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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Macro-physical Properties of Shallow Cumulus from Integrated ARM Observations (Final Report)

Fair-weather shallow cumuli (ShCu) play an important role in many climate-related processes. Irregular geometry of ShCu and their strong temporal and spatial variability make it challenging to observe ShCu holistically and to represent them correctly in climate models. To improve ShCu parameterizations, information on both vertically and horizontally resolved cloud properties is required. Commonly, the vertically resolved cloud properties are provided by zenith pointing lidar-radar observations with a very narrow field of view (FOV). Thus, these “pencil-beam” properties may not be representative of a larger surrounding area. Limited number of areal-averaged cloud properties, such as fractional sky cover (FSC), are offered typically by wide-FOV observations. The main goal of our project was to integrate advantages of the narrow-FOV (vertical structure of clouds) and wide-FOV (spatial arrangement of clouds) observations for an improved characterization of single-layer ShCu observed at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site for an 18-yr period (2000-2017). There are four major accomplishments of our project, First, an updated operational cloud classification for days with ShCu has been suggested and evaluated through a detailed comparison with the manually curated records. Our classification extends successfully the latest ARM cloud type Value Added Product (VAP) based on the Active Remote Sensing of Clouds (ARSCL) cloud product by incorporating both cloud fraction (CF) provided by narrow-FOV ceilometer data and FSC from wide-FOV images offered by a Total Sky Imager (TSI). Moreover, our classification allows one to identify impact of instrumentation changes at the SGP site, namely the transition to KAZRARSCL with the updated cloud radar, on the identification of periods with single-layer ShCu. Second, a new approach that resolves cloud area distributions for a given region (up to 4x4 km 2 ) has been suggested and cloud equivalent diameters (CEDs) have been estimated for the first time. These estimations have been performed over a wide range of cloud sizes (about 0.01–3.5 km) with high temporal resolution (30s) using wide-FOV TSI images and cloud base height (CBH) provided by complementary narrow-FOV lidar measurements. Our simple and computationally inexpensive approach offers a previously unavailable dataset for process studies in the convective boundary layer and evaluation of ShCu parameterizations in cloud-resolving models. Third, a long-term integrated record of ShCu macrophysical properties has been developed. The developed record represents the longest available compilation of events with ShCu and includes (i) a novel visualization of the spatial variability in cloud cover both along- and across-wind directions, (ii) updated estimates of narrow-FOV CF and wide-FOV FSC, (iii) updated narrow-FOV CBH, and (iv) complementary data, such as wind speed and direction from the 915-MHz Radar Wind Profiler (RWP) data. The developed record has been used successfully to assess conventional observational estimates of cloud cover and their sensitivity to the following two factors: (i) instrument-dependent cloud detection and data merging criteria and (ii) FOV configuration. Fourth, co-variability of the ShCu macrophysical properties and environmental parameters has been analyzed for a 3-yr period (2016-2018). Our initial analysis includes diurnal changes of FSCs obtained for clouds with small, moderate and large CEDs and several environmental parameters, such as lifted condensation level (LCL) and mixed layer height (zi). Preliminary results of our analysis suggest that the horizontal extent of ShCu is controlled substantially by the sign and magnitude of difference between these two parameters (zi-LCL): the CED tends to grow with increase of this difference (zi exceeds LCL). We have initiated relationships between the ShCu and key atmospheric parameters that control both the development and evolution of ShCu using our new data product, which combines effectively the advantages of narrow-FOV data offered by zenith pointing cloud radars and lidars and wide-FOV TSI images. While the latest instrumentation at the ARM sites may address these challenging relationships in the future, we believe that the historical ARM data at the SGP site has not yet been fully utilized. Overall, our data product can be used by researchers working on a wide range of climate-related projects. These projects may include (i) a comprehensive evaluation of outputs from the Large-Eddy Simulation (LES) and single-column models for their future improvement, (ii) the representativeness of “short-period” results obtained from the previous model and observational studies and (iii) the planning of future field campaigns with focus on improved understanding of the diurnal cycle of cumulus convection.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Investigation of boundary-layer wind predictions during nocturnal low-level jet events using the Weather Research and Forecasting model

