Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “GOES”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

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

The Geostationary Operational Environmental Satellite-R Series (GOES-R), which launched in November 2016, is the first of the next generation geostationary weather satellites. GOES-R provides 4 times the resolution, 5 times the observation rate, and 3 times the number of spectral bands for Earth observations compared with its predecessor spacecraft. Additionally, Earth relative and Sun-relative pointing and pointing stability requirements are maintained throughout reaction wheel desaturation events and station keeping activities, allowing GOES-R to provide continuous Earth and sun observations. This paper reviews 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. This paper presents a comparison between low-frequency on-orbit pointing results and simulation predictions for both the Earth Pointed Platform (EPP) and Sun Pointed Platform (SPP). Results indicate excellent agreement between simulation predictions and observed on-orbit performance, and compliance with pointing performance requirements. The EPP instrument suite includes 6 seismic accelerometers sampled at 2 KHz, allowing in-flight verification of jitter responses and comparison back to simulation predictions. This paper presents flight results of acceleration, shock response spectrum (SRS), and instrument line of sight responses for various operational scenarios and instrument observation modes. The results demonstrate the effectiveness of the dual-isolation approach employed on GOES-R. The spacecraft provides attitude and rate data to the primary Earth-observing instrument at 100 Hz, which are used to adjust instrument scanning. The data must meet accuracy and latency numbers defined by the Integrated Rate Error (IRE) requirements. This paper discusses the on-orbit IRE results, showing compliance to these requirements with margin. During the spacecraft checkout period, IRE disturbances were observed and subsequently attributed to thermal control of the Inertial Measurement Unit (IMU) mounting interface. Adjustments of IMU thermal control and the resulting improvements in IRE are presented. Orbit knowledge represents the final element of INR performance. Extremely accurate orbital position is achieved by GPS navigation at Geosynchronous Earth Orbit (GEO). On-orbit performance results are shown demonstrating compliance with the stringent orbit position accuracy requirements of GOES-R, including during station keeping activities and momentum desaturation events. As we show in this paper, the on-orbit performance of the GNC design provides the necessary capabilities to achieve GOES-R mission objectives.

Chapel, Jim↗
DOE OSTI2021

Summertime Continental Shallow Cumulus Cloud Detection Using GOES-16 Satellite and Ground-Based Stereo Cameras at the DOE ARM Southern Great Plains Site

Summertime continental shallow cumulus clouds (ShCu) are detected using Geostationary Operational Environmental Satellite (GOES)-16 reflectance data, with cross-validation by observations from ground-based stereo cameras at the Department of Energy Atmospheric Radiation Measurement Southern Great Plains site. A ShCu cloudy pixel is identified when the GOES reflectance exceeds the clear-sky surface reflectance by a reflectance detection threshold of ShCu, ΔR. We firstly construct diurnally varying clear-sky surface reflectance maps and then estimate the ΔR. A GOES simulator is designed, projecting the clouds reconstructed by stereo cameras towards the surface along the satellite’s slanted viewing direction. The dynamic ShCu detection threshold ΔR is determined by making the GOES cloud fraction (CF) equal to the CF from the GOES simulator. Although there are temporal variabilities in ΔR, cloud fractions and cloud size distributions can be well reproduced using a constant ΔR value of 0.045. The method presented in this study enables daytime ShCu detection, which is usually falsely reported as clear sky in the GOES-16 cloud mask data product. Using this method, a new ShCu dataset can be generated to bridge the observational gap in detecting ShCu, which may transition into deep precipitating clouds, and to facilitate further studies on ShCu development over heterogenous land surface.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2019

GOES-R Spacecraft Verification and Validation Compared with Flight Results

The Geostationary Operational Environmental Satellite, R-Series (GOES-R) represents a dramatic improvement in GEO (Geostationary Earth Orbit) weather observation capabilities over the previous generation. To provide these new capabilities, GOES-R incorporates a number of new technologies flying for the first time. As with any new spacecraft design, extensive ground testing was performed to validate the vehicle performance. In this paper, we present several successes and several lessons-learned from the GOES-R verification and validation (V&V) efforts. Included are the Dynamic Interaction Test (DIT) results for jitter assessment, and comparison to flight results. Also included are the effects of thermally-induced alignment perturbations, along with post-launch mitigations. Finally, we discuss unexpected GOES-17 gyro performance, which caused a Safe Mode entry shortly after launch. V&V mitigations are presented, which will be used for the next two GOES-R vehicles.

