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NASA NTRS1988

GOES-next navigation operations

The next generation of Geostationary Operational Environmental Satellites, GOES-I through -M (hereafter referred to as GOES-Next), begins a new era in the operation of weather satellites by the National Oceanic and Atmospheric Administration (NOAA). With a new spacecraft design, three-axis attitude stabilization, new ground support equipment, and improved methods of image navigation and registration that use on board compensation techniques to correct images for satellite motion, NOAA expects improved performance over the current series of dual-spin spacecraft. To meet these expectations, planning is currently underway for providing the complex and intensive operational environment that will meet the challenge of operating the GOES-Next spacecraft. This paper describes that operational environment.

Fiorello, John L., Jr.↗

NASA NTRS1988

Suggested GOES I-M satellite operational scenarios

Plans for the GOES I-M satellite system are reviewed, focusing on the use of GOES data in severe local storm and tropical cyclone analysis and forecasting. The instrumentation and capabilities of the GOES I-M system, which is expected to be launched beginning in the spring of 1990, are discussed. Sounder and imaging coverage scenarios and scenario timetables are presented.

Shenk, William E.↗

NASA NTRS1990

Cloud parameters derived from GOES during the 1987 marine stratocumulus FIRE Intensive Field Observation (IFO) period

The Geostationary Operational Environmental Satellite (GOES) is well suited for observations of the variations of clouds over many temporal and spatial scales. For this reason, GOES data taken during the Marine Stratocumulus Intensive Field Observations (IFO) (June 29 to July 19, 1987, Kloessel et al.) serve several purposes. One facet of the First ISCCP Regional Experiment (FIRE) is improvement of the understanding of cloud parameter retrievals from satellite-observed radiances. This involves comparisons of coincident satellite cloud parameters and high resolution data taken by various instruments on other platforms during the IFO periods. Another aspect of FIRE is the improvement of both large- and small-scale models of stratocumulus used in general circulation models (GCMs). This may involve, among other studies, linking the small-scale processes observed during the IFO to the variations in large-scale cloud fields observed with the satellites during the IFO and Extended Time Observation (ETO) periods. Preliminary results are presented of an analysis of GOES data covering most of the IFO period. The large scale cloud-field characteristics are derived, then related to a longer period of measurements. Finally, some point measurements taken from the surface are compared to regional scale cloud parameters derived from satellite radiances.

Young, David F.↗

NASA NTRS1990

Characteristics of the GOES I-M Imager and Sounder

The design and the parameters of the improved thermal-imaging and sounding instruments (the Imager and the Sounder) that will be part of the instrument complements of the next-generation Geostationary Operational Environmental Satellite (GOES I-M) are discussed. The new design incorporates many features that enhance instrumental reliability over the previous GOES radiometric instruments, such as independently functioning Sounder and Imager, redundancy, and more reliable position sensors and lubrication methods. Tables are presented which list the instrument parameters of the GOES I-M Imager and Sounder and the performance characteristics of the two instruments.

Ernst, Thomas J.↗

NASA NTRS1993

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

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.

Fantano, Louis G.↗

NASA NTRS2001

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

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.

Minnis, P.↗

NASA NTRS2000

Satellite and Skin Layer Effects on the Accuracy of Sea Surface Temperature Measurements from the GOES Satellites

The latest Geostationary Operational Environmental Satellites (GOES) have facilitated significant improvements in our ability to measure sea surface temperature (SST) from geostationary satellites. Nonetheless, difficulties associated with sensor calibration and oceanic near-surface temperature gradients affect the accuracy of the measurements and our ability to estimate and interpret the diurnal cycle of the bulk SST. Overall, measurements of SST from the GOES Imagers on the GOES 8-10 satellites are shown to have very small bias (less than 0.02 K) and rms differences of between 0.6 and 0.9 K relative to buoy observations. Separate consideration of individual measurement times, however, demonstrates systematic bias variations of over 0.6 K with measurement hour. These bias variations significantly affect both the amplitude and shape of estimates of the diurnal SST cycle. Modeled estimates of the temperature difference across the oceanic cool skin and diurnal thermocline show that bias variations up to 0.3 K can result from variability in the near-surface layer. Oceanic near-surface layer and known "satellite midnight" calibration effects, however, explain only a portion of the observed bias variations, suggesting other possible calibration concerns. Methods of explicitly incorporating skin layer and diurnal thermocline effects in satellite bulk SST measurements were explored in an effort to further improve the measurement accuracy. While the approaches contain more complete physics, they do not yet significantly improve the accuracy of bulk SST measurements due to remaining uncertainties in the temperature difference across the near-surface layer.

Wick, Gary A.↗

NASA NTRS2002

Prelaunch Instrument Calibration in the Real World: The GOES Example

The pre-launch ground infrared calibration of the Geostationary Operational Environmental Satellite (GOES) N-Q Imager and Sounder is presented. Ground calibration provides information necessary to the accurate on-orbit calibration of these radiometers. Infrared channels are calibrated in a thermal vacuum environment, under minimum and maximum mission operation temperatures, using a variable-temperature warm target to simulate the Earth scene and a cold target to simulate the space scene. Brightness temperatures derived from observation of the instrument internal calibration target, used for on-orbit calibration, are compared to brightness temperatures of the external calibration target as a check of relative accuracy using these two sources. Changes to the GOES N-Q specification from GOES I-M are highlighted, as well as results of noise, relative calibration accuracy, and spectral response performance to date. For completeness, results of spatial and pointing performance will be presented. Enhancements to test methodology and data processing techniques are highlighted throughout.

