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At least 271 records · Page 15
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NASA NTRS2024

Southern California Water Resources: Using NASA Earth Observations to Monitor Seagrass Extent and Water Quality Parameters in Southern California

Eelgrass (Zostera marina) is a species of submerged aquatic vegetation found in shallow bays and estuaries with soft seafloors. Eelgrass is recognized for providing ecosystem benefits, such as carbon sequestration, sediment stabilization, water clarification, and fish and wildlife habitats. However, eelgrass is impacted by both marine and terrestrial threats associated with climate change. In this project, we worked with the Southern California Coastal Water Research Project, the National Oceanic and Atmospheric Administration’s National Marine Fisheries Service, and the State of California San Diego Regional Water Quality Control Board to investigate water quality parameters (i.e., chlorophyll-a concentration, sea surface temperature, and turbidity) associated with eelgrass in Newport Bay and Mission Bay, California. The team used Landsat 8 Operational Land Imager and Thermal Infrared Sensor, Landsat 9 Operational Land Imager-2 and Thermal Infrared Sensor-2, Sentinel-2 MultiSpectral Instrument, and ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station land surface temperature and cloud mask to create a time series of these water quality parameters from 2019–2023. We found that the parameters followed cyclical, seasonal patterns with turbidity and sea surface temperature peaking in the summer. We did not find that the parameters had changed significantly over longer time periods. These results will be used in a model developed by the Southern California Coastal Water Research Project to assess eelgrass ecosystem health and predict ecosystem occupancy in the future.

Katya Beener↗
NASA NTRS2018

Results of the Aerosol Sampling Experiment on the International Space Station

The indoor air quality of the International Space Station (ISS), in terms of particulate matter, has been assessed through a sampling experiment that collected airborne debris for return to Earth. The Aerosol Sampling Experiment took place on ISS in December 2016 and January 2017, with sample return in February 2017. For redundancy, two different aerosol samplers collected particles in two size ranges spanning from 10 nm to hundreds of micrometers. Multiple analysis techniques have been used to characterize the particles, such as reflective light microscopy, manual scanning electron microscopy (SEM) analysis (secondary and backscattered imaging) with energy dispersive spectroscopy (EDS) x-ray analysis, computer controlled scanning electron microscopy (CCSEM) and Raman spectroscopy. Sampling took place in five locations on ISS, with the greatest deposition of particles in Node 3, followed by Node 1, the US Lab and Node 2. The PMM had very few airborne particles, as expected, owing to the lack of human presence. A large proportion of the sampled material consisted of fibers from clothing. Many particles had complex morphologies or contained multiple metals in a carbonaceous matrix. Metal particles were analyzed for each sampling location in terms of both weight and number percent, with 27 heavy metals detected. Fiberglass and TiO2 particles were present in every location. Quantitative analysis results are presented, and where possible, particle emission sources are identified with the intention to fuel discussions on mitigation.

Meyer, Marit E.↗
NASA NTRS1982

An assessment of various side-stick controller/stability and control augmentation systems for night nap-of-Earth flight using piloted simulation

Several night nap-of-the-earth mission tasks were evaluated using a helmet-mounted display which provided a limited field-of-view image with superimposed flight control symbology. A wide range of stability and control augmentation designs was investigated. Variations in controller force-deflection characteristics and the number of axes controlled through an integrated side-stick controller were studied. In general, a small displacement controller is preferred over a stiffstick controller particularly for maneuvering flight. Higher levels of stability augmentation were required for IMC tasks to provide handling qualities comparable to those achieved for the same tasks conducted under simulated visual flight conditions.

