Engineering topics

Francis Padula

Publications and source records attributed to Francis Padula.

8 records

NASA NTRS2022

Polarization performance simulation for the GeoXO atmospheric composition instrument: NO2 retrieval impacts

NOAA’s Geostationary Extended Observations (GeoXO) constellation will continue and expand on the capabilities of the current generation of geostationary satellite systems to support US weather, ocean, atmosphere, and climate operations. It is planned to consist of a dedicated atmospheric composition instrument (ACX) to support air quality forecasting and monitoring by providing similar capabilities to missions such as TEMPO (Tropospheric Emission: Monitoring Pollution), currently planned to launch in 2023, and Ozone Monitoring Instrument (OMI), TROPOMI (TROPOspheric Monitoring Instrument), and GEMS (Geostationary Environment Monitoring Spectrometer) currently in operation. As the early phases of ACX development are progressing, design trade-offs are being considered to understand the relationship between instrument design choices and trace gas retrieval impacts. Some of these choices will affect the instrument polarization sensitivity (PS), which can have radiometric impacts on environmental satellite observations. We conducted a study to investigate how such radiometric impacts can affect NO2 retrievals by exploring their sensitivities to time of day, location, and scene type with an ACX instrument model that incorporates PS. The study addresses the basic steps of operational NO2 retrievals: the spectral fitting step and the conversion of slant column to vertical column via the air mass factor (AMF). The spectral fitting step was performed by generating at-sensor radiance from a clear sky scene with a known NO2 amount, the application of an instrument model including both instrument PS and noise, and a physical retrieval. The spectral fitting step was found to mitigate the impacts of instrument PS. The AMF-related step was considered for clear sky and partially cloudy scenes, where instrument PS can lead to errors in interpreting the cloud content, propagating to AMF errors and finally to NO2 retrieval errors. For this step, the NO2 retrieval impacts were small but non-negligible for high NO2 amounts; we estimated that a typical high NO2 amount can cause maximum of 0.25 x 10^15 molecules/cm^2 for a PS of 5%. These simulation capabilities were designed to aid in the development of a GeoXO atmospheric composition instrument that will improve our ability to monitor and understand the Earth’s atmosphere.

trace gases↗

NASA NTRS2022

Polarization Performance Simulation for the GeoXO Atmospheric Composition Instrument: NO2 Retrieval Impacts

NOAA's Geostationary Extended Observations (GeoXO) constellation will continue and expand on the capabilities of the current generation of geostationary satellite systems to support US weather, ocean, atmosphere, and climate operations. It is planned to consist of a dedicated atmospheric composition instrument (ACX) to support air quality forecasting and monitoring by providing capabilities similar to missions such as TEMPO (Tropospheric Emission: Monitoring Pollution), currently planned to launch in 2023, as well as OMI (Ozone Monitoring Instrument), TROPOMI (TROPOspheric Monitoring Instrument), and GEMS (Geostationary Environment Monitoring Spectrometer) currently in operation. As the early phases of ACX development are progressing, design trade-offs are being considered to understand the relationship between instrument design choices and trace gas retrieval impacts. Some of these choices will affect the instrument polarization sensitivity (PS), which can have radiometric impacts on environmental satellite observations. We conducted a study to investigate how such radiometric impacts can affect NO2 retrievals by exploring their sensitivities to time of day, location, and scene type with an ACX instrument model that incorporates PS. The study addresses the basic steps of operational NO2 retrievals: the spectral fitting step and the conversion of slant column to vertical column via the air mass factor (AMF). The spectral fitting step was performed by generating at-sensor radiance from a clear-sky scene with a known NO2 amount, the application of an instrument model including both instrument PS and noise, and a physical retrieval. The spectral fitting step was found to mitigate the impacts of instrument PS. The AMF-related step was considered for clear-sky and partially cloudy scenes, for which instrument PS can lead to errors in interpreting the cloud content, propagating to AMF errors and finally to NO2 retrieval errors. For this step, the NO2 retrieval impacts were small but non-negligible for high NO2 amounts; we estimated that a typical high NO2 amount can cause a maximum retrieval error of 0.25×1015 molec. cm−2 for a PS of 5 %. These simulation capabilities were designed to aid in the development of a GeoXO atmospheric composition instrument that will improve our ability to monitor and understand the Earth's atmosphere.

