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All sourcesNASA NTRSDOE OSTI
DOE OSTI2012

GAPS IN PROTOPLANETARY DISKS AS SIGNATURES OF PLANETS. I. METHODOLOGY AND VALIDATION

We examine the observational consequences of partial gaps being opened by planets in protoplanetary disks. We model the disk using a static {alpha}-disk model with detailed radiative transfer, parameterizing the shape and size of the partially cleared gaps based on the results of hydrodynamic simulations. Shadowing and illumination by stellar irradiation at the surface of the gap leads to increased contrast as the gap trough is deepened by shadowing and cooling and the far gap wall is puffed up by illumination and heating. In calculating observables, we find that multiple scattering is important and derive an approximation to include these effects. A gap produced by a 200 M{sub Circled-Plus} (70 M{sub Circled-Plus }) planet at 10 AU can lower/raise the midplane temperature of the disk by up to {approx} - 25%/+29% ({approx} - 11/+ 19) by shadowing in the gap trough and illumination on the far shoulder of the gap. At the distance of Taurus, this gap would be resolvable with {approx}0.''01 angular resolution. The gap contrast is most significant in scattered light and at thermal continuum wavelengths characteristic of the surface temperature, reducing or raising the surface brightness by up to order of magnitude. Since gap sizes are correlated with planet mass, this is a promising way of finding and determining the masses of planets embedded in protoplanetary disks.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Ab initio calculation of carrier mobility in semiconductors including ionized-impurity scattering

The past decade has seen the emergence of ab initio computational methods for calculating phonon-limited carrier mobilities in semiconductors with predictive accuracy. More realistic calculations ought to take into account additional scattering mechanisms such as, for example, impurity and grain-boundary scattering. Here, in this paper, we investigate the effect of ionized-impurity scattering on the carrier mobility. We model the analytical impurity potential parameterized from first principles by a collection of randomly distributed Coulomb scattering centers, and we include this relaxation channel into the ab initio Boltzmann transport equation, as implemented in the EPW code. We demonstrate this methodology by considering silicon, silicon carbide, and gallium phosphide, for which detailed experimental data are available. Our calculations agree well with experiments over a broad range of temperatures and impurity concentrations. For each compound investigated here, we compare the relative importance of electron-phonon scattering and ionized-impurity scattering, and we critically assess the reliability of Matthiessen's rule. We also show that an accurate description of dielectric screening and carrier effective masses can improve quantitative agreement with experiments.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Aboveground Biomass Estimation Using NISAR Simulated ALOS-2 Time Series Data

Aboveground biomass (AGB) is a critical parameter to better understand the global carbon cycle and to develop sustainable forest management. However, a large uncertainty prevails. L-band SAR data have demonstrated strong potential to accurately retrieve AGB over low-biomass regions (<100 Mg ha-1). The upcoming NASA-ISRO Synthetic Aperture Radar mission will collect data at L- and S-band over earth’s landmass with a repeat period of 12 days, allowing us to have ample data for monitoring biomass and its dynamics. One of the key science requirements of the mission is to produce annual AGB maps at 1-ha resolution with RMS accuracy of 20 Mg/ha for 80 percentage of area over low-biomass regions in Calibration/Validation sites. The NISAR biomass algorithm will generate AGB maps based on the parameterization of semi-empirical model along with NISAR time-series dual pol data (HH and HV). To calibrate and validate the model for mission requirements, the mission will use reference estimates of AGB produced from ground inventory plots and airborne LiDAR data collected over selected sites distributed across different global ecoregions. This paper presents the initial results of the calibration/validation of the NISAR AGB retrieval algorithm over the Lenoir Landing (LENO), Alabama, USA site using NISAR simulated ALOS-2 time series data. Five multi-temporal dual-pol HH and HV NISAR Simulated ALOS 2 data collections were used as input to assess the performance of the model. The model AGB retrieval results shows that the NISAR model was able to achieve RMS accuracy within 20 Mg/ha.