Landis, K. H.↗
NASA NTRS1985

LANDSAT TM image data quality analysis for energy-related applications

This project represents a no-cost agreement between National Aeronautic Space Administration Goddard Space Flight Center (NASA GSFC) and the Pacific Northwest Laboratory (PNL). PNL is a Department of Energy (DOE) national laboratory operted by Battelle Memorial Institute at its Pacific Northwest Laboratories in Richland, Washington. The objective of this investigation is to evaluate LANDSAT's thematic mapper (TM) data quality and utility characteristics from an energy research and technological perspective. Of main interest is the extent to which repetitive TM data might support DOE efforts relating to siting, developing, and monitoring energy-related facilities, and to basic geoscientific research. The investigation utilizes existing staff and facility capabilities, and ongoing programmatic activities at PNL and other DOE national laboratories to cooperatively assess the potential usefulness of the improved experimental TM data. The investigation involves: (1) both LANDSAT 4 and 5 TM data, (2) qualitative and quantitative use consideration, and 3) NASA P (corrected) and A (uncorrected) CCT analysis for a variety of sites of DOE interest. Initial results were presented at the LANDSAT Investigator's Workshops and at specialized LANDSAT TM sessions at various conferences.

Wukelic, G. E.↗
NASA NTRS2014

Modeling the X-Ray Process, and X-Ray Flaw Size Parameter for POD Studies

Nondestructive evaluation (NDE) method reliability can be determined by a statistical flaw detection study called probability of detection (POD) study. In many instances the NDE flaw detectability is given as a flaw size such as crack length. The flaw is either a crack or behaving like a crack in terms of affecting the structural integrity of the material. An alternate approach is to use a more complex flaw size parameter. The X-ray flaw size parameter, given here, takes into account many setup and geometric factors. The flaw size parameter relates to X-ray image contrast and is intended to have a monotonic correlation with the POD. Some factors such as set-up parameters including X-ray energy, exposure, detector sensitivity, and material type that are not accounted for in the flaw size parameter may be accounted for in the technique calibration and controlled to meet certain quality requirements. The proposed flaw size parameter and the computer application described here give an alternate approach to conduct the POD studies. Results of the POD study can be applied to reliably detect small flaws through better assessment of effect of interaction between various geometric parameters on the flaw detectability. Moreover, a contrast simulation algorithm for a simple part-source-detector geometry using calibration data is also provided for the POD estimation.

Khoshti, Ajay↗
NASA NTRS2014

Modeling the X-ray Process, and X-ray Flaw Size Parameter for POD Studies

Nondestructive evaluation (NDE) method reliability can be determined by a statistical flaw detection study called probability of detection (POD) study. In many instances, the NDE flaw detectability is given as a flaw size such as crack length. The flaw is either a crack or behaving like a crack in terms of affecting the structural integrity of the material. An alternate approach is to use a more complex flaw size parameter. The X-ray flaw size parameter, given here, takes into account many setup and geometric factors. The flaw size parameter relates to X-ray image contrast and is intended to have a monotonic correlation with the POD. Some factors such as set-up parameters, including X-ray energy, exposure, detector sensitivity, and material type that are not accounted for in the flaw size parameter may be accounted for in the technique calibration and controlled to meet certain quality requirements. The proposed flaw size parameter and the computer application described here give an alternate approach to conduct the POD studies. Results of the POD study can be applied to reliably detect small flaws through better assessment of effect of interaction between various geometric parameters on the flaw detectability. Moreover, a contrast simulation algorithm for a simple part-source-detector geometry using calibration data is also provided for the POD estimation.

Koshti, Ajay M.↗
NASA NTRS2020

Philadelphia Health & Air Quality: Assessing Land Surface Temperature, Vegetation Cover, and Compounding Vulnerability Factors to Identify High Priority Areas for Cooling Initiatives in Philadelphia, Pennsylvania

