Assessing and Ensuring GOES-R Magnetometer Accuracy

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

Assessing and Ensuring GOES-R Magnetometer Accuracy

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

Summary of Space Environment Magnetometer and Particle Replacement Experiment (SEMPRE) Study

As part of the GOES-R series follow on architecture study following the NOAA Satellite Observing System Architecture (NSOSA) study, a study team evaluated the feasibility of accommodating the GOES in-situ instruments (Magnetometer and Particle Detectors) on a dedicated spacecraft with no impact to the overall baseline mission cost assuming two large observatories. The accommodations cost on a primary operational type observatory are non-negligible requiring: a large non-magnetic boom to reduce the impact of the spacecraft interference on the magnetometer; and strict contamination control and magnetic cleanliness to prevent magnetic contamination near the magnetometers. These, along with the additional interface complexities greatly increase the cost of larger spacecraft by extending integration time with a large marching army. By contrast, a dedicated mission provides flexibility in location and refresh rate not afforded when these sensors are launched as secondary payloads. This study performed an informal industry survey of small form-factor instruments currently flying or in process of being developed. The study identified three potential particle detector suites and multiple magnetometers that will satisfy the requirements while having low enough volume and mass to allow accommodation on a rideshare class spacecraft. Using the largest of the identified particle detector suites, the Goddard Space Flight Center Mission Design Lab developed a design for a rideshare spacecraft that will accommodate the particle detector suite and magnetometer. The cost of the spacecraft, based on multiple cost models, is comparable to the cost of accommodating the magnetometer and particle detector suite on two (East and West) larger main observatories

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

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-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

Expression quantitative trait locus fine mapping of the 17q12–21 asthma locus in African American children: a genetic association and gene expression study

Background: African ancestry is associated with a higher prevalence and greater severity of asthma than European ancestries, yet genetic studies of the most common locus associated with childhood-onset asthma, 17q12–21, in African Americans have been inconclusive. The aim of this study was to leverage both the phenotyping of the Children's Respiratory and Environmental Workgroup (CREW) birth cohort consortium, and the reduced linkage disequilibrium in African Americans, to fine map the 17q12–21 locus. Methods: We first did a genetic association study and meta-analysis using 17q12–21 tag single-nucleotide polymorphisms (SNPs) for childhood-onset asthma in 1613 European American and 870 African American children from the CREW consortium. Nine tag SNPs were selected based on linkage disequilibrium patterns at 17q12–21 and their association with asthma, considering the effect allele under an additive model (0, 1, or 2 effect alleles). Results were meta-analysed with publicly available summary data from the EVE consortium (on 4303 European American and 3034 African American individuals) for seven of the nine SNPs of interest. Subsequently, we tested for expression quantitative trait loci (eQTLs) among the SNPs associated with childhood-onset asthma and the expression of 17q12–21 genes in resting peripheral blood mononuclear cells (PBMCs) from 85 African American CREW children and in upper airway epithelial cells from 246 African American CREW children; and in lower airway epithelial cells from 44 European American and 72 African American adults from a case-control study of asthma genetic risk in Chicago (IL, USA). Findings: 17q12–21 SNPs were broadly associated with asthma in European Americans. Only two SNPs (rs2305480 in gasdermin-B [GSDMB] and rs8076131 in ORMDL sphingolipid biosynthesis regulator 3 [ORMDL3]) were associated with asthma in African Americans, at a Bonferroni-corrected threshold of p<0·0055 (for rs2305480_G, odds ratio [OR] 1·36 [95% CI 1·12–1·65], p=0·0014; and for rs8076131_A, OR 1·37 [1·13–1·67], p=0·0010). In upper airway epithelial cells from African American children, genotype at rs2305480 was the most significant eQTL for GSDMB (eQTL effect size [β] 1·35 [95% CI 1·25–1·46], p<0·0001), and to a lesser extent showed an eQTL effect for post-GPI attachment to proteins phospholipase 3 (β 1·15 [1·08–1·22], p<0·0001). No SNPs were eQTLs for ORMDL3. By contrast, in PBMCs, the five core SNPs were associated only with expression of GSDMB and ORMDL3. Genotype at rs12936231 (in zona pellucida binding protein 2) showed the strongest associations across both genes (for GSDMB, eQTLβ 1·24 [1·15–1·32], p<0·0001; and for ORMDL3 (β 1·19 [1·12–1·24], p<0·0001). The eQTL effects of rs2305480 on GSDMB expression were replicated in lower airway cells from African American adults (β 1·29 [1·15–1·44], p<0·0001). Interpretation: Our study suggests that SNPs regulating GSDMB expression in airway epithelial cells have a major role in childhood-onset asthma, whereas SNPs regulating the expression levels of 17q12–21 genes in resting blood cells are not central to asthma risk. Our genetic and gene expression data in African Americans and European Americans indicated GSDMB to be the leading candidate gene at this important asthma locus.6 month embargo; published: 01 May 2020This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]