Simulations of two periods featuring three consecutive low level jet (LLJ) events in the US Upper Great Plains during the autumn of 2011 were conducted to explore the impacts of various setup configurations and physical process models on simulated flow parameters within the lowest 200 m above the surface, using the Weather Research and Forecasting (WRF) model. Sensitivities of simulated flow parameters to the horizontal and vertical grid spacing, planetary boundary layer (PBL) and land surface model (LSM) physics options, were assessed. Data from a Light Detection and Ranging (lidar) system, deployed to the Weather Forecast Improvement Project (WFIP; Finley et al. 2013) were used to evaluate the accuracy of simulated wind speed and direction at 80 m above the surface, as well as their vertical distributions between 120 and 40 m, covering the typical span of contemporary tall wind turbines. All of the simulations qualitatively captured the overall diurnal cycle of wind speed and stratification, producing LLJs during each overnight period, however large discrepancies occurred at certain times for each simulation in relation to the observations. 54-member ensembles encompassing changes of the above discussed configuration parameters displayed a wide range of simulated vertical distributions of wind speed and direction, and potential temperature, reflecting highly variable representations of stratification during the weakly stable overnight conditions. Root mean square error (RMSE) statistics show that different ensemble members performed better and worse in various simulated parameters at different times, with no clearly superior configuration . Simulations using a PBL parameterization designed specifically for the stable conditions investigated herein provided superior overall simulations of wind speed at 80 m, demonstrating the efficacy of targeting improvements of physical process models in areas of known deficiencies. However, the considerable magnitudes of the RMSE values of even the best performing simulations indicate ample opportunities for further improvements.

Mirocha, Jeff D.↗
NASA NTRS2001

Global Surface Solar Energy Anomalies Including El Nino and La Nina Years

This paper synthesizes past events in an attempt to define the general magnitude, duration, and location of large surface solar anomalies over the globe. Surface solar energy values are mostly a function of solar zenith angle, cloud conditions, column atmospheric water vapor, aerosols, and surface albedo. For this study, solar and meteorological parameters for the 10-yr period July 1983 through June 1993 are used. These data were generated as part of the Release 3 Surface meteorology and Solar Energy (SSE) activity under the NASA Earth Science Enterprise (ESE) effort. Release 3 SSE uses upgraded input data and methods relative to previous releases. Cloud conditions are based on recent NASA Version-D International Satellite Cloud Climatology Project (ISCCP) global satellite radiation and cloud data. Meteorological inputs are from Version-I Goddard Earth Observing System (GEOS) reanalysis data that uses both weather station and satellite information. Aerosol transmission for different regions and seasons are for an 'average' year based on historic solar energy data from over 1000 ground sites courtesy of Natural Resources Canada (NRCan). These data are input to a new Langley Parameterized Shortwave Algorithm (LPSA) that calculates surface albedo and surface solar energy. That algorithm is an upgraded version of the 'Staylor' algorithm. Calculations are performed for a 280X280 km equal-area grid system over the globe based on 3-hourly input data. A bi-linear interpolation process is used to estimate data output values on a 1 X 1 degree grid system over the globe. Maximum anomalies are examined relative to El Nino and La Nina events in the tropical Pacific Ocean. Maximum year-to-year anomalies over the globe are provided for a 10-year period. The data may assist in the design of systems with increased reliability. It may also allow for better planning for emergency assistance during some atypical events.

Whitlock, C. H.↗
NASA NTRS2016

On the Importance of High Frequency Gravity Waves for Ice Nucleation in the Tropical Tropopause Layer

Recent investigations of the influence of atmospheric waves on ice nucleation in cirrus have identified a number of key processes and sensitivities: (1) ice concentrations produced by homogeneous freezing are strongly dependent on cooling rates, with gravity waves dominating upper tropospheric cooling rates; (2) rapid cooling driven by high-frequency waves are likely responsible for the rare occurrences of very high ice concentrations in cirrus; (3) sedimentation and entrainment tend to decrease ice concentrations as cirrus age; and (4) in some situations, changes in temperature tendency driven by high-frequency waves can quench ice nucleation events and limit ice concentrations. Here we use parcel-model simulations of ice nucleation driven by long-duration, constant-pressure balloon temperature time series, along with an extensive dataset of cold cirrus microphysical properties from the recent ATTREX high-altitude aircraft campaign, to statistically examine the importance of high-frequency waves as well as the consistency between our theoretical understanding of ice nucleation and observed ice concentrations. The parcel-model simulations indicate common occurrence of peak ice concentrations exceeding several hundred per liter. Sedimentation and entrainment would reduce ice concentrations as clouds age, but 1-D simulations using a wave parameterization (which underestimates rapid cooling events) still produce ice concentrations higher than indicated by observations. We find that quenching of nucleation events by high-frequency waves occurs infrequently and does not prevent occurrences of large ice concentrations in parcel simulations of homogeneous freezing. In fact, the high-frequency variability in the balloon temperature data is entirely responsible for production of these high ice concentrations in the simulations.

