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At least 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

Contrasting Patterns of Damage and Recovery in Logged Amazon Forests From Small Footprint LiDAR Data

Tropical forests ecosystems respond dynamically to climate variability and disturbances on time scales of minutes to millennia. To date, our knowledge of disturbance and recovery processes in tropical forests is derived almost exclusively from networks of forest inventory plots. These plots typically sample small areas (less than or equal to 1 ha) in conservation units that are protected from logging and fire. Amazon forests with frequent disturbances from human activity remain under-studied. Ongoing negotiations on REDD+ (Reducing Emissions from Deforestation and Forest Degradation plus enhancing forest carbon stocks) have placed additional emphasis on identifying degraded forests and quantifying changing carbon stocks in both degraded and intact tropical forests. We evaluated patterns of forest disturbance and recovery at four -1000 ha sites in the Brazilian Amazon using small footprint LiDAR data and coincident field measurements. Large area coverage with airborne LiDAR data in 2011-2012 included logged and unmanaged areas in Cotriguacu (Mato Grosso), Fiona do Jamari (Rondonia), and Floresta Estadual do Antimary (Acre), and unmanaged forest within Reserva Ducke (Amazonas). Logging infrastructure (skid trails, log decks, and roads) was identified using LiDAR returns from understory vegetation and validated based on field data. At each logged site, canopy gaps from logging activity and LiDAR metrics of canopy heights were used to quantify differences in forest structure between logged and unlogged areas. Contrasting patterns of harvesting operations and canopy damages at the three logged sites reflect different levels of pre-harvest planning (i.e., informal logging compared to state or national logging concessions), harvest intensity, and site conditions. Finally, we used multi-temporal LiDAR data from two sites, Reserva Ducke (2009, 2012) and Antimary (2010, 2011), to evaluate gap phase dynamics in unmanaged forest areas. The rates and patterns of canopy gap formation at these sites illustrate potential issues for separating logging damages from natural forest disturbances over longer time scales. Multi-temporal airborne LiDAR data and coincident field measurements provide complementary perspectives on disturbance and recovery processes in intact and degraded Amazon forests. Compared to forest inventory plots, the large size of each individual site permitted analyses of landscape-scale processes that would require extremely high investments to study using traditional forest inventory methods.

Morton, D. C.↗
NASA NTRS2012

Dynamics of Aboveground Phytomass of the Circumpolar Arctic Tundra During the Past Three Decades

Numerous studies have evaluated the dynamics of Arctic tundra vegetation throughout the past few decades, using remotely sensed proxies of vegetation, such as the normalized difference vegetation index (NDVI). While extremely useful, these coarse-scale satellite-derived measurements give us minimal information with regard to how these changes are being expressed on the ground, in terms of tundra structure and function. In this analysis, we used a strong regression model between NDVI and aboveground tundra phytomass, developed from extensive field-harvested measurements of vegetation biomass, to estimate the biomass dynamics of the circumpolar Arctic tundra over the period of continuous satellite records (1982-2010). We found that the southernmost tundra subzones (C-E) dominate the increases in biomass, ranging from 20 to 26%, although there was a high degree of heterogeneity across regions, floristic provinces, and vegetation types. The estimated increase in carbon of the aboveground live vegetation of 0.40 Pg C over the past three decades is substantial, although quite small relative to anthropogenic C emissions. However, a 19.8% average increase in aboveground biomass has major implications for nearly all aspects of tundra ecosystems including hydrology, active layer depths, permafrost regimes, wildlife and human use of Arctic landscapes. While spatially extensive on-the-ground measurements of tundra biomass were conducted in the development of this analysis, validation is still impossible without more repeated, long-term monitoring of Arctic tundra biomass in the field.

Arctic tundra↗
NASA NTRS2022

Exceptional Warmth in the Northern Hemisphere during January through March of 2020: The Roles of Unforced and Forced Modes of Atmospheric Variability

Much of northern Eurasia experienced record high temperatures during the first three months of 2020, and the eastern United States experienced a significant heat wave during March. In this study, we show that the above episodes of extraordinary warmth reflect to a large extent the unusual persistence and large amplitude of three well-known modes of atmospheric variability: the Arctic Oscillation (AO), the North Atlantic Oscillation (NAO), and the Pacific–North American (PNA) pattern. We employ a “replay” approach in which simulations with the NASA GEOS AGCM are constrained to remain close to MERRA-2 over specified regions of the globe in order to identify the underlying forcings and regions that acted to maintain these modes well beyond their typical submonthly time scales. We show that an extreme positive AO played a major role in the surface warming over Eurasia, with forcing from the tropical Pacific and Indian Ocean regions acting to maintain its positive phase. Forcing from the tropical Indian Ocean and Atlantic regions produced positive NAO-like responses, contributing to the warming over eastern North America and Europe. The strong heat wave that developed over eastern North America during March was primarily associated with an extreme negative PNA that developed as an instability of the North Pacific jet, with tropical forcing providing support for a prolonged negative phase. A diagnosis of the zonally symmetric circulation shows that the above extratropical surface warming occurred underneath a deep layer of tropospheric warming, driven by stationary eddy-induced changes in the mean meridional circulation.

Northern Hemisphere↗
DOE OSTI2021

Quantifying the impacts of compound extremes on agriculture

Agricultural production and food prices are affected by hydroclimatic extremes. There has been a growing amount of literature measuring the impacts of individual extreme events (heat stress or water stress) on agricultural and human systems. Yet, we lack a comprehensive understanding of the significance and the magnitude of the impacts of compound extremes. This study combines a fine-scale weather product with outputs of a hydrological model to construct functional metrics of individual and compound hydroclimatic extremes for agriculture. Then, a yield response function is estimated with individual and compound metrics, focusing on corn in the United States during the 1981–2015 period. Supported by statistical evidence, the findings suggest that metrics of compound hydroclimatic extremes are better predictors of corn yield variations than metrics of individual extremes. The results also confirm that wet heat is more damaging than dry heat for corn. This study shows the average yield damage from heat stress has been up to four times more severe when combined with water stress.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Climatology of Severe Local Storm Environments and Synoptic-Scale Features over North America in ERA5 Reanalysis and CAM6 Simulation

Severe local storm (SLS) activity is known to occur within specific thermodynamic and kinematic environments. These environments are commonly associated with key synoptic-scale features—including southerly Great Plains low-level jets, drylines, elevated mixed layers, and extratropical cyclones—that link the large-scale climate to SLS environments. This work analyzes spatiotemporal distributions of both extreme values of SLS environmental parameters and synoptic-scale features in the ERA5 reanalysis and in the Community Atmosphere Model, version 6 (CAM6), historical simulation during 1980–2014 over North America. Compared to radiosondes, ERA5 successfully reproduces SLS environments, with strong spatiotemporal correlations and low biases, especially over the Great Plains. Both ERA5 and CAM6 reproduce the climatology of SLS environments over the central United States as well as its strong seasonal and diurnal cycles. ERA5 and CAM6 also reproduce the climatological occurrence of the synoptic-scale features, with the distribution pattern similar to that of SLS environments. Compared to ERA5, CAM6 exhibits a high bias in convective available potential energy over the eastern United States primarily due to a high bias in surface moisture and, to a lesser extent, storm-relative helicity due to enhanced low-level winds. Additionally, composite analysis indicates consistent synoptic anomaly patterns favorable for significant SLS environments over much of the eastern half of the United States in both ERA5 and CAM6, though the pattern differs for the southeastern United States. Overall, our results indicate that both ERA5 and CAM6 are capable of reproducing SLS environments as well as the synoptic-scale features and transient events that generate them.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2021

Intergenerational Inequities in Exposure to Climate Extremes: Young Generations Are Severely Threatened By Climate Change

Under continued global warming, extreme events such as heat waves will continue to rise in frequency, intensity, duration, and spatial extent over the next decades. Younger generations are therefore expected to face more such events across their lifetimes compared with older generations. This raises important issues of solidarity and fairness across generations that have fueled a surge of climate protests led by young people in recent years and that underpin issues of intergenerational equity raised in recent climate litigation. However, the standard scientific paradigm is to assess climate change in discrete time windows or at discrete levels of warming, a “period” approach that inhibits quantification of how much more extreme events a particular generation will experience over its lifetime compared with another. By developing a “cohort” perspective to quantify changes in lifetime exposure to climate extremes and compare across generations (see the first figure), we estimate that children born in 2020 will experience a two- to sevenfold increase in extreme events, particularly heat waves, compared with people born in 1960, under current climate policy pledges. Our results highlight a severe threat to the safety of young generations and call for drastic emission reductions to safeguard their future. Meteorological extremes, hazards, or climate change impacts are mostly studied as they evolve over time under varying emission scenarios and socioeconomic pathways. For example, applying a heat wave indicator (see table S1) to four bias-adjusted global climate models indicates that the land area annually affected by such heat waves will increase from ~15% around 2020 to ~22% by 2100 under a scenario compatible with limiting global warming to 1.5°C, and to ~46% under a scenario in line with current emission reduction pledges (see the first figure). Recent studies extended this approach, studying aspects of climate change as a function of global mean temperature (GMT) increments, highlighting the scenario-independence of several extreme event indicators but remaining, in essence, a comparison of time windows. By contrast, we performed a birth cohort analysis by combining a collection of multimodel extreme event projections with country-scale life expectancy information, gridded population data, and future global temperature trajectories from the Intergovernmental Panel on Climate Change (IPCC) Special Report on Global Warming of 1.5°C (see supplementary materials). By integrating the exposure of an average person in a country or region to extreme events across their lifetime, we encapsulate spatiotemporal changes in climate hazards, population density, cohort size, and life expectancy (see the first figure).

global warming↗
NASA NTRS1997

Deviations from uniform power law scaling in nonstationary time series

A classic problem in physics is the analysis of highly nonstationary time series that typically exhibit long-range correlations. Here we test the hypothesis that the scaling properties of the dynamics of healthy physiological systems are more stable than those of pathological systems by studying beat-to-beat fluctuations in the human heart rate. We develop techniques based on the Fano factor and Allan factor functions, as well as on detrended fluctuation analysis, for quantifying deviations from uniform power-law scaling in nonstationary time series. By analyzing extremely long data sets of up to N = 10(5) beats for 11 healthy subjects, we find that the fluctuations in the heart rate scale approximately uniformly over several temporal orders of magnitude. By contrast, we find that in data sets of comparable length for 14 subjects with heart disease, the fluctuations grow erratically, indicating a loss of scaling stability.

Non-NASA Center↗
NASA NTRS1993

Structural similitude and design of scaled down laminated models

The excellent mechanical properties of laminated composite structures make them prime candidates for wide variety of applications in aerospace, mechanical and other branches of engineering. The enormous design flexibility of advanced composites is obtained at the cost of large number of design parameters. Due to complexity of the systems and lack of complete design based informations, designers tend to be conservative in their design. Furthermore, any new design is extensively evaluated experimentally until it achieves the necessary reliability, performance and safety. However, the experimental evaluation of composite structures are costly and time consuming. Consequently, it is extremely useful if a full-scale structure can be replaced by a similar scaled-down model which is much easier to work with. Furthermore, a dramatic reduction in cost and time can be achieved, if available experimental data of a specific structure can be used to predict the behavior of a group of similar systems. This study investigates problems associated with the design of scaled models. Such study is important since it provides the necessary scaling laws, and the factors which affect the accuracy of the scale models. Similitude theory is employed to develop the necessary similarity conditions (scaling laws). Scaling laws provide relationship between a full-scale structure and its scale model, and can be used to extrapolate the experimental data of a small, inexpensive, and testable model into design information for a large prototype. Due to large number of design parameters, the identification of the principal scaling laws by conventional method (dimensional analysis) is tedious. Similitude theory based on governing equations of the structural system is more direct and simpler in execution. The difficulty of making completely similar scale models often leads to accept certain type of distortion from exact duplication of the prototype (partial similarity). Both complete and partial similarity are discussed. The procedure consists of systematically observing the effect of each parameter and corresponding scaling laws. Then acceptable intervals and limitations for these parameters and scaling laws are discussed. In each case, a set of valid scaling factors and corresponding response scaling laws that accurately predict the response of prototypes from experimental models is introduced. The examples used include rectangular laminated plates under destabilizing loads, applied individually, vibrational characteristics of same plates, as well as cylindrical bending of beam-plates.

Simitses, G. J.↗
NASA NTRS2003

Pseudo Linear Gyro Calibration

Previous high fidelity onboard attitude algorithms estimated only the spacecraft attitude and gyro bias. The desire to promote spacecraft and ground autonomy and improvements in onboard computing power has spurred development of more sophisticated calibration algorithms. Namely, there is a desire to provide for sensor calibration through calibration parameter estimation onboard the spacecraft as well as autonomous estimation on the ground. Gyro calibration is a particularly challenging area of research. There are a variety of gyro devices available for any prospective mission ranging from inexpensive low fidelity gyros with potentially unstable scale factors to much more expensive extremely stable high fidelity units. Much research has been devoted to designing dedicated estimators such as particular Extended Kalman Filter (EKF) algorithms or Square Root Information Filters. This paper builds upon previous attitude, rate, and specialized gyro parameter estimation work performed with Pseudo Linear Kalman Filter (PSELIKA). The PSELIKA advantage is the use of the standard linear Kalman Filter algorithm. A PSELIKA algorithm for an orthogonal gyro set which includes estimates of attitude, rate, gyro misalignments, gyro scale factors, and gyro bias is developed and tested using simulated and flight data. The measurements PSELIKA uses include gyro and quaternion tracker data.

Harman, Richard↗
DOE OSTI2026

Data, model inputs, and analysis scripts associated with a manuscript on stream intermittency controls across spatial scales in Pacific Northwest watersheds

NOTE: The manuscript associated with this data package is currently in review. The data may be revised based on reviewer feedback. Upon manuscript acceptance, this data package will be updated with the final dataset and additional metadata. This data package is associated with the manuscript "Hydroclimatic Memory and Watershed Template Shape Stream Intermittency: Multi-scale Attribution Using Process-based Simulation and Explainable ML" by Niroula et al. (2026), submitted to Water Resources Research (WRR). The study investigates the dominant controls on stream intermittency across local, reach, and watershed scales using a coupled process-based simulation and explainable machine-learning framework. Long-term daily simulations from the Advanced Terrestrial Simulator (ATS) were used to generate wetness states and ponded-depth responses over river-corridor cells. These ATS outputs were then aggregated across scales and used to train XGBoost (eXtreme Gradient Boosting) models. SHAP (SHapley Additive exPlanations) was applied to quantify the relative importance of hydroclimatic forcings, watershed template attributes, and antecedent-memory effects in shaping intermittency behavior. The analysis is carried out for three contrasting Pacific Northwest watersheds: Oak Creek (OCW), American River Watershed (ARW), and H.J. Andrews (HJA). Across these testbeds, the package contains ATS-ready watershed inputs, ATS run configuration and selected output files, model-evaluation data products, intermittency-analysis datasets, machine-learning target-feature tables, SHAP outputs, and notebooks used to organize, analyze, and visualize results. At a high level, the package documents a workflow in which ATS provides the physically based simulation backbone and explainable machine learning is used as a post-processing attribution tool. The contents are intended to support interpretation of the manuscript figures and results, provide context for how intermittency metrics were generated at multiple scales, and preserve the key artifacts needed to understand and reuse the analysis workflow. The package contains a high-level directory summary file (`summary.txt`) and four main content folders (1) `evaluation_plots` contains evaluation figures and supporting evaluation datasets; (2) `intermittency_plots` contains intermittency-focused analysis notebook and prepared datasets; (3) `ml-training-and-shap_values_plots` contains ML training inputs, SHAP outputs, and figure-generation notebooks; and (4) `watershed_mesh_and_ats_input` contains ATS model setup materials, forcing inputs, geometry, and selected run files. More specifically, the `evaluation_plots` folder contains the notebook used for ATS evaluation plotting and site-specific evaluation datasets. These include evapotranspiration and water-balance products for three watersheds, as well as an Oak Creek field-measurement discharge file. The `intermittency_plots` folder contains the notebook used for intermittency analysis and the prepared datasets used to analyze intermittent and non-intermittent wetness behavior across the study watersheds. The `ml-training-and-shap_values_plots` folder contains notebooks and outputs for the machine-learning and explainability workflow. This includes the main XGBoost and SHAP notebook(s), a beeswarm plotting notebook, target-feature tables for machine-learning training, SHAP summary tables, and per-sample SHAP value archives. The `watershed_mesh_and_ats_input` folder contains ATS-related watershed inputs and supporting materials. This includes mesh and shape products, ATS-readable LAI and meteorological forcing inputs, selected ATS spinup and transient-run files, and a watershed workflow example notebook. Subdirectories are organized by watershed where applicable.All files are .cpg (codepage files), .csv (comma-separated values), .dbf (database files), .exo (Exodus mesh format), .h5 (HDF5 format), .ipynb (Jupyter notebooks), .pkl (Python pickle), .prj (projection files), .sh (shell scripts), .shp (shapefile geometry), .shx (shapefile index), .txt (text files), or .xml (markup data).

Advanced Terrestrial Simulator↗
DOE OSTI2022

Radio fossils, relics, and haloes in Abell 3266: cluster archaeology with ASKAP-EMU and the ATCA

ABSTRACT Abell 3266 is a massive and complex merging galaxy cluster that exhibits significant substructure. We present new, highly sensitive radio continuum observations of Abell 3266 performed with the Australian Square Kilometre Array Pathfinder (0.8–1.1 GHz) and the Australia Telescope Compact Array (1.1–3.1 GHz). These deep observations provide new insights into recently reported diffuse non-thermal phenomena associated with the intracluster medium, including a ‘wrong-way’ relic, a fossil plasma source, and an as-yet unclassified central diffuse ridge, which we reveal comprises the brightest part of a large-scale radio halo detected here for the first time. The ‘wrong-way’ relic is highly atypical of its kind: it exhibits many classical signatures of a shock-related radio relic, while at the same time exhibiting strong spectral steepening. While radio relics are generally consistent with a quasi-stationary shock scenario, the ‘wrong-way’ relic is not. We study the spectral properties of the fossil plasma source; it exhibits an ultrasteep and highly curved radio spectrum, indicating an extremely aged electron population. The larger scale radio halo fills much of the cluster centre, and presents a strong connection between the thermal and non-thermal components of the intracluster medium, along with evidence of substructure. Whether the central diffuse ridge is simply a brighter component of the halo, or a mini-halo, remains an open question. Finally, we study the morphological and spectral properties of the multiple complex radio galaxies in this cluster in unprecedented detail, tracing their evolutionary history.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2000

Gravitational Effects on Flow Instability and Transition in Low Density Jets

Recent experiments have shown that low-density gas jets injected into a high-density ambient gas undergo an instability mode, leading to highly-periodic oscillations in the flow-field for certain conditions. The transition from laminar to turbulent flow in these jets is abrupt, without the gradual change in scales. Even the fine scale turbulent structure repeats itself with extreme regularity from cycle to cycle. Similar observations were obtained in buoyancy-dominated and momentum-dominated jets characterized by the Richardson numbers, Ri = [gD(rho(sub a)-rho(sub j))/rho(sub j)U(sub j)(exp 2) ] where g is the gravitational acceleration, D is the jet diameter, rho(sub a) and rho(sub a) are, respectively, the free-stream and jet densities, and U(sub j) is the mean jet exit velocity. At high Richardson numbers, the instability is presumably caused by buoyancy since the flow-oscillation frequency (f) or the Strouhal number, St = [fD/U(sub j)] scales with Ri. In momentum-dominated jets, however, the Strouhal number of the oscillating flow is relatively independent of the Ri. In this case, a local absolute instability is predicted in the potential core of low-density jets with S [= rho(sub j)/rho(sub a)] < 0.7, which agrees qualitatively with experiments. Although the instability in gas jets of high Richardson numbers is attributed to buoyancy, direct physical evidence has not been acquired in experiments. If the instability is indeed caused by buoyancy, the near-field flow structure of the jet will change significantly when the buoyancy is removed, for example, in the microgravity environment. Thus, quantitative data on the spatial and temporal evolutions of the instability, length and time scale of the oscillating mode and its effects on the mean flow and breakdown of the potential core are needed in normal and microgravity to delineate gravitational effects in buoyant jets. In momentum dominated low-density jets, the instability is speculated to originate in the potential core. However, experiments have not succeeded in identifying the direct physical cause of the instability. For example, the theory predicts an oscillating mode for S<0.62 in the limit of zero momentum thickness, which contradicts with the experimental findings of Kyle and Sreenivasan. The analyses of momentum-dominated jets neglect buoyancy effects because of the small Richardson number. Although this assumption is appropriate in the potential core, the gravitational effects are important in the annular region surrounding the jet, where the density and velocity gradients are large. This reasoning provides basis for the hypothesis that the instability in low Richardosn number jets studied by Kyle and Sreenivasan and Monkewitz et al. is caused by buoyancy. The striking similarity in characteristics of the instability and virtually the identical conclusions reached by Subbarao and Cantwell in buoyant (Ri>0.5) helium jets on one hand and by Kyle and Sreenivasan in momentum-dominated (Ri<1x10(exp -3)) helium jets on the other support this hypothesis. However, quantitative experiments in normal and microgravity are necessary to obtain direct physical evidence of buoyancy effects on the flow instability and structure of momentum-dominated low-density jets. The primary objective of this new research project is to quantify how buoyancy affects the flow instability and structure in the near field of low-density jets. The flow will be described by the spatial and temporal evolutions of the instability, length and time scales of the oscillating mode, and the mean and fluctuating concentration fields. To meet this objective, concentration measurements will be obtained across the whole field using quantitative Rainbow Schlieren Deflectometry, providing spatial resolution of 0.1mm and temporal resolution of 0.017s to 1ms. The experimental effort will be supplemented with linear stability analysis of low-density jets by considering buoyancy. The first objective of this research is to investigate the effects of gravity on the flow instability and structure of low-density jets. The flow instability in these jets has been attributed to buoyancy. By removing buoyancy in our experiments, we seek to obtain the direct physical evidence of the instability mechanism. In the absence of the instability, the flow structure will undergo a significant change. We seek to quantify these changes by mapping the flow field (in terms of the concentration profiles) of these jets at non-buoyant conditions. Such information is presently lacking in the existing literature. The second objective of this research is to determine if the instability in momentum-driven, low-density jets is caused by buoyancy. At these conditions, the buoyancy effects are commonly ignored because of the small Richardson based on global parameters. By eliminating buoyancy in our experiments, globally as well as locally, we seek to examine the possibility that the instability mechanism in self-excited, buoyant or momentum-driven jets is the same. To meet this objective, we would quantify the jet flow in normal and microgravity, while systematically decreasing the Richardson number from buoyancy-driven to momentum driven flow regime. The third objective of this research is to perform a linear stability analysis of low-density gas jets by including the gravitational effects. The flow oscillations in these jets are attributed to an absolute instability, whereby the disturbance grows exponentially at the site to ultimately contaminate the entire flow field. We seek to study the characteristics of both convective and absolute instabilities and demarcate the boundary between them.

Agrawal A. K.↗
DOE OSTI2021

Application of remote sensing precipitation data and the $\mathrm{CONNECT}$ algorithm to investigate spatiotemporal variations of heavy precipitation: Case study of major floods across Iran (Spring 2019)

In recent years, the number of floods following unprecedented rainfall events have increased in Iran during early spring (March 21st to April 20th, referred to in Iran as the month of “Farvadin”). While numerous studies have addressed changes in climate extremes and precipitation trends at different temporal scales from daily to annual across the country, analyses of short-duration and heavy precipitation, especially during recent years, are rarely considered. Furthermore, most studies investigate the variations in extremes and total precipitation using a limited number of synoptic weather stations across Iran. Here this study assesses the variations in heavy precipitation (precipitation with intensities greater than or equal to 3 mm/3 h) at 0.04° spatial and 3-hourly temporal resolution during the month of Farvardin. In addition, the effect of atmospheric river conditions over Iran and their possible link to intensifying heavy precipitation is explored. For this purpose, the CONNected-objECT (CONNECT) algorithm is applied on a precipitation dataset, Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS), and an Integrated Water Vapor Transport (IVT) dataset from the NASA Modern-Era Retrospective Analysis for Research and Applications Version-2 (MERRA-2). The results suggest that the increase in the number of floods in recent years is related to the increase in the intensity and volume of heavy precipitation events, although the frequency and duration of heavy precipitation events have not changed significantly. Furthermore, the results show that atmospheric river conditions over the country are present during the same window as each year’s most extreme events. It is found that 8 out of 13 of the largest ARs over Iran come from moisture plumes with pathways over the African and Red Sea.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2001

Chemical Engineering in Space

The aerospace industry has long been perceived as the domain of both physicists and mechanical engineers. This perception has endured even though the primary method of providing the thrust necessary to launch a rocket into space is chemical in nature. The chemical engineering and chemistry personnel behind the systems that provide access to space have labored in the shadows of the physicists and mechanical engineers. As exploration into the cosmos moves farther away from Earth, there is a very distinct need for new chemical processes to help provide the means for advanced space exploration. The state of the art in launch systems uses chemical propulsion systems, primarily liquid hydrogen and liquid oxygen, to provide the energy necessary to achieve orbit. As we move away from Earth, there are additional options for propulsion. Unfortunately, few of these options can compare to the speed or ease of use provided by the chemical propulsion agents. It is with great care and significant cost that gaseous compounds such as hydrogen and oxygen are liquefied and become dense enough to use for rocket fuel. These low-temperature liquids fall within a specialty area known as cryogenics. Cryogenics, the science and art of producing cold operating conditions for use on Earth, in orbit, or on some other nonterrestrial body, has become increasingly important to our ability to travel within our solar system. The production of cryogenic fuels and the long-term storage of these fluids are necessary for travel. As our explorations move farther away from Earth, we need to address how to produce the necessary fuels to make a round-trip. The cost and the size of these expeditions are extreme at best. If we take everything necessary for our survival for the round-trip, we invalidate any chance of travel in the near future. As with the early explorers on Earth, we need to harvest much of our energy and our life support from the celestial bodies. The in situ production of these energy sources is paramount to success. We are currently working on several processes to produce the propellants that would allow us to visit and explore the surface of Mars. The capabilities currently at our disposal for launching and delivering equipment to another planet or satellite dictate that the size and scale of any hardware must be extremely small. The miniaturization of the processes needed to prepare the in situ propellants and life support commodities is a real challenge. Chemical engineers are faced with the prospect of reproducing an entire production facility in miniature so the complex can be lifted into space and delivered to our destination. Another area that does not normally concern chemical engineers is the extreme physical aspects payloads are subjected to with the launch of a spacecraft. Extreme accelerations followed by the sudden loss of nearly all gravitational forces are well outside normal equipment design conditions. If the equipment cannot survive the overall trip, then it obviously will not be able to yield the needed products upon arrival. These launch constraints must be taken into account. Finally, we must consider both the effectiveness and efficiencies of the processes. A facility located on the Moon or Mars will not have an unlimited supply of power or other ancillary utilities. For a Mars expedition, the available electric power is severely limited. The design of both the processes and the equipment must be considered. With these constraints in mind, only the most efficient designs will be viable. Cryogenics, in situ resource utilization, miniaturization, launchability, and power/process efficiencies are only a few of the areas that chemical engineers provide support and expertise for the exploration of space.

Lobmeyer, Dennis A.↗
DOE OSTI2025

An atomic cluster expansion (ACE) potential for water under extreme conditions

We present a machine learning interatomic potential for water designed to capture its complex multiphase behavior, including both molecular and superionic ice phases. The potential is based on the atomic cluster expansion (ACE) formulation and has been parameterized to enable high-fidelity molecular dynamics simulations of water under extreme conditions, for pressures up to 100 GPa and for temperatures between 500 and 6000 K. A diverse range of configurations was generated through ab initio molecular dynamics (AI-MD) simulations, covering insulating and superionic ice phases, liquid water, and dissociated plasma phase. We demonstrate that the H 2 O ACE potential accurately reproduces experimental and DFT predicted isotherms and Hugoniots. Crucially, the potential is able to capture the intricate phase behavior of water, including the transition from molecular fluid to the appropriate solid ice phases, and the superionic ice phases. This work provides a robust interatomic potential that can be used for large-scale, accurate simulations of water under extreme thermodynamic conditions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Accurate and efficient parameterization of an atomic cluster expansion (ACE) potential for ammonia under extreme conditions

We present a machine learning interatomic potential for ammonia designed to capture its complex multiphase behavior, including both molecular and superionic phases. The potential is based on the atomic cluster expansion (ACE) formulation and has been parameterized to facilitate high-fidelity molecular dynamics simulations of ammonia under extreme conditions, for pressures up to 100 GPa and for temperatures above 500 K and up to 6000 K. A diverse range of configurations was generated through high-quality ab initio molecular dynamics simulations, covering insulating and superionic ice phases, liquid ammonia, molecular nitrogen (N 2 ) and hydrogen (H 2 ), and metastable compounds that form upon dissociation, including $NH^{+}_{4}$, $H^{+}_{3}$, N 2 H 4 , and N 3 H. We demonstrate that the ammonia ACE potential accurately reproduces experimental and density functional theory predicted isotherms and Hugoniots. Crucially, the potential is able to capture the intricate phase behavior of ammonia, including the transition from insulating molecular fluid to the superionic phase. This work provides a robust interatomic potential that can be used for large-scale, accurate simulations of ammonia under extreme thermodynamic conditions, offering a powerful tool for investigating its behavior in various phases and applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