Ramachandran, Naveen [Jet Propulsion Laboratory, C↗
DOE OSTI2021

Data-Driven Learning of Nonautonomous Systems

In this work, we present a numerical framework for recovering unknown nonautonomous dynamical systems with time-dependent inputs. To circumvent the difficulty presented by the nonautonomous nature of the system, our method transforms the solution state into piecewise integration of the system over a discrete set of time instances. The time-dependent inputs are then locally parameterized by using a proper model, for example, polynomial regression, in the pieces determined by the time instances. This transforms the original system into a piecewise parametric system that is locally time invariant. We then design a deep neural network structure to learn the local models. Once the network model is constructed, it can be iteratively used over time to conduct global system prediction. We provide theoretical analysis of our algorithm and present a number of numerical examples to demonstrate the effectiveness of the method.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2011

Moist thermodynamics of the Madden-Julian Oscillation in a cloud resolving simulation

The moist thermodynamic processes that determine the scale and energy of the Madden-Julian Oscillation are investigated using moisture and eddy available potential energy (EAPE) budget analyses on a high resolution regional model simulation. The two MJO episodes observed during the winter of 2007-2008 are realistically simulated. In the model, small differences among the timescales of convective vertical transport, mixing and condensation of moisture determine the timescale of MJO moistening. Furthermore, various cloud types play a damping or destabilizing contribution role in the EAPE budget of the MJO, depending on their characteristic latent heating profile and its covariance with the temperature fluctuations. The results are used identify possible sources of the difficulties in simulating MJO in low resolution models that rely on cumulus parameterizations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Observed Covariations in Boundary Layer and Cumulus Cloud Layer Processes

In this paper we examine variations in boundary-layer processes spanning the shallow to deep cumulus transition. This is accomplished by differentiating boundary layer properties on the basis of convective outcomes, ranging from shallow to deep, as observed at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site in Oklahoma, USA. Doppler lidar, radar, and radiosonde data are combined to determine statistical differences in boundary layer and cloud layer properties using a large sample (236) of days with a range of convective outcomes: shallow, congestus, and deep convection. In these analyses, the radar characterizes diurnal cloud depth, the lidar quantifies updraft and downdraft properties in the subcloud layer, and daily radiosonde data provides the convective inhibition (CIN). Combined, these data are used to test the hypothesis that deep convection occurs when the strength of the boundary layer turbulence (i.e., TKE) exceeds the strength of the energy barrier (i.e., CIN) at the top of the CBL. Results show that days with deep convective clouds have significantly lower vertical velocity variance and weaker updrafts within the subcloud layer. However, CIN values are also found to be significantly lower on deep convective days, allowing for these weaker updrafts to penetrate the energy barrier and reach the level of free convection (LFC). In contrast, shallow convective outcomes occur when the updrafts are strong in an absolute sense, but are weak when compared to the strength of the energy barrier. These findings support the use of the CIN/TKE framework in parameterizing convection in coarse resolution models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Monsoon Depression Amplification by Horizontal Shear and Humidity Gradients: A Shallow Water Perspective

Transient, synoptic-scale vortices produce a large fraction of total rainfall in most monsoon regions and are often associated with extreme precipitation. However, the mechanism of their amplification remains a topic of active research. For monsoon depressions, which are the most prominent synoptic-scale vortex in the Asian–Australian monsoon, recent work has suggested that meridional gradients in zonal wind in the vortex environment may produce growth through barotropic instability, while meridional gradients in environmental humidity have also been proposed to cause amplification through coupling with precipitating convection. Here, a two-dimensional shallow water model on a sphere with parameterized precipitation is used to examine the relative role played by these two environmental gradients. By systematically varying the meridional moisture gradient and meridional wind shear for both weak, quasi-linear waves and finite-amplitude isolated vortices, we show that rotational winds in the initial vortex are amplified most strongly by meridional shear of the environmental zonal wind, while vortex precipitation rates are most sensitive to environmental moisture gradients. The growth rate in the presence of both gradients is less than the sum of growth rates in the presence of isolated gradients, as the phase relation between moisture and vorticity anomalies becomes distorted with increasing shear. In conclusion, these results suggest that background meridional gradients in both zonal wind and environmental humidity can contribute to the amplification of vortices to monsoon depression strength, but with some degree of decoupling of the dry rotational flow and the moist convection.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

