-LO), a high energy particle sensor (MPS-HI) that measures keV to MeV electrons and protons, east and west facing Solar and Galactic Proton Sensor (SGPS) units with 13 differential channels between 1-500 MeV, and an Energetic Heavy Ion Sensor (EHIS) that measures 30 species of heavy ions (He-Ni) in five energy bands in the 10-200 MeV/nuc range. Measurement of low energy magnetospheric particles by MPS-LO and heavy ions by EHIS are new capabilities not previously flown on the GOES system. Real-time data from GOES-16 will support space weather monitoring and first-principles space weather modeling by NOAA's Space Weather Prediction Center (SWPC). Space weather level 2+ data products under development at NOAA's National Centers for Environmental Information (NCEI) include the Solar Energetic Particle (SEP) Event Detection algorithm. Legacy components of the SEP event detection algorithm (currently produced by SWPC) include the Solar Radiation Storm Scales. New components will include, e.g., event fluences. New level 2+ data products also include the SEP event Linear Energy Transfer (LET) Algorithm, for transforming energy spectra from EHIS into LET spectra, and the Density and Temperature Moments and Spacecraft Charging algorithm. The moments and charging algorithm identifies electron and ion signatures of spacecraft surface (frame) charging in the MPS-LO fluxes. Densities and temperatures from MPS-LO will also be used to support a magnetopause crossing detection algorithm. The new data products will provide real-time indicators of potential radiation hazards for the satellite community and data for future studies of space weather effects. This presentation will include an overview of these algorithms and examples of their performance during recent co-rotation interaction region (CIR) associated radiation belt enhancements and a solar particle event on 14-15 July 2017.

Essential SpaceWire Hardware Capabilities for a Robust Network

NASA Technical Reports Server (NTRS)

Birmingham, Michael; Krimchansky, Alexander; Anderson, William; Lombardi, Matthew

2016-01-01

The Geostationary Operational Environmental Satellite R-Series Program (GOES-R) mission is a joint program between National Oceanic & Atmospheric Administration (NOAA) and National Aeronautics & Space Administration (NASA) Goddard Space Flight Center (GSFC). GOES-R project selected SpaceWire as the best solution to satisfy the desire for simple and flexible instrument to spacecraft command and telemetry communications. GOES-R development and integration is complete and the observatory is scheduled for launch October 2016. The spacecraft design was required to support redundant SpaceWire links for each instrument side, as well as to route the fewest number of connections through a Slip Ring Assembly necessary to support Solar pointing instruments. The final design utilized two different router designs. The SpaceWire standard alone does not ensure the most practical or reliable network. On GOES-R a few key hardware capabilities were identified that merit serious consideration for future designs. Primarily these capabilities address persistent port stalls and the prevention of receive buffer overflows. Workarounds were necessary to overcome shortcomings that could be avoided in future designs if they utilize the capabilities, discussed in this paper, above and beyond the requirements of the SpaceWire standard.

Calibration/validation strategy for GOES-R L1b data products

NASA Astrophysics Data System (ADS)

Fulbright, Jon P.; Kline, Elizabeth; Pogorzala, David; MacKenzie, Wayne; Williams, Ryan; Mozer, Kathryn; Carter, Dawn; Race, Randall; Sims, Jamese; Seybold, Matthew

2016-10-01

The Geostationary Operational Environmental Satellite-R series (GOES-R) will be the next generation of NOAA geostationary environmental satellites. The first satellite in the series is planned for launch in November 2016. The satellite will carry six instruments dedicated to the study of the Earth's weather, lightning mapping, solar observations, and space weather monitoring. Each of the six instruments require specialized calibration plans to achieve their product quality requirements. In this talk we will describe the overall on-orbit calibration program and data product release schedule of the GOES-R program, as well as an overview of the strategies of the individual instrument science teams. The Advanced Baseline Imager (ABI) is the primary Earth-viewing weather imaging instrument on GOES-R. Compared to the present on-orbit GOES imagers, ABI will provide three times the spectral bands, four times the spatial resolution, and operate five times faster. The increased data demands and product requirements necessitate an aggressive and innovative calibration campaign. The Geostationary Lightning Mapper (GLM) will provide continuous rapid lightning detection information covering the Americas and nearby ocean regions. The frequency of lightning activity points to the intensification of storms and may improve tornado warning lead time. The calibration of GLM will involve intercomparisons with ground-based lightning detectors, an airborne field campaign, and a ground-based laser beacon campaign. GOES-R also carries four instruments dedicated to the study of the space environment. The Solar Ultraviolet Imager (SUVI) and the Extreme Ultraviolet and X-Ray Irradiance Sensors (EXIS) will study solar activity that may affect power grids, communication, and spaceflight. The Space Environment In-Situ Suite (SEISS) and the Magnetometer (MAG) study the in-situ space weather environment. These instruments follow a calibration and validation (cal/val) program that relies on intercomparisons with other space-based sensors and utilize special spacecraft maneuvers. Given the importance of cal/val to the success of GOES-R, the mission is committed to a long-term effort. This commitment enhances our knowledge of the long-term data quality and builds user confidence. The plan is a collaborative effort amongst the National Oceanic and Atmospheric Administration (NOAA), the National Institute of Standards and Technology (NIST), and the National Aeronautics and Space Administration (NASA). It is being developed based on the experience and lessons-learned from the heritage GOES and Polar-orbiting Operational Environmental Satellite (POES) systems, as well as other programs. The methodologies described in the plan encompass both traditional approaches and the current state-of-the-art in cal/val.

Post Launch Calibration and Testing of the Geostationary Lightning Mapper on the GOES-R Satellite

NASA Technical Reports Server (NTRS)

Rafal, Marc D.; Clarke, Jared T.; Cholvibul, Ruth W.

2016-01-01

The Geostationary Operational Environmental Satellite R (GOES-R) series is the planned next generation of operational weather satellites for the United States National Oceanic and Atmospheric Administration (NOAA). The National Aeronautics and Space Administration (NASA) is procuring the GOES-R spacecraft and instruments with the first launch of the GOES-R series planned for October 2016. Included in the GOES-R Instrument suite is the Geostationary Lightning Mapper (GLM). GLM is a single-channel, near-infrared optical detector that can sense extremely brief (800 microseconds) transient changes in the atmosphere, indicating the presence of lightning. GLM will measure total lightning activity continuously over the Americas and adjacent ocean regions with near-uniform spatial resolution of approximately 10 km. Due to its large CCD (1372x1300 pixels), high frame rate, sensitivity and onboard event filtering, GLM will require extensive post launch characterization and calibration. Daytime and nighttime images will be used to characterize both image quality criteria inherent to GLM as a space-based optic system (focus, stray light, crosstalk, solar glint) and programmable image processing criteria (dark offsets, gain, noise, linearity, dynamic range). In addition ground data filtering will be adjusted based on lightning-specific phenomenology (coherence) to isolate real from false transients with their own characteristics. These parameters will be updated, as needed, on orbit in an iterative process guided by pre-launch testing. This paper discusses the planned tests to be performed on GLM over the six-month Post Launch Test period to optimize and demonstrate GLM performance.

Post launch calibration and testing of the Geostationary Lightning Mapper on GOES-R satellite

NASA Astrophysics Data System (ADS)

Rafal, Marc; Clarke, Jared T.; Cholvibul, Ruth W.

2016-05-01

The Geostationary Operational Environmental Satellite R (GOES-R) series is the planned next generation of operational weather satellites for the United States National Oceanic and Atmospheric Administration (NOAA). The National Aeronautics and Space Administration (NASA) is procuring the GOES-R spacecraft and instruments with the first launch of the GOES-R series planned for October 2016. Included in the GOES-R Instrument suite is the Geostationary Lightning Mapper (GLM). GLM is a single-channel, near-infrared optical detector that can sense extremely brief (800 μs) transient changes in the atmosphere, indicating the presence of lightning. GLM will measure total lightning activity continuously over the Americas and adjacent ocean regions with near-uniform spatial resolution of approximately 10 km. Due to its large CCD (1372x1300 pixels), high frame rate, sensitivity and onboard event filtering, GLM will require extensive post launch characterization and calibration. Daytime and nighttime images will be used to characterize both image quality criteria inherent to GLM as a space-based optic system (focus, stray light, crosstalk, solar glint) and programmable image processing criteria (dark offsets, gain, noise, linearity, dynamic range). In addition ground data filtering will be adjusted based on lightning-specific phenomenology (coherence) to isolate real from false transients with their own characteristics. These parameters will be updated, as needed, on orbit in an iterative process guided by pre-launch testing. This paper discusses the planned tests to be performed on GLM over the six-month Post Launch Test period to optimize and demonstrate GLM performance.

Post Launch Calibration and Testing of the Geostationary Lightning Mapper on GOES-R Satellite

NASA Technical Reports Server (NTRS)

Rafal, Marc; Cholvibul, Ruth; Clarke, Jared

2016-01-01

The Geostationary Operational Environmental Satellite R (GOES-R) series is the planned next generation of operational weather satellites for the United States National Oceanic and Atmospheric Administration (NOAA). The National Aeronautics and Space Administration (NASA) is procuring the GOES-R spacecraft and instruments with the first launch of the GOES-R series planned for October 2016. Included in the GOES-R Instrument suite is the Geostationary Lightning Mapper (GLM). GLM is a single-channel, near-infrared optical detector that can sense extremely brief (800 s) transient changes in the atmosphere, indicating the presence of lightning. GLM will measure total lightning activity continuously over the Americas and adjacent ocean regions with near-uniform spatial resolution of approximately 10 km. Due to its large CCD (1372x1300 pixels), high frame rate, sensitivity and onboard event filtering, GLM will require extensive post launch characterization and calibration. Daytime and nighttime images will be used to characterize both image quality criteria inherent to GLM as a space-based optic system (focus, stray light, crosstalk, solar glint) and programmable image processing criteria (dark offsets, gain, noise, linearity, dynamic range). In addition ground data filtering will be adjusted based on lightning-specific phenomenology (coherence) to isolate real from false transients with their own characteristics. These parameters will be updated, as needed, on orbit in an iterative process guided by pre-launch testing. This paper discusses the planned tests to be performed on GLM over the six-month Post Launch Test period to optimize and demonstrate GLM performance.

GOES-R Prelaunch News Conference

NASA Image and Video Library

2016-11-17

From left, Sandra Smalley, director, Joint Agency Satellite Division, NASA Headquarters; Omar Baez, launch director, NASA Kennedy; and Scott Messer, program manager, NASA Missions, United Launch Alliance, speak to members of the news media during a Geostationary Operational Environmental Satellite (GOES-R) prelaunch news conference in the Kennedy Space Center's Press Site auditorium in Florida.

Multisensor satellite data integration for sea surface wind speed and direction determination

NASA Technical Reports Server (NTRS)

Glackin, D. L.; Pihos, G. G.; Wheelock, S. L.

1984-01-01

Techniques to integrate meteorological data from various satellite sensors to yield a global measure of sea surface wind speed and direction for input to the Navy's operational weather forecast models were investigated. The sensors were launched or will be launched, specifically the GOES visible and infrared imaging sensor, the Nimbus-7 SMMR, and the DMSP SSM/I instrument. An algorithm for the extrapolation to the sea surface of wind directions as derived from successive GOES cloud images was developed. This wind veering algorithm is relatively simple, accounts for the major physical variables, and seems to represent the best solution that can be found with existing data. An algorithm for the interpolation of the scattered observed data to a common geographical grid was implemented. The algorithm is based on a combination of inverse distance weighting and trend surface fitting, and is suited to combing wind data from disparate sources.

A Prototype Web-based system for GOES-R Space Weather Data

NASA Astrophysics Data System (ADS)

Sundaravel, A.; Wilkinson, D. C.

2010-12-01

The Geostationary Operational Environmental Satellite-R Series (GOES-R) makes use of advanced instruments and technologies to monitor the Earth's surface and provide with accurate space weather data. The first GOES-R series satellite is scheduled to be launched in 2015. The data from the satellite will be widely used by scientists for space weather modeling and predictions. This project looks into the ways of how these datasets can be made available to the scientists on the Web and to assist them on their research. We are working on to develop a prototype web-based system that allows users to browse, search and download these data. The GOES-R datasets will be archived in NetCDF (Network Common Data Form) and CSV (Comma Separated Values) format. The NetCDF is a self-describing data format that contains both the metadata information and the data. The data is stored in an array-oriented fashion. The web-based system will offer services in two ways: via a web application (portal) and via web services. Using the web application, the users can download data in NetCDF or CSV format and can also plot a graph of the data. The web page displays the various categories of data and the time intervals for which the data is available. The web application (client) sends the user query to the server, which then connects to the data sources to retrieve the data and delivers it to the users. Data access will also be provided via SOAP (Simple Object Access Protocol) and REST (Representational State Transfer) web services. These provide functions which can be used by other applications to fetch data and use the data for further processing. To build the prototype system, we are making use of proxy data from existing GOES and POES space weather datasets. Java is the programming language used in developing tools that formats data to NetCDF and CSV. For the web technology we have chosen Grails to develop both the web application and the services. Grails is an open source web application framework based on the Groovy language. We are also making use of the THREDDS (Thematic Realtime Environmental Distributed Data Services) server to publish and access the NetCDF files. We have completed developing software tools to generate NetCDF and CSV data files and also tools to translate NetCDF to CSV. The current phase of the project involves in designing and developing the web interface.

GOES-S Mission Science Briefing

NASA Image and Video Library

2018-02-27

GOES-S Mission Science Briefing hosted by Steve Cole, NASA Communications, with Dan Lindsey, GOES-R senior scientific advisor, NOAA; Louis Uccellini, director, National Weather Service, NOAA; Jim Roberts, scientist, Earth System Research Laboratory, Office of Atmospheric Research, NOAA; Kristin Calhoun, research scientist, National Severe Storms Laboratory, NOAA; and George Morrow, deputy director, NASA Goddard Space Flight Center.

GOES-16 Space Weather Data Availability and Applications

NASA Astrophysics Data System (ADS)

Tilton, M.; Rowland, W. F.; Codrescu, S.; Seaton, D. B.; Redmon, R. J.; Hsu, V.

2017-12-01

In November 2016, NOAA launched the first in the "R" series of Geostationary Operational Environmental Satellites, GOES-16. Compared to its GOES predecessors, the GOES-R series satellites provide improved in situ measurements of charged particles, higher cadence magnetic field measurements, and enhanced remote sensing of the sun through ultraviolet (UV) imagery and X-ray/UV irradiance. GOES-16 space weather instruments will nominally reach provisional status near the beginning of 2018. After this milestone has been achieved, NOAA's National Centers for Environmental Information (NCEI) will provide archive access to GOES-16 space weather data. This presentation will describe the status of the space weather instruments, including available products and their applicability for forecasters, modelers, academics, spacecraft operators, and other users. It will discuss the available access systems for all levels of data-raw telemetry (Level 0), science measurements in high resolution (L1b), and higher-level (L2+) products developed by NCEI scientists. Finally, it will cover NCEI's efforts to promote space weather awareness through data visualization tools and image dissemination via the Helioviewer project.

Assessing and Ensuring GOES-R Magnetometer Accuracy

NASA Technical Reports Server (NTRS)

Carter, Delano R.; Todirita, Monica; Kronenwetter, Jeffrey; Chu, Donald

2016-01-01

The GOES-R magnetometer subsystem accuracy requirement is 1.7 nanoteslas (nT). During quiet times (100 nT), accuracy is defined as absolute mean plus 3 sigma. During storms (300 nT), accuracy is defined as absolute mean plus 2 sigma. Error comes both from outside the magnetometers, e.g. spacecraft fields and misalignments, as well as inside, e.g. zero offset and scale factor errors. Because zero offset and scale factor drift over time, it will be necessary to perform annual calibration maneuvers. To predict performance before launch, we have used Monte Carlo simulations and covariance analysis. Both behave as expected, and their accuracy predictions agree within 30%. With the proposed calibration regimen, both suggest that the GOES-R magnetometer subsystem will meet its accuracy requirements.

Validation of the GOES-16 magnetometer using multipoint measurements and magnetic field models

NASA Astrophysics Data System (ADS)

Califf, S.; Loto'aniu, P. T. M.; Redmon, R. J.; Sarris, T. E.; Brito, T.

2017-12-01

The Geostationary Operational Environmental Satellites (GOES) have been providing continuous geomagnetic field measurements for over 40 years. While the primary purpose of GOES is operational, the magnetometer data are also widely used in the scientific community. In an effort to validate the recently launched GOES-16 magnetometer, we compare the measurements to existing magnetic field models and other GOES spacecraft currently on orbit. There are four concurrent measurements from GOES-13, 14, 15 and 16 spanning 75W to 135W longitude. Also, GOES-13 is being replaced by GOES-16 in the GOES-East location, and during the transition, GOES-13 and GOES-16 will be parked nearby in order to assist with calibration of the new operational satellite. This work explores techniques to quantify the performance of the GOES-16 magnetometer by comparison to data from nearby spacecraft. We also build on previous work to assimilate in situ measurements with existing magnetic field models to assist in comparing data from different spatial locations. Finally, we use this unique dataset from four simultaneous geosynchronous magnetometer measurements and the close separation between GOES-13 and GOES-16 to study the spatial characteristics of ULF waves and other magnetospheric processes.

Near-Real-Time Satellite Cloud Products for Icing Detection and Aviation Weather over the USA

NASA Technical Reports Server (NTRS)

Minnis, Patrick; Smith, William L., Jr.; Nguyen, Louis; Murray, J. J.; Heck, Patrick W.; Khaiyer, Mandana M.

2003-01-01

A set of physically based retrieval algorithms has been developed to derive from multispectral satellite imagery a variety of cloud properties that can be used to diagnose icing conditions when upper-level clouds are absent. The algorithms are being applied in near-real time to the Geostationary Operational Environmental Satellite (GOES) data over Florida, the Southern Great Plains, and the midwestern USA. The products are available in image and digital formats on the world-wide web. The analysis system is being upgraded to analyze GOES data over the CONUS. Validation, 24-hour processing, and operational issues are discussed.

Development of RGB Composite Imagery for Operational Weather Forecasting Applications

NASA Technical Reports Server (NTRS)

Molthan, Andrew L.; Fuell, Kevin K.; Oswald, Hayden, K; Knaff, John A.

2012-01-01

The NASA Short-term Prediction Research and Transition (SPoRT) Center, in collaboration with the Cooperative Institute for Research in the Atmosphere (CIRA), is providing red-green-blue (RGB) color composite imagery to several of NOAA s National Centers and National Weather Service forecast offices as a demonstration of future capabilities of the Advanced Baseline Imager (ABI) to be implemented aboard GOES-R. Forecasters rely upon geostationary satellite imagery to monitor conditions over their regions of responsibility. Since the ABI will provide nearly three times as many channels as the current GOES imager, the volume of data available for analysis will increase. RGB composite imagery can aid in the compression of large data volumes by combining information from multiple channels or paired channel differences into single products that communicate more information than provided by a single channel image. A standard suite of RGB imagery has been developed by the European Organization for the Exploitation of Meteorological Satellites (EUMETSAT), based upon the Spinning Enhanced Visible and Infrared Imager (SEVIRI). The SEVIRI instrument currently provides visible and infrared wavelengths comparable to the future GOES-R ABI. In addition, the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments aboard the NASA Terra and Aqua satellites can be used to demonstrate future capabilities of GOES-R. This presentation will demonstrate an overview of the products currently disseminated to SPoRT partners within the GOES-R Proving Ground, and other National Weather Service forecast offices, along with examples of their application. For example, CIRA has used the channels of the current GOES sounder to produce an "air mass" RGB originally designed for SEVIRI. This provides hourly imagery over CONUS for looping applications while demonstrating capabilities similar to the future ABI instrument. SPoRT has developed similar "air mass" RGB imagery from MODIS, and through a case study example, synoptic-scale features evident in single-channel water vapor imagery are shown in the context of the air mass product. Other products, such as the "nighttime microphysics" RGB, are useful in the detection of low clouds and fog. Nighttime microphysics products from MODIS offer some advantages over single-channel or spectral difference techniques and will be discussed in the context of a case study. Finally, other RGB products from SEVIRI are being demonstrated as precursors to GOES-R within the GOES-R Proving Ground. Examples of "natural color" and "dust" imagery will be shown with relevant applications.

Spectral radiation analyses of the GOES solar illuminated hexagonal cell scan mirror back

NASA Technical Reports Server (NTRS)

Fantano, Louis G.

1993-01-01

A ray tracing analytical tool has been developed for the simulation of spectral radiation exchange in complex systems. Algorithms are used to account for heat source spectral energy, surface directional radiation properties, and surface spectral absorptivity properties. This tool has been used to calculate the effective solar absorptivity of the geostationary operational environmental satellites (GOES) scan mirror in the calibration position. The development and design of Sounder and Imager instruments on board GOES is reviewed and the problem of calculating the effective solar absorptivity associated with the GOES hexagonal cell configuration is presented. The analytical methodology based on the Monte Carlo ray tracing technique is described and results are presented and verified by experimental measurements for selected solar incidence angles.

GOES-S Prelaunch News Conference

NASA Image and Video Library

2018-02-27

In the Kennedy Space Center's Press Site auditorium, Tim Walsh, acting GOES-R System Program director for NOAA, speaks to members of the media at a prelaunch news conference about National Oceanic and Atmospheric Administration's, or NOAA's, Geostationary Operational Environmental Satellite, or GOES-S. The GOES series of satellites will significantly improve the detection and observation of environmental phenomena that directly affect public safety, protection of property and the nation's economic health and prosperity. GOES-S is slated to lift off at 5:02 p.m. EST on March 1, 2018 aboard a United Launch Alliance Atlas V rocket.

Image navigation and registration for the geostationary lightning mapper (GLM)

NASA Astrophysics Data System (ADS)

van Bezooijen, Roel W. H.; Demroff, Howard; Burton, Gregory; Chu, Donald; Yang, Shu S.

2016-10-01

The Geostationary Lightning Mappers (GLM) for the Geostationary Operational Environmental Satellite (GOES) GOES-R series will, for the first time, provide hemispherical lightning information 24 hours a day from longitudes of 75 and 137 degrees west. The first GLM of a series of four is planned for launch in November, 2016. Observation of lightning patterns by GLM holds promise to improve tornado warning lead times to greater than 20 minutes while halving the present false alarm rates. In addition, GLM will improve airline traffic flow management, and provide climatology data allowing us to understand the Earth's evolving climate. The paper describes the method used for translating the pixel position of a lightning event to its corresponding geodetic longitude and latitude, using the J2000 attitude of the GLM mount frame reported by the spacecraft, the position of the spacecraft, and the alignment of the GLM coordinate frame relative to its mount frame. Because the latter alignment will experience seasonal variation, this alignment is determined daily using GLM background images collected over the previous 7 days. The process involves identification of coastlines in the background images and determination of the alignment change necessary to match the detected coastline with the coastline predicted using the GSHHS database. Registration is achieved using a variation of the Lucas-Kanade algorithm where we added a dither and average technique to improve performance significantly. An innovative water mask technique was conceived to enable self-contained detection of clear coastline sections usable for registration. Extensive simulations using accurate visible images from GOES13 and GOES15 have been used to demonstrate the performance of the coastline registration method, the results of which are presented in the paper.

Investigation of biomass burning and aerosol loading and transport in South America utilizing geostationary satellites

NASA Technical Reports Server (NTRS)

Menzel, Paul; Prins, Elaine

1995-01-01

This study attempts to assess the extent of burning and associated aerosol transport regimes in South America and the South Atlantic using geostationary satellite observations, in order to explore the possible roles of biomass burning in climate change and more directly in atmospheric chemistry and radiative transfer processes. Modeling and analysis efforts have suggested that the direct and indirect radiative effects of aerosols from biomass burning may play a major role in the radiative balance of the earth and are an important factor in climate change calculations. One of the most active regions of biomass burning is located in South America, associated with deforestation in the selva (forest), grassland management, and other agricultural practices. As part of the NASA Aerosol Interdisciplinary Program, we are utilizing GOES-7 (1988) and GOES-8 (1995) visible and multispectral infrared data (4, 11, and 12 microns) to document daily biomass burning activity in South America and to distinguish smoke/aerosols from other multi-level clouds and low-level moisture. This study catalogues the areal extent and transport of smoke/aerosols throughout the region and over the Atlantic Ocean for the 1988 (July-September) and 1995 (June-October) biomass burning seasons. The smoke/haze cover estimates are compared to the locations of fires to determine the source and verify the haze is actually associated with biomass burning activities. The temporal resolution of the GOES data (half-hourly in South America) makes it possible to determine the prevailing circulation and transport of aerosols by considering a series of visible and infrared images and tracking the motion of smoke, haze and adjacent clouds. The study area extends from 40 to 70 deg W and 0 to 40 deg S with aerosol coverage extending over the Atlantic Ocean when necessary. Fire activity is estimated with the GOES Automated Biomass Burning Algorithm (ABBA). To date, our efforts have focused on GOES-7 and GOES-8 ABBA development, algorithm development for aerosol monitoring, data acquisition and archiving, and participation in the SCAR-C and SCAR-B field programs which have provided valuable information for algorithm testing and validation. Implementation of the initial version of the GEOS-8 ABBA on case studies in North, Central, and South America has demonstrated the improved capability for monitoring diurnal fire activity and smoke/aerosol transport with the GOES-8 throughout the Western Hemisphere.

Improvements in Cloud Remote Sensing from Fusing VIIRS and CrIS data

NASA Astrophysics Data System (ADS)

Heidinger, A. K.; Walther, A.; Lindsey, D. T.; Li, Y.; NOH, Y. J.; Botambekov, D.; Miller, S. D.; Foster, M. J.

2016-12-01

In the fall of 2016, NOAA began the operational production of cloud products from the S-NPP Visible and Infrared Imaging Radiometer Suite (VIIRS) using the NOAA Enterprise Algorithms. VIIRS, while providing unprecedented spatial resolution and imaging clarity, does lack certain IR channels that are beneficial to cloud remote sensing. At the UW Space Science and Engineering Center (SSEC), tools were written to generate the missing IR channels from the Cross Track Infrared Sounder (CrIS) and to map them into the VIIRS swath. The NOAA Enterprise Algorithms are also implemented into the NESDIS CLAVR-x system. CLAVR-x has been modified to use the fused VIIRS and CrIS data. This presentation will highlight the benefits offered by the CrIS data to the NOAA Enterprise Algorithms. In addition, these benefits also have enabled the generation of 3D cloud retrievals to support the request from the National Weather Service (NWS) for a Cloud Cover Layers product. Lastly, the benefits of using VIIRS and CrIS for achieving consistency with GOES-R will also be demonstrated.

Sao Paulo Lightning Mapping Array (SP-LMA): Deployment and Plans

NASA Technical Reports Server (NTRS)

Bailey, J. C.; Carey, L. D.; Blakeslee, R. J.; Albrecht, R.; Morales, C. A.; Pinto, O., Jr.

2011-01-01

An 8-10 station Lightning Mapping Array (LMA) network is being deployed in the vicinity of Sao Paulo to create the SP-LMA for total lightning measurements in association with the international CHUVA [Cloud processes of tHe main precipitation systems in Brazil: A contribUtion to cloud resolVing modeling and to the GPM (GlobAl Precipitation Measurement)] field campaign. Besides supporting CHUVA science/mission objectives and the Sao Luz Paraitinga intensive operation period (IOP) in December 2011-January 2012, the SP-LMA will support the generation of unique proxy data for the Geostationary Lightning Mapper (GLM) and Advanced Baseline Imager (ABI), both sensors on the NOAA Geostationary Operational Environmental Satellite-R (GOES-R), presently under development and scheduled for a 2015 launch. The proxy data will be used to develop and validate operational algorithms so that they will be ready for use on "day1" following the launch of GOES-R. A preliminary survey of potential sites in the vicinity of Sao Paulo was conducted in December 2009 and January 2010, followed up by a detailed survey in July 2010, with initial network deployment scheduled for October 2010. However, due to a delay in the Sa Luz Paraitinga IOP, the SP-LMA will now be installed in July 2011 and operated for one year. Spacing between stations is on the order of 15-30 km, with the network "diameter" being on the order of 30-40 km, which provides good 3-D lightning mapping 150 km from the network center. Optionally, 1-3 additional stations may be deployed in the vicinity of Sa Jos dos Campos.

Sao Paulo Lightning Mapping Array (SP-LMA): Deployment, Operation and Initial Data Analysis

NASA Technical Reports Server (NTRS)

Blakeslee, R.; Bailey, J. C.; Carey, L. D.; Rudlosky, S.; Goodman, S. J.; Albrecht, R.; Morales, C. A.; Anseimo, E. M.; Pinto, O.

2012-01-01

An 8-10 station Lightning Mapping Array (LMA) network is being deployed in the vicinity of Sao Paulo to create the SP-LMA for total lightning measurements in association with the international CHUVA [Cloud processes of the main precipitation systems in Brazil: A contribution to cloud resolving modeling and to the GPM (Global Precipitation Measurement)] field campaign. Besides supporting CHUVA science/mission objectives and the Sao Luiz do Paraitinga intensive operation period (IOP) in November-December 2011, the SP-LMA will support the generation of unique proxy data for the Geostationary Lightning Mapper (GLM) and Advanced Baseline Imager (ABI), both sensors on the NOAA Geostationary Operational Environmental Satellite-R (GOES-R), presently under development and scheduled for a 2015 launch. The proxy data will be used to develop and validate operational algorithms so that they will be ready for use on "day1" following the launch of GOES-R. A preliminary survey of potential sites in the vicinity of Sao Paulo was conducted in December 2009 and January 2010, followed up by a detailed survey in July 2010, with initial network deployment scheduled for October 2010. However, due to a delay in the Sao Luiz do Paraitinga IOP, the SP-LMA will now be installed in July 2011 and operated for one year. Spacing between stations is on the order of 15-30 km, with the network "diameter" being on the order of 30-40 km, which provides good 3-D lightning mapping 150 km from the network center. Optionally, 1-3 additional stations may be deployed in the vicinity of Sao Jos dos Campos.

Correcting GOES-R Magnetometer Data for Stray Fields

NASA Technical Reports Server (NTRS)

Carter, Delano R.; Freesland, Douglas C.; Tadikonda, Sivakumara K.; Kronenwetter, Jeffrey; Todirita, Monica; Dahya, Melissa; Chu, Donald

2016-01-01

Time-varying spacecraft magnetic fields or stray fields are a problem for magnetometer systems. While constant fields can be removed with zero offset calibration, stray fields are difficult to distinguish from ambient field variations. Putting two magnetometers on a long boom and solving for both the ambient and stray fields can be a good idea, but this gradiometer solution is even more susceptible to noise than a single magnetometer. Unless the stray fields are larger than the magnetometer noise, simply averaging the two measurements is a more accurate approach. If averaging is used, it may be worthwhile to explicitly estimate and remove stray fields. Models and estimation algorithms are provided for solar array, arcjet and reaction wheel fields.

Comparison of GOES Cloud Classification Algorithms Employing Explicit and Implicit Physics

NASA Technical Reports Server (NTRS)

Bankert, Richard L.; Mitrescu, Cristian; Miller, Steven D.; Wade, Robert H.

2009-01-01

Cloud-type classification based on multispectral satellite imagery data has been widely researched and demonstrated to be useful for distinguishing a variety of classes using a wide range of methods. The research described here is a comparison of the classifier output from two very different algorithms applied to Geostationary Operational Environmental Satellite (GOES) data over the course of one year. The first algorithm employs spectral channel thresholding and additional physically based tests. The second algorithm was developed through a supervised learning method with characteristic features of expertly labeled image samples used as training data for a 1-nearest-neighbor classification. The latter's ability to identify classes is also based in physics, but those relationships are embedded implicitly within the algorithm. A pixel-to-pixel comparison analysis was done for hourly daytime scenes within a region in the northeastern Pacific Ocean. Considerable agreement was found in this analysis, with many of the mismatches or disagreements providing insight to the strengths and limitations of each classifier. Depending upon user needs, a rule-based or other postprocessing system that combines the output from the two algorithms could provide the most reliable cloud-type classification.

Evaluation of NASA SPoRT's Pseudo-Geostationary Lightning Mapper Products in the 2011 Spring Program

NASA Technical Reports Server (NTRS)

Stano, Geoffrey T.; Carcione, Brian; Siewert, Christopher; Kuhlman, Kristin M.

2012-01-01

NASA's Short-term Prediction Research and Transition (SPoRT) program is a contributing partner with the GOES-R Proving Ground (PG) preparing forecasters to understand and utilize the unique products that will be available in the GOES-R era. This presentation emphasizes SPoRT s actions to prepare the end user community for the Geostationary Lightning Mapper (GLM). This preparation is a collaborative effort with SPoRT's National Weather Service partners, the National Severe Storms Laboratory (NSSL), and the Hazardous Weather Testbed s Spring Program. SPoRT continues to use its effective paradigm of matching capabilities to forecast problems through collaborations with our end users and working with the developers at NSSL to create effective evaluations and visualizations. Furthermore, SPoRT continues to develop software plug-ins so that these products will be available to forecasters in their own decision support system, AWIPS and eventually AWIPS II. In 2009, the SPoRT program developed the original pseudo geostationary lightning mapper (PGLM) flash extent product to demonstrate what forecasters may see with GLM. The PGLM replaced the previous GLM product and serves as a stepping-stone until the AWG s official GLM proxy is ready. The PGLM algorithm is simple and can be applied to any ground-based total lightning network. For 2011, the PGLM used observations from four ground-based networks (North Alabama, Kennedy Space Center, Oklahoma, and Washington D.C.). While the PGLM is not a true proxy product, it is intended as a tool to train forecasters about total lightning as well as foster discussions on product visualizations and incorporating GLM-resolution data into forecast operations. The PGLM has been used in 2010 and 2011 and is likely to remain the primary lightning training tool for the GOES-R program for the near future. This presentation will emphasize the feedback received during the 2011 Spring Program. This will discuss several topics. Based on feedback from the 2010 Spring Program, SPoRT created two variant PGLM products, which NSSL produced locally and provided in real-time within AWIPS for 2011. The first is the flash initiation density (FID) product, which creates a gridded display showing the number of flashes that originated in each 8 8 km grid box. The second product is the maximum flash density (MFD). This shows the highest PGLM value for each grid point over a specific period of time, ranging from 30 to 120 minutes. In addition to the evaluation of these two new products, the evaluation of the PGLM itself will be covered. The presentation will conclude with forecaster feedback for additional improvements requested for future evaluations, such as within the 2012 Spring Program.

Use and Assessment of Multi-Spectral Satellite Imagery in NWS Operational Forecasting Environments

NASA Technical Reports Server (NTRS)

Molthan, Andrew; Fuell, Kevin; Stano, Geoffrey; McGrath, Kevin; Schultz, Lori; LeRoy, Anita

2015-01-01

NOAA's Satellite Proving Grounds have established partnerships between product developers and NWS WFOs for the evaluation of new capabilities from the GOES-R and JPSS satellite systems. SPoRT has partnered with various WFOs to evaluate multispectral (RGB) products from MODIS, VIIRS and Himawari/AHI to prepare for GOES-R/ABI. Assisted through partnerships with GINA, UW/CIMSS, NOAA, and NASA Direct Broadcast capabilities.

Initial design and performance of the near surface unmanned aircraft system sensor suite in support of the GOES-R field campaign

NASA Astrophysics Data System (ADS)

Pearlman, Aaron J.; Padula, Francis; Shao, Xi; Cao, Changyong; Goodman, Steven J.

2016-09-01

One of the main objectives of the Geostationary Operational Environmental Satellite R-Series (GOES-R) field campaign is to validate the SI traceability of the Advanced Baseline Imager. The campaign plans include a feasibility demonstration study for new near surface unmanned aircraft system (UAS) measurement capability that is being developed to meet the challenges of validating geostationary sensors. We report our progress in developing our initial systems by presenting the design and preliminary characterization results of the sensor suite. The design takes advantage of off-the-shelf technologies and fiber-based optical components to make hemispheric directional measurements from a UAS. The characterization results - including laboratory measurements of temperature effects and polarization sensitivity - are used to refine the radiometric uncertainty budget towards meeting the validation objectives for the campaign. These systems will foster improved validation capabilities for the GOES-R field campaign and other next generation satellite systems.

The Geostationary Operational Environmental Satellite (GOES) Product Generation System

NASA Technical Reports Server (NTRS)

Haines, S. L.; Suggs, R. J.; Jedlovec, G. J.

2004-01-01

The Geostationary Operational Environmental Satellite (GOES) Product Generation System (GPGS) is introduced and described. GPGS is a set of computer programs developed and maintained at the Global Hydrology and Climate Center and is designed to generate meteorological data products using visible and infrared measurements from the GOES-East Imager and Sounder instruments. The products that are produced by GPGS are skin temperature, total precipitable water, cloud top pressure, cloud albedo, surface albedo, and surface insolation. A robust cloud mask is also generated. The retrieval methodology for each product is described to include algorithm descriptions and required inputs and outputs for the programs. Validation is supplied where applicable.

GOES-16 On-Orbit Dual Isolation Performance Characterization Results

NASA Technical Reports Server (NTRS)

Carter, Delano; Clapp, Brian; Early, Derrick; Freesland, Douglas; Chapel, Jim; Bailey, Robert; Krimchansky, Alexander

2016-01-01

The Geostationary Operational Environmental Satellite-R Series (GOES-R) is the first of the next generation geostationary weather satellites. GOES-R successfully launched on November19, 2016 and renamed GOES-16 upon entering geostationary orbit. Subsequently, GOES-16post-launch testing began. This paper presents the GOES-16 Satellite Dynamic Interaction Characterization results for the Earth Pointed Platform (EPP) stowed, referred to as the Reaction Wheel Assembly (RWA) Isolation Only configuration, and deployed, referred to as the Dual Isolation configuration. GOES-R represents a quantum increase in Earth and solar weather observation capabilities, with 4 times the resolution, 5 times the observation rate, and 3 times the number of spectral bands for Earth observations. With the improved resolution, comes the instrument suites increased sensitivity to disturbances over a broad spectrum 0-512Hz. Sources of disturbance include reaction wheels, thruster firings for station keeping and momentum management, gimbal motion, and internal instrument disturbances. To minimize the impact of these disturbances, the baseline design included an EPP, a stiff optical bench to which the two nadir pointed instruments are collocated together with the Guidance Navigation Control (GNC) star trackers and Inertial Measurement Units (IMUs). The EPP is passively isolated from the spacecraft bus with Honeywell D-Strut isolators providing attenuation for frequencies above 5 Hz in all six degrees-of-freedom. To reduce the risk of wheel disturbances impacting performance, a secondary passive isolation system manufactured by Moog CSA Engineering was incorporated under each of the six 160 Nms reaction wheels, tuned to provide attenuation at frequencies above 50 Hz. Integrated wheel and isolator testing was performed on a Kistler table at NASA Goddard Space Flight Center. Pre-launch Satellite Dynamic Interaction Characterization high-fidelity simulations and ground testing were conducted to evaluate jitter performance for two cases: 1) deployed EPP and reaction wheel (Dual Isolation) and 2) EPP hard mounted (RWA Isolation Only) to the spacecraft. A comparison of pre-launch to post-launch Satellite Dynamic Interaction Characterization results are also presented in this paper.

GOES-S Prelaunch News Conference

NASA Image and Video Library

2018-02-27

GOES-S Prelaunch News Conference hosted by NASA Communications' Tori Mclendon, with Stephen Volz, Director for Satellite and Information Services, NOAA; Tim Walsh, GOES-R system program director (acting), NOAA; Sandra Smalley, Director, NASA Joint Agency Satellite Division; Tim Dunn, NASA Launch Director, Kennedy Space Center, Florida; Scott Messer, Program Manager, NASA Missions, United Launch Alliance; and Kathy Winters, Launch Weather Officer, 45th Weather Squadron, Cape Canaveral Air Force Station, Florida.

Obtaining the Grobner Initialization for the Ground Flash Fraction Retrieval Algorithm

NASA Technical Reports Server (NTRS)

Solakiewicz, R.; Attele, R.; Koshak, W.

2011-01-01

At optical wavelengths and from the vantage point of space, the multiple scattering cloud medium obscures one's view and prevents one from easily determining what flashes strike the ground. However, recent investigations have made some progress examining the (easier, but still difficult) problem of estimating the ground flash fraction in a set of N flashes observed from space In the study by Koshak, a Bayesian inversion method was introduced for retrieving the fraction of ground flashes in a set of flashes observed from a (low earth orbiting or geostationary) satellite lightning imager. The method employed a constrained mixed exponential distribution model to describe the lightning optical measurements. To obtain the optimum model parameters, a scalar function of three variables (one of which is the ground flash fraction) was minimized by a numerical method. This method has formed the basis of a Ground Flash Fraction Retrieval Algorithm (GoFFRA) that is being tested as part of GOES-R GLM risk reduction.

Near-Real Time Cloud Retrievals from Operational and Research Meteorological Satellites

NASA Technical Reports Server (NTRS)

Minnis, Patrick; Nguyen, Louis; Palilonda, Rabindra; Heck, Patrick W.; Spangenberg, Douglas A.; Doelling, David R.; Ayers, J. Kirk; Smith, William L., Jr.; Khaiyer, Mandana M.; Trepte, Qing Z.;

Automated identification of basalt spectra in Clementine lunar data

NASA Astrophysics Data System (ADS)

Antonenko, I.; Osinski, G. R.