Heat is the leading cause of weather-related deaths in the US, with heat-related hospitalizations increasing by 2-5% between 2001-2010. In Philadelphia alone, 137 heat-related deaths were recorded between 2010-2018, while a total of 18 daily temperature records have been set since 2010. Temperature is relatively higher in cities compared to rural areas, a phenomenon known as the urban heat island effect.This effect exaggerates daytime maximum temperatures and nighttime heat retention in urban areas, which increases heat exposure inurban environments and especially impacts vulnerable populations. Vulnerability to heat-related illnesses is determined by a combination of risk factors, such as demographics, socioeconomic status, and preexisting health conditions. This project supported the Philadelphia Department of Public Health and Office of Sustainability by identifying priority areas for cooling interventions, such as heat danger educational outreach and urban tree planting. The team developed heat vulnerability scores for each census tract within Philadelphia. Remotely sensed land surface temperature, normalized difference vegetation index, normalized difference built-up index, normalized difference water index, and albedo data were calculated from Aqua Moderate Resolution Imaging Spectroradiometer and Landsat 8 Operational Land Imager/Thermal Infrared Sensor instruments. These variables were weighted against socioeconomic variables and preexisting health conditions using a principal component analysis. A total of 74 census tracts clustered were identified as high-risk areas for heat-related illnesses. 15 of these census tracts also had very low tree density (lower 20th percentile) and should be targeted for tree planting initiatives. The findings of this project will help target interventions to mitigate heat-related health issues and improve the overall wellness of Philadelphia residents.

Health & Air Quality↗
NASA NTRS2018

Performance Analysis of Airborne Photon-Counting Lidar Data in Preparation for the ICESat-2 Mission

Two airborne photon-counting laser altimeters have been deployed in direct support of National Aeronautics and Space Adminsitration (NASA's) upcoming Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) mission. Multiple Altimeter Beam Experimental Lidar (MABEL) was developed specifically for ICESat-2 testing and development. MABEL data are used to simulate key aspects of the ICESat-2 measurement strategy and are critical to the development of the algorithms for geophysical data-product generation. Slope Imaging Multipolarization Photon-counting Lidar (SIMPL) is a NASA Goddard Space Flight Center instrument that has also been deployed in support of ICESat-2 performance discovery. Both instruments are photon-counting, small footprint laser altimeters that sample in both the 532- and 1064-nm wavelengths. And both instruments serve as a proxy for ICESat-2 operational performance and error assessment and a basis for the development of potential validation strategies. This paper provides an overview of how data from MABEL and SIMPL overflights have specifically provided the foundation for understanding the quality of ICESat-2 data and how we can plan to evaluate ICESat-2 products through comparison with other modalities of lidar data and/or groundtruth locations using ground fiducials.

MABEL↗
NASA NTRSDate not supplied

Lessons Learned From Smallsat Microwave Sounders Data Assimilation in the NASA Goddard Earth Observing System (GEOS)

The NASA Time-Resolved Observations of Precipitation structure and storm Intensity with a Constellation of Smallsats (TROPICS) mission is a constellation of small satellites carrying state-of-art microwave temperature and humidity sounders with 12 channels between 91 GHz and 205 GHz frequency. Including TROPICS-pathfinder, launched on 30 June 2021, five TROPICS satellites operate and provide temperature and humidity data to NWP and atmospheric retrieval communities. This study evaluates the quality of radiance data from these five satellites. It assesses data impacts on NASA Goddard Earth Observing System (GEOS) global NWP analysis and forecasts while seeking answers to the following key questions: 1. What information do TROPICS satellites bring to NWP analysis? 2. How will TROPICS data assimilation affect NWP forecasts, including tropical cyclone analysis and forecasts? 3. What are the benefits of having multiple TROPICS satellites in NWP forecasts? 4. What are the weaknesses regarding instrument stability, consistency, and data quality of these CubeSats? 5. Can multiple TROPICS make similar impacts as conventional MW sensors such as ATMS or GPM Microwave Imager (GMI)? The sensitivities of each TROPICS channel to temperature, water vapor, cloud, and precipitation are examined in various weather conditions. Results from observing system experiments assimilating TROPICS radiance are used for evaluation metrics, including forecast skills and fit to other observations such as radiosondes and microwave and infrared sounders. Finally, the lessons learned from using these cube satellite radiance data in the GEOS atmospheric data assimilation system are shared.

Min-Jeong Kim↗
NASA NTRS2020

Philadelphia Health & Air Quality: Assessing Land Surface Temperature, Vegetation Cover, and Compounding Vulnerability Factors to Identify High Priority Areas for Cooling Initiatives in Philadelphia, Pennsylvania

Heat is the leading cause of weather-related deaths in the US, with heat-related hospitalizations increasing by 2-5% between 2001-2010. In Philadelphia alone, 137 heat-related deaths were recorded between 2010-2018, while a total of 18 daily temperature records have been set since 2010. Temperature is relatively higher in cities compared to rural areas, a phenomenon known as the urban heat island effect. This effect exaggerates daytime maximum temperatures and nighttime heat retention in urban areas, which increases heat exposure in urban environments and especially impacts vulnerable populations. Vulnerability to heat-related illnesses is determined by a combination of risk factors, such as demographics, socioeconomic status, and preexisting health conditions. This project supported the Philadelphia Department of Public Health and Office of Sustainability by identifying priority areas for cooling interventions, such as heat danger educational outreach and urban tree planting. The team developed heat vulnerability scores for each census tract within Philadelphia. Remotely sensed land surface temperature, normalized difference vegetation index, normalized difference built-up index, normalized difference water index, and albedo data were calculated from Aqua Moderate Resolution Imaging Spectroradiometer and Landsat 8 Operational Land Imager/Thermal Infrared Sensor instruments. These variables were weighted against socioeconomic variables and preexisting health conditions using a principal component analysis. A total of 74 census tracts clustered were identified as high-risk areas for heat-related illnesses. 15 of these census tracts also had very low tree density (lower 20th percentile) and should be targeted for tree planting initiatives. The findings of this project will help target interventions to mitigate heat-related health issues and improve the overall wellness of Philadelphia residents.

Health & Air Quality↗
NASA NTRS2011

A Study on the Potential Applications of Satellite Data in Air Quality Monitoring and Forecasting

In this study we explore the potential applications of MODIS (Moderate Resolution Imaging Spectroradiometer) -like satellite sensors in air quality research for some Asian regions. The MODIS aerosol optical thickness (AOT), NCEP global reanalysis meteorological data, and daily surface PM(sub 10) concentrations over China and Thailand from 2001 to 2009 were analyzed using simple and multiple regression models. The AOT-PM(sub 10) correlation demonstrates substantial seasonal and regional difference, likely reflecting variations in aerosol composition and atmospheric conditions, Meteorological factors, particularly relative humidity, were found to influence the AOT-PM(sub 10) relationship. Their inclusion in regression models leads to more accurate assessment of PM(sub 10) from space borne observations. We further introduced a simple method for employing the satellite data to empirically forecast surface particulate pollution, In general, AOT from the previous day (day 0) is used as a predicator variable, along with the forecasted meteorology for the following day (day 1), to predict the PM(sub 10) level for day 1. The contribution of regional transport is represented by backward trajectories combined with AOT. This method was evaluated through PM(sub 10) hindcasts for 2008-2009, using ohservations from 2005 to 2007 as a training data set to obtain model coefficients. For five big Chinese cities, over 50% of the hindcasts have percentage error less than or equal to 30%. Similar performance was achieved for cities in northern Thailand. The MODIS AOT data are responsible for at least part of the demonstrated forecasting skill. This method can be easily adapted for other regions, but is probably most useful for those having sparse ground monitoring networks or no access to sophisticated deterministic models. We also highlight several existing issues, including some inherent to a regression-based approach as exemplified by a case study for Beijing, Further studies will be necessa1Y before satellite data can see more extensive applications in the operational air quality monitoring and forecasting.

Li, Can↗
NASA NTRS2016

CME Flux Rope and Shock Identifications and Locations: Comparison of White Light Data, Graduated Cylindrical Shell Model, and MHD Simulations

