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NASA NTRSDate not supplied

Investigating Space Weathering Effects on Carbonaceous Asteroids Using High-flux and Low-flux Ion Irradiation of the Murchison Meteorite

Airless planetary bodies are continuously altered by space weathering processes such as solar wind irradiation and micrometeoroid bombardment. These processes change the microstructural, chemical, and optical properties of planetary regoliths and, in turn, complicate interpretations of surface composition from remote sensing data. Previous space weathering investigations have focused primarily on lunar and ordinary chondrite materials, the latter of which have been directly linked to S-type asteroids [1]. However, relatively little is known about space weathering of primitive carbonaceous chondrites, which contain a combination of hydrous silicate and organic phases and are hypothesized to be fragments of C-complex asteroids [2]. To address this knowledge gap and maximize the science return of missions targeting C-complex asteroids (e.g., NASA OSIRIS-REx targeting Bennu and JAXA Hayabusa2 targeting Ryugu)[3-4], we examine the spectral, microstructural, and chemical effects of simulated solar wind weathering on a carbonaceous asteroid analog material. Here, we present the results from coordinated analyses of Murchison (CM2) meteorite slabs irradiated with 1 keV/amu H+ and He+ ions.

space weathering↗

NASA NTRSDate not supplied

Collaborative Weather Research and Development for Urban Air Mobility

NASA recently collaborated with National Center for Atmospheric Research (NCAR) and AvMet Application Inc. to identify the weather information, existing aviation weather products, and the novel approaches that are required to model and mitigate various impacts of uncertain atmospheric conditions to support safe and efficient Urban Air Mobility (UAM) operations. This presentation will provide updates on the collaborative efforts of weather impacts modelling and analysis for future evaluation of UAM concepts of operations in the presence of weather.

Urban Air Mobility↗

NASA NTRS2022

Building Space Weather Literacy Through Sustained Engagement

Space weather affects all space systems, both natural and artificial. There is a rapid growth of awareness in past decades of this reality and a critical need for space weather prediction due to technology advances. Above all, space weather science and its history are outstanding vehicles for teaching science, technology, engineering, and mathematics (STEM) topics. As a white paper group, we recommend that the Decadal Survey builds space weather literacy within K–14 classrooms and the general public, covering all areas of studies in Heliophysics through sustained engagement beyond celestial and spacecraft events.

Space Weather↗

NASA NTRS2023

Integrating NASA Aqua AIRS in a Real-Time NUCAPS Science-to-Applications System to Support Severe Weather Forecasting

In recent years, National Oceanic and Atmospheric Administration (NOAA) Unique Combined Atmospheric Processing System (NUCAPS) hyperspectral infrared satellite sounding retrievals derived from Joint Polar Satellite System (JPSS) polar-orbiting satellites have been documented as observations that add value to weather forecasting applications. NUCAPS is currently the operational algorithm delivering JPSS satellite sounding retrievals to the NOAA National Weather Service (NWS) and is based on the heritage Atmospheric Infrared Sounder (AIRS) Science Team algorithm for processing vertical temperature, moisture, and trace gas retrievals. For the Special Collection on “Twenty Years of Observations from AIRS,” we highlight the methodology we implemented to develop a prototype science-to-applications system to enable real-time processing of AIRS satellite sounding retrievals through the NUCAPS algorithm (i.e., NUCAPS-Aqua) to support weather forecasting applications. The addition of NUCAPS-Aqua to experimental real-time pathways alongside operational JPSS NUCAPS soundings, facilitated assessment of NUCAPS-Aqua at the 2022 Hazardous Weather Testbed (HWT) Spring Experiment. Development of NUCAPS-Aqua described in this technical report includes preservation of microwave observations and calculation of a-priori regression coefficients. Additionally, the real-time processing and challenges with implementing a science-to-applications system are discussed. Two illustrative pre-convective forecasting examples analyzed by NWS forecasters during the 2022 HWT Spring Experiment are highlighted to demonstrate the benefit of NUCAPS-Aqua as (a) special afternoon soundings, (b) an additional observation to assess temporal trends using multiple satellites, and (c) a complement to observational and model analysis.

remote sensing↗

NASA NTRSDate not supplied

Supporting Space Weather Modelling at the Community Coordinated Modeling Center (CCMC)