GOES-17↗
NASA NTRS2001

Intercomparison of GOES-8 Imager and Sounder Land Surface Temperature Retrievals

Recent studies at the Global Hydrology and Climate Center (GHCC) have shown that the assimilation of land skin temperature (LST) tendencies into a mesoscale model can significantly improve short term forecasts of near surface temperature and moisture. The high spatial and temporal resolution of GOES derived land surface products provide valuable information about the spatial and temporal variability of the land surface forcing simulated in the model. In the GHCC studies LST was derived using a split window technique requiring at least two longwave infrared window channels and thus, utilized the 11 and 12 micron channels found on the GOES-8 Imager with a nadir spatial resolution of 4km. However, beginning with the launch of GOES-M (scheduled for mid 2001 ) and subsequent satellites the 12 micron channel will be removed from the Imager leaving only one longwave window channel. The GOES Sounder will continue to have more than one longwave infrared window channel (including a 12 micron channel) but, with a spatial resolution of 10 km nadir. LST retrievals from the newer GOES satellites will thus be derived from Sounder measurements at a reduced spatial resolution. This paper intercompares the LST retrievals from the GOES-8 Imager and Sounder. The effects on the LST retrievals due to the Sounder's reduced resolution from that of the Imager and its different longwave infrared channel characteristics are examined. The effects of transitioning from Imager to Sounder LST products on the results from model assimilation of these products are also examined.

Suggs, Ronnie J.↗
NASA NTRS2010

NASA SPoRT GOES-R Proving Ground Activities

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.

Stano, Geoffrey T.↗
NASA NTRS2011

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

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.

Jedlovec, Gary↗
NASA NTRS2016

GOES-16 On-Orbit Dual Isolation Performance Characterization Results

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.

Carter, Delano↗
NASA NTRSDate not supplied

Goes-16 On-Station Custom Maneuver Generation with Focussuite

This paper discusses the process of the NOAA GOES Mission Operations Support Team (MOST) in mitigating the effects of inconsistently performing ArcJet Thrusters (AJTs) aboard the GOES-16 spacecraft in geostationary orbit. These AJTs are hot-gas thrusters which augment the gas flow using an electric arc to increase the exit velocity of the gases. Fuel flow problems have led to GOES-16 being unable to safely use its AJTs for maneuvers at times. This primarily affects North/South Station-Keeping (NSSK) maneuvers, which control inclination and use a majority of the station-keeping fuel budget. As a result, GOES-16 has had to occasionally resort to using non-AJT hot-gas thrusters. These thrusters are not placed as close to GOES-16's centerline, have lower thrust, and have lower specific impulse when compared to AJTs. In addition, MOST’s ground systems do not officially support using these non-AJT thrusters for NSSK maneuvers. MOST had to quickly develop workaround solutions using the FocusSuite Autofocus programming environment to compute the maneuvers. This paper outlines the mixture of commercial off-the-shelf (COTS) and MOST-developed products which have allowed GOES-16 to continue station-keeping even with inconsistently-per-forming AJTs, showing that script-based automation systems like Autofocus can simplify complex solutions to a few scripted user inputs.

Henry Heim↗
NASA NTRS2017

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

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.

SUVI↗
NASA NTRS2017

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

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.

GOES-16↗
NASA NTRSDate not supplied

Validation of GOES-17 ABI Reflective Channels Performance: Salar De Uyuni 2018 Field Campaign Results

Validation results from a reflectance-based field campaign at the Salar de Uyuni in Bolivia (September 2018) are presented for GOES-17 and GOES-16 Advanced Baseline Imagers (ABI) reflective channels. The in situ measurements were used to characterize the surface reflectance and the atmosphere in order to constrain a radiative transfer model and predict the reflectance at the top of the atmosphere (TOA), which was then compared to the ABI measurements. The field campaign provides TOA reflectance estimates over several days, allowing assessment of the calibration accuracy and stability of channels 1, 2, 3, 5 and 6 for GOES-17 andGOES-16 ABI. Channel 1 of GOES-17 ABI shows -5.5% bias in comparison to the ground-based predicted TOA. Over 6% bias in GOES-17 B2 was confirmed. A comparison to NOAA-20 VIIRS was also carried on during a near nadir overpass.

validation↗
NASA NTRS2014

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

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.

Control↗
NASA NTRS2016

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

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.

stair-step artifact↗
NASA NTRS2017

A Closer Look at the ABI on the GOES-R Series

The Advanced Baseline Imager (ABI) on board the Geostationary Operational Environmental Satellite-R (GOES-R) is America's next-generation geostationary advanced imager. GOES-R launched on 19 November 2016. The ABI is a state-of-the-art 16-band radiometer, with spectral bands covering the visible, near-infrared, and infrared portions of the electromagnetic spectrum. Many attributes of the ABI-such as spectral, spatial, and temporal resolution; radiometrics; and image navigation/registration-are much improved from the current series of GOES imagers. This paper highlights and discusses the expected improvements of each of these attributes. From ABI data many higher-level-derived products can be generated and used in a large number of environmental applications. The ABI's design allows rapid-scan and contiguous U.S. imaging automatically interleaved with full-disk scanning. In this paper the expected instrument attributes are covered, as they relate to signal-to-noise ratio, image navigation and registration, the various ABI scan modes, and other parameters. There will be several methods for users to acquire GOES-R imagery and products depending on their needs. These include direct reception of the imagery via the satellite downlink and an online-accessible archive. The information from the ABI on the GOES-R series will be used for many applications related to severe weather, tropical cyclones and hurricanes, aviation, natural hazards, the atmosphere, the ocean, and the cryosphere.