simulation↗
NASA NTRS2015

A WRF-Chem Analysis of Flash Rates, Lightning-NOx Production and Subsequent Trace Gas Chemistry of the 29-30 May 2012 Convective Event in Oklahoma During DC3

The Deep Convective Clouds and Chemistry (DC3) field campaign in 2012 provided a plethora of aircraft and ground-based observations (e.g., trace gases, lightning and radar) to study deep convective storms, their convective transport of trace gases, and associated lightning occurrence and production of nitrogen oxides (NOx). This is a continuation of previous work, which compared lightning observations (Oklahoma Lightning Mapping Array and National Lightning Detection Network) with flashes generated by various flash rate parameterization schemes (FRPSs) from the literature in a Weather Research and Forecasting Chemistry (WRF-Chem) model simulation of the 29-30 May 2012 Oklahoma thunderstorm. Based on the Oklahoma radar observations and Lightning Mapping Array data, new FRPSs are being generated and incorporated into the model. The focus of this analysis is on estimating the amount of lightning-generated nitrogen oxides (LNOx) produced per flash in this storm through a series of model simulations using different production per flash assumptions and comparisons with DC3 aircraft anvil observations. The result of this analysis will be compared with previously studied mid-latitude storms. Additional model simulations are conducted to investigate the upper troposphere transport, distribution, and chemistry of the LNOx plume during the 24 hours following the convective event to investigate ozone production. These model-simulated mixing ratios are compared against the aircraft observations made on 30 May over the southern Appalachians.

Cummings, Kristin A.↗
DOE OSTI2024

Extreme Risk Mitigation in Reinforcement Learning using Extreme Value Theory

Risk-sensitive reinforcement learning (RL) has garnered significant attention in recent years due to the growing interest in deploying RL agents in real-world scenarios. A critical aspect of risk awareness involves modelling highly rare risk events (rewards) that could potentially lead to catastrophic outcomes. These infrequent occurrences present a formidable challenge for data-driven methods aiming to capture such risky events accurately. While risk-aware RL techniques do exist, they suffer from high variance estimation due to the inherent data scarcity. Our work proposes to enhance the resilience of RL agents when faced with very rare and risky events by focusing on refining the predictions of the extreme values predicted by the state-action value distribution. To achieve this, we formulate the extreme values of the state-action value function distribution as parameterized distributions, drawing inspiration from the principles of extreme value theory (EVT). We propose an extreme value theory based actor-critic approach, namely, Extreme Valued Actor-Critic (EVAC) which effectively addresses the issue of infrequent occurrence by leveraging EVT-based parameterization. Importantly, we theoretically demonstrate the advantages of employing these parameterized distributions in contrast to other risk-averse algorithms. Our evaluations show that the proposed method outperforms other risk averse RL algorithms on a diverse range of benchmark tasks, each encompassing distinct risk scenarios.

Wang, Yu↗
DOE OSTI2020

Collaborative Research: Advancing Arctic Climate Projection Capability at Seasonal to Decadal Scales (Final Technical Report)