Space weather models are essential to our ability to understand and predict space weather events. Nonetheless, some of the most cutting-edge models may struggle to move past the initial research stage, remaining unknown and inaccessible to a wider research audience, thereby hindering validation, intercomparison and adoption of the models. The Community Coordinated Modeling Center (CCMC, https://ccmc.gsfc.nasa.gov) closes this gap by providing a convenient platform for hosting space weather models and associated services. Using these services, researchers and other end-users may exercise, evaluate, and intercompare contributed models, as well as collaborate on a growing archive of model run results. In this presentation, we will discuss current and planned capabilities in some of the model services at CCMC, including Runs-on-Request, Instant Runs, and Real-Time Continuous Runs. We will also review new models added to the extensive collection of space weather models hosted at CCMC. Finally, we will talk about our efforts at streamlining model delivery to CCMC, including support for containerized models and establishment of an open collaborative environment based on Amazon Web Services (AWS).

space weather↗

NASA NTRSDate not supplied

Enabling Collaborative Space Weather Research at the Community Coordinated Modeling Center (CCMC)

Space weather models have been actively developed by the international research community, covering extensive spatial and physical domains. Still, many of the ground-breaking models remain a granular effort, insulated from a wider research audience, particularly that in different domains, and possible end users. The Community Coordinated Modeling Center (CCMC, https://ccmc.gsfc.nasa.gov) seeks to remove such barriers to collaboration and coordination by providing a convenient platform for hosting space weather models and associated services. Using these services, researchers and other end-users may exercise, evaluate, and intercompare contributed models, as well as collaborate on a continuously updated archive of model run results. Moreover, the multi-disciplinary science support team at CCMC facilitates and enables collaboration across domains. In our presentation, we will discuss the space weather model services at CCMC, including Runs-on-Request, Real-Time Continuous Runs, and Instant Runs. We will also review new and updated models added to the extensive collection of space weather models hosted at CCMC. We will focus on trends in model, service, and science support utilization at CCMC as a proxy to the most pressing needs of the collaborative modeling community.

space weather↗

NASA NTRSDate not supplied

Lowering Barriers to Science and Space Weather Research at the Community Coordinated Modeling Center (CCMC)

The Space Weather and Heliophysics research and modeling community has been pushing the limits of our ability to understand and predict space weather events. The Community Coordinated Modeling Center (CCMC, https://ccmc.gsfc.nasa.gov) supports the community by providing a convenient collaborative platform hosting space weather models, model simulation data, curated datasets of solar events, and associated value-added services. Using these services, researchers and other end-users may exercise, evaluate, and intercompare contributed models, triage designated R2O models, as well as collaborate on a continuously updated archive of model run results. We will focus on CCMC’s ongoing commitment to the principles and guidelines of the Open Science initiative. Particularly, we will discuss our work towards making our services more transparent and our library of model simulations more accessible, open, and reproducible. We will introduce our recent tools for data discovery and correlative analysis designed to further increase the value of the user-generated data and metadata. We will also present our recent work on making heliophysical models more accessible and open to the community, particularly through simplified user experience and expert domain support. We will report on our progress in establishing an inter-center infrastructure with the ESA Virtual Space Weather Modelling Centre (VSWMC), designed to cross organizational boundaries and provide streamlined access to a joint palette of the models.

space weather↗

DOE OSTI2019

Implementation and Investigation of a Weather- and Jam Density-tuned Network Perimeter Controller

This paper implements and evaluates the performance of a network fundamental diagram (NFD) proportional-integral perimeter controller (PC) using base tuned parameters (clear weather conditions and a base jam density of 160 veh/km/lane). The parameters were then re-tuned separately for different weather conditions and jam density values (reflecting different percentage of trucks), resulting in two new control methods: a weather-tuned perimeter controller (WTPC) and a jam density-tuned perimeter controller (JTPC). The WTPC was shown to outperform the no control strategy and the PC for different weather conditions. Specifically, the WTPC decreased the congestion inside the protected network (PN) and improved the overall performance of the full network (FN) by decreasing the average vehicle travel time, decreasing the vehicle total delay, increasing the average vehicle speed and decreasing the average vehicle fuel consumption. Alternatively, the JTPC was shown to perform similar to the PC for jam densities higher than the base-case jam density used in the PC (in our case 160 veh/km/lane). However, the JTPC outperformed the PC for smaller jam densities given that these smaller jam densities result in queues spilling back faster to upstream traffic signals. The results demonstrate the need to tune the controller to the actual jam density especially when the jam density decreases (e.g. trucks are introduced to the network). http://pubsindex.trb.org/