Coronal mass ejections (CMEs) are major transient phenomena in the solar corona that are observed with ground-based and spacecraft-based coronagraphs in white light or with in situ measurements by spacecraft. CMEs transport mass and momentum and often drive shocks. In order to derive the CME and shock trajectories with high precision, we apply the graduated cylindrical shell (GCS) model to fit a flux rope to the CME directed toward STEREO A after about 19:00 UT on 29 November 2013 and check the quality of the heliocentric distance-time evaluations by carrying out a three-dimensional magnetohydrodynamic (MHD) simulation of the same CME with the Block Adaptive Tree Solar-Wind Roe Upwind Scheme (BATS-R-US) code. Heliocentric distances of the CME and shock leading edges are determined from the simulated white light images and magnetic field strength data. We find very good agreement between the predicted and observed heliocentric distances, showing that the GCS model and the BATS-R-US simulation approach work very well and are consistent. In order to assess the validity of CME and shock identification criteria in coronagraph images, we also compute synthetic white light images of the CME and shock. We find that the outer edge of a cloud-like illuminated area in the observed and predicted images in fact coincides with the leading edge of the CME flux rope and that the outer edge of a faint illuminated band in front of the CME leading edge coincides with the CME-driven shock front.

Schmidt, J. M.↗
NASA NTRS2012

A New Approach to Monitoring Coastal Marshes for Persistent Flooding

Many areas in coastal Louisiana are below sea level and protected from flooding by a system of natural and man-made levees. Flooding is common when the levees are overtopped by storm surge or rising rivers. Many levees in this region are further stressed by erosion and subsidence. The floodwaters can become constricted by levees and trapped, causing prolonged inundation. Vegetative communities in coastal regions, from fresh swamp forest to saline marsh, can be negatively affected by inundation and changes in salinity. As saltwater persists, it can have a toxic effect upon marsh vegetation causing die off and conversion to open water types, destroying valuable species habitats. The length of time the water persists and the average annual salinity are important variables in modeling habitat switching (cover type change). Marsh type habitat switching affects fish, shellfish, and wildlife inhabitants, and can affect the regional ecosystem and economy. There are numerous restoration and revitalization projects underway in the coastal region, and their effects on the entire ecosystem need to be understood. For these reasons, monitoring persistent saltwater intrusion and inundation is important. For this study, persistent flooding in Louisiana coastal marshes was mapped using MODIS (Moderate Resolution Imaging Spectroradiometer) time series of a Normalized Difference Water Index (NDWI). The time series data were derived for 2000 through 2009, including flooding due to Hurricane Rita in 2005 and Hurricane Ike in 2008. Using the NDWI, duration and extent of flooding can be inferred. The Time Series Product Tool (TSPT), developed at NASA SSC, is a suite of software developed in MATLAB(R) that enables improved-quality time series images to be computed using advanced temporal processing techniques. This software has been used to compute time series for monitoring temporal changes in environmental phenomena, (e.g. NDVI times series from MODIS), and was modified and used to compute the NDWI indices and also the Normalized Difference Soil Index (NDSI). Coastwide Reference Monitoring System (CRMS) water levels from various hydrologic monitoring stations and aerial photography were used to optimize thresholds for MODIS-derived time series of NDWI and to validate resulting flood maps. In most of the profiles produced for post-hurricane assessment, the increase in the NDWI index (from storm surge) is accompanied by a decrease in the vegetation index (NDVI) and then a period of declining water. The NDSI index represents non-green or dead vegetation and increases after the hurricane s destruction of the marsh vegetation. Behavior of these indices over time is indicative of which areas remain flooded, which areas recover to their former levels of vegetative vigor, and which areas are stressed or in transition. Tracking these indices over time shows the recovery rate of vegetation and the relative behavior to inundation persistence. The results from this study demonstrated that identification of persistent marsh flooding, utilizing the tools developed in this study, provided an approximate 70-80 percent accuracy rate when compared to the actual days flooded at the CRMS stations.

Kalcic, M. T.↗
NASA NTRS2011

The 2010 Desert Rats Science Operations Test: Outcomes and Lessons Learned

The Desert RATS 2010 Team tested a variety of science operations management techniques, applying experience gained during the manned Apollo missions and the robotic Mars missions. This test assessed integrated science operations management of human planetary exploration using real-time, tactical science operations to oversee daily crew science activities, and a night shift strategic science operations team to conduct strategic level assessment of science data and daily traverse results. In addition, an attempt was made to collect numerical metric data on the outcome of the science operations to assist test evaluation. The two most important outcomes were 1) the production of significant (almost overwhelming) volume of data produced during daily traverse operations with two rovers, advanced imaging systems and well trained, scientifically proficient crew-members, and 2) the degree to which the tactical team s interaction with the surface crew enhanced science return. This interaction depended on continuous real-time voice and data communications, and the quality of science return from any human planetary exploration mission will be based strongly on the aggregate interaction between a well trained surface crew and a dedicated science operations support team using voice and imaging data from a planet s surface. In addition, the scientific insight developed by both the science operations team and the crews could not be measurable by simple numerical quantities, and its value will be missed by a purely metric-based evaluation of test outcome. In particular, failure to recognize the critical importance of this qualitative type interaction may result in mission architecture choices that will reduce science return.

