Comparison of measured and simulated concentrations of 133Xe in the shallow subsurface
Not Available
Johnson, C.↗
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Results for “Shallow”
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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Quantifying small changes in uranium oxidation states using XPS of a shallow core level
Quantification of U( iv ), U( v ), and U( vi ) in UO 2+x using the 5d XPS.
Ilton, Eugene S.↗
Discriminating a deep defect from shallow acceptors in supercell calculations: Gallium antisite in GaAs.
Abstract not provided.
Schultz, Peter A.↗
Neutrino cross sections: Interface of shallow- and deep-inelastic scattering for collider neutrinos
Not Available
Jeong, Yu Seon (ORCID:0000000231634810)↗
Techno-Economic Analysis and Market Potential of Geological Thermal Energy Storage (GeoTES) Charged With Solar Thermal and Heat Pumps into Depleted Oil/Gas Reservoirs and Shallow Reservoirs: A Technology Overview: Preprint
Depleted oil/gas reservoirs represent a waste of underground resources and investments of drilling, and also a potential risk to the earth's environment. Geologic thermal energy storage (GeoTES) is proposed as a solution to convert depleted oil/gas reservoirs into long-term seasonal energy storage. GeoTES can be hybridized with other techniques for viable commercial deployment, such as 1) concentrating solar power (CSP) collectors and 2) heat pumps with excess renewable energy. Here, a technology overview is given on the two GeoTES technologies, which includes system overview, techno-economic models, and case study. Both GeoTES technologies show great potential in the economics of individual project deployment and applicability across the US.
concentrating solar power↗
A Generalized Interpolation Material Point Method for Shallow Ice Shelves. 1: Shallow Shelf Approximation and Ice Thickness Evolution
Explore the source record for details and available documents.
Alex Huth↗
Simulation of Shallow Cumuli and Their Transition to Deep Convective Clouds by Cloud-resolving Models with Different Third-order Turbulence Closures
The abilities of cloud-resolving models (CRMs) with the double-Gaussian based and the single-Gaussian based third-order closures (TOCs) to simulate the shallow cumuli and their transition to deep convective clouds are compared in this study. The single-Gaussian based TOC is fully prognostic (FP), while the double-Gaussian based TOC is partially prognostic (PP). The latter only predicts three important third-order moments while the former predicts all the thirdorder moments. A shallow cumulus case is simulated by single-column versions of the FP and PP TOC models. The PP TOC improves the simulation of shallow cumulus greatly over the FP TOC by producing more realistic cloud structures. Large differences between the FP and PP TOC simulations appear in the cloud layer of the second- and third-order moments, which are related mainly to the underestimate of the cloud height in the FP TOC simulation. Sensitivity experiments and analysis of probability density functions (PDFs) used in the TOCs show that both the turbulence-scale condensation and higher-order moments are important to realistic simulations of the boundary-layer shallow cumuli. A shallow to deep convective cloud transition case is also simulated by the 2-D versions of the FP and PP TOC models. Both CRMs can capture the transition from the shallow cumuli to deep convective clouds. The PP simulations produce more and deeper shallow cumuli than the FP simulations, but the FP simulations produce larger and wider convective clouds than the PP simulations. The temporal evolutions of cloud and precipitation are closely related to the turbulent transport, the cold pool and the cloud-scale circulation. The large amount of turbulent mixing associated with the shallow cumuli slows down the increase of the convective available potential energy and inhibits the early transition to deep convective clouds in the PP simulation. When the deep convective clouds fully develop and the precipitation is produced, the cold pools produced by the evaporation of the precipitation are not favorable to the formation of shallow cumuli.
Cheng, Anning↗
A moist Boussinesq shallow water equations set for testing atmospheric models
The shallow water equations have long been used as an initial test for numerical methods applied to atmospheric models with the test suite of Williamson et al. being used extensively for validating new schemes and assessing their accuracy. However the lack of physics forcing within this simplified framework often requires numerical techniques to be reworked when applied to fully three dimensional models. In this paper a novel two-dimensional shallow water equations system that retains moist processes is derived. This system is derived from three-dimensional Boussinesq approximation of the hydrostatic Euler equations where, unlike the classical shallow water set, we allow the density to vary slightly with temperature. This results in extra (or buoyancy) terms for the momentum equations, through which a two-way moist-physics dynamics feedback is achieved. The temperature and moisture variables are advected as separate tracers with sources that interact with the mean-flow through a simplified yet realistic bulk moist-thermodynamic phase-change model. This moist shallow water system provides a unique tool to assess the usually complex and highly non-linear dynamics–physics interactions in atmospheric models in a simple yet realistic way. The full non-linear shallow water equations are solved numerically on several case studies and the results suggest quite realistic interaction between the dynamics and physics and in particular the generation of cloud and rain. - Highlights: • Novel shallow water equations which retains moist processes are derived from the three-dimensional hydrostatic Boussinesq equations. • The new shallow water set can be seen as a more general one, where the classical equations are a special case of these equations. • This moist shallow water system naturally allows a feedback mechanism from the moist physics increments to the momentum via buoyancy. • Like full models, temperature and moistures are advected as tracers that interact through a simplified yet realistic phase-change model. • This model is a unique tool to test numerical methods for atmospheric models, and physics–dynamics coupling, in a very realistic and simple way.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
The roll-up and merging of coherent structures in shallow mixing layers
The current study seeks a fundamental explanation to the development of two-dimensional coherent structures (2DCSs) in shallow mixing layers. A nonlinear numerical model based on the depth-averaged shallow water equations is used to investigate the temporal evolution of shallow mixing layers, where the mapping from temporal to spatial results is made using the velocity at the center of the mixing layers. The flow is periodic in the streamwise direction. Transmissive boundary conditions are used in the cross-stream boundaries to prevent reflections. Numerical results are compared to linear stability analysis, mean-field theory, and secondary stability analysis. Results suggest that the onset and development of 2DCS in shallow mixing layers are the result of a sequence of instabilities governed by linear theory, mean-field theory, and secondary stability theory. The linear instability of the shearing velocity gradient gives the onset of 2DCS. When the perturbations reach a certain amplitude, the flow field of the perturbations changes from a wavy shape to a vortical (2DCS) structure because of nonlinearity. The development of the vertical 2DCS does not appear to follow weakly nonlinear theory; instead, it follows mean-field theory. After the formation of 2DCS, separate 2DCSs merge to form larger 2DCS. In this way, 2DCSs grow and shallow mixing layers develop and grow in scale. The merging of 2DCS in shallow mixing layers is shown to be caused by the secondary instability of the 2DCS. Eventually 2DCSs are dissipated by bed friction. The sequence of instabilities can cause the upscaling of the turbulent kinetic energy in shallow mixing layers.
42 ENGINEERING↗
Shallow Soil Polychlorinated Biphenyl Site Assessment Report
This report presents a summary of the shallow soil polychlorinated biphenyl (PCB) site assessment activities that occurred from December 2020 through July 2022 at General Services Administration Reclamation Yard, Solid Waste Management Unit (SWMU) 010, located at the John F. Kennedy Space Center (KSC), Florida. The site is monitored under KSC’s Resource Conservation and Recovery Act Corrective Action Program, which also meets the requirements of Chapter 62-780, Florida Administrative Code. For the purposes of this report, three separate shallow soil plumes, known as the Northeast Shallow Soil PCB Plume, Southeast Shallow Soil PCB Plume, and West Shallow Soil PCB Plume, were identified for this site. The activities presented in this report include seven field events conducted between December 2020 and July 2022, which include shallow soil sample collection in the Northeast, Southeast, and West Shallow Soil PCB Plumes. AECOM Technical Services, Inc., personnel collected 330 soil samples from 118 boring locations. The samples were collected at 0.5-foot depth intervals to various depths based on analytical results and depth to groundwater. The soil samples were submitted to a fixed-based laboratory for analysis by United States Environmental Protection Agency Method 8082A for total PCBs. Several soil samples had PCB concentrations above the State of Florida Direct Exposure Residential and Industrial Soil Cleanup Target Levels (SCTLs), and two soil samples had PCB concentrations above the State of Florida Leachability for Groundwater. No soil borings were located beneath impervious surfaces, such as concrete or asphalt. The current Land Use Control Implementation Plan (LUCIP) covers PCBs in soils above the residential SCTL, which includes the paved areas.
PCBs↗
Shallow Soil Polychlorinated Biphenyl Site Assessment Report: General Services Administration Reclamation Yard Solid Waste Management Unit 010
This report presents a summary of the shallow soil polychlorinated biphenyl (PCB) site assessment activities that occurred from December 2020 through July 2022 at General Services Administration Reclamation Yard, Solid Waste Management Unit (SWMU) 010, located at the John F. Kennedy Space Center (KSC), Florida. The site is monitored under KSC’s Resource Conservation and Recovery Act Corrective Action Program, which also meets the requirements of Chapter 62-780, Florida Administrative Code. For the purposes of this report, three separate shallow soil plumes, known as the Northeast Shallow Soil PCB Plume, Southeast Shallow Soil PCB Plume, and West Shallow Soil PCB Plume, were identified for this site. The activities presented in this report include seven field events conducted between December 2020 and July 2022, which include shallow soil sample collection in the Northeast, Southeast, and West Shallow Soil PCB Plumes. AECOM Technical Services, Inc., personnel collected 330 soil samples from 118 boring locations. The samples were collected at 0.5-foot depth intervals to various depths based on analytical results and depth to groundwater. The soil samples were submitted to a fixed-based laboratory for analysis by United States Environmental Protection Agency Method 8082A for total PCBs. Several soil samples had PCB concentrations above the State of Florida Direct Exposure Residential and Industrial Soil Cleanup Target Levels (SCTLs), and two soil samples had PCB concentrations above the State of Florida Leachability for Groundwater. No soil borings were located beneath impervious surfaces, such as concrete or asphalt. The current Land Use Control Implementation Plan (LUCIP) covers PCBs in soils above the residential SCTL, which includes the paved areas.
soil assessment↗
Towards district scale flood simulations using conventional and anisotropic porosity shallow water models with high-resolution topographic information
Current topographic survey technology provides high-resolution (HR) datasets for urban environments. Incorporating this HR information in models aiming to provide flood risk assessment is desirable because the flood wave propagation is depending on the urban topographic features, i.e. buildings, bridges and street networks. Conceptual, numerical and practical challenges arise from the application of shallow water models to HR urban flood modeling. For example, numerical challenges are occurrence of wet-dry fronts, geometric discontinuities in the urban environment and discontinuous solutions, i.e. shock waves. These challenges can be overcome by using a Godunov-type scheme. However, the computational cost of this type of schemes is high, such that HR two-dimensional shallow water simulations with practical relevance have to be run on supercomputers. The porous shallow water model is an alternative approach that aims to reduce computational cost by using a coarse resolution and accounting for unresolved processes by means of the porosity terms. Usually, a speedup between two and three orders of magnitude in comparison to HR simulations can be obtained. This study presents preliminary results of a practical test case concerning pluvial flooding in a district of the city of Nice, France, caused by the intense rainfall event on October 3rd, 2015. HR topography data set on a 1 m resolution is available for the district, whereby street features of infra-metric dimensions have been included. A reference solution is calculated by a HR shallow water model on a 1 m by 1 m structured computational grid. The porous shallow water model is run on a 10 m by 10 m grid and the influence of the drag source term is studied. The model calculations show a large deviation, which is caused by the poor meshing strategy of the porous shallow water (AP) model. The study also summarizes practical challenges that arise during the application of the AP and HR models to a large urban catchment. The main difficulty is to obtain a good mesh. In smaller scale investigations, the mesh is currently constructed by hand such that the cell edges align with buildings. This approach is not feasible for large scale urban catchments with a large number of buildings. Future steps that have to be taken, such as a strategy for automatic mesh generation, are reported on.
