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NASA NTRSDate not supplied

Assimilation of GEO and LEO Satellite Retrievals in WRF-Chem (15 km and 4 km) with ‘Top-Down’ Emissions Estimation

We are constraining concentrations and emissions for all criteria pollutants (CO, O3, NO2, SO2, PM10, and PM2.5) with WRF-Chem/DART in applications for FRAPPE (15-km grid) and COLORADO (4-km grid). Our results show that: (i) dynamic emissions estimation at medium resolutions (15 km) improves forecast skill; (ii) At high resolutions, the results look good, but we do not have validation data; (iii) for what may be the first time, we assimilate O3 retrieval profiles in a regional model. The problem is that the averaging kernels generally extend above the upper boundary of regional models. We use O3 upper boundary conditions from the global model to solve that problem; and (iv) In the high resolution experiments, we document the potential benefits of assimilating TEMPO O3 profile and NO2 tropospheric column retrievals. Here, we assimilate proxy TEMPO retrievals from a GEOS-Chem nature run, so there’s a conceptual problem due to the potential bias of the proxy retrievals, but the point is to demonstrate our ability to assimilate TEMPO and identify its potential impacts.

Chemical data assimilation↗

NASA NTRS2009

DSN Beowulf Cluster-Based VLBI Correlator

The NASA Deep Space Network (DSN) requires a broadband VLBI (very long baseline interferometry) correlator to process data routinely taken as part of the VLBI source Catalogue Maintenance and Enhancement task (CAT M&E) and the Time and Earth Motion Precision Observations task (TEMPO). The data provided by these measurements are a crucial ingredient in the formation of precision deep-space navigation models. In addition, a VLBI correlator is needed to provide support for other VLBI related activities for both internal and external customers. The JPL VLBI Correlator (JVC) was designed, developed, and delivered to the DSN as a successor to the legacy Block II Correlator. The JVC is a full-capability VLBI correlator that uses software processes running on multiple computers to cross-correlate two-antenna broadband noise data. Components of this new system (see Figure 1) consist of Linux PCs integrated into a Beowulf Cluster, an existing Mark5 data storage system, a RAID array, an existing software correlator package (SoftC) originally developed for Delta DOR Navigation processing, and various custom- developed software processes and scripts. Parallel processing on the JVC is achieved by assigning slave nodes of the Beowulf cluster to process separate scans in parallel until all scans have been processed. Due to the single stream sequential playback of the Mark5 data, some ramp-up time is required before all nodes can have access to required scan data. Core functions of each processing step are accomplished using optimized C programs. The coordination and execution of these programs across the cluster is accomplished using Pearl scripts, PostgreSQL commands, and a handful of miscellaneous system utilities. Mark5 data modules are loaded on Mark5 Data systems playback units, one per station. Data processing is started when the operator scans the Mark5 systems and runs a script that reads various configuration files and then creates an experiment-dependent status database used to delegate parallel tasks between nodes and storage areas (see Figure 2). This script forks into three processes: extract, translate, and correlate. Each of these processes iterates on available scan data and updates the status database as the work for each scan is completed. The extract process coordinates and monitors the transfer of data from each of the Mark5s to the Beowulf RAID storage systems. The translate process monitors and executes the data conversion processes on available scan files, and writes the translated files to the slave nodes. The correlate process monitors the execution of SoftC correlation processes on the slave nodes for scans that have completed translation. A comparison of the JVC and the legacy Block II correlator outputs reveals they are well within a formal error, and that the data are comparable with respect to their use in flight navigation. The processing speed of the JVC is improved over the Block II correlator by a factor of 4, largely due to the elimination of the reel-to-reel tape drives used in the Block II correlator.

