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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Environmental sensitivities of shallow-cumulus dilution – Part 1: Selected thermodynamic conditions

Cumulus entrainment, and its consequent dilution of buoyant cloud cores, strongly regulates the life cycle of shallow cumuli yet remains poorly understood. Herein, new insights into this problem are obtained through large-eddy simulations that systematically investigate the sensitivity of shallow-cumulus dilution to cloud-layer relative humidity (RH), cloud- and subcloud-layer depths, and continentality (i.e., the land–ocean contrast). The simulated cloud-core dilution is found to be strongly sensitive to continentality, with fractional dilution rates twice as large over the ocean as over land. Using a similarity theory based on the turbulent-kinetic-energy (TKE) budget, the reduced cloud-core dilution over land is attributed to larger cloud-base mass flux (mb), driven by stronger surface heating and subcloud turbulence. As mb increases, the fractional dilution rate must decrease to maintain energetic equilibrium. A positive sensitivity is also found to cloud-layer RH, with the core dilution increasing by 25 %–50 % for a 10 % enhancement in RH. This sensitivity is interpreted using the buoyancy-sorting hypothesis, in that mixtures of cloud and environmental air are more likely to become negatively buoyant and detrain (rather than diluting the cloud core) in drier cloud layers. By contrast, the sensitivities of (marine) shallow-cumulus dilution to cloud- and subcloud-layer depths are weak, with a 3 % decrease for a doubling for the former and a 4 % reduction in dilution for a 50 % deeper subcloud layer. These surprisingly weak sensitivities are readily explained by offsetting effects in the TKE similarity theory. Altogether, these experimental findings provide useful, though still incomplete, guidance for flow-dependent shallow-cumulus entrainment formulations in large-scale models.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1981

Vibrations of cantilevered shallow cylindrical shells of rectangular planform

A cantilevered, shallow shell of circular cylindrical curvature and rectangular planform exhibits free vibration behavior which differs considerably from that of a cantilevered beam or of a flat plate. Some numerical results can be found for the problem in the previously published literature, mainly obtained by using various finite element methods. The present paper is the first definitive study of the problem, presenting accurate non-dimensional frequency parameters for wide ranges of aspect ratio, shallowness ratio and thickness ratio. The analysis is based upon shallow shell theory. Numerical results are obtained by using the Ritz method, with algebraic polynomial trial functions for the displacements. Convergence is investigated, with attention being given both to the number of terms taken for each co-ordinate direction and for each of the three components of displacement. Accuracy of the results is also established by comparison with finite element results for shallow shells and with other accurate flat plate solutions.

Leissa, A. W.↗
NASA NTRS1980

Shallow moonquakes - How they compare with earthquakes

Of three types of moonquakes strong enough to be detectable at large distances - deep moonquakes, meteoroid impacts and shallow moonquakes - only shallow moonquakes are similar in nature to earthquakes. A comparison of various characteristics of moonquakes with those of earthquakes indeed shows a remarkable similarity between shallow moonquakes and intraplate earthquakes: (1) their occurrences are not controlled by tides; (2) they appear to occur in locations where there is evidence of structural weaknesses; (3) the relative abundances of small and large quakes (b-values) are similar, suggesting similar mechanisms; and (4) even the levels of activity may be close. The shallow moonquakes may be quite comparable in nature to intraplate earthquakes, and they may be of similar origin.

Nakamura, Y.↗
NASA NTRS2001

Numerical Study of the Role of Shallow Convection in Moisture Transport and Climate

The objective of this investigation was to study the role of shallow convection on the regional water cycle of the Mississippi and Little Washita Basins of the Southern Great Plains (SGP) using a 3-D mesoscale model, the PSU/NCAR MM5. The underlying premise of the project was that current modeling of regional-scale climate and moisture cycles over the continents is deficient without adequate treatment of shallow convection. At the beginning of the study, it was hypothesized that an improved treatment of the regional water cycle can be achieved by using a 3-D mesoscale numerical model having high-quality parameterizations for the key physical processes controlling the water cycle. These included a detailed land-surface parameterization (the Parameterization for Land-Atmosphere-Cloud Exchange (PLACE) sub-model of Wetzel and Boone), an advanced boundary-layer parameterization (the 1.5-order turbulent kinetic energy (TKE) predictive scheme of Shafran et al.), and a more complete shallow convection parameterization (the hybrid-closure scheme of Deng et al.) than are available in most current models. PLACE is a product of researchers working at NASA's Goddard Space Flight Center in Greenbelt, MD. The TKE and shallow-convection schemes are the result of model development at Penn State. The long-range goal is to develop an integrated suite of physical sub-models that can be used for regional and perhaps global climate studies of the water budget. Therefore, the work plan focused on integrating, improving, and testing these parameterizations in the MM5 and applying them to study water-cycle processes over the SGP. These schemes have been tested extensively through the course of this study and the latter two have been improved significantly as a consequence.

Seaman, Nelson L.↗
NASA NTRS2015

RACORO Continental Boundary Layer Cloud Investigations: 3. Separation of Parameterization Biases in Single-Column Model CAM5 Simulations of Shallow Cumulus

Climatically important low-level clouds are commonly misrepresented in climate models. The FAst-physics System TEstbed and Research (FASTER) Project has constructed case studies from the Atmospheric Radiation Measurement Climate Research Facility's Southern Great Plain site during the RACORO aircraft campaign to facilitate research on model representation of boundary-layer clouds. This paper focuses on using the single-column Community Atmosphere Model version 5 (SCAM5) simulations of a multi-day continental shallow cumulus case to identify specific parameterization causes of low-cloud biases. Consistent model biases among the simulations driven by a set of alternative forcings suggest that uncertainty in the forcing plays only a relatively minor role. In-depth analysis reveals that the model's shallow cumulus convection scheme tends to significantly under-produce clouds during the times when shallow cumuli exist in the observations, while the deep convective and stratiform cloud schemes significantly over-produce low-level clouds throughout the day. The links between model biases and the underlying assumptions of the shallow cumulus scheme are further diagnosed with the aid of large-eddy simulations and aircraft measurements, and by suppressing the triggering of the deep convection scheme. It is found that the weak boundary layer turbulence simulated is directly responsible for the weak cumulus activity and the simulated boundary layer stratiform clouds. Increased vertical and temporal resolutions are shown to lead to stronger boundary layer turbulence and reduction of low-cloud biases.

parameterization↗
NASA NTRS2017

Shallow Lunar Seismic Activity and the Current Stress State of the Moon

A vast, global network of more than 3200 lobate thrust fault scarps has been revealed in high resolution Lunar Reconnaissance Orbiter Camera (LROC) images. The fault scarps very young, less than 50 Ma, based on their small scale and crisp appearance, crosscutting relations with small-diameter impact craters, and rates of infilling of associated small, shallow graben and may be actively forming today. The population of young thrust fault scarps provides a window into the recent stress state of the Moon and offers insight into the origin of global lunar stresses. The distribution of orientations of the fault scarps is non-random, inconsistent with isotropic stresses from late-stage global contraction as the sole source of stress Modeling shows that tidal stresses contribute significantly to the current stress state of the lunar crust. Tidal stresses (orbital recession and diurnal tides) superimposed on stresses from global contraction result in non-isotropic compressional stress and thrust faults consistent with lobate scarp orientations. Stresses due to orbital recession do not change with orbital position, thus it is with the addition of diurnal stresses that peak stresses are reached. At apogee, diurnal and recession stresses are most compressive near the tidal axis, while at perigee they are most compressive 90 degrees away from the tidal axis. Coseismic slip events on currently active thrust faults are expected to be triggered when peak stresses are reached. Analysis of the timing of the 28 the shallow moonquakes recorded by the Apollo seismic network shows that 19 indeed occur when the Moon is closer to apogee, while only 9 shallow events occur when the Moon is closer to perigee. Here we show the results of relocating the shallow moonquake using an algorithm designed for sparse networks to better constrain their epicentral locations in order to compare them with stress models. The model for the current stress state of the Moon is refined by investigating the contribution of polar wander.

siesmology↗
NASA NTRS2017

Shallow Lunar Seismic Activity and the Current Stress State of the Moon

A vast, global network of more than 3200 lobate thrust fault scarps has been revealed in high resolution Lunar Reconnaissance Orbiter Camera (LROC) images. The fault scarps are very young, less than 50 Ma, based on their small scale and crisp appearance, crosscutting relations with small-diameter impact craters, and rates of infilling of associated small, shallow graben and may be actively forming today. The population of young thrust fault scarps provides a window into the recent stress state of the Moon and offers insight into the origin of global lunar stresses. The distribution of orientations of the fault scarps is non-random, inconsistent with isotropic stresses from late-stage global contraction as the sole source of stress. Modeling shows that tidal stresses contribute significantly to the current stress state of the lunar crust. Tidal stresses (orbital recession and diurnal tides) superimposed on stresses from global contraction result in non-isotropic compressional stress and may produce thrust faults consistent with lobate scarp orientations. At any particular point on the lunar surface, peak compressive stress will be reached at a certain time in the diurnal cycle. Coseismic slip events on currently active thrust faults are expected to be triggered when peak stresses are reached. Analysis of the timing of the 28 the shallow moonquakes recorded by the Apollo seismic network shows that 19 indeed occur when the Moon is closer to apogee, while only 9 shallow events occur when the Moon is closer to perigee. Here we report efforts to refine the model for the current stress state of the Moon by investigating the contribution of polar wander. Progress on relocating the epicentral locations of the shallow moonquakes using an algorithm designed for sparse networks is also reported.

structure↗
NASA NTRS2020

Determining the Shallow Surface Velocity at the Apollo 17 Landing Site

Many studies have been performed to determine the shallow surface velocity model at the Apollo 17 landing site. The Lunar Seismic Profiling Experiment (LSPE) had both an active component with eight explosive packages (EPs) and a passive experiment collecting data at various time intervals. Using the eight EPs, the initial shallow surface velocity model was determined to be 250 m/s in the first layer of depth 248 m, 1200 m/s with a depth of 927 m in the second layer, and 4000 m/s down to a depth of 2 km in the third layer. Have performed variations on this study to produce new velocity models shown. Recent studies have also been reanalyzing the passive LSPE data and have found three different thermal moonquake event types occurring at different times within the lunar day. The current goal of the project is to collocate the thermal moonquakes to physical surface features to determine the breakdown of lunar rocks. However, to locate shallow surface events, an accurate velocity model is needed. Presented a thermal moonquake location algorithm using first order approximation, including surface events only. To improve these approximations, a shallow surface velocity is needed.

Phillips, D.↗
DOE OSTI2024

Identifying recharge sources and their impacts on a North Central New Mexico shallow aquifer using unsupervised machine learning

In this article, shallow aquifers are important but highly variable resources in arid to semi-arid regions. Limited shallow aquifer volume results in high sensitivity to recharge fluctuations, which can impact the local fauna and flora, and transport of contaminants in the aquifer or vadose zone. Aquifer response to external forcing (e.g., precipitation) is usually solved by estimating aquifer parameters and running physics-based models to match known fluctuations of hydraulic head. However, this technique is time and computationally expensive. Furthermore, high aquifer complexity decreases precision in physics-based models. Alternatively supervised machine learning is used to predict aquifer dynamics. However, these techniques rely on input data and struggle to interpret aquifer response for missing sources (i.e., snowpack data). To counter these problems, we propose an unsupervised machine learning technique (NMFk) to estimate the impact of different sources on aquifer recharge. NMFk is used to understand the influence of external forcing on shallow aquifer recharge in the Pajarito Plateau (Los Alamos, NM, USA). The results show how NMFk can be used to reduce the data dimension in a complex field dataset to three recharge signals that cause fluctuations within the field data. Here, the source signals are interpreted as rainfall, snowmelt, and a delayed aquifer response to the previous two signals. These results evidence how heterogeneous aquifers delimited by canyons incised into the Pajarito Plateau respond in similar ways to the source signals identified by NMFk. Furthermore, results show the importance of the local geology where faults act as sinks, and anthropogenic disturbances can facilitate infiltration amplifying the interpreted signal.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Comparison of exponential integrators and traditional time integration schemes for the shallow water equations

We report the time integration scheme is probably one of the most fundamental choices in the development of an ocean model. In this paper, we investigate several time integration schemes when applied to the shallow water equations. This set of equations is accurate enough for the modeling of a shallow ocean and is also relevant to study as it is the one solved for the barotropic (i.e. vertically averaged) component of a three dimensional ocean model. We analyze different time stepping algorithms for the linearized shallow water equations. High order explicit schemes are accurate but the time step is constrained by the Courant-Friedrichs-Lewy stability condition. Implicit schemes can be unconditionally stable but, in practice lack accuracy when used with large time steps. In this paper we propose a detailed comparison of such classical schemes with exponential integrators. The accuracy and the computational costs are analyzed in different configurations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Interpreting the Diurnal Cycle of Clouds and Precipitation in the ARM GoAmazon Observations: Shallow to Deep Convection Transition

The Green Ocean Amazon (GoAmazon) 2014/5 field campaign data are used to study the diurnal cycle of clouds and precipitation. Through a careful classification of days with shallow cumulus, congestus and deep convection, we investigate the major differences among locally generated convection regimes and the most important environmental factors governing the shallow-to-deep convection transition. On shallow cumulus days, a greater sensible heat flux drives deeper boundary layer growth, which entrains drier free-tropospheric air and lowers the relative humidity, thus leading to a significantly higher cloud base than those on days with deeper convection. Congestus and deep convection regimes exhibit distinct cloud top height distributions with noticeable differences in the vertical wind shear in the mid-troposphere, suggesting an important role of wind shear in limiting the vertical extent of convection. On deep convection days, with preexisting nocturnal convection or cold-pools from external disturbances, the timing of peak surface precipitation (12:00–13:00 LST) tends to be in-phase with the diurnal variation in surface fluxes. However, it takes longer for local deep convection to develop without these disturbances. A plume model with thermodynamic and dynamical constraints is developed to explore the relative importance of various convection-controlling factors. Initial cloud-base vertical velocity and buoyancy are important in helping parcels ascend to the level of free convection (LFC). After parcels reach the LFC, entrainment of environmental air and lower free troposphere humidity become crucial in determining cloud top. Entrainment rate differentiates among convection regimes, which may be tied to the cloud size distribution at cloud base.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Assessing CLUBB PDF Closure Assumptions for a Continental Shallow-to-Deep Convective Transition Case Over Multiple Spatial Scales

Assumed-PDF (probability density function) higher-order turbulence closures (APHOCs) are now widely used for parameterizing boundary layer turbulence and shallow convection in Earth system models (ESMs). A better understanding of the resolution-dependent behavior of APHOCs is essential for improving the performance of next-generation ESMs with intended horizontal resolutions finer than 10 km. In this study, we evaluate the PDF family of Analytic double-Gaussian 1 implemented in Cloud Layers Unified By Binormals (CLUBB) over a range of spatial scales (Dx) from 2 to 100 km. A 120-km-wide large eddy simulation (LES) for a continental convection case during 2016 Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems (HI-SCALE) field campaign serves as benchmark to evaluate the PDF closure using an off-line approach. We find during the shallow convection period, the CLUBB PDF closure tends to produce positive biases of cloud properties and liquid water flux near cloud base for all scales of analysis. It produces negative biases for these variables near cloud top that are more severe for Dx larger than 25 km. Results show that replacing the CLUBB-parameterized moisture and temperature skewnesses with LES-derived ones can fix most of the biases if clipping of input moments is allowed to prevent the occurrence of unrealizable solutions. Overall, the performance of the PDF closure is better for smaller Dx = 2–5 km than for larger Dx = 50–100 km; for a given grid spacing, it is better when the convective clouds become deeper in the late afternoon. Likely causes for the resolution dependence and implications for improving the PDF closure are discussed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

CFL Optimized Forward–Backward Runge–Kutta Schemes for the Shallow-Water Equations

Abstract We present the formulation and optimization of a Runge–Kutta-type time-stepping scheme for solving the shallow-water equations, aimed at substantially increasing the effective allowable time step over that of comparable methods. This scheme, called FB-RK(3,2), uses weighted forward–backward averaging of thickness data to advance the momentum equation. The weights for this averaging are chosen with an optimization process that employs a von Neumann–type analysis, ensuring that the weights maximize the admittable Courant number. Through a simplified local truncation error analysis and numerical experiments, we show that the method is at least second-order in time for any choice of weights and exhibits low dispersion and dissipation errors for well-resolved waves. Further, we show that an optimized FB-RK(3,2) can take time steps up to 2.8 times as large as a popular three-stage, third-order strong stability-preserving Runge–Kutta method in a quasi-linear test case. In fully nonlinear shallow-water test cases relevant to oceanic and atmospheric flows, FB-RK(3,2) outperforms SSPRK3 in admittable time step by factors roughly between 1.6 and 2.2, making the scheme approximately twice as computationally efficient with little to no effect on solution quality. Significance Statement The purpose of this work is to develop and optimize time-stepping schemes for models relevant to oceanic and atmospheric flows. Specifically, for the shallow-water equations we optimize for schemes that can take time steps as large as possible while retaining solution quality. We find that our optimized schemes can take time steps between 1.6 and 2.2 times larger than schemes that cost the same number of floating point operations, translating directly to a corresponding speedup. Our ultimate goal is to use these schemes in climate-scale simulations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Scrutinizing entrainment and mass flux closures in shallow cumulus parameterizations using cloud-radar observations and large-eddy simulation (Final Report)

Representing warm, shallow clouds is a challenge for Global Climate Models, which leads to uncertainty in model projections of future climate. Our study was particularly concerned with how climate models represent the effects of shallow, non-precipitating cumulus clouds. Climate models must make certain assumptions when representing low clouds such as how much dry air from outside the cloud is mixed into the warm, moist cloud updraft. This process is called “entrainment” and tends to weaken the cloud updraft and dry out the cloud, compared to a theoretical cloud with no mixing. This project was a joint observational and modeling study to derive estimates of entrainment from field observations and use high-resolution modeling to evaluate the assumptions used in climate model representations of shallow cumulus. Our research took advantage of a wide variety of Department of Energy measurements from fixed climate-monitoring locations over the Southern Great Plains of the U.S. and the in the Eastern North Atlantic, along with short-term field projects (MAGIC, CAP–MBL, ACE–ENA). During the project, the PI maintained regular collaborations with Department of Energy Scientists at Brookhaven and Argonne National Laboratories. The project funded two students, who both obtained their M.S. in Atmospheric Science and are currently in the Atmospheric Science Ph.D. program. Both were lead authors on research papers funded by this grant.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

Automated Tracking of Shallow Cu Growth Rates on Geostationary Imagery and Linkages to Cloud Organization

Shallow moist convection is ubiquitous throughout the tropics and represents a key player in boundary layer processes. Common tropical cloud features, such as convective rolls and cold pool fronts, form and persist for different periods within environments that support such development. Determining differences in lifecycle amongst these features in varying environments requires viewing their evolution from initiation to decay. Geostationary satellites provide a means to follow the clouds with enhanced spatiotemporal sampling from space. We apply a cloud-tracking tool to study lifecycle properties of shallow cumulus sampled during the NASA Cloud, Aerosol, and Monsoon Processes Philippines Experiment (CAMP2Ex) field campaign of 2019. The mission conducted airborne and shipborne operations over the West Pacific Ocean, in tandem with Rapid Scan imagery from the Advanced Himawari Imager (AHI) on the Japan Meteorological Agency’s (JMA) Himawari-8 satellite. Shallow cumulus was segmented on AHI 0.5-km visible reflectance and tracked during the daylit hours of several research flights that exhibited ideal atmospheric conditions for tracking. The resulting cloud tracks were collected according to regions containing airborne sampling of individual clouds at various stages of their lifecycles, yielding ensembles of tracks in separate environments. We present an analysis on lifecycle properties extracted from the cloud-track ensembles and their potential connections to cloud organizations observed throughout CAMP2Ex. Each ensemble is evaluated by calculating cloud-layer growth rates and comparing to spatial parameters, including track-achieved area and cloud-top height. The apparent clustering of growth rates for specific ensembles is then compared against overall cloud organizations, such as isolated congestus and cold pool fronts, that are observed with the airborne data. Finally, we consider how such differences in cloud growth appear in the airborne radar observations of intercepted cloud tracks.

Cloud Tracking↗
DOE OSTI2020

Building thermal load prediction through shallow machine learning and deep learning

Building thermal load prediction informs the optimization of cooling plant and thermal energy storage. Physics-based prediction models of building thermal load are constrained by the model and input complexity. In this study, we developed 12 data-driven models (7 shallow learning, 2 deep learning, and 3 heuristic methods) to predict building thermal load and compared shallow machine learning and deep learning. The 12 prediction models were compared with the measured cooling demand. It was found XGBoost (Extreme Gradient Boost) and LSTM (Long Short Term Memory) provided the most accurate load prediction in the shallow and deep learning category, and both outperformed the best baseline model, which uses the previous day's data for prediction. Then, we discussed how the prediction horizon and input uncertainty would influence the load prediction accuracy. Major conclusions are twofold: first, LSTM performs well in short-term prediction (1 h ahead) but not in long term prediction (24 h ahead), because the sequential information becomes less relevant and accordingly not so useful when the prediction horizon is long. Second, the presence of weather forecast uncertainty deteriorates XGBoost's accuracy and favors LSTM, because the sequential information makes the model more robust to input uncertainty. Training the model with the uncertain rather than accurate weather data could enhance the model's robustness. Finally, our findings have two implications for practice. First, LSTM is recommended for short-term load prediction given that weather forecast uncertainty is unavoidable. Second, XGBoost is recommended for long term prediction, and the model should be trained with the presence of input uncertainty.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Efficient shallow Ritz method for 1D diffusion problems

This paper studies the shallow Ritz method for solving the one-dimensional diffusion problem. It is shown that the shallow Ritz method improves the order of approximation dramatically for non-smooth problems. To realize this optimal or nearly optimal order of the shallow Ritz approximation, we develop a damped block Newton (dBN) method that alternates between updates of the linear and non-linear parameters. Per each iteration, the linear and the non-linear parameters are updated by exact inversion and one step of a modified, damped Newton method applied to a reduced non-linear system, respectively. The computational cost of each dBN iteration is $\mathcal{O}$(n). Starting with the non-linear parameters as a uniform partition of the interval, numerical experiments show that the dBN is capable of efficiently moving mesh points to nearly optimal locations. In conclusion, to improve the efficiency of the dBN further, we propose an adaptive damped block Newton (AdBN) method by combining the dBN with the adaptive neuron enhancement (ANE) method [28].

Diffusion problems↗
DOE OSTI2021

Background Concentrations of Argon-39 in Shallow Soil Gas

While radioisotopes of noble gases are known to be indicators of underground nuclear explosions (UNE), McIntyre et al. (2017) was the first to report the presence of 39Ar in shallow soil gas in association with a decades old UNE. While this finding hinted at the potential application of 39Ar to be used as an indicator of an UNE, doing so would also require an understanding of the natural concentrations of 39Ar present in soil gas. Without knowing the expected range and variability of naturally occurring concentrations of 39Ar, it is difficult to determine what measured concentrations would be indicative of an elevated concentration. This paper presents results from 16 soil gas samples and three atmospheric air samples collected from various locations across the western United States. Shallow soil gas samples were collected into self-contained underwater breathing apparatus (SCUBA) tanks using a custom-built soil gas sampling system and then processed and analyzed for 39Ar. The measured concentrations of 39Ar varied from atmospheric air concentrations to about 3.5 times atmospheric air concentrations. The variation in concentration was primarily attributed to the latitude the sample was collected at, which was consistent with previous work (Johnson et al. 2015). The results presented here represent the first measurements of natural background 39Ar concentrations in shallow soil gas. This data will be necessary if 39Ar is to be used as an indicator of UNE.

Fritz, Brad G.↗