2011-06-01

The identification of fresh basalt spectra plays an important role in lunar stratigraphic studies; however, the process can be time consuming and labor intensive. Thus motivated, we developed an empirically derived algorithm for the automated identification of fresh basalt spectra from Clememtine UVVIS data. This algorithm has the following four parameters and limits: BC Ratio=3(R950-R900)/(R900-R750)<1.1, CD Delta=(R1000-R950)/R750-1.09(R950-R900)/R750>0.003 and <0.06, B Slope=(R900-R750)/(3R750)<-0.012, and Band Depth=(R750-R950)/(R750-R415)>0.1, where R750 represents the unnormalized reflectance of the 750 nm Clementine band, and so on. Algorithm results were found to be accurate to within an error of 4.5% with respect to visual classification, though olivine spectra may be under-represented. Overall, fresh basalts identified by the algorithm are consistent with expectations and previous work in the Mare Humorum area, though accuracy in other areas has not yet been tested. Great potential exists in using this algorithm for identifying craters that have excavated basalts, estimating the thickness of mare and cryptomare deposits, and other applications.

GOES-R STATIONKEEPING AND MOMENTUM MANAGEMENT

NASA Technical Reports Server (NTRS)

Chu, Donald; Chen, Sam; Early, Derrick; Freesland, Doug; Krimchansky, Alexander; Naasz, Bo; Reth, Alan; Tadikonda, Kumar; Tsui, John; Walsh, Tim

2006-01-01

The NOAA Geostationary Operational Environmental Satellites (GOES) fire thrusters to remain within a 1deg longitude-latitude box and to dump accumulated angular momentum. In the past, maneuvers have disrupted GOES imaging due to attitude transients and the loss of orbit knowledge. If the R-series of spacecraft to be launched starting in 2012 were to follow current practice, maneuvers would still fail to meet Image Navigation and Registration (INR) specifications during and after thruster firings. Although maneuvers and recovery take only one percent of spacecraft lifetime, they sometimes come at inopportune times, such as hurricane season, when coverage is critical. To alleviate this problem, thruster firings small enough not to affect imaging are being considered. Eliminating post-maneuver recovery periods increases availability and facilitates autonomous operation. Frequent maneuvers also reduce 1ongitudeAatitude variation and allow satellite co-location. Improved orbit observations come from a high-altitude GPS receiver, and improved attitude control comes from thruster torque compensation. This paper reviews the effects of thruster firings on position knowledge and pointing control and suggests that low-thrust burns plus GPS and feedforward control offer a less disruptive approach to GOES-R stationkeeping and momentum management.

Automated Storm Tracking and the Lightning Jump Algorithm Using GOES-R Geostationary Lightning Mapper (GLM) Proxy Data.

PubMed

Schultz, Elise V; Schultz, Christopher J; Carey, Lawrence D; Cecil, Daniel J; Bateman, Monte

2016-01-01

This study develops a fully automated lightning jump system encompassing objective storm tracking, Geostationary Lightning Mapper proxy data, and the lightning jump algorithm (LJA), which are important elements in the transition of the LJA concept from a research to an operational based algorithm. Storm cluster tracking is based on a product created from the combination of a radar parameter (vertically integrated liquid, VIL), and lightning information (flash rate density). Evaluations showed that the spatial scale of tracked features or storm clusters had a large impact on the lightning jump system performance, where increasing spatial scale size resulted in decreased dynamic range of the system's performance. This framework will also serve as a means to refine the LJA itself to enhance its operational applicability. Parameters within the system are isolated and the system's performance is evaluated with adjustments to parameter sensitivity. The system's performance is evaluated using the probability of detection (POD) and false alarm ratio (FAR) statistics. Of the algorithm parameters tested, sigma-level (metric of lightning jump strength) and flash rate threshold influenced the system's performance the most. Finally, verification methodologies are investigated. It is discovered that minor changes in verification methodology can dramatically impact the evaluation of the lightning jump system.

Automated Storm Tracking and the Lightning Jump Algorithm Using GOES-R Geostationary Lightning Mapper (GLM) Proxy Data

NASA Technical Reports Server (NTRS)

Schultz, Elise; Schultz, Christopher Joseph; Carey, Lawrence D.; Cecil, Daniel J.; Bateman, Monte

2016-01-01

This study develops a fully automated lightning jump system encompassing objective storm tracking, Geostationary Lightning Mapper proxy data, and the lightning jump algorithm (LJA), which are important elements in the transition of the LJA concept from a research to an operational based algorithm. Storm cluster tracking is based on a product created from the combination of a radar parameter (vertically integrated liquid, VIL), and lightning information (flash rate density). Evaluations showed that the spatial scale of tracked features or storm clusters had a large impact on the lightning jump system performance, where increasing spatial scale size resulted in decreased dynamic range of the system's performance. This framework will also serve as a means to refine the LJA itself to enhance its operational applicability. Parameters within the system are isolated and the system's performance is evaluated with adjustments to parameter sensitivity. The system's performance is evaluated using the probability of detection (POD) and false alarm ratio (FAR) statistics. Of the algorithm parameters tested, sigma-level (metric of lightning jump strength) and flash rate threshold influenced the system's performance the most. Finally, verification methodologies are investigated. It is discovered that minor changes in verification methodology can dramatically impact the evaluation of the lightning jump system.

Automated Storm Tracking and the Lightning Jump Algorithm Using GOES-R Geostationary Lightning Mapper (GLM) Proxy Data

PubMed Central

SCHULTZ, ELISE V.; SCHULTZ, CHRISTOPHER J.; CAREY, LAWRENCE D.; CECIL, DANIEL J.; BATEMAN, MONTE

2017-01-01

This study develops a fully automated lightning jump system encompassing objective storm tracking, Geostationary Lightning Mapper proxy data, and the lightning jump algorithm (LJA), which are important elements in the transition of the LJA concept from a research to an operational based algorithm. Storm cluster tracking is based on a product created from the combination of a radar parameter (vertically integrated liquid, VIL), and lightning information (flash rate density). Evaluations showed that the spatial scale of tracked features or storm clusters had a large impact on the lightning jump system performance, where increasing spatial scale size resulted in decreased dynamic range of the system’s performance. This framework will also serve as a means to refine the LJA itself to enhance its operational applicability. Parameters within the system are isolated and the system’s performance is evaluated with adjustments to parameter sensitivity. The system’s performance is evaluated using the probability of detection (POD) and false alarm ratio (FAR) statistics. Of the algorithm parameters tested, sigma-level (metric of lightning jump strength) and flash rate threshold influenced the system’s performance the most. Finally, verification methodologies are investigated. It is discovered that minor changes in verification methodology can dramatically impact the evaluation of the lightning jump system. PMID:29303164

Scan-Line Methods in Spatial Data Systems

DTIC Science & Technology

1990-09-04

algorithms in detail to show some of the implementation issues. Data Compression Storage and transmission times can be reduced by using compression ...goes through the data . Luckily, there are good one-directional compression algorithms , such as run-length coding 13 in which each scan line can be...independently compressed . These are the algorithms to use in a parallel scan-line system. Data compression is usually only used for long-term storage of

The Incremental Multiresolution Matrix Factorization Algorithm

PubMed Central

Ithapu, Vamsi K.; Kondor, Risi; Johnson, Sterling C.; Singh, Vikas

2017-01-01

Multiresolution analysis and matrix factorization are foundational tools in computer vision. In this work, we study the interface between these two distinct topics and obtain techniques to uncover hierarchical block structure in symmetric matrices – an important aspect in the success of many vision problems. Our new algorithm, the incremental multiresolution matrix factorization, uncovers such structure one feature at a time, and hence scales well to large matrices. We describe how this multiscale analysis goes much farther than what a direct “global” factorization of the data can identify. We evaluate the efficacy of the resulting factorizations for relative leveraging within regression tasks using medical imaging data. We also use the factorization on representations learned by popular deep networks, providing evidence of their ability to infer semantic relationships even when they are not explicitly trained to do so. We show that this algorithm can be used as an exploratory tool to improve the network architecture, and within numerous other settings in vision. PMID:29416293

GLM Post Launch Testing and Airborne Science Field Campaign

NASA Astrophysics Data System (ADS)

Goodman, S. J.; Padula, F.; Koshak, W. J.; Blakeslee, R. J.

2017-12-01

The Geostationary Operational Environmental Satellite (GOES-R) series provides the continuity for the existing GOES system currently operating over the Western Hemisphere. The Geostationary Lightning Mapper (GLM) is a wholly new instrument that provides a capability for total lightning detection (cloud and cloud-to-ground flashes). The first satellite in the GOES-R series, now GOES-16, was launched in November 2016 followed by in-orbit post launch testing for approximately 12 months before being placed into operations replacing the GOES-E satellite in December. The GLM will map total lightning continuously throughout day and night with near-uniform spatial resolution of 8 km with a product latency of less than 20 sec over the Americas and adjacent oceanic regions. The total lightning is very useful for identifying hazardous and severe thunderstorms, monitoring storm intensification and tracking evolution. Used in tandem with radar, satellite imagery, and surface observations, total lightning data has great potential to increase lead time for severe storm warnings, improve aviation safety and efficiency, and increase public safety. In this paper we present initial results from the post-launch in-orbit performance testing, airborne science field campaign conducted March-May, 2017 and assessments of the GLM instrument and science products.

Operational algorithm development and refinement approaches

NASA Astrophysics Data System (ADS)

Ardanuy, Philip E.

2003-11-01

Next-generation polar and geostationary systems, such as the National Polar-orbiting Operational Environmental Satellite System (NPOESS) and the Geostationary Operational Environmental Satellite (GOES)-R, will deploy new generations of electro-optical reflective and emissive capabilities. These will include low-radiometric-noise, improved spatial resolution multi-spectral and hyperspectral imagers and sounders. To achieve specified performances (e.g., measurement accuracy, precision, uncertainty, and stability), and best utilize the advanced space-borne sensing capabilities, a new generation of retrieval algorithms will be implemented. In most cases, these advanced algorithms benefit from ongoing testing and validation using heritage research mission algorithms and data [e.g., the Earth Observing System (EOS)] Moderate-resolution Imaging Spectroradiometer (MODIS) and Shuttle Ozone Limb Scattering Experiment (SOLSE)/Limb Ozone Retreival Experiment (LORE). In these instances, an algorithm's theoretical basis is not static, but rather improves with time. Once frozen, an operational algorithm can "lose ground" relative to research analogs. Cost/benefit analyses provide a basis for change management. The challenge is in reconciling and balancing the stability, and "comfort," that today"s generation of operational platforms provide (well-characterized, known, sensors and algorithms) with the greatly improved quality, opportunities, and risks, that the next generation of operational sensors and algorithms offer. By using the best practices and lessons learned from heritage/groundbreaking activities, it is possible to implement an agile process that enables change, while managing change. This approach combines a "known-risk" frozen baseline with preset completion schedules with insertion opportunities for algorithm advances as ongoing validation activities identify and repair areas of weak performance. This paper describes an objective, adaptive implementation roadmap that takes into account the specific maturities of each system"s (sensor and algorithm) technology to provide for a program that contains continuous improvement while retaining its manageability.

Algorithms and the Future of Music Education: A Response to Shuler

ERIC Educational Resources Information Center

Thibeault, Matthew D.

2014-01-01

This article is a response to Shuler's 2001 article predicting the future of music education. The respondent assesses Shuler's predictions, finding that many have come true but critiquing Shuler's overall positive assessment. The respondent then goes on to make one prediction about the future of music education: that algorithms will…

Optimizing the real-time ground level enhancement alert system based on neutron monitor measurements: Introducing GLE Alert Plus

NASA Astrophysics Data System (ADS)

Souvatzoglou, G.; Papaioannou, A.; Mavromichalaki, H.; Dimitroulakos, J.; Sarlanis, C.

2014-11-01

Whenever a significant intensity increase is being recorded by at least three neutron monitor stations in real-time mode, a ground level enhancement (GLE) event is marked and an automated alert is issued. Although, the physical concept of the algorithm is solid and has efficiently worked in a number of cases, the availability of real-time data is still an open issue and makes timely GLE alerts quite challenging. In this work we present the optimization of the GLE alert that has been set into operation since 2006 at the Athens Neutron Monitor Station. This upgrade has led to GLE Alert Plus, which is currently based upon the Neutron Monitor Database (NMDB). We have determined the critical values per station allowing us to issue reliable GLE alerts close to the initiation of the event while at the same time we keep the false alert rate at low levels. Furthermore, we have managed to treat the problem of data availability, introducing the Go-Back-N algorithm. A total of 13 GLE events have been marked from January 2000 to December 2012. GLE Alert Plus issued an alert for 12 events. These alert times are compared to the alert times of GOES Space Weather Prediction Center and Solar Energetic Particle forecaster of the University of Málaga (UMASEP). In all cases GLE Alert Plus precedes the GOES alert by ≈8-52 min. The comparison with UMASEP demonstrated a remarkably good agreement. Real-time GLE alerts by GLE Alert Plus may be retrieved by http://cosray.phys.uoa.gr/gle_alert_plus.html, http://www.nmdb.eu, and http://swe.ssa.esa.int/web/guest/space-radiation. An automated GLE alert email notification system is also available to interested users.

GOES-S NASA Social

NASA Image and Video Library

2018-02-28

Tim Walsh, GOES-R System Program director for the National Oceanic and Atmospheric Administration, or NOAA, speaks to members of social media in the Kennedy Space Center’s Press Site auditorium. The briefing focused on the Geostationary Operational Environmental Satellite, or GOES-S, the second spacecraft in a series of next-generation NOAA weather satellites. It will launch to a geostationary position over the U.S. to provide images of storms and help predict weather forecasts, severe weather outlooks, watches, warnings, lightning conditions and longer-term forecasting. GOES-S is slated to lift off at 5:02 p.m. EST on March 1, 2018 aboard a United Launch Alliance Atlas V rocket.

GOES-S Mission Science Briefing

NASA Image and Video Library

2018-02-27

In the Kennedy Space Center's Press Site auditorium, Dan Lindsey, GOES-R senior scientific advisor for NOAA, speaks to members of the media at a mission briefing on National Oceanic and Atmospheric Administration's, or NOAA's, Geostationary Operational Environmental Satellite, or GOES-S. The spacecraft is the second satellite in a series of next-generation NOAA weather satellites. It will launch to a geostationary position over the U.S. to provide images of storms and help predict weather forecasts, severe weather outlooks, watches, warnings, lightning conditions and longer-term forecasting. GOES-S is slated to lift off at 5:02 p.m. EST on March 1, 2018 aboard a United Launch Alliance Atlas V rocket.

Improvements to GOES Twilight Cloud Detection over the ARM SGP

NASA Technical Reports Server (NTRS)

Yost, c. R.; Trepte, Q.; Khaiyer, M. M.; Palikonda, R.; Nguyen, L.

2007-01-01

The current ARM satellite cloud products derived from Geostationary Operational Environmental Satellite (GOES) data provide continuous coverage of many cloud properties over the ARM Southern Great Plains domain. However, discontinuities occur during daylight near the terminator, a time period referred to here as twilight. This poster presentation will demonstrate the improvements in cloud detection provided by the improved cloud mask algorithm as well as validation of retrieved cloud properties using surface observations from the Atmospheric Radiation Measurement Southern Great Plains (ARM SGP) site.

Merging thermal and microwave satellite observations for a high-resolution soil moisture data product

USDA-ARS?s Scientific Manuscript database

Many societal applications of soil moisture data products require high spatial resolution and numerical accuracy. Current thermal geostationary satellite sensors (GOES Imager and GOES-R ABI) could produce 2-16km resolution soil moisture proxy data. Passive microwave satellite radiometers (e.g. AMSR...

GEONEX: algorithm development and validation of Gross Primary Production from geostationary satellites

NASA Astrophysics Data System (ADS)

Hashimoto, H.; Wang, W.; Ganguly, S.; Li, S.; Michaelis, A.; Higuchi, A.; Takenaka, H.; Nemani, R. R.

2017-12-01

New geostationary sensors such as the AHI (Advanced Himawari Imager on Himawari-8) and the ABI (Advanced Baseline Imager on GOES-16) have the potential to advance ecosystem modeling particularly of diurnally varying phenomenon through frequent observations. These sensors have similar channels as in MODIS (MODerate resolution Imaging Spectroradiometer), and allow us to utilize the knowledge and experience in MODIS data processing. Here, we developed sub-hourly Gross Primary Production (GPP) algorithm, leverating the MODIS 17 GPP algorithm. We run the model at 1-km resolution over Japan and Australia using geo-corrected AHI data. Solar radiation was directly calculated from AHI using a neural network technique. The other necessary climate data were derived from weather stations and other satellite data. The sub-hourly estimates of GPP were first compared with ground-measured GPP at various Fluxnet sites. We also compared the AHI GPP with MODIS 17 GPP, and analyzed the differences in spatial patterns and the effect of diurnal changes in climate forcing. The sub-hourly GPP products require massive storage and strong computational power. We use NEX (NASA Earth Exchange) facility to produce the GPP products. This GPP algorithm can be applied to other geostationary satellites including GOES-16 in future.

Matrix Models and A Proof of the Open Analog of Witten's Conjecture

NASA Astrophysics Data System (ADS)

Buryak, Alexandr; Tessler, Ran J.

2017-08-01

In a recent work, R. Pandharipande, J. P. Solomon and the second author have initiated a study of the intersection theory on the moduli space of Riemann surfaces with boundary. They conjectured that the generating series of the intersection numbers satisfies the open KdV equations. In this paper we prove this conjecture. Our proof goes through a matrix model and is based on a Kontsevich type combinatorial formula for the intersection numbers that was found by the second author.

Rack Insertion End Effector (RIEE) guidance

NASA Technical Reports Server (NTRS)

Malladi, Narasimha S.

1994-01-01

NASA-KSC has developed a mechanism to handle and insert Racks into the Space Station Logistic Modules. This mechanism consists of a Base with 3 motorized degrees of freedom, a 3 section motorized Boom that goes from 15 to 44 feet in length, and a Rack Insertion End Effector (RIEE) with 5 hand wheels for precise alignment. During the 1993 NASA-ASEE Summer Faculty Fellowship Program at KSC, I designed an Active Vision (Camera) Arrangement and developed an algorithm to determine (1) the displacements required by the Room for its initial positioning and (2) the rotations required at the five hand-wheels of the RIEE, for the insertion of the Rack, using the centroids fo the Camera Images of the Location Targets in the Logistic Module. Presently, during the summer of '94, I completed the preliminary design of an easily portable measuring instrument using encoders to obtain the 3-Dimensional Coordinates of Location Targets in the Logistics Module relative to the RIEE mechanism frame. The algorithm developed in '93 can use the output of this instrument also. Simplification of the '93 work and suggestions for the future work are discussed.

Hands-on Activities Designed to Familiarize Users with Data from ABI on GOES-R and AHI on Himawari-8

NASA Astrophysics Data System (ADS)

Lindstrom, S. S.; Schmit, T.; Gerth, J.; Gunshor, M. M.; Mooney, M. E.; Whittaker, T. M.

2016-12-01

Recent and ongoing launches of next-generation geostationary satellites offer a challenge to familiarize National Weather Service (and other) forecasters with the new capabilities of different spectral channels sensed by the Advanced Baseline Imager (ABI) on GOES-R and the Advanced Himawari Imager (AHI) on Himawari-8. Hands on HTML5-based applets developed at the Cooperative Institute for Meteorological Satellite Studies allow for quick comparisons of reflectance in the visible (0.4 to 0.7 um) and near-infrared channels (0.86 to 2.2 um) and brightness temperatures in the infrared (3.9 to 13.3 um). The web apps to explore the different channels on ABI and AHI are at http://cimss.ssec.wisc.edu/goes/webapps/bandapp/; those that offer guidance on how to produce Red/Green/Blue composites are at http://cimss.ssec.wisc.edu/goes/webapps/satrgb/overview.html. This talk will briefly discuss highlights from both websites, and suggest ways the applications can be used to educate forecasters and the general public.

New Energetic Particle Data and Products from the GOES Program

NASA Astrophysics Data System (ADS)

Onsager, Terrance; Rodriguez, Juan

The NOAA Geostationary Operational Environmental Satellite (GOES) program has provided continuous, real-time measurements of the near-Earth space environment for decades. In addition to their scientific value, the GOES energetic particle measurements are the basis for a variety of space weather products and services, including the forecasting of elevated energetic particle levels, real-time knowledge of the satellite environment at geostationary orbit, and data to allow post-event analyses when satellite anomalies occur. The GOES satellites have traditionally provided measurements of high-energy electrons, protons, and alpha particles (100s of keV to 100s of MeV). Beginning with the launch of GOES-13 in 2006, the measurement capabilities were expanded to include medium-energy electrons and protons (10s to 100s of keV) with pitch angle resolution. The next generation of GOES satellites, starting with GOES-R in 2016, will include low-energy electrons and ions (10s of eV to 10s of keV) as well as energetic heavy ions. In this presentation, we will overview the GOES particle measurements available now and in the future and describe the space weather services and scientific investigations that these data support.

An iPhone Game with GOES-R Insight

NASA Astrophysics Data System (ADS)

Fitzpatrick, A. J.; Fisher, D. K.; Leon, N.; Space Place Team

2011-12-01

Our team developed a game, "Satellite Insight," for iPhone, iPod, or iPad. The game highlights the environmental and weather data-gathering potential of the next generation GOES-R satellite. We aimed to create a game that would have educational value, feature a real NOAA mission, and increase awareness of the GOES satellites and especially of the societal benefits deriving from this next generation of technology. We also wanted to reach a different, broader audience of a wider age range than we normally target with our NASA (spaceplace.nasa.gov) and NOAA (scijinks.gov) websites for kids. Oh . . . and we wanted the game to be fun. Although we had developed many fun and educational Flash games hosted on our Space Place and SciJinks Weather Laboratory websites for kids, developing an iOS game presented some different challenges: (1) players are usually interested in playing only very short games, under two minutes; (2) we wanted the game to appeal to a range of ages; and (3) the small touch screen requires a totally different type of interface design. The game is about gathering and storing different types of data collected by GOES-R, with the data rate increasing rapidly while you try to keep up. Six different types (colors, with different symbols) of tiles drop down from the top of a grid and collect in the columns. Touch any block that is in a group of three or more like blocks, then touch the GOES-R satellite icon below the grid to "save" the data and clear the selected blocks off the grid. If more than two columns completely fill up, the game is over. The "data rate" speeds up quickly, making it more challenging to keep the grid from overflowing. "Power-up" symbols appear periodically, which, when touched, do helpful things, such as clear out your tallest column. Players try to beat their own best "survival" time. The first lesson we learned in developing this game was to make sure the game play concept was simple and feasible to implement. Our first idea, in which the player combined raw data types to create processed GOES-R data products, turned out to require human invention of each and every game scenario. It would have been way too labor intensive to create enough of them to keep the game interesting. The second lesson we learned was the need to simplify the science. We had to come up with a much simplified set of data to represent the numerous and sophisticated data types collected by GOES-R's six major instruments. The third lesson was that the interface must take into account that the user's two thumbs cover about 25% of the screen, thus elements must placed and spaced accordingly. And the fourth lesson was that game behavior may need to be modified or enhanced (with "power-ups" and rate adjustments, for example) to make the game fun.

Characterization of mesoscale convective systems over the eastern Pacific during boreal summer

NASA Astrophysics Data System (ADS)

Berthet, Sarah; Rouquié, Bastien; Roca, Rémy

2015-04-01

The eastern Pacific Ocean is one of the most active tropical disturbances formation regions on earth. This preliminary study is part of a broader project that aims to investigate how mesoscale convective systems (MCS) may be related to these synoptic disturbances with emphasis on local initiation of tropical depressions. As a first step, the main characteristics of the MCS over the eastern Pacific are documented with the help of the recently developed TOOCAN tracking algorithm (Fiolleau and Roca, 2013) applied to the infrared satellite imagery data from GOES-W and -E for the period JJAS 2012-2014. More specifically, the spatial distribution of the MCS population, the statistics of their spatial extensions and durations, as well as their trajectories and propagation speeds are summarized. In addition the environment of the MCS will be investigated using various Global Precipitation Mission datasets and the Megha-Tropiques/SAPHIR humidity microwave sounder derived products. Reference: Fiolleau T. and R. Roca, (2013), An Algorithm For The Detection And Tracking Of Tropical Mesoscale Convective Systems Using Infrared Images From Geostationary Satellite, Transactions on Geoscience and Remote Sensing, doi: 10.1109/TGRS.2012.2227762.

Evaluation of an Area-Based matching algorithm with advanced shape models

NASA Astrophysics Data System (ADS)

Re, C.; Roncella, R.; Forlani, G.; Cremonese, G.; Naletto, G.

2014-04-01

Nowadays, the scientific institutions involved in planetary mapping are working on new strategies to produce accurate high resolution DTMs from space images at planetary scale, usually dealing with extremely large data volumes. From a methodological point of view, despite the introduction of a series of new algorithms for image matching (e.g. the Semi Global Matching) that yield superior results (especially because they produce usually smooth and continuous surfaces) with lower processing times, the preference in this field still goes to well established area-based matching techniques. Many efforts are consequently directed to improve each phase of the photogrammetric process, from image pre-processing to DTM interpolation. In this context, the Dense Matcher software (DM) developed at the University of Parma has been recently optimized to cope with very high resolution images provided by the most recent missions (LROC NAC and HiRISE) focusing the efforts mainly to the improvement of the correlation phase and the process automation. Important changes have been made to the correlation algorithm, still maintaining its high performance in terms of precision and accuracy, by implementing an advanced version of the Least Squares Matching (LSM) algorithm. In particular, an iterative algorithm has been developed to adapt the geometric transformation in image resampling using different shape functions as originally proposed by other authors in different applications.

Numerical Calculation of the Propagation of Spatial Coherence from Partially Coherent Sources.

DTIC Science & Technology

1982-10-01

can determine appropriate wj, aj, and n such that, for a given error e, I ° - 2~ jI "ja(E -E2) j Wj GoE1P -21,aj) < C,4 where x <a .(x,a) (5) 10 x > a...Since the major work in evaluating the integrand of JI (PI is in evaluating J[Efla(P2)], it is natural to express the integral in polar coordinates...The last step follows from observing that since OR w, OR 0’ < 2w- (OR + e’)- (4) eR e,0 < 0, eR + 61 >W The integration is treated as follows: JOR

Development and Applications of the GOES Sounder Products

NASA Astrophysics Data System (ADS)

Li, Jun; Menzel, W. P.; Li, Z.; Wade, G.; Schmit, T. J.; Li, J. L.; Aune, R.; Schreiner, A. J.; Schmidt, C. C.; Genkova, I.

Since 1994 a new generation of Geostationary Operational Environmental Satellite GOES Sounders GOES-8 9 10 11 12 has been measuring radiances in 18 infrared spectral bands ranging from approximately 3 7um - 14 7 um This data has been used to provide atmospheric sounding and cloud products for meteorological applications on an hourly basis over North America and adjacent oceanic regions The products include atmospheric temperature and moisture profiles total precipitable water cloud-top pressure water-vapor tracked winds etc Products are generated operationally by NOAA NESDIS in Washington D C Some Sounder products including total column ozone are also produced at the Cooperative Institute for Meteorological Satellite Studies at the University of Wisconsin-Madison Applications of those products include nowcasting and forecasting of weather events assimilation of cloud products into regional numerical forecast models and monitoring of temperature and moisture changes during active convective periods The impact of GOES Sounder products on numerical model forecasts will be demonstrated Furthermore recent improvements to several of the products have been made by taking into account the GOES Sounder temporal and spatial information within the processing algorithms These improvements and implications thereof will be presented and discussed

Fire Monitoring from the New Generation of US Polar and Geostationary Satellites

NASA Astrophysics Data System (ADS)

Csiszar, I.; Justice, C. O.; Prins, E.; Schroeder, W.; Schmidt, C.; Giglio, L.

2012-04-01

Sensors on the new generation of US operational environmental satellites will provide measurements suitable for active fire detection and characterization. The NPOESS Preparatory Project (NPP) satellite, launched on October 28, 2011, carries the Visible Infrared Imager Radiometer Suite (VIIRS), which is expected to continue the active fire data record from the Moderate Resolution Imaging Spectroradiometer (MODIS) on the NASA Earth Observing System Terra and Aqua Satellites. Early evaluation of the VIIRS active fire product, including comparison to near-simultaneous MODIS data, is underway. The new generation of Geostationary Operational Environmental Satellite (GOES) series, starting with GOES-R to be launched in 2015, will carry the Advanced Baseline Imager (ABI), providing higher spatial and temporal resolution than the current GOES imager. The ABI will also include a dedicated band to provide radiance observations over a wider dynamic range to detect and characterize hot targets. In this presentation we discuss details of the monitoring capabilities from both VIIRS and ABI and the current status of the corresponding algorithm development and testing efforts. An integral part of this activity is explicit product validation, utilizing high resolution satellite and airborne imagery as reference data. The new capabilities also represent challenges to establish continuity with data records from heritage missions, and to coordinate compatible international missions towards a global multi-platform fire monitoring system. These objectives are pursued by the Fire Mapping and Monitoring Implementation Team of the Global Observation of Forest and Land Cover Dynamics (GOFC-GOLD) program, which also provides coordinated contribution to relevant initiatives by the Committee on Earth Observation Satellites (CEOS), the Coordination Group for Meteorological Satellites (CGMS) and the Global Climate Observing System (GCOS).

Use of GOES, SSM/I, TRMM Satellite Measurements Estimating Water Budget Variations in Gulf of Mexico - Caribbean Sea Basins

NASA Technical Reports Server (NTRS)

Smith, Eric A.

2004-01-01

This study presents results from a multi-satellite/multi-sensor retrieval system designed to obtain the atmospheric water budget over the open ocean. A combination of 3ourly-sampled monthly datasets derived from the GOES-8 5-channel Imager, the TRMM TMI radiometer, and the DMSP 7-channel passive microwave radiometers (SSM/I) have been acquired for the combined Gulf of Mexico-Caribbean Sea basin. Whereas the methodology has been tested over this basin, the retrieval system is designed for portability to any open-ocean region. Algorithm modules using the different datasets to retrieve individual geophysical parameters needed in the water budget equation are designed in a manner that takes advantage of the high temporal resolution of the GOES-8 measurements, as well as the physical relationships inherent to the TRMM and SSM/I passive microwave measurements in conjunction with water vapor, cloud liquid water, and rainfall. The methodology consists of retrieving the precipitation, surface evaporation, and vapor-cloud water storage terms in the atmospheric water balance equation from satellite techniques, with the water vapor advection term being obtained as the residue needed for balance. Thus, the intent is to develop a purely satellite-based method for obtaining the full set of terms in the atmospheric water budget equation without requiring in situ sounding information on the wind profile. The algorithm is validated by cross-checking all the algorithm components through multiple- algorithm retrieval intercomparisons. A further check on the validation is obtained by directly comparing water vapor transports into the targeted basin diagnosed from the satellite algorithms to those obtained observationally from a network of land-based upper air stations that nearly uniformly surround the basin, although it is fair to say that these checks are more effective m identifying problems in estimating vapor transports from a leaky operational radiosonde network than in verifying the transport estimates determined from the satellite algorithm system Total columnar atmospheric water budget results are presented for an extended annual cycle consisting of the months of October-97, January-98, April-98, July-98,October-98, and January 1999. These results are used to emphasize the changing relationship in E-P, as well as in the varying roles of storage and advection in balancing E-P both on daily and monthly time scales and on localized and basin space scales. Results from the algorithm-to-algorithm intercomparisons are also presented in the context of sensitivity testing to help understand the intrinsic uncertainties in evaluating the water budget terms by an all-satellite algorithm approach.

Comparison Between GOES-12 Overshooting-Top Detections, WSR-88D Radar Reflectivity, and Severe Storm Reports

NASA Technical Reports Server (NTRS)

Dworak, Richard; Bedka, Kristopher; Brunner, Jason; Feltz, Wayne

2012-01-01

Studies have found that convective storms with overshooting-top (OT) signatures in weather satellite imagery are often associated with hazardous weather, such as heavy rainfall, tornadoes, damaging winds, and large hail. An objective satellite-based OT detection product has been developed using 11-micrometer infrared window (IRW) channel brightness temperatures (BTs) for the upcoming R series of the Geostationary Operational Environmental Satellite (GOES-R) Advanced Baseline Imager. In this study, this method is applied to GOES-12 IRW data and the OT detections are compared with radar data, severe storm reports, and severe weather warnings over the eastern United States. The goals of this study are to 1) improve forecaster understanding of satellite OT signatures relative to commonly available radar products, 2) assess OT detection product accuracy, and 3) evaluate the utility of an OT detection product for diagnosing hazardous convective storms. The coevolution of radar-derived products and satellite OT signatures indicates that an OT often corresponds with the highest radar echo top and reflectivity maximum aloft. Validation of OT detections relative to composite reflectivity indicates an algorithm false-alarm ratio of 16%, with OTs within the coldest IRW BT range (less than 200 K) being the most accurate. A significant IRW BT minimum typically present with an OT is more often associated with heavy precipitation than a region with a spatially uniform BT. Severe weather was often associated with OT detections during the warm season (April September) and over the southern United States. The severe weather to OT relationship increased by 15% when GOES operated in rapid-scan mode, showing the importance of high temporal resolution for observing and detecting rapidly evolving cloud-top features. Comparison of the earliest OT detection associated with a severe weather report showed that 75% of the cases occur before severe weather and that 42% of collocated severe weather reports had either an OT detected before a severe weather warning or no warning issued at all. The relationships between satellite OT signatures, severe weather, and heavy rainfall shown in this paper suggest that 1) when an OT is detected, the particular storm is likely producing heavy rainfall and/or possibly severe weather; 2) an objective OT detection product can be used to increase situational awareness and forecaster confidence that a given storm is severe; and 3) this product may be particularly useful in regions with insufficient radar coverage.

An Accelerated Recursive Doubling Algorithm for Block Tridiagonal Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Seal, Sudip K

2014-01-01

Block tridiagonal systems of linear equations arise in a wide variety of scientific and engineering applications. Recursive doubling algorithm is a well-known prefix computation-based numerical algorithm that requires O(M^3(N/P + log P)) work to compute the solution of a block tridiagonal system with N block rows and block size M on P processors. In real-world applications, solutions of tridiagonal systems are most often sought with multiple, often hundreds and thousands, of different right hand sides but with the same tridiagonal matrix. Here, we show that a recursive doubling algorithm is sub-optimal when computing solutions of block tridiagonal systems with multiplemore » right hand sides and present a novel algorithm, called the accelerated recursive doubling algorithm, that delivers O(R) improvement when solving block tridiagonal systems with R distinct right hand sides. Since R is typically about 100 1000, this improvement translates to very significant speedups in practice. Detailed complexity analyses of the new algorithm with empirical confirmation of runtime improvements are presented. To the best of our knowledge, this algorithm has not been reported before in the literature.« less

Classification of ECG signal with Support Vector Machine Method for Arrhythmia Detection

NASA Astrophysics Data System (ADS)

Turnip, Arjon; Ilham Rizqywan, M.; Kusumandari, Dwi E.; Turnip, Mardi; Sihombing, Poltak

2018-03-01

An electrocardiogram is a potential bioelectric record that occurs as a result of cardiac activity. QRS Detection with zero crossing calculation is one method that can precisely determine peak R of QRS wave as part of arrhythmia detection. In this paper, two experimental scheme (2 minutes duration with different activities: relaxed and, typing) were conducted. From the two experiments it were obtained: accuracy, sensitivity, and positive predictivity about 100% each for the first experiment and about 79%, 93%, 83% for the second experiment, respectively. Furthermore, the feature set of MIT-BIH arrhythmia using the support vector machine (SVM) method on the WEKA software is evaluated. By combining the available attributes on the WEKA algorithm, the result is constant since all classes of SVM goes to the normal class with average 88.49% accuracy.

An Overview of NASA SPoRT GOES-R JPSS Proving Ground Testbed Activities

NASA Technical Reports Server (NTRS)

Berndt, Emily; Stano, Geoffrey; Fuell, Kevin; Leroy, Anita; Mcgrath, Kevin; Molthan, Andrew; Schultz, Lori; Smith, Matthew; White, Kris; Schultz, Christopher;

KSC-08pd1601

NASA Image and Video Library

2008-06-09

CAPE CANAVERAL, Fla. -- At Cape Canaveral Air Force Station, the second stage for the GOES-O Delta IV rocket is suspended vertically. It will be moved into a work cell for processing. GOES – O is one of a series of Geostationary Operational Environmental Satellites. The multimission GOES series N-P will be a vital contributor to weather, solar, and space operations and science. NASA and the National Oceanic and Atmospheric Administration, or NOAA, are actively engaged in a cooperative program to expand the existing GOES system with the launch of the GOES N-P satellites. Photo credit: NASA/Kim Shiflett

KSC-08pd1600

NASA Image and Video Library

2008-06-09

CAPE CANAVERAL, Fla. -- At Cape Canaveral Air Force Station, the second stage for the GOES-O Delta IV rocket is rotated vertically. Once upright, the second stage will be moved into a work cell for processing. GOES – O is one of a series of Geostationary Operational Environmental Satellites. The multimission GOES series N-P will be a vital contributor to weather, solar, and space operations and science. NASA and the National Oceanic and Atmospheric Administration, or NOAA, are actively engaged in a cooperative program to expand the existing GOES system with the launch of the GOES N-P satellites. Photo credit: NASA/Kim Shiflett

27 CFR 9.103 - Mimbres Valley.

Code of Federal Regulations, 2014 CFR

2014-04-01

..., T16S/R11W; (4) It then goes south on the Mimbres River for .25 mile until it intersects the 6,000 foot... it goes west on the section line for approximately .6 mile to a light duty road located 500 feet... miles until it intersects the 4,200 foot elevation contour line at the southeast corner of Sec. 34, T25S...

The Hazard Mapping System (HMS)-a Multiplatform Remote Sensing Approach to Fire and Smoke Detection

NASA Astrophysics Data System (ADS)

Kibler, J.; Ruminski, M. G.

2003-12-01

The HMS is a multiplatform remote sensing approach to detecting fires and smoke over the US and adjacent areas of Canada and Mexico that has been in place since June 2002. This system is an integral part of the National Environmental Satellite and Data Information Service (NESDIS) near realtime hazard detection and mitigation efforts. The system utilizes NOAA's Geostationary Operational Environmental Satellites (GOES), Polar Operational Environmental Satellites (POES) and the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument on NASA's Terra and Aqua spacecraft. Automated detection algorithms are employed for each of the satellites for the fire detects while smoke is added by a satellite image analyst. In June 2003 the HMS underwent an upgrade. A number of features were added for users of the products generated on the HMS. Sectors covering Alaska and Hawaii were added. The use of Geographic Information System (GIS) shape files for smoke analysis is a new feature. Shape files show the progression and time of a single smoke plume as each analysis is drawn and then updated. The analyst now has the ability to view GOES, POES, and MODIS data in a single loop. This allows the fire analyst the ability to easily confirm a fire in three different data sets. The upgraded HMS has faster satellite looping and gives the analyst the ability to design a false color image for a particular region. The GOES satellites provide a relatively coarse 4 km infrared resolution at satellite subpoint for thermal fire detection but provide the advantage of a rapid update cycle. GOES imagery is updated every 15 minutes utilizing both GOES-10 and GOES-12. POES imagery from NOAA-15, NOAA-16 and NOAA-17 and MODIS from Terra and Aqua are employed with each satellite providing twice per day coverage (more frequent over Alaska). While the frequency of imagery is much less than with GOES the higher resolution of these satellites (1 km along the suborbital track) allows for detection of smaller and/or cooler burning fires. Each of the algorithms utilizes a number of temporal, thermal and contextual filters in an attempt to screen out false detects. However, false detects do get processed by the algorithms to varying degrees. Therefore, the automated fire detects from each algorithm are quality controlled by an analyst who scans the imagery and may either accept or delete fire points. The analyst also has the ability to manually add additional fire points based on the imagery. Smoke is outlined by the analyst using visible imagery, primarily GOES which provides 1 km resolution. Occasionally a smoke plume seen in visible imagery is the only indicator of a fire and would be manually added to the fire detect file. The Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) is a forecast model that projects the trajectory and dispersion of a smoke plume over a period of time. The HYSPLIT is run for fires that are selected by the analyst that are seen to be producing a significant smoke plume. The analyst defines a smoke producing area commensurate with the size of the fire and amount of smoke detected. The output is hosted on an Air Resources Lab (ARL) web site which can be accessed from the web site listed below. All of the information is posted to the web page noted below. Besides the interactive GIS presentation users can view the product in graphical jpg format. The analyst edited points as well as the unedited automated fire detects are available for users to view directly on the web page or to download. All of the data is also archived and accessed via ftp.

GOES-S NASA Social

NASA Image and Video Library

2018-02-28

A.J. Sandora, Lockheed Martin's GOES-R Series Mechanical Operations Assembly, Test and Launch Operations (ATLO) manager, speaks to members of social media in the Kennedy Space Center’s Press Site auditorium. The briefing focused on the National Oceanic and Atmospheric Administration's, or NOAA's, Geostationary Operational Environmental Satellite, or GOES-S. Built by Lockheed Martin Space Systems of Littleton, Colorado, the spacecraft is the second satellite in a series of next-generation NOAA weather satellites. It will launch to a geostationary position over the U.S. to provide images of storms and help predict weather forecasts, severe weather outlooks, watches, warnings, lightning conditions and longer-term forecasting. GOES-S is slated to lift off at 5:02 p.m. EST on March 1, 2018 aboard a United Launch Alliance Atlas V rocket.

SUVI Thematic Maps: A new tool for space weather forecasting

NASA Astrophysics Data System (ADS)

Hughes, J. M.; Seaton, D. B.; Darnel, J.