Eppler, D. B.↗
NASA NTRS2022

MODIS TEB Electronic Crosstalk Correction Update and Impact on L1B Product Uncertainty

The MODIS instruments onboard the Terra and Aqua satellites have been in operation for over22 and 20 years, respectively. The instruments’ calibration accuracy has been maintained, even with instrument degradation. Electronic crosstalk in the thermal emissive bands (TEB) is a known issue with an increasing impact on the calibration and product. The Terra MODIS photovoltaic (PV) longwave infrared (LWIR) bands crosstalk corrections have been applied in Collection 6.1 (C6.1). However, the electronic crosstalk contamination for some detectors in the mid-wave infrared (MWIR) bands and the Aqua PVLWIR bands affect the Level-1B (L1B) product’s measurement accuracy and image quality. In Collection 7 (C7), crosstalk corrections for select detectors in the Terra and Aqua MWIR and Aqua PV LWIR bands are applied. The entire mission crosstalk coefficients for the select detectors and bands are derived from scheduled lunar observations and populated in the form of look-up tables (LUTs). The Aqua PV-LWIR bands exhibit similar downward crosstalk trends as the Terra PV-LWIR bands, especially in recent years. The crosstalk coefficients and their trends provide a guideline for the correction application. Earth measurement analyses before and after the correction provide contamination and correction assessments. It has been shown that the product quality is enhanced with the crosstalk correction applied in C7. For C7, the crosstalk coefficient uncertainty is derived from the fit residuals between the measured values and a linear fit over a three-year sliding window. The uncertainty propagation is modeled and applied in the total uncertainty calculation intheL1B product. The TEB electronic crosstalk LUTs have been processed over the entire Terra and Aqua MODIS missions. This paper presents the C7 crosstalk correction, as well as its assessment and uncertainty propagation algorithm to the TEB uncertainty.

Tiejun Chang↗
NASA NTRS2023

Commercial Smallsat Data Acquisition Program: Airbus U.S. Synthetic Aperture Radar Quality Assessment Summary

Quality assessment of the Airbus X-band Synthetic Aperture Radar (SAR) satellite products was conducted by the Commercial Smallsat Data Acquisition (CSDA) program’s radar subject matter experts, following the Joint NASA/ESA (European Space Agency) assessment draft guidelines. All three Airbus SAR spacecraft (TerraSAR-X, TanDEM-X, and PAZ) are based on the TerraSAR-X platform, and each have an active phased array antenna that is 4.8 x 0.7 m in the along-track and cross-track dimensions, respectively. TerraSAR-X and TanDEM-X are in a helical orbit, creating a bistatic imaging geometry, in addition to being capable of independent monostatic observations. The PAZ mission follows TerraSAR-X and TanDEM-X in the same 11-day orbit with a 5.5-day lag. TerraSAR-X and TanDEM-X are designed, developed, and operated through a Public-Private Partnership, while PAZ is a dual-use mission (civil and defense agencies), funded and owned by the Spanish Ministry of Defense and managed by Hisdesat (Hisdesat Servicios Estratégicos, S.A.), a Spanish private communications company. The assessment presented in this document is divided into two main parts: documentation review and the assessment of test datasets. The documentation review in sections 2.1 through 2.4 includes the assessment of the Airbus documentation provided to the CSDA evaluation team. The grading of these documents is given in columns 1-4 of the maturity matrix shown in section 1.1. Section 2.5 summarizes the evaluation performed by NASA using the data purchased through the CSDA program. The grading for this is given in the last column of the maturity matrix. Section 3 provides more detailed explanations on the methods and the results of the data analysis performed by NASA. Only the documents provided by Airbus for the evaluation were considered for the review. Additional documentation with more detailed description of the calibration and validation procedures may be available online but were not considered for this evaluation. The product information provided in the available documentation (RD-1, RD-2) and the product metadata together provided adequate information to work with the data. The product details in the metadata included the required information to work with the data in the common XML file format. Metrological traceability documentation was not provided to CSDA. All relevant characterization of the SAR system and data were provided, and the metadata include all relevant ancillary information. Documentation provided to CSDA included limited pre-flight and post-launch calibration information.