Rogstad, Stephen P.↗

NASA NTRS2015

Spatial and Temporal Variability of Trace Gas Columns Derived from WRF/Chem Regional Model Output: Planning for Geostationary Observations of Atmospheric Composition

We quantify both the spatial and temporal variability of column integrated O3, NO2, CO, SO2, and HCHO over the Baltimore / Washington, DC area using output from the Weather Research and Forecasting model with on-line chemistry (WRF/Chem) for the entire month of July 2011, coinciding with the first deployment of the NASA Earth Venture program mission Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ). Using structure function analyses, we find that the model reproduces the spatial variability observed during the campaign reasonably well, especially for O3. The Tropospheric Emissions: Monitoring of Pollution (TEMPO) instrument will be the first NASA mission to make atmospheric composition observations from geostationary orbit and partially fulfills the goals of the Geostationary Coastal and Air Pollution Events (GEO-CAPE) mission. We relate the simulated variability to the precision requirements defined by the science traceability matrices of these space-borne missions. Results for O3 from 0- 2 km altitude indicate that the TEMPO instrument would be able to observe O3 air quality events over the Mid-Atlantic area, even on days when the violations of the air quality standard are not widespread. The results further indicated that horizontal gradients in CO from 0-2 km would be observable over moderate distances (≥ 20 km). The spatial and temporal results for tropospheric column NO2 indicate that TEMPO would be able to observe not only the large urban plumes at times of peak production, but also the weaker gradients between rush hours. This suggests that the proposed spatial and temporal resolutions for these satellites as well as their prospective precision requirements are sufficient to answer the science questions they are tasked to address.

TEMPO↗

NASA NTRSDate not supplied

NASA GEOS Composition Forecast System: GEOS-CF

NASA's Global Modeling and Assimilation Office (GMAO) produces high-resolution analysis and forecasts for weather, aerosols, and air quality. Since 2019, the NASA Global Earth Observing System (GEOS) model provides global near-real-time historical estimates and daily 5-day forecasts of atmospheric composition to the public at unprecedented horizontal resolution of 0.25 degrees (~25 km) from the surface up to the lower mesosphere. This composition forecast system (“GEOS-CF”) combines the operational GEOS weather forecasting model with the state-of-the-science GEOS-Chem chemistry module to deliver detailed analysis of a wide range of air pollutants, including the policy-relevant species such as ozone, carbon monoxide, nitrogen oxides, sulfur dioxide and fine particulate matter (PM2.5). The GEOS-CF is a tool for scientists and the public health community. This presentation will cover 1) an overview of the GEOS-CF modeling framework compared to the GEOS-5 Nature Run with Chemistry (used in the post-processing to make the TEMPO Proxy Data), 2) description of the file used to support the TEMPO retrieval team, and 3) research and development activities as the GEOS-CF system continues to evolve to include multi-constituent data assimilation.

K. Emma Knowland↗

NASA NTRS2016

Understanding the Laminar Distribution of Tropospheric Ozone from Ground-Based, Airborne, Spaceborne, and Modeling Perspectives

Laminar ozone structure is a ubiquitous feature of tropospheric-ozone distributions resulting from dynamic and chemical atmospheric processes. Understanding the characteristics of these ozone laminae and the mechanisms responsible for producing them is important to outline the transport pathways of trace gases and to quantify the impact of different sources on tropospheric background ozone. In this study, we present a new method to detect ozone laminae to understand their climatological characteristics of occurrence frequency in terms of thickness and altitude. We employ both ground-based and airborne ozone lidar measurements and other synergistic observations and modeling to investigate the sources and mechanisms such as biomass burning transport, stratospheric intrusion, lightning-generated NOx, and nocturnal low-level jets that are responsible for depleted or enhanced tropospheric ozone layers. Spaceborne (e.g., OMI (Ozone Monitoring Instrument), TROPOMI (Tropospheric Monitoring Instrument), TEMPO (Tropospheric Emissions: Monitoring of Pollution)) measurements of these laminae will observe greater horizontal extent and lower vertical resolution than balloon-borne or lidar measurements will quantify. Using integrated ground-based, airborne, and spaceborne observations in a modeling framework affords insight into how to gain knowledge of both the vertical and horizontal evolution of these ubiquitous ozone laminae.