2017-12-01

The new Solar Ultraviolet Imager (SUVI) instruments aboard NOAA's GOES-R series satellites collect continuous, high-quality imagery of the Sun in six wavelengths. SUVI imagers produce at least one image every 10 seconds, or 8,640 images per day, considerably more data than observers can digest in real time. Over the projected 20-year lifetime of the four GOES-R series spacecraft, SUVI will provide critical imagery for space weather forecasters and produce an extensive but unwieldy archive. In order to condense the database into a dynamic and searchable form we have developed solar thematic maps, maps of the Sun with key features, such as coronal holes, flares, bright regions, quiet corona, and filaments, identified. Thematic maps will be used in NOAA's Space Weather Prediction Center to improve forecaster response time to solar events and generate several derivative products. Likewise, scientists use thematic maps to find observations of interest more easily. Using an expert-trained, naive Bayesian classifier to label each pixel, we create thematic maps in real-time. We created software to collect expert classifications of solar features based on SUVI images. Using this software, we compiled a database of expert classifications, from which we could characterize the distribution of pixels associated with each theme. Given new images, the classifier assigns each pixel the most appropriate label according to the trained distribution. Here we describe the software to collect expert training and the successes and limitations of the classifier. The algorithm excellently identifies coronal holes but fails to consistently detect filaments and prominences. We compare the Bayesian classifier to an artificial neural network, one of our attempts to overcome the aforementioned limitations. These results are very promising and encourage future research into an ensemble classification approach.

The NOAA Satellite Observing System Architecture Study

NASA Technical Reports Server (NTRS)

Volz, Stephen; Maier, Mark; Di Pietro, David

2016-01-01

NOAA is beginning a study, the NOAA Satellite Observing System Architecture (NSOSA) study, to plan for the future operational environmental satellite system that will follow GOES and JPSS, beginning about 2030. This is an opportunity to design a modern architecture with no pre-conceived notions regarding instruments, platforms, orbits, etc. The NSOSA study will develop and evaluate architecture alternatives to include partner and commercial alternatives that are likely to become available. The objectives will include both functional needs and strategic characteristics (e.g., flexibility, responsiveness, sustainability). Part of this study is the Space Platform Requirements Working Group (SPRWG), which is being commissioned by NESDIS. The SPRWG is charged to assess new or existing user needs and to provide relative priorities for observational needs in the context of the future architecture. SPRWG results will serve as input to the process for new foundational (Level 0 and Level 1) requirements for the next generation of NOAA satellites that follow the GOES-R, JPSS, DSCOVR, Jason-3, and COSMIC-2 missions.

KSC-08pd1598

NASA Image and Video Library

2008-06-09

CAPE CANAVERAL, Fla. -- At Cape Canaveral Air Force Station, the second stage for the GOES-O Delta IV rocket rests in the rotation stand. The second stage will be rotated to vertical and moved into a work cell for processing. GOES – O is one of a series of Geostationary Operational Environmental Satellites. The multimission GOES series N-P will be a vital contributor to weather, solar, and space operations and science. NASA and the National Oceanic and Atmospheric Administration, or NOAA, are actively engaged in a cooperative program to expand the existing GOES system with the launch of the GOES N-P satellites. Photo credit: NASA/Kim Shiflett

KSC-08pd1599

NASA Image and Video Library

2008-06-09

CAPE CANAVERAL, Fla. -- At Cape Canaveral Air Force Station, the second stage for the GOES-O Delta IV rocket is lifted from its horizontal position on the rotation stand. Once vertical, the second stage will be moved into a work cell for processing. GOES – O is one of a series of Geostationary Operational Environmental Satellites. The multimission GOES series N-P will be a vital contributor to weather, solar, and space operations and science. NASA and the National Oceanic and Atmospheric Administration, or NOAA, are actively engaged in a cooperative program to expand the existing GOES system with the launch of the GOES N-P satellites. Photo credit: NASA/Kim Shiflett

KSC-08pd1602

NASA Image and Video Library

2008-06-09

CAPE CANAVERAL, Fla. -- At Cape Canaveral Air Force Station, workers on a crane check the attachments of the sling suspending the second stage for the GOES-O Delta IV rocket. The second stage will be moved into a work cell for processing. GOES – O is one of a series of Geostationary Operational Environmental Satellites. The multimission GOES series N-P will be a vital contributor to weather, solar, and space operations and science. NASA and the National Oceanic and Atmospheric Administration, or NOAA, are actively engaged in a cooperative program to expand the existing GOES system with the launch of the GOES N-P satellites. Photo credit: NASA/Kim Shiflett

Performance appraisal of VAS radiometry for GOES-4, -5 and -6

NASA Technical Reports Server (NTRS)

Chesters, D.; Robinson, W. D.

1983-01-01

The first three VISSR Atmospheric Sounders (VAS) were launched on GOES-4, -5, and -6 in 1980, 1981 and 1983. Postlaunch radiometric performance is assessed for noise, biases, registration and reliability, with special attention to calibration and problems in the data processing chain. The postlaunch performance of the VAS radiometer meets its prelaunch design specifications, particularly those related to image formation and noise reduction. The best instrument is carried on GOES-5, currently operational as GOES-EAST. Single sample noise is lower than expected, especially for the small longwave and large shortwave detectors. Detector to detector offsets are correctable to within the resolution limits of the instrument. Truncation, zero point and droop errors are insignificant. Absolute calibration errors, estimated from HIRS and from radiation transfer calculations, indicate moderate, but stable biases. Relative calibration errors from scanline to scanline are noticeable, but meet sounding requirements for temporarily and spatially averaged sounding fields of view. The VAS instrument is a potentially useful radiometer for mesoscale sounding operations. Image quality is very good. Soundings derived from quality controlled data meet prelaunch requirements when calculated with noise and bias resistant algorithms.

Development of GPS Receiver Kalman Filter Algorithms for Stationary, Low-Dynamics, and High-Dynamics Applications

DTIC Science & Technology

2016-06-01

UNCLASSIFIED Development of GPS Receiver Kalman Filter Algorithms for Stationary, Low-Dynamics, and High-Dynamics Applications Peter W. Sarunic 1 1...determine instantaneous estimates of receiver position and then goes on to develop three Kalman filter based estimators, which use stationary receiver...used in actual GPS receivers, and cover a wide range of applications. While the standard form of the Kalman filter , of which the three filters just

A Numerical Testbed for Remote Sensing of Aerosols, and its Demonstration for Evaluating Retrieval Synergy from a Geostationary Satellite Constellation of GEO-CAPE and GOES-R

NASA Technical Reports Server (NTRS)

Wang, Jun; Xu, Xiaoguang; Ding, Shouguo; Zeng, Jing; Spurr, Robert; Liu, Xiong; Chance, Kelly; Mishchenko, Michael I.

2014-01-01

We present a numerical testbed for remote sensing of aerosols, together with a demonstration for evaluating retrieval synergy from a geostationary satellite constellation. The testbed combines inverse (optimal-estimation) software with a forward model containing linearized code for computing particle scattering (for both spherical and non-spherical particles), a kernel-based (land and ocean) surface bi-directional reflectance facility, and a linearized radiative transfer model for polarized radiance. Calculation of gas absorption spectra uses the HITRAN (HIgh-resolution TRANsmission molecular absorption) database of spectroscopic line parameters and other trace species cross-sections. The outputs of the testbed include not only the Stokes 4-vector elements and their sensitivities (Jacobians) with respect to the aerosol single scattering and physical parameters (such as size and shape parameters, refractive index, and plume height), but also DFS (Degree of Freedom for Signal) values for retrieval of these parameters. This testbed can be used as a tool to provide an objective assessment of aerosol information content that can be retrieved for any constellation of (planned or real) satellite sensors and for any combination of algorithm design factors (in terms of wavelengths, viewing angles, radiance and/or polarization to be measured or used). We summarize the components of the testbed, including the derivation and validation of analytical formulae for Jacobian calculations. Benchmark calculations from the forward model are documented. In the context of NASA's Decadal Survey Mission GEOCAPE (GEOstationary Coastal and Air Pollution Events), we demonstrate the use of the testbed to conduct a feasibility study of using polarization measurements in and around the O2 A band for the retrieval of aerosol height information from space, as well as an to assess potential improvement in the retrieval of aerosol fine and coarse mode aerosol optical depth (AOD) through the synergic use of two future geostationary satellites, GOES-R (Geostationary Operational Environmental Satellite R-series) and TEMPO (Tropospheric Emissions: Monitoring of Pollution). Strong synergy between GEOS-R and TEMPO are found especially in their characterization of surface bi-directional reflectance, and thereby, can potentially improve the AOD retrieval to the accuracy required by GEO-CAPE.

EQS Goes R: Simulations for SEM Using the Package REQS

ERIC Educational Resources Information Center

Mair, Patrick; Wu, Eric; Bentler, Peter M.

2010-01-01

The REQS package is an interface between the R environment of statistical computing and the EQS software for structural equation modeling. The package consists of 3 main functions that read EQS script files and import the results into R, call EQS script files from R, and run EQS script files from R and import the results after EQS computations.…

Retrieving Aerosol in a Cloudy Environment: Aerosol Availability as a Function of Spatial and Temporal Resolution

NASA Technical Reports Server (NTRS)

Remer, Lorraine A.; Mattoo, Shana; Levy, Robert C.; Heidinger, Andrew; Pierce, R. Bradley; Chin, Mian

2011-01-01

The challenge of using satellite observations to retrieve aerosol properties in a cloudy environment is to prevent contamination of the aerosol signal from clouds, while maintaining sufficient aerosol product yield to satisfy specific applications. We investigate aerosol retrieval availability at different instrument pixel resolutions, using the standard MODIS aerosol cloud mask applied to MODIS data and a new GOES-R cloud mask applied to GOES data for a domain covering North America and surrounding oceans. Aerosol availability is not the same as the cloud free fraction and takes into account the technqiues used in the MODIS algorithm to avoid clouds, reduce noise and maintain sufficient numbers of aerosol retrievals. The inherent spatial resolution of each instrument, 0.5x0.5 km for MODIS and 1x1 km for GOES, is systematically degraded to 1x1 km, 2x2 km, 4x4 km and 8x8 km resolutions and then analyzed as to how that degradation would affect the availability of an aerosol retrieval, assuming an aerosol product resolution at 8x8 km. The results show that as pixel size increases, availability decreases until at 8x8 km 70% to 85% of the retrievals available at 0.5 km have been lost. The diurnal pattern of aerosol retrieval availability examined for one day in the summer suggests that coarse resolution sensors (i.e., 4x4 km or 8x8 km) may be able to retrieve aerosol early in the morning that would otherwise be missed at the time of current polar orbiting satellites, but not the diurnal aerosol properties due to cloud cover developed during the day. In contrast finer resolution sensors (i.e., 1x1 km or 2x2 km) have much better opportunity to retrieve aerosols in the partly cloudy scenes and better chance of returning the diurnal aerosol properties. Large differences in the results of the two cloud masks designed for MODIS aerosol and GOES cloud products strongly reinforce that cloud masks must be developed with specific purposes in mind and that a generic cloud mask applied to an independent aerosol retrieval will likely fail.

McIDAS-V: Data Analysis and Visualization for NPOESS and GOES-R

NASA Astrophysics Data System (ADS)

Rink, T.; Achtor, T. H.

2009-12-01

McIDAS-V, the next-generation McIDAS, is being built on top a modern, cross-platform software framework which supports development of 4-D, interactive displays and integration of wide-array of geophysical data. As the replacement of McIDAS, the development emphasis is on future satellite observation platforms such as NPOESS and GOES-R. Data interrogation, analysis and visualization capabilities have been developed for multi- and hyper-spectral instruments like MODIS, AIRS and IASI, and are being extended for application to VIIRS and CrIS. Compatibility with GOES-R ABI level1 and level2 product storage formats has been demonstrated. The abstract data model, which can internalize most any geophysical data, opens up new possibilities for data fusion techniques, for example, polar and geostationary, (LEO/GEO), synergy for research and validation. McIDAS-V follows an object-oriented design model, using the Java programming language, allowing specialized extensions for for new sources of data, and novel displays and interactive behavior. The reference application, what the user sees on startup, can be customized, and the system has a persistence mechanism allowing sharing of the application state across the internet. McIDAS-V is open-source, and free to the public.

GOES-S Mission Science Briefing

NASA Image and Video Library

2018-02-27

In the Kennedy Space Center's Press Site auditorium, members of the media participate in a mission briefing on National Oceanic and Atmospheric Administration's, or NOAA's, Geostationary Operational Environmental Satellite, or GOES-S. Briefing participants from left are: Steve Cole of NASA Communications; Dan Lindsey, GOES-R senior scientific advisor for NOAA; Louis Uccellini, director of the National Weather Service for NOAA; Jim Roberts, a scientist with the Earth System Research Laboratory's Office of Atmospheric Research for NOAA; Kristin Calhoun, a research scientist with NOAA's National Severe Storms Laboratory, and George Morrow, deputy director of NASA's Goddard Space Flight Center in Greenbelt, Maryland. GOES-S is the second satellite in a series of next-generation NOAA weather satellites. It will launch to a geostationary position over the U.S. to provide images of storms and help predict weather forecasts, severe weather outlooks, watches, warnings, lightning conditions and longer-term forecasting. GOES-S is slated to lift off at 5:02 p.m. EST on March 1, 2018 aboard a United Launch Alliance Atlas V rocket.

GOES-S Prelaunch News Conference

NASA Image and Video Library

2018-02-27

In the Kennedy Space Center's Press Site auditorium, NASA and industry leaders speak to members of the media at a prelaunch news conference about National Oceanic and Atmospheric Administration's, or NOAA's, Geostationary Operational Environmental Satellite, or GOES-S. Participants from left are: Tori McLendon of NASA Communications; Stephen Volz, director for Satellite and Information Services for NOAA; Tim Walsh, acting GOES-R System Program director for NOAA; Sandra Smalley, director of the Joint Agency Satellite Division at NASA Headquarters in Washington D.C.; Tim Dunn, NASA launch director at Kennedy; Scott Messer, manager of NASA Programs for United launch Alliance; and Kathy Winters, launch weather officer for the U.S. Air Force 45th Weather Squadron at Cape Canaveral Air Force Station. The GOES series of satellites will significantly improve the detection and observation of environmental phenomena that directly affect public safety, protection of property and the nation's economic health and prosperity. GOES-S is slated to lift off at 5:02 p.m. EST on March 1, 2018 aboard a United Launch Alliance Atlas V rocket.

Onsets of Solar Proton Events in Satellite and Ground Level Observations: A Comparison

NASA Astrophysics Data System (ADS)

He, Jing; Rodriguez, Juan V.

2018-03-01

The early detection of solar proton event onsets is essential for protecting humans and electronics in space, as well as passengers and crew at aviation altitudes. Two commonly compared methods for observing solar proton events that are sufficiently large and energetic to be detected on the ground through the creation of secondary radiation—known as ground level enhancements (GLEs)—are (1) a network of ground-based neutron monitors (NMs) and (2) satellite-based particle detectors. Until recently, owing to the different time resolution of the two data sets, it has not been feasible to compare these two types of observations using the same detection algorithm. This paper presents a comparison between the two observational platforms using newly processed >100 MeV 1 min count rates and fluxes from National Oceanic and Atmospheric Administration's Geostationary Operational Environmental Satellite (GOES) 8-12 satellites, and 1 min count rates from the Neutron Monitor Database. We applied the same detection algorithm to each data set (tuned to the different background noise levels of the instrument types). Seventeen SPEs with GLEs were studied: GLEs 55-70 from Solar Cycle 23 and GLE 71 from Solar Cycle 24. The median difference in the event detection times by GOES and NM data is 0 min, indicating no innate benefit in time of either system. The 10th, 25th, 75th, and 90th percentiles of the onset time differences (GOES minus NMs) are -7.2 min, -1.5 min, 2.5 min, and 4.2 min, respectively. This is in contrast to previous studies in which NM detections led GOES by 8 to 52 min without accounting for different alert protocols.

1/ r potential in higher dimensions

NASA Astrophysics Data System (ADS)

Chakraborty, Sumanta; Dadhich, Naresh

2018-01-01

In Einstein gravity, gravitational potential goes as 1/r^{d-3} in d non-compactified spacetime dimensions, which assumes the familiar 1 / r form in four dimensions. On the other hand, it goes as 1/r^{α }, with α =(d-2m-1)/m, in pure Lovelock gravity involving only one mth order term of the Lovelock polynomial in the gravitational action. The latter offers a novel possibility of having 1 / r potential for the non-compactified dimension spectrum given by d=3m+1. Thus it turns out that in the two prototype gravitational settings of isolated objects, like black holes and the universe as a whole - cosmological models, the Einstein gravity in four and mth order pure Lovelock gravity in 3m+1 dimensions behave in a similar fashion as far as gravitational interactions are considered. However propagation of gravitational waves (or the number of degrees of freedom) does indeed serve as a discriminator because it has two polarizations only in four dimensions.

GOES (Geostationary Operational Environmental Satellite)-Next Overview.

DTIC Science & Technology

1985-09-01

shows the locations and sizes of warm and cold eddies. r * Hydrological services. GOES (and polar orbiter) data are used to produce maps and charts...rationale used to develop specifications for the N next generation of satellites of this series. The payload * instruments of the current satellites are...reviewed in con- junction with the products prepared from their data outputs. The rationale used by the National Weather Service (NWS) in developing

Relationships Between Long-Range Lightning Networks and TRMM/LIS Observations

NASA Technical Reports Server (NTRS)

Rudlosky, Scott D.; Holzworth, Robert H.; Carey, Lawrence D.; Schultz, Chris J.; Bateman, Monte; Cummins, Kenneth L.; Cummins, Kenneth L.; Blakeslee, Richard J.; Goodman, Steven J.

2012-01-01

Recent advances in long-range lightning detection technologies have improved our understanding of thunderstorm evolution in the data sparse oceanic regions. Although the expansion and improvement of long-range lightning datasets have increased their applicability, these applications (e.g., data assimilation, atmospheric chemistry, and aviation weather hazards) require knowledge of the network detection capabilities. The present study intercompares long-range lightning data with observations from the Lightning Imaging Sensor (LIS) aboard the Tropical Rainfall Measurement Mission (TRMM) satellite. The study examines network detection efficiency and location accuracy relative to LIS observations, describes spatial variability in these performance metrics, and documents the characteristics of LIS flashes that are detected by the long-range networks. Improved knowledge of relationships between these datasets will allow researchers, algorithm developers, and operational users to better prepare for the spatial and temporal coverage of the upcoming GOES-R Geostationary Lightning Mapper (GLM).

Evaluation of Long-Range Lightning Detection Networks Using TRMM/LIS Observations

NASA Technical Reports Server (NTRS)

Rudlosky, Scott D.; Holzworth, Robert H.; Carey, Lawrence D.; Schultz, Chris J.; Bateman, Monte; Cecil, Daniel J.; Cummins, Kenneth L.; Petersen, Walter A.; Blakeslee, Richard J.; Goodman, Steven J.

2011-01-01

Recent advances in long-range lightning detection technologies have improved our understanding of thunderstorm evolution in the data sparse oceanic regions. Although the expansion and improvement of long-range lightning datasets have increased their applicability, these applications (e.g., data assimilation, atmospheric chemistry, and aviation weather hazards) require knowledge of the network detection capabilities. Toward this end, the present study evaluates data from the World Wide Lightning Location Network (WWLLN) using observations from the Lightning Imaging Sensor (LIS) aboard the Tropical Rainfall Measurement Mission (TRMM) satellite. The study documents the WWLLN detection efficiency and location accuracy relative to LIS observations, describes the spatial variability in these performance metrics, and documents the characteristics of LIS flashes that are detected by WWLLN. Improved knowledge of the WWLLN detection capabilities will allow researchers, algorithm developers, and operational users to better prepare for the spatial and temporal coverage of the upcoming GOES-R Geostationary Lightning Mapper (GLM).

Preliminary Development and Evaluation of Lightning Jump Algorithms for the Real-Time Detection of Severe Weather

NASA Technical Reports Server (NTRS)

Schultz, Christopher J.; Petersen, Walter A.; Carey, Lawrence D.

2009-01-01

Previous studies have demonstrated that rapid increases in total lightning activity (intracloud + cloud-to-ground) are often observed tens of minutes in advance of the occurrence of severe weather at the ground. These rapid increases in lightning activity have been termed "lightning jumps." Herein, we document a positive correlation between lightning jumps and the manifestation of severe weather in thunderstorms occurring across the Tennessee Valley and Washington D.C. A total of 107 thunderstorms were examined in this study, with 69 of the 107 thunderstorms falling into the category of non-severe, and 38 into the category of severe. From the dataset of 69 isolated non-severe thunderstorms, an average peak 1 minute flash rate of 10 flashes/min was determined. A variety of severe thunderstorm types were examined for this study including an MCS, MCV, tornadic outer rainbands of tropical remnants, supercells, and pulse severe thunderstorms. Of the 107 thunderstorms, 85 thunderstorms (47 non-severe, 38 severe) from the Tennessee Valley and Washington D.C tested 6 lightning jump algorithm configurations (Gatlin, Gatlin 45, 2(sigma), 3(sigma), Threshold 10, and Threshold 8). Performance metrics for each algorithm were then calculated, yielding encouraging results from the limited sample of 85 thunderstorms. The 2(sigma) lightning jump algorithm had a high probability of detection (POD; 87%), a modest false alarm rate (FAR; 33%), and a solid Heidke Skill Score (HSS; 0.75). A second and more simplistic lightning jump algorithm named the Threshold 8 lightning jump algorithm also shows promise, with a POD of 81% and a FAR of 41%. Average lead times to severe weather occurrence for these two algorithms were 23 minutes and 20 minutes, respectively. The overall goal of this study is to advance the development of an operationally-applicable jump algorithm that can be used with either total lightning observations made from the ground, or in the near future from space using the GOES-R Geostationary Lightning Mapper.

Data Filtering of Western Hemisphere GOES Wildfire ABBA Products

NASA Astrophysics Data System (ADS)

Theisen, M.; Prins, E.; Schmidt, C.; Reid, J. S.; Hunter, J.; Westphal, D.

2002-05-01

The Fire Locating and Modeling of Burning Emissions (FLAMBE') project was developed to model biomass burning emissions, transport, and radiative effects in real time. The model relies on data from the Geostationary Operational Environment Satellites (GOES-8, GOES-10), that is generated by the Wildfire Automated Biomass Burning Algorithm (WF ABBA). In an attempt to develop the most accurate modeling system the data set needs to be filtered to distinguish the true fire pixels from false alarms. False alarms occur due to reflection of solar radiation off of standing water, surface structure variances, and heat anomalies. The Reoccurring Fire Filtering algorithm (ReFF) was developed to address such false alarms by filtering data dependent on reoccurrence, location in relation to region and satellite, as well as heat intensity. WF ABBA data for the year 2000 during the peak of the burning season were analyzed using ReFF. The analysis resulted in a 45% decrease in North America and only a 15% decrease in South America, respectively, in total fire pixel occurrence. The lower percentage decrease in South America is a result of fires burning for longer periods of time, less surface variance, as well as an increase in heat intensity of fires for that region. Also fires are so prevalent in the region that multiple fires may coexist in the same 4-kilometer pixel.

Pre-Hardware Optimization of Spacecraft Image Processing Software Algorithms and Hardware Implementation

NASA Technical Reports Server (NTRS)

Kizhner, Semion; Flatley, Thomas P.; Hestnes, Phyllis; Jentoft-Nilsen, Marit; Petrick, David J.; Day, John H. (Technical Monitor)

2001-01-01

Spacecraft telemetry rates have steadily increased over the last decade presenting a problem for real-time processing by ground facilities. This paper proposes a solution to a related problem for the Geostationary Operational Environmental Spacecraft (GOES-8) image processing application. Although large super-computer facilities are the obvious heritage solution, they are very costly, making it imperative to seek a feasible alternative engineering solution at a fraction of the cost. The solution is based on a Personal Computer (PC) platform and synergy of optimized software algorithms and re-configurable computing hardware technologies, such as Field Programmable Gate Arrays (FPGA) and Digital Signal Processing (DSP). It has been shown in [1] and [2] that this configuration can provide superior inexpensive performance for a chosen application on the ground station or on-board a spacecraft. However, since this technology is still maturing, intensive pre-hardware steps are necessary to achieve the benefits of hardware implementation. This paper describes these steps for the GOES-8 application, a software project developed using Interactive Data Language (IDL) (Trademark of Research Systems, Inc.) on a Workstation/UNIX platform. The solution involves converting the application to a PC/Windows/RC platform, selected mainly by the availability of low cost, adaptable high-speed RC hardware. In order for the hybrid system to run, the IDL software was modified to account for platform differences. It was interesting to examine the gains and losses in performance on the new platform, as well as unexpected observations before implementing hardware. After substantial pre-hardware optimization steps, the necessity of hardware implementation for bottleneck code in the PC environment became evident and solvable beginning with the methodology described in [1], [2], and implementing a novel methodology for this specific application [6]. The PC-RC interface bandwidth problem for the class of applications with moderate input-output data rates but large intermediate multi-thread data streams has been addressed and mitigated. This opens a new class of satellite image processing applications for bottleneck problems solution using RC technologies. The issue of a science algorithm level of abstraction necessary for RC hardware implementation is also described. Selected Matlab functions already implemented in hardware were investigated for their direct applicability to the GOES-8 application with the intent to create a library of Matlab and IDL RC functions for ongoing work. A complete class of spacecraft image processing applications using embedded re-configurable computing technology to meet real-time requirements, including performance results and comparison with the existing system, is described in this paper.

Satellite Imagery Analysis for Nighttime Temperature Inversion Clouds

NASA Technical Reports Server (NTRS)

Kawamoto, K.; Minnis, P.; Arduini, R.; Smith, W., Jr.

2001-01-01

Clouds play important roles in the climate system. Their optical and microphysical properties, which largely determine their radiative property, need to be investigated. Among several measurement means, satellite remote sensing seems to be the most promising. Since most of the cloud algorithms proposed so far are daytime use which utilizes solar radiation, Minnis et al. (1998) developed a nighttime use one using 3.7-, 11 - and 12-microns channels. Their algorithm, however, has a drawback that is not able to treat temperature inversion cases. We update their algorithm, incorporating new parameterization by Arduini et al. (1999) which is valid for temperature inversion cases. This updated algorithm has been applied to GOES satellite data and reasonable retrieval results were obtained.

The Sao Paulo Lightning Mapping Array (SPLMA): Prospects to GOES-R GLM and CHUVA

NASA Technical Reports Server (NTRS)

Albrecht, Rachel I.; Carrey, Larry; Blakeslee, Richard J.; Bailey, Jeffrey C.; Goodman, Steven J.; Bruning, Eric C.; Koshak, William; Morales, Carlos A.; Machado, Luiz A. T.; Angelis, Carlos F.;

Assessing and Ensuring GOES-R Magnetometer Accuracy

NASA Technical Reports Server (NTRS)

Kronenwetter, Jeffrey; Carter, Delano R.; Todirita, Monica; Chu, Donald

2016-01-01

The GOES-R magnetometer accuracy requirement is 1.7 nanoteslas (nT). During quiet times (100 nT), accuracy is defined as absolute mean plus 3 sigma. During storms (300 nT), accuracy is defined as absolute mean plus 2 sigma. To achieve this, the sensor itself has better than 1 nT accuracy. Because zero offset and scale factor drift over time, it is also necessary to perform annual calibration maneuvers. To predict performance, we used covariance analysis and attempted to corroborate it with simulations. Although not perfect, the two generally agree and show the expected behaviors. With the annual calibration regimen, these predictions suggest that the magnetometers will meet their accuracy requirements.

KSC-2009-5456

NASA Image and Video Library

2009-10-15

CAPE CANAVERAL, Fla. – At the Receipt Inspection Shop on Cape Canaveral Air Force Station in Florida, an ATK Space Systems' 60-inch graphite epoxy motor, or GEM, slated for launch of the GOES-P spacecraft rests on a work stand awaiting further processing. The United Launch Alliance Delta IV is the launch vehicle for GOES-P, the latest Geostationary Operational Environmental Satellite developed by NASA for the National Oceanic and Atmospheric Administration, or NOAA. Launch is targeted for March 4, 2010, from Launch Complex 37. For information on GOES-P, visit http://nasascience.nasa.gov/missions/goes-n-o-p. Photo credit: NASA/Dimitri Gerondidakis

KSC-2009-5454

NASA Image and Video Library

2009-10-15

CAPE CANAVERAL, Fla. – At the Receipt Inspection Shop on Cape Canaveral Air Force Station in Florida, ATK Space Systems workers guide a 60-inch graphite epoxy motor, or GEM, slated for launch of the GOES-P spacecraft as it is moved toward a work stand. The United Launch Alliance Delta IV is the launch vehicle for GOES-P, the latest Geostationary Operational Environmental Satellite developed by NASA for the National Oceanic and Atmospheric Administration, or NOAA. Launch is targeted for March 4, 2010, from Launch Complex 37. For information on GOES-P, visit http://nasascience.nasa.gov/missions/goes-n-o-p. Photo credit: NASA/Dimitri Gerondidakis

KSC-2009-5455

NASA Image and Video Library

2009-10-15

CAPE CANAVERAL, Fla. – At the Receipt Inspection Shop on Cape Canaveral Air Force Station in Florida, ATK Space Systems workers guide a 60-inch graphite epoxy motor, or GEM, slated for launch of the GOES-P spacecraft as it is lowered toward a work stand. The United Launch Alliance Delta IV is the launch vehicle for GOES-P, the latest Geostationary Operational Environmental Satellite developed by NASA for the National Oceanic and Atmospheric Administration, or NOAA. Launch is targeted for March 4, 2010, from Launch Complex 37. For information on GOES-P, visit http://nasascience.nasa.gov/missions/goes-n-o-p. Photo credit: NASA/Dimitri Gerondidakis

Status and Future of GOES X-Ray Sensor Observations

NASA Astrophysics Data System (ADS)

Viereck, R.; Biesecker, D.

2008-05-01

The GOES X-Ray Sensor (XRS) has provided x-ray irradiance measurements in the 0.05 to 0.8 nm spectral band for nearly 30 years. These observations define the magnitude of x-ray flares. There are three issues that should be brought to the attention of the scientific community. First, today's XRS data have multiplicative factors of 0.7 and 0.85 that have been applied to the data to make recent (since GOES 8) observations match the earlier ones. We now believe that these factors are not correct and should be removed. There are implications on the magnitudes of flares and the historic record. The second issue is the current state of the XRS sensors. Two concurrent satellites, GOES 11 and GOES 12, now have failed XRS systems and the GOES 13 XRS (soon to be deployed) is only partially functioning leaving a serious vulnerability in the near future. The third issue is the future of these observations. From the beginning, the XRS detectors have been gas ionization cells which have proven to be very robust and stable. The future GOES R+ XRS instruments will be changing to solid state silicon diode detectors. The possible implications of this new detector technology should be considered as well. Details of these three issues will be presented and the implications discussed. Alternatives for the multiplicative factor and the failed XRS's will be presented.

Biomass Combustions and Burning Emissions Inferred from GOES Fire Radiative Power

NASA Astrophysics Data System (ADS)

Zhang, X.; Kondragunta, S.; Schmidt, C.

2007-12-01

Biomass burning significantly affects air quality and climate changes. Current estimates of burning emissions are rather imprecise and vary markedly with different methodologies. This paper investigates biomass burning consumption and emissions using GOES (Geostationary Operational Environmental Satellites) WF_ABBA (Wildfire Automated Biomass Burning Algorithm) fire product. In doing this, we establish a set of representatives in diurnal patterns of half-hourly GOES Fire Radiative Power (FRP) for various ecosystems. The representative patterns are used to fill the missed and poor observations of half hourly FRP in GOES fire data for individual fire pixels. The simulated FRP is directly applied to the calculation of the biomass combusted during fire activities. The FRP-based biomass combustion is evaluated using the estimates using a traditional model which integrates burned area, fuel loading, and combustion factor. In the traditional model calculation, we derive burned areas from GOES WF_ABBA fire size. Fuel loading includes three different types (1) MODIS Vegetation Property-based Fuel System (MVPFS), (2) National Dangerous Rating Systems (NFDRS), and (3) the Fuel Characteristic Classification System (FCCS). By comparing the biomass combustions across the Contiguous United States (CONUS) from 2003-2005, we conclude that FRP is an effective tool to estimate the biomass burning emissions. Finally, we examine the temporal and spatial patterns in biomass combustions and emissions (PM2.5, CO, NH3) across the CONUS.

Development and validation of satellite-based estimates of surface visibility

NASA Astrophysics Data System (ADS)

Brunner, J.; Pierce, R. B.; Lenzen, A.

2016-02-01

A satellite-based surface visibility retrieval has been developed using Moderate Resolution Imaging Spectroradiometer (MODIS) measurements as a proxy for Advanced Baseline Imager (ABI) data from the next generation of Geostationary Operational Environmental Satellites (GOES-R). The retrieval uses a multiple linear regression approach to relate satellite aerosol optical depth, fog/low cloud probability and thickness retrievals, and meteorological variables from numerical weather prediction forecasts to National Weather Service Automated Surface Observing System (ASOS) surface visibility measurements. Validation using independent ASOS measurements shows that the GOES-R ABI surface visibility retrieval (V) has an overall success rate of 64.5 % for classifying clear (V ≥ 30 km), moderate (10 km ≤ V < 30 km), low (2 km ≤ V < 10 km), and poor (V < 2 km) visibilities and shows the most skill during June through September, when Heidke skill scores are between 0.2 and 0.4. We demonstrate that the aerosol (clear-sky) component of the GOES-R ABI visibility retrieval can be used to augment measurements from the United States Environmental Protection Agency (EPA) and National Park Service (NPS) Interagency Monitoring of Protected Visual Environments (IMPROVE) network and provide useful information to the regional planning offices responsible for developing mitigation strategies required under the EPA's Regional Haze Rule, particularly during regional haze events associated with smoke from wildfires.

Development and validation of satellite based estimates of surface visibility

NASA Astrophysics Data System (ADS)

Brunner, J.; Pierce, R. B.; Lenzen, A.

2015-10-01

A satellite based surface visibility retrieval has been developed using Moderate Resolution Imaging Spectroradiometer (MODIS) measurements as a proxy for Advanced Baseline Imager (ABI) data from the next generation of Geostationary Operational Environmental Satellites (GOES-R). The retrieval uses a multiple linear regression approach to relate satellite aerosol optical depth, fog/low cloud probability and thickness retrievals, and meteorological variables from numerical weather prediction forecasts to National Weather Service Automated Surface Observing System (ASOS) surface visibility measurements. Validation using independent ASOS measurements shows that the GOES-R ABI surface visibility retrieval (V) has an overall success rate of 64.5% for classifying Clear (V ≥ 30 km), Moderate (10 km ≤ V < 30 km), Low (2 km ≤ V < 10 km) and Poor (V < 2 km) visibilities and shows the most skill during June through September, when Heidke skill scores are between 0.2 and 0.4. We demonstrate that the aerosol (clear sky) component of the GOES-R ABI visibility retrieval can be used to augment measurements from the United States Environmental Protection Agency (EPA) and National Park Service (NPS) Interagency Monitoring of Protected Visual Environments (IMPROVE) network, and provide useful information to the regional planning offices responsible for developing mitigation strategies required under the EPA's Regional Haze Rule, particularly during regional haze events associated with smoke from wildfires.

VizieR Online Data Catalog: Quasi-periodic pulsations in solar flares (Inglis+, 2016)

NASA Astrophysics Data System (ADS)

Inglis, A. R.; Ireland, J.; Dennis, B. R.; Hayes, L.; Gallagher, P.

2018-04-01

We have used data from the Geostationary Operational Environmental Satellite (GOES) instrument series, and from Fermi/Gamma-ray Burst Monitor (GBM). For this reason, we choose the interval 2011 February 1 - 2015 December 31, as it not only coincides with the availability of GOES-15 satellite data, but also includes regular solar observations by GBM. GOES satellites are equipped with solar X-ray detectors that record the incident flux in the 0.5-4Å and 1-8Å wavelength ranges. Solar X-ray data from the most recent satellite, GOES-15, has been available since 2010 at a nominal 2s cadence. To access the GOES catalog, we use the Heliophysics Event Knowledgebase (HEK). Fermi/GBM operates in the 8keV-40MeV range and regularly observes emission from solar flares, with a solar duty cycle of ~60%, similar to the solar-dedicated Reuven Ramaty High Energy Solar Spectroscopic Imager (RHESSI). To accumulate the database of Fermi/GBM events, we use the GBM trigger catalog produced by the instrument team, selecting all events marked as flares. (2 data files).

An Overview of Recent Geostationary Fire Monitoring Activities and Applications in the Western Hemisphere

NASA Astrophysics Data System (ADS)

McRae, D. J.; Conard, S. G.; Ivanova, G. A.; Sukhinin, A. I.; Hao, W. M.; Koutzenogii, K. P.; Prins, E. M.; Schmidt, C. C.; Feltz, J. M.

2002-05-01

Over the past twenty years the international scientific research and environmental monitoring communities have recognized the vital role environmental satellites can play in detecting and monitoring active fires both regionally and around the globe for hazards applications and to better understand the extent and impact of biomass burning on the global environment. Both groups have stressed the importance of utilizing operational satellites to produce routine fire products and to ensure long-term stable records of fire activity for applications such as land-use/land cover change analyses and global climate change research. The current NOAA GOES system provides the unique opportunity to detect fires throughout the Western Hemisphere every half-hour from a series of nearly identical satellites for a period of 15+ years. This presentation will provide an overview of the GOES biomass burning monitoring program at UW-Madison Cooperative Institute for Meteorological Satellite Studies (CIMSS) with an emphasis on recent applications of the new GOES Wildfire Automated Biomass Burning Algorithm (WF_ABBA). For the past 8 years, CIMSS has utilized the GOES-8 imager to monitor biomass burning trends in South America. Since September 2000, CIMSS has been producing half-hourly fire products in real-time for most of the Western Hemisphere. The WF_ABBA half-hourly fire product is providing new insights into diurnal, spatial, seasonal and interannual fire dynamics in North, Central, and South America. In North America these products are utilized to detect and monitor wildfires in northerly and remote locations. In South America the diurnal GOES fire product is being used as an indicator of land-use and land-cover change and carbon dynamics along the borders between Brazil, Peru, and Bolivia. The Navy is assimilating the Wildfire ABBA fire product into the Navy Aerosol Analysis and Prediction System (NAAPS) to analyze and predict aerosol loading and transport as part of the NASA-ESE Fire Locating And Mapping of Burning Emissions (FLAMBE) project. Furthermore, the dissemination and use of geostationary imagery and derived fire products in the Western Hemisphere provide a glimpse of future global geostationary fire monitoring capabilities. Global geostationary active fire monitoring will be possible with the launch of the European METEOSAT (METEOrological SATellite) Second Generation (MSG) and the replacement Japanese Multi-functional Transport Satellite (MTSAT-1R) over the next two years. This global network of geostationary satellites will complement the U.S. and international suite of environmental polar-orbiting satellites.

Parallel, stochastic measurement of molecular surface area.

PubMed

Juba, Derek; Varshney, Amitabh

2008-08-01

Biochemists often wish to compute surface areas of proteins. A variety of algorithms have been developed for this task, but they are designed for traditional single-processor architectures. The current trend in computer hardware is towards increasingly parallel architectures for which these algorithms are not well suited. We describe a parallel, stochastic algorithm for molecular surface area computation that maps well to the emerging multi-core architectures. Our algorithm is also progressive, providing a rough estimate of surface area immediately and refining this estimate as time goes on. Furthermore, the algorithm generates points on the molecular surface which can be used for point-based rendering. We demonstrate a GPU implementation of our algorithm and show that it compares favorably with several existing molecular surface computation programs, giving fast estimates of the molecular surface area with good accuracy.

Towards a Cloud Computing Environment: Near Real-time Cloud Product Processing and Distribution for Next Generation Satellites

NASA Astrophysics Data System (ADS)

Nguyen, L.; Chee, T.; Minnis, P.; Palikonda, R.; Smith, W. L., Jr.; Spangenberg, D.

2016-12-01

The NASA LaRC Satellite ClOud and Radiative Property retrieval System (SatCORPS) processes and derives near real-time (NRT) global cloud products from operational geostationary satellite imager datasets. These products are being used in NRT to improve forecast model, aircraft icing warnings, and support aircraft field campaigns. Next generation satellites, such as the Japanese Himawari-8 and the upcoming NOAA GOES-R, present challenges for NRT data processing and product dissemination due to the increase in temporal and spatial resolution. The volume of data is expected to increase to approximately 10 folds. This increase in data volume will require additional IT resources to keep up with the processing demands to satisfy NRT requirements. In addition, these resources are not readily available due to cost and other technical limitations. To anticipate and meet these computing resource requirements, we have employed a hybrid cloud computing environment to augment the generation of SatCORPS products. This paper will describe the workflow to ingest, process, and distribute SatCORPS products and the technologies used. Lessons learn from working on both AWS Clouds and GovCloud will be discussed: benefits, similarities, and differences that could impact decision to use cloud computing and storage. A detail cost analysis will be presented. In addition, future cloud utilization, parallelization, and architecture layout will be discussed for GOES-R.

A Synchronous Search for Documents

DTIC Science & Technology

An algorithm is described of a synchronous search in a complex system of selective retrieval of documents, with an allowance for exclusion of...stored on a magnetic tape. The number of topics served by the synchronous search goes into thousands; a search within 500-600 topics is performed without additional access to the tape.

