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NASA NTRS2012

Global Scale Attribution of Anthropogenic and Natural Dust Sources and their Emission Rates Based on MODIS Deep Blue Aerosol Products

Our understanding of the global dust cycle is limited by a dearth of information about dust sources, especially small-scale features which could account for a large fraction of global emissions. Here we present a global-scale high-resolution (0.1 deg) mapping of sources based on Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue estimates of dust optical depth in conjunction with other data sets including land use. We ascribe dust sources to natural and anthropogenic (primarily agricultural) origins, calculate their respective contributions to emissions, and extensively compare these products against literature. Natural dust sources globally account for 75% of emissions; anthropogenic sources account for 25%. North Africa accounts for 55% of global dust emissions with only 8% being anthropogenic, mostly from the Sahel. Elsewhere, anthropogenic dust emissions can be much higher (75% in Australia). Hydrologic dust sources (e.g., ephemeral water bodies) account for 31% worldwide; 15% of them are natural while 85% are anthropogenic. Globally, 20% of emissions are from vegetated surfaces, primarily desert shrublands and agricultural lands. Since anthropogenic dust sources are associated with land use and ephemeral water bodies, both in turn linked to the hydrological cycle, their emissions are affected by climate variability. Such changes in dust emissions can impact climate, air quality, and human health. Improved dust emission estimates will require a better mapping of threshold wind velocities, vegetation dynamics, and surface conditions (soil moisture and land use) especially in the sensitive regions identified here, as well as improved ability to address small-scale convective processes producing dust via cold pool (haboob) events frequent in monsoon regimes.

aerosols↗
NASA NTRS2014

The International Space Station: A Unique Platform for Remote Sensing of Natural Disasters

Assembly of the International Space Station (ISS) was completed in 2012, and the station is now fully operational as a platform for remote sensing instruments tasked with collecting scientific data about the Earth system. Remote sensing systems are mounted inside the ISS, primarily in the U.S. Destiny Module's Window Observational Research Facility (WORF), or are located on the outside of the ISS on any of several attachment points. While NASA and other space agencies have had remote sensing systems orbiting Earth and collecting publicly available data since the early 1970s, these sensors are carried onboard free-flying, unmanned satellites. These satellites are traditionally placed into Sun-synchronous polar orbits that allow imaging of the entire surface of the Earth to be repeated with approximately the same Sun illumination (typically local solar noon) over specific areas, with set revisit times that allow uniform data to be taken over long time periods and enable straightforward analysis of change over time. In contrast, the ISS has an inclined, Sun-asynchronous orbit (the solar illumination for data collections over any location changes as the orbit precesses) that carries it over locations on the Earth between approximately 52degnorth and 52deg south latitudes (figure 1). The ISS is also unique among NASA orbital platforms in that it has a human crew. The presence of a crew provides options not available to robotic sensors and platforms, such as the ability to collect unscheduled data of an unfolding event using handheld digital cameras as part of the Crew Earth Observations (CEO) facility and on-the-fly assessment of environmental conditions, such as cloud cover, to determine whether conditions are favorable for data collection. The crew can also swap out internal sensor systems installed in the WORF as needed. The ISS orbit covers more than 90 percent of the inhabited surface of the Earth, allowing the ISS to pass over the same ground locations at different times of the day and night. This is important for two reasons: 1) certain surface processes (i.e., development of coastal fog banks) occur at times other than local solar noon, making it difficult to collect relevant data from traditional satellite platforms, and 2) it provides opportunities for the ISS to collect data for short-duration events, such as natural disasters, that polar-orbiting satellites may miss due to their orbital dynamics - in essence, the ISS can be "in the right place at the right time" to collect data. An immediate application of ISS remote sensing data collection is that the data can be used to provide information for humanitarian aid after a natural disaster. This activity contributes directly to the station's Benefits to Humanity mission. The International Charter, Space and Major Disasters (also known as the International Disaster Charter, or IDC) is an agreement between agencies of several countries to provide - on a best-effort basis - remotely sensed data related to natural disasters to requesting countries in support of disaster response. In the United States, the lead agency for interaction with the IDC is the United States Geological Survey (USGS); when an IDC request, or activation, is received, the USGS notifies the science teams for NASA instruments with targeting information for data collection. In the case of the ISS, Earth scientists in the JSC ARES Directorate, in association with the ISS Program Science Office, coordinate targeting and data collection with the USGS. If data is collected, it is passed back to the USGS for posting on its Hazards Data Distribution System and made available for download. The ISS was added to the USGS's list of NASA remote sensing assets that could respond to IDC activations in May 2012. Initially, the NASA ISS sensor systems available to respond to IDC activations included the ISS Agricultural Camera (ISSAC), an internal multispectral visible-near infrared wavelength system mounted in the WORF; CEO, a project that collects imagery through the ISS windows using off-the-shelf handheld digital visible-wavelength cameras; and the Hyperspectral Imager for the Coastal Oceans (HICO), a visible to near-infrared system mounted externally on the Japanese Experiment Module - Exposed Facility. Since May 2012, there have been 37 IDC activations; ISS sensor systems have collected data for 10 of these events.