Tropospheric Ozone↗

DOE OSTI2021

A Nitroxide Containing Organic Molecule in a Deep Eutectic Solvent for Flow Battery Applications

The nitroxide radical redox organic molecule, 2-phenyl-4,4,5,5-tetrame- thylimidazoline-1-oxyl-3-oxide (PTIO), was investigated for the first time in a deep eutectic solvent (DES)-like system consisting of a 1:4 molar ratio of choline chloride and ethylene glycol(Ch1EG4) as a redox flow battery electrolyte. PTIO is a single molecule with three oxidation states, and can provide both positive and negative redox couples for a flow battery. A flow battery using the PTIO/Ch1EG4 electrolyte demonstrated nearly 50% roundtrip efficiency with an approximately 1 V open circuit potential. Inefficiencies were primarily due to membrane resistance which can be significantly lowered with increased temperature. While PTIO appears stable over short periods (hours), the oxidized form is not stable in the DES-like electrolyte over longer times. Molecular modeling was performed to investigate the relative stability of PTIO in DES as compared to the previously studied 4-hydroxy-TEMPO (4HT). It was found that the oxoammonium cation 4HT + exhibits a noticeably larger nucleophilic reactive cloud as compared to PTIO + , indicating a higher reactivity. This method to predict stability of the oxoammonium cation shows promise to inform the design and synthesis of promising redox systems based on nitroxide radicals in DES electrolytes to identify new chemistries for large scale energy storage.

25 ENERGY STORAGE↗

NASA NTRS2012

Effects of Tropospheric Spatio-Temporal Correlated Noise on the Analysis of Space Geodetic Data

The standard VLBI analysis models the distribution of measurement noise as Gaussian. Because the price of recording bits is steadily decreasing, thermal errors will soon no longer dominate. As a result, it is expected that troposphere and instrumentation/clock errors will increasingly become more dominant. Given that both of these errors have correlated spectra, properly modeling the error distributions will become increasingly relevant for optimal analysis. We discuss the advantages of modeling the correlations between tropospheric delays using a Kolmogorov spectrum and the frozen flow assumption pioneered by Treuhaft and Lanyi. We then apply these correlated noise spectra to the weighting of VLBI data analysis for two case studies: X/Ka-band global astrometry and Earth orientation. In both cases we see improved results when the analyses are weighted with correlated noise models vs. the standard uncorrelated models. The X/Ka astrometric scatter improved by approx.10% and the systematic Delta delta vs. delta slope decreased by approx. 50%. The TEMPO Earth orientation results improved by 17% in baseline transverse and 27% in baseline vertical.

instrumentation errors↗

NASA NTRSDate not supplied

NASA GEOS-CF: Overview, Applications, Future Direction

K. Emma Knowland↗

NASA NTRSDate not supplied

1235 Preparing for TEMPO: A Review of Planned Metadata, Data Structure, and Distribution by NASA’s Atmospheric Science Data Center

The Atmospheric Science Data Center (ASDC) is in the Science Directorate located at the NASA Langley Research Center (LaRC), in Hampton, Virginia. The ASDC is one of NASA’s Distributed Active Archive Centers (DAAC) and supports over 60 projects and provides access to more than 1,000 archived collections. These datasets were created from satellite measurements, field experiments, and modeled data products. ASDC projects focus on the following Earth science disciplines: Radiation Budget, Clouds, Aerosols, and Tropospheric Composition. The ASDC is the official Distributed Active Archive Center (DAAC) of record for the upcoming Tropospheric Emissions: Monitoring of Pollution (TEMPO) instrument.. The instrument will share a ride on a commercial satellite as a hosted payload and will be launched to an orbit about 22,000 miles above Earth's equator. The investigation will, for the first time, use a space-based instrument to make accurate observations of tropospheric pollution concentrations of ozone, nitrogen dioxide, formaldehyde, and aerosols with high resolution and frequency over the U.S, Canada, and Mexico.