GOES-R↗
NASA NTRS2016

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

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.

image registration↗
NASA NTRS2019

GOES-17 Magnetometer On-Orbit Calibration Design and Results

The Geostationary Operational Environmental Satellite-R (GOES-R) is a series of four NOAA weather satellites. Each spacecraft flies a Magnetometer instrument which includes two boom mounted fluxgate sensors located 6.3 and 8.5 meters from the spacecraft. Sensor readings are corrupted by both internal (bias and scale factor) and external (spacecraft emitted fields and misalignments) error sources. In order to estimate the bias, an on-orbit calibration is performed, slewing the spacecraft about multiple axes and then performing a fit of the data to determine zero offset and misalignment terms. The first satellite in the series, GOES-16 was launched in November 2016. Its magnetometer calibration maneuver was found to be inadequate providing insufficient rotation about orthogonal axes. The uncertainty in the estimated biases was found to be in the 3-5 nanotesla range, exceeding the magnetometer accuracy requirement of 1.0 nanotesla. Based on lessons learned, the maneuver was redesigned to provide multiple 360 degree rotations about two orthogonal axes, providing optimal visibility into bias and misalignment. Varying ambient fields over the duration of the calibration maneuvers, corrupts the ability to accurately determine parameters of interest. To address this issue, rather than assuming a constant field for the duration of the maneuver, a non-linear least squares filter was employed that uses a series of spline functions to better fit the ambient field. The number of splines can be varied to minimize the least squares filter residuals. Simulations were performed using 360 days of GOES-16 data to bound the uncertainty in the biases for given residuals of the fit to the ambient field. Following the launch of the second satellite in the series, GOES-17 in March 2018, the new calibration maneuver and enhanced bias estimation algorithm were exercised twice. Based on the residuals of the fit, the uncertainty of the estimated zero offset was reduced by an order of magnitude from 3-5 nanotesla to approximately 0.4 nanotesla per axis. This paper provides details of the maneuver design and the innovative algorithm used to estimate the GOES-17 biases and misalignments.

GOES-17↗
NASA NTRSDate not supplied

A Comparative Study of Contrail Frequency Indices and GOES-16 Contrail Data Set

Contrail formations have been shown to contribute to the greenhouse effect: they are practically transparent to incoming solar radiation and do little to reflect heat away from Earth but are highly effective at trapping heat within Earth’s atmosphere. To understand the impact contrails have on climate change, contrail frequency indices (CFIs) can be used as a method to quantify aircraft-induced persistent contrails. These indices are capable of tracking long-term contrail formation and identify regions of airspace with the highest contrail formation rates. In this aper, an algorithm is proposed which is capable of using NASA Sherlock and Global Forecast System (GFS) datasets and computing CFIs over large geographic regions and long temporal intervals using NASA Ames’ High-End Computing Capability (HECC) supercomputing system. CFIs are computed using nowcast weather data and previously flown flight tracks. This paper calculated the CFIs of all twenty Air Route Traffic Control Centers in the National Airspace System on October 28th, 2019 and compared the distribution of non-zero CFIs with observed contrail data collected from GOES-16 Satellite data in order to assess the accuracy of the CFI system as a contrail prediction model. It was ultimately determined that the computed CFIs were broadly distributed in the same way as the GOES-16 contrail data and that the individual CFIs computed at the latitude/longitude points at which GOES-16 contrail masks were available had high precision and recall (at 0.75 and 0.86 respectively). While these validation results bode well for the accuracy of the CFI method, the number of provided GOES-16 masks was quite small. Future work should aim to increase the size of the GOES-16 dataset in order to perform a more comprehensive comparison between these two datasets.

Contrails↗
NASA NTRSDate not supplied

A Comparative Study of Contrail Frequency Indices and GOES-16 Contrail Data Set

Contrail formations have been shown to contribute to the greenhouse effect: they are practically transparent to incoming solar radiation and do little to reflect heat away from Earth but are highly effective at trapping heat within Earth’s atmosphere. To understand the impact contrails have on climate change, contrail frequency indices (CFIs) can be used as a method to quantify aircraft-induced persistent contrails. These indices are capable of tracking long-term contrail formation and identify regions of airspace with the highest contrail formation rates. In this aper, an algorithm is proposed which is capable of using NASA Sherlock and Global Forecast System (GFS) datasets and computing CFIs over large geographic regions and long temporal intervals using NASA Ames’ High-End Computing Capability (HECC) supercomputing system. CFIs are computed using nowcast weather data and previously flown flight tracks. This paper calculated the CFIs of all twenty Air Route Traffic Control Centers in the National Airspace System on October 28th, 2019 and compared the distribution of non-zero CFIs with observed contrail data collected from GOES-16 Satellite data in order to assess the accuracy of the CFI system as a contrail prediction model. It was ultimately determined that the computed CFIs were broadly distributed in the same way as the GOES-16 contrail data and that the individual CFIs computed at the latitude/longitude points at which GOES-16 contrail masks were available had high precision and recall (at 0.75 and 0.86 respectively). While these validation results bode well for the accuracy of the CFI method, the number of provided GOES-16 masks was quite small. Future work should aim to increase the size of the GOES-16 dataset in order to perform a more comprehensive comparison between these two datasets.

Contrails↗