Stefanov, William L.↗
NASA NTRS2016

Study of the Effect of Temporal Sampling Frequency on DSCOVR Observations Using the GEOS-5 Nature Run Results (Part I): Earths Radiation Budget

Satellites always sample the Earth-atmosphere system in a finite temporal resolution. This study investigates the effect of sampling frequency on the satellite-derived Earth radiation budget, with the Deep Space Climate Observatory (DSCOVR) as an example. The output from NASA's Goddard Earth Observing System Version 5 (GEOS-5) Nature Run is used as the truth. The Nature Run is a high spatial and temporal resolution atmospheric simulation spanning a two-year period. The effect of temporal resolution on potential DSCOVR observations is assessed by sampling the full Nature Run data with 1-h to 24-h frequencies. The uncertainty associated with a given sampling frequency is measured by computing means over daily, monthly, seasonal and annual intervals and determining the spread across different possible starting points. The skill with which a particular sampling frequency captures the structure of the full time series is measured using correlations and normalized errors. Results show that higher sampling frequency gives more information and less uncertainty in the derived radiation budget. A sampling frequency coarser than every 4 h results in significant error. Correlations between true and sampled time series also decrease more rapidly for a sampling frequency less than 4 h.

GEOS-5↗
NASA NTRS2016

Orion Versus Poseidon: Understanding How Nasa's Crewed Capsule Survives Nature's Fury

This presentation summarizes the Marshall Space Flight Center Natural Environments Terrestrial and Planetary Environments (TPE) Team support to the NASA Orion space vehicle. The Orion vehicle, part of the Multi-Purpose Crew Vehicle Program, is designed to carry astronauts beyond low-Earth orbit and is currently undergoing a series of tests including Exploration Flight Test (EFT)-1. This design must address the natural environment to which the capsule and launch vehicle are exposed during all mission phases. In addition, the design must, to the best extent possible, implement the same process and data to be utilized on launch day. The TPE utilizes meteorological data to assess the sensitivities of the vehicle due to the terrestrial environment. The presentation describes examples of TPE support for vehicle design and several tests, as well as support for EFT-1 and planning for upcoming Exploration Missions while emphasizing the importance of accounting for the natural environment's impact to the vehicle early in the vehicle's program.

Barbre, Robert E., Jr.↗
NASA NTRS2017

'Fly Like This': Natural Language Interface for UAV Mission Planning

With the increasing presence of unmanned aerial vehicles (UAVs) in everyday environments, the user base of these powerful and potentially intelligent machines is expanding beyond exclusively highly trained vehicle operators to include non-expert system users. Scientists seeking to augment costly and often inflexible methods of data collection historically used are turning towards lower cost and reconfigurable UAVs. These new users require more intuitive and natural methods for UAV mission planning. This paper explores two natural language interfaces - gesture and speech - for UAV flight path generation through individual user studies. Subjects who participated in the user studies also used a mouse-based interface for a baseline comparison. Each interface allowed the user to build flight paths from a library of twelve individual trajectory segments. Individual user studies evaluated performance, efficacy, and ease-of-use of each interface using background surveys, subjective questionnaires, and observations on time and correctness. Analysis indicates that natural language interfaces are promising alternatives to traditional interfaces. The user study data collected on the efficacy and potential of each interface will be used to inform future intuitive UAV interface design for non-expert users.