The Regional Arctic System Model (RASM) at process resolving configurations has been used to (i) advance understanding of physical processes and feedbacks involved in Arctic amplification and (ii) understand and potentially reduce uncertainty in prediction of arctic climate change at seasonal to decadal scales. RASM consists the atmosphere (Weather and Research Forecasting model, WRF), ocean (Parallel Ocean Program, POP), sea ice (CICE), land hydrology (Variable Infiltration Capacity model, VIC), river routing scheme (RVIC), marine biogeochemistry components and the coupling framework (CPL7). Its domain is pan-Arctic, with the atmosphere and land components configured on a 50-km or 25-km grid and four configurations of the ocean and sea ice components: 1/12°(~9.3km) or 1/48°(~2.4km) and 45 or 60 vertical layers. These RASM configurations have been motivated by the emerging exascale capability for high performance computing to improve model fidelity. The dynamical downscaling of reanalysis allows comparison of RASM results with observations in place and time to: (i) advance system level understanding of physical processes and coupling involved in an event, (ii) optimize model parameter space, (iii) diagnose and reduce model biases and (iv) produce realistic and consistent across all the components initial conditions for predictions and predictability studies, which are all unique capabilities not available in global Earth System Models (ESMs). An evaluation of RASM 1.0 (Cassano et al. 2017) revealed that it had a cold bias over the oceans and a warm bias over land areas due largely to cloud and radiation biases in the model, with too little cloud cover simulated over land and too much cloud cover simulated over sub-polar oceans. This study has motivated an upgrade to WRF version 3.7.1 in RASM and allowed for the inclusion of the radiative impact of convective clouds. A variety of atmospheric physics parameterizations were evaluated against observations (e.g. data from the Arctic Clouds in Summer Experiment (ACSE); Sedlar et al. 2020) to identify an optimal suite of WRF physics options in RASM. The RASM with the optimized WRF physics were used to study the impact of strong mesoscale winds over the ocean around the southern tip of Greenland (DuVivier and Cassano 2016) and their impact on oceanic convection (DuVivier et al. 2017a). Data from the PolarWinds field campaign were used to evaluate WRF boundary layer physics and resolution impacts on the simulation of a Greenland barrier wind event (DuVivier et al. 2017b). The RVIC streamflow routing model has been implemented in RASM to realistically represent high-resolution streamflow processes (Hamman et al. 2017) and to couple the land buoyancy fluxes to the ocean. The RASM-RVIC high-resolution data set of all coastal freshwater fluxes for the Arctic drainage basin and surrounding areas for 1979-2014 was published as a separate product (https://doi.org/10.5281/zenodo.293037). The fidelity of atmospheric momentum transfer to and the response of polar marine Ekman layer in RASM and Community Earth System Model (CESM) was investigated by Roberts et al. (2015). The increased frequency of oceanic flux exchange in CESM, following the RASM guidance, caused a considerable increase in the median inertial ice speed across the Southern Ocean and parts of the Arctic. A comprehensive evaluation of the RASM1.0 atmosphere-ocean-sea ice-land interface was completed by Brunke et al. (2018). RASM was also demonstrated for its capability to simulate extreme events in agreement with observations in space and time (Lee et al. submitted). In particular, the development of three open water events, known as polynyas, have been simulated north of Greenland in February of 2011, 2017 and 2018, in agreement with satellite observations for the past four decades. The optimized RASM sea ice results have been favorably evaluated against satellite observations and a subset of eleven CMIP6 models (Watts et al. submitted). In a complementary project, Jin et al. (2018) have shown that RASM with higher-resolution and new sea-ice processes contributed to lower model errors in sea-ice conditions, concentrations of nutrients and ice algae, in comparison to results from the coarse-resolution (1°) CESM. In two other complementary studies, RASM results were used (i) to explain areas of concentrated use by bowhead whales, the seasonal progression in the use, and the physical environment within those areas (Citta et al. 2015) and (ii) for a synthesis of fall bowhead whales distribution and migration in the Bering-Chukchi-Beaufort (BCB) Sea to investigate whale movements and feeding to the local ocean hydrography and currents (Citta et al. 2018). However, the multi-decadal output from the CESM Large Ensemble yielded unrealistic forcing. Instead, the shorter NCEP CFSv2 9-month forecasts were successfully tested and afforded an increased ensemble size (~30) to demonstrate gains of dynamical downscaling at sub-seasonal to intra-annual time scales. The improved model physics and coupling among RASM model components have yielded more realistic representation of the sea ice cover and consistent across all model components initial conditions. Consequently, RASM demonstrates significant gains compared to simulation of sea ice in the NCEP reanalysis. In addition, RASM 6-month ensemble forecasts yield very realistic sea ice distribution, which demonstrates both significant gains of dynamical downscaling and the continued impact of the initial conditions on forecasts out to 6 months (https://nps.edu/web/rasm/predictions). A follow up study using RASM for dynamical downscaling of the more realistic CESM initialized Decadal Prediction Large Ensemble output is currently ongoing as part of the DOE RGMA HiLAT-RASM project.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Event Horizon Telescope imaging of the archetypal blazar 3C 279 at an extreme 20 microarcsecond resolution