Aaron Pearlman↗

NASA NTRS2020

Reflective Solar Band Striping Mitigation Method for the GOES-R Series Advanced Baseline Imager Using Special Scans

The large focal plane arrays used in the new generation of the Geostationary Operational Environmental Satellites (GOES) advanced baseline imager (ABI) introduce new calibration challenges compared with the heritage GOES imagers. The increased number of detectors allows for increased spatial, spectral, and temporal performance, but as a trade-off, it has an increased risk of image striping. We detail the development of a new postlaunch relative calibration capability for ABI reflective solar bands that utilizes ABI special scans to generate a set of relative gains that can be applied to improve image quality and reduce image striping. Results demonstrate that the method reduces image striping in the ABI solar reflective bands over varying scene content and time, both diurnally and over an extended period. This methodology ensures a calibration strategy that is consistent with heritage approaches yet adapts to the new postlaunch validation challenges presented by the new class of operational imagers in the GOES-R series. The developed approach is ready for operational use, as needed, and can be easily implemented into operations to support the operational production of geostationary imagery of the Earth.

Monica Cook↗

NASA NTRSDate not supplied

A Modeling and Simulation Study for the GeoXO Atmospheric Composition Instrument (ACX): System Level SO2 and O3 Retrieval Performance as a Function of SNR

NOAA’s Geostationary Extended Observations (GeoXO) program is planning to include a hyperspectral UV/visible atmospheric composition instrument in geostationary orbit slated for operations by the early 2030s. Trace gas retrievals provide critical information about our Earth’s system as it relates to both natural and anthropogenic activity. This work focused on the impacts of the signal-to-noise ratio (SNR) on the retrieval uncertainty of SO2 and O3. An end-to-end physics-based imaging system and scene modeling and simulation framework was developed to assess instrument performance considerations in support of the planned GeoXO atmospheric composition instrument (ACX). The framework is composed of three primary components: 1) simulated at-sensor radiance via radiative transfer models of a known atmospheric composition, 2) a noise model driven by previous and planned sensor specifications, and 3) a physical retrieval algorithm. In this analysis, the tropospheric concentrations of SO2 and O3 in the atmospheric column were varied in the boundary layer (0-3 km) and at an elevation of 5 km with a thickness of 1-2 km; the uncertainty in retrieval was studied for various SNR levels for multiple viewing geometries and solar zenith angles. This effort supports the development of the GeoXO ACX instrument by providing a simulated ACX performance assessment of the system-level retrieval performance as a function of SNR, particularly with respect to the wavelength range of interest (approximately 305 – 340 nm) for SO2 and O3 trace gas retrievals.

Monica Cook↗

NASA NTRSDate not supplied

GeoXO Ocean Color Instrument (OCX) Spatial and Temporal Coverage Assessment

NOAA’s next generation Geostationary Extended Observations (GeoXO) satellite system will advance Earth observations from geostationary orbit. GeoXO will supply vital information supporting the U.S. weather, ocean, and climate operations. The recommended three-satellite constellation includes spacecrafts at the current GOES-East and GOES-West positions that will carry an imager, lightning mapper, and an ocean color (OCX) instrument. In this poster we describe an assessment of U.S. Exclusive Economic Zone (EEZ) availability for OCX observations, based on EEZ view geometry, solar angle range over the year, sun glint, as well as cloud climatology. The availability for observations for each EEZ region is estimated per day of the year, as function of atmospheric mass factor (AMF) and sun glint. In addition, cloud climatology – based on statistics derived from three years of GOES-16 ABI cloud mask – is considered to determine the fraction of cloud-free OCX observations for each region as function of time of day and season. The results of such assessments can be used to optimize OCX collections and potentially explore regions outside the EEZ.