PAVC Gridded 20m Alaska NGEE Tier3 PFTs v1.0

These 20-meter spatial resolution gridded products provide per-pixel fractional cover (%) of Next Generation Ecosystem Experiments (NGEE) Arctic Plant Functional Types (PFTs) Tier 3 across Alaska, north of the boreal treeline. The products were developed for the NGEE Arctic project, which is improving Arctic vegetation representation and parameterization of the E3SM Land Model. This dataset includes 8 files containing fractional cover for NGEE Tier 3 PFTs (https://data.ess-dive.lbl.gov/view/doi:10.15485/2529470): (1) bryophytes; (2) lichens; (3) non-vascular plants, i.e., the sum of lichens and bryophytes; (4) deciduous shrubs, (5) evergreen shrubs, (6) forbs, (7) graminoids, and a non-PFT class, (8) litter. Each pixel contains the percent cover (expressed as a fraction of total ground cover) that was predicted by random-forest regression models. The random-forest models were trained on cover data collected at 978 plots from 2010 to 2021, of which are archived in the Pan-Arctic Vegetation Cover (PAVC) database (https://data.ess-dive.lbl.gov/datasets/doi:10.15485/2483557). The plot cover was linked to 20-meter spatial resolution, satellite-derived predictor variables: Sentinel-2 spectra and Sentinel-1 polarizations averaged over the 2019 growing season, as well as topographical features derived from ArcticDEM. Then, spatio-temporally anomalous plot data that introduced large variability to the regression outcomes were dropped using the Cook’s distance outlier detection method, and the models were re-created using high-quality plots and their associated satellite derived explanatory variables per each PFT. The correlations between plot-observed and satellite-derived fractional cover for all PFTs were well correlated (R2 = 0.69–0.95 and 0.5 for litter) and had low RMSE bias (0.02–0.11). This research was performed as a part of the NGEE Arctic project. The NGEE Arctic project was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Geophysical Monitoring with Seismic Metamaterial Contrast Agents

Acoustic impedance tube and forced-oscillation seismic core test measurements were conducted to examine the low-frequency properties of acoustic metamaterial contrast agents. Water-stable suspensions of metal-organic framework (MOF) nanoparticles increased sound transmission loss (100-1250 Hz) and seismic attenuation (10-70 Hz), and reduced Young’s modulus of nanofluid-saturated Berea Sandstone cores. Preliminary measurements were used to parameterize a seismic wave velocity model. These results indicate that injectable MOF nanofluid contrast agents have potential to enhance seismic delineation of subsurface fluids and structures.

Miller, Quin RS↗
DOE OSTI2015

Intermediate Scale Laboratory Testing to Understand Mechanisms of Capillary and Dissolution Trapping during Injection and Post-Injection of CO 2 in Heterogeneous Geological Formations

Carbon Capture and Storage (CCS) represents a technology aimed to reduce atmospheric loading of CO 2 from power plants and heavy industries by injecting it into deep geological formations, such as saline aquifers. A number of trapping mechanisms contribute to effective and secure storage of the injected CO 2 in supercritical fluid phase (scCO 2 ) in the formation over the long term. The primary trapping mechanisms are structural, residual, dissolution and mineralization. Knowledge gaps exist on how the heterogeneity of the formation manifested at all scales from the pore to the site scales affects trapping and parameterization of contributing mechanisms in models. An experimental and modeling study was conducted to fill these knowledge gaps. Experimental investigation of fundamental processes and mechanisms in field settings is not possible as it is not feasible to fully characterize the geologic heterogeneity at all relevant scales and gathering data on migration, trapping and dissolution of scCO 2 . Laboratory experiments using scCO 2 under ambient conditions are also not feasible as it is technically challenging and cost prohibitive to develop large, two- or three-dimensional test systems with controlled high pressures to keep the scCO 2 as a liquid. Hence, an innovative approach that used surrogate fluids in place of scCO 2 and formation brine in multi-scale, synthetic aquifers test systems ranging in scales from centimeter to meter scale developed used. New modeling algorithms were developed to capture the processes controlled by the formation heterogeneity, and they were tested using the data from the laboratory test systems. The results and findings are expected to contribute toward better conceptual models, future improvements to DOE numerical codes, more accurate assessment of storage capacities, and optimized placement strategies. This report presents the experimental and modeling methods and research results.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Data-Driven Learning of Non-Autonomous Systems

We present a numerical framework for recovering unknown non-autonomous dynamical systems with time-dependent inputs. To circumvent the difficulty presented by the non-autonomous nature of the system, our method transforms the solution state into piecewise integration of the system over a discrete set of time instances. The time-dependent inputs are then locally parameterized by using a proper model, for example, polynomial regression, in the pieces determined by the time instances. This transforms the original system into a piecewise parametric system that is locally time invariant. We then design a deep neural network structure to learn the local models. Once the network model is constructed, it can be iteratively used over time to conduct global system prediction. We provide theoretical analysis of our algorithm and present a number of numerical examples to demonstrate the effectiveness of the method.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Micro2Macro: Origins of Climate Change Uncertainty