Chandarana, Meghan↗
NASA NTRS2013

Human and Natural Influences on the Changing Thermal Structure of the Atmosphere

Since the late 1970s, satellite-based instruments have monitored global changes in atmospheric temperature. These measurements reveal multidecadal tropospheric warming and stratospheric cooling, punctuated by short-term volcanic signals of reverse sign. Similar long- and short-term temperature signals occur in model simulations driven by human-caused changes in atmospheric composition and natural variations in volcanic aerosols. Most previous comparisons of modeled and observed atmospheric temperature changes have used results from individual models and individual observational records. In contrast, we rely on a large multimodel archive and multiple observational datasets. We show that a human-caused latitude/altitude pattern of atmospheric temperature change can be identified with high statistical confidence in satellite data. Results are robust to current uncertainties in models and observations. Virtually all previous research in this area has attempted to discriminate an anthropogenic signal from internal variability. Here, we present evidence that a human-caused signal can also be identified relative to the larger "total" natural variability arising from sources internal to the climate system, solar irradiance changes, and volcanic forcing. Consistent signal identification occurs because both internal and total natural variability (as simulated by state-of-the-art models) cannot produce sustained global-scale tropospheric warming and stratospheric cooling. Our results provide clear evidence for a discernible human influence on the thermal structure of the atmosphere.

Santer, Benjamin D.↗
NASA NTRS2019

Simplifying NASA Earth Science Data and Information Access Through Natural Language Processing Based Data Analysis and Visualization

NASA Earth science data collected from satellites, model assimilation, airborne missions, and field campaigns, are large, complex and evolving. Such characteristics pose great challenges for end users (e.g., Earth science and applied science users, students, citizen scientists), particularly for those who are unfamiliar with NASA's EOSDIS and thus unable to access and utilize datasets effectively. For example, a novice user may simply ask: what is the total rainfall for a flooding event in my county yesterday? For an experienced user (e.g., algorithm developer), a question can be: how did my rainfall product perform, compared to ground observations, during a flooding event? Nonetheless, with rapid information technology development such as natural language processing, it is possible to develop simplified Web interfaces and back-end processing components to handle such questions and deliver answers in terms of text, data, or graphic results directly to users.In this presentation, we describe the main challenges for end users with different levels of expertise in accessing and utilizing NASA Earth science data. Surveys reveal that most non-professional users normally do not want to download and handle raw data as well as conduct heavy-duty data processing tasks. Often they just want some simple graphics or data for various purposes. To them, simple and intuitive user interfaces are sufficient because complicated ones can be difficult and time-consuming to learn. Professionals also want such interfaces to answer many questions from datasets. One solution is to develop a natural language based search box like Google and the search results can be text, data, graphics and more. Now the challenge is, with natural language processing, can we design a system to process a scientific question typed in by a user? In this presentation, we describe our plan for such a prototype. The workflow is: 1) extract needed information (e.g., variables, spatial and temporal information, processing methods, etc.) from the input, 2) process the data in the backend, and 3) deliver the results (data or graphics) to the user.

Liu, Zhong↗
NASA NTRSDate not supplied

Validation of Rendered Natural and Artificial Lighting Environments in Real Time Lunar South Pole Simulations