Boryana Efremova↗

NASA NTRSDate not supplied

An Initial Assessment of the Impact of System Spectral Response Parameters on Driving Ocean Color Applications for the GeoXO Ocean Color Instrument (OCX)

NOAA’s Geostationary Extended Observations (GeoXO) program is planning to include a hyperspectral ocean color instrument (OCX) in geostationary orbit slated for operations by the early 2030s. Shared international focus has led to a diverse legacy of space-based remote sensing ocean color missions that have and will continue to provide ocean color products into the future at a variety of spatial, temporal, and spectral resolutions. This work reports on an investigation of the impacts of system spectral response parameters on spectral shape and algal bloom detection for the planned OCX instrument. A dataset of high resolution (1 nm spectral sampling) in-situ spectra of red tide collected with an above water spectrometer, and associated K. brevis cell concentrations, were used to simulate OCX observations of varying system spectral response parameters. The OCX Performance Operational Requirements Document (PORD) level spectral resolution and sampling are varied concurrently and the location of band centers is varied independently. The impacts to the spectral shape using hyperspectral signature analysis, as well as the impacts to two heritage multispectral algal bloom detection algorithms – red band difference (RBD) and Karenia brevis bloom index (KBBI) – are assessed considering both changes in resolution/sampling and band center location. This work provides a quantitative assessment of the impacts of system spectral response requirements on both the spectral shape of observations as well as the algal bloom detection to provide insight on how various instrument performance parameters influence science and operational utility of OCX. Future work will seek to expand this analysis to include a larger dataset that considers additional water cases.

Monica Cook↗

NASA NTRSDate not supplied

An assessment of the impact of system spectral response parameters on spectral shape and algal bloom detection for the GeoXO ocean color instrument (OCX)

NOAA’s Geostationary Extended Observations (GeoXO) program is planning to include a hyperspectral ocean color instrument (OCX) in geostationary orbit slated for operations by the early 2030s. Shared international focus has led to a diverse legacy of space-based remote sensing ocean color missions that have and will continue to provide ocean color products into the future at a variety of spatial, temporal, and spectral resolutions. This work reports on an investigation of the impacts of system spectral response parameters on spectral shape and algal bloom detection for the planned OCX instrument. A large dataset in-situ spectra, from a variety of locations and water cases collected with an above water spectrometer, was used to simulate OCX observations of varying system spectral response parameters. The OCX Performance Operational Requirements Document (PORD) level spectral resolution and sampling are varied concurrently and the location of band centers is varied independently. The impacts to the spectral shape using hyperspectral signature analysis, as well as the impacts to two heritage multispectral algal bloom detection algorithms – red band difference (RBD) and Karenia brevis bloom index (KBBI) – are assessed considering both changes in resolution/sampling and band center location. This work provides a quantitative assessment of the impacts of system spectral response requirements on both the spectral shape of observations as well as the algal bloom detection to provide insight on how various instrument performance parameters influence science and operational utility of OCX.

Monica Cook↗

NASA NTRSDate not supplied

GeoXO Atmospheric Composition Instrument (AC) Measurements Conditions Assessment

NOAA’s next generation Geostationary Extended Observations (GeoXO) satellite system will advance Earth observations from geostationary orbit. GeoXO will supply vital information supporting the U.S. weather, ocean, and climate operations. The recommended three-satellite constellation includes spacecraft at GOES-Central position, that will carry an Atmospheric Composition Instrument (ACX) among its payloads; the requirement on the ACX is to scan its region of interest in one hour. An assessment of ACX observational conditions is presented, based on view geometry and solar angle range over the year. The availability for observations of each pixel is estimated per day of the year, as function of the geometric air mass factor (AMF), which can be related to signal to noise ratio using a model of the ACX instrument performance, and ultimately to expected column error for specific atmospheric species. In addition, cloud climatology – based on statistics derived from GOES-16 ABI cloud product data – is considered to determine typical fractions of cloud-free ACX observations and typical cloud optical depths, for each pixel as function of time of day and season. The results of such assessments can be used to prepare for GeoXO ACX data and further the understanding and development of the future instrument operations.

Boryana Efremova↗