Novel Semi-Parametric Algorithm for Interference-Immune Tunable Absorption Spectroscopy Gas Sensing

PubMed Central

Michelucci, Umberto; Venturini, Francesca

2017-01-01

One of the most common limits to gas sensor performance is the presence of unwanted interference fringes arising, for example, from multiple reflections between surfaces in the optical path. Additionally, since the amplitude and the frequency of these interferences depend on the distance and alignment of the optical elements, they are affected by temperature changes and mechanical disturbances, giving rise to a drift of the signal. In this work, we present a novel semi-parametric algorithm that allows the extraction of a signal, like the spectroscopic absorption line of a gas molecule, from a background containing arbitrary disturbances, without having to make any assumption on the functional form of these disturbances. The algorithm is applied first to simulated data and then to oxygen absorption measurements in the presence of strong fringes.To the best of the authors’ knowledge, the algorithm enables an unprecedented accuracy particularly if the fringes have a free spectral range and amplitude comparable to those of the signal to be detected. The described method presents the advantage of being based purely on post processing, and to be of extremely straightforward implementation if the functional form of the Fourier transform of the signal is known. Therefore, it has the potential to enable interference-immune absorption spectroscopy. Finally, its relevance goes beyond absorption spectroscopy for gas sensing, since it can be applied to any kind of spectroscopic data. PMID:28991161

New GOES High-Resolution Magnetic Measurements and their Contribution to Understanding Magnetospheric Particle Dynamics

NASA Astrophysics Data System (ADS)

Redmon, R. J.; Loto'aniu, P. T. M.; Boudouridis, A.; Chi, P. J.; Singer, H. J.; Kress, B. T.; Rodriguez, J. V.; Abdelqader, A.; Tilton, M.

2017-12-01

The era of NOAA observations of the geomagnetic field started with SMS-1 in May 1974 and continues to this day with GOES-13-16 (on-orbit). We describe the development of a new 20+ year archive of science-quality, high-cadence geostationary measurements of the magnetic field from eight NOAA spacecraft (GOES-8 through GOES-15), the status of GOES-16 and new scientific results using these data. GOES magnetic observations provide an early warning of impending space weather, are the core geostationary data set used for the construction of magnetospheric magnetic models, and can be used to estimate electromagnetic wave power in frequency bands important for plasma processes. Many science grade improvements are being made across the GOES archive to unify the format and content from GOES-8 through the new GOES-R series (with the first of that series launched on November 19, 2016). A majority of the 2-Hz magnetic observations from GOES-8-12 have never before been publicly accessible due to processing constraints. Now, a NOAA Big Earth Data Initiative project is underway to process these measurements starting from original telemetry records. Overall the new archive will include vector measurements in geophysically relevant coordinates (EPN, GSM, and VDH), comprehensive documentation, highest temporal cadence, best calibration parameters, recomputed means, updated quality flagging, full spacecraft ephemeris information, a unified standard format and public access. We are also developing spectral characterization tools for estimating power in standard frequency bands (up to 1 Hz for G8-15), and detecting ULF waves related to field-line resonances. We present the project status and findings, including in-situ statistical and extreme ULF event properties, and case studies where the ULF oscillations along the same field line were observed simultaneously by GOES near the equator in the magnetosphere, the ST-5 satellites at low altitudes, and ground magnetometer stations. For event studies, we find that the wave amplitude of poloidal oscillations is amplified at low altitudes but attenuated on the ground, confirming the theoretical predictions of wave propagation from the magnetosphere to the ground. We include examples of GOES-16 particle flux and magnetic field observations illustrating complex particle dynamics.

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

NASA Astrophysics Data System (ADS)

Kalia, S.; Li, S.; Ganguly, S.; Nemani, R. R.

2017-12-01

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 remotesensing. 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 iscritical. 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 classifycloud/shadow from Himawari-8 AHI and GOES-16 ABI multispectral data. DeepSAT's CloudCNN consists of an encoder-decoder 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 multi-spectral 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.

Maximizing the Science Output of GOES-R SUVI during Operations

NASA Astrophysics Data System (ADS)

Shaw, M.; Vasudevan, G.; Mathur, D. P.; Mansir, D.; Shing, L.; Edwards, C. G.; Seaton, D. B.; Darnel, J.; Nwachuku, C.

2017-12-01

Regular manual calibrations are an often-unavoidable demand on ground operations personnel during long-term missions. This paper describes a set of features built into the instrument control software and the techniques employed by the Solar Ultraviolet Imager (SUVI) team to automate a large fraction of regular on-board calibration activities, allowing SUVI to be operated with little manual commanding from the ground and little interruption to nominal sequencing. SUVI is a Generalized Cassegrain telescope with a large field of view that images the Sun in six extreme ultraviolet (EUV) narrow bandpasses centered at 9.4, 13.1, 17.1, 19.5, 28.4 and 30.4 nm. It is part of the payload of the Geostationary Operational Environmental Satellite (GOES-R) mission.

Physics-Based GOES Product for Use in NREL's National Solar Radiation Database: Preprint

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sengupta, Manajit; Habte, Aron; Gotseff, Peter

The Global Solar Insolation Project (GSIP) is an operational physical model from the National Oceanic and Atmospheric Administration (NOAA) that computes global horizontal radiation (GHI) using the visible and infrared channel measurements from geostationary operational environmental satellites (GOES). GSIP uses a two-stage scheme that retrieves cloud properties and uses those properties in the Satellite Algorithm for Surface Radiation Budget (SASRAB) model to calculate surface radiation. The National Renewable Energy Laboratory, University of Wisconsin, and NOAA have recently collaborated to adapt GSIP to create a high-temporal and spatial resolution data set. The data sets are currently being incorporated into the widelymore » used National Solar Radiation Data Base.« less

Flight and ground tests of a GOES satellite time receiver for satellite communications applications

NASA Technical Reports Server (NTRS)

Swanson, R. L.; Nichols, S. A.

1981-01-01

A satellite time receiver was tested in various environmental conditions during the past year. The commercial receiver designed to work with the National Oceanic and Atmospheric Administration's (NOAA) Geostationary Operational Environmental Satellites (GOES). The test program included operation at low elevation during flight in a military cargo aircraft and long term comparison with laboratory standards. The GOES satellite time receiver offers an opportunity to provide easy wide area coverage synchronization at low cost.

The S.M.A.R.T. Strategy to Recruiting and Retaining High School Coaches

ERIC Educational Resources Information Center

Lubisco, Robyn; Birren, Genevieve F. E.

2017-01-01

This article discusses the S.M.A.R.T. strategy for recruiting and retaining quality high school coaches. S.M.A.R.T. stands for Scouting, Mentoring and Coaching, Appreciation, Rating, and Time. Scouting addresses how one goes about locating and hiring quality coaches. Mentoring and Coaching addresses how to develop the coach within the specific…

Human Signatures for Personnel Detection

DTIC Science & Technology

2010-09-14

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Two-Column Aerosol Project (TCAP): Ground-Based Radiation and Aerosol Validation Using the NOAA Mobile SURFRAD Station Field Campaign Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Michalsky, Joseph; Lantz, Kathy

The National Oceanic and Atmospheric Administration (NOAA) is preparing for the launch of the Geostationary Operational Environmental Satellite R-Series (GOES-R) satellite in 2015. This satellite will feature higher time (5-minute versus 30-minute sampling) and spatial resolution (0.5 km vs 1 km in the visible channel) than current GOES instruments provide. NOAA’s National Environmental Satellite Data and Information Service has funded the Global Monitoring Division at the Earth System Research Laboratory to provide ground-based validation data for many of the new and old products the new GOES instruments will retrieve specifically related to radiation at the surface and aerosol and itsmore » extensive and intensive properties in the column. The Two-Column Aerosol Project (TCAP) had an emphasis on aerosol; therefore, we asked to be involved in this campaign to de-bug our new instrumentation and to provide a new capability that the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Climate Research Facility’s Mobile Facilities (AMF) did not possess, namely surface albedo measurement out to 1625 nm. This gave us a chance to test remote operation of our new multi-filter rotating shadowband radiometer/multi-filter radiometer (MFRSR/MFR) combination. We did not deploy standard broadband shortwave and longwave radiation instrumentation because ARM does this as part of every AMF deployment. As it turned out, the ARM standard MFRSR had issues, and we were able to provide the aerosol column data for the first 2 months of the campaign covering the summer flight phase of the deployment. Using these data, we were able to work with personnel at Pacific Northwest National Laboratory (PNNL) to retrieve not only aerosol optical depth (AOD), but single scattering albedo and asymmetry parameter, as well.« less

Improved target detection algorithm using Fukunaga-Koontz transform and distance classifier correlation filter

NASA Astrophysics Data System (ADS)

Bal, A.; Alam, M. S.; Aslan, M. S.

2006-05-01

Often sensor ego-motion or fast target movement causes the target to temporarily go out of the field-of-view leading to reappearing target detection problem in target tracking applications. Since the target goes out of the current frame and reenters at a later frame, the reentering location and variations in rotation, scale, and other 3D orientations of the target are not known thus complicating the detection algorithm has been developed using Fukunaga-Koontz Transform (FKT) and distance classifier correlation filter (DCCF). The detection algorithm uses target and background information, extracted from training samples, to detect possible candidate target images. The detected candidate target images are then introduced into the second algorithm, DCCF, called clutter rejection module, to determine the target coordinates are detected and tracking algorithm is initiated. The performance of the proposed FKT-DCCF based target detection algorithm has been tested using real-world forward looking infrared (FLIR) video sequences.

SPHERES National Lab Facility

NASA Technical Reports Server (NTRS)

Benavides, Jose

2014-01-01

SPHERES is a facility of the ISS National Laboratory with three IVA nano-satellites designed and delivered by MIT to research estimation, control, and autonomy algorithms. Since Fall 2010, The SPHERES system is now operationally supported and managed by NASA Ames Research Center (ARC). A SPHERES Program Office was established and is located at NASA Ames Research Center. The SPHERES Program Office coordinates all SPHERES related research and STEM activities on-board the International Space Station (ISS), as well as, current and future payload development. By working aboard ISS under crew supervision, it provides a risk tolerant Test-bed Environment for Distributed Satellite Free-flying Control Algorithms. If anything goes wrong, reset and try again! NASA has made the capability available to other U.S. government agencies, schools, commercial companies and students to expand the pool of ideas for how to test and use these bowling ball-sized droids. For many of the researchers, SPHERES offers the only opportunity to do affordable on-orbit characterization of their technology in the microgravity environment. Future utilization of SPHERES as a facility will grow its capabilities as a platform for science, technology development, and education.

Real-Time Cloud, Radiation, and Aircraft Icing Parameters from GOES over the USA

NASA Technical Reports Server (NTRS)

Minnis, Patrick; Nguyen, Louis; Smith, William, Jr.; Young, David; Khaiyer, Mandana; Palikonda, Rabindra; Spangenberg, Douglas; Doelling, Dave; Phan, Dung; Nowicki, Greg

2004-01-01

A preliminary new, physically based method for realtime estimation of the probability of icing conditions has been demonstrated using merged GOES-10 and 12 data over the continental United States and southern Canada. The algorithm produces pixel-level cloud and radiation properties as well as an estimate of icing probability with an associated intensity rating Because icing depends on so many different variables, such as aircraft size or air speed, it is not possible to achieve 100% success with this or any other type of approach. This initial algorithm, however, shows great promise for diagnosing aircraft icing and putting it at the correct altitude within 0.5 km most of the time. Much additional research must be completed before it can serve as a reliable input for the operational CIP. The delineation of the icing layer vertical boundaries will need to be improved using either the RUC or balloon soundings or ceilometer data to adjust the cloud base height, a change that would require adjustment of the cloud-top altitude also.

Fly's Eye GLM Simulator

NASA Image and Video Library

2017-07-27

The Fly’s Eye GLM Simulator (FEGS) is an airborne array of multi-spectral radiometers optimized to measure the optical emission from lightning. The instrument was designed by the Lightning Group in the Earth Science Office at the Marshall Space Flight Center as part of the validation effort for the first Geostationary Lightning Mapper (GLM) onboard GOES-16. From March to May of 2017, FEGS was flown on the NASA Armstrong Flight Research Center ER-2 along with a payload of other instruments during the GOES-16 Validation Flight Campaign. Data collected during the campaign are being analyzed by scientists at NASA and collaborating institutions to test the accuracy of GLM and other GOES-16 instruments. FEGS adds the capability to investigate sub-millisecond lightning energetics to the NASA Airborne Earth Science program. When flown with its complimentary suite of instruments, the FEGS package observes lightning radiation signatures that span from radio frequencies to gamma-ray emission. Learn more about the GOES-16 Validation Flight Campaign here: https://www.youtube.com/watch?v=rCTIk...

Colorado Lightning Mapping Array Collaborations through the GOES-R Visiting Scientist Program

NASA Technical Reports Server (NTRS)

Stano, Geoffrey T.; Szoke, Edward; Rydell, Nezette; Cox, Robert; Mazur, Rebecca

2014-01-01

For the past two years, the GOES-R Proving Ground has solicited proposals for its Visiting Scientist Program. NASA's Short-term Prediction Research and Transition (SPoRT) Center has used this opportunity to support the GOES-R Proving Ground by expanding SPoRT's total lightning collaborations. In 2012, this expanded the evaluation of SPoRT's pseudo-geostationary lightning mapper product to the Aviation Weather Center and Storm Prediction Center. This year, SPoRT has collaborated with the Colorado Lightning Mapping Array (COLMA) and potential end users. In particular, SPoRT is collaborating with the Cooperative Institute for Research in the Atmosphere (CIRA) and Colorado State University (CSU) to obtain these data in real-time. From there, SPoRT is supporting the transition of these data to the local forecast offices in Boulder, Colorado and Cheyenne, Wyoming as well as to Proving Ground projects (e.g., the Hazardous Weather Testbed's Spring Program and Aviation Weather Center's Summer Experiment). This presentation will focus on the results of this particular Visiting Scientist Program trip. In particular, the COLMA data are being provided to both forecast offices for initial familiarization. Additionally, several forecast issues have been highlighted as important uses for COLMA data in the operational environment. These include the utility of these data for fire weather situations, situational awareness for both severe weather and lightning safety, and formal evaluations to take place in the spring of 2014.

Multipole Algorithms for Molecular Dynamics Simulation on High Performance Computers.

NASA Astrophysics Data System (ADS)

Elliott, William Dewey

1995-01-01

A fundamental problem in modeling large molecular systems with molecular dynamics (MD) simulations is the underlying N-body problem of computing the interactions between all pairs of N atoms. The simplest algorithm to compute pair-wise atomic interactions scales in runtime {cal O}(N^2), making it impractical for interesting biomolecular systems, which can contain millions of atoms. Recently, several algorithms have become available that solve the N-body problem by computing the effects of all pair-wise interactions while scaling in runtime less than {cal O}(N^2). One algorithm, which scales {cal O}(N) for a uniform distribution of particles, is called the Greengard-Rokhlin Fast Multipole Algorithm (FMA). This work describes an FMA-like algorithm called the Molecular Dynamics Multipole Algorithm (MDMA). The algorithm contains several features that are new to N-body algorithms. MDMA uses new, efficient series expansion equations to compute general 1/r^{n } potentials to arbitrary accuracy. In particular, the 1/r Coulomb potential and the 1/r^6 portion of the Lennard-Jones potential are implemented. The new equations are based on multivariate Taylor series expansions. In addition, MDMA uses a cell-to-cell interaction region of cells that is closely tied to worst case error bounds. The worst case error bounds for MDMA are derived in this work also. These bounds apply to other multipole algorithms as well. Several implementation enhancements are described which apply to MDMA as well as other N-body algorithms such as FMA and tree codes. The mathematics of the cell -to-cell interactions are converted to the Fourier domain for reduced operation count and faster computation. A relative indexing scheme was devised to locate cells in the interaction region which allows efficient pre-computation of redundant information and prestorage of much of the cell-to-cell interaction. Also, MDMA was integrated into the MD program SIgMA to demonstrate the performance of the program over several simulation timesteps. One MD application described here highlights the utility of including long range contributions to Lennard-Jones potential in constant pressure simulations. Another application shows the time dependence of long range forces in a multiple time step MD simulation.

Site testing in Colombia : Identification of the least-worst places for optical telescopes

NASA Astrophysics Data System (ADS)

Pinzón, G.

2017-07-01

With the aim of identifying a set of least-worst sites for astronomical observations in Colombia we used a novel algorithm for the computation of the number of clear nights over an extended region covering Colombia and the western part of Venezuela. This algorithm compares the brightness temperatures of five years of GOES images with reference temperature values obtained from long-term records of monthly temperatures at ground and at heights of 8, 9 and 10 kilometers. Our predictions were validated with cloud cover information from the log-books of the Observatorio Nacional de Llano del Hato in Venezuela. Short and sporadic expeditions to four of those sites were also done from 2013 to 2015 in order to conduct measurements in-situ of temperature and humidity along the night, seeing, sky brightness and atmospheric extinction using basic instrumentation. The final conclusions have been derived solely on the basis of the actually visited sites. It was found that at Cañón del río Nevado the Seeing during the nights was more stable with rms=0.59'' and then a suitable and extended region (of almost 30 km) for the location of optical telescopes aimed to enhance astronomy research and outreach in the country.

Evaluation and modeling of autonomous attitude thrust control for the Geostation Operational Environmental Satellite (GOES)-8 orbit determination

NASA Technical Reports Server (NTRS)

Forcey, W.; Minnie, C. R.; Defazio, R. L.

1995-01-01

The Geostationary Operational Environmental Satellite (GOES)-8 experienced a series of orbital perturbations from autonomous attitude control thrusting before perigee raising maneuvers. These perturbations influenced differential correction orbital state solutions determined by the Goddard Space Flight Center (GSFC) Goddard Trajectory Determination System (GTDS). The maneuvers induced significant variations in the converged state vector for solutions using increasingly longer tracking data spans. These solutions were used for planning perigee maneuvers as well as initial estimates for orbit solutions used to evaluate the effectiveness of the perigee raising maneuvers. This paper discusses models for the incorporation of attitude thrust effects into the orbit determination process. Results from definitive attitude solutions are modeled as impulsive thrusts in orbit determination solutions created for GOES-8 mission support. Due to the attitude orientation of GOES-8, analysis results are presented that attempt to absorb the effects of attitude thrusting by including a solution for the coefficient of reflectivity, C(R). Models to represent the attitude maneuvers are tested against orbit determination solutions generated during real-time support of the GOES-8 mission. The modeling techniques discussed in this investigation offer benefits to the remaining missions in the GOES NEXT series. Similar missions with large autonomous attitude control thrusting, such as the Solar and Heliospheric Observatory (SOHO) spacecraft and the INTELSAT series, may also benefit from these results.

The Detection, Characterization and Tracking of Recent Aleutian Island Volcanic Ash Plumes and the Assessment of Their Impact on Aviation

NASA Technical Reports Server (NTRS)

Murray, John J.; Hudnall, L. A.; Matus, A.; Krueger, A. J.; Trepte, C. r.

2010-01-01

The Aleutian Islands of Alaska are home to a number of major volcanoes which periodically present a significant hazard to aviation. During summer of 2008, the Okmok and Kasatochi volcanoes experienced moderate eruptive events. These were followed a dramatic, major eruption of Mount Redoubt in late March 2009. The Redoubt case is extensively covered in this paper. Volcanic ash and SO2 from each of these eruptions dispersed throughout the atmosphere. This created the potential for major problems for air traffic near the ash dispersions and at significant distances downwind. The NASA Applied Sciences Weather Program implements a wide variety of research projects to develop volcanic ash detection, characterization and tracking applications for NASA Earth Observing System and NOAA GOES and POES satellites. Chemistry applications using NASA AURA satellite Ozone Monitoring System (OMI) retrievals produced SO2 measurements to trace the dispersion of volcanic aerosol. This work was complimented by advanced multi-channel imager applications for the discrimination and height assignment of volcanic ash using NASA MODIS and NOAA GOES and POES imager data. Instruments similar to MODIS and OMI are scheduled for operational deployment on NPOESS. In addition, the NASA Calipso satellite provided highly accurate measurements of aerosol height and dispersion for the calibration and validation of these algorithms and for corroborative research studies. All of this work shortens the lead time for transition to operations and ensures that research satellite data and applications are operationally relevant and utilized quickly after the deployment of operational satellite systems. Introduction

The GOES-R Geostationary Lightning Mapper (GLM) and the Global Observing System for Total Lightning

NASA Technical Reports Server (NTRS)

Goodman, Steven J.; Blakeslee, R. J.; Koshak, W.; Buechler, D.; Carey, L.; Chronis, T.; Mach, D.; Bateman, M.; Peterson, H.; McCaul, E. W., Jr.;

GOES-R SUVI EUV Flatfields Generated Using Boustrophedon Scans

NASA Astrophysics Data System (ADS)

Shing, L.; Edwards, C.; Mathur, D.; Vasudevan, G.; Shaw, M.; Nwachuku, C.

2017-12-01

The Solar Ultraviolet Imager (SUVI) is mounted on the Solar Pointing Platform (SPP) of the Geostationary Operational Environmental Satellite, GOES-R. SUVI is a Generalized Cassegrain telescope with a large field of view that employs multilayer coatings optimized to operate in six extreme ultraviolet (EUV) narrow bandpasses centered at 9.4, 13.1, 17.1, 19.5, 28.4 and 30.4 nm. The SUVI CCD flatfield response was determined using two different techniques; The Kuhn-Lin-Lorentz (KLL) Raster and a new technique called, Dynamic Boustrophedon Scans. The new technique requires less time to collect the data and is also less sensitive to Solar features compared with the KLL method. This paper presents the flatfield results of the SUVI using this technique during Post Launch Testing (PLT).

Study on light weight design of truss structures of spacecrafts

NASA Astrophysics Data System (ADS)

Zeng, Fuming; Yang, Jianzhong; Wang, Jian

2015-08-01

Truss structure is usually adopted as the main structure form for spacecrafts due to its high efficiency in supporting concentrated loads. Light-weight design is now becoming the primary concern during conceptual design of spacecrafts. Implementation of light-weight design on truss structure always goes through three processes: topology optimization, size optimization and composites optimization. During each optimization process, appropriate algorithm such as the traditional optimality criterion method, mathematical programming method and the intelligent algorithms which simulate the growth and evolution processes in nature will be selected. According to the practical processes and algorithms, combined with engineering practice and commercial software, summary is made for the implementation of light-weight design on truss structure for spacecrafts.

Education and Happiness in the School-to-Work Transition

ERIC Educational Resources Information Center

Dockery, Alfred Michael

2010-01-01

Education is generally seen as enhancing people's lives. However, previous research has reported an inverse relationship between education and happiness or satisfaction with life: as education level goes up, happiness goes down. Using data from the Longitudinal Surveys of Australian Youth (LSAY), this report examines the relationship between…

X-ray dose reduction in abdominal computed tomography using advanced iterative reconstruction algorithms.

PubMed

Ning, Peigang; Zhu, Shaocheng; Shi, Dapeng; Guo, Ying; Sun, Minghua

2014-01-01

This work aims to explore the effects of adaptive statistical iterative reconstruction (ASiR) and model-based iterative reconstruction (MBIR) algorithms in reducing computed tomography (CT) radiation dosages in abdominal imaging. CT scans on a standard male phantom were performed at different tube currents. Images at the different tube currents were reconstructed with the filtered back-projection (FBP), 50% ASiR and MBIR algorithms and compared. The CT value, image noise and contrast-to-noise ratios (CNRs) of the reconstructed abdominal images were measured. Volumetric CT dose indexes (CTDIvol) were recorded. At different tube currents, 50% ASiR and MBIR significantly reduced image noise and increased the CNR when compared with FBP. The minimal tube current values required by FBP, 50% ASiR, and MBIR to achieve acceptable image quality using this phantom were 200, 140, and 80 mA, respectively. At the identical image quality, 50% ASiR and MBIR reduced the radiation dose by 35.9% and 59.9% respectively when compared with FBP. Advanced iterative reconstruction techniques are able to reduce image noise and increase image CNRs. Compared with FBP, 50% ASiR and MBIR reduced radiation doses by 35.9% and 59.9%, respectively.

Electrostatic screening in classical Coulomb fluids: exponential or power-law decay or both? An investigation into the effect of dispersion interactions

NASA Astrophysics Data System (ADS)

Kjellander, Roland

2006-04-01

It is shown that the nature of the non-electrostatic part of the pair interaction potential in classical Coulomb fluids can have a profound influence on the screening behaviour. Two cases are compared: (i) when the non-electrostatic part equals an arbitrary finite-ranged interaction and (ii) when a dispersion r-6 interaction potential is included. A formal analysis is done in exact statistical mechanics, including an investigation of the bridge function. It is found that the Coulombic r-1 and the dispersion r-6 potentials are coupled in a very intricate manner as regards the screening behaviour. The classical one-component plasma (OCP) is a particularly clear example due to its simplicity and is investigated in detail. When the dispersion r-6 potential is turned on, the screened electrostatic potential from a particle goes from a monotonic exponential decay, exp(-κr)/r, to a power-law decay, r-8, for large r. The pair distribution function acquire, at the same time, an r-10 decay for large r instead of the exponential one. There still remains exponentially decaying contributions to both functions, but these contributions turn oscillatory when the r-6 interaction is switched on. When the Coulomb interaction is turned off but the dispersion r-6 pair potential is kept, the decay of the pair distribution function for large r goes over from the r-10 to an r-6 behaviour, which is the normal one for fluids of electroneutral particles with dispersion interactions. Differences and similarities compared to binary electrolytes are pointed out.

Alaska Imagery (GOES-WEST) - Satellite Services Division / Office of

Science.gov Websites

-- Dissemination Schedules METEOSAT MTSAT-1R POES -- Satellite Operations -- Satellite Status Pre-Processing Status Pre-Processing -- Dissemination Schedules Original SSD Links SSD Fire Products Precipitation

Hawaii Imagery (GOES-WEST) - Satellite Services Division / Office of

Science.gov Websites

-- Dissemination Schedules METEOSAT MTSAT-1R POES -- Satellite Operations -- Satellite Status Pre-Processing Status Pre-Processing -- Dissemination Schedules Original SSD Links SSD Fire Products Precipitation

Towards Verification and Validation for Increased Autonomy

NASA Technical Reports Server (NTRS)

Giannakopoulou, Dimitra

2017-01-01

This presentation goes over the work we have performed over the last few years on verification and validation of the next generation onboard collision avoidance system, ACAS X, for commercial aircraft. It describes our work on probabilistic verification and synthesis of the model that ACAS X is based on, and goes on to the validation of that model with respect to actual simulation and flight data. The presentation then moves on to identify the characteristics of ACAS X that are related to autonomy and to discuss the challenges that autonomy pauses on VV. All work presented has already been published.

Comparison of Nimbus-7 SMMR and GOES-1 VISSR Atmospheric Liquid Water Content.

NASA Astrophysics Data System (ADS)

Lojou, Jean-Yves; Frouin, Robert; Bernard, René

1991-02-01

Vertically integrated atmospheric liquid water content derived from Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR) brightness temperatures and from GOES-1 Visible and Infrared Spin-Scan Radiometer (VISSR) radiances in the visible are compared over the Indian Ocean during MONEX (monsoon experiment). In the retrieval procedure, Wilheit and Chang' algorithm and Stephens' parameterization schemes are applied to the SMMR and VISSR data, respectively. The results indicate that in the 0-100 mg cm2 range of liquid water content considered, the correlation coefficient between the two types of estimates is 0.83 (0.81- 0.85 at the 99 percent confidence level). The Wilheit and Chang algorithm, however, yields values lower than those obtained with Stephens's schemes by 24.5 mg cm2 on the average, and occasionally the SMMR-based values are negative. Alternative algorithms are proposed for use with SMMR data, which eliminate the bias, augment the correlation coefficient, and reduce the rms difference. These algorithms include using the Witheit and Chang formula with modified coefficients (multilinear regression), the Wilheit and Chang formula with the same coefficients but different equivalent atmospheric temperatures for each channel (temperature bias adjustment), and a second-order polynomial in brightness temperatures at 18, 21, and 37 GHz (polynomial development). When applied to a dataset excluded from the regressionn dataset, the multilinear regression algorithm provides the best results, namely a 0.91 correlation coefficient, a 5.2 mg cm2 (residual) difference, and a 2.9 mg cm2 bias. Simply shifting the liquid water content predicted by the Wilheit and Chang algorithm does not yield as good comparison statistics, indicating that the occasional negative values are not due only to a bias. The more accurate SMMR-derived liquid water content allows one to better evaluate cloud transmittance in the solar spectrum, at least in the area and during the period analyzed. Combining this cloud transmittance with a clear sky model would provide ocean surface insulation estimates from SMMR data alone.

Tuning of Kalman filter parameters via genetic algorithm for state-of-charge estimation in battery management system.

PubMed

Ting, T O; Man, Ka Lok; Lim, Eng Gee; Leach, Mark

2014-01-01

In this work, a state-space battery model is derived mathematically to estimate the state-of-charge (SoC) of a battery system. Subsequently, Kalman filter (KF) is applied to predict the dynamical behavior of the battery model. Results show an accurate prediction as the accumulated error, in terms of root-mean-square (RMS), is a very small value. From this work, it is found that different sets of Q and R values (KF's parameters) can be applied for better performance and hence lower RMS error. This is the motivation for the application of a metaheuristic algorithm. Hence, the result is further improved by applying a genetic algorithm (GA) to tune Q and R parameters of the KF. In an online application, a GA can be applied to obtain the optimal parameters of the KF before its application to a real plant (system). This simply means that the instantaneous response of the KF is not affected by the time consuming GA as this approach is applied only once to obtain the optimal parameters. The relevant workable MATLAB source codes are given in the appendix to ease future work and analysis in this area.

Tuning of Kalman Filter Parameters via Genetic Algorithm for State-of-Charge Estimation in Battery Management System

PubMed Central

Ting, T. O.; Lim, Eng Gee

2014-01-01

In this work, a state-space battery model is derived mathematically to estimate the state-of-charge (SoC) of a battery system. Subsequently, Kalman filter (KF) is applied to predict the dynamical behavior of the battery model. Results show an accurate prediction as the accumulated error, in terms of root-mean-square (RMS), is a very small value. From this work, it is found that different sets of Q and R values (KF's parameters) can be applied for better performance and hence lower RMS error. This is the motivation for the application of a metaheuristic algorithm. Hence, the result is further improved by applying a genetic algorithm (GA) to tune Q and R parameters of the KF. In an online application, a GA can be applied to obtain the optimal parameters of the KF before its application to a real plant (system). This simply means that the instantaneous response of the KF is not affected by the time consuming GA as this approach is applied only once to obtain the optimal parameters. The relevant workable MATLAB source codes are given in the appendix to ease future work and analysis in this area. PMID:25162041

KSC01pp0799

NASA Image and Video Library

2001-04-12

Workers at Astrotech, Titusville, Fla., work on the GOES-M satellite. The GOES-M provides weather imagery and quantitative sounding data used to support weather forecasting, severe storm tracking and meteorological research. The satellite is undergoing testing at Astrotech before its scheduled launch July 12 on an Atlas-IIA booster, Centaur upper stage from Cape Canaveral Air Force Station

Neural Nets for Generalization and Classification: Comment on Staddon and Reid (1990).

ERIC Educational Resources Information Center

Shepard, Roger N.

1990-01-01

The neural net model of J. E. R. Staddon and A. K. Reid (1990) explains exponential and Gaussian generalization gradients in the same way as the diffusion model of R. N. Shepard (1958). The cognitive generalization theory of Shepard (1987), also implemented as a connectionist network, goes beyond both models in accounting for classification…

Report of the Presidential Commission on the Space Shuttle Challenger Accident. Volume 4 and 5

DTIC Science & Technology

1986-06-06

protected with what we call a milk can. It is a stainless steel fairing that goes, which has cork on it to protect the cabling between the 880 external...miiST*? ■pt*-r~A**’ j>stffnr*ss Kie^z*-vr-kjjy-if,*j 1 tf/m • \\eni-r iu.Lr>sw*> rvF - pi^nf- a-*&*=- ro e^r^r /rs ^-/-’■■uut.T-tK. |UO Af^-f-JfriT^J

Multi Scale Multi Temporal Near Real Time Approach for Volcanic Eruptions monitoring, Test Case: Mt Etna eruption 2017

NASA Astrophysics Data System (ADS)

Buongiorno, M. F.; Silvestri, M.; Musacchio, M.

2017-12-01

In this work a complete processing chain from the detection of the beginning of eruption to the estimation of lava flow temperature on active volcanoes using remote sensing data is presented showing the results for the Mt. Etna eruption on March 2017. The early detection of new eruption is based on the potentiality ensured by geostationary very low spatial resolution satellite (3x3 km in nadiral view), the hot spot/lava flow evolution is derived by S2 polar medium/high spatial resolution (20x20 mt) while the surface temperature is estimated by polar medium/low spatial resolution such as L8, ASTER and S3 (from 90 mt up to 1km).This approach merges two outcome derived by activity performed for monitoring purposes within INGV R&D activities and the results obtained by Geohazards Exploitation Platform ESA funded project (GEP) aimed to the development of shared platform for providing services based on EO data. Because the variety of phenomena to be analyzed a multi temporal multi scale approach has been used to implement suitable and robust algorithms for the different sensors. With the exception of Sentinel 2 (MSI) data, for which the algorithm used is based on NIR-SWIR bands, we exploit the MIR-TIR channels of L8, ASTER, S3 and SEVIRI for generating automatically the surface thermal state analysis. The developed procedure produces time series data and allows to extract information from each single co-registered pixel, to highlight variation of temperatures within specific areas. The final goal is to implement an easy tool which enables scientists and users to extract valuable information from satellite time series at different scales produced by ESA and EUMETSAT in the frame of Europe's Copernicus program and other Earth observation satellites programs such as LANDSAT (USGS) and GOES (NOAA).

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

NASA Technical Reports Server (NTRS)

Kalia, Subodh; Ganguly, Sangram; Li, Shuang; Nemani, Ramakrishna R.

2017-01-01

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.

Development of an Algorithm for Satellite Remote Sensing of Sea and Lake Ice

NASA Astrophysics Data System (ADS)

Dorofy, Peter T.

Satellite remote sensing of snow and ice has a long history. The traditional method for many snow and ice detection algorithms has been the use of the Normalized Difference Snow Index (NDSI). This manuscript is composed of two parts. Chapter 1, Development of a Mid-Infrared Sea and Lake Ice Index (MISI) using the GOES Imager, discusses the desirability, development, and implementation of alternative index for an ice detection algorithm, application of the algorithm to the detection of lake ice, and qualitative validation against other ice mapping products; such as, the Ice Mapping System (IMS). Chapter 2, Application of Dynamic Threshold in a Lake Ice Detection Algorithm, continues with a discussion of the development of a method that considers the variable viewing and illumination geometry of observations throughout the day. The method is an alternative to Bidirectional Reflectance Distribution Function (BRDF) models. Evaluation of the performance of the algorithm is introduced by aggregating classified pixels within geometrical boundaries designated by IMS and obtaining sensitivity and specificity statistical measures.

GOES-R Dual Isolation

NASA Technical Reports Server (NTRS)

Freesland, Doug; Carter, Delano; Chapel, Jim; Clapp, Brian; Howat, John; Krimchansky, Alexander

2015-01-01

The Geostationary Operational Environmental Satellite-R Series (GOES-R) is the first of the next generation geostationary weather satellites, scheduled for delivery in late 2015. GOES-R represents a quantum increase in Earth and solar weather observation capabilities, with 4 times the resolution, 5 times the observation rate, and 3 times the number of spectral bands for Earth observations. With the improved resolution, comes the instrument suite's increased sensitive to disturbances over a broad spectrum 0-512 Hz. Sources of disturbance include reaction wheels, thruster firings for station keeping and momentum management, gimbal motion, and internal instrument disturbances. To minimize the impact of these disturbances, the baseline design includes an Earth Pointed Platform (EPP), a stiff optical bench to which the two nadir pointed instruments are collocated together with the Guidance Navigation & Control (GN&C) star trackers and Inertial Measurement Units (IMUs). The EPP is passively isolated from the spacecraft bus with Honeywell D-Strut isolators providing attenuation for frequencies above approximately 5 Hz in all six degrees-of-freedom. A change in Reaction Wheel Assembly (RWA) vendors occurred very late in the program. To reduce the risk of RWA disturbances impacting performance, a secondary passive isolation system manufactured by Moog CSA Engineering was incorporated under each of the six 160 Nms RWAs, tuned to provide attenuation at frequencies above approximately 50 Hz. Integrated wheel and isolator testing was performed on a Kistler table at NASA Goddard Space Flight Center. High fidelity simulations were conducted to evaluate jitter performance for four topologies: 1) hard mounted no isolation, 2) EPP isolation only, 2) RWA isolation only, and 4) dual isolation. Simulation results demonstrate excellent performance relative to the pointing stability requirements, with dual isolated Line of Sight (LOS) jitter less than 1 micron rad.

Pure field theories and MACSYMA algorithms

NASA Technical Reports Server (NTRS)

Ament, W. S.

1977-01-01

A pure field theory attempts to describe physical phenomena through singularity-free solutions of field equations resulting from an action principle. The physics goes into forming the action principle and interpreting specific results. Algorithms for the intervening mathematical steps are sketched. Vacuum general relativity is a pure field theory, serving as model and providing checks for generalizations. The fields of general relativity are the 10 components of a symmetric Riemannian metric tensor; those of the Einstein-Straus generalization are the 16 components of a nonsymmetric. Algebraic properties are exploited in top level MACSYMA commands toward performing some of the algorithms of that generalization. The light cone for the theory as left by Einstein and Straus is found and simplifications of that theory are discussed.

[The work of R.T.H. Laennec at the Necker Hospital, then Charity Hospital from 1821 to 1826].

PubMed

Dubois, Charles

2006-01-01

His bad health obliged RTH Laennec to interrupt his hospital activities from 1819 to 1821. He goes back to his head functions in Necker's then Charity's Hospitals from 1821 to 1826. His others activities, especially teaching, affect his busy time table. His unit's recruitment is less specialized in thoracic pathologies than it was from 1816 to 1819. It is true that his "Collège of France Lessons" as his lectures, in the faculty of medicine concern all the clinical aspects. So the links between hospital activities and the second edition of his Treaty are not so strong as they were with the first one.

Meteorological Satellite Education Resources: Web-based Learning Modules, Initiatives, and the Environmental Satellite Resource Center (ESRC)

NASA Astrophysics Data System (ADS)

Schreiber-Abshire, W.; Dills, P.

2008-12-01

The COMET® Program (www.comet.ucar.edu) receives funding from NOAA NESDIS and the NPOESS Integrated Program Office (IPO), with additional contributions from the GOES-R Program Office and EUMETSAT, to directly support education and training efforts in the area of satellite meteorology. This partnership enables COMET to create educational materials of global interest on geostationary and polar- orbiting remote sensing platforms and their instruments, data, products, and operational applications. Over the last several years, COMET's satellite education programs have focused on the capabilities and applications of the upcoming next generation operational polar-orbiting NPP/NPOESS system and its relevance to operational forecasters and other user communities. COMET's activities have recently expanded to include education on the future Geostationary Operational Environmental Satellites (GOES-R). By partnering with experts from the Naval Research Laboratory, NOAA-NESDIS and various user communities, COMET stimulates greater utilization of both current and future satellite observations and products. In addition, COMET has broadened the scope of its online training to include materials on the EUMETSAT Polar-orbiting System (EPS) and Meteosat geostationary satellites. EPS represents an important contribution to the Initial Joint Polar System (IJPS) between NOAA and EUMETSAT, while Meteosat imaging capabilities provide an early look for the next generation GOES-R satellites. Also in collaboration with EUMETSAT, COMET is developing future modules on the joint NASA-CNES Jason altimetry mission and on satellite capabilities for monitoring the global climate. COMET also provides Spanish translations of relevant GOES materials in order to support the GEOSS (Global Earth Observation System of Systems) Americas effort, which is associated with the move of GOES-10 to provide routine satellite coverage over South America. This poster presentation provides an overview of COMET's recent satellite training efforts and publications, highlighting new materials relevant to both polar-orbiting and geostationary satellites. The presentation also showcases COMET's new community-drive Website, the Environmental Satellite Resource Center (ESRC), sponsored by the NPOESS IPO, NOAA, and NESDIS. The ESRC (www.meted.ucar.edu/ESRC) provides search capabilities and free access to a wide range of polar-orbiting and geostationary satellite information and training resources from multiple trusted sources, including MetEd (www.meted.ucar.edu).

Assimilation of GOES satellite-based convective initiation and cloud growth observations into the Rapid Refresh and HRRR systems to improve aviation forecast guidance

NASA Astrophysics Data System (ADS)

Mecikalski, John; Smith, Tracy; Weygandt, Stephen

2014-05-01

Latent heating profiles derived from GOES satellite-based cloud-top cooling rates are being assimilated into a retrospective version of the Rapid Refresh system (RAP) being run at the Global Systems Division. Assimilation of these data may help reduce the time lag for convection initiation (CI) in both the RAP model forecasts and in 3-km High Resolution Rapid Refresh (HRRR) model runs that are initialized off of the RAP model grids. These data may also improve both the location and organization of developing convective storm clusters, especially in the nested HRRR runs. These types of improvements are critical for providing better convective storm guidance around busy hub airports and aviation corridor routes, especially in the highly congested Ohio Valley - Northeast - Mid-Atlantic region. Additional work is focusing on assimilating GOES-R CI algorithm cloud-top cooling-based latent heating profiles directly into the HRRR model. Because of the small-scale nature of the convective phenomena depicted in the cloud-top cooling rate data (on the order of 1-4 km scale), direct assimilation of these data in the HRRR may be more effective than assimilation in the RAP. The RAP is an hourly assimilation system developed at NOAA/ESRL and was implemented at NCEP as a NOAA operational model in May 2012. The 3-km HRRR runs hourly out to 15 hours as a nest within the ESRL real-time experimental RAP. The RAP and HRRR both use the WRF ARW model core, and the Gridpoint Statistical Interpolation (GSI) is used within an hourly cycle to assimilate a wide variety of observations (including radar data) to initialize the RAP. Within this modeling framework, the cloud-top cooling rate-based latent heating profiles are applied as prescribed heating during the diabatic forward model integration part of the RAP digital filter initialization (DFI). No digital filtering is applied on the 3-km HRRR grid, but similar forward model integration with prescribed heating is used to assimilate information from radar reflectivity, lightning flash density and the satellite based cloud-top cooling rate data. In the current HRRR configuration, 4 15-min cycles of latent heating are applied during a pre-forecast hour of integration. This is followed by a final application of GSI at 3-km to fit the latest conventional observation data. At the conference, results from a 5-day retrospective period (July 5-10, 2012) will be shown, focusing on assessment of data impact for both the RAP and HRRR, as well as the sensitivity to various assimilation parameters, including assumed heating strength. Emphasis will be given to documenting the forecast impacts for aviation applications in the Eastern U.S.

DD3MAT - a code for yield criteria anisotropy parameters identification.

NASA Astrophysics Data System (ADS)

Barros, P. D.; Carvalho, P. D.; Alves, J. L.; Oliveira, M. C.; Menezes, L. F.

2016-08-01

This work presents the main strategies and algorithms adopted in the DD3MAT inhouse code, specifically developed for identifying the anisotropy parameters. The algorithm adopted is based on the minimization of an error function, using a downhill simplex method. The set of experimental values can consider yield stresses and r -values obtained from in-plane tension, for different angles with the rolling direction (RD), yield stress and r -value obtained for biaxial stress state, and yield stresses from shear tests performed also for different angles to RD. All these values can be defined for a specific value of plastic work. Moreover, it can also include the yield stresses obtained from in-plane compression tests. The anisotropy parameters are identified for an AA2090-T3 aluminium alloy, highlighting the importance of the user intervention to improve the numerical fit.

Detection of supercooled liquid water-topped mixed-phase clouds >from shortwave-infrared satellite observations

NASA Astrophysics Data System (ADS)

NOH, Y. J.; Miller, S. D.; Heidinger, A. K.

2015-12-01

Many studies have demonstrated the utility of multispectral information from satellite passive radiometers for detecting and retrieving the properties of cloud globally, which conventionally utilizes shortwave- and thermal-infrared bands. However, the satellite-derived cloud information comes mainly from cloud top or represents a vertically integrated property. This can produce a large bias in determining cloud phase characteristics, in particular for mixed-phase clouds which are often observed to have supercooled liquid water at cloud top but a predominantly ice phase residing below. The current satellite retrieval algorithms may report these clouds simply as supercooled liquid without any further information regarding the presence of a sub-cloud-top ice phase. More accurate characterization of these clouds is very important for climate models and aviation applications. In this study, we present a physical basis and preliminary results for the algorithm development of supercooled liquid-topped mixed-phase cloud detection using satellite radiometer observations. The detection algorithm is based on differential absorption properties between liquid and ice particles in the shortwave-infrared bands. Solar reflectance data in narrow bands at 1.6 μm and 2.25 μm are used to optically probe below clouds for distinction between supercooled liquid-topped clouds with and without an underlying mixed phase component. Varying solar/sensor geometry and cloud optical properties are also considered. The spectral band combination utilized for the algorithm is currently available on Suomi NPP Visible/Infrared Imaging Radiometer Suite (VIIRS), Himawari-8 Advanced Himawari Imager (AHI), and the future GOES-R Advance Baseline Imager (ABI). When tested on simulated cloud fields from WRF model and synthetic ABI data, favorable results were shown with reasonable threat scores (0.6-0.8) and false alarm rates (0.1-0.2). An ARM/NSA case study applied to VIIRS data also indicated promising potential of the algorithm.

Near-Real-Time Detection and Monitoring of Intense Pyroconvection from Geostationary Satellites

NASA Astrophysics Data System (ADS)

Peterson, D. A.; Fromm, M. D.; Hyer, E. J.; Surratt, M. L.; Solbrig, J. E.; Campbell, J. R.

2016-12-01

Intense fire-triggered thunderstorms, known as pyrocumulonimbus (or pyroCb), can alter fire behavior, influence smoke plume trajectories, and hinder fire suppression efforts. PyroCb are also known for injecting a significant quantity of aerosol mass into the upper-troposphere and lower-stratosphere (UTLS). Near-real-time (NRT) detection and monitoring of pyroCb is highly desirable for a variety of forecasting and research applications. The Naval Research Laboratory (NRL) recently developed the first automated NRT pyroCb detection algorithm for geostationary satellite sensors. The algorithm uses multispectral infrared observations to isolate deep convective clouds with the distinct microphysical signal of pyroCb. Application of this algorithm to 88 intense wildfires observed during the 2013 fire season in western North America resulted in detection of individual intense events, pyroCb embedded within traditional convection, and multiple, short-lived pulses of activity. Comparisons with a community inventory indicate that this algorithm captures the majority of pyroCb. The primary limitation of the current system is that pyroCb anvils can be small relative to satellite pixel size, especially in in regions with large viewing angles. The algorithm is also sensitive to some false positives from traditional convection that either ingests smoke or exhibits extreme updraft velocities. This algorithm has been automated using the GeoIPS processing system developed at NRL, which produces a variety of imagery products and statistical output for rapid analysis of potential pyroCb events. NRT application of this algorithm has been extended to the majority of regions worldwide known to have a high frequency of pyroCb occurrence. This involves a constellation comprised of GOES-East, GOES-West, and Himawari-8. Imagery is posted immediately to an NRL-maintained web page. Alerts are generated by the system and disseminated via email. This detection system also has potential to serve as a data source for other NRT environmental monitoring systems. While the current geostationary constellation has several important limitations, the next-generation of geostationary sensors will offer significant advantages for achieving the goal of global NRT pyroCb detection.

Numerical Polynomial Homotopy Continuation Method and String Vacua

DOE PAGES

Mehta, Dhagash

2011-01-01

Finding vmore » acua for the four-dimensional effective theories for supergravity which descend from flux compactifications and analyzing them according to their stability is one of the central problems in string phenomenology. Except for some simple toy models, it is, however, difficult to find all the vacua analytically. Recently developed algorithmic methods based on symbolic computer algebra can be of great help in the more realistic models. However, they suffer from serious algorithmic complexities and are limited to small system sizes. In this paper, we review a numerical method called the numerical polynomial homotopy continuation (NPHC) method, first used in the areas of lattice field theories, which by construction finds all of the vacua of a given potential that is known to have only isolated solutions. The NPHC method is known to suffer from no major algorithmic complexities and is embarrassingly parallelizable , and hence its applicability goes way beyond the existing symbolic methods. We first solve a simple toy model as a warm-up example to demonstrate the NPHC method at work. We then show that all the vacua of a more complicated model of a compactified M theory model, which has an S U ( 3 ) structure, can be obtained by using a desktop machine in just about an hour, a feat which was reported to be prohibitively difficult by the existing symbolic methods. Finally, we compare the various technicalities between the two methods.« less

Automated Dynamic Demand Response Implementation on a Micro-grid

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kuppannagari, Sanmukh R.; Kannan, Rajgopal; Chelmis, Charalampos

In this paper, we describe a system for real-time automated Dynamic and Sustainable Demand Response with sparse data consumption prediction implemented on the University of Southern California campus microgrid. Supply side approaches to resolving energy supply-load imbalance do not work at high levels of renewable energy penetration. Dynamic Demand Response (D 2R) is a widely used demand-side technique to dynamically adjust electricity consumption during peak load periods. Our D 2R system consists of accurate machine learning based energy consumption forecasting models that work with sparse data coupled with fast and sustainable load curtailment optimization algorithms that provide the ability tomore » dynamically adapt to changing supply-load imbalances in near real-time. Our Sustainable DR (SDR) algorithms attempt to distribute customer curtailment evenly across sub-intervals during a DR event and avoid expensive demand peaks during a few sub-intervals. It also ensures that each customer is penalized fairly in order to achieve the targeted curtailment. We develop near linear-time constant-factor approximation algorithms along with Polynomial Time Approximation Schemes (PTAS) for SDR curtailment that minimizes the curtailment error defined as the difference between the target and achieved curtailment values. Our SDR curtailment problem is formulated as an Integer Linear Program that optimally matches customers to curtailment strategies during a DR event while also explicitly accounting for customer strategy switching overhead as a constraint. We demonstrate the results of our D 2R system using real data from experiments performed on the USC smartgrid and show that 1) our prediction algorithms can very accurately predict energy consumption even with noisy or missing data and 2) our curtailment algorithms deliver DR with extremely low curtailment errors in the 0.01-0.05 kWh range.« less

Comparing MODIS-Terra and GOES surface albedo for New York City NY, Baltimore MD and Washington DC for 2005

NASA Astrophysics Data System (ADS)

Mubenga, K.; Hoff, R.; McCann, K.; Chu, A.; Prados, A.

2006-05-01

The NOAA GOES Aerosol and Smoke Product (GASP) is a product displaying the Aerosol Optical Depth (AOD) over the United States. The GASP retrieval involves discriminating the upwelling radiance from the atmosphere from that of the variable underlying surface. Unlike other sensors with more visible and near- infrared spectral channels such as MODIS, the sensors on GOES 8 through 12 only have one visible and a several far infrared channels. The GASP algorithm uses the detection of the second-darkest pixel from the visible channel over a 28-day period as the reference from which a radiance look-up table gives the corresponding AOD. GASP is reliable in capturing the AOD during large events. As an example, GASP was able to precisely show the Alaska and British Columbia smoke plume advecting from Alaska to the northeastern U.S. during the summer of 2004. Knapp et al. (2005) has shown that the AOD retrieval for GOES- 8 is within +/-0.13 of AERONET ground data with a coefficient of correlation of 0.72. Prados (this meeting) will update that study. However, GASP may not be as reliable when it comes to observing smaller AOD events in the northeast where the surface brightness is relatively high. The presence of large cities, such as New York, increases the surface albedo and produces a bright background against which it may be difficult to deduce the AOD. The Moderate Resolution Imaging Spectroradiometer (MODIS) sensor on the Earth Observing System Terra and Aqua platforms provides an independent measurement of the surface albedo at a resolution greater than available on GOES. In this research, the MODIS and GOES surface albedo product for New York, Washington and Baltimore are compared in order to see how we can improve the AOD retrieval in urban areas for air quality applications. Ref: K. Knapp et al. 2005. Toward aerosol optical depth retrievals over land from GOES visible radiances: determining surface reflectance. Int.Journal of Remote Sensing 26, 4097-4116

Putting It All Together: A Unified Account of Word Recognition and Reaction-Time Distributions

ERIC Educational Resources Information Center

Norris, Dennis

2009-01-01

R. Ratcliff, P. Gomez, and G. McKoon (2004) suggested much of what goes on in lexical decision is attributable to decision processes and may not be particularly informative about word recognition. They proposed that lexical decision should be characterized by a decision process, taking the form of a drift-diffusion model (R. Ratcliff, 1978), that…

Reducing the time requirement of k-means algorithm.

PubMed

Osamor, Victor Chukwudi; Adebiyi, Ezekiel Femi; Oyelade, Jelilli Olarenwaju; Doumbia, Seydou

2012-01-01

Traditional k-means and most k-means variants are still computationally expensive for large datasets, such as microarray data, which have large datasets with large dimension size d. In k-means clustering, we are given a set of n data points in d-dimensional space R(d) and an integer k. The problem is to determine a set of k points in R(d), called centers, so as to minimize the mean squared distance from each data point to its nearest center. In this work, we develop a novel k-means algorithm, which is simple but more efficient than the traditional k-means and the recent enhanced k-means. Our new algorithm is based on the recently established relationship between principal component analysis and the k-means clustering. We provided the correctness proof for this algorithm. Results obtained from testing the algorithm on three biological data and six non-biological data (three of these data are real, while the other three are simulated) also indicate that our algorithm is empirically faster than other known k-means algorithms. We assessed the quality of our algorithm clusters against the clusters of a known structure using the Hubert-Arabie Adjusted Rand index (ARI(HA)). We found that when k is close to d, the quality is good (ARI(HA)>0.8) and when k is not close to d, the quality of our new k-means algorithm is excellent (ARI(HA)>0.9). In this paper, emphases are on the reduction of the time requirement of the k-means algorithm and its application to microarray data due to the desire to create a tool for clustering and malaria research. However, the new clustering algorithm can be used for other clustering needs as long as an appropriate measure of distance between the centroids and the members is used. This has been demonstrated in this work on six non-biological data.

Method for hyperspectral imagery exploitation and pixel spectral unmixing

NASA Technical Reports Server (NTRS)

Lin, Ching-Fang (Inventor)

2003-01-01

An efficiently hybrid approach to exploit hyperspectral imagery and unmix spectral pixels. This hybrid approach uses a genetic algorithm to solve the abundance vector for the first pixel of a hyperspectral image cube. This abundance vector is used as initial state in a robust filter to derive the abundance estimate for the next pixel. By using Kalman filter, the abundance estimate for a pixel can be obtained in one iteration procedure which is much fast than genetic algorithm. The output of the robust filter is fed to genetic algorithm again to derive accurate abundance estimate for the current pixel. The using of robust filter solution as starting point of the genetic algorithm speeds up the evolution of the genetic algorithm. After obtaining the accurate abundance estimate, the procedure goes to next pixel, and uses the output of genetic algorithm as the previous state estimate to derive abundance estimate for this pixel using robust filter. And again use the genetic algorithm to derive accurate abundance estimate efficiently based on the robust filter solution. This iteration continues until pixels in a hyperspectral image cube end.

Global Precipitation Measurement (GPM) Ground Validation (GV) Science Implementation Plan

NASA Technical Reports Server (NTRS)

Petersen, Walter A.; Hou, Arthur Y.

2008-01-01

For pre-launch algorithm development and post-launch product evaluation Global Precipitation Measurement (GPM) Ground Validation (GV) goes beyond direct comparisons of surface rain rates between ground and satellite measurements to provide the means for improving retrieval algorithms and model applications.Three approaches to GPM GV include direct statistical validation (at the surface), precipitation physics validation (in a vertical columns), and integrated science validation (4-dimensional). These three approaches support five themes: core satellite error characterization; constellation satellites validation; development of physical models of snow, cloud water, and mixed phase; development of cloud-resolving model (CRM) and land-surface models to bridge observations and algorithms; and, development of coupled CRM-land surface modeling for basin-scale water budget studies and natural hazard prediction. This presentation describes the implementation of these approaches.

Optimal Limited Contingency Planning

NASA Technical Reports Server (NTRS)

Meuleau, Nicolas; Smith, David E.

2003-01-01

For a given problem, the optimal Markov policy over a finite horizon is a conditional plan containing a potentially large number of branches. However, there are applications where it is desirable to strictly limit the number of decision points and branches in a plan. This raises the question of how one goes about finding optimal plans containing only a limited number of branches. In this paper, we present an any-time algorithm for optimal k-contingency planning. It is the first optimal algorithm for limited contingency planning that is not an explicit enumeration of possible contingent plans. By modelling the problem as a partially observable Markov decision process, it implements the Bellman optimality principle and prunes the solution space. We present experimental results of applying this algorithm to some simple test cases.

High-order Newton-penalty algorithms

NASA Astrophysics Data System (ADS)

Dussault, Jean-Pierre

2005-10-01

Recent efforts in differentiable non-linear programming have been focused on interior point methods, akin to penalty and barrier algorithms. In this paper, we address the classical equality constrained program solved using the simple quadratic loss penalty function/algorithm. The suggestion to use extrapolations to track the differentiable trajectory associated with penalized subproblems goes back to the classic monograph of Fiacco & McCormick. This idea was further developed by Gould who obtained a two-steps quadratically convergent algorithm using prediction steps and Newton correction. Dussault interpreted the prediction step as a combined extrapolation with respect to the penalty parameter and the residual of the first order optimality conditions. Extrapolation with respect to the residual coincides with a Newton step.We explore here higher-order extrapolations, thus higher-order Newton-like methods. We first consider high-order variants of the Newton-Raphson method applied to non-linear systems of equations. Next, we obtain improved asymptotic convergence results for the quadratic loss penalty algorithm by using high-order extrapolation steps.

Development of an algorithm for automatic detection and rating of squeak and rattle events

NASA Astrophysics Data System (ADS)

Chandrika, Unnikrishnan Kuttan; Kim, Jay H.

2010-10-01

A new algorithm for automatic detection and rating of squeak and rattle (S&R) events was developed. The algorithm utilizes the perceived transient loudness (PTL) that approximates the human perception of a transient noise. At first, instantaneous specific loudness time histories are calculated over 1-24 bark range by applying the analytic wavelet transform and Zwicker loudness transform to the recorded noise. Transient specific loudness time histories are then obtained by removing estimated contributions of the background noise from instantaneous specific loudness time histories. These transient specific loudness time histories are summed to obtain the transient loudness time history. Finally, the PTL time history is obtained by applying Glasberg and Moore temporal integration to the transient loudness time history. Detection of S&R events utilizes the PTL time history obtained by summing only 18-24 barks components to take advantage of high signal-to-noise ratio in the high frequency range. A S&R event is identified when the value of the PTL time history exceeds the detection threshold pre-determined by a jury test. The maximum value of the PTL time history is used for rating of S&R events. Another jury test showed that the method performs much better if the PTL time history obtained by summing all frequency components is used. Therefore, r ating of S&R events utilizes this modified PTL time history. Two additional jury tests were conducted to validate the developed detection and rating methods. The algorithm developed in this work will enable automatic detection and rating of S&R events with good accuracy and minimum possibility of false alarm.

Compact, high-speed algorithm for laying out printed circuit board runs

NASA Astrophysics Data System (ADS)

Zapolotskiy, D. Y.

1985-09-01

A high speed printed circuit connection layout algorithm is described which was developed within the framework of an interactive system for designing two-sided printed circuit broads. For this reason, algorithm speed was considered, a priori, as a requirement equally as important as the inherent demand for minimizing circuit run lengths and the number of junction openings. This resulted from the fact that, in order to provide psychological man/machine compatibility in the design process, real-time dialog during the layout phase is possible only within limited time frames (on the order of several seconds) for each circuit run. The work was carried out for use on an ARM-R automated work site complex based on an SM-4 minicomputer with a 32K-word memory. This limited memory capacity heightened the demand for algorithm speed and also tightened data file structure and size requirements. The layout algorithm's design logic is analyzed. The structure and organization of the data files are described.

The GOES-R Rebroadcast (GRB) Data Stream Simulator

NASA Astrophysics Data System (ADS)

Dittberner, G. J.; Gibbons, K.; Czopkiewicz, E.; Miller, C.; Brown-Bergtold, B.; Haman, B.; Marley, S.

2013-12-01

GOES Rebroadcast (GRB) signals in the GOES-R era will replace the current legacy GOES Variable (GVAR) signal and will have substantially different characteristics, including a change in data rate from a single 2.1 Mbps stream to two digital streams of 15.5 Mbps each. Five GRB Simulators were developed as portable systems that output a high-fidelity stream of Consultative Committee for Space Data Systems (CCSDS) formatted GRB packet data equivalent to live GRB data. The data are used for on-site testing of user ingest and data handling systems known as field terminal sites. The GRB Simulator is a fully self-contained system which includes all software and hardware units needed for operation. The operator manages configurations to edit preferences, define individual test scenarios, and manage event logs and reports. Simulations are controlled by test scenarios, which are scripts that specify the test data and provide a series of actions for the GRB Simulator to perform when generating GRB output. Scenarios allow for the insertion of errors or modification of GRB packet headers for testing purposes. The GRB Simulator provides a built-in editor for managing scenarios. The GRB Simulator provides GRB data as either baseband (digital) or Intermediate Frequency (IF) output to the test system. GRB packet data are sent in the same two output streams used in the operational system: one for Left Hand Circular Polarization (LHCP) and one for Right Hand Circular Polarization (RHCP). Use of circular polarization in the operational system allows the transmitting antenna to multiplex the two digital streams into the same signal, thereby doubling the available bandwidth. The GRB Simulator is designed to be used at sites that receive the GRB downlink.

An Integrated 0-1 Hour First-Flash Lightning Nowcasting, Lightning Amount and Lightning Jump Warning Capability

NASA Technical Reports Server (NTRS)

Mecikalski, John; Jewett, Chris; Carey, Larry; Zavodsky, Brad; Stano, Geoffrey

2015-01-01

Lightning one of the most dangerous weather-related phenomena, especially as many jobs and activities occur outdoors, presenting risk from a lightning strike. Cloud-to-ground (CG) lightning represents a considerable safety threat to people at airfields, marinas, and outdoor facilities-from airfield personnel, to people attending outdoor stadium events, on beaches and golf courses, to mariners, as well as emergency personnel. Holle et al. (2005) show that 90% of lightning deaths occurred outdoors, while 10% occurred indoors despite the perception of safety when inside buildings. Curran et al. (2000) found that nearly half of fatalities due to weather were related to convective weather in the 1992-1994 timeframe, with lightning causing a large component of the fatalities, in addition to tornadoes and flash flooding. Related to the aviation industry, CG lightning represents a considerable hazard to baggage-handlers, aircraft refuelers, food caterers, and emergency personnel, who all become exposed to the risk of being struck within short time periods while convective storm clouds develop. Airport safety protocols require that ramp operations be modified or discontinued when lightning is in the vicinity (typically 16 km), which becomes very costly and disruptive to flight operations. Therefore, much focus has been paid to nowcasting the first-time initiation and extent of lightning, both of CG and of any lightning (e.g, in-cloud, cloud-to-cloud). For this project three lightning nowcasting methodologies will be combined: (1) a GOESbased 0-1 hour lightning initiation (LI) product (Harris et al. 2010; Iskenderian et al. 2012), (2) a High Resolution Rapid Refresh (HRRR) lightning probability and forecasted lightning flash density product, such that a quantitative amount of lightning (QL) can be assigned to a location of expected LI, and (3) an algorithm that relates Pseudo-GLM data (Stano et al. 2012, 2014) to the so-called "lightning jump" (LJ) methodology (Shultz et al. 2011) to monitor lightning trends and to anticipate/forecast severe weather (hail > or =2.5 cm, winds > or =25 m/s, tornadoes). The result will be a time-continuous algorithm that uses GOES satellite, radar fields, and HRRR model fields to nowcast first-flash LI and QL, and subsequently monitors lightning trends on a perstorm basis within the LJ algorithm for possible severe weather occurrence out to > or =3 hours. The LI-QL-LJ product will also help prepare the operational forecast community for Geostationary Lightning Mapper (GLM) data expected in late 2015, as these data are monitored for ongoing convective storms. The LI-QL-LJ product will first predict where new lightning is highly probable using GOES imagery of developing cumulus clouds, followed by n analysis of NWS (dual-polarization) radar indicators (reflectivity at the -10 C altitude) of lightning occurrence, to increase confidence that LI is immanent. Once lightning is observed, time-continuous lightning mapping array and Pseudo-GLM observations will be analyzed to assess trends and the severe weather threat as identified by trends in lightning (i.e. LJs). Additionally, 5- and 15-min GOES imagery will then be evaluated on a per-storm basis for overshooting and other cloud-top features known to be associated with severe storms. For the processing framework, the GOES-R 0-1 hour convective initiation algorithm's output will be developed within the Warning Decision Support System - Integrated Information (WDSS-II) tracking tool, and merged with radar and lightning (LMA/Psuedo-GLM) datasets for active storms. The initial focus of system development will be over North Alabama for select lightning-active days in summer 2014, yet will be formed in an expandable manner. The lightning alert tool will also be developed in concert with National Weather Service (NWS) forecasters to meet their needs for real-time, accurate first-flash LI and timing, as well as anticipated lightning trends, amounts, continuation and cessation, so to provide key situational awareness and decision support information. The NASA Short-term Prediction Research and Transition (SPoRT) Center will provide important logistical and collaborative support and training, involving interactions with the NWS and broader user community.

The Use of Neural Networks in Identifying Error Sources in Satellite-Derived Tropical SST Estimates

PubMed Central

Lee, Yung-Hsiang; Ho, Chung-Ru; Su, Feng-Chun; Kuo, Nan-Jung; Cheng, Yu-Hsin

2011-01-01

An neural network model of data mining is used to identify error sources in satellite-derived tropical sea surface temperature (SST) estimates from thermal infrared sensors onboard the Geostationary Operational Environmental Satellite (GOES). By using the Back Propagation Network (BPN) algorithm, it is found that air temperature, relative humidity, and wind speed variation are the major factors causing the errors of GOES SST products in the tropical Pacific. The accuracy of SST estimates is also improved by the model. The root mean square error (RMSE) for the daily SST estimate is reduced from 0.58 K to 0.38 K and mean absolute percentage error (MAPE) is 1.03%. For the hourly mean SST estimate, its RMSE is also reduced from 0.66 K to 0.44 K and the MAPE is 1.3%. PMID:22164030

Evolution of multicellularity coincided with increased diversification of cyanobacteria and the Great Oxidation Event.

PubMed

Schirrmeister, Bettina E; de Vos, Jurriaan M; Antonelli, Alexandre; Bagheri, Homayoun C

2013-01-29

Cyanobacteria are among the most diverse prokaryotic phyla, with morphotypes ranging from unicellular to multicellular filamentous forms, including those able to terminally (i.e., irreversibly) differentiate in form and function. It has been suggested that cyanobacteria raised oxygen levels in the atmosphere around 2.45-2.32 billion y ago during the Great Oxidation Event (GOE), hence dramatically changing life on the planet. However, little is known about the temporal evolution of cyanobacterial lineages, and possible interplay between the origin of multicellularity, diversification of cyanobacteria, and the rise of atmospheric oxygen. We estimated divergence times of extant cyanobacterial lineages under Bayesian relaxed clocks for a dataset of 16S rRNA sequences representing the entire known diversity of this phylum. We tested whether the evolution of multicellularity overlaps with the GOE, and whether multicellularity is associated with significant shifts in diversification rates in cyanobacteria. Our results indicate an origin of cyanobacteria before the rise of atmospheric oxygen. The evolution of multicellular forms coincides with the onset of the GOE and an increase in diversification rates. These results suggest that multicellularity could have played a key role in triggering cyanobacterial evolution around the GOE.

Evolution of multicellularity coincided with increased diversification of cyanobacteria and the Great Oxidation Event

PubMed Central

Schirrmeister, Bettina E.; de Vos, Jurriaan M.; Antonelli, Alexandre; Bagheri, Homayoun C.

2013-01-01

Cyanobacteria are among the most diverse prokaryotic phyla, with morphotypes ranging from unicellular to multicellular filamentous forms, including those able to terminally (i.e., irreversibly) differentiate in form and function. It has been suggested that cyanobacteria raised oxygen levels in the atmosphere around 2.45–2.32 billion y ago during the Great Oxidation Event (GOE), hence dramatically changing life on the planet. However, little is known about the temporal evolution of cyanobacterial lineages, and possible interplay between the origin of multicellularity, diversification of cyanobacteria, and the rise of atmospheric oxygen. We estimated divergence times of extant cyanobacterial lineages under Bayesian relaxed clocks for a dataset of 16S rRNA sequences representing the entire known diversity of this phylum. We tested whether the evolution of multicellularity overlaps with the GOE, and whether multicellularity is associated with significant shifts in diversification rates in cyanobacteria. Our results indicate an origin of cyanobacteria before the rise of atmospheric oxygen. The evolution of multicellular forms coincides with the onset of the GOE and an increase in diversification rates. These results suggest that multicellularity could have played a key role in triggering cyanobacterial evolution around the GOE. PMID:23319632

Refining the GPS Space Service Volume (SSV) and Building a Multi-GNSS SSV

NASA Technical Reports Server (NTRS)

Parker, Joel J. K.

2017-01-01

The GPS (Global Positioning System) Space Service Volume (SSV) was first defined to protect the GPS main lobe signals from changes from block to block. First developed as a concept by NASA in 2000, it has been adopted for the GPS III block of satellites, and is being used well beyond the current specification to enable increased navigation performance for key missions like GOES-R. NASA has engaged the US IFOR (Interagency Forum Operational Requirements) process to adopt a revised requirement to protect this increased and emerging use. Also, NASA is working through the UN International Committee on GNSS (Global Navigation Satellite System) to develop an interoperable multi-GNSS SSV in partnership with all of the foreign GNSS providers.

Candid views of STS-41C crew preparing food on middeck

NASA Image and Video Library

1984-04-08

Candid views of the STS-41C crew preparing and eating food on the middeck include : Mission pilot Francis R. (Dick) Scobee goes bobbing for a morsel of food from his position on the middeck near the galley.

Analysis and optimization of three main organic Rankine cycle configurations using a set of working fluids with different thermodynamic behaviors

NASA Astrophysics Data System (ADS)

Hamdi, Basma; Mabrouk, Mohamed Tahar; Kairouani, Lakdar; Kheiri, Abdelhamid

2017-06-01

Different configurations of organic Rankine cycle (ORC) systems are potential thermodynamic concepts for power generation from low grade heat. The aim of this work is to investigate and optimize the performances of the three main ORC systems configurations: basic ORC, ORC with internal heat exchange (IHE) and regenerative ORC. The evaluation for those configurations was performed using seven working fluids with typical different thermodynamic behaviours (R245fa, R601a, R600a, R227ea, R134a, R1234ze and R1234yf). The optimization has been performed using a genetic algorithm under a comprehensive set of operative parameters such as the fluid evaporating temperature, the fraction of flow rate or the pressure at the steam extracting point in the turbine. Results show that there is no general best ORC configuration for all those fluids. However, there is a suitable configuration for each fluid. Contribution to the topical issue "Materials for Energy harvesting, conversion and storage II (ICOME 2016)", edited by Jean-Michel Nunzi, Rachid Bennacer and Mohammed El Ganaoui

ENERGY CONVERSION FOR THE TRANSITION FROM Al TO γ-Al2O3 NANOPARTICLES

NASA Astrophysics Data System (ADS)

Wang, Shulin; Li, Shengjuan; Xu, Bo; Jian, Dunliang; Zhu, Yufang

2013-07-01

We have successfully converted large volume Al particles into γ-Al2O3 nanostructures by vibration milling at room temperature and successive treatment. We show that there exist special relationships among stacking fault energy (SFE), strain energy (SRE), and surface energy (SE) of the materials, including interdependence, intercompetition, and interconversion during the phase transition. SFE and SRE perform the same changing tendency, while SE just does the opposite. However, it is not the particle size but the energy state that determines the reactivity of the materials. And it is the SE that can directly determine the physical chemical reaction and the conversion into the end product rather than SFE and SRE. When SE goes up, the material reactivity and the product yield will be enhanced; and when SE goes down, the reaction and the product yield will decay. However, the state of SE depends closely on the change tendency of the SFE and SRE. That is, when SFE and SRE goes up, SE will goes down; if SFE and SRE goes down, SE will goes up. It seems that energy conservation law may be followed in a sense in the particle system if the external input keeps constant. The work may be significant for energy conversion in nano-scale and mechanosynthesis of oxide nanoparticles.

Solar thematic maps for space weather operations

USGS Publications Warehouse

Rigler, E. Joshua; Hill, Steven M.; Reinard, Alysha A.; Steenburgh, Robert A.

2012-01-01

Thematic maps are arrays of labels, or "themes", associated with discrete locations in space and time. Borrowing heavily from the terrestrial remote sensing discipline, a numerical technique based on Bayes' theorem captures operational expertise in the form of trained theme statistics, then uses this to automatically assign labels to solar image pixels. Ultimately, regular thematic maps of the solar corona will be generated from high-cadence, high-resolution SUVI images, the solar ultraviolet imager slated to fly on NOAA's next-generation GOES-R series of satellites starting ~2016. These thematic maps will not only provide quicker, more consistent synoptic views of the sun for space weather forecasters, but digital thematic pixel masks (e.g., coronal hole, active region, flare, etc.), necessary for a new generation of operational solar data products, will be generated. This paper presents the mathematical underpinnings of our thematic mapper, as well as some practical algorithmic considerations. Then, using images from the Solar Dynamics Observatory (SDO) Advanced Imaging Array (AIA) as test data, it presents results from validation experiments designed to ascertain the robustness of the technique with respect to differing expert opinions and changing solar conditions.

Mutated hilltop inflation revisited

NASA Astrophysics Data System (ADS)

Pal, Barun Kumar

2018-05-01

In this work we re-investigate pros and cons of mutated hilltop inflation. Applying Hamilton-Jacobi formalism we solve inflationary dynamics and find that inflation goes on along the {W}_{-1} branch of the Lambert function. Depending on the model parameter mutated hilltop model renders two types of inflationary solutions: one corresponds to small inflaton excursion during observable inflation and the other describes large field inflation. The inflationary observables from curvature perturbation are in tune with the current data for a wide range of the model parameter. The small field branch predicts negligible amount of tensor to scalar ratio r˜ O(10^{-4}), while the large field sector is capable of generating high amplitude for tensor perturbations, r˜ O(10^{-1}). Also, the spectral index is almost independent of the model parameter along with a very small negative amount of scalar running. Finally we find that the mutated hilltop inflation closely resembles the α -attractor class of inflationary models in the limit of α φ ≫ 1.

Quantum heat engine operating between thermal and spin reservoirs

NASA Astrophysics Data System (ADS)

Wright, Jackson S. S. T.; Gould, Tim; Carvalho, André R. R.; Bedkihal, Salil; Vaccaro, Joan A.

2018-05-01

Landauer's erasure principle is a cornerstone of thermodynamics and information theory [R. Landauer, IBM J. Res. Dev. 5, 183 (1961), 10.1147/rd.53.0183]. According to this principle, erasing information incurs a minimum energy cost. Recently, Vaccaro and Barnett [J. A. Vaccaro and S. M. Barnett, Proc. R. Soc. A 467, 1770 (2011), 10.1098/rspa.2010.0577] explored information erasure in the context of multiple conserved quantities and showed that the erasure cost can be solely in terms of spin angular momentum. As Landauer's erasure principle plays a fundamental role in heat engines, their result considerably widens the possible configurations that heat engines can have. Motivated by this, we propose here an optical heat engine that operates under a single thermal reservoir and a spin angular momentum reservoir coupled to a three-level system with two energy degenerate ground states. The proposed heat engine operates without producing waste heat and goes beyond the traditional Carnot engine where the working fluid is subjected to two thermal baths at different temperatures.

Transforming System Engineering through Model-Centric Engineering

DTIC Science & Technology

2015-01-31

story that is being applied and evolved on Jupiter Europa Orbiter (JEO) project [75], and we summarize some aspects of it here, because it goes beyond...JEO Jupiter Europa Orbiter project at NASA/JPL JSF Joint Strike Fighter JPL Jet Propulsion Laboratory of NASA Linux An operating system created by...Adaptation of Flight-Critical Systems, Digital Avionics Systems Conference, 2009. [75] Rasumussen, R., R. Shishko, Jupiter Europa Orbiter Architecture

Using the SPoRT POES/GOES Hybrid Product in OCONUS Forecasting

NASA Technical Reports Server (NTRS)

Smith, Matt; Fuell, Kevin; Nelson, Jim

2014-01-01

The SPoRT (Short-term Prediction and Research Transition) Program at the NASA/Marshall Space Flight Center has been providing unique NASA and NOAA data and techniques to partner Weather Forecast Offices (WFOs) for ten years. Data are provided in the Decision Support System used by WFO forecasters: AWIPS. For the last couple of years, SPoRT has been producing the POES/GOES Hybrid. This suite of products combines the strength ofl5- minute animations of GOES imagery - providing temporal continuity, with the higher resolution, relatively random availability, of polar orbiting (POES) imagery data. The product was first introduced with only MODIS data from NASA's Terra and Aqua satellites, but recently the VIIRS instrument onboard the Suomi-NPP satellite was added, providing better high-resolution coverage. These products represent SPoRT's efforts to prepare for higher resolution, higher frequency GOES-R imagery - as well as helping to move VIIRS (JPSS) data into the mainstream of weather forecasting. SPoRT generates 5 products for this dataset: Visible, Longwave Infrared (11 micrometers), Shortwave IR (3.7 micrometers), Water Vapor (6.7 micrometers), and Fog (Difference of 11 micrometer and 3.7 micrometer channels). The Water Vapor hybrid product has a Red-Blue-Green image from MODIS inlaid, since it provides even more qualitative information than water vapor alone. Animated examples of the products will be shown in this presentation. While the resolution at nadir of GOES imagery is nominally Han (4km for IR channels), the inlaid polar orbiter imagery has a resolution of 250m (lkm for IR channels). This has tremendous application in the continental US. However, in high latitudes, since the usefulness of GOES degrades poleward rapidly, the contrast of GOES and POES data is stark. The consistent temporal nature of GOES, even though at a reduced resolution at high latitudes, provides basic situational awareness, but the introduction of polar data is very helpful in seeing the big picture with clarity - even if only briefly. This presentation will offer real situations where these products helped forecasters make better informed decisions quickly. Plans to augment the product further with the addition of data from several A VHRR instruments will be described.

Sulfur Oxidation and Contrail Precursor Chemistry

NASA Technical Reports Server (NTRS)

DeWitt, Kenneth J.

2003-01-01

Sulfuric acid (H2SO4), formed in commercial aircraft operations via fuel-S (goes to) SO2 (goes to) SO3 (goes to) H2SO4 plays an important role in the formation of contrails. It is believed that the first step occurs inside the combustor, the second step in the engine exit nozzle, and the third step in the exhaust plume. Thus, measurements of the sulfur oxidation rates are critical to the understanding of contrail formation. Field measurements of contrails formed behind commercial aircraft indicate that significantly greater conversion of fuel-bound sulfur to sulfate aerosol occurs than can be explained by our current knowledge of contrail physics and chemistry. The conversion of sulfur from S(IV) to S(VI) oxidation state, required for sulfate aerosol formation, is thermodynamically favored for the conditions that exist within jet engines but is kinetically disfavored. The principal reaction pathway is O+SO2+M (goes to) SO3+M. The rates of this reaction have never been measured in the temperature and pressure regimes available to aircraft operation. In the first year (FY02) of this project, we performed a series of experiments to elucidate the rate information for the O+SO2+M (goes to) SO3+M reaction. The work performed is described following the proposed work plan. Because we used the H2/O2 system for an O-atom source and rate coefficients were obtained via computer simulation, construction of a reaction mechanism and either recalculation or estimation of thermodynamic properties of H(x)SO(y) species are described first.

Building on crossvalidation for increasing the quality of geostatistical modeling

USGS Publications Warehouse

Olea, R.A.

2012-01-01

The random function is a mathematical model commonly used in the assessment of uncertainty associated with a spatially correlated attribute that has been partially sampled. There are multiple algorithms for modeling such random functions, all sharing the requirement of specifying various parameters that have critical influence on the results. The importance of finding ways to compare the methods and setting parameters to obtain results that better model uncertainty has increased as these algorithms have grown in number and complexity. Crossvalidation has been used in spatial statistics, mostly in kriging, for the analysis of mean square errors. An appeal of this approach is its ability to work with the same empirical sample available for running the algorithms. This paper goes beyond checking estimates by formulating a function sensitive to conditional bias. Under ideal conditions, such function turns into a straight line, which can be used as a reference for preparing measures of performance. Applied to kriging, deviations from the ideal line provide sensitivity to the semivariogram lacking in crossvalidation of kriging errors and are more sensitive to conditional bias than analyses of errors. In terms of stochastic simulation, in addition to finding better parameters, the deviations allow comparison of the realizations resulting from the applications of different methods. Examples show improvements of about 30% in the deviations and approximately 10% in the square root of mean square errors between reasonable starting modelling and the solutions according to the new criteria. ?? 2011 US Government.

Electrochemical oxidation of textile industry wastewater by graphite electrodes.

PubMed

Bhatnagar, Rajendra; Joshi, Himanshu; Mall, Indra D; Srivastava, Vimal C

2014-01-01

In the present article, studies have been performed on the electrochemical (EC) oxidation of actual textile industry wastewater by graphite electrodes. Multi-response optimization of four independent parameters namely initial pH (pHo): 4-10, current density (j): 27.78-138.89 A/m(2), NaCl concentration (w): 0-2 g/L and electrolysis time (t): 10-130 min have been performed using Box-Behnken (BB) experimental design. It was aimed to simultaneously maximize the chemical oxygen demand (COD) and color removal efficiencies and minimize specific energy consumption using desirability function approach. Pareto analysis of variance (ANOVA) showed a high coefficient of determination value for COD (R(2) = 0.8418), color (R(2) = 0.7010) and specific energy (R(2) = 0.9125) between the experimental values and the predicted values by a second-order regression model. Maximum COD and color removal and minimum specific energy consumed was 90.78%, 96.27% and 23.58 kWh/kg COD removed, respectively, were observed at optimum conditions. The wastewater, sludge and scum obtained after treatment at optimum condition have been characterized by various techniques. UV-visible study showed that all azo bonds of the dyes present in the wastewater were totally broken and most of the aromatic rings were mineralized during EC oxidation with graphite electrode. Carbon balance showed that out of the total carbon eroded from the graphite electrodes, 27-29.2% goes to the scum, 71.1-73.3% goes into the sludge and rest goes to the treated wastewater. Thermogravimetric analysis showed that the generated sludge and scum can be dried and used as a fuel in the boilers/incinerators.

Monthly-Diurnal Water Budget Variability Over Gulf of Mexico-Caribbean Sea Basin from Satellite Observations

NASA Technical Reports Server (NTRS)

Smith, E. A.; Santos, P.