3C 279 is an archetypal blazar with a prominent radio jet that show broadband flux density variability across the entire electromagnetic spectrum. We use an ultra-high angular resolution technique – global Very Long Baseline Interferometry (VLBI) at 1.3 mm (230 GHz) – to resolve the innermost jet of 3C 279 in order to study its fine-scale morphology close to the jet base where highly variable γ-ray emission is thought to originate, according to various models. The source was observed during four days in April 2017 with the Event Horizon Telescope at 230 GHz, including the phased Atacama Large Millimeter/submillimeter Array (ALMA), at an angular resolution of ∼20 μas (at a redshift of z = 0.536 this corresponds to ∼0.13 pc ∼ 1700 Schwarzschild radii with a black hole mass MBH = 8 × 108 M⊙). Imaging and model-fitting techniques were applied to the data to parameterize the fine-scale source structure and its variation. We find a multicomponent inner jet morphology with the northernmost component elongated perpendicular to the direction of the jet, as imaged at longer wavelengths. The elongated nuclear structure is consistent on all four observing days and across different imaging methods and model-fitting techniques, and therefore appears robust. Owing to its compactness and brightness, we associate the northern nuclear structure as the VLBI “core”. This morphology can be interpreted as either a broad resolved jet base or a spatially bent jet. We also find significant day-to-day variations in the closure phases, which appear most pronounced on the triangles with the longest baselines. Our analysis shows that this variation is related to a systematic change of the source structure. Two inner jet components move non-radially at apparent speeds of ∼15 c and ∼20 c (∼1.3 and ∼1.7 μas day−1, respectively), which more strongly supports the scenario of traveling shocks or instabilities in a bent, possibly rotating jet. The observed apparent speeds are also coincident with the 3C 279 large-scale jet kinematics observed at longer (cm) wavelengths, suggesting no significant jet acceleration between the 1.3 mm core and the outer jet. The intrinsic brightness temperature of the jet components are ≲1010 K, a magnitude or more lower than typical values seen at ≥7 mm wavelengths. The low brightness temperature and morphological complexity suggest that the core region of 3C 279 becomes optically thin at short (mm) wavelengths.Key words: galaxies: active / galaxies: jets / galaxies: individual: 3C 279 / techniques: interferometric⋆ The data are only available at the CDS via anonymous ftp to cdsarc.u-strasbg.fr (130.79.128.5) or via http://cdsarc.u-strasbg.fr/viz-bin/cat/J/A+A/640/A69 and at https://eventhorizontelescope.org/for-astronomers/data⋆⋆ Deceased.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

Impact of form factor uncertainties on interpretations of coherent elastic neutrino-nucleus scattering data

The standard model coherent elastic neutrino-nucleus scattering (CEνNS) cross section is subject to nuclear form factor uncertainties, mainly driven by the root-mean-square radius of the neutron density distribution. Motivated by COHERENT phases I-III and future multi-ton direct detection dark matter searches, we evaluate these uncertainties in cesium iodide, germanium, xenon and argon detectors. We find that the uncertainties become relevant for momentum transfers q≳20 MeV and are essentially independent of the form factor parameterization. Consequently, form factor uncertainties are not important for CEνNS induced by reactor or solar neutrinos. Taking into account these uncertainties, we then evaluate their impact on measurements of CEνNS at COHERENT, the diffuse supernova background (DSNB) neutrinos and sub-GeV atmospheric neutrinos. We also calculate the relative uncertainties in the number of COHERENT events for different nuclei as a function of recoil energy. For DSNB and atmospheric neutrinos, event rates at a liquid argon detector can be uncertain to more than 5%. Finally, we consider the impact of form factor uncertainties on searches for nonstandard neutrino interactions, sterile neutrinos and neutrino generalized interactions. We point out that studies of new physics using CEνNS data are affected by neutron form factor uncertainties, which if not properly taken into account may lead to the misidentification of new physics signals. The uncertainties quantified here are also relevant for dark matter direct detection search