NASA’s Artemis campaign is making heavy use of simulation to help return humans to the lunar surface by the end of the decade. There are several aspects of the lunar surface and its environment which must be accurately modeled before these simulations can be relied upon to influence decisions being made under these programs. Digital Lunar Exploration Sites, a paper submitted to the 2022 IEEE Aerospace Conference, outlined the process used to generate the lunar surface in a digital environment. This paper will expand upon this topic and delve into the steps being taken by the NASA Exploration Systems Simulations (NExSyS) team at NASA’s Johnson Space Center (JSC) to properly verify and validate these simulations, with a focus on the visual aspects of the environment. Natural lighting validation relies in part on the wealth of data generated during the Apollo program. Many images taken by Apollo astronauts on the lunar surface have been replicated in the simulated environments to gain confidence in the accuracy of terrain and lighting models. However, because the environment the Artemis astronauts will experience at the Lunar South Pole (LSP) is dissimilar from the near-equatorial Apollo sites, other validation techniques must be applied. At the LSP, the sun crests only about three degrees above the horizon and when combined with the lack of a lunar atmosphere, lighting in this region is often very different than what a human would experience on Earth. Solar illumination, earthshine, human eye response, solar blooming, lunar regolith optical properties, and shadows cast by rocks and crater walls will play a significant role in an astronaut’s ability to safely conduct an Extra-Vehicular Activity (EVA) or perform a traverse with a lunar rover. Approaches for validation of these aspects of the rendered LSP environment are considered in this paper. In addition to natural lighting, approaches for the validation of artificial lighting models at the LSP are discussed. The JSC Lighting Lab has been studying the illumination profile of the Exploration Infomatics Subsystem (xINFO) lighting on the Exploration EVA Mobility Unit (xEMU). How these lights interact with the solar illumination and the shadows being cast on the lunar surface is of particular interest, so the validity of models representing these lights in a human-in-the-loop virtual reality environment becomes very important. This paper also touches on some of the simulation performance considerations when a Human in the Loop (HITL) is present, which drives the need for real time rendering of the environment. Natural and artificial lighting will play a crucial role to decisions being made when planning and executing missions at the Lunar South Pole (LSP) and it is vitally important to understand the LSP environment before we return.

Lunar↗
NASA NTRSDate not supplied

Hypervelocity Dust Impact in Olivine: Fib/Tem Characterization and Comparison of Experimental and Natural Microcraters

The flux of objects impacting the surfaces of solar system airless bodies is dominated by micrometeoroids less than 1 mm diameter whose impact effects play a major role in the space weathering of airless body surfaces. To obtain better understanding of how small scale impact effects vary as a function of impact speed in an important lunar and asteroidal mineral, we produced artificial microcraters in San Carlos olivine using Fe metal dust particles 0.10 to 5 µm in diameter electrostatically accelerated to speeds between 0.35 to 25 km s-1. The crater morphologies, size distrrubiton and microstruc-tures were characterized by field-emission SEM (FE-SEM) and also by FIB cross sectioning of selected craters for field-emission scanning transmission electron microscopy (FE-STEM). These same techniques were also applied to study a natural 20 µm-diameter microcrater in a olivine grain on the surface of lunar rock 12075. Measured microcrater diameters in the experimental sample range between 0.20 to 5 µm with larger craters having more irregular outlines dominated by spallation fractures. FE-SEM and FE-STEM imaging docu-ment the formation of shock melt in the size population of experimental craters below approximately 1 µm in diameter, corresponding to particle impact speeds in the 10-25 km s-1 range. The natural olivine crater exhibits similar shock melt features along the perimeter of its cavity, but the shock melt also contains nanophase Fe metal particles, something not observed in the experimental samples. FE-STEM imaging of the experimental craters reveals complex shock-generated dislocation and nanofracture microstructures in zones extend-ing 1-2 µm into the olivine from the crater cavity. The natural microcrater shows a lower density of shock-generated disloca-tions that extends a factor of 2 deeper into the the olivine than in the experimental samples.

Roy Gray Christoffersen↗
NASA NTRS2023

Two Decades of Land Cover Change and Forest Fragmentation in Liberia: Consequences for the Contribution of Nature to People

The Guinean forests of West Africa have been identified as a global biodiversity hotspot due to its exceptional concentrations of endemic species and exceptional loss of habitats. The majority of what remains of the Guinean forests lies within Liberia, a country whose share of total wealth is nearly equally distributed into human and natural capital. The Liberian government seeks a more inclusive development agenda that forges a path for improved human capital while sustainably managing its natural capital wealth, which requires consistent data on land cover change and forest disturbance over time. To address this need, Landsat data were used to map and quantify land cover change and forest fragmentation in Liberia between 2000 and 2018. In addition, LiDAR data from the Global Ecosystem Dynamics Investigation (GEDI) mission were applied to assess the integrity of forest remnants. Between 2000 and 2018, only 1% of all forest cover classes (i.e., dense/primary, open/secondary and sparse/degraded) were converted into non-forest classes, with the most observed change being between these three forest classes. During the study period, 27% of the dense/primary forest class transitioned to either the open/secondary or sparse/degraded canopy classes through consistent fragmentation along the edges of the last large remaining blocks of dense/primary forest located in the north-west and south-east of Liberia and more than 14% of dense/primary forest areas identified in previous studies as “essential natural capital” for either biodiversity, forest carbon storage or provision of freshwater ecosystem services were degraded. The 2018 GEDI-based measurements show that the overall average height of dense/primary forest decreases by 24% and 48%, and canopy closure decreases by 33% and 59%, when transitioned to the open/secondary and sparse/degraded classes, respectively. The information derived from this analysis will be critical for informing the development of new policies and actions, leading to more sustainable forest management in Liberia.