42 ENGINEERING↗

DOE OSTI2020

Degradation in photovoltaic encapsulation strength of attachment: Results of the first PVQAT TG5 artificial weathering study

Delamination of the encapsulant in photovoltaic (PV) module technology results in immediate optical loss and may enable subsequent corrosion or mechanical damage. The effects of artificial weathering were not previously known; therefore, an empirical study was performed to survey the factors most affecting adhesion, including the ultraviolet (UV) source (ie, Xe or fluorescent lamp[s]), the optical filters for the lamp, the chamber temperature, and the relative humidity. Natural weathering was also performed at locations, including the following: Golden, Colorado; Miami, Florida; Phoenix, Arizona; QiongHai, China; Riyadh, Saudi Arabia; and Turpan, China. Specimens were constructed using a laminated glass/poly (ethylene-co-vinyl acetate)/glass geometry. The compressive shear test (CST) was used to quantify the mechanical strength of attachment, taken as a proxy for adhesion. The fractography of select specimens (including cross-sectional optical microscopy) was used to verify the failure mode (delamination or decohesion). Additional analysis of the local solar spectrum as well as the specimen temperature was performed to interpret the results of natural weathering. The goals of this study include to identify the most significant stressors, clarify where strong coupling may occur between stressors, and validate accelerated test results relative to natural weathering. The importance of specimen conditioning (for moisture) and hygrometric degradation as well as the effects of UV degradation are identified in this paper.

14 SOLAR ENERGY↗

DOE OSTI2017

Atmospheric Corrosion Behavior and Mechanism of a Ni-Advanced Weathering Steel in Simulated Tropical Marine Environment

Corrosion behavior of Ni-advanced weathering steel, as well as carbon steel and conventional weathering steel, in a simulated tropical marine atmosphere was studied by field exposure and indoor simulation tests. Meanwhile, morphology and composition of corrosion products formed on the exposed steels were surveyed through scanning electron microscopy, energy-dispersive x-ray spectroscopy and x-ray diffraction. Results indicated that the additive Ni in weathering steel played an important role during the corrosion process, which took part in the formation of corrosion products, enriched in the inner rust layer and promoted the transformation from loose γ-FeOOH to dense α-FeOOH. As a result, the main aggressive ion, i.e., Cl{sup −}, was effectively separated in the outer rust layer which leads to the lowest corrosion rate among these tested steels. Thus, the resistance of Ni-advanced weathering steel to atmospheric corrosion was significantly improved in a simulated tropical marine environment.

36 MATERIALS SCIENCE↗

DOE OSTI2014

Impact of sedimentary provenance and weathering on arsenic distribution in aquifers of the Datong basin, China: Constraints from elemental geochemistry

Arsenic (As)-contaminated aquifer sediments from Datong basin, China have been analyzed to infer the provenance and depositional environment related to As distribution in the aquifer sediments. The As content in the sediments ranged from 2.45 to 27.38 mg/kg with an average value of 9.54 mg/kg, which is comparable to the average value in modern unconsolidated sediments. However, minor variation in As concentration with depth has been observed in the core. There was a significant correlation between Fe, and Al and As, which was attributed to the adsorption or co-precipitation of As onto/with Fe oxides/hydroxides and/or Fe-coated clay minerals. Post-Archean Australian Shale (PAAS)-normalized REEs patterns of sediment samples along the borehole were constant, and the sediments had a notably restricted range of La-N/Yb-N ratios from 0.7 to 1.0. These results suggested that the provenance of the Datong basin remained similar throughout the whole depositional period. The analysis of major geochemical compositions confirmed that all core sediments were from the same sedimentary source and experienced significant sedimentary recycling. The co-variation of As, V/Al, Ni/Al and chemical index of alteration (CIA) values in the sediments along the borehole suggested that As distribution in the sediments was primarily controlled by weathering processes. The calculated CIA values of the sediments along the borehole indicate that a relative strong chemical weathering occurred during the deposition of sediments at depths of similar to 35 to 88 m, which was corresponding to the depth at which high As groundwater was observed at the site. Strong chemical weathering favored the deposition of Fe-bearing minerals including poorly crystalline and crystalline Fe oxide mineral phases and concomitant co-precipitation of As with these minerals in the sediments. Subsequent reductive dissolution of As-bearing poorly crystalline and crystalline Fe oxides would result in the enrichment of As in groundwater. In general, the chemical weathering during the deposition of the sediments governed the co-accumulation of Fe oxides and As in the aquifer sediments. And then, the reductive dissolution of Fe oxides/hydroxides is the mechanism of As enrichment in the groundwater in the Datong basin

