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A signal simulator designed to function as a signal source for Doppler tracking high data rate receivers is described. The simulator produces modulated signals whose carrier frequency can be varied between 200 and 900 MHz at rates greater than 20 MHz/sec. The modulation is phase shift keying with data rate up to 300 megabits per second.
Four model intercomparisons were run and evaluated using the TWP-ICE field campaign, each involving different types of atmospheric model. Here we highlight what can be learnt from having single-column model (SCM), cloud-resolving model (CRM), global atmosphere model (GAM) and limited-area model (LAM) intercomparisons all based around the same field campaign. We also make recommendations for anyone planning further large multi-model intercomparisons to ensure they are of maximum value to the model development community. CRMs tended to match observations better than other model types, although there were exceptions such as outgoing long-wave radiation. All SCMs grew large temperature and moisture biases and performed worse than other model types for many diagnostics. The GAMs produced a delayed and significantly reduced peak in domain-average rain rate when compared to the observations. While it was shown that this was in part due to the analysis used to drive these models, the LAMs were also driven by this analysis and did not have the problem to the same extent. Based on differences between the models with parametrized convection (SCMs and GAMs) and those without (CRMs and LAMs), we speculate that that having explicit convection helps to constrain liquid water whereas the ice contents are controlled more by the representation of the microphysics.
A model is presented which simulates the MSFC Univac 1108 multiprocessor system. The hardware/operating system is described to enable a good statistical measurement of the system behavior. The performance of the 1108 is evaluated by performing twenty-four different experiments designed to locate system bottlenecks and also to test the sensitivity of system throughput with respect to perturbation of the various Exec 8 scheduling algorithms. The model is implemented in the general purpose system simulation language and the techniques described can be used to assist in the design, development, and evaluation of multiprocessor systems.
A proposed manned spacecraft design, designated the HL-20, has been under investigation at Langley Research Center. Included in that investigation are flight control design and flying qualities studies utilizing a man-in-the-loop real-time simulator. This report documents the current real-time simulation model of the HL-20 lifting body vehicle, known as version 2.0, presently in use at NASA Langley Research Center. Included are data on vehicle aerodynamics, inertias, geometries, guidance and control laws, and cockpit displays and controllers. In addition, trim case and dynamic check case data is provided. The intent of this document is to provide the reader with sufficient information to develop and validate an equivalent simulation of the HL-20 for use in real-time or analytical studies.
A comprehensive computer program for the modeling of wind energy and storage systems utilizing any combination of five types of storage (pumped hydro, battery, thermal, flywheel and pneumatic) was developed. The level of detail of Simulation Model for Wind Energy Storage (SIMWEST) is consistent with a role of evaluating the economic feasibility as well as the general performance of wind energy systems. The software package consists of two basic programs and a library of system, environmental, and load components. The first program is a precompiler which generates computer models (in FORTRAN) of complex wind source storage application systems, from user specifications using the respective library components. The second program provides the techno-economic system analysis with the respective I/O, the integration of systems dynamics, and the iteration for conveyance of variables. SIMWEST program, as described, runs on the UNIVAC 1100 series computers.
Purpose: Traditionally, image quality in radiation therapy is assessed subjectively or by utilizing physically-based metrics. Some model observers exist for task-based medical image quality assessment, but almost exclusively for diagnostic imaging tasks. As opposed to disease diagnosis, the task for image observers in radiation therapy is to utilize the available images to design and deliver a radiation dose which maximizes patient disease control while minimizing normal tissue damage. The purpose of this study was to design and implement a new computer simulation model observer to enable task-based image quality assessment in radiation therapy. Methods: A modular computer simulation framework was developed to resemble the radiotherapy observer by simulating an end-to-end radiation therapy treatment. Given images and the ground-truth organ boundaries from a numerical phantom as inputs, the framework simulates an external beam radiation therapy treatment and quantifies patient treatment outcomes using the previously defined therapeutic operating characteristic (TOC) curve. As a preliminary demonstration, TOC curves were calculated for various CT acquisition and reconstruction parameters, with the goal of assessing and optimizing simulation CT image quality for radiation therapy. Sources of randomness and bias within the system were analyzed. Results: The relationship between CT imaging dose and patient treatment outcome was objectively quantified in terms of a singular value, the area under the TOC (AUTOC) curve. The AUTOC decreases more rapidly for low-dose imaging protocols. AUTOC variation introduced by the dose optimization algorithm was approximately 0.02%, at the 95% confidence interval. Conclusion: A model observer has been developed and implemented to assess image quality based on radiation therapy treatment efficacy. It enables objective determination of appropriate imaging parameter values (e.g. imaging dose). Framework flexibility allows for incorporation of additional modules to include any aspect of the treatment process, and therefore has great potential for both assessment and optimization within radiation therapy.
Reactive transport models (RTMs) are essential tools that simulate the coupling of advective, diffusive, and reactive processes in the subsurface, but their complexity makes them difficult to understand, develop and improve without accompanying statistical analyses. Although global sensitivity analysis (SA) can address these issues, the computational cost associated with most global SA techniques limits their use with RTMs. In this study, we apply distance-based generalized sensitivity analysis (DGSA), a novel and computationally efficient method of global SA, to a floodplain-scale RTM and compare DGSA results to those from local SA. Our test case focuses on the impact of 17 uncertain environmental parameters on spatially and temporally variable redox conditions within a floodplain aquifer. The input parameters considered include flow and diffusion rates, geochemical reaction rates, and the spatial distribution of sediment facies. Sensitivity was evaluated for three distinct components of the model response, encompassing both multidimensional and categorical output. