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All sourcesNASA NTRSDOE OSTI
NASA NTRS2023

Using Virtual Reality to Envision Deployment of Spacesuit-Compatible Augmented Reality Displays for Lunar Surface Operations

The National Aeronautics and Space Administration (NASA) will soon land crew on the lunar surface to establish a sustainable presence and develop operational concepts for future long-duration missions. New technologies will be necessary to extend planning and execution capabilities for lunar surface activities. The Joint Augmented Reality Visual Informatics System (Joint AR) at NASA Johnson Space Center (JSC) is one such technology. Joint AR is a suit-mounted augmented reality (AR) display and compute system which facilitates unprecedented information exchange and data visualization capabilities between mission support operators and suited crew. This paper describes challenges associated with developing an AR technology for an envisioned work domain by applying a sociotechnical lens to the iterative testing and development of novel AR technology through virtual reality (VR). A foundational VR testbed was established, providing a high-fidelity approximation of the lunar surface and enabling testing of envisioned AR system features in parallel with real world product development. Using this environment, a series of human-in-the-loop experiments were conducted using VR to deploy a notional AR system supporting use cases envisioned for lunar exploration extravehicular activity (xEVA). Our findings indicate VR is a powerful and immersive tool for testing capabilities which extend beyond the limitations of current AR technology. Our VR testbed enables early testing of proposed system features, advancing identification of high-value features and driving present-day development of Joint AR. Future work directions are discussed, including lessons learned and a roadmap for an iterative research and development approach applying VR (among other testbeds) to accelerate Joint AR system maturation.

Augmented reality↗
DOE OSTI2026

Generalizing synthetic data-trained acoustic predictive models to real-world measurements

Acoustic Resonance Spectroscopy (ARS) is highly sensitive to structural properties such as material, geometry, and environmental conditions; as a consequence, it can noninvasively measure internal properties that are unobservable by most other methods. Because of its sensing capabilities and low implementation cost and complexity, ARS has potential as a paradigm shift in noninvasive sensing, characterization, and monitoring applications. However, extracting specific properties from ARS measurements, comprising the vibration spectrum of a test object, is challenging due to the sensitivity of the spectra to other structural changes not being measured, e.g. manufacturing tolerances, component coupling, environmental variation, etc. Neural Networks are promising tools for identifying trends in ARS measurements, but their training typically requires large datasets, which are often impractical to obtain for real-world systems. Synthetic data can be simulated efficiently, but discrepancies between synthetic and real-world data frequently lead to poor generalization when testing on the real-world data. We propose a novel ARS model training framework that enables networks trained exclusively on synthetic ARS data to generalize effectively to real-world measurements. Our approach leverages the Correlation Alignment (CORAL) technique to enforce the extraction of features common to both synthetic and real-world domains. As a case study, we demonstrate noninvasive ARS-based pressure measurements in sealed systems. Finite element method (FEM) simulations were used to generate synthetic training data across diverse vessel configurations and pressure conditions, and model performance was then tested on real-world measurements. We demonstrate that robust machine learning models for ARS can be developed without large real-world datasets, significantly broadening the applicability of ARS for noninvasive sensing. Moreover, the approach is extensible to other sensing modalities where synthetic data are abundant but real-world data are limited.

36 MATERIALS SCIENCE↗
DOE OSTI2020

The Shifting Scales of Western U.S. Landfalling Atmospheric Rivers Under Climate Change

Atmospheric rivers (ARs) can be a boon and bane to water resource managers as they have the ability to replenish water reserves, but they can also generate million-to-billion-dollar flood damages. To investigate how anthropogenic climate change may influence AR characteristics in the coastal western United States by end century, we employ a suite of novel tools such as variable resolution in the Community Earth System Model (VR-CESM), the TempestExtremes AR detection algorithm, and the Ralph, Rutz, et al. (2019, https://doi.org/10.1175/BAMS-D-18-0023.1) AR category scale.We show that end-century ARs primarily shift from being “mostly or primarily beneficial” to “mostly or primarily hazardous” with a concomitant sharpening and intensification of winter season precipitation totals. Changes in precipitation totals are due to a significant increase in AR (+260%) rather than non-AR (+7%) precipitation, largely through increases in the most intense category of AR events and a decrease in the interval between landfalling ARs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Atmospheric Rivers in the Eastern and Midwestern United States Associated With Baroclinic Waves

Atmospheric rivers (ARs) significantly impact the hydrological cycle and associated extremes in western continental regions. Recent studies suggest ARs also influence water resources and extremes in continental interiors. AR detection tools indicate that AR conditions are relatively frequent in areas east of the Rocky Mountains. The origin of these ARs, whether from synoptic-scale waves or mesoscale processes, is unclear. This study uses meteorological composite maps and transects of AR conditions during the four seasons. The analysis reveals that ARs east of the Rockies are associated with long-wave, baroclinic Rossby waves. This result demonstrates that eastern North American ARs are dynamically similar to their western coastal counterparts, though mechanisms for vertical moisture flux differ between the two. These findings provide a foundation for understanding future climate change and ARs in this region and offer new methods for evaluating climate model simulations.

58 GEOSCIENCES↗
DOE OSTI2023

Structural basis of agonist specificity of α 1A -adrenergic receptor

α 1 -adrenergic receptors (α 1 -ARs) play critical roles in the cardiovascular and nervous systems where they regulate blood pressure, cognition, and metabolism. However, the lack of specific agonists for all α 1 subtypes has limited our understanding of the physiological roles of different α 1 -AR subtypes, and led to the stagnancy in agonist-based drug development for these receptors. Here we report cryo-EM structures of α 1A -AR in complex with heterotrimeric G-proteins and either the endogenous common agonist epinephrine or the α 1A -AR-specific synthetic agonist A61603. These structures provide molecular insights into the mechanisms underlying the discrimination between α 1A -AR and α 1B -AR by A61603. Guided by the structures and corresponding molecular dynamics simulations, we engineer α 1A -AR mutants that are not responsive to A61603, and α 1B -AR mutants that can be potently activated by A61603. Together, these findings advance our understanding of the agonist specificity for α 1 -ARs at the molecular level, opening the possibility of rational design of subtype-specific agonists.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Intelligent Process Visualization through Nuclear Operation Process Modeling, Reasoning, and Object Detection from Field Videos (Final Report)

This report is a deliverable for the “Final Report” task of DOE NEET Project 19-16790, "Context-Aware Safety Information Display for Nuclear Field Workers." This project's overall goal is to test the hypothesis that integrating computer vision and process reasoning methods will enable proactive visualization of the safe operation and maintenance processes of Nuclear Power Plants (NPP) for field workers. Augmented Reality (AR) glasses adopting such proactive safety information visualization techniques can significantly increase personnel safety and reduce the NPP’s operating costs. The current practice of monitoring NPPs requires workers to switch between digital models, data, and physical workspaces in identifying relevant but potentially occluded objects and in assessing the risks of operation and maintenance processes. On the other hand, frequently changed field conditions require field workers to report to supervisors for real-time guidance. Such guidance is essential to ensure that changing conditions will not invalidate or endanger the work order and other ongoing processes that may jeopardize NPP operations. Additionally, incorrect recognition of equipment objects can result in communication errors and safety problems. AR techniques can assist engineers in viewing the physical workspaces with objects labeled with detailed operation procedures and safety reminders during field operations. The project team developed an “Intelligent Context-Aware Safety Information Display” (ICAD) for supporting Nuclear Power Plant (NPP) field workers in achieving safe and efficient execution of a series of operational tasks in uncertain and changing workspaces of an NPP. Before designing the ICAD-AR prototype, the project team synthesized NPP operational knowledge models through literature review studies, surveys, interviews with domain experts, and knowledge modeling. The project team conducted an extensive study of the operational procedures of various NPPs, and digital technologies that can support the safe and efficient execution of those procedures in different NPP operational contexts. This literature review helped the project team conduct surveys and interviews with nuclear engineers and field workers to identify three categories of information. The NPP knowledge modeling efforts reveal that the three categories of information identified have different levels of importance in a typical procedure of carrying out a series of tasks to achieve a specific NPP operation goal (e.g., shutdown, mode changes). These three categories of information include 1) Workspace dynamics – the changing spatial arrangements of workspaces, tools, protection equipment, and supporting materials, 2) Workflow prognostics – the dynamic dependencies between different parts of an NPP that functionally support and influence each other in terms of safety and efficiency, and 3) Hazards – objects and spaces that contain hazardous materials or physical conditions that can pose risks to workers or mechanical systems. The project team has profiled the importance levels of these categories of information into a knowledge model. This knowledge model specifies what types of information are more critical for a given task in a given workspace so that computers can automatically identify critical objects and sensors in a scene for delivering context-ware safety information to field workers through AR devices. Significant research development of this project results in technical research outcomes and a prototyping system that illustrates the technical feasibility of establishing an ICAD-AR system supporting the proactive safety information display for nuclear field workers. This final report summarizes the project team’s technological achievements in the past three years. Overall, the project team completed the development and integration of five techniques into a prototype ICAD Augmented Reality (ICAD-AR) system and demonstrated the developed system’s real-time execution in a mechanical room. The project team completed the analysis of using this prototype in other types of workspaces based on 3D image data and digital design models collected from two additional workspaces (a water treatment plant and a flow loop training facility). The integrated techniques include 1) Natural Language Processing (NLP) algorithms supporting the generation and updates of nuclear fieldwork process models based on text analysis of work packages and operation manuals; 2) sensor log analysis for predicting control actions in given sensor reading contexts; 3) computer vision algorithms for automatic localization and navigation of workers; 4) object detection algorithms for identifying task-related objects and correlated sensors for safety checking; 5) AR technique as a platform for supporting the integration. The testing results of these five techniques have shown that 1) the sensor log analysis model can predict the next control action with an accuracy of 0.883; 2) the trained natural language processing model can extract more than 80% of the critical information from paper-based procedures (PBPs); 3) the navigation algorithm with the integration of Visual Inertial Odometry (VIO) and Non-Recursive Bayesian Filter methods make operator’s trajectory estimation resilient to drift error; 4) the computer vision algorithm can detect task-specific and safety-critical objects with an average accuracy of 95.3%. The project team used work procedures collected from a flow loop training facility and two datasets collected from two mechanical rooms simulating the workspaces of NPPs to demonstrate the technical capabilities of the developed ICAD-AR prototype. The demonstration validated the technical feasibility of establishing the ICAD-AR system for nuclear field workers and identified the challenges in 1) automatic text analysis of work packages; 2) use of limited samples of sensor logs for predicting the proper timings of control actions; 3) reliably tracking workers and their task progress in mechanical rooms with many similar objects.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

A new metrics framework for quantifying and intercomparing atmospheric rivers in observations, reanalyses, and climate models

We present a new atmospheric river (AR) analysis and benchmarking tool, namely Atmospheric River Metrics Package (ARMP). It includes a suite of new AR metrics that are designed for quick analysis of AR characteristics via statistics in gridded climate datasets such as model output and reanalysis. This package can be used for climate model evaluation in comparison with reanalysis and observational products. Integrated metrics such as mean bias and spatial pattern correlation are efficient for diagnosing systematic AR biases in climate models. For example, the package identifies the fact that, in CMIP5 and CMIP6 (Coupled Model Intercomparison Project Phases 5 and 6) models, AR tracks in the South Atlantic are positioned farther poleward compared to ERA5 reanalysis, while in the South Pacific, tracks are generally biased towards the Equator. For the landfalling AR peak season, we find that most climate models simulate a completely opposite seasonal cycle over western Africa. This tool can also be used for identifying and characterizing structural differences among different AR detectors (ARDTs). For example, ARs detected with the Mundhenk algorithm exhibit systematically larger size, width, and length compared to the TempestExtremes (TE) method. The AR metrics developed from this work can be routinely applied for model benchmarking and during the development cycle to trace performance evolution across model versions or generations and set objective targets for the improvement of models. They can also be used by operational centers to perform near-real-time climate and extreme event impact assessments as part of their forecast cycle.

58 GEOSCIENCES↗
DOE OSTI2023

Climatology and surface impacts of atmospheric rivers on West Antarctica

Abstract. Atmospheric rivers (ARs) transport large amounts of moisture from the mid- to high-latitudes and they are a primary driver of the most extreme snowfall events, along with surface melting, in Antarctica. In this study, we characterize the climatology and surface impacts of ARs on West Antarctica, focusing on the Amundsen Sea Embayment and Marie Byrd Land. First, we develop a climatology of ARs in this region, using an Antarctic-specific AR detection tool combined with the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2) and the European Centre for Medium-Range Weather Forecasts (ECMWF) Reanalysis v5 (ERA5) atmospheric reanalyses. We find that while ARs are infrequent (occurring 3 % of the time), they cause intense precipitation in short periods of time and account for 11 % of the annual surface accumulation. They are driven by the coupling of a blocking high over the Antarctic Peninsula with a low-pressure system known as the Amundsen Sea Low. Next, we use observations from automatic weather stations on Thwaites Eastern Ice Shelf with the firn model SNOWPACK and interferometric reflectometry (IR) to examine a case study of three ARs that made landfall in rapid succession from 2 to 8 February 2020, known as an AR family event. While accumulation dominates the surface impacts of the event on Thwaites Eastern Ice Shelf (> 100 kg m−2 or millimeters water equivalent), we find small amounts of surface melt as well (< 5 kg m−2). The results presented here enable us to quantify the past impacts of ARs on West Antarctica's surface mass balance (SMB) and characterize their interannual variability and trends, enabling a better assessment of future AR-driven changes in the SMB.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Augmentation of progestin signaling rescues testis organization and spermatogenesis in zebrafish with the depletion of androgen signaling

Disruption of androgen signaling is known to cause testicular malformation and defective spermatogenesis in zebrafish. However, knockout of cyp17a1 , a key enzyme responsible for the androgen synthesis, in ar -/- male zebrafish paradoxically causes testicular hypertrophy and enhanced spermatogenesis. Because Cyp17a1 plays key roles in hydroxylation of pregnenolone and progesterone (P4), and converts 17α-hydroxypregnenolone to dehydroepiandrosterone and 17α-hydroxyprogesterone to androstenedione, we hypothesize that the unexpected phenotype in cyp17a1 -/-; androgen receptor ( ar )-/- zebrafish may be mediated through an augmentation of progestin/nuclear progestin receptor (nPgr) signaling. In support of this hypothesis, we show that knockout of cyp17a1 leads to accumulation of 17α,20β-dihydroxy-4-pregnen-3-one (DHP) and P4. Further, administration of progestin, a synthetic DHP mimetic, is sufficient to rescue testicular development and spermatogenesis in ar -/- zebrafish, whereas knockout of npgr abolishes the rescue effect of cyp17a1 -/- in the cyp17a1 -/-; ar -/- double mutant. Analyses of the transcriptomes among the mutants with defective testicular organization and spermatogenesis ( ar -/-, ar -/-; npgr -/- and cyp17a -/-; ar -/-; npgr -/-), those with normal phenotype (control and cyp17a1 -/-), and rescued phenotype ( cyp17a1 -/-; ar -/-) reveal a common link between a downregulated expression of insl3 and its related downstream genes in cyp17a -/-; ar -/-; npgr -/- zebrafish. Taken together, our data suggest that genetic or pharmacological augmentation of the progestin/nPgr pathway is sufficient to restore testis organization and spermatogenesis in zebrafish with the depletion of androgen signaling.

Zhai, Gang↗
NASA NTRS2002

Quantitative analysis of aortic regurgitation: real-time 3-dimensional and 2-dimensional color Doppler echocardiographic method--a clinical and a chronic animal study

BACKGROUND: For evaluating patients with aortic regurgitation (AR), regurgitant volumes, left ventricular (LV) stroke volumes (SV), and absolute LV volumes are valuable indices. AIM: The aim of this study was to validate the combination of real-time 3-dimensional echocardiography (3DE) and semiautomated digital color Doppler cardiac flow measurement (ACM) for quantifying absolute LV volumes, LVSV, and AR volumes using an animal model of chronic AR and to investigate its clinical applicability. METHODS: In 8 sheep, a total of 26 hemodynamic states were obtained pharmacologically 20 weeks after the aortic valve noncoronary (n = 4) or right coronary (n = 4) leaflet was incised to produce AR. Reference standard LVSV and AR volume were determined using the electromagnetic flow method (EM). Simultaneous epicardial real-time 3DE studies were performed to obtain LV end-diastolic volumes (LVEDV), end-systolic volumes (LVESV), and LVSV by subtracting LVESV from LVEDV. Simultaneous ACM was performed to obtain LVSV and transmitral flows; AR volume was calculated by subtracting transmitral flow volume from LVSV. In a total of 19 patients with AR, real-time 3DE and ACM were used to obtain LVSVs and these were compared with each other. RESULTS: A strong relationship was found between LVSV derived from EM and those from the real-time 3DE (r = 0.93, P <.001, mean difference (3D - EM) = -1.0 +/- 9.8 mL). A good relationship between LVSV and AR volumes derived from EM and those by ACM was found (r = 0.88, P <.001). A good relationship between LVSV derived from real-time 3DE and that from ACM was observed (r = 0.73, P <.01, mean difference = 2.5 +/- 7.9 mL). In patients, a good relationship between LVSV obtained by real-time 3DE and ACM was found (r = 0.90, P <.001, mean difference = 0.6 +/- 9.8 mL). CONCLUSION: The combination of ACM and real-time 3DE for quantifying LV volumes, LVSV, and AR volumes was validated by the chronic animal study and was shown to be clinically applicable.

Validation Studies↗
NASA NTRS2008

Static and Impulsive Models of Solar Active Regions

The physical modeling of active regions (ARs) and of the global coronal is receiving increasing interest lately. Recent attempts to model ARs using static equilibrium models were quite successful in reproducing AR images of hot soft X-ray (SXR) loops. They however failed to predict the bright EUV warm loops permeating ARs: the synthetic images were dominated by intense footpoint emission. We demonstrate that this failure is due to the very weak dependence of loop temperature on loop length which cannot simultaneously account for both hot and warm loops in the same AR. We then consider time-dependent AR models based on nanoflare heating. We demonstrate that such models can simultaneously reproduce EUV and SXR loops in ARs. Moreover, they predict radial intensity variations consistent with the localized core and extended emissions in SXR and EUV AR observations respectively. We finally show how the AR morphology can be used as a gauge of the properties (duration, energy, spatial dependence, repetition time) of the impulsive heating.

Patsourakos, S.↗
NASA NTRS2014

A Ground Testbed to Advance US Capability in Autonomous Rendezvous and Docking Project

This project will advance the Autonomous Rendezvous and Docking (AR&D) GNC system by testing it on hardware, particularly in a flight processor, with a goal of testing it in IPAS with the Waypoint L2 AR&D scenario. The entire Agency supports development of a Commodity for Autonomous Rendezvous and Docking (CARD) as outlined in the Agency-wide Community of Practice whitepaper entitled: "A Strategy for the U.S. to Develop and Maintain a Mainstream Capability for Automated/Autonomous Rendezvous and Docking in Low Earth Orbit and Beyond". The whitepaper establishes that 1) the US is in a continual state of AR&D point-designs and therefore there is no US "off-the-shelf" AR&D capability in existence today, 2) the US has fallen behind our foreign counterparts particularly in the autonomy of AR&D systems, 3) development of an AR&D commodity is a national need that would benefit NASA, our commercial partners, and DoD, and 4) an initial estimate indicates that the development of a standardized AR&D capability could save the US approximately $60M for each AR&D project and cut each project's AR&D flight system implementation time in half.

D'Souza, Chris↗
NASA NTRS2024

Assessing the Impact of Climate Change on Atmospheric Rivers: A Modeling Perspective

Atmospheric rivers (ARs) play a crucial role in the poleward transport of water vapor, and the AR-associated precipitation is a critical component of global water supplies, making it critical that we understand how ARs may change in the future. To approach this issue, integrations of the NASA Goddard Institute for Space Studies global climate model ModelE version 2.1 (GISSE2.1) are employed. Multiple configurations of the model simulating different climates are analyzed: (1) the last-glacial maximum; (2) present day; (3) the end of the 21st century. The thermodynamic and dynamic components of changes to AR frequency are analyzed using a decomposition method. This method utilizes differences in distinct AR seasonal climatology frequencies derived from various vertically integrated water vapor transport (IVT) thresholds to resolve AR frequency into its components. Global mean state changes in poleward AR frequency for different climates are dominated by precipitable water vapor (PWV) changes. A set of idealized cold and warm climates in which present day sea surface temperatures are uniformly changed are considered for a targeted analysis of the south Pacific Ocean basin. For this analysis, frequency and distribution of AR events in the model runs are analyzed by comparing them to changes in the jet stream as well as the Eulerian storm tracks and low-level baroclinicity. Latitudinal shifts in the ARs in the south Pacific Ocean basin using our integrations are not as tightly coupled to these two storm-related climatological metrics in the midlatitudes but fare better on the poleward side of the storm tracks.

Atmospheric rivers↗
DOE OSTI2024

Quantifying the Potential of Argon Detection Capabilities for Nuclear Explosion Monitoring

Abstract Current noble gas detection systems for nuclear explosion monitoring are based on the detection of four radioxenon isotopes—Xe-131m, -133, -133m and -135. The data provided by radioxenon detection could be enhanced by other radionuclide signatures such as Ar-37. Activation of Ca-40 in rock by neutrons produces Ar-37, and monitoring for this additional nuclide could help distinguish detections of nuclear explosions from background sources, such as medical isotope production. This work studies the capabilities of a hypothetical argon detection network. A 10 kt explosion was modeled using MCNP and SCALE to determine the inventory of Ar-37 created in a representative granite rock layer, assuming either 0.1, 1 or 10% of the total inventory was released. The Ar-37 inventory was combined with atmospheric transport data from HYSPLIT compiled in a previous study, along with the detection limits of standard Ar-37 detection systems, to determine how many hypothetical monitoring stations would detect Ar-37 from an explosion. This method was repeated for 365 HYSPLIT data sets to create a year’s worth of hypothetical explosions, releases, and detections. The study quantified the average number of detections per release, the number of stations detecting Ar-37, and the possibility of detecting Ar-37 in coincidence with xenon.

37Ar↗
DOE OSTI2023

Noble gas insights into early impact delivery and volcanic outgassing to Earth's atmosphere: A limited role for the continental crust

Earth's atmosphere, crust and mantle have evolved together through continuous geochemical exchange throughout Earth's history. Constraints on the transport of volatile elements and compounds between these reservoirs are crucial for understanding how Earth could have stayed habitable for extended periods of time. In this work, we present a new forward model of He, Ne and Ar in the mantle, crust and atmosphere. We explore concentrations of noble gases at the end of accretion, bulk silicate Earth K/U ratios, crustal growth scenarios, and upper mantle processing rates throughout Earth's history. We search for parameter combinations that simultaneously satisfy observational constraints on present-day mantle 4 He/ 3 He and 40 Ar/ 36 Ar (sensitive to mantle outgassing and continental crust growth, which depletes the mantle of U, Th and K), atmospheric 20 Ne/ 22 Ne (which tracks the mix of outgassed vs. delivered Ne in the atmosphere), and atmospheric 40 Ar/ 36 Ar in the past and today (sensitive to volatile delivery, mantle outgassing and crustal growth). Leveraging this intertwined set of noble gas abundances and isotopic compositions yields new constraints on initial noble gas abundances in the mantle and on the proportions of atmospheric volatiles originating from delivery by impact degassing, mantle outgassing, and degassing of the continental crust. We find that atmospheric Ar isotopic evolution is primarily sensitive to the mantle processing rate history; the atmospheric Ar isotopic record should therefore not be used to reconstruct continental crust growth, but instead provides valuable insights into mantle processing rates. Our model predicts a measurably low 20 Ne/ 22 Ne ratio of ~9.7 in Archean atmospheric samples. Most of atmospheric primordial 36 Ar was directly delivered by chondritic bodies and not transferred to the atmosphere during an intense early episode of mantle outgassing. Nitrogen delivered by impact degassing could account for the present-day atmospheric nitrogen inventory.

58 GEOSCIENCES↗
DOE OSTI2022

Contrasting Climatic Trends of Atmospheric River Occurrences Over East Asia

Atmospheric rivers (ARs) are increasingly recognized as a major driver of hydrological cycles, and are projected to increase around the world under a changing climate. However, the long-term trends of ARs over East Asia (EA) remains less elucidated. Here we fill the gap by developing a longest-ever archive of EA ARs, and examine its role in determining spatiotemporal precipitation variability over EA. We find contrasting changes in AR occurrences, with more frequent ARs in low latitudes but less in high latitudes during the period 1950-2020. The “dipole” pattern of decadal changes in AR occurrences is dictated by atmospheric dynamics (i.e., winds) in the north but thermodynamics (i.e., moisture) in the south. The reduced AR occurrences explain 49% of decreased annual precipitation in northern China, while more AR-related precipitation is observed in southern China. Furthermore, our results provide new insights into regional hydroclimate over EA by connecting it with large-scale weather systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

The Contribution of Subtropical Moisture Within an Atmospheric River on Moisture Flux, Cloud Structure, and Precipitation Over the Salmon River Mountains of Idaho Using Moisture Tracers

The impact of an atmospheric river (AR) on the flux of subtropical moisture across Idaho's Salmon River Mountains and precipitation over the mountains is evaluated using the Weather, Research, and Forecasting model with water vapor tracers (WRF-WVT). The AR impacted Idaho between 17 and 19 January 2017 during the Seeded and Natural Orographic Wintertime Clouds: The Idaho Experiment (SNOWIE) campaign. WRF-WVT is configured to isolate the subtropical moisture contribution to the AR, the moisture flux, and precipitation. Subtropical water vapor advected by the AR into Idaho is tagged and tracked in three-dimensional space throughout the run. This allows the contribution of the subtropical moisture to the vertical distribution of water vapor and the precipitation to be directly calculated. The simulated cloud structure is compared with airborne radar data collected during two SNOWIE intensive operation periods. This study found that more than 70% of the moisture flux and more than 80% of the precipitation across the Idaho Mountains during SNOWIE IOP 4 could be attributed to subtropical moisture within the AR. Nearly all of the moisture flux in the upper cloud and 50% of the moisture in the lower cloud was attributable to the subtropical moisture. The subtropical moisture contribution within the AR to precipitation ranged from 35% in northern Idaho to more than 90% in southern Idaho. Across the entire period of impact of the AR, more than 60% of precipitation in Idaho was attributable to the subtropical moisture within the AR, with this percentage increasing toward the south across the state.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Improved Simulations of Atmospheric River Climatology and Variability in High-Resolution CESM

Atmospheric rivers (ARs) can trigger extreme rainfall and snowfall events, causing high risk of flooding. Meanwhile, they are sometimes responsible for the occurrence and break of drought events. So, it is of great importance for weather and climate forecast models to accurately represent ARs. Studies have shown that AR variability is linked to various climate modes, such as El Niño/Southern Oscillation, Pacific Decadal Oscillation, Pacific-North America pattern, providing the potential for predicting ARs at subseasonal-to-decadal timescales. In this study, we examine the impact of climate model resolution on AR simulations and their relationship with major climate modes by comparing a pair of high-resolution and a low-resolution (LR) Community Earth System Model (CESM) simulations against the observations. The results reveal major deficiencies in LR that include underestimated climatological AR strength and associated precipitation, and inaccurate representations of ARs relationships with climate modes. Significant improvements are observed by increasing CESM horizontal resolution, suggesting a path for more accurate prediction of ARs.

54 ENVIRONMENTAL SCIENCES↗