2006-01-01

This study presents results from a multi-satellite/multi-sensor retrieval system design d to obtain the atmospheric water budget over the open ocean. A combination of hourly-sampled monthly datasets derived from the GOES-8 5-channel Imager, the TRMM TMI radiometer, and the DMSP 7-channel passive microwave radiometers (SSM/I) have been acquired for the combined Gulf of Mexico-Caribbean Sea basin. Whereas the methodology has been tested over this basin, the retrieval system is designed for portability to any open-ocean region. Algorithm modules using the different datasets to retrieve individual geophysical parameters needed in the water budget equation are designed in a manner that takes advantage of the high temporal resolution of the GOES-8 measurements, as well as the physical relationships inherent to the TRMM and SSM/I passive microwave measurements in conjunction with water vapor, cloud liquid water, and rainfall. The methodology consists of retrieving the precipitation, surface evaporation, and vapor-cloud water storage terms in the atmospheric water balance equation from satellite techniques, with the water vapor advection term being obtained as the residue needed for balance. Thus, the intent is to develop a purely satellite-based method for obtaining the full set of terms in the atmospheric water budget equation without requiring in situ sounding information on the wind profile. The algorithm is validated by cross-checking all the algorithm components through multiple-algorithm retrieval intercomparisons. A further check on the validation is obtained by directly comparing water vapor transports into the targeted basin diagnosed from the satellite algorithms to those obtained observationally from a network of land-based upper air stations that nearly uniformly surround the basin, although it is fair to say that these checks are more effective in identifying problems in estimating vapor transports from a "leaky" operational radiosonde network than in verifying the transport estimates determined from the satellite algorithm system. Total columnar atmospheric water budget results are presented for an extended annual cycle consisting of the months of October-97, January-98, April-98, July-98,October-98, and January- 1999. These results are used to emphasize the changing relationship in E-P, as well as in the varying roles of storage and advection in balancing E-P both on daily and monthly time scales and on localized and basin space scales. Results from the algorithm-to-algorithm intercomparisons are also presented in the context of sensitivity testing to help understand the intrinsic uncertainties in evaluating the water budget terms by an all-satellite algorithm approach.

Satellite Retrieval of Atmospheric Water Budget over Gulf of Mexico- Caribbean Basin: Seasonal Variability

NASA Technical Reports Server (NTRS)

Smith, Eric A.; Santos, Pablo; Einaudi, Franco (Technical Monitor)

2001-01-01

This study presents results from a multi-satellite/multi-sensor retrieval system designed to obtain the atmospheric water budget over the open ocean. A combination of hourly-sampled monthly datasets derived from the GOES-8 5 Imager and the DMSP 7-channel passive microwave radiometer (SSM/I) have been acquired for the Gulf of Mexico-Caribbean Sea basin. Whereas the methodology is being tested over this basin, the retrieval system is designed for portability to any open-ocean region. Algorithm modules using the different datasets to retrieve individual geophysical parameters needed in the water budget equation are designed in a manner that takes advantage of the high temporal resolution of the GOES-8 measurements, as well as the physical relationships inherent to the SSM/I passive microwave signals in conjunction with water vapor, cloud liquid water, and rainfall. The methodology consists of retrieving the precipitation, surface evaporation, and vapor-cloud water storage terms in the atmospheric water balance equation from satellite techniques, with the water vapor advection term being obtained as the residue needed for balance. Thus, we have sought to develop a purely satellite-based method for obtaining the full set of terms in the atmospheric water budget equation without requiring in situ sounding information on the wind profile. The algorithm is partly validated by first cross-checking all the algorithm components through multiple-algorithm retrieval intercomparisons. More fundamental validation is obtained by directly comparing water vapor transports into the targeted basin diagnosed from the satellite algorithm to those obtained observationally from a network of land-based upper air stations that nearly uniformly surround the basin. Total columnar atmospheric water budget results will be presented for an extended annual cycle consisting of the months of October-97, January-98, April-98, July-98, October-98, and January-1999. These results are used to emphasize the changing relationship in E-P, as well as in the varying roles of storage and advection in balancing E-P both on daily and monthly time scales and on localized and basin space scales. Results from the algorithm-to-algorithm intercomparisons will also be presented in the context of sensitivity testing to help understand the intrinsic uncertainties in the water budget terms.

A Vectorized ’Nearest-Neighbors’ Algorithm of Order N Using a Monotonic Logical Grid

DTIC Science & Technology

1985-05-29

Computational Phy’sics 0 4 May 29 , 1985 This work was supported by the Office of Naval Research. . ~ Q~JUN 1719851- * NAVAL RESEARCH LABORATORY * lit...YE ’.ARK:NGS UNCLASSIFIED_______________ _____ K -. A R, ~ CA7,ON 4, 71CO1, 3 :)-S7R,9U-ON AdA,.A3:L ’Y OF REPOR7Io - EC..ASi.’ CA27 ON., DOWNGAZING...Year. Month. Day) 5 PAGE COUNT Interim FROM -____ Toi__ 1985 May 29 50 𔄀 SuPPILSMENTARY NOTATION This work was supported by the Office of Naval

Real-time identification of residential appliance events based on power monitoring

NASA Astrophysics Data System (ADS)

Yang, Zhao; Zhu, Zhicheng; Wei, Zhiqiang; Yin, Bo; Wang, Xiuwei

2018-03-01

Energy monitoring for specific home appliances has been regarded as the pre-requisite for reducing residential energy consumption. To enhance the accuracy of identifying operation status of household appliances and to keep pace with the development of smart power grid, this paper puts forward the integration of electric current and power data on the basis of existing algorithm. If average power difference of several adjacent cycles varies from the baseline and goes beyond the pre-assigned threshold value, the event will be flagged. Based on MATLAB platform and domestic appliances simulations, the results of tested data and verified algorithm indicate that the power method has accomplished desired results of appliance identification.

Fireworks algorithm for mean-VaR/CVaR models

NASA Astrophysics Data System (ADS)

Zhang, Tingting; Liu, Zhifeng

2017-10-01

Intelligent algorithms have been widely applied to portfolio optimization problems. In this paper, we introduce a novel intelligent algorithm, named fireworks algorithm, to solve the mean-VaR/CVaR model for the first time. The results show that, compared with the classical genetic algorithm, fireworks algorithm not only improves the optimization accuracy and the optimization speed, but also makes the optimal solution more stable. We repeat our experiments at different confidence levels and different degrees of risk aversion, and the results are robust. It suggests that fireworks algorithm has more advantages than genetic algorithm in solving the portfolio optimization problem, and it is feasible and promising to apply it into this field.

Hotplate precipitation gauge calibrations and field measurements

NASA Astrophysics Data System (ADS)

Zelasko, Nicholas; Wettlaufer, Adam; Borkhuu, Bujidmaa; Burkhart, Matthew; Campbell, Leah S.; Steenburgh, W. James; Snider, Jefferson R.

2018-01-01

First introduced in 2003, approximately 70 Yankee Environmental Systems (YES) hotplate precipitation gauges have been purchased by researchers and operational meteorologists. A version of the YES hotplate is described in Rasmussen et al. (2011; R11). Presented here is testing of a newer version of the hotplate; this device is equipped with longwave and shortwave radiation sensors. Hotplate surface temperature, coefficients describing natural and forced convective sensible energy transfer, and radiative properties (longwave emissivity and shortwave reflectance) are reported for two of the new-version YES hotplates. These parameters are applied in a new algorithm and are used to derive liquid-equivalent accumulations (snowfall and rainfall), and these accumulations are compared to values derived by the internal algorithm used in the YES hotplates (hotplate-derived accumulations). In contrast with R11, the new algorithm accounts for radiative terms in a hotplate's energy budget, applies an energy conversion factor which does not differ from a theoretical energy conversion factor, and applies a surface area that is correct for the YES hotplate. Radiative effects are shown to be relatively unimportant for the precipitation events analyzed. In addition, this work documents a 10 % difference between the hotplate-derived and new-algorithm-derived accumulations. This difference seems consistent with R11's application of a hotplate surface area that deviates from the actual surface area of the YES hotplate and with R11's recommendation for an energy conversion factor that differs from that calculated using thermodynamic theory.

Hacia la predicción del Número R de Wolf de manchas solares utilizando Redes Neuronales con retardos temporales

NASA Astrophysics Data System (ADS)

Francile, C.; Luoni, M. L.

We present a prediction of the time series of the Wolf number R of sunspots using "time lagged feed forward neural networks". We use two types of networks: the focused and distributed ones which were trained with the back propagation of errors algorithm and the temporal back propagation algorithm respectively. As inputs to neural networks we use the time series of the number R averaged annually and monthly with the method IR5. As data sets for training and test we choose certain intervals of the time series similar to other works, in order to compare the results. Finally we discuss the topology of the networks used, the number of delays used, the number of neurons per layer, the number of hidden layers and the results in the prediction of the series between one and six steps ahead. FULL TEXT IN SPANISH

A Flexible Computational Framework Using R and Map-Reduce for Permutation Tests of Massive Genetic Analysis of Complex Traits.

PubMed

Mahjani, Behrang; Toor, Salman; Nettelblad, Carl; Holmgren, Sverker

2017-01-01

In quantitative trait locus (QTL) mapping significance of putative QTL is often determined using permutation testing. The computational needs to calculate the significance level are immense, 10 4 up to 10 8 or even more permutations can be needed. We have previously introduced the PruneDIRECT algorithm for multiple QTL scan with epistatic interactions. This algorithm has specific strengths for permutation testing. Here, we present a flexible, parallel computing framework for identifying multiple interacting QTL using the PruneDIRECT algorithm which uses the map-reduce model as implemented in Hadoop. The framework is implemented in R, a widely used software tool among geneticists. This enables users to rearrange algorithmic steps to adapt genetic models, search algorithms, and parallelization steps to their needs in a flexible way. Our work underlines the maturity of accessing distributed parallel computing for computationally demanding bioinformatics applications through building workflows within existing scientific environments. We investigate the PruneDIRECT algorithm, comparing its performance to exhaustive search and DIRECT algorithm using our framework on a public cloud resource. We find that PruneDIRECT is vastly superior for permutation testing, and perform 2 ×10 5 permutations for a 2D QTL problem in 15 hours, using 100 cloud processes. We show that our framework scales out almost linearly for a 3D QTL search.

A Hybrid Shared-Memory Parallel Max-Tree Algorithm for Extreme Dynamic-Range Images.

PubMed

Moschini, Ugo; Meijster, Arnold; Wilkinson, Michael H F

2018-03-01

Max-trees, or component trees, are graph structures that represent the connected components of an image in a hierarchical way. Nowadays, many application fields rely on images with high-dynamic range or floating point values. Efficient sequential algorithms exist to build trees and compute attributes for images of any bit depth. However, we show that the current parallel algorithms perform poorly already with integers at bit depths higher than 16 bits per pixel. We propose a parallel method combining the two worlds of flooding and merging max-tree algorithms. First, a pilot max-tree of a quantized version of the image is built in parallel using a flooding method. Later, this structure is used in a parallel leaf-to-root approach to compute efficiently the final max-tree and to drive the merging of the sub-trees computed by the threads. We present an analysis of the performance both on simulated and actual 2D images and 3D volumes. Execution times are about better than the fastest sequential algorithm and speed-up goes up to on 64 threads.

Practical Application of PRA as an Integrated Design Tool for Space Systems

NASA Technical Reports Server (NTRS)

Kalia, Prince; Shi, Ying; Pair, Robin; Quaney, Virginia; Uhlenbrock, John

2013-01-01

This paper presents the application of the first comprehensive Probabilistic Risk Assessment (PRA) during the design phase of a joint NASA/NOAA weather satellite program, Geostationary Operational Environmental Satellite Series R (GOES-R). GOES-R is the next generation weather satellite primarily to help understand the weather and help save human lives. PRA has been used at NASA for Human Space Flight for many years. PRA was initially adopted and implemented in the operational phase of manned space flight programs and more recently for the next generation human space systems. Since its first use at NASA, PRA has become recognized throughout the Agency as a method of assessing complex mission risks as part of an overall approach to assuring safety and mission success throughout project lifecycles. PRA is now included as a requirement during the design phase of both NASA next generation manned space vehicles as well as for high priority robotic missions. The influence of PRA on GOES-R design and operation concepts are discussed in detail. The GOES-R PRA is unique at NASA for its early implementation. It also represents a pioneering effort to integrate risks from both Spacecraft (SC) and Ground Segment (GS) to fully assess the probability of achieving mission objectives. PRA analysts were actively involved in system engineering and design engineering to ensure that a comprehensive set of technical risks were correctly identified and properly understood from a design and operations perspective. The analysis included an assessment of SC hardware and software, SC fault management system, GS hardware and software, common cause failures, human error, natural hazards, solar weather and infrastructure (such as network and telecommunications failures, fire). PRA findings directly resulted in design changes to reduce SC risk from micro-meteoroids. PRA results also led to design changes in several SC subsystems, e.g. propulsion, guidance, navigation and control (GNC), communications, mechanisms, and command and data handling (C&DH). The fault tree approach assisted in the development of the fault management system design. Human error analysis, which examined human response to failure, indicated areas where automation could reduce the overall probability of gaps in operation by half. In addition, the PRA brought to light many potential root causes of system disruptions, including earthquakes, inclement weather, solar storms, blackouts and other extreme conditions not considered in the typical reliability and availability analyses. Ultimately the PRA served to identify potential failures that, when mitigated, resulted in a more robust design, as well as to influence the program's concept of operations. The early and active integration of PRA with system and design engineering provided a well-managed approach for risk assessment that increased reliability and availability, optimized lifecyc1e costs, and unified the SC and GS developments.

NASA/SPoRt: GOES-R Activities in Support of Product Development, Management, and Training

NASA Technical Reports Server (NTRS)

Fuell, Kevin; Jedlovec, Gary; Molthan, Andrew; Stano, Geoffrey

2012-01-01

SPoRT is using current capabilities of MODIS and VIIRS, combined with current GOES (i.e. Hybrid Imagery) to demonstrate mesoscale capabilities of future ABI instrument. SPoRT is transitioning RGBs from EUMETSAT standard "recipes" to demonstrate a method to more efficiently handle the increase channels/frequency of ABI. Challenges for RGB production exist. Internal vs. external production, Bit depth needed, Adding quantitative information, etc. SPoRT forming group to address these issues. SPoRT is leading efforts on the application of total lightning in operations and to educate users of this new capability. Training in many forms is used to support testbed activities and is a key part to the transition process.

Applications and Benefits for Big Data Sets Using Tree Distances and The T-SNE Algorithm

DTIC Science & Technology

2016-03-01

BENEFITS FOR BIG DATA SETS USING TREE DISTANCES AND THE T-SNE ALGORITHM by Suyoung Lee March 2016 Thesis Advisor: Samuel E. Buttrey...REPORT TYPE AND DATES COVERED Master’s thesis 4. TITLE AND SUBTITLE APPLICATIONS AND BENEFITS FOR BIG DATA SETS USING TREE DISTANCES AND THE T-SNE...this work we use tree distance computed using Buttrey’s treeClust package in R, as discussed by Buttrey and Whitaker in 2015, to process mixed data

How C2 Goes Wrong (Briefing Chart)

DTIC Science & Technology

2014-06-01

Guardian/Pix/pictures/2012/12/19/1355903591995/Hillsborough-disaster-010.jpg Cases (3): Disaster/Emergency Response (Cont.) Columbine High School ...r337173_1529332.jpg http://bossip.files.wordpress.com/2012/11/ massacre -e1352384704110.jpeg?w=625&h=389 The Punchline “What we’ve got here, is

Derivation of Improved Surface and TOA Broadband Fluxes Using CERES-derived Narrowband-to-Broadband Coefficients

NASA Technical Reports Server (NTRS)

Khaiyer, Mandana M.; Doelling, David R.; Chan, Pui K.; Nordeen, MIchele L.; Palikonda, Rabindra; Yi, Yuhong; Minnis, Patrick

2006-01-01

Satellites can provide global coverage of a number of climatically important radiative parameters, including broadband (BB) shortwave (SW) and longwave (LW) fluxes at the top of the atmosphere (TOA) and surface. These parameters can be estimated from narrowband (NB) Geostationary Operational Environmental Satellite (GOES) data, but their accuracy is highly dependent on the validity of the narrowband-to-broadband (NB-BB) conversion formulas that are used to convert the NB fluxes to broadband values. The formula coefficients have historically been derived by regressing matched polarorbiting satellite BB fluxes or radiances with their NB counterparts from GOES (e.g., Minnis et al., 1984). More recently, the coefficients have been based on matched Earth Radiation Budget Experiment (ERBE) and GOES-6 data (Minnis and Smith, 1998). The Clouds and the Earth's Radiant Energy Budget (CERES see Wielicki et al. 1998)) project has recently developed much improved Angular Distribution Models (ADM; Loeb et al., 2003) and has higher resolution data compared to ERBE. A limited set of coefficients was also derived from matched GOES-8 and CERES data taken on Topical Rainfall Measuring Mission (TRMM) satellite (Chakrapani et al., 2003; Doelling et al., 2003). The NB-BB coefficients derived from CERES and the GOES suite should yield more accurate BB fluxes than from ERBE, but are limited spatially and seasonally. With CERES data taken from Terra and Aqua, it is now possible to derive more reliable NB-BB coefficients for any given area. Better TOA fluxes should translate to improved surface radiation fluxes derived using various algorithms. As part of an ongoing effort to provide accurate BB flux estimates for the Atmospheric Radiation Measurement (ARM) Program, this paper documents the derivation of new NB-BB coefficients for the ARM Southern Great Plains (SGP) domain and for the Darwin region of the Tropical Western Pacific (DTWP) domain.

Automated Spectroscopic Analysis Using the Particle Swarm Optimization Algorithm: Implementing a Guided Search Algorithm to Autofit

NASA Astrophysics Data System (ADS)

Ervin, Katherine; Shipman, Steven

2017-06-01

While rotational spectra can be rapidly collected, their analysis (especially for complex systems) is seldom straightforward, leading to a bottleneck. The AUTOFIT program was designed to serve that need by quickly matching rotational constants to spectra with little user input and supervision. This program can potentially be improved by incorporating an optimization algorithm in the search for a solution. The Particle Swarm Optimization Algorithm (PSO) was chosen for implementation. PSO is part of a family of optimization algorithms called heuristic algorithms, which seek approximate best answers. This is ideal for rotational spectra, where an exact match will not be found without incorporating distortion constants, etc., which would otherwise greatly increase the size of the search space. PSO was tested for robustness against five standard fitness functions and then applied to a custom fitness function created for rotational spectra. This talk will explain the Particle Swarm Optimization algorithm and how it works, describe how Autofit was modified to use PSO, discuss the fitness function developed to work with spectroscopic data, and show our current results. Seifert, N.A., Finneran, I.A., Perez, C., Zaleski, D.P., Neill, J.L., Steber, A.L., Suenram, R.D., Lesarri, A., Shipman, S.T., Pate, B.H., J. Mol. Spec. 312, 13-21 (2015)

Using a genetic algorithm to abbreviate the Psychopathic Personality Inventory-Revised (PPI-R).

PubMed

Eisenbarth, Hedwig; Lilienfeld, Scott O; Yarkoni, Tal

2015-03-01

Some self-report measures of personality and personality disorders, including the widely used Psychopathic Personality Inventory-Revised (PPI-R), are lengthy and time-intensive. In recent work, we introduced an automated genetic algorithm (GA)-based method for abbreviating psychometric measures. In Study 1, we used this approach to generate a short (40-item) version of the PPI-R using 3 large-N German student samples (total N = 1,590). The abbreviated measure displayed high convergent correlations with the original PPI-R, and outperformed an alternative measure constructed using a conventional approach. Study 2 tested the convergent and discriminant validity of this short version in a fourth student sample (N = 206) using sensation-seeking and sensitivity to reward and punishment scales, again demonstrating similar convergent and discriminant validity for the PPI-R-40 compared with the full version. In a fifth community sample of North American participants acquired using Amazon Mechanical Turk, the PPI-R-40 showed similarly high convergent correlations, demonstrating stability across language, culture, and data-collection method. Taken together, these studies suggest that the GA approach is a viable method for abbreviating measures of psychopathy, and perhaps personality measures in general. 2015 APA, all rights reserved

Geostationary Lightning Mapper: Lessons Learned from Post Launch Test

NASA Astrophysics Data System (ADS)

Edgington, S.; Tillier, C. E.; Demroff, H.; VanBezooijen, R.; Christian, H. J., Jr.; Bitzer, P. M.

2017-12-01

Pre-launch calibration and algorithm design for the GOES Geostationary Lightning Mapper resulted in a successful and trouble-free on-orbit activation and post-launch test sequence. Within minutes of opening the GLM aperture door on January 4th, 2017, lightning was detected across the entire field of view. During the six-month post-launch test period, numerous processing parameters on board the instrument and in the ground processing algorithms were fine-tuned. Demonstrated on-orbit performance exceeded pre-launch predictions. We provide an overview of the ground calibration sequence, on-orbit tuning of the instrument, tuning of the ground processing algorithms (event filtering and navigation). We also touch on new insights obtained from analysis of a large and growing archive of raw GLM data, containing 3e8 flash detections derived from over 1e10 full-disk images of the Earth.

GEONEX: Land Monitoring From a New Generation of Geostationary Satellite Sensors

NASA Technical Reports Server (NTRS)

Nemani, Ramakrishna; Lyapustin, Alexei; Wang, Weile; Wang, Yujie; Hashimoto, Hirofumi; Li, Shuang; Ganguly, Sangram; Michaelis, Andrew; Higuchi, Atsushi; Takaneka, Hideaki;

GEONEX: Land monitoring from a new generation of geostationary satellite sensors

NASA Astrophysics Data System (ADS)

Nemani, R. R.; Lyapustin, A.; Wang, W.; Ganguly, S.; Wang, Y.; Michaelis, A.; Hashimoto, H.; Li, S.; Higuchi, A.; Huete, A. R.; Yeom, J. M.; camacho De Coca, F.; Lee, T. J.; Takenaka, H.

2017-12-01

The latest generation of geostationary satellites carry sensors such as ABI (Advanced Baseline Imager on GOES-16) and the AHI (Advanced Himawari Imager on Himawari) that closely mimic the spatial and spectral characteristics of Earth Observing System flagship MODIS for monitoring land surface conditions. More importantly they provide observations at 5-15 minute intervals. Such high frequency data offer exciting possibilities for producing robust estimates of land surface conditions by overcoming cloud cover, enabling studies of diurnally varying local-to-regional biosphere-atmosphere interactions, and operational decision-making in agriculture, forestry and disaster management. But the data come with challenges that need special attention. For instance, geostationary data feature changing sun angle at constant view for each pixel, which is reciprocal to sun-synchronous observations, and thus require careful adaptation of EOS algorithms. Our goal is to produce a set of land surface products from geostationary sensors by leveraging NASA's investments in EOS algorithms and in the data/compute facility NEX. The land surface variables of interest include atmospherically corrected surface reflectances, snow cover, vegetation indices and leaf area index (LAI)/fraction of photosynthetically absorbed radiation (FPAR), as well as land surface temperature and fires. In order to get ready to produce operational products over the US from GOES-16 starting 2018, we have utilized 18 months of data from Himawari AHI over Australia to test the production pipeline and the performance of various algorithms for our initial tests. The end-to-end processing pipeline consists of a suite of modules to (a) perform calibration and automatic georeference correction of the AHI L1b data, (b) adopt the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm to produce surface spectral reflectances along with compositing schemes and QA, and (c) modify relevant EOS retrieval algorithms (e.g., LAI and FPAR, GPP, etc.) for subsequent science product generation. Initial evaluation of Himawari AHI products against standard MODIS products indicate general agreement, suggesting that data from geostationary sensors can augment low earth orbit (LEO) satellite observations.

Scintillation Control for Adaptive Optical Sensors

DTIC Science & Technology

1999-09-21

defining where one influence function goes to zero fall directly under the peaks of the adjoining influcence functions. These actuators were fit to ^>gp(i...not orthogonal the influence function interaction matrix R must be computed with elements given by [3] rH = J dxPW(xp)e/b(xp)e,(xp). (22) In our...control signals can be found from the wave front phase by the least squares phase reconstruction technique [3]. An influence function and the

Improving HVAC operational efficiency in small-and medium-size commercial buildings

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, Woohyun; Katipamula, Srinivas; Lutes, Robert

Small- and medium-size (<100,000 sf) commercial buildings (SMBs) represent over 95% of the U.S. commercial building stock and consume over 60% of total site energy consumption. Many of these buildings use rudimentary controls that are mostly manual, with limited scheduling capability, no monitoring, or failure management. Therefore, many of these buildings are operated inefficiently and consume excess energy. SMBs typically use packaged rooftop units (RTUs) that are controlled by an individual thermostat. There is increased urgency to improve the operating efficiency of existing commercial building stock in the United States for many reasons, chief among them being to mitigate themore » climate change impacts. Studies have shown that managing set points and schedules of the RTUs will result in up to 20% energy and cost savings. Another problem associated with RTUs is short cycling, when an RTU goes through ON and OFF cycles too frequently. Excessive cycling can lead to excessive wear and to premature failure of the compressor or its components. Also, short cycling can result in a significantly decreased average efficiency (up to 10%), even if there are no physical failures in the equipment. Ensuring correct use of the zone set points and eliminating frequent cycling of RTUs thereby leading to persistent building operations can significantly increase the operational efficiency of the SMBs. A growing trend is to use low-cost control infrastructure that can enable scalable and cost-effective intelligent building operations. The work reported in this paper describes two algorithms for detecting the zone set point temperature and RTU cycling rate that can be deployed on the low-cost infrastructure. These algorithms only require the zone temperature data for detection. The algorithms have been tested and validated using field data from a number of RTUs from six buildings in different climate locations. Overall, the algorithms were successful in detecting the set points and ON/OFF cycles accurately using the peak detection technique. The paper describes the two algorithms, results from testing the algorithms using field data, how the algorithms can be used to improve SMBs efficiency, and presents related conclusions.« less

Early Warning Report: Use of Contractors to Conduct Clean Air Act Risk Management Program Inspections in Certain States Goes Against Court Decisions

EPA Pesticide Factsheets

Report #12-P-0376, March 28, 2012. The OIG is currently evaluating whether the EPA has adequate management controls for ensuring the effectiveness of its Clean Air Act (CAA) Section 112(r) risk management program inspections.

Spending Money Wisely.

ERIC Educational Resources Information Center

Wentworth, Donald R.; And Others

1982-01-01

The theme article of this issue, "Spending Money Wisely," by Donald R. Wentworth, begins with an explanation of basic strategies which aid wise spending. The article goes on to provide an introduction to economic reasoning related to consumer purchases and focusing on the role of incentives, scarcity, and alternatives. Four teaching units follow…

Development of image processing method to detect noise in geostationary imagery

NASA Astrophysics Data System (ADS)

Khlopenkov, Konstantin V.; Doelling, David R.

2016-10-01

The Clouds and the Earth's Radiant Energy System (CERES) has incorporated imagery from 16 individual geostationary (GEO) satellites across five contiguous domains since March 2000. In order to derive broadband fluxes uniform across satellite platforms it is important to ensure a good quality of the input raw count data. GEO data obtained by older GOES imagers (such as MTSAT-1, Meteosat-5, Meteosat-7, GMS-5, and GOES-9) are known to frequently contain various types of noise caused by transmission errors, sync errors, stray light contamination, and others. This work presents an image processing methodology designed to detect most kinds of noise and corrupt data in all bands of raw imagery from modern and historic GEO satellites. The algorithm is based on a set of different approaches to detect abnormal image patterns, including inter-line and inter-pixel differences within a scanline, correlation between scanlines, analysis of spatial variance, and also a 2D Fourier analysis of the image spatial frequencies. In spite of computational complexity, the described method is highly optimized for performance to facilitate volume processing of multi-year data and runs in fully automated mode. Reliability of this noise detection technique has been assessed by human supervision for each GEO dataset obtained during selected time periods in 2005 and 2006. This assessment has demonstrated the overall detection accuracy of over 99.5% and the false alarm rate of under 0.3%. The described noise detection routine is currently used in volume processing of historical GEO imagery for subsequent production of global gridded data products and for cross-platform calibration.

Bounded Kalman filter method for motion-robust, non-contact heart rate estimation

PubMed Central

Prakash, Sakthi Kumar Arul; Tucker, Conrad S.

2018-01-01

The authors of this work present a real-time measurement of heart rate across different lighting conditions and motion categories. This is an advancement over existing remote Photo Plethysmography (rPPG) methods that require a static, controlled environment for heart rate detection, making them impractical for real-world scenarios wherein a patient may be in motion, or remotely connected to a healthcare provider through telehealth technologies. The algorithm aims to minimize motion artifacts such as blurring and noise due to head movements (uniform, random) by employing i) a blur identification and denoising algorithm for each frame and ii) a bounded Kalman filter technique for motion estimation and feature tracking. A case study is presented that demonstrates the feasibility of the algorithm in non-contact estimation of the pulse rate of subjects performing everyday head and body movements. The method in this paper outperforms state of the art rPPG methods in heart rate detection, as revealed by the benchmarked results. PMID:29552419

Theoretical and experimental study on near infrared time-resolved optical diffuse tomography

NASA Astrophysics Data System (ADS)

Zhao, Huijuan; Gao, Feng; Tanikawa, Yukari; Yamada, Yukio

2006-08-01

Parts of the works of our group in the past five years on near infrared time-resolved (TR) optical tomography are summarized in this paper. The image reconstruction algorithm is based on Newton Raphson scheme with a datatype R generated from modified Generalized Pulse Spectrum Technique. Firstly, the algorithm is evaluated with simulated data from a 2-D model and the datatype R is compared with other popularly used datatypes. In this second part of the paper, the in vitro and in vivo NIR DOT imaging on a chicken leg and a human forearm, respectively are presented for evaluating both the image reconstruction algorithm and the TR measurement system. The third part of this paper is about the differential pathlength factor of human head while monitoring head activity with NIRS and applying the modified Lambert-Beer law. Benefiting from the TR system, the measured DPF maps of the three import areas of human head are presented in this paper.

As Mobile Goes, So Goes the Corps: A Look At Change Inside A Government Agency

DTIC Science & Technology

2006-01-01

security and " nation building" with a low-cost investment. He particularly thought that the Corps effort to support SOUTH COM in Latin America was ...little else was said regarding the initiative. The Army ’s plan to reorganize, presented to the new administration in 1992 and accepted by the National ...much of the work was still done by hand. For example, purchase orders, after being completed by Contracting, had to be typed manually into the

Fluidica CFD software for fluids instruction

NASA Astrophysics Data System (ADS)

Colonius, Tim

2008-11-01

Fluidica is an open-source freely available Matlab graphical user interface (GUI) to to an immersed-boundary Navier- Stokes solver. The algorithm is programmed in Fortran and compiled into Matlab as mex-function. The user can create external flows about arbitrarily complex bodies and collections of free vortices. The code runs fast enough for complex 2D flows to be computed and visualized in real-time on the screen. This facilitates its use in homework and in the classroom for demonstrations of various potential-flow and viscous flow phenomena. The GUI has been written with the goal of allowing the student to learn how to use the software as she goes along. The user can select which quantities are viewed on the screen, including contours of various scalars, velocity vectors, streamlines, particle trajectories, streaklines, and finite-time Lyapunov exponents. In this talk, we demonstrate the software in the context of worked classroom examples demonstrating lift and drag, starting vortices, separation, and vortex dynamics.

Fast associative memory + slow neural circuitry = the computational model of the brain.

NASA Astrophysics Data System (ADS)

Berkovich, Simon; Berkovich, Efraim; Lapir, Gennady

1997-08-01

We propose a computational model of the brain based on a fast associative memory and relatively slow neural processors. In this model, processing time is expensive but memory access is not, and therefore most algorithmic tasks would be accomplished by using large look-up tables as opposed to calculating. The essential feature of an associative memory in this context (characteristic for a holographic type memory) is that it works without an explicit mechanism for resolution of multiple responses. As a result, the slow neuronal processing elements, overwhelmed by the flow of information, operate as a set of templates for ranking of the retrieved information. This structure addresses the primary controversy in the brain architecture: distributed organization of memory vs. localization of processing centers. This computational model offers an intriguing explanation of many of the paradoxical features in the brain architecture, such as integration of sensors (through DMA mechanism), subliminal perception, universality of software, interrupts, fault-tolerance, certain bizarre possibilities for rapid arithmetics etc. In conventional computer science the presented type of a computational model did not attract attention as it goes against the technological grain by using a working memory faster than processing elements.

A MULTIPLE GRID ALGORITHM FOR ONE-DIMENSIONAL TRANSIENT OPEN CHANNEL FLOWS. (R825200)

EPA Science Inventory

Numerical modeling of open channel flows with shocks using explicit finite difference schemes is constrained by the choice of time step, which is limited by the CFL stability criteria. To overcome this limitation, in this work we introduce the application of a multiple grid al...

Geostationary Communications Satellites as Sensors for the Space Weather Environment: Telemetry Event Identification Algorithms

NASA Astrophysics Data System (ADS)

Carlton, A.; Cahoy, K.

2015-12-01

Reliability of geostationary communication satellites (GEO ComSats) is critical to many industries worldwide. The space radiation environment poses a significant threat and manufacturers and operators expend considerable effort to maintain reliability for users. Knowledge of the space radiation environment at the orbital location of a satellite is of critical importance for diagnosing and resolving issues resulting from space weather, for optimizing cost and reliability, and for space situational awareness. For decades, operators and manufacturers have collected large amounts of telemetry from geostationary (GEO) communications satellites to monitor system health and performance, yet this data is rarely mined for scientific purposes. The goal of this work is to acquire and analyze archived data from commercial operators using new algorithms that can detect when a space weather (or non-space weather) event of interest has occurred or is in progress. We have developed algorithms, collectively called SEER (System Event Evaluation Routine), to statistically analyze power amplifier current and temperature telemetry by identifying deviations from nominal operations or other events and trends of interest. This paper focuses on our work in progress, which currently includes methods for detection of jumps ("spikes", outliers) and step changes (changes in the local mean) in the telemetry. We then examine available space weather data from the NOAA GOES and the NOAA-computed Kp index and sunspot numbers to see what role, if any, it might have played. By combining the results of the algorithm for many components, the spacecraft can be used as a "sensor" for the space radiation environment. Similar events occurring at one time across many component telemetry streams may be indicative of a space radiation event or system-wide health and safety concern. Using SEER on representative datasets of telemetry from Inmarsat and Intelsat, we find events that occur across all or many of telemetry files at certain dates. We compare these system-wide events to known space weather storms, such as the 2003 Halloween storms, and to spacecraft operational events, such as maneuvers. We also present future applications and expansions of SEER for robust space environment sensing and system health and safety monitoring.

Generalized and efficient algorithm for computing multipole energies and gradients based on Cartesian tensors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lin, Dejun, E-mail: dejun.lin@gmail.com

2015-09-21

Accurate representation of intermolecular forces has been the central task of classical atomic simulations, known as molecular mechanics. Recent advancements in molecular mechanics models have put forward the explicit representation of permanent and/or induced electric multipole (EMP) moments. The formulas developed so far to calculate EMP interactions tend to have complicated expressions, especially in Cartesian coordinates, which can only be applied to a specific kernel potential function. For example, one needs to develop a new formula each time a new kernel function is encountered. The complication of these formalisms arises from an intriguing and yet obscured mathematical relation between themore » kernel functions and the gradient operators. Here, I uncover this relation via rigorous derivation and find that the formula to calculate EMP interactions is basically invariant to the potential kernel functions as long as they are of the form f(r), i.e., any Green’s function that depends on inter-particle distance. I provide an algorithm for efficient evaluation of EMP interaction energies, forces, and torques for any kernel f(r) up to any arbitrary rank of EMP moments in Cartesian coordinates. The working equations of this algorithm are essentially the same for any kernel f(r). Recently, a few recursive algorithms were proposed to calculate EMP interactions. Depending on the kernel functions, the algorithm here is about 4–16 times faster than these algorithms in terms of the required number of floating point operations and is much more memory efficient. I show that it is even faster than a theoretically ideal recursion scheme, i.e., one that requires 1 floating point multiplication and 1 addition per recursion step. This algorithm has a compact vector-based expression that is optimal for computer programming. The Cartesian nature of this algorithm makes it fit easily into modern molecular simulation packages as compared with spherical coordinate-based algorithms. A software library based on this algorithm has been implemented in C++11 and has been released.« less

Trees, bialgebras and intrinsic numerical algorithms

NASA Technical Reports Server (NTRS)

Crouch, Peter; Grossman, Robert; Larson, Richard

1990-01-01

Preliminary work about intrinsic numerical integrators evolving on groups is described. Fix a finite dimensional Lie group G; let g denote its Lie algebra, and let Y(sub 1),...,Y(sub N) denote a basis of g. A class of numerical algorithms is presented that approximate solutions to differential equations evolving on G of the form: dot-x(t) = F(x(t)), x(0) = p is an element of G. The algorithms depend upon constants c(sub i) and c(sub ij), for i = 1,...,k and j is less than i. The algorithms have the property that if the algorithm starts on the group, then it remains on the group. In addition, they also have the property that if G is the abelian group R(N), then the algorithm becomes the classical Runge-Kutta algorithm. The Cayley algebra generated by labeled, ordered trees is used to generate the equations that the coefficients c(sub i) and c(sub ij) must satisfy in order for the algorithm to yield an rth order numerical integrator and to analyze the resulting algorithms.

Electro-optic tracking R&D for defense surveillance

NASA Astrophysics Data System (ADS)

Sutherland, Stuart; Woodruff, Chris J.

1995-09-01

Two aspects of work on automatic target detection and tracking for electro-optic (EO) surveillance are described. Firstly, a detection and tracking algorithm test-bed developed by DSTO and running on a PC under Windows NT is being used to assess candidate algorithms for unresolved and minimally resolved target detection. The structure of this test-bed is described and examples are given of its user interfaces and outputs. Secondly, a development by Australian industry under a Defence-funded contract, of a reconfigurable generic track processor (GTP) is outlined. The GTP will include reconfigurable image processing stages and target tracking algorithms. It will be used to demonstrate to the Australian Defence Force automatic detection and tracking capabilities, and to serve as a hardware base for real time algorithm refinement.

NIRSS Upgrades: Final Report

NASA Technical Reports Server (NTRS)

Politovich, Marcia K.

2007-01-01

This year we were able to further the NIRSS program by re-writing the data ingest and display code from LabVIEW to C++ and Java. This was leveraged by a University of Colorado Computer Science Department Senior Project. The upgrade made the display more portable and upgradeable. Comparisons with research aircraft flights conducted during AIRS-2 were also done and demonstrate reasonable skill in determining cloud altitudes and liquid water distribution. Improvements can still be made to the cloud and liquid logic. The icing hazard index was not evaluated here since that represents work in progress and needs to be made compatible with the new CIP-Severity algorithm. CIP is the Current Icing Potential product that uses a combination decision tree/fuzzy logic algorithm to combine numerical weather model output with operational sensor data (NEXRAD, GOES, METARs and voice pilot reports) to produce an hourly icing diagnosis across the CONUS. The new severity algorithm seeks to diagnose liquid water production through rising, cooling air, and depletion by ice processes. The information used by CIP is very different from that ingested by NIRSS but some common ground does exist. Additionally, the role of NIRSS and the information it both needs and provides needs to be determined in context of the Next Generation Air Traffic System (NGATS). The Weather Integrated Products Team has a plan for an Initial Operating Capability (IOC) to take place in 2012. NIRSS is not explicitly a part of that IOC but should be considered as a follow-on as part of the development path to a 2025 full capability.

Validation of Improved Broadband Shortwave and Longwave Fluxes Derived From GOES

NASA Technical Reports Server (NTRS)

Khaiyer, Mandana M.; Nordeen, Michele L.; Palikonda, Rabindra; Yi, Yuhong; Minnis, Patrick; Doelling, David R.

2009-01-01

Broadband (BB) shortwave (SW) and longwave (LW) fluxes at TOA (Top of Atmosphere) are crucial parameters in the study of climate and can be monitored over large portions of the Earth's surface using satellites. The VISST (Visible Infrared Solar Split-Window Technique) satellite retrieval algorithm facilitates derivation of these parameters from the Geostationery Operational Environmental Satellites (GOES). However, only narrowband (NB) fluxes are available from GOES, so this derivation requires use of narrowband-to-broadband (NB-BB) conversion coefficients. The accuracy of these coefficients affects the validity of the derived broadband (BB) fluxes. Most recently, NB-BB fits were re-derived using the NB fluxes from VISST/GOES data with BB fluxes observed by the CERES (Clouds and the Earth's Radiant Energy Budget) instrument aboard Terra, a sun-synchronous polar-orbiting satellite that crosses the equator at 10:30 LT. Subsequent comparison with ARM's (Atmospheric Radiation Measurement) BBHRP (Broadband Heating Rate Profile) BB fluxes revealed that while the derived broadband fluxes agreed well with CERES near the Terra overpass times, the accuracy of both LW and SW fluxes decreased farther away from the overpass times. Terra's orbit hampers the ability of the NB-BB fits to capture diurnal variability. To account for this in the LW, seasonal NB-BB fits are derived separately for day and night. Information from hourly SW BB fluxes from the Meteosat-8 Geostationary Earth Radiation Budget (GERB) is employed to include samples over the complete solar zenith angle (SZA) range sampled by Terra. The BB fluxes derived from these improved NB-BB fits are compared to BB fluxes computed with a radiative transfer model.

Earthquake fracture energy inferred from kinematic rupture models on extended faults

USGS Publications Warehouse

Tinti, E.; Spudich, P.; Cocco, M.