Where we are: Global Earth system models (ESMs) are essential tools for seasonal-to decadal environmental predictions, which decision-makers across government and industry require. However, uncertainties originating at the microphysical scale, i.e., in processes occurring on scales smaller than typical ESM grid boxes, remain a major challenge. While resolution continues to improve in our predictive models, we will need to parameterize microphysical processes that contribute the bulk of prediction uncertainty for the foreseeable future. Microphysical uncertainties contribute broadly to remaining limitations on Earth system predictability on seasonal and decadal time scales.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Editorial for Special Issue “Environmentally Sound In Situ Recovery Mining of Uranium”

This Special Issue features seven articles that cover a range of topics pertaining to the environmentally sound in situ recovery mining of uranium (U ISR). The topics include: (1) methods for assessing the potential environmental impacts of future U ISR operations using historical operational records and available geohydrologic, geochemical and climate data in a specific regional setting; (2) laboratory column studies to parameterize a uranium surface complexation model that can be used to predict uranium fate and transport in groundwater; and (3) a field evaluation of both a chemical reductant and a biostimulant to promote reducing geochemical conditions after oxidative mining at a U ISR facility.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Influences of emission sources and meteorology on aerosol chemistry in a polluted urban environment: results from DISCOVER-AQ California

Abstract. The San Joaquin Valley (SJV) in California experiences persistent air-quality problems associated with elevated particulate matter (PM) concentrations due to anthropogenic emissions, topography, and meteorological conditions. Thus it is important to unravel the various sources and processes that affect the physicochemical properties of PM in order to better inform pollution abatement strategies and improve parameterizations in air-quality models. During January and February 2013, a ground supersite was installed at the Fresno–Garland California Air Resources Board (CARB) monitoring station, where comprehensive, real-time measurements of PM and trace gases were performed using instruments including an Aerodyne high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) and an Ionicon proton transfer reaction time-of-flight mass spectrometer (PTR-TOF-MS) as part of the NASA Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) campaign. The average submicron aerosol (PM1) concentration was 31.0 µg m−3 and the total mass was dominated by organic aerosols (OA, 55 %), followed by ammonium nitrate (35 %). High PM pollution events were commonly associated with elevated OA concentrations, mostly from primary sources. Organic aerosols had average atomic oxygen-to-carbon (O / C), hydrogen-to-carbon (H / C), and nitrogen-to-carbon (N / C) ratios of 0.42, 1.70, and 0.017, respectively. Six distinct sources of organic aerosol were identified from positive matrix factorization (PMF) analysis of the AMS data: hydrocarbon-like OA (HOA; 9 % of total OA, O / C = 0.09) associated with local traffic, cooking OA (COA; 18 % of total OA, O / C = 0.19) associated with food cooking activities, two biomass burning OA (BBOA1: 13 % of total OA, O / C = 0.33; BBOA2: 20 % of total OA, O / C = 0.60) most likely associated with residential space heating from wood combustion, and semivolatile oxygenated OA (SV-OOA; 16 % of total OA, O / C = 0.63) and low-volatility oxygenated OA (LV-OOA; 24 % of total OA, O / C = 0.90) formed via chemical reactions in the atmosphere. Large differences in aerosol chemistry at Fresno were observed between the current campaign (winter 2013) and a previous campaign in winter 2010, most notably that PM1 concentrations were nearly 3 times higher in 2013 than in 2010. These variations were attributed to differences in the meteorological conditions, which influenced primary emissions and secondary aerosol formation. In particular, COA and BBOA concentrations were greater in 2013 than 2010, where colder temperatures in 2013 likely resulted in increased biomass burning activities. The influence from a nighttime formed residual layer that mixed down in the morning was found to be much more intense in 2013 than 2010, leading to sharp increases in ground-level concentrations of secondary aerosol species including nitrate, sulfate, and OOA, in the morning between 08:00 and 12:00 PST. This is an indication that nighttime chemical reactions may have played a more important role in 2013. As solar radiation was stronger in 2013 the higher nitrate and OOA concentrations in 2013 could also be partly due to greater photochemical production of secondary aerosol species. The greater solar radiation and larger range in temperature in 2013 also likely led to both SV-OOA and LV-OOA being observed in 2013 whereas only a single OOA factor was identified in 2010.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Ice particle production in mid-level stratiform mixed-phase clouds observed with collocated A-Train measurements

Abstract. Collocated A-Train CloudSat radar and CALIPSO lidar measurements between 2006 and 2010 are analyzed to study primary ice particle production characteristics in mid-level stratiform mixed-phase clouds on a global scale. For similar clouds in terms of cloud top temperature and liquid water path, Northern Hemisphere latitude bands have layer-maximum radar reflectivity (ZL) that is ∼ 1 to 8 dBZ larger than their counterparts in the Southern Hemisphere. The systematically larger ZL under similar cloud conditions suggests larger ice number concentrations in mid-level stratiform mixed-phase clouds over the Northern Hemisphere, which is possibly related to higher background aerosol loadings. Furthermore, we show that springtime northern mid- and high latitudes have ZL that is larger by up to 6 dBZ (a factor of 4 higher ice number concentration) than other seasons, which might be related to more dust events that provide effective ice nucleating particles. Our study suggests that aerosol-dependent ice number concentration parameterizations are required in climate models to improve mixed-phase cloud simulations, especially over the Northern Hemisphere.

47 OTHER INSTRUMENTATION↗
DOE OSTI2023

Rapid saturation of cloud water adjustments to shipping emissions

Abstract. Human aerosol emissions change cloud properties by providing additional cloud condensation nuclei. This increases cloud droplet numbers, which in turn affects other cloud properties like liquid-water content and ultimately cloud albedo. These adjustments are poorly constrained, making aerosol effects the most uncertain part of anthropogenic climate forcing. Here we show that cloud droplet number and water content react differently to changing emission amounts in shipping exhausts. We use information about ship positions and modeled emission amounts together with reanalysis winds and satellite retrievals of cloud properties. The analysis reveals that cloud droplet numbers respond linearly to emission amount over a large range (1–10 kg h−1) before the response saturates. Liquid water increases in raining clouds, and the anomalies are constant over the emission ranges observed. There is evidence that this independence of emissions is due to compensating effects under drier and more humid conditions, consistent with suppression of rain by enhanced aerosol. This has implications for our understanding of cloud processes and may improve the way clouds are represented in climate models, in particular by changing parameterizations of liquid-water responses to aerosol.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Improved observations of turbulence dissipation rates from wind profiling radars

Observations of turbulence dissipation rates in the planetary boundary layer are crucial for validation of parameterizations in numerical weather prediction models. However, because dissipation rates are difficult to obtain, they are infrequently measured through the depth of the boundary layer. For this reason, demonstrating the ability of commonly used wind profiling radars (WPRs) to estimate this quantity would be greatly beneficial. During the XPIA field campaign at the Boulder Atmospheric Observatory, two WPRs operated in an optimized configuration, using high spectral resolution for increased accuracy of Doppler spectral width, specifically chosen to estimate turbulence from a vertically pointing beam. Multiple post-processing techniques, including different numbers of spectral averages and peak processing algorithms for calculating spectral moments, were evaluated to determine the most accurate procedures for estimating turbulence dissipation rates using the information contained in the Doppler spectral width, using sonic anemometers mounted on a 300 m tower for validation. Furthermore, the optimal settings were determined, producing a low bias, which was later corrected. Resulting estimations of turbulence dissipation rates correlated well ( R 2 = 0.54 and 0.41) with the sonic anemometers, and profiles up to 2 km from the 449 MHz WPR and 1 km from the 915 MHz WPR were observed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Evaluation of a high-resolution regional climate simulation for surface and hub-height wind climatology over North America

Assessing the availability of key wind resources requires augmenting observations to support the implementation of wind energy infrastructure. However, observations are limited, necessitating the development of high-resolution, long-term gridded datasets. This study presents a robust, dynamically downscaled climatological dataset, offering 20 years of hourly wind data at a 4 km spatial resolution across North America, and evaluates its performance against observations, including meteorological towers and automated surface-observing system (ASOS) stations, as well as coarse-resolution reanalysis data (the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis version 5 (ERA5)). Results demonstrate that the downscaled high-resolution wind data outperform ERA5 in regions of complex terrain and coastal areas, with improved overlap coefficients for wind data distributions and reduced root mean square errors (RMSEs) for hub-height and near-surface diurnal wind patterns. The downscaled simulation also captures the synoptic drivers of seasonal wind direction patterns reasonably well, indicated by high wind rose similarity indices. This study also provides an analysis of interannual variability, utilizing the dataset's full 20-year period, and model uncertainty, generated by varying model initial conditions and physics parameterizations across 1-year ensemble members, which are key considerations for wind resource assessment in wind farm development.

17 WIND ENERGY↗