Xie, Xianjun↗

DOE OSTI2023

Fracture Intensity Impacts on Reaction Front Propagation and Mineral Weathering in Three‐Dimensional Fractured Media

Abstract Studying reaction front propagation in heterogeneous natural settings is challenging, but numerical simulations can provide insight into the varying spatial and temporal scales of reaction front propagation. Here, the impact of increasing fracture intensity on mineral dissolution rates, and the extent of reaction front propagation is investigated using reactive transport simulations in upscaled discrete fracture network domains with varied fracture intensity. Domain‐averaged dissolution rates vary less than 0.5 log units regardless of the fracture intensity, but the spatial distribution of reactions is controlled by the location and number of dead‐end fractures and the number of connected flowpaths through the domain. Higher fracture intensities lead to more weathering in the domain because of more available mineral for water‐rock interactions. We find that reaction fronts propagate through the primary flowpaths in the first 10,000 years of the simulation for a 10‐m length domain, then propagate into secondary flowpaths and dead‐end fractures between 10,000 and 100,000 years, and finally into the matrix over timescales of hundreds of thousands of years. The domain‐averaged reaction rates decrease through time corresponding to a transition from dissolution in advection‐dominated, fast‐flowing pathways, to dissolution in transport‐limited zones of disconnected fractures and matrix. Matrix dissolution, or dissolution under transport‐limited conditions, is the dominant process at late times in these simulations. The results of these simulations recreate the observed paradox found in nature where highly fractured hillslopes tend to be more weathered but have slower weathering rates, while hillslopes with fewer fractures, are less weathered but have higher dissolution rates.

58 GEOSCIENCES↗

DOE OSTI2024

Enhancing Severe Weather Prediction With Microwave All‐Sky Radiance Assimilation: The 10 August 2020 Midwest Derecho

Abstract In this study, we assimilated microwave (MW) all‐sky radiances from low‐Earth‐orbiting satellites and examined their impact on the analyses and forecasts of weather hazards associated with the 10 August 2020 Midwest derecho. Compared with the baseline that assimilated conventional surface and upper‐air observations and infrared (IR) all‐sky radiances from geostationary satellites, the addition of MW all‐sky radiances improved the analyzed and forecasted convection‐stratiform structures of the derecho. Results show that MW all‐sky radiances provided additional information, compared with IR radiances, on hydrometeors within the storm, leading to improved forecasts out to 2 hr with quantitatively more accurate surface gusts. This is the first study to assimilate MW all‐sky radiances for a severe weather event using a convection‐permitting numerical weather prediction model (our model resembles NOAA's High‐Resolution Rapid Refresh), and the results suggest promising avenues for improving severe weather forecasts worldwide in the future.

Zhang, Yunji↗

DOE OSTI2023

Space Weather in the Popular Media, and the Opportunities the Upcoming Solar Maximum Brings

The media interest/coverage of space weather has been increasing as we approach solar maximum and the private space industry has grown significantly since the last significant solar maximum in 2000–2002. It is not uncommon for space weather media coverage to use hyperbole with frequent references to the infamous “Carrington event.” The implications of associating each of the many upcoming moderate-to-severe storms with the Carrington event are discussed, and we encourage the curbing of hyperbole whenever possible. While there is an excellent but small cohort of space weather researchers actively engaging with the media, we urge more (particularly early-to-mid career) to take advantage of media training resources and to join in. We also call for these efforts to be broadly supported by peers and institutions for the benefit of space weather as a discipline.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Unified 0.25-degree gridded infrastructure-critical extreme weather for the United States from 1979 to 2100

Extreme weather events can severely disrupt critical infrastructure, triggering cascading effects on power, transportation, and essential services. However, standard weather and climate datasets often lack specialized variables necessary for hazard assessments. We present a unified dataset of infrastructure-critical weather and climate variables across the United States at 0.25° resolution, covering daily or sub-daily intervals from 1979 to 2100. The dataset includes temperature, dew point, wind gusts, precipitation partitioned by rain, snow, and freezing rain or ice pellets, lightning, and wildfire metrics. Historical conditions (1979-2023) are synthesized from observations and reanalysis products, while future projections are derived from 14 CMIP6 global climate models (historical, SSP245, and SSP585 experiments). Physically based and data-driven methods are used to estimate variables not directly provided by existing models. By integrating these variables into a single unified dataset, we enable consistent, high-resolution assessments of weather-related infrastructure risks across past and future periods, supporting wide-ranging applications in energy, transportation, water resources, emergency management, and beyond.