42 ENGINEERING↗
SWIM: A Semi-Analytical Ocean Color Inversion Algorithm for Optically Shallow Waters
In clear shallow waters, light that is transmitted downward through the water column can reflect off the sea floor and thereby influence the water-leaving radiance signal. This effect can confound contemporary ocean color algorithms designed for deep waters where the seafloor has little or no effect on the water-leaving radiance. Thus, inappropriate use of deep water ocean color algorithms in optically shallow regions can lead to inaccurate retrievals of inherent optical properties (IOPs) and therefore have a detrimental impact on IOP-based estimates of marine parameters, including chlorophyll-a and the diffuse attenuation coefficient. In order to improve IOP retrievals in optically shallow regions, a semi-analytical inversion algorithm, the Shallow Water Inversion Model (SWIM), has been developed. Unlike established ocean color algorithms, SWIM considers both the water column depth and the benthic albedo. A radiative transfer study was conducted that demonstrated how SWIM and two contemporary ocean color algorithms, the Generalized Inherent Optical Properties algorithm (GIOP) and Quasi-Analytical Algorithm (QAA), performed in optically deep and shallow scenarios. The results showed that SWIM performed well, whilst both GIOP and QAA showed distinct positive bias in IOP retrievals in optically shallow waters. The SWIM algorithm was also applied to a test region: the Great Barrier Reef, Australia. Using a single test scene and time series data collected by NASA's MODIS-Aqua sensor (2002-2013), a comparison of IOPs retrieved by SWIM, GIOP and QAA was conducted.
shallow waters↗
A Type–Curve Approach for Evaluating Aquifer Properties by Interpreting Shallow Strain Measured During Well Tests
Strains occur at shallow depths in response to pressure changes during well tests in an underlying aquifer, and recent developments in instrumentation have made it feasible to measure essentially the full strain tensor. Simulations using poroelastic analyses indicate that shallow normal strains are approximately proportional to the logarithm of time when a well is injecting into or pumping from a deep aquifer or reservoir. The drawdown is also a linear function of log time, as shown by the classic Cooper-Jacob type-curve analysis. The time when the semilog straight line intercepts the zero-strain axis is similar to the time determined from the Cooper-Jacob pressure analysis, and it can be used to estimate hydraulic diffusivity, suggesting that horizontal strain data can be used directly to estimate aquifer properties. This approach was validated using measurements from shallow (30-m deep) borehole strainmeters during an injection test at a 530-m-deep sandstone aquifer/reservoir in Oklahoma. The results show intercept times for the shallow normal strain data are essentially the same as for deep pressure data from an equivalent radial distance. The slopes of the semilog plots of the pressure and the strain increase at the same time, suggesting that they both respond to a lateral aquifer boundary. Significantly, though, strain was measured at shallow depths while the pressure data were measured at 530-m depth. This suggests that strain data from shallow depths could be an effective way to improve the characterization of an underlying aquifer.