Celio De Sousa↗
NASA NTRS2023

Arguments for the Physical Nature of the Triggered Ion-Acoustic Waves Observed on the Parker Solar Probe

Triggered ion-acoustic waves are a pair of coupled waves observed in the previously unexplored plasma regime near the Sun. They may be capable of producing important effects on the solar wind. Because this wave mode has not been observed or studied previously and it is not fully understood, the issue of whether it has a natural origin or is an instrumental artifact can be raised. This paper discusses this issue by examining 13 features of the data such as whether the triggered ion-acoustic waves are electrostatic, whether they are both narrowband, whether they satisfy the requirement that the electric field is parallel to the k-vector, whether the phase difference between the electric field and the density fluctuations is 90°, whether the two waves have the same phase velocity as they must if they are coupled, whether the phase velocity is that of an ion-acoustic wave, whether they are associated with other parameters such as electron heating, whether the electric field instrument otherwise performed as expected, etc. The conclusion reached from these analyses is that triggered ion-acoustic waves are highly likely to have a natural origin although the possibility that they are artifacts unrelated to processes occurring in the natural plasma cannot be eliminated. This inability to absolutely rule out artifacts as the source of a measured result is a characteristic of all measurements.

Electric fields↗
NASA NTRSDate not supplied

A Natural Language Understanding Approach for Digitizing Aircraft Ground Taxi Instructions

Advancements in natural language processing (NLP) technologies offer a unique opportunity to furnish aircraft crews, primarily pilots, with digital instructions for taxiing operations. Digital taxi instructions, delivered either as text or graphics, can streamline taxiing procedures, thereby reducing radio congestion, minimizing communication errors, and enhancing aircraft monitoring. Techniques used for natural language understanding (NLU), a subset of NLP focused on machine comprehension of natural language, can extract taxi instructions directly from verbal radio communications. This capability paves the way for implementing a digital taxi communication framework with minimal adjustments to the existing air traffic controller operations. This paper delves into a novel application of NLU: the automated generation of digital taxi instructions from air traffic controller speech. We detail the development of an annotation scheme to represent aircraft ground traffic communications within the US National Airspace System (NAS), employing intent classification (IC) and slot filling (SF) to extract taxi instructions using NLU models. Several neural network models were trained on a dataset annotated with our scheme, achieving notable accuracy and F1 scores. Our research demonstrates the feasibility of using NLU to automatically generate digital taxi instructions, showcasing its potential to streamline the implementation of digital taxi communications.

LSTM↗
NASA NTRSDate not supplied

A Natural Language Understanding Approach for Digitizing Aircraft Ground Taxi Instructions

Advancements in natural language processing (NLP) technologies offer a unique opportunity to furnish aircraft crews, primarily pilots, with digital instructions for taxiing operations. Digital taxi instructions, delivered either as text or graphics, can streamline taxiing procedures, thereby reducing radio congestion, minimizing communication errors, and enhancing aircraft monitoring. Techniques used for natural language understanding (NLU), a subset of NLP focused on machine comprehension of natural language, can extract taxi instructions directly from verbal radio communications. This capability paves the way for implementing a digital taxi communication framework with minimal adjustments to the existing air traffic controller operations. This paper delves into a novel application of NLU: the automated generation of digital taxi instructions from air traffic controller speech. We detail the development of an annotation scheme to represent aircraft ground traffic communications within the US National Airspace System (NAS), employing intent classification (IC) and slot filling (SF) to extract taxi instructions using NLU models. Several neural network models were trained on a dataset annotated with our scheme, achieving notable accuracy and 𝐹1 scores. Our research demonstrates the feasibility of using NLU to automatically generate digital taxi instructions, showcasing its potential to streamline the implementation of digital taxi communications.