Climate and Earth system modelling↗

DOE OSTI2019

A coupled microscopy approach to assess the nano-landscape of weathering

Mineral weathering is a balanced interplay among physical, chemical, and biological processes. Fundamental knowledge gaps exist in characterizing the biogeochemical mechanisms that transform microbe-mineral interfaces at submicron scales, particularly in complex field systems. Our objective was to develop methods targeting the nanoscale by using high-resolution microscopy to assess biological and geochemical drivers of weathering in natural settings. Basalt, granite, and quartz (53–250 µm) were deployed in surface soils (10 cm) of three ecosystems (semiarid, subhumid, humid) for one year. We successfully developed a reference grid method to analyze individual grains using: (1) helium ion microscopy to capture micron to sub-nanometer imagery of mineral-organic interactions; and (2) scanning electron microscopy to quantify elemental distribution on the same surfaces via element mapping and point analyses. Here, we detected locations of biomechanical weathering, secondary mineral precipitation, biofilm formation, and grain coatings across the three contrasting climates. To our knowledge, this is the first time these coupled microscopy techniques were applied in the earth and ecosystem sciences to assess microbe-mineral interfaces and in situ biological contributors to incipient weathering.

58 GEOSCIENCES↗

DOE OSTI2019

Ecosystem-bedrock interaction changes nutrient compartmentalization during early oxidative weathering

Ecosystem-bedrock interactions power the biogeochemical cycles of Earth’s shallow crust, supporting life, stimulating substrate transformation, and spurring evolutionary innovation. While oxidative processes have dominated half of terrestrial history, the relative contribution of the biosphere and its chemical fingerprints on Earth’s developing regolith are still poorly constrained. Here, we report results from a two-year incipient weathering experiment. We found that the mass release and compartmentalization of major elements during weathering of granite, rhyolite, schist and basalt was rock-specific and regulated by ecosystem components. A tight interplay between physiological needs of different biota, mineral dissolution rates, and substrate nutrient availability resulted in intricate elemental distribution patterns. Biota accelerated CO 2 mineralization over abiotic controls as ecosystem complexity increased, and significantly modified the stoichiometry of mobilized elements. Microbial and fungal components inhibited element leaching (23.4% and 7%), while plants increased leaching and biomass retention by 63.4%. All biota left comparable biosignatures in the dissolved weathering products. Nevertheless, the magnitude and allocation of weathered fractions under abiotic and biotic treatments provide quantitative evidence for the role of major biosphere components in the evolution of upper continental crust, presenting critical information for large-scale biogeochemical models and for the search for stable in situ biosignatures beyond Earth.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Predicting weather impacts on corn production in a data-limited region using a transfer learning approach

The stability of food supply and prices may depend more on annual changes in yields from year-to-year variability in weather than on longer-term average changes from changing climatic conditions. However, the absence of high-quality data on crop yields at fine spatial resolutions in many regions of the world makes it challenging to statistically model their response to interannual variability in weather patterns. Therefore, there is a need for empirical methods that can project annual crop yield changes even in limited data regions. Here, we propose a transfer learning algorithm that uses high spatial resolution data from one region to project yields in another region with more limited data. The goal of our work is to understand what data types can be beneficial for transferring learning from a source region to a very different target region with more limited data. We utilize Long Short-Term Memory to develop a transfer learning model that is trained on historical county-level corn yield in the United States and predicts district-level corn yield variations in India. Even using smaller amounts of data in India, simulating a data-scarce region, we achieve an average root mean square error of 0.48 bu acre−1 in predicting interannual yield variations. Using Shapley values to interpret results, we explore the contribution of the different weather parameters to interannual yield variability and find a larger influence of precipitation-related variables. Our study demonstrates the usefulness of this method for transferring models of weather impacts on crop yields trained on a data-rich country to one with more limited data. It suggests the potential of applying the transfer learning model to mitigate the need for extensive raw data globally.

Vishwakarma, Srishti [ORNL] (ORCID:000000031674419↗