54 ENVIRONMENTAL SCIENCES↗
Downward Convective Moisture Transport Dominated by a Few Overshooting Clouds in Marine and Continental Shallow Convection
Abstract In a previous study (Xiao et al., 2023, https://doi.org/10.1029/2022ms003526 ), we found that ignoring the moist convective downdrafts associated with overshooting clouds in parameterizations can lead to significant biases in the simulated depth and liquid water content of a shallow cloud layer. In this study, we seek to better quantify the properties of the clouds responsible for these moist downdrafts to help improve shallow convection parameterizations. We apply a 3‐D cloud‐tracking algorithm to large‐eddy simulations (LESs) of marine and continental shallow convection. We find that top 1% and 2% of the tracked cloud population ranked by lifetime‐mean cloud‐base mass flux can explain 90%–95% of the total downward moisture transport in the upper cloud layer whereas top 10%–20% is required to explain 90%–95% of the total upward moisture transport near mean cloud base. The vertical structure of the clouds in the top 1% and 2% (the overshooting “deep mode”) is also distinctively different from that of the rest of the cloud population (the “shallow mode”). Shallow convection parameterizations need to capture accurately the properties and convective transports of the clouds in both the deep and shallow modes. To do that, our results suggest that mass‐flux parameterizations need to (a) accurately predict the size and number of the deep‐mode clouds and (b) explicitly represent overshooting cloud updrafts and associated moist downdrafts.
54 ENVIRONMENTAL SCIENCES↗
SWIM: A Semi-Analytical Ocean Color Inversion Algorithm for Optically Shallow Waters
Ocean color remote sensing provides synoptic-scale, near-daily observations of marine inherent optical properties (IOPs). Whilst contemporary ocean color algorithms are known to perform well in deep oceanic waters, they have difficulty operating in optically clear, shallow marine environments where light reflected from the seafloor contributes to the water-leaving radiance. The effect of benthic reflectance in optically shallow waters is known to adversely affect algorithms developed for optically deep waters [1, 2]. Whilst adapted versions of optically deep ocean color algorithms have been applied to optically shallow regions with reasonable success [3], there is presently no approach that directly corrects for bottom reflectance using existing knowledge of bathymetry and benthic albedo.To address the issue of optically shallow waters, we have developed a semi-analytical ocean color inversion algorithm: the Shallow Water Inversion Model (SWIM). SWIM uses existing bathymetry and a derived benthic albedo map to correct for bottom reflectance using the semi-analytical model of Lee et al [4]. The algorithm was incorporated into the NASA Ocean Biology Processing Groups L2GEN program and tested in optically shallow waters of the Great Barrier Reef, Australia. In-lieu of readily available in situ matchup data, we present a comparison between SWIM and two contemporary ocean color algorithms, the Generalized Inherent Optical Property Algorithm (GIOP) and the Quasi-Analytical Algorithm (QAA).
QAA↗
The Impact of Surface Heterogeneities and Land‐Atmosphere Interactions on Shallow Clouds Over ARM SGP Site
Abstract Continental shallow clouds are an important component of the land‐atmosphere coupled climate system because of their role in modulating energy and water budgets. The parameterization of these clouds in climate models presents a significant challenge. We evaluate the potential impact of subgrid‐scale (for climate models) land‐atmosphere interactions on shallow clouds using nested large‐eddy simulations (LESs). We compare LESs that allow for land‐atmosphere interactions to ones that artificially suppress all or part of them by smoothing out surface heterogeneities in surface heat, moisture and radiation fluxes within the domain. The LES domains are coupled to an interactive land surface model and nested inside a mesoscale domain. Three summertime shallow convection cases over the Department of Energy Atmospheric Radiation Measurement Facility's Southern Great Plains site are examined. A consistent increase in cloud water content is observed in all cases when surface heterogeneities and the land‐atmosphere interactions they induce in the LES domain are removed. By comparing experiments where only surface flux heterogeneities induced by cloud shadows are removed to ones where all surface flux heterogeneities are removed, we find that cloud shading‐induced surface heterogeneities can have a larger impact on shallow convection than static land surface heterogeneities in our cases. Furthermore, the impact of cloud shading on cloud water content and cloud size is found to vary significantly with the solar incidence angle. Our results suggest that the impact of cloud shadows needs to be considered when parameterizing land‐atmosphere interactions in the presence of shallow clouds for regional or global climate models.
54 ENVIRONMENTAL SCIENCES↗