ATC↗
NASA NTRSDate not supplied

Effects of Natural Variability on the Use of Standard Deviation to Represent Measurement Uncertainties in Atmospheric Composition Studies

Measurement uncertainty is defined as a “non-negative parameter characterizing the dispersion of the quantity values being attributed to a measurand”. It is most common that the uncertainties of GAW hourly measurements, such as greenhouse gas measurements, are reported as standard deviations derived from individual sampling at a higher time resolution (e.g., 1 min). In contrast, the uncertainties of GAW measurements of reactive gases and aerosol properties are reported in percentiles covering the same probability. A quick look at hourly CO 2 data from Cape Grim, Australia yielded some interesting findings: the hourly standard deviation is, on average, more than a factor of 10 higher for the measurements under non-background conditions (over 50% observations), while the difference in average CO 2 amount fraction was less than 2 ppm. The dramatic contrast cannot be explained by the difference in measurement uncertainties, but can largely be attributed the natural variability, or episodic ambient CO 2 variation reflecting changes in meteorological conditions or emissions. These initial findings motivated a more in-depth analysis of the ground-based measurements of trace gases and aerosol properties. This analysis will be using continuous 1 min ground site observations to construct time averaged statistical indicators to evaluate whether the standard deviation is adequate to represent the dispersion, especially under marked influence by natural variability. The suitability of this representation can be determined by examining the difference between the standard deviation and percentiles encompassing the same probability. We will examine time intervals of 1 hour, 3 hours, and 24 hours, with the latter time intervals chosen to match those commonly used in model assessments. We will also investigate how natural variability can alter the probability distribution of the measurands and how adequate the quadrature propagation of uncertainties is under these conditions. The results will include several trace gases (e.g., CO 2 , CO, O 3 , and NO 2 ) with a range of measurement techniques (e.g., PANDORA, in situ), atmospheric lifetimes, and aerosol properties (e.g. scattering coefficient). The findings from this analysis should provide some useful feedback on the best practices for uncertainty reporting.

Measurement Uncertainty↗
NASA NTRS2003

Role of major histocompatibility complex class II in resistance of mice to naturally acquired infection with Syphacia obvelata

Genetics plays a substantial role in host resistance in many host-parasite interactions. We examined the prevalence of naturally acquired infection with Syphacia obvelata in a number of mouse strains housed in a non-barrier facility. These mice, which included cross-bred and congenic, inbred strains on various genetic backgrounds, differ in the loci for the immune function genes--major histocompatibility complex class II (MHCII), toll-like receptor 4 (Tlr4), and solute carrier family 11, member 1 (Slc11a1)--which allowed comparisons of the impact of these genes on resistance to pinworm infection. Male and female mice of various ages were sampled over an 18-month period; infection was determined by use of the cellophane tape test. Results indicated that mice that were MHCII+/+ had a significantly lower prevalence of infection than did mice that were MHCII-/-. Differences were not seen between male and female mice. Although MHCII+/+ mice had an age-associated decrease in infection prevalence, such decrease was not seen in MHCII-/- mice. In contrast, infection prevalence in mice with the normal Tlr4 gene (Tlr4(LPS-n/LPS-n)) gene did not differ significantly compared with that in mice that were homozygous for either the point mutation (Tlr4(LPS-d/LPS-d)) or deletion (Tlr4(LPS-del/LPS-del)) of that gene. Likewise, the presence (Sle11a1r/r) or absence (Slc11a1s/s) of functional alleles for Slc11a1 had no effect on the prevalence of infection with S. obvelata. In conclusion, presence of MHCII, but not Tlr4 or Slc11a1 significantly influences prevalence of naturally acquired infection with S. obvelata. These data justify further comprehensive analyses of the immune components that are involved in pinworm resistance.