2005-01-01

We estimate fracture energy on extended faults for several recent earthquakes by retrieving dynamic traction evolution at each point on the fault plane from slip history imaged by inverting ground motion waveforms. We define the breakdown work (Wb) as the excess of work over some minimum traction level achieved during slip. Wb is equivalent to "seismological" fracture energy (G) in previous investigations. Our numerical approach uses slip velocity as a boundary condition on the fault. We employ a three-dimensional finite difference algorithm to compute the dynamic traction evolution in the time domain during the earthquake rupture. We estimate Wb by calculating the scalar product between dynamic traction and slip velocity vectors. This approach does not require specifying a constitutive law and assuming dynamic traction to be collinear with slip velocity. If these vectors are not collinear, the inferred breakdown work depends on the initial traction level. We show that breakdown work depends on the square of slip. The spatial distribution of breakdown work in a single earthquake is strongly correlated with the slip distribution. Breakdown work density and its integral over the fault, breakdown energy, scale with seismic moment according to a power law (with exponent 0.59 and 1.18, respectively). Our estimates of breakdown work range between 4 ?? 105 and 2 ?? 107 J/m2 for earthquakes having moment magnitudes between 5.6 and 7.2. We also compare our inferred values with geologic surface energies. This comparison might suggest that breakdown work for large earthquakes goes primarily into heat production. Copyright 2005 by the American Geophysical Union.

China takes microgravity work to new heights | Science | AAAS

Science.gov Websites

China takes microgravity work to new heights By Dennis Normile Apr. 5, 2016 , 2:00 PM China's space :10.1126/science.aaf9876 Dennis Normile More from News illustration of GOES-17 Cooling failure threatens

Nondestructive evaluation of soluble solid content in strawberry by near infrared spectroscopy

NASA Astrophysics Data System (ADS)

Guo, Zhiming; Huang, Wenqian; Chen, Liping; Wang, Xiu; Peng, Yankun

This paper indicates the feasibility to use near infrared (NIR) spectroscopy combined with synergy interval partial least squares (siPLS) algorithms as a rapid nondestructive method to estimate the soluble solid content (SSC) in strawberry. Spectral preprocessing methods were optimized selected by cross-validation in the model calibration. Partial least squares (PLS) algorithm was conducted on the calibration of regression model. The performance of the final model was back-evaluated according to root mean square error of calibration (RMSEC) and correlation coefficient (R2 c) in calibration set, and tested by mean square error of prediction (RMSEP) and correlation coefficient (R2 p) in prediction set. The optimal siPLS model was obtained with after first derivation spectra preprocessing. The measurement results of best model were achieved as follow: RMSEC = 0.2259, R2 c = 0.9590 in the calibration set; and RMSEP = 0.2892, R2 p = 0.9390 in the prediction set. This work demonstrated that NIR spectroscopy and siPLS with efficient spectral preprocessing is a useful tool for nondestructively evaluation SSC in strawberry.

Low-complexity R-peak detection in ECG signals: a preliminary step towards ambulatory fetal monitoring.

PubMed

Rooijakkers, Michiel; Rabotti, Chiara; Bennebroek, Martijn; van Meerbergen, Jef; Mischi, Massimo

2011-01-01

Non-invasive fetal health monitoring during pregnancy has become increasingly important. Recent advances in signal processing technology have enabled fetal monitoring during pregnancy, using abdominal ECG recordings. Ubiquitous ambulatory monitoring for continuous fetal health measurement is however still unfeasible due to the computational complexity of noise robust solutions. In this paper an ECG R-peak detection algorithm for ambulatory R-peak detection is proposed, as part of a fetal ECG detection algorithm. The proposed algorithm is optimized to reduce computational complexity, while increasing the R-peak detection quality compared to existing R-peak detection schemes. Validation of the algorithm is performed on two manually annotated datasets, the MIT/BIH Arrhythmia database and an in-house abdominal database. Both R-peak detection quality and computational complexity are compared to state-of-the-art algorithms as described in the literature. With a detection error rate of 0.22% and 0.12% on the MIT/BIH Arrhythmia and in-house databases, respectively, the quality of the proposed algorithm is comparable to the best state-of-the-art algorithms, at a reduced computational complexity.

The GOES-R Advanced Baseline Imager: detector spectral response effects on thermal emissive band calibration

NASA Astrophysics Data System (ADS)

Pearlman, Aaron J.; Padula, Francis; Cao, Changyong; Wu, Xiangqian

2015-10-01

The Advanced Baseline Imager (ABI) will be aboard the National Oceanic and Atmospheric Administration's Geostationary Operational Environmental Satellite R-Series (GOES-R) to supply data needed for operational weather forecasts and long-term climate variability studies, which depend on high quality data. Unlike the heritage operational GOES systems that have two or four detectors per band, ABI has hundreds of detectors per channel requiring calibration coefficients for each one. This increase in number of detectors poses new challenges for next generation sensors as each detector has a unique spectral response function (SRF) even though only one averaged SRF per band is used operationally to calibrate each detector. This simplified processing increases computational efficiency. Using measured system-level SRF data from pre-launch testing, we have the opportunity to characterize the calibration impact using measured SRFs, both per detector and as an average of detector-level SRFs similar to the operational version. We calculated the spectral response impacts for the thermal emissive bands (TEB) theoretically, by simulating the ABI response viewing an ideal blackbody and practically, with the measured ABI response to an external reference blackbody from the pre-launch TEB calibration test. The impacts from the practical case match the theoretical results using an ideal blackbody. The observed brightness temperature trends show structure across the array with magnitudes as large as 0.1 K for and 12 (9.61 µm), and 0.25 K for band 14 (11.2 µm) for a 300 K blackbody. The trends in the raw ABI signal viewing the blackbody support the spectral response measurements results, since they show similar trends in bands 12 (9.61µm), and 14 (11.2 µm), meaning that the spectral effects dominate the response differences between detectors for these bands. We further validated these effects using the radiometric bias calculated between calibrations using the external blackbody and another blackbody, the ABI on-board calibrator. Using the detector-level SRFs reduces the structure across the arrays but leaves some residual bias. Further understanding of this bias could lead to refinements of the blackbody thermal model. This work shows the calibration impacts of using an average SRF across many detectors instead of accounting for each detector SRF independently in the TEB calibration. Note that these impacts neglect effects from the spectral sampling of Earth scene radiances that include atmospheric effects, which may further contribute to artifacts post-launch and cannot be mitigated by processing with detector-level SRFs. This study enhances the ability to diagnose anomalies on-orbit and reduce calibration uncertainty for improved system performance.

"Response to Comments": Straw Makeovers, Dogmatic Holism, and Interesting Conversation

ERIC Educational Resources Information Center

Howe, Kenneth R.

2009-01-01

This paper presents the author's response to commentaries by Eric Bredo, R. Burke Johnson, and Linda Tillman on his article "Positivist Dogmas, Rhetoric, and the Education Science Question." Each of the commentaries goes beyond merely characterizing and assessing the author's analysis to also suggest an alternative emphasis, if not an alternative…

CrAlN coating to enhance the power loss and magnetostriction in grain oriented electrical steel

NASA Astrophysics Data System (ADS)

Goel, Vishu; Anderson, Philip; Hall, Jeremy; Robinson, Fiona; Bohm, Siva

2016-05-01

Grain oriented electrical steels (GOES) are coated with aluminium orthophosphate on top of a forsterite (Mg2SiO4) layer to provide stress and insulation resistance to reduce the power loss and magnetostriction. In this work Chromium Aluminium Nitride (CrAlN) was coated on GOES samples with electron beam physical vapour deposition and was tested in the single strip and magnetostriction tester to measure the power loss and magnetostriction before and after coating. Power loss was reduced by 2% after coating and 6 % post annealing at 800 °C. For applied compressive stress of 6 MPa, the magnetostrictive strain was zero with the CrAlN coating as compared to 22 and 24 μɛ for fully finished GOES and GOES without phosphate coating. The thickness of the coating was found to be 1.9 ± 0.2 μm estimated with Glow Discharge Optical Emission Spectroscopy (GDOES). The magnetic domain imaging showed domain narrowing after coating. The reduction in power loss and magnetostriction was due to the large residual compressive stress and Young's modulus (270 GPa) of the coating.

Several thoughts for using new satellite remote sensing and global modeling for aerosol and cloud climate studies

NASA Astrophysics Data System (ADS)

Nakajima, Teruyuki; Hashimoto, Makiko; Takenaka, Hideaki; Goto, Daisuke; Oikawa, Eiji; Suzuki, Kentaroh; Uchida, Junya; Dai, Tie; Shi, Chong

2017-04-01

The rapid growth of satellite remote sensing technologies in the last two decades widened the utility of satellite data for understanding climate impacts of aerosols and clouds. The climate modeling community also has received the benefit of the earth observation and nowadays closed-collaboration of the two communities make us possible to challenge various applications for societal problems, such as for global warming and global-scale air pollution and others. I like to give several thoughts of new algorithm developments, model use of satellite data for climate impact studies and societal applications related with aerosols and clouds. Important issues are 1) Better aerosol detection and solar energy application using expanded observation ability of the third generation geostationary satellites, i.e. Himawari-8, GOES-R and future MTG, 2) Various observation functions by directional, polarimetric, and high resolution near-UV band by MISR, POLDER&PARASOL, GOSAT/CAI and future GOSAT2/CAI2, 3) Various applications of general purpose-imagers, MODIS, VIIRS and future GCOM-C/SGLI, and 4) Climate studies of aerosol and cloud stratification and convection with active and passive sensors, especially climate impact of BC aerosols using CLOUDSAT&CALIPSO and future Earth Explorer/EarthCARE.

Study on ice cloud optical thickness retrieval with MODIS IR spectral bands

NASA Astrophysics Data System (ADS)

Zhang, Hong; Li, Jun

2005-01-01

The operational Moderate-Resolution Imaging Spectroradiometer (MODIS) products for cloud properties such as cloud-top pressure (CTP), effective cloud amount (ECA), cloud particle size (CPS), cloud optical thickness (COT), and cloud phase (CP) have been available for users globally. An approach to retrieve COT is investigated using MODIS infrared (IR) window spectral bands (8.5 mm, 11mm, and 12 mm). The COT retrieval from MODIS IR bands has the potential to provide microphysical properties with high spatial resolution during night. The results are compared with those from operational MODIS products derived from the visible (VIS) and near-infrared (NIR) bands during day. Sensitivity of COT to MODIS spectral brightness temperature (BT) and BT difference (BTD) values is studied. A look-up table is created from the cloudy radiative transfer model accounting for the cloud absorption and scattering for the cloud microphysical property retrieval. The potential applications and limitations are also discussed. This algorithm can be applied to the future imager systems such as Visible/Infrared Imager/Radiometer Suite (VIIRS) on the National Polar-orbiting Operational Environmental Satellite System (NPOESS) and Advanced Baseline Imager (ABI) on the Geostationary Operational Environmental Satellite (GOES)-R.

Modeling 13.3nm Fe XXIII Flare Emissions Using the GOES-R EXIS Instrument

NASA Astrophysics Data System (ADS)

Rook, H.; Thiemann, E.

2017-12-01

The solar EUV spectrum is dominated by atomic transitions in ionized atoms in the solar atmosphere. As solar flares evolve, plasma temperatures and densities change, influencing abundances of various ions, changing intensities of different EUV wavelengths observed from the sun. Quantifying solar flare spectral irradiance is important for constraining models of Earth's atmosphere, improving communications quality, and controlling satellite navigation. However, high time cadence measurements of flare irradiance across the entire EUV spectrum were not available prior to the launch of SDO. The EVE MEGS-A instrument aboard SDO collected 0.1nm EUV spectrum data from 2010 until 2014, when the instrument failed. No current or future instrument is capable of similar high resolution and time cadence EUV observation. This necessitates a full EUV spectrum model to study EUV phenomena at Earth. It has been recently demonstrated that one hot flare EUV line, such as the 13.3nm Fe XXIII line, can be used to model cooler flare EUV line emissions, filling the role of MEGS-A. Since unblended measurements of Fe XXIII are typically unavailable, a proxy for the Fe XXIII line must be found. In this study, we construct two models of this line, first using the GOES 0.1-0.8nm soft x-ray (SXR) channel as the Fe XXIII proxy, and second using a physics-based model dependent on GOES emission measure and temperature data. We determine that the more sophisticated physics-based model shows better agreement with Fe XXIII measurements, although the simple proxy model also performs well. We also conclude that the high correlation between Fe XXIII emissions and the GOES 0.1-0.8nm band is because both emissions tend to peak near the GOES emission measure peak despite large differences in their contribution functions.

The GOES-16 Energetic Heavy Ion Sensor (EHIS) Ion Composition and Flux Measurements

NASA Astrophysics Data System (ADS)

Connell, J. J.; Lopate, C.

2017-12-01

The Energetic Heavy Ion Sensor (EHIS) was built by the University of New Hampshire, subcontracted to Assurance Technology Corporation, as part of the Space Environmental In-Situ Suite (SEISS) on the new GOES-16 satellite (formerly GOES-R) in Geostationary orbit. EHIS measures energetic ions over the range 10-200 MeV for protons, and energy ranges for heavy ions corresponding to the same stopping range (e.g., 19-207 MeV/u for carbon and 38-488 MeV/u for iron). EHIS uses the Angle Detecting Inclined Sensors (ADIS) technique to provide single-element charge resolution. Though on an operational mission for Space Weather monitoring, EHIS can thus provide a new source of high quality Solar Particle Event (SPE) data for science studies. With a high rate of on-board processing ( 2000 events/s), EHIS will provide exceptional statistics for ion composition measurements in large SPEs. For the GOES Level 1-B and Level 2 data products, heavy ions are distinguished in EHIS using pulse-height analysis with on-board processing producing charge histograms for five energy bands. Fits to these data are normalized to priority rate data on the ground. The instrumental cadence for histograms is 1 minute and the primary Level 1-B heavy ion data products are 1-minute and 5-minute averages. We discuss the preliminary EHIS heavy ion data results which show elemental peaks from H to Fe, with peaks for the isotopes D and 3He. (GOES-16 was launched in 19 November, 2016 and data has, though July 2017, been dominated by Galactic Cosmic Rays.) The EHIS instrument development project was funded by NASA under contract NNG06HX01C.

Dynamic Pricing Criteria in Linear Programming

DTIC Science & Technology

1988-07-01

DTICE’ECTE h QSEPO08 19880 Department of Operations Researchs Stanford University Stanford, CA 94305 Fl . dommd lum b dLvulbcjasa Im %ailmft@d.I &~ T...information about positive ones. 38 C- M .9 ~ ,~- - ~ fl .’ %’% ’ % % .,h.] However, this rule works extremely well on the PILOT set, achieving...34 .r " .:." ," "e .-r".’.€ .-,N., N REFERENCES [1] Adler, I., Resende, M.G. and Veiga , G. (1986). An implementation of Karmax- kar’s algorithm for

Three Dimensional Reconstruction Algorithm for Imaging Pathophysiological Signals Within Breast Tissue Using Near Infrared Light

DTIC Science & Technology

2006-07-01

of water, gelatin (G2625, Sigma Inc.), India ink (for absorption), and titanium dioxide powder (for scatter) (TiO2, Sigma Inc.) is poured into a mold...R. C., Ference, R. J, Refractive index of some mammalian tissue using a fiber optic cladding method. Applied Optics, 1989. 28(12): p. 2297-2303. 3...scans. The NIR system utilizes six optical wavelengths from 660 to 850 nm using intensity modulated diode lasers nominally working at 100 MHz

An efficient framework for optimization and parameter sensitivity analysis in arterial growth and remodeling computations

PubMed Central

Sankaran, Sethuraman; Humphrey, Jay D.; Marsden, Alison L.

2013-01-01

Computational models for vascular growth and remodeling (G&R) are used to predict the long-term response of vessels to changes in pressure, flow, and other mechanical loading conditions. Accurate predictions of these responses are essential for understanding numerous disease processes. Such models require reliable inputs of numerous parameters, including material properties and growth rates, which are often experimentally derived, and inherently uncertain. While earlier methods have used a brute force approach, systematic uncertainty quantification in G&R models promises to provide much better information. In this work, we introduce an efficient framework for uncertainty quantification and optimal parameter selection, and illustrate it via several examples. First, an adaptive sparse grid stochastic collocation scheme is implemented in an established G&R solver to quantify parameter sensitivities, and near-linear scaling with the number of parameters is demonstrated. This non-intrusive and parallelizable algorithm is compared with standard sampling algorithms such as Monte-Carlo. Second, we determine optimal arterial wall material properties by applying robust optimization. We couple the G&R simulator with an adaptive sparse grid collocation approach and a derivative-free optimization algorithm. We show that an artery can achieve optimal homeostatic conditions over a range of alterations in pressure and flow; robustness of the solution is enforced by including uncertainty in loading conditions in the objective function. We then show that homeostatic intramural and wall shear stress is maintained for a wide range of material properties, though the time it takes to achieve this state varies. We also show that the intramural stress is robust and lies within 5% of its mean value for realistic variability of the material parameters. We observe that prestretch of elastin and collagen are most critical to maintaining homeostasis, while values of the material properties are most critical in determining response time. Finally, we outline several challenges to the G&R community for future work. We suggest that these tools provide the first systematic and efficient framework to quantify uncertainties and optimally identify G&R model parameters. PMID:23626380

Improved liver R2* mapping by pixel-wise curve fitting with adaptive neighborhood regularization.

PubMed

Wang, Changqing; Zhang, Xinyuan; Liu, Xiaoyun; He, Taigang; Chen, Wufan; Feng, Qianjin; Feng, Yanqiu

2018-08-01

To improve liver R2* mapping by incorporating adaptive neighborhood regularization into pixel-wise curve fitting. Magnetic resonance imaging R2* mapping remains challenging because of the serial images with low signal-to-noise ratio. In this study, we proposed to exploit the neighboring pixels as regularization terms and adaptively determine the regularization parameters according to the interpixel signal similarity. The proposed algorithm, called the pixel-wise curve fitting with adaptive neighborhood regularization (PCANR), was compared with the conventional nonlinear least squares (NLS) and nonlocal means filter-based NLS algorithms on simulated, phantom, and in vivo data. Visually, the PCANR algorithm generates R2* maps with significantly reduced noise and well-preserved tiny structures. Quantitatively, the PCANR algorithm produces R2* maps with lower root mean square errors at varying R2* values and signal-to-noise-ratio levels compared with the NLS and nonlocal means filter-based NLS algorithms. For the high R2* values under low signal-to-noise-ratio levels, the PCANR algorithm outperforms the NLS and nonlocal means filter-based NLS algorithms in the accuracy and precision, in terms of mean and standard deviation of R2* measurements in selected region of interests, respectively. The PCANR algorithm can reduce the effect of noise on liver R2* mapping, and the improved measurement precision will benefit the assessment of hepatic iron in clinical practice. Magn Reson Med 80:792-801, 2018. © 2018 International Society for Magnetic Resonance in Medicine. © 2018 International Society for Magnetic Resonance in Medicine.

The Discriminant Analysis Flare Forecasting System (DAFFS)

NASA Astrophysics Data System (ADS)

Leka, K. D.; Barnes, Graham; Wagner, Eric; Hill, Frank; Marble, Andrew R.

2016-05-01

The Discriminant Analysis Flare Forecasting System (DAFFS) has been developed under NOAA/Small Business Innovative Research funds to quantitatively improve upon the NOAA/SWPC flare prediction. In the Phase-I of this project, it was demonstrated that DAFFS could indeed improve by the requested 25% most of the standard flare prediction data products from NOAA/SWPC. In the Phase-II of this project, a prototype has been developed and is presently running autonomously at NWRA.DAFFS uses near-real-time data from NOAA/GOES, SDO/HMI, and the NSO/GONG network to issue both region- and full-disk forecasts of solar flares, based on multi-variable non-parametric Discriminant Analysis. Presently, DAFFS provides forecasts which match those provided by NOAA/SWPC in terms of thresholds and validity periods (including 1-, 2-, and 3- day forecasts), although issued twice daily. Of particular note regarding DAFFS capabilities are the redundant system design, automatically-generated validation statistics and the large range of customizable options available. As part of this poster, a description of the data used, algorithm, performance and customizable options will be presented, as well as a demonstration of the DAFFS prototype.DAFFS development at NWRA is supported by NOAA/SBIR contracts WC-133R-13-CN-0079 and WC-133R-14-CN-0103, with additional support from NASA contract NNH12CG10C, plus acknowledgment to the SDO/HMI and NSO/GONG facilities and NOAA/SWPC personnel for data products, support, and feedback. DAFFS is presently ready for Phase-III development.

When Working Becomes Hazardous. Punching, Spitting, Swearing, Shooting: Violence at Work Goes Global.

ERIC Educational Resources Information Center

World of Work, 1998

1998-01-01

Workplace violence has gone global, crossing borders, work settings, and occupational groups. A report from the International Labor Organization points out high-risk occupations and indicates that women are especially vulnerable. It highlights the problem and provides ways for policymakers to remove violence from the workplace. (JOW)

A single scan skeletonization algorithm: application to medical imaging of trabecular bone

NASA Astrophysics Data System (ADS)

Arlicot, Aurore; Amouriq, Yves; Evenou, Pierre; Normand, Nicolas; Guédon, Jean-Pierre

2010-03-01

Shape description is an important step in image analysis. The skeleton is used as a simple, compact representation of a shape. A skeleton represents the line centered in the shape and must be homotopic and one point wide. Current skeletonization algorithms compute the skeleton over several image scans, using either thinning algorithms or distance transforms. The principle of thinning is to delete points as one goes along, preserving the topology of the shape. On the other hand, the maxima of the local distance transform identifies the skeleton and is an equivalent way to calculate the medial axis. However, with this method, the skeleton obtained is disconnected so it is required to connect all the points of the medial axis to produce the skeleton. In this study we introduce a translated distance transform and adapt an existing distance driven homotopic algorithm to perform skeletonization with a single scan and thus allow the processing of unbounded images. This method is applied, in our study, on micro scanner images of trabecular bones. We wish to characterize the bone micro architecture in order to quantify bone integrity.

SIMULATIONS OF 2D AND 3D THERMOCAPILLARY FLOWS BY A LEAST-SQUARES FINITE ELEMENT METHOD. (R825200)

EPA Science Inventory

Numerical results for time-dependent 2D and 3D thermocapillary flows are presented in this work. The numerical algorithm is based on the Crank-Nicolson scheme for time integration, Newton's method for linearization, and a least-squares finite element method, together with a matri...

Nonconvergence of the Wang-Landau algorithms with multiple random walkers.

PubMed

Belardinelli, R E; Pereyra, V D

2016-05-01

This paper discusses some convergence properties in the entropic sampling Monte Carlo methods with multiple random walkers, particularly in the Wang-Landau (WL) and 1/t algorithms. The classical algorithms are modified by the use of m-independent random walkers in the energy landscape to calculate the density of states (DOS). The Ising model is used to show the convergence properties in the calculation of the DOS, as well as the critical temperature, while the calculation of the number π by multiple dimensional integration is used in the continuum approximation. In each case, the error is obtained separately for each walker at a fixed time, t; then, the average over m walkers is performed. It is observed that the error goes as 1/sqrt[m]. However, if the number of walkers increases above a certain critical value m>m_{x}, the error reaches a constant value (i.e., it saturates). This occurs for both algorithms; however, it is shown that for a given system, the 1/t algorithm is more efficient and accurate than the similar version of the WL algorithm. It follows that it makes no sense to increase the number of walkers above a critical value m_{x}, since it does not reduce the error in the calculation. Therefore, the number of walkers does not guarantee convergence.

Preparing for the Next Generation of Direct Broadcast

NASA Astrophysics Data System (ADS)

Shin, H.; Friedman Dubey, K.; Baptiste, E.; Prasad, K.; Lawrence, D.

2010-12-01

With the anticipated launch of NPP, JPSS-1 and GOES-R in the next five years, the flow of weather data to users will rise ten times (Berchoff, 2009). This volume of data will put a strain on the government infrastructure tasked for data distribution, which could limit real-time data distribution to government users only, forcing others to retrieve their data days to weeks later. In order to receive real-time data, direct reception will become a necessity. SeaSpace Corporation has created a complete solution in anticipation of the forthcoming needs of data users. This solution is made up of four parts: 1) ground reception stations, 2) software to process the data into products, 3) data storage hardware, and 4) data cataloging software and server. The ground station component consists of two systems, an X/L/S-band tracking system and an L-band geostationary system. The combined X-, L-, and S-band reception capabilities are included to ensure the user can receive the maximum amount of data. The X-band receiver in this system can receive data from Terra, Aqua, NPP, JPSS, Oceansat-2, and FY-3. The L-band receiver can currently receive NOAA and MetOp. The follow-on to MetOp will be assigned the mid-morning orbit in the next generation constellation, ensuring L-band reception will continue to be a necessity. The S-band is used for DMSP reception, which may, in the near-future, become more widely available to non-defense clients. The L-band stationary antenna in the proposed solution is used for reception of geostationary satellites, such as GOES, COMS, and MTSAT. Upon launch, GOES-R data can be received with hardware/software upgrade. Once the data is received by the ground stations, TeraScan’s Rapid Environmental Processing System (REPS) automatically processes the data through level 3 products using the official NOAA and NASA algorithms. REPS can process large amounts of satellite data incredibly quickly: for instance, all MODIS products are produced in less than fifteen minutes. After processing, the raw data and products are moved to TeraVault™, SeaSpace’s data storage solution. TeraVault™ comes standard with 84 TB of storage, can be easily expanded, and allows online and readily accessible storage for data. In order to easily manage data of this volume, SeaSpace recommends the TeraCat™ data catalog and retrieval system, which gives users and their customers a web-based interface to search for and order their data. A full direct-reception solution is the only way to guarantee real-time access to the next generation of environmental satellite data. The currently over-tasked system of data distribution via the internet is ill-equipped to service local and foreign customers on a real-time basis now, and this will only get worse as more data comes online.

Creating Situational Awareness in Spacecraft Operations with the Machine Learning Approach

NASA Astrophysics Data System (ADS)

Li, Z.

2016-09-01

This paper presents a machine learning approach for the situational awareness capability in spacecraft operations. There are two types of time dependent data patterns for spacecraft datasets: the absolute time pattern (ATP) and the relative time pattern (RTP). The machine learning captures the data patterns of the satellite datasets through the data training during the normal operations, which is represented by its time dependent trend. The data monitoring compares the values of the incoming data with the predictions of machine learning algorithm, which can detect any meaningful changes to a dataset above the noise level. If the difference between the value of incoming telemetry and the machine learning prediction are larger than the threshold defined by the standard deviation of datasets, it could indicate the potential anomaly that may need special attention. The application of the machine-learning approach to the Advanced Himawari Imager (AHI) on Japanese Himawari spacecraft series is presented, which has the same configuration as the Advanced Baseline Imager (ABI) on Geostationary Environment Operational Satellite (GOES) R series. The time dependent trends generated by the data-training algorithm are in excellent agreement with the datasets. The standard deviation in the time dependent trend provides a metric for measuring the data quality, which is particularly useful in evaluating the detector quality for both AHI and ABI with multiple detectors in each channel. The machine-learning approach creates the situational awareness capability, and enables engineers to handle the huge data volume that would have been impossible with the existing approach, and it leads to significant advances to more dynamic, proactive, and autonomous spacecraft operations.

Optical Algorithms at Satellite Wavelengths for Total Suspended Matter in Tropical Coastal Waters.

PubMed

Ouillon, Sylvain; Douillet, Pascal; Petrenko, Anne; Neveux, Jacques; Dupouy, Cécile; Froidefond, Jean-Marie; Andréfouët, Serge; Muñoz-Caravaca, Alain

2008-07-10

Is it possible to derive accurately Total Suspended Matter concentration or its proxy, turbidity, from remote sensing data in tropical coastal lagoon waters? To investigate this question, hyperspectral remote sensing reflectance, turbidity and chlorophyll pigment concentration were measured in three coral reef lagoons. The three sites enabled us to get data over very diverse environments: oligotrophic and sediment-poor waters in the southwest lagoon of New Caledonia, eutrophic waters in the Cienfuegos Bay (Cuba), and sediment-rich waters in the Laucala Bay (Fiji). In this paper, optical algorithms for turbidity are presented per site based on 113 stations in New Caledonia, 24 stations in Cuba and 56 stations in Fiji. Empirical algorithms are tested at satellite wavebands useful to coastal applications. Global algorithms are also derived for the merged data set (193 stations). The performances of global and local regression algorithms are compared. The best one-band algorithms on all the measurements are obtained at 681 nm using either a polynomial or a power model. The best two-band algorithms are obtained with R412/R620, R443/R670 and R510/R681. Two three-band algorithms based on Rrs620.Rrs681/Rrs412 and Rrs620.Rrs681/Rrs510 also give fair regression statistics. Finally, we propose a global algorithm based on one or three bands: turbidity is first calculated from Rrs681 and then, if < 1 FTU, it is recalculated using an algorithm based on Rrs620.Rrs681/Rrs412. On our data set, this algorithm is suitable for the 0.2-25 FTU turbidity range and for the three sites sampled (mean bias: 3.6 %, rms: 35%, mean quadratic error: 1.4 FTU). This shows that defining global empirical turbidity algorithms in tropical coastal waters is at reach.

Adaptive Correlation Model for Visual Tracking Using Keypoints Matching and Deep Convolutional Feature.

PubMed

Li, Yuankun; Xu, Tingfa; Deng, Honggao; Shi, Guokai; Guo, Jie

2018-02-23

Although correlation filter (CF)-based visual tracking algorithms have achieved appealing results, there are still some problems to be solved. When the target object goes through long-term occlusions or scale variation, the correlation model used in existing CF-based algorithms will inevitably learn some non-target information or partial-target information. In order to avoid model contamination and enhance the adaptability of model updating, we introduce the keypoints matching strategy and adjust the model learning rate dynamically according to the matching score. Moreover, the proposed approach extracts convolutional features from a deep convolutional neural network (DCNN) to accurately estimate the position and scale of the target. Experimental results demonstrate that the proposed tracker has achieved satisfactory performance in a wide range of challenging tracking scenarios.

CSE database: extended annotations and new recommendations for ECG software testing.

PubMed

Smíšek, Radovan; Maršánová, Lucie; Němcová, Andrea; Vítek, Martin; Kozumplík, Jiří; Nováková, Marie

2017-08-01

Nowadays, cardiovascular diseases represent the most common cause of death in western countries. Among various examination techniques, electrocardiography (ECG) is still a highly valuable tool used for the diagnosis of many cardiovascular disorders. In order to diagnose a person based on ECG, cardiologists can use automatic diagnostic algorithms. Research in this area is still necessary. In order to compare various algorithms correctly, it is necessary to test them on standard annotated databases, such as the Common Standards for Quantitative Electrocardiography (CSE) database. According to Scopus, the CSE database is the second most cited standard database. There were two main objectives in this work. First, new diagnoses were added to the CSE database, which extended its original annotations. Second, new recommendations for diagnostic software quality estimation were established. The ECG recordings were diagnosed by five new cardiologists independently, and in total, 59 different diagnoses were found. Such a large number of diagnoses is unique, even in terms of standard databases. Based on the cardiologists' diagnoses, a four-round consensus (4R consensus) was established. Such a 4R consensus means a correct final diagnosis, which should ideally be the output of any tested classification software. The accuracy of the cardiologists' diagnoses compared with the 4R consensus was the basis for the establishment of accuracy recommendations. The accuracy was determined in terms of sensitivity = 79.20-86.81%, positive predictive value = 79.10-87.11%, and the Jaccard coefficient = 72.21-81.14%, respectively. Within these ranges, the accuracy of the software is comparable with the accuracy of cardiologists. The accuracy quantification of the correct classification is unique. Diagnostic software developers can objectively evaluate the success of their algorithm and promote its further development. The annotations and recommendations proposed in this work will allow for faster development and testing of classification software. As a result, this might facilitate cardiologists' work and lead to faster diagnoses and earlier treatment.

Zimmermann's forest formula, infrared divergences and the QCD beta function

NASA Astrophysics Data System (ADS)

Herzog, Franz

2018-01-01

We review Zimmermann's forest formula, which solves Bogoliubov's recursive R-operation for the subtraction of ultraviolet divergences in perturbative Quantum Field Theory. We further discuss a generalisation of the R-operation which subtracts besides ultraviolet also Euclidean infrared divergences. This generalisation, which goes under the name of the R*-operation, can be used efficiently to compute renormalisation constants. We will discuss several results obtained by this method with focus on the QCD beta function at five loops as well as the application to hadronic Higgs boson decay rates at N4LO. This article summarizes a talk given at the Wolfhart Zimmermann Memorial Symposium.

VISION User Guide - VISION (Verifiable Fuel Cycle Simulation) Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jacob J. Jacobson; Robert F. Jeffers; Gretchen E. Matthern

2009-08-01

The purpose of this document is to provide a guide for using the current version of the Verifiable Fuel Cycle Simulation (VISION) model. This is a complex model with many parameters; the user is strongly encouraged to read this user guide before attempting to run the model. This model is an R&D work in progress and may contain errors and omissions. It is based upon numerous assumptions. This model is intended to assist in evaluating “what if” scenarios and in comparing fuel, reactor, and fuel processing alternatives at a systems level for U.S. nuclear power. The model is not intendedmore » as a tool for process flow and design modeling of specific facilities nor for tracking individual units of fuel or other material through the system. The model is intended to examine the interactions among the components of a fuel system as a function of time varying system parameters; this model represents a dynamic rather than steady-state approximation of the nuclear fuel system. VISION models the nuclear cycle at the system level, not individual facilities, e.g., “reactor types” not individual reactors and “separation types” not individual separation plants. Natural uranium can be enriched, which produces enriched uranium, which goes into fuel fabrication, and depleted uranium (DU), which goes into storage. Fuel is transformed (transmuted) in reactors and then goes into a storage buffer. Used fuel can be pulled from storage into either separation of disposal. If sent to separations, fuel is transformed (partitioned) into fuel products, recovered uranium, and various categories of waste. Recycled material is stored until used by its assigned reactor type. Note that recovered uranium is itself often partitioned: some RU flows with recycled transuranic elements, some flows with wastes, and the rest is designated RU. RU comes out of storage if needed to correct the U/TRU ratio in new recycled fuel. Neither RU nor DU are designated as wastes. VISION is comprised of several Microsoft Excel input files, a Powersim Studio core, and several Microsoft Excel output files. All must be co-located in the same folder on a PC to function. We use Microsoft Excel 2003 and have not tested VISION with Microsoft Excel 2007. The VISION team uses both Powersim Studio 2005 and 2009 and it should work with either.« less

Analytic Calculation of Noise Power Robbing, NPR, and Polarization Isolation Degradation

NASA Technical Reports Server (NTRS)

Peters, Robert; Woolner, Peter; Ekelman, Ernest

2008-01-01

Three Geostationary Operational Environmental Satellite (GOES) R transponders (services) required analysis and measurements to develop an accurate link budget. These are a) Search and Rescue transponder which suffers from power robbing due to thermal uplink noise, b) the Data Collection Platform Report which suffers from degradation due to NPR (Noise Power Ratio), and c) GOES Rebroadcast transponder which uses a dual circular downlink L band for which there was no depolarization data. The first two services required development of extended link budget to analytically calculate the impact of these degradations which are shown to have a significant impact on the link budget. The third service required measurements of atmospheric L band CP depolarization as there were no known previous measurements and results are reported her

Use of machine learning to improve autism screening and diagnostic instruments: effectiveness, efficiency, and multi-instrument fusion

PubMed Central

Bone, Daniel; Bishop, Somer; Black, Matthew P.; Goodwin, Matthew S.; Lord, Catherine; Narayanan, Shrikanth S.

2016-01-01

Background Machine learning (ML) provides novel opportunities for human behavior research and clinical translation, yet its application can have noted pitfalls (Bone et al., 2015). In this work, we fastidiously utilize ML to derive autism spectrum disorder (ASD) instrument algorithms in an attempt to improve upon widely-used ASD screening and diagnostic tools. Methods The data consisted of Autism Diagnostic Interview-Revised (ADI-R) and Social Responsiveness Scale (SRS) scores for 1,264 verbal individuals with ASD and 462 verbal individuals with non-ASD developmental or psychiatric disorders (DD), split at age 10. Algorithms were created via a robust ML classifier, support vector machine (SVM), while targeting best-estimate clinical diagnosis of ASD vs. non-ASD. Parameter settings were tuned in multiple levels of cross-validation. Results The created algorithms were more effective (higher performing) than current algorithms, were tunable (sensitivity and specificity can be differentially weighted), and were more efficient (achieving near-peak performance with five or fewer codes). Results from ML-based fusion of ADI-R and SRS are reported. We present a screener algorithm for below (above) age 10 that reached 89.2% (86.7%) sensitivity and 59.0% (53.4%) specificity with only five behavioral codes. Conclusions ML is useful for creating robust, customizable instrument algorithms. In a unique dataset comprised of controls with other difficulties, our findings highlight limitations of current caregiver-report instruments and indicate possible avenues for improving ASD screening and diagnostic tools. PMID:27090613

Use of machine learning to improve autism screening and diagnostic instruments: effectiveness, efficiency, and multi-instrument fusion.

PubMed

Bone, Daniel; Bishop, Somer L; Black, Matthew P; Goodwin, Matthew S; Lord, Catherine; Narayanan, Shrikanth S

2016-08-01

Machine learning (ML) provides novel opportunities for human behavior research and clinical translation, yet its application can have noted pitfalls (Bone et al., 2015). In this work, we fastidiously utilize ML to derive autism spectrum disorder (ASD) instrument algorithms in an attempt to improve upon widely used ASD screening and diagnostic tools. The data consisted of Autism Diagnostic Interview-Revised (ADI-R) and Social Responsiveness Scale (SRS) scores for 1,264 verbal individuals with ASD and 462 verbal individuals with non-ASD developmental or psychiatric disorders, split at age 10. Algorithms were created via a robust ML classifier, support vector machine, while targeting best-estimate clinical diagnosis of ASD versus non-ASD. Parameter settings were tuned in multiple levels of cross-validation. The created algorithms were more effective (higher performing) than the current algorithms, were tunable (sensitivity and specificity can be differentially weighted), and were more efficient (achieving near-peak performance with five or fewer codes). Results from ML-based fusion of ADI-R and SRS are reported. We present a screener algorithm for below (above) age 10 that reached 89.2% (86.7%) sensitivity and 59.0% (53.4%) specificity with only five behavioral codes. ML is useful for creating robust, customizable instrument algorithms. In a unique dataset comprised of controls with other difficulties, our findings highlight the limitations of current caregiver-report instruments and indicate possible avenues for improving ASD screening and diagnostic tools. © 2016 Association for Child and Adolescent Mental Health.

Precipitable Water Variability Using SSM/I and GOES VAS Pathfinder Data Sets

NASA Technical Reports Server (NTRS)

Lerner, Jeffrey A.; Jedlovec, Gary J.; Kidder, Stanley Q.

1996-01-01

Determining moisture variability for all weather scenes is critical to understanding the earth's hydrologic cycle and global climate changes. Remote sensing from geostationary satellites provides the necessary temporal and spatial resolutions necessary for global change studies. Due to antenna size constraints imposed with the use of microwave radiometers, geostationary satellites have carried instruments passively measuring radiation at infrared wavelengths or shorter. The shortfall of using infrared instruments in moisture studies lies in its inability to sense terrestrial radiation through clouds. Microwave emissions, on the other hand, are mostly unaffected by cloudy atmospheres. Land surface emissivity at microwave frequencies exhibit both high temporal and spatial variability thus confining moisture retrievals at microwave frequencies to over marine atmospheres (a near uniform cold background). This study intercompares the total column integrated water content Precipitable Water, (PW) as derived from both the Special Sensor Microwave Imager (SSM/I) and the Geostationary Operational Environmental Satellite (GOES) VISSR Atmospheric Sounder (VAS) pathfinder data sets. PW is a bulk parameter often used to quantify moisture variability and is important to understanding the earth's hydrologic cycle and climate system. This research has been spawned in an effort to combine two different algorithms which together can lead to a more comprehensive quantification of global water vapor. The approach taken here is to intercompare two independent PW retrieval algorithms and to validate the resultant retrievals against an existing data set, namely the European Center for Medium range Weather Forecasts (ECMWF) model analysis data.

Estimation of precipitable water over the Amazon Basin using GOES imagery

NASA Astrophysics Data System (ADS)

Callahan, John Andrew

The Amazon Rainforest is the largest continuous rainforest on Earth. It holds a rich abundance of life containing approximately one-half of all existing plant and animal species and 20% of the world's fresh water. Climatologically, the Amazon Rainforest is a massive storehouse of carbon dioxide and water vapor and hosts hydrologic and energy cycles that influence regional and global patterns. However, this region has gone through vast land cover changes during the past several decades. Lack of conventional, in situ data sources prohibits detailed measurements to assess the climatological impact these changes may cause. This thesis applies a satellite-based, thermal infrared remote sensing algorithm to determine precipitable water in the Amazon Basin to test its applicability in the region and to measure the diurnal changes in water vapor. Imagery from the GOES geostationary satellite and estimated atmospheric conditions and radiance values derived from the NCEP/NCAR Reanalysis project were used as inputs to the Physical Split Window (PSW) technique. Retrievals of precipitable water were made every 3 hours throughout each day from 12Z to 24Z for the months of June and October, 1988 and 1995. These months correspond to when the atmosphere is not dominated by clouds during the rainy (wet) season or smoke and haze during the burning (dry) season. Monthly, daily, and diurnal aggregates of precipitable water Fields were analyzed spatially through seven zones located uniformly throughout the region. Monthly average precipitable water values were found to be 20mm to 25mm in the southeast and 45mm to 50mm in the northwest zones. Central and northwest zones showed little variation throughout the day with most areas peaking between 15Z and 21Z, representing early to late afternoon local time. Comparisons were made to nearby, coincident radiosonde observations with r ranging from 0.7 to 0.9 and MAE from 6mm to 12 mm.

IDEF5 Ontology Description Capture Method: Concepts and Formal Foundations

DTIC Science & Technology

1992-11-01

cutter comes to exist. The puzzle here goes back to Greek times iii the guise of the Ship of Theseus : if we bit by bit replace the planks of a ship...831 Barwise, J. and Perry, J., Situations and Attitudes, The MIT Press, Cambridge, 1983. [Burch 911 Burch, R., A Peircean Reduction Thesis : The

36 CFR 7.71 - Delaware Water Gap National Recreation Area.

Code of Federal Regulations, 2014 CFR

2014-07-01

... of L. R. 45012 (commonly known as the River Road). Loop Two is approximately 6 miles long and begins at the northwest end of Loop One; it goes northeasterly between the Delaware River and River Road for about one mile until it crosses River Road; then southwesterly along the ridge which is south of Hidden...