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Atomic-Level Features for Kinetic Monte Carlo Models of Complex Chemistry from Molecular Dynamics Simulations

The high computational cost of evaluating atomic interactions recently motivated the development of computationally inexpensive kinetic models, which can be parametrized from MD simulations of complex chemistry of thousands of species or other processes and accelerate the prediction of the chemical evolution by up to four order of magnitude. Such models go beyond the commonly employed potential energy surface fitting methods in that they are aimed purely at describing kinetic effects. So far, such kinetic models utilize molecular descriptions of reactions and have been constrained to only reproduce molecules previously observed in MD simulations. Therefore, these descriptions fail to predict the reactivity of unobserved molecules, for example in the case of large molecules or solids. In this work, we propose a new approach for the extraction of reaction mechanisms and reaction rates from MD simulations, namely the use of atomic-level features. Using the complex chemical network of hydrocarbon pyrolysis as example, it is demonstrated that kinetic models built using atomic features are able to explore chemical reaction pathways never observed in the MD simulations used to parametrize them, a critical feature to describe rare events. Atomic-level features are shown to construct reaction mechanisms and estimate reaction rates of unknown molecular species from elementary atomic events. Through comparisons of the model ability to extrapolate to longer simulation timescales and different chemical compositions than the ones used for parameterization, it is demonstrated that kinetic models employing atomic features retain the same level of accuracy and transferability as the use of features based on molecular species, while being more compact and parametrized with less data. We also find that atomic features can better describe the formation of large molecules enabling the simultaneous description of small molecules and condensed phases.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

A library of AI-assisted FAIR water cycle and related disturbance datasets to enable model training, parameterization and validation

This whitepaper is responsive to focal area Data acquisition and assimilation enabled by machine learning, AI, and advanced methods. Here we describe how FAIR (Findable, Accessible, Reusable, Interoperable) datasets related to water cycle extremes are essential for successful implementation of ML in Earth System and other models. We also describe how AI can be used to acquire and integrate water cycle data related to extreme events to create a library of FAIR datasets for training and evaluating algorithms.

58 GEOSCIENCES↗
DOE OSTI2021

Metrics for evaluating tropical cyclones in climate data

This manuscript describes a software suite that can be used for objective evaluation of tropical cyclones (TCs) in gridded climate data. Using cyclone trajectories derived from 6-hourly data, a comprehensive set of metrics is defined to systematically compare and contrast products to one another. In addition to annual TC climatologies, attention is paid to spatial and temporal patterns of storm occurrence and intensity. Assessment can be performed either on the global scale or regional domains. Simple to visualize ‘scorecards’ allow for rapid credibility assessment. We showcase three key findings enabled by this suite. First, we compare the representation of TCs in seven current-generation global reanalyses and conclude that higher resolution models and those with TC-specific assimilation contain more accurate storm climatologies. Second, using a free-running Earth system model (ESM) we find that full basin refinement is required in variable-resolution configurations to adequately simulate North Atlantic TC frequency. Furthermore, upstream refinement over northern Africa offers little benefit in simulating storm occurrence but spatial genesis patterns are improved. Finally, we show that TCs simulated by ESMs can be highly sensitive to individual parameterizations in climate models, with North Atlantic TC metrics varying greatly depending on version of the Morrison-Gettelman microphysics package.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Identification and Characterization of Persistent Cold Pool Events from Temperature and Wind Profilers in the Columbia River Basin

Cold pool events occur when deep layers of stable, cold air remain trapped in a valley or basin for multiple days, without mixing out from daytime heating. With large impacts on air quality, freezing events, and es-pecially on wind energy production, they are often poorly forecast by modern mesoscale numerical weather prediction (NWP) models. Understanding the characteristics of cold pools is, therefore, important to provide more accurate forecasts. This study analyzes cold pool characteristics with data collected during the Second Wind Forecast Improvement Project (WFIP2), which took place in the Columbia River basin and Gorge of Oregon and Washington from fall 2015 until spring 2017. A subset of the instrumentation included three microwave radiometer pro?lers, six radar wind pro?lers with radio acoustic sounding systems, and seven sodars, which together provided seven sites with collocated vertical pro?les of temperature, humidity, wind speed, and wind direction. Using these collocated observations, we developed a set of criteria to determine if a cold pool was present based on stability, wind speed, direction, and temporal continuity, and then developed an automated algorithm based on these criteria to identify all cold pool events over the 18 months of the ?eld project. Characteristics of these events are described, including statistics of the wind speed distributions and pro?les, stability conditions, cold pool depths, and descent rates of the cold pool top. The goal of this study is a better understanding of these characteristics and their processes to ultimately lead to improved physical parameterizations in NWP models, and consequently improve forecasts of cold pool events in the study region as well at other locations that experiences similar events.

McCaffrey, Katherine L.↗
DOE OSTI2026

Benchmarking state-of-the-art theory and empirical models of pionless neutrino-argon scattering in GENIE

Upcoming experiments need improved simulations of neutrino scattering. This work uses the popular GENIE event generator to test a variety of neutrino interaction models against recent MicroBooNE measurements of pionless charged-current interactions. The GENIE code can easily interchange model components, including nucleon form factor parameterizations, quasielastic cross-section calculations, treatments of the nuclear ground state and hadronic final-state interactions. Leveraging this software capability in comparisons with MicroBooNE data, the performance of some of GENIE’s most theoretically sophisticated model components is evaluated and contrasted with more empirically-driven alternatives.

Neutrino cross section↗
DOE OSTI2020

Application of Numerical Atmospheric Models

In this study, a numerical modeling framework for simulating extreme storm events was established using the Weather Research and Forecasting (WRF) model. Such a framework is necessary for the derivation of engineering parameters such as probable maximum precipitation that are the cornerstone of large water-management infrastructure design. Here, this framework was built based on a heavy storm that occurred in Nashville, Tennessee (U.S.), in 2010, and verified using two other extreme storms. To achieve the optimal setup, several combinations of model resolutions, initial/boundary conditions (IC/BC), cloud microphysics, and cumulus parameterization schemes were evaluated using multiple metrics of precipitation characteristics. The evaluation suggests that WRF is most sensitive to the IC/BC option. Simulation generally benefits from finer resolutions up to 5 km. At the 15 km level, NCEP2 IC/BC produces better results, whereas NAM IC/BC performs best at the 5 km level. The recommended model configuration from this study is: NAM or NCEP2 IC/BC (depending on data availability), 15 km or 15–5 km nested grids, Morrison microphysics, and Kain-Fritsch cumulus schemes. Validation of the optimal framework suggests that these options are good starting choices for modeling extreme events similar to the test cases. This optimal framework is proposed in response to emerging engineering demands of extreme storm event forecasting and analyses for design, operations, and risk assessment of large water infrastructures.

Chen, Xiaodong↗
DOE OSTI2011

Multi-Scale Mass Transfer Processes Controlling Natural Attenuation and Engineered Remediation: An IFRC Focused on Hanford’s 300 Area Uranium Plume January 2010 to January 2011