Murphy-Morris, J.↗

NASA NTRS2002

Comparison of ScaRaB, GOES 8, Aircraft, and Surface Observations of the Absorption of Solar Radiation by Clouds

Data obtained by the Scanner for Radiation Budget (ScaRaB) instrument on the Meteor 3 satellite have been analyzed and compared to satellite (GOES 8), aircraft (Radiation Measurement System, RAMS), and surface (Baseline Solar Radiation Network (BSRN), Solar and Infrared Observations System (SIROS), and RAMS) measurements of irradiance obtained during the Atmospheric Radiation Measurements Enhanced Shortwave Experiment (ARESE). It is found that the ScaRaB data covering the period from March 1994 to February 1995 (the instrument's operational lifetime) indicate excess absorption of solar radiation by the cloudy atmosphere in agreement with previous aircraft, surface, and GOES 8 results. The full ScaRaB data set combined with BSRN and SIROS surface observations gives an average all-sky absorptance of 0.28. The GOES 8 data set combined with RAMS surface observations gives an average all-sky absorptance of 0.26. The aircraft data set (RAMS) gives a mean all-sky absorptance of 0.24 (for the column between 0.5 and 13 km).

Pope, Shelly K.↗

NASA NTRS2004

GOES SXI Monthly Project Status Report Lockheed Martin Advanced Technology Center Month of October 2004

The Lockheed Martin Missiles and Space Advanced Technology Center (LMATC) is developing three Solar X-ray Imager (SXI) instruments. Two are being built for flights on the National Oceanic and Atmospheric Administration's (NOAA) Geostationary Operational Environmental Satellites (GOES) N and O, and one will be a flight spare. The SXI development is being managed by the NASA Goddard Space Flight Center. The SXI will image the full sun at wavelengths between approximately 6 and 60 A with a detector having 5 arcsec pixels. The launch of the first SXI will be on GOES N and the second SXI is to be launched on on GOES O or P.

Morrison, Mons D.↗

NASA NTRS2005

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

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.

Goodman, S. J.↗

NASA NTRS2006

GOES-R STATIONKEEPING AND MOMENTUM MANAGEMENT

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.

Chu, Donald↗

NASA NTRS2007

Validation of GOES-10 Satellite-derived Cloud and Radiative Properties for the MASRAD ARM Mobile Facility Deployment

This poster presentation reviews the process used to validate the GOES-10 satellite derived cloud and radiative properties. The ARM Mobile Facility (AMF) deployment at Pt Reyes, CA as part of the Marine Stratus Radiation Aerosol and Drizzle experiment (MASRAD), 14 March - 14 September 2005 provided an excellent chance to validate satellite cloud-property retrievals with the AMF's flexible suite of ground-based remote sensing instruments. For this comparison, NASA LaRC GOES10 satellite retrievals covering this region and period were re-processed using an updated version of the Visible Infrared Solar-Infrared Split-Window Technique (VISST), which uses data taken at 4 wavelengths (0.65, 3.9,11 and 12 m resolution), and computes broadband fluxes using improved CERES (Clouds and Earth's Radiant Energy System)-GOES-10 narrowband-to-broadband flux conversion coefficients. To validate MASRAD GOES-10 satellite-derived cloud property data, VISST-derived cloud amounts, heights, liquid water paths are compared with similar quantities derived from available ARM ground-based instrumentation and with CERES fluxes from Terra.

Khaiyer, M. M.↗

NASA NTRS2007

Geostationary Lightning Mapper for GOES-R

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).

Goodman, Steven↗

NASA NTRS2008

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

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.

Solakiewiz, Richard↗

NASA NTRS2011

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

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

Molthan, Andrew↗

NASA NTRS2012

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

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.

Dworak, Richard↗

NASA NTRS2013

Phase Change Material for Temperature Control of Imager or Sounder on GOES Type Satellites in GEO

An imager or sounder on satellites, such as the Geostationary Operational Environmental Satellite (GOES), in geostationary orbit (GEO) has a scan mirror and motor in the scan cavity. The GEO orbit is 24 hours long. During part of the orbit, direct sunlight enters the scan aperture and adds heat to components in the scan cavity. Solar heating also increases the scan motor temperature. Overheating of the scan motor could reduce its reliability. For GOES-N to P, a radiator with a thermal louver rejects the solar heat absorbed to keep the scan cavity cool. A sunshield shields the radiator/louver from the Sun. This innovation uses phase change material (PCM) in the scan cavity to maintain the temperature stability of the scan mirror and motor. When sunlight enters the scan aperture, solar heating causes the PCM to melt. When sunlight stops entering the scan aperture, the PCM releases the thermal energy stored to keep the components in the scan cavity warm. It reduces the heater power required to make up the heat lost by radiation to space through the aperture. This is a major advantage when compared to a radiator/ louver. PCM is compact because it has a high solid-to-liquid enthalpy. Also, it could be spread out in the scan cavity. This is another advantage. Paraffin wax is a good PCM candidate, with high solid-to-liquid enthalpy, which is about 225 kJ/kg. For GOES-N to P, a radiator with a louver rejects the solar heat that enters the aperture to keep the scan cavity cool. For the remainder of the orbit, sunlight does not enter the scan aperture. However, the radiator/louver continues radiating heat to space because the louver effective emittance is about 0.12, even if the louver is fully closed. This requires makeup heater power to maintain the temperature within the stability range.

Choi, Michael↗