36 CFR 7.71 - Delaware Water Gap National Recreation Area.

Code of Federal Regulations, 2012 CFR

2012-07-01

... of L. R. 45012 (commonly known as the River Road). Loop Two is approximately 6 miles long and begins at the northwest end of Loop One; it goes northeasterly between the Delaware River and River Road for about one mile until it crosses River Road; then southwesterly along the ridge which is south of Hidden...

36 CFR 7.71 - Delaware Water Gap National Recreation Area.

Code of Federal Regulations, 2010 CFR

2010-07-01

... of L. R. 45012 (commonly known as the River Road). Loop Two is approximately 6 miles long and begins at the northwest end of Loop One; it goes northeasterly between the Delaware River and River Road for about one mile until it crosses River Road; then southwesterly along the ridge which is south of Hidden...

36 CFR 7.71 - Delaware Water Gap National Recreation Area.

Code of Federal Regulations, 2013 CFR

2013-07-01

... of L. R. 45012 (commonly known as the River Road). Loop Two is approximately 6 miles long and begins at the northwest end of Loop One; it goes northeasterly between the Delaware River and River Road for about one mile until it crosses River Road; then southwesterly along the ridge which is south of Hidden...

36 CFR 7.71 - Delaware Water Gap National Recreation Area.

Code of Federal Regulations, 2011 CFR

2011-07-01

... of L. R. 45012 (commonly known as the River Road). Loop Two is approximately 6 miles long and begins at the northwest end of Loop One; it goes northeasterly between the Delaware River and River Road for about one mile until it crosses River Road; then southwesterly along the ridge which is south of Hidden...

Validation of Local-Cloud Model Outputs With the GOES Satellite Imagery

NASA Astrophysics Data System (ADS)

Malek, E.

2005-05-01

Clouds (visible aggregations of minute droplets of water or tiny crystals of ice suspended in the air) affect the radiation budget of our planet by reflecting, absorbing and scattering solar radiation, and the re-emission of terrestrial radiation. They affect the weather and climate by positive or negative feedbacks. Many researchers have worked on the parameterization of clouds and their effects on the radiation budget. There is little information about ground-based approaches for continuous evaluation of cloud, such as cloud base height, cloud base temperature, and cloud coverage, at local and regional scales. This present article deals with the development of an algorithm for continuous (day and night) evaluation of cloud base temperature, cloud base height and percent of skies covered by cloud at local scale throughout the year. The Vaisala model CT-12K laser beam ceilometer is used at the Automated Surface Observing Systems (ASOS) to measure the cloud base height and report the sky conditions on an hourly basis or at shorter intervals. This laser ceilometer is a fixed-type whose transmitter and receiver point straight up at the cloud (if any) base. It is unable to measure clouds that are not above the sensor. To report cloudiness at the local scale, many of these type of ceilometers are needed. This is not a perfect method for cloud measurement. A single cloud hanging overhead the sensor will cause overcast readings, whereas, a hole in the clouds could cause a clear reading to be reported. To overcome this problem, we have set up a ventilated radiation station at Logan-Cache airport, Utah, U.S.A., since 1995, which is equipped with one of the above-mentioned ceilometers. This radiation station (composed of pyranometers, pyrgeometers and net radiometer) provides continuous measurements of incoming and outgoing shortwave and longwave radiation and the net radiation throughout the year. We have also measured the surface temperature and pressure, the 2-m air temperature and humidity, precipitation, and the 3-m wind and direction at this station. Having the air temperature, moisture, and the measured cloudless incoming longwave (atmospheric) radiation during 1999 through 2004, based upon the ASOS and the algorithm data, we found the appropriate formula (among four reported approaches) for computation of the cloudless-skies atmospheric emissivity. Considering the additional longwave radiation captured by the facing-up pyrgeometer during the cloudy skies, coming from the cloud in the wave band which the gaseous emission lacks (from 8-13 ìm), we developed an algorithm which provides the continuous 20-min cloud information (cloud base height, cloud base temperature, and percent of skies covered by cloud) over the Cache Valley during day and night throughout the year. The comparisons between the ASOS and the algorithm data during the period of 8-12 June, 2004 are reported in this article. The proposed algorithm is a promising approach for evaluation of the cloud base temperature, cloud base height, and percent of skies covered by cloud at the local scale throughout the year. It also reports the comparison between model outputs and GOES 10 satellite images.

Low-complexity R-peak detection for ambulatory fetal monitoring.

PubMed

Rooijakkers, Michael J; Rabotti, Chiara; Oei, S Guid; Mischi, Massimo

2012-07-01

Non-invasive fetal health monitoring during pregnancy is becoming increasingly important because of the increasing number of high-risk pregnancies. Despite recent advances in signal-processing technology, which have enabled fetal monitoring during pregnancy using abdominal electrocardiogram (ECG) recordings, ubiquitous fetal health monitoring is still unfeasible due to the computational complexity of noise-robust solutions. In this paper, an ECG R-peak detection algorithm for ambulatory R-peak detection is proposed, as part of a fetal ECG detection algorithm. The proposed algorithm is optimized to reduce computational complexity, without reducing the R-peak detection performance compared to the existing R-peak detection schemes. Validation of the algorithm is performed on three manually annotated datasets. With a detection error rate of 0.23%, 1.32% and 9.42% on the MIT/BIH Arrhythmia and in-house maternal and fetal databases, respectively, the detection rate of the proposed algorithm is comparable to the best state-of-the-art algorithms, at a reduced computational complexity.

Modified automatic R-peak detection algorithm for patients with epilepsy using a portable electrocardiogram recorder.

PubMed

Jeppesen, J; Beniczky, S; Fuglsang Frederiksen, A; Sidenius, P; Johansen, P

2017-07-01

Earlier studies have shown that short term heart rate variability (HRV) analysis of ECG seems promising for detection of epileptic seizures. A precise and accurate automatic R-peak detection algorithm is a necessity in a real-time, continuous measurement of HRV, in a portable ECG device. We used the portable CE marked ePatch® heart monitor to record the ECG of 14 patients, who were enrolled in the videoEEG long term monitoring unit for clinical workup of epilepsy. Recordings of the first 7 patients were used as training set of data for the R-peak detection algorithm and the recordings of the last 7 patients (467.6 recording hours) were used to test the performance of the algorithm. We aimed to modify an existing QRS-detection algorithm to a more precise R-peak detection algorithm to avoid the possible jitter Qand S-peaks can create in the tachogram, which causes error in short-term HRVanalysis. The proposed R-peak detection algorithm showed a high sensitivity (Se = 99.979%) and positive predictive value (P+ = 99.976%), which was comparable with a previously published QRS-detection algorithm for the ePatch® ECG device, when testing the same dataset. The novel R-peak detection algorithm designed to avoid jitter has very high sensitivity and specificity and thus is a suitable tool for a robust, fast, real-time HRV-analysis in patients with epilepsy, creating the possibility for real-time seizure detection for these patients.

Estimating and forecasting the precipitable water vapor from GOES satellite data at high altitude sites

NASA Astrophysics Data System (ADS)

Marín, Julio C.; Pozo, Diana; Curé, Michel

2015-01-01

In this work, we describe a method to estimate the precipitable water vapor (PWV) from Geostationary Observational Environmental Satellite (GOES) data at high altitude sites. The method was applied at Atacama Pathfinder Experiment (APEX) and Cerro Toco sites, located above 5000 m altitude in the Chajnantor plateau, in the north of Chile. It was validated using GOES-12 satellite data over the range 0-1.2 mm since submillimeter/millimeter astronomical observations are only useful within this PWV range. The PWV estimated from GOES and the Final Analyses (FNL) at APEX for 2007 and 2009 show root mean square error values of 0.23 mm and 0.36 mm over the ranges 0-0.4 mm and 0.4-1.2 mm, respectively. However, absolute relative errors of 51% and 33% were shown over these PWV ranges, respectively. We recommend using high-resolution thermodynamic profiles from the Global Forecast System (GFS) model to estimate the PWV from GOES data since they are available every three hours and at an earlier time than the FNL data. The estimated PWV from GOES/GFS agrees better with the observed PWV at both sites during night time. The largest errors are shown during daytime. Short-term PWV forecasts were implemented at both sites, applying a simple persistence method to the PWV estimated from GOES/GFS. The 12 h and 24 h PWV forecasts evaluated from August to October 2009 indicates that 25% of them show a very good agreement with observations whereas 50% of them show reasonably good agreement with observations. Transmission uncertainties calculated for PWV estimations and forecasts over the studied sites are larger over the range 0-0.4 mm than over the range 0.4-1.2 mm. Thus, the method can be used over the latter interval with more confidence.

Daily and 3-hourly Variability in Global Fire Emissions and Consequences for Atmospheric Model Predictions of Carbon Monoxide

NASA Technical Reports Server (NTRS)

Mu, M.; Randerson, J. T.; vanderWerf, G. R.; Giglio, L.; Kasibhatla, P.; Morton, D.; Collatz, G. J.; DeFries, R. S.; Hyer, E. J.; Prins, E. M.;

The Ground Flash Fraction Retrieval Algorithm Employing Differential Evolution: Simulations and Applications

NASA Technical Reports Server (NTRS)

Koshak, William; Solakiewicz, Richard

2012-01-01

The ability to estimate the fraction of ground flashes in a set of flashes observed by a satellite lightning imager, such as the future GOES-R Geostationary Lightning Mapper (GLM), would likely improve operational and scientific applications (e.g., severe weather warnings, lightning nitrogen oxides studies, and global electric circuit analyses). A Bayesian inversion method, called the Ground Flash Fraction Retrieval Algorithm (GoFFRA), was recently developed for estimating the ground flash fraction. The method uses a constrained mixed exponential distribution model to describe a particular lightning optical measurement called the Maximum Group Area (MGA). To obtain the optimum model parameters (one of which is the desired ground flash fraction), a scalar function must be minimized. This minimization is difficult because of two problems: (1) Label Switching (LS), and (2) Parameter Identity Theft (PIT). The LS problem is well known in the literature on mixed exponential distributions, and the PIT problem was discovered in this study. Each problem occurs when one allows the numerical minimizer to freely roam through the parameter search space; this allows certain solution parameters to interchange roles which leads to fundamental ambiguities, and solution error. A major accomplishment of this study is that we have employed a state-of-the-art genetic-based global optimization algorithm called Differential Evolution (DE) that constrains the parameter search in such a way as to remove both the LS and PIT problems. To test the performance of the GoFFRA when DE is employed, we applied it to analyze simulated MGA datasets that we generated from known mixed exponential distributions. Moreover, we evaluated the GoFFRA/DE method by applying it to analyze actual MGAs derived from low-Earth orbiting lightning imaging sensor data; the actual MGA data were classified as either ground or cloud flash MGAs using National Lightning Detection Network[TM] (NLDN) data. Solution error plots are provided for both the simulations and actual data analyses.

The use of satellite data for monitoring temporal and spatial patterns of fire: a comprehensive review

NASA Astrophysics Data System (ADS)

Lasaponara, R.

2009-04-01

Remotely sensed (RS) data can fruitfully support both research activities and operative monitoring of fire at different temporal and spatial scales with a synoptic view and cost effective technologies. "The contribution of remote sensing (RS) to forest fires may be grouped in three categories, according to the three phases of fire management: (i) risk estimation (before fire), (ii) detection (during fire) and (iii) assessment (after fire)" Chuvieco (2006). Relating each phase, wide research activities have been conducted over the years. (i) Risk estimation (before fire) has been mainly based on the use of RS data for (i) monitoring vegetation stress and assessing variations in vegetation moisture content, (ii) fuel type mapping, at different temporal and spatial scales from global, regional down to a local scale (using AVHRR, MODIS, TM, ASTER, Quickbird images and airborne hyperspectral and LIDAR data). Danger estimation has been mainly based on the use of AVHRR (onborad NOAA), MODIS (onboard TERRA and AQUA), VEGETATION (onboard SPOT) due to the technical characteristics (i.e. spectral, spatial and temporal resolution). Nevertheless microwave data have been also used for vegetation monitoring. (ii) Detection: identification of active fires, estimation of fire radiative energy and fire emission. AVHRR was one of the first satellite sensors used for setting up fire detection algorithms. The availbility of MODIS allowed us to obtain global fire products free downloaded from NASA web site. Sensors onboard geostationary satellite platforms, such as GOES, SEVIRI, have been used for fire detection, to obtain a high temporal resolution (at around 15 minutes) monitoring of active fires. (iii) Post fire damage assessment includes: burnt area mapping, fire emission, fire severity, vegetation recovery, fire resilience estimation, and, more recently, fire regime characterization. Chuvieco E. L. Giglio, C. Justice, 2008 Global charactrerization of fire activity: toward defining fire regimes from Earth observation data Global Change Biology vo. 14. doi: 10.1111/j.1365-2486.2008.01585.x 1-15, Chuvieco E., P. Englefield, Alexander P. Trishchenko, Yi Luo Generation of long time series of burn area maps of the boreal forest from NOAA-AVHRR composite data. Remote Sensing of Environment, Volume 112, Issue 5, 15 May 2008, Pages 2381-2396 Chuvieco Emilio 2006, Remote Sensing of Forest Fires: Current limitations and future prospects in Observing Land from Space: Science, Customers and Technology, Advances in Global Change Research Vol. 4 pp 47-51 De Santis A., E. Chuvieco Burn severity estimation from remotely sensed data: Performance of simulation versus empirical models, Remote Sensing of Environment, Volume 108, Issue 4, 29 June 2007, Pages 422-435. De Santis A., E. Chuvieco, Patrick J. Vaughan, Short-term assessment of burn severity using the inversion of PROSPECT and GeoSail models, Remote Sensing of Environment, Volume 113, Issue 1, 15 January 2009, Pages 126-136 García M., E. Chuvieco, H. Nieto, I. Aguado Combining AVHRR and meteorological data for estimating live fuel moisture content Remote Sensing of Environment, Volume 112, Issue 9, 15 September 2008, Pages 3618-3627 Ichoku C., L. Giglio, M. J. Wooster, L. A. Remer Global characterization of biomass-burning patterns using satellite measurements of fire radiative energy. Remote Sensing of Environment, Volume 112, Issue 6, 16 June 2008, Pages 2950-2962. Lasaponara R. and Lanorte, On the capability of satellite VHR QuickBird data for fuel type characterization in fragmented landscape Ecological Modelling Volume 204, Issues 1-2, 24 May 2007, Pages 79-84 Lasaponara R., A. Lanorte, S. Pignatti,2006 Multiscale fuel type mapping in fragmented ecosystems: preliminary results from Hyperspectral MIVIS and Multispectral Landsat TM data, Int. J. Remote Sens., vol. 27 (3) pp. 587-593. Lasaponara R., V. Cuomo, M. F. Macchiato, and T. Simoniello, 2003 .A self-adaptive algorithm based on AVHRR multitemporal data analysis for small active fire detection.n International Journal of Remote Sensing, vol. 24, No 8, 1723-1749. Minchella A., F. Del Frate, F. Capogna, S. Anselmi, F. Manes Use of multitemporal SAR data for monitoring vegetation recovery of Mediterranean burned areas Remote Sensing of Environment, In Press Næsset E., T. Gobakken Estimation of above- and below-ground biomass across regions of the boreal forest zone using airborne laser Remote Sensing of Environment, Volume 112, Issue 6, 16 June 2008, Pages 3079-3090 Peterson S. H, Dar A. Roberts, Philip E. Dennison Mapping live fuel moisture with MODIS data: A multiple regression approach, Remote Sensing of Environment, Volume 112, Issue 12, 15 December 2008, Pages 4272-4284. Schroeder Wilfrid, Elaine Prins, Louis Giglio, Ivan Csiszar, Christopher Schmidt, Jeffrey Morisette, Douglas Morton Validation of GOES and MODIS active fire detection products using ASTER and ETM+ data Remote Sensing of Environment, Volume 112, Issue 5, 15 May 2008, Pages 2711-2726 Shi J., T. Jackson, J. Tao, J. Du, R. Bindlish, L. Lu, K.S. Chen Microwave vegetation indices for short vegetation covers from satellite passive microwave sensor AMSR-E Remote Sensing of Environment, Volume 112, Issue 12, 15 December 2008, Pages 4285-4300 Tansey, K., Grégoire, J-M., Defourny, P., Leigh, R., Pekel, J-F., van Bogaert, E. and Bartholomé, E., 2008 A New, Global, Multi-Annual (2000-2007) Burnt Area Product at 1 km Resolution and Daily Intervals Geophysical Research Letters, VOL. 35, L01401, doi:10.1029/2007GL031567, 2008. Telesca L. and Lasaponara R., 2006; "Pre-and Post- fire Behaviural trends revealed in satellite NDVI time series" Geophysical Research Letters,., 33, L14401, doi:10.1029/2006GL026630 Telesca L. and Lasaponara R 2005 Discriminating Dynamical Patterns in Burned and Unburned Vegetational Covers by Using SPOT-VGT NDVI Data. Geophysical Research Letters,, 32, L21401, doi:10.1029/2005GL024391. Telesca L. and Lasaponara R. Investigating fire-induced behavioural trends in vegetation covers , Communications in Nonlinear Science and Numerical Simulation, 13, 2018-2023, 2008 Telesca L., A. Lanorte and R. Lasaponara, 2007. Investigating dynamical trends in burned and unburned vegetation covers by using SPOT-VGT NDVI data. Journal of Geophysics and Engineering, Vol. 4, pp. 128-138, 2007 Telesca L., R. Lasaponara, and A. Lanorte, Intra-annual dynamical persistent mechanisms in Mediterranean ecosystems revealed SPOT-VEGETATION Time Series, Ecological Complexity, 5, 151-156, 2008 Verbesselt, J., Somers, B., Lhermitte, S., Jonckheere, I., van Aardt, J., and Coppin, P. (2007) Monitoring herbaceous fuel moisture content with SPOT VEGETATION time-series for fire risk prediction in savanna ecosystems. Remote Sensing of Environment 108: 357-368. Zhang X., S. Kondragunta Temporal and spatial variability in biomass burned areas across the USA derived from the GOES fire product Remote Sensing of Environment, Volume 112, Issue 6, 16 June 2008, Pages 2886-2897 Zhang X., Shobha Kondragunta Temporal and spatial variability in biomass burned areas across the USA derived from the GOES fire product Remote Sensing of Environment, Volume 112, Issue 6, 16 June 2008, Pages 2886-2897

Advanced Fiber Optic-Based Sensing Technology for Unmanned Aircraft Systems

NASA Technical Reports Server (NTRS)

Richards, Lance; Parker, Allen R.; Piazza, Anthony; Ko, William L.; Chan, Patrick; Bakalyar, John

2011-01-01

This presentation provides an overview of fiber optic sensing technology development activities performed at NASA Dryden in support of Unmanned Aircraft Systems. Examples of current and previous work are presented in the following categories: algorithm development, system development, instrumentation installation, ground R&D, and flight testing. Examples of current research and development activities are provided.

Get the Balance Right.

ERIC Educational Resources Information Center

Haddock, Rebecca Jaurigue

Today work goes on 24 hours a day, 7 days a week, and is about acceleration and access. Workers need balance more than ever. In fact, recent college graduates value work/life balance as their key factor in selecting employers. This paper, written for career counselors, defines balance as encompassing emotional, spiritual, physical, and…

The Role of Attractiveness and Aggression in High School Popularity

ERIC Educational Resources Information Center

Borch, Casey; Hyde, Allen; Cillessen, Antonius H. N.

2011-01-01

This study examines the effects of physical attractiveness and aggression on popularity among high school students. Previous work has found positive relationships between aggression and popularity and physical attractiveness and popularity. The current study goes beyond this work by examining the interactive effects of physical attractiveness and…

CrAlN coating to enhance the power loss and magnetostriction in grain oriented electrical steel

DOE Office of Scientific and Technical Information (OSTI.GOV)

Goel, Vishu; Anderson, Philip; Hall, Jeremy

Grain oriented electrical steels (GOES) are coated with aluminium orthophosphate on top of a forsterite (Mg{sub 2}SiO{sub 4}) layer to provide stress and insulation resistance to reduce the power loss and magnetostriction. In this work Chromium Aluminium Nitride (CrAlN) was coated on GOES samples with electron beam physical vapour deposition and was tested in the single strip and magnetostriction tester to measure the power loss and magnetostriction before and after coating. Power loss was reduced by 2% after coating and 6 % post annealing at 800 °C. For applied compressive stress of 6 MPa, the magnetostrictive strain was zero with themore » CrAlN coating as compared to 22 and 24 μϵ for fully finished GOES and GOES without phosphate coating. The thickness of the coating was found to be 1.9 ± 0.2 μm estimated with Glow Discharge Optical Emission Spectroscopy (GDOES). The magnetic domain imaging showed domain narrowing after coating. The reduction in power loss and magnetostriction was due to the large residual compressive stress and Young’s modulus (270 GPa) of the coating.« less

High Energy Particle Events in Solar Cycles 23 and 24

NASA Astrophysics Data System (ADS)

Thakur, N.; Gopalswamy, N.; Makela, P. A.; Yashiro, S.; Akiyama, S.; Xie, H.

2014-12-01

We present a study of high-energy solar energetic particle (SEP) events in solar cycles 23 and 24 using GOES data. We selected large SEP events, which showed intensity enhancements in the >500 MeV and >700 MeV GOES energy channels. A study of cycle 24 and the first half of cycle 23 ground level enhancements (GLEs) by Gopalswamy et al. 2014 showed that typically, SEP events with intensity enhancement at >700 MeV have been associated with GLEs. We have extended the survey to cover the whole cycle 23. Our preliminary survey confirms this to be true for all except for three cases. There were two GLEs (1998/05/06 and 2006/12/06) for which a clear increase in >700 MeV protons was not observed by GOES. There was one high energy SEP event (2000/11/08), for which GOES observed >700 MeV protons but no GLE was produced. Here we compare all the high-energy particle events from cycles 23 and 24 with GLEs. We also compare energy spectra of all high-energy SEP events with those that produced GLEs. Work supported by NASA's Living with a Star Program. Ref.: Gopalswamy et al. 2014, GRL, 41, 2673

VizieR Online Data Catalog: Positions and distances of RR Lyrae stars (Sesar+, 2014)

NASA Astrophysics Data System (ADS)

Sesar, B.; Banholzer, S. R.; Cohen, J. G.; Martin, N. F.; Grillmair, C. J.; Levitan, D.; Laher, R. R.; Ofek, E. O.; Surace, J. A.; Kulkarni, S. R.; Prince, T. A.; Rix, H.-W.

2017-04-01

RRab stars used in this work were selected by an automated classification algorithm that uses imaging data provided by the Palomar Transient Factory survey (PTF). The PTF (Law et al. 2009PASP..121.1395L; Rau et al. 2009PASP..121.1334R) is a synoptic survey designed to explore the transient sky. The project utilizes the 48-inch Samuel Oschin Schmidt Telescope on Mount Palomar. Each PTF image covers 7.26 deg2 with a pixel scale of 1.01''. The typical PTF cadence consists of two 60 s exposures separated by ~1 hr and repeated every one to five days. By 2013 June, PTF observed ~11000 deg2 of sky at least 25 times in the Mould-R filter (hereafter the R-band filter), and about 2200 deg2 in the SDSS g' filter. PTF photometry is calibrated to an accuracy of about 0.02 mag (Ofek et al. 2012PASP..124...62O, 2012PASP..124..854O) and light curves have relative precision of better than 10 mmag at the bright end, and about 0.2 mag at the survey limiting magnitude of R=20.6 mag. The relative photometry algorithm is described in Ofek et al. (2011, J/ApJ/740/65, see their Appendix A). (1 data file).

Precipitation Estimation from Remotely Sensed Information using Artificial Neural Network-Cloud Classification System

NASA Astrophysics Data System (ADS)

Hong, Yang

Precipitation estimation from satellite information (VISIBLE , IR, or microwave) is becoming increasingly imperative because of its high spatial/temporal resolution and board coverage unparalleled by ground-based data. After decades' efforts of rainfall estimation using IR imagery as basis, it has been explored and concluded that the limitations/uncertainty of the existing techniques are: (1) pixel-based local-scale feature extraction; (2) IR temperature threshold to define rain/no-rain clouds; (3) indirect relationship between rain rate and cloud-top temperature; (4) lumped techniques to model high variability of cloud-precipitation processes; (5) coarse scales of rainfall products. As continuing studies, a new version of Precipitation Estimation from Remotely Sensed Information using Artificial Neural Network (PERSIANN), called Cloud Classification System (CCS), has been developed to cope with these limitations in this dissertation. CCS includes three consecutive components: (1) a hybrid segmentation algorithm, namely Hierarchically Topographical Thresholding and Stepwise Seeded Region Growing (HTH-SSRG), to segment satellite IR images into separated cloud patches; (2) a 3D feature extraction procedure to retrieve both pixel-based local-scale and patch-based large-scale features of cloud patch at various heights; (3) an ANN model, Self-Organizing Nonlinear Output (SONO) network, to classify cloud patches into similarity-based clusters, using Self-Organizing Feature Map (SOFM), and then calibrate hundreds of multi-parameter nonlinear functions to identify the relationship between every cloud types and their underneath precipitation characteristics using Probability Matching Method and Multi-Start Downhill Simplex optimization techniques. The model was calibrated over the Southwest of United States (100°--130°W and 25°--45°N) first and then adaptively adjusted to the study region of North America Monsoon Experiment (65°--135°W and 10°--50°N) using observations from Geostationary Operational Environmental Satellite (GOES) IR imagery, Next Generation Radar (NEXRAD) rainfall network, and Tropical Rainfall Measurement Mission (TRMM) microwave rain rate estimates. CCS functions as a distributed model that first identifies cloud patches and then dispatches different but the best matching cloud-precipitation function for each cloud patch to estimate instantaneous rain rate at high spatial resolution (4km) and full temporal resolution of GOES IR images (every 30-minute). Evaluated over a range of spatial and temporal scales, the performance of CCS compared favorably with GOES Precipitation Index (GPI), Universal Adjusted GPI (UAGPI), PERSIANN, and Auto-Estimator (AE) algorithms, consistently. Particularly, the large number of nonlinear functions and optimum IR-rain rate thresholds of CCS model are highly variable, reflecting the complexity of dominant cloud-precipitation processes from cloud patch to cloud patch over various regions. As a result, CCS can more successfully capture variability in rain rate at small scales than existing algorithms and potentially provides rainfall product from GOES IR-NEXARD-TRMM TMI (SSM/I) at 0.12° x 0.12° and 3-hour resolution with relative low standard error (˜=3.0mm/hr) and high correlation coefficient (˜=0.65).

Technical note: Mining data from on-farm electronic equipment to identify the time dairy cows spend away from the pen.

PubMed

Thompson, A J; Weary, D M; von Keyserlingk, M A G

2017-05-01

The electronic equipment used on farms can be creatively co-opted to collect data for which it was not originally designed. In the current study, we describe 2 novel algorithms that harvest data from electronic feeding equipment and data loggers used to record standing and lying behavior, to estimate the time that dairy cows spend away from their pen to be milked. Our 2 objectives were to (1) measure the ability of the first algorithm to estimate the time cows spend away from the pen as a group and (2) determine the capability of a second algorithm to estimate the time it takes for individual cows to return to their pen after being milked. To achieve these objectives, we conducted 2 separate experiments: first, to estimate group time away, the feeding behavior of 1 pen of 20 Holstein cows was monitored electronically for 1 mo; second, to measure individual latency to return to the pen, feeding and lying behavior of 12 healthy Holstein cows was monitored electronically from parturition to 21 d in milk. For both experiments, we monitored the time each individual cow exited the pen before each milking and when she returned to the pen after milking using video recordings. Estimates generated by our algorithms were then compared with the times captured from the video recordings. Our first algorithm provided reliable pen-based estimates for the minimum time cows spent away from the pen to be milked in the morning [coefficient of determination (R 2 ) = 0.92] and afternoon (R 2 = 0.96). The second algorithm was able to estimate of the time it took for individual cows to return to the pen after being milked in the morning (R 2 = 0.98), but less so in the afternoon (R 2 = 0.67). This study illustrates how data from electronic systems used to assess feeding and lying behavior can be mined to estimate novel measures. New work is now required to improve the estimates of our algorithm for individuals, for example by adding data from other electronic monitoring systems on the farm. Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Innovative Approaches for the Dissemination of Near Real-time Geostationary Satellite Data for Terrestrial and Space Weather Applications

NASA Astrophysics Data System (ADS)

Jedlovec, G.; McGrath, K.; Meyer, P. J.; Berndt, E.

2017-12-01

A GOES-R series receiving station has been installed at the NASA Marshall Space Flight Center (MSFC) to support GOES-16 transition-to-operations projects of NASA's Earth science program and provide a community portal for GOES-16 data access. This receiving station is comprised of a 6.5-meter dish; motor-driven positioners; Quorum feed and demodulator; and three Linux workstations for ingest, processing, display, and subsequent product generation. The Community Satellite Processing Package (CSPP) is used to process GOES Rebroadcast data from the Advanced Baseline Imager (ABI), Geostationary Lightning Mapper (GLM), Solar Ultraviolet Imager (SUVI), Extreme Ultraviolet and X-ray Irradiance Sensors (EXIS), and Space Environment In-Situ Suite (SEISS) into Level 1b and Level 2 files. GeoTIFFs of the imagery from several of these instruments are ingested into an Esri Arc Enterprise Web Map Service (WMS) server with tiled imagery displayable through a web browser interface or by connecting directly to the WMS with a Geographic Information System software package. These data also drive a basic web interface where users can manually zoom to and animate regions of interest or acquire similar results using a published Application Program Interface. While not as interactive as a WMS-driven interface, this system is much more expeditious with generating and distributing requested imagery. The legacy web capability enacted for the predecessor GOES Imager currently supports approximately 500,000 unique visitors each month. Dissemination capabilities have been refined to support a significantly larger number of anticipated users. The receiving station also supports NASA's Short-term Prediction, Research, and Transition Center's (SPoRT) project activities to dissemination near real-time ABI RGB products to National Weather Service National Centers, including the Satellite Analysis Branch, National Hurricane Center, Ocean Prediction Center, and Weather Prediction Center, where they are displayed in N-AWIPS and AWIPS II. The multitude of additional real-time data users include the U.S. Coast Guard, Federal Aviation Administration, and The Weather Company. A second antenna is being installed for the ingest, processing, and dissemination of GOES-S data.

A Mixed-Integer Linear Programming Problem which is Efficiently Solvable.

DTIC Science & Technology

1987-10-01

INTEGER LINEAR PROGRAMMING PROBLEM WHICH IS EFFICIENTLY SOLVABLE 12. PERSONAL AUTHOR(S) Leiserson, Charles, and Saxe, James B. 13a. TYPE OF REPORT j13b TIME...ger prongramn rg versions or the problem is not ac’hievable in genieral for sparse inistancves of’ P rolem(r Mi. Th le remrai nder or thris paper is...rClazes c:oIh edge (i,I*) by comlpli urg +- rnirr(z 3, ,x + a,j). A sirnI) le analysis (11 vto Nei [131 indicates why whe Iellinan-Ford algorithm works

Precipitation Nowcast using Deep Recurrent Neural Network

NASA Astrophysics Data System (ADS)

Akbari Asanjan, A.; Yang, T.; Gao, X.; Hsu, K. L.; Sorooshian, S.

2016-12-01

An accurate precipitation nowcast (0-6 hours) with a fine temporal and spatial resolution has always been an important prerequisite for flood warning, streamflow prediction and risk management. Most of the popular approaches used for forecasting precipitation can be categorized into two groups. One type of precipitation forecast relies on numerical modeling of the physical dynamics of atmosphere and another is based on empirical and statistical regression models derived by local hydrologists or meteorologists. Given the recent advances in artificial intelligence, in this study a powerful Deep Recurrent Neural Network, termed as Long Short-Term Memory (LSTM) model, is creatively used to extract the patterns and forecast the spatial and temporal variability of Cloud Top Brightness Temperature (CTBT) observed from GOES satellite. Then, a 0-6 hours precipitation nowcast is produced using a Precipitation Estimation from Remote Sensing Information using Artificial Neural Network (PERSIANN) algorithm, in which the CTBT nowcast is used as the PERSIANN algorithm's raw inputs. Two case studies over the continental U.S. have been conducted that demonstrate the improvement of proposed approach as compared to a classical Feed Forward Neural Network and a couple simple regression models. The advantages and disadvantages of the proposed method are summarized with regard to its capability of pattern recognition through time, handling of vanishing gradient during model learning, and working with sparse data. The studies show that the LSTM model performs better than other methods, and it is able to learn the temporal evolution of the precipitation events through over 1000 time lags. The uniqueness of PERSIANN's algorithm enables an alternative precipitation nowcast approach as demonstrated in this study, in which the CTBT prediction is produced and used as the inputs for generating precipitation nowcast.

Using the Light Microscopy Module (LMM) on the International Space Station (ISS), The Advanced Colloids Experiment (ACE) and MacroMolecular Biophysics (MMB)

NASA Technical Reports Server (NTRS)

Meyer, William; Foster, William M.; Motil, Brian J.; Sicker, Ronald; Abbott-Hearn, Amber; Chao, David; Chiaramonte, Fran; Atherton, Arthur; Beltram, Alexander; Bodzioney, Christopher M.;

Light Microscopy Module: International Space Station Premier Automated Microscope

NASA Technical Reports Server (NTRS)

Sicker, Ronald J.; Foster, William M.; Motil, Brian J.; Meyer, William V.; Chiaramonte, Francis P.; Abbott-Hearn, Amber; Atherton, Arthur; Beltram, Alexander; Bodzioney, Christopher; Brinkman, John;

Neurologic Diseases

MedlinePlus

... brain, spinal cord, and nerves make up the nervous system. Together they control all the workings of the ... something goes wrong with a part of your nervous system, you can have trouble moving, speaking, swallowing, breathing, ...

Trellises and Trellis-Based Decoding Algorithms for Linear Block Codes. Part 3; A Recursive Maximum Likelihood Decoding

NASA Technical Reports Server (NTRS)

Lin, Shu; Fossorier, Marc

1998-01-01

The Viterbi algorithm is indeed a very simple and efficient method of implementing the maximum likelihood decoding. However, if we take advantage of the structural properties in a trellis section, other efficient trellis-based decoding algorithms can be devised. Recently, an efficient trellis-based recursive maximum likelihood decoding (RMLD) algorithm for linear block codes has been proposed. This algorithm is more efficient than the conventional Viterbi algorithm in both computation and hardware requirements. Most importantly, the implementation of this algorithm does not require the construction of the entire code trellis, only some special one-section trellises of relatively small state and branch complexities are needed for constructing path (or branch) metric tables recursively. At the end, there is only one table which contains only the most likely code-word and its metric for a given received sequence r = (r(sub 1), r(sub 2),...,r(sub n)). This algorithm basically uses the divide and conquer strategy. Furthermore, it allows parallel/pipeline processing of received sequences to speed up decoding.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, Woohyun; Katipamula, Srinivas; Lutes, Robert G.

Small- and medium-sized (<100,000 sf) commercial buildings (SMBs) represent over 95% of the U.S. commercial building stock and consume over 60% of total site energy consumption. Many of these buildings use rudimentary controls that are mostly manual, with limited scheduling capability, no monitoring or failure management. Therefore, many of these buildings are operated inefficiently and consume excess energy. SMBs typically utilize packaged rooftop units (RTUs) that are controlled by an individual thermostat. There is increased urgency to improve the operating efficiency of existing commercial building stock in the U.S. for many reasons, chief among them is to mitigate the climatemore » change impacts. Studies have shown that managing set points and schedules of the RTUs will result in up to 20% energy and cost savings. Another problem associated with RTUs is short-cycling, where an RTU goes through ON and OFF cycles too frequently. Excessive cycling can lead to excessive wear and lead to premature failure of the compressor or its components. The short cycling can result in a significantly decreased average efficiency (up to 10%), even if there are no physical failures in the equipment. Also, SMBs use a time-of-day scheduling is to start the RTUs before the building will be occupied and shut it off when unoccupied. Ensuring correct use of the zone set points and eliminating frequent cycling of RTUs thereby leading to persistent building operations can significantly increase the operational efficiency of the SMBs. A growing trend is to use low-cost control infrastructure that can enable scalable and cost-effective intelligent building operations. The work reported in this report describes three algorithms for detecting the zone set point temperature, RTU cycling rate and occupancy schedule detection that can be deployed on the low-cost infrastructure. These algorithms only require the zone temperature data for detection. The algorithms have been tested and validated using field data from a number of RTUs from six buildings in different climate locations. Overall, the algorithms were successful in detecting the set points and ON/OFF cycles accurately using the peak detection technique and occupancy schedule using symbolic aggregate approximation technique. The report describes the three algorithms, results from testing the algorithms using field data, how the algorithms can be used to improve SMBs efficiency, and presents related conclusions.« less

Comparative Analysis of Document level Text Classification Algorithms using R

NASA Astrophysics Data System (ADS)

Syamala, Maganti; Nalini, N. J., Dr; Maguluri, Lakshamanaphaneendra; Ragupathy, R., Dr.

2017-08-01

From the past few decades there has been tremendous volumes of data available in Internet either in structured or unstructured form. Also, there is an exponential growth of information on Internet, so there is an emergent need of text classifiers. Text mining is an interdisciplinary field which draws attention on information retrieval, data mining, machine learning, statistics and computational linguistics. And to handle this situation, a wide range of supervised learning algorithms has been introduced. Among all these K-Nearest Neighbor(KNN) is efficient and simplest classifier in text classification family. But KNN suffers from imbalanced class distribution and noisy term features. So, to cope up with this challenge we use document based centroid dimensionality reduction(CentroidDR) using R Programming. By combining these two text classification techniques, KNN and Centroid classifiers, we propose a scalable and effective flat classifier, called MCenKNN which works well substantially better than CenKNN.

J. J. Thomson goes to America.

PubMed

Downard, Kevin M

2009-11-01

Joseph John (J. J.) Thomson was an accomplished scientist who helped lay the foundations of nuclear physics. A humble man of working class roots, Thomson went on to become one of the most influential physicists of the late 19th century. He is credited with the discovery of the electron, received a Nobel Prize in physics in 1906 for investigations into the conduction of electricity by gases, was knighted in 1908, and served as a Cavendish Professor and Director of the laboratory for over 35 years from 1884. His laboratory attracted some of the world's brightest minds; Francis W. Aston, Niels H. D. Bohr, Hugh L. Callendar, Charles T. R. Wilson, Ernest Rutherford, George F. C. Searle, Geoffrey I. Taylor, and John S. E. Townsend all worked under him. This article recounts J. J. Thomson's visits to North America in 1896, 1903, 1909, and finally 1923. It presents his activities and his personal impressions of the people and society of the U.S.A. and Canada, and the science of atomic physics and chemistry in the late 1800s and early 1900s.

The infinite sites model of genome evolution.

PubMed

Ma, Jian; Ratan, Aakrosh; Raney, Brian J; Suh, Bernard B; Miller, Webb; Haussler, David

2008-09-23

We formalize the problem of recovering the evolutionary history of a set of genomes that are related to an unseen common ancestor genome by operations of speciation, deletion, insertion, duplication, and rearrangement of segments of bases. The problem is examined in the limit as the number of bases in each genome goes to infinity. In this limit, the chromosomes are represented by continuous circles or line segments. For such an infinite-sites model, we present a polynomial-time algorithm to find the most parsimonious evolutionary history of any set of related present-day genomes.

Optical Algorithms at Satellite Wavelengths for Total Suspended Matter in Tropical Coastal Waters

PubMed Central

Ouillon, Sylvain; Douillet, Pascal; Petrenko, Anne; Neveux, Jacques; Dupouy, Cécile; Froidefond, Jean-Marie; Andréfouët, Serge; Muñoz-Caravaca, Alain

2008-01-01

Is it possible to derive accurately Total Suspended Matter concentration or its proxy, turbidity, from remote sensing data in tropical coastal lagoon waters? To investigate this question, hyperspectral remote sensing reflectance, turbidity and chlorophyll pigment concentration were measured in three coral reef lagoons. The three sites enabled us to get data over very diverse environments: oligotrophic and sediment-poor waters in the southwest lagoon of New Caledonia, eutrophic waters in the Cienfuegos Bay (Cuba), and sediment-rich waters in the Laucala Bay (Fiji). In this paper, optical algorithms for turbidity are presented per site based on 113 stations in New Caledonia, 24 stations in Cuba and 56 stations in Fiji. Empirical algorithms are tested at satellite wavebands useful to coastal applications. Global algorithms are also derived for the merged data set (193 stations). The performances of global and local regression algorithms are compared. The best one-band algorithms on all the measurements are obtained at 681 nm using either a polynomial or a power model. The best two-band algorithms are obtained with R412/R620, R443/R670 and R510/R681. Two three-band algorithms based on Rrs620.Rrs681/Rrs412 and Rrs620.Rrs681/Rrs510 also give fair regression statistics. Finally, we propose a global algorithm based on one or three bands: turbidity is first calculated from Rrs681 and then, if < 1 FTU, it is recalculated using an algorithm based on Rrs620.Rrs681/Rrs412. On our data set, this algorithm is suitable for the 0.2-25 FTU turbidity range and for the three sites sampled (mean bias: 3.6 %, rms: 35%, mean quadratic error: 1.4 FTU). This shows that defining global empirical turbidity algorithms in tropical coastal waters is at reach. PMID:27879929