The Integrated Field Research Challenge (IFRC) at the Hanford Site 300 Area uranium (U) plume addresses multi-scale mass transfer processes in a complex subsurface hydrogeologic setting where groundwater and riverwater interact. A series of forefront science questions on reactive mass transfer focus research. These questions relate to the effect of spatial heterogeneities; the importance of scale; coupled interactions between biogeochemical, hydrologic, and mass transfer processes; and measurements and approaches needed to characterize and model a mass-transfer dominated system. The project was initiated in February 2007, with CY 2007, CY 2008, and CY 2009 progress summarized in preceding reports. A project peer review was held in March 2010, and the IFRC project has responded to all suggestions and recommendations made in consequence by reviewers and SBR/DOE. These responses have included the development of “Modeling” and “Well-Field Mitigation” plans that are now posted on the Hanford IFRC web-site. The site has 35 instrumented wells, and an extensive monitoring system. It includes a deep borehole for microbiologic and biogeochemical research that sampled the entire thickness of the unconfined 300 A aquifer. Significant, impactful progress has been made in CY 2010 including the quantification of well-bore flows in the fully screened wells and the testing of means to mitigate them; the development of site geostatistical models of hydrologic and geochemical properties including the distribution of U; developing and parameterizing a reactive transport model of the smear zone that supplies contaminant U to the groundwater plume; performance of a second passive experiment of the spring water table rise and fall event with a associated multi-point tracer test; performance of downhole biogeochemical experiments where colonization substrates and discrete water and gas samplers were deployed to the lower aquifer zone; and modeling of past injection experiments for model parameterization, deconvolution of well-bore flow effects, system understanding, and publication. We continued efforts to assimilate geophysical logging and 3D ERT characterization data into our site wide geophysical model, and have now implemented a new strategy for this activity to bypass an approach that was found unworkable. An important focus of CY 2010 activities has been infrastructure modification to the IFRC site to eliminate vertical well bore flows in the fully screened wells. The mitigation procedure was carefully evaluated and is now being implementated. A new experimental campaign is planned for early spring 2011 that will utilize the modified well-field for a U reactive transport experiment in the upper aquifer zone. Preliminary geophysical monitoring experiments of rainwater recharge in the vadose zone have been initiated with promising results, and a controlled infiltration experiment to evaluate U mobilization from the vadose zone is now under planning for the September 2011. The increasingly comprehensive field experimental results, along with the field and laboratory characterization, are leading to a new conceptual model of U(VI) flow and transport in the IFRC footprint and the 300 Area in general, and insights on the microbiological community and associated biogeochemical processes.

300 Area↗
DOE OSTI2021

Facilitating better and faster simulations of aerosol-cloud interactions in Earth system models

Focal Area(s): 1. Predictive modeling through the use of AI techniques and AI-derived model components; the use of AI and other tools to design a prediction system comprising a hierarchy of models. 2. Insight gleaned from complex data (both observed and simulated) using AI, big data analytics, and other advanced methods, including explainable AI and physics- or knowledge-guided AI. Science Challenge: One major challenge that Earth system models (ESMs) face in providing credible prediction of the Earth system and its water cycle characteristics (e.g., mean state, variability, and extreme events) is to accurately simulate aerosol-cloud interactions (ACI). The physical, chemical, and dynamical processes affecting ACI are extremely complex and they range from nanoscale to planetary scale. In each model development cycle, scientists spend significant efforts investigating model deficiencies and uncertainties associated with aerosols (e.g., emissions, chemical processes, aerosol microphysics, and transport) and clouds (e.g., macrophysics, microphysics, turbulence, and large-scale circulation) in order to develop improved treatments. However, despite decades of active research, ACI is still a major source of uncertainty in climate projections, even though great progress has been made. Specific scientific challenges include: (i) Parameterizations are developed based on limited data; (ii) The complexity of a parameterization required for accurate predictions is not understood; (iii) Incomplete and unknown physics leads to errors in the fully coupled Earth system; and (iv) Complex physics is computationally too expensive to employ in ESMs.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1998

MAMI: Modeling of the Magnetosphere-Ionosphere-Atmosphere System

Major emphasis of the investigation was the development of theoretical and numerical models of the aurora and of high latitude ionospheric processes. In particular: (1) the NCAR TIGCM (Thermosphere-Ionosphere Global Circulation Model) was updated to include mid and low latitude electrodynamics (this version is called TIE-GCM); (2) the NCAR TIE-GCM was modified to include a more realistic representation of the aurora; (3) the UAF auroral electron transport model was modified to include local acceleration processes; (4) a local ionospheric and auroral model (AURORA) was developed to allow detailed studies of the aurora; (5) a proton-hydrogen transport code has been developed to model proton aurora; and (6) a theory for the production of suprathermal atoms and ions in the upper atmosphere was developed and applied to studies of atomic nitrogen transport and helium escape on open field lines. These models enable us to devise schemes for tile interpretation and quantitative analysis of data obtained by the POLAR spacecraft. Parameterizations were formulated and are available to the GGS investigators. The UVI and VIS teams have adopted these parameterizations and include them in their data analysis. We have developed software for the quantitative interpretation of UVI and VIS images. After the launch of the POLAR satellite we used the image data from UVI and VIS in combination with ground based data from SuperDARN and incoherent scatter radars, magnetometers, and in situ observations from DMSP and NOAA satellites to characterize the state of the ionosphere. A number of event studies have been carried out in cooperation with other CGS theory teams.

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