Batuhan Osmanoglu↗
NASA NTRS2022

Modis TEB Electronic Crosstalk Correction Update and Impact on L1B Product Uncertainty

The MODIS instruments on board the Terra and Aqua satellites have been in operation for over 22 and 20 years, respectively. The instruments’ calibration accuracy has been maintained, even with instrument degradation. Electronic crosstalk in the thermal emissive bands (TEB) is a known issue with an increasing impact on the calibration and product. The Terra MODIS photovoltaic (PV) longwave infrared (LWIR) bands crosstalk corrections have been applied in Collection 6.1 (C6.1). However, the electronic crosstalk contamination for some detectors in the mid-wave infrared(MWIR) bands and the Aqua PVLWIR bands affect the Level-1B(L1B) product’s measurement accuracy and image quality. In Collection 7 (C7), crosstalk corrections for select detectors in the Terra and Aqua MWIR and Aqua PV LWIR bands are applied. The entire mission crosstalk coefficients for the select detectors and bands are derived from scheduled lunar observations and populated in the form of look-up tables (LUTs). The Aqua PV-LWIR bands exhibit similar downward crosstalk trends as the Terra PV-LWIR bands, especially in recent years. The crosstalk coefficients and their trends provide a guideline for the correction application. Earth measurement analyses before and after the correction provide contamination and correction assessments. It has been shown that the product quality is enhanced with the crosstalk correction applied in C7. For C7, the crosstalk coefficient uncertainty is derived from the fit residuals between the measured values and a linear fit over a three-year sliding window. The uncertainty propagation is modeled and applied in the total uncertainty calculation intheL1B product. The TEB electronic cross talk LUT shave been processed over the entire Terra and Aqua MODIS missions. This paper presents the C7 crosstalk correction, as well as its assessment and uncertainty propagation algorithm to the TEB uncertainty.

Tiejun Chang↗
NASA NTRS2020

Wildfire Smoke Particle Properties and Evolution, from Space-Based Multi-Angle Imaging

Emitted smoke composition is determined by properties of the biomass burning source and ambient ecosystem. However, conditions that mediate the partitioning of black carbon (BC) and brown carbon (BrC) formation, as well as the spatial and temporal factors that drive particle evolution, are not understood adequately for many climate and air-quality related modeling applications. In situ observations provide considerable detail about aerosol microphysical and chemical properties, although sampling is extremely limited. Satellites offer the frequent global coverage that would allow for statistical characterization of emitted and evolved smoke, but generally lack microphysical detail. However, once properly validated, data from the National Aeronautics and Space Administration (NASA) Earth Observing System’s Multi-Angle Imaging Spectroradiometer (MISR) instrument can create at least a partial picture of smoke particle properties and plume evolution. We use in situ data from the Department of Energy’s Biomass Burning Observation Project (BBOP) field campaign to assess the strengths and limitations of smoke particle retrieval results from the MISR Research Aerosol (RA) retrieval algorithm. We then use MISR to characterize wildfire smoke particle properties and to identify the relevant aging factors in several cases, to the extent possible. The RA successfully maps qualitative changes in effective particle size, light absorption, and its spectral dependence, when compared to in situ observations. By observing the entire plume uniformly, the satellite data can be interpreted in terms of smoke plume evolution, including size-selective deposition, new-particle formation, and locations within the plume where BC or BrC dominates.

Noyes, Katherine Junghenn↗