Non-NASA Center↗
NASA NTRS2015

Bundle Data Approach at GES DISC Targeting Natural Hazards

Severe natural phenomena such as hurricane, volcano, blizzard, flood and drought have the potential to cause immeasurable property damages, great socioeconomic impact, and tragic loss of human life. From searching to assessing the Big, i.e., massive and heterogeneous scientific data (particularly, satellite and model products) in order to investigate those natural hazards, it has, however, become a daunting task for Earth scientists and applications researchers, especially during recent decades. The NASA Goddard Earth Sciences Data and Information Service Center (GES DISC) has served Big Earth science data, and the pertinent valuable information and services to the aforementioned users of diverse communities for years. In order to help and guide our users to online readily (i.e., with a minimum effort) acquire their requested data from our enormous resource at GES DISC for studying their targeted hazard event, we have thus initiated a Bundle Data approach in 2014, first targeting the hurricane event topic. We have recently worked on new topics such as volcano and blizzard. The bundle data of a specific hazard event is basically a sophisticated integrated data package consisting of a series of proper datasets containing a group of relevant (knowledge--based) data variables readily accessible to users via a system-prearranged table linking those data variables to the proper datasets (URLs). This online approach has been developed by utilizing a few existing data services such as Mirador as search engine; Giovanni for visualization; and OPeNDAP for data access, etc. The online Data Cookbook site at GES DISC is the current host for the bundle data. We are now also planning on developing an Automated Virtual Collection Framework that shall eventually accommodate the bundle data, as well as further improve our management in Big Data.

GES DISC↗
NASA NTRS2018

Natural and Induced Environment around the International Space Station (ISS) as Observed during On-Orbit Operations of the Robotic External Leak Locator (RELL)

Final Document is attached. The Robotic External Leak Locator (RELL) was deployed to the International Space Station (ISS) with the goal of detecting and locating on-orbit leaks around the ISS. Three activities to investigate and corroborate the background natural and induced environment of ISS were performed with RELL as part of the on-orbit validation and demonstration conducted in November – December 2016. The first demonstration activity pointed RELL directly in the ram and wake directions for one orbit each. The ram facing measurements showed high partial pressure for mass-to-charge ratio 16, corresponding to atomic oxygen (AO), as well as the presence of mass-to-charge ratio 17. RELL™s view in the wake-facing direction included more ISS structure and several Environmental Control and Life Support System (ECLSS) on-orbit vents were detected, including the Carbon Dioxide Removal Assembly (CDRA), Russian segment ECLSS, and Sabatier vents. The second demonstration activity pointed RELL at three faces of the P1 Truss segment. Effluents from ECLSS and European Space Agency (ESA) Columbus module on-orbit vents were detected by RELL. The partial pressures of mass-to-charge ratios 17 and 18 remained consistent with the first on-orbit activity of characterizing the natural environment. The third demonstration activity involved RELL scanning an Active Thermal Control System (ATCS) radiator. Three locations along the radiator were scanned and the angular position of RELL with respect to the radiator was varied. Mass-to-charge ratios 16 and 17 both had upward shifts in partial pressure when pointing toward the Radiator Beam Valve Modules (RBVMs), likely corresponding to a known, small ammonia leak.

International Space Station↗
NASA NTRS2021

Investigations on the Anthropogenic Reversal of the Natural Ozone Gradient Between Northern and Southern Midlatitudes

Our quantitative understanding of natural tropospheric ozone concentrations is limited by the paucity of reliable measurements before the 1980s. We utilize the existing measurements to compare the long-term ozone changes that occurred within the marine boundary layer at northern and southern midlatitudes. Since 1950 ozone concentrations have increased by a factor of 2.1 ± 0.2 in the Northern Hemisphere (NH) and are presently larger than in the Southern Hemisphere (SH), where only a much smaller increase has occurred. These changes are attributed to increased ozone production driven by anthropogenic emissions of photochemical ozone precursors that increased with industrial development. The greater ozone concentrations and increases in the NH are consistent with the predominant location of anthropogenic emission sources in that hemisphere. The available measurements indicate that this interhemispheric gradient was much smaller and was likely reversed in the pre-industrial troposphere with higher concentrations in the SH. Six Earth system model (ESM) simulations indicate similar total NH increases (1.9 with a standard deviation of 0.3), but they occurred more slowly over a longer time period, and the ESMs do not find higher pre-industrial ozone in the SH. Several uncertainties in the ESMs may cause these model–measurement disagreements: the assumed natural nitrogen oxide emissions may be too large, the relatively greater fraction of ozone injected by stratosphere–troposphere exchange to the NH may be overestimated, ozone surface deposition to ocean and land surfaces may not be accurately simulated, and model treatment of emissions of biogenic hydrocarbons and their photochemistry may not be adequate.

natural tropospheric ozone concentrations↗