Ashlee Autore↗

NASA NTRSDate not supplied

1235 Preparing for TEMPO: A Review of Planned Metadata, Data Structure, and Distribution by NASA’s Atmospheric Science Data Center

Ashlee Autore↗

NASA NTRSDate not supplied

NASA GEOS Composition Forecast System, GEOS-CF

NASA's Global Modeling and Assimilation Office (GMAO) produces high-resolution analysis and forecasts for weather, aerosols, and air quality. Since 2019, the NASA Global Earth Observing System (GEOS) model provides global near-real-time historical estimates and daily 5-day forecasts of atmospheric composition to the public at unprecedented horizontal resolution of 0.25 degrees (~25 km) from the surface up to the lower mesosphere. This composition forecast system (“GEOS-CF”) combines the operational GEOS weather forecasting model with the state-of-the-science GEOS-Chem chemistry module to deliver detailed analysis of a wide range of air pollutants, including the policy-relevant species such as ozone, carbon monoxide, nitrogen oxides, sulfur dioxide and fine particulate matter (PM2.5). The GEOS-CF is a tool for scientists and the public health community. This presentation will cover 1) an overview of the GEOS-CF modeling framework and data/visualization access, 2) examples of current and future applications to support NASA missions (e.g., a priori for trace gas retrievals by TEMPO, ground-based instrument teams and field campaigns), and 3) research and development activities as the GEOS-CF system continues to evolve to include multi-constituent data assimilation, near-real time emission adjustment estimates, down-scaling methods to urban-scale, and data access on Google Earth Engine, Amazon Web Services, and other platforms to integrate our state-of-the-science air quality information onto platforms used by stakeholders, air quality managers, and the public.

K. Emma Knowland↗

NASA NTRSDate not supplied

Advancing Wildfire Monitoring with TEMPO and ML tools: Hourly Smoke and Fire‑Front Mapping and Near‑Surface NO₂ Predictions

Wildfires impose substantial impacts on communities and regions downwind of wildfire smoke. We present a TEMPO‑enabled workflow that generates value‑added Level‑3 smoke‑plume masks and fire‑front maps for large wildfires, such as 2024 Park Fire, using the self‑supervised deep learning system SIT‑FUSE, along with near‑surface NO₂ predictions produced by a foundation model (Microsoft Aurora). We conclude by outlining a roadmap for expanding these capabilities to additional Western U.S. wildfire events and for delivering actionable tools to stakeholders. This open-source, reproducible workflow provides a scalable framework for cross-agency wildfire monitoring to overcome traditional limitations in smoke-cloud discrimination and air-quality forecasting by incorporating TEMPO data and beyond.

Xiaohua Pan↗

NASA NTRS2020

Inter-Calibration of Nine UV Sensing Instruments Over Antarctica and Greenland Since 1980

Nadir-viewed intensities (radiances) from nine UV sensing satellite instruments are calibrated over the East Antarctic Plateau and Greenland during summer. The calibrated radiances from these UV instruments ultimately will provide a global long-term record of cloud trends and cloud response from ENSO events since 1980. We first remove the strong solar zenith angle dependence from the intensities using an empirical approach rather than a radiative trans-fer model. Then small multiplicative adjustments are made to these solar zenith angle normalized intensities in order to minimize differences when two or more instruments tempo-rally overlap. While the calibrated intensities show a negligible long-term trend over Antarctica and a statistically in-significant UV albedo trend of−0.05 % per decade over the interior of Greenland, there are small episodic reductions in intensities which are often seen by multiple instruments. Three of these darkening events are explained by boreal forest. Other events are caused by surface melting or volcanoes. We estimate a 2-sigma uncertainty of 0.35% for the calibrated radiances

Nadir-viewed intensities (radiances) from nine UV ↗

NASA NTRSDate not supplied

Considerations for Health and Performance During Surface Extravehicular Activities

BACKGROUND: NASA’s objectives for expanding human presence beyond low Earth orbit will require Extravehicular Activities (EVAs) on lunar and planetary surfaces. Given the physiological and functional demands of conducting surface EVAs in a pressurized spacesuit in reduced gravity environments, there is a possibility that crew injury and compromised physiological and/or functional performance may present. OVERVIEW: Many human health and performance knowledge gaps exist in regards to exploration EVA that require characterization to ensure safety, reliability, and mission success. To address knowledge gaps, EVA simulations in Earth-based analog environments and/or spacesuit simulators can be utilized to provide valuable insights into task-based physiologic and metabolic costs, cognitive loads, and associated operational limitations to inform future mission concepts. Physical workloads approaching 60% of maximum metabolic rates and 85% age-predicted heart rate maxima; core body temperatures approaching 100o F; and subjective responses indicating limited spare cognitive capacity via Bedford scale have been observed during ground-based exploration EVA simulations in the NASA Active Response Gravity Offload Simulator (ARGOS) and Neutral Buoyancy Lab (NBL) during simulated planetary EVAs in pressurized suits. Further, ground-based EVA analogs vary in their ability to simulate planetary EVA and resulting physical workloads. DISCUSSION: Metabolic costs, thermal burdens, functional strength, and cognitive impacts have been and must continue to be assessed in ground-based analogs to fully characterize operational demands and crew readiness levels for exploration EVA. Considerations should be given to enabling a new concept of high-tempo surface EVA operations and associated work-rest intervals, understanding human health and performance impacts of evolving commercial suit designs and capabilities, and predictive modeling and decision support capabilities to enable safe and successful EVA operations.

EVA↗

NASA NTRS2024

Considerations for Health and Performance during Surface Extravehicular Activities

BACKGROUND: NASA’s objectives for expanding human presence beyond low Earth orbit will require Extravehicular Activities (EVAs) on lunar and planetary surfaces. Given the physiological and functional demands of conducting surface EVAs in a pressurized spacesuit in reduced gravity environments, there is a possibility that crew injury and compromised physiological and/or functional performance may present. OVERVIEW: Many human health and performance knowledge gaps exist in regards to exploration EVA that require characterization to ensure safety, reliability, and mission success. To address knowledge gaps, EVA simulations in Earth-based analog environments and/or spacesuit simulators can be utilized to provide valuable insights into task-based physiologic and metabolic costs, cognitive loads, and associated operational limitations to inform future mission concepts. Physical workloads approaching 60% of maximum metabolic rates and 85% age-predicted heart rate maxima; core body temperatures approaching 100° F; and subjective responses indicating limited spare cognitive capacity via Bedford scale have been observed during ground-based exploration EVA simulations in the NASA Active Response Gravity Offload Simulator (ARGOS) and Neutral Buoyancy Lab (NBL) during simulated planetary EVAs in pressurized suits. Further, ground-based EVA analogs vary in their ability to simulate planetary EVA and resulting physical workloads. DISCUSSION: Metabolic costs, thermal burdens, functional strength, and cognitive impacts have been and must continue to be assessed in ground-based analogs to fully characterize operational demands and crew readiness levels for exploration EVA. Considerations should be given to enabling a new concept of high-tempo surface EVA operations and associated work-rest intervals, understanding human health and performance impacts of evolving commercial suit designs and capabilities, and predictive modeling and decision support capabilities to enable safe and successful EVA operations.

P Estep↗

NASA NTRSDate not supplied

Global-to-local air quality forecasts using the NASA GEOS Composition Forecast System

Since 2019, the NASA Global Earth Observing System (GEOS) model has been used to generate global, near-real-time estimates and daily five-day forecasts of atmospheric composition at a horizontal resolution of 0.25 degrees (~25 km) from the surface up to the lower mesosphere. This composition forecast system (“GEOS-CF”) combines the GEOS weather forecasting model with the state-of-the-science GEOS-Chem chemistry module to deliver detailed analysis of a wide range of air pollutants, including the policy-relevant species such as ozone, carbon monoxide, nitrogen oxides, sulfur dioxide and fine particulate matter (PM2.5). Because GEOS-CF includes atmospheric levels up through the stratosphere, this system has been leveraged to support the Tropospheric Emissions: Monitoring of Pollution (TEMPO) satellite mission and provide stratospheric intrusion alerts to ground-based monitoring stations. We will present recent advances to GEOS-CF which target increased computational efficiency and accuracy. These include the incorporation of simplified chemistry mechanisms to accelerate model forecasts, use of model-observation data fusion techniques to provide highly localized forecasts, and assimilation of satellite observations to produce more accurate model analyses. We further discuss our attempts to make these tools publicly available on platforms outside the NASA domain, such as Google Earth Engine and Amazon Web Services with the goal to facilitate the integration of state-of-the-science air quality information onto platforms used by stakeholders, air quality managers, and the public.

Emma Knowland↗

NASA NTRSDate not supplied

Assessing the Influence of Decompression Sickness on Medical Risk for Artemis

As NASA begins to shift its focus from LEO missions to the Moon and beyond, our understanding of the risk associated with human spaceflight is challenged by mission profiles and objectives far different from preceding missions. For Artemis, one of these aspects is surface Extra Vehicular Activity (EVA) tempo, in which the crew will perform 3 to 4 surface EVA’s in quick succession. The crew health and performance risk associated with EVA Decompression Sickness (DCS) and its associated countermeasures, is an important consideration for Artemis missions given this new and unprecedented EVA frequency. Successfully completing Artemis mission objectives relies heavily on the crew being able to perform and complete these EVAs. This analysis quantifies how medical risk changes when accounting for the expected increase in DCS risk due to the increase in EVA frequency. If there is an occurrence of DCS during a mission, appropriate downtime needs to be accounted for. Treatment for DCS requires crewmember to stop the current EVA and return to the habitat. This impacts the current EVA the crew is performing, could potentially delay the next EVA, and increases the chance of the crewmember being unable to perform future EVAs. Capturing the downtime and impact of that downtime based on the number of DCS occurrences allows us to better understand how the risk associated with DCS affects the overall medical risk and completion of missions that have more frequent EVA tempo. There are preventative strategies and mitigation countermeasures to decrease the chance of DCS occurring such as different prebreathe protocols, variable suit pressure, and vehicle pressure settings. Modeling the medical risk with and without different DCS countermeasures enables quantitative comparisons of risk reduction associated with each DCS countermeasure. We present results on how these countermeasures affect medical risks and quantify changes in the medical kit contents with respect to the countermeasures implemented within Artemis-class missions.

Clara Gasiewski↗

NASA NTRS2018

A Geostationary Instrument Simulator for Aerosol Observing System Simulation Experiments

In the near future, there will be several new instruments measuring atmospheric composition from geostationary orbit over North America, East Asia, and Europe. This constellation of satellites will provide high resolution, time resolved measurements of trace gases and aerosols for monitoring air quality and tracking pollution sources. This paper describes a detailed, fast, and accurate (less than 1.0% uncertainty) method for calculating synthetic top of the atmosphere (TOA) radiances from a global simulation with a mesoscale free running model, the GEOS-5 Nature Run, for remote sensing instruments in geostationary orbit that measure in the ultraviolet-visible spectral range (UV-Vis). Generating these synthetic observations is the first step of an Observing System Simulation Experiment (OSSE), a framework for evaluating the impact of a new observation or algorithm. This paper provides details of the model sampling, aerosol and cloud optical properties, surface reflectance modeling, Rayleigh scattering calculations, and a discussion of the uncertainties of the simulated TOA radiance. An application for the simulated TOA radiance observations is demonstrated in the manuscript. Simulated TEMPO (Tropospheric Emissions: Monitoring of Pollution) and GOES-R (Geostationary Operational Environmental Satellites) observations were used to show how observations from the two instruments could be combined to facilitate aerosol type discrimination. The results demonstrate the viability of a detailed instrument simulator for radiance measurements in the UV-Vis that is capable of accurately simulating high resolution, time-resolved measurements with reasonable computational efficiency.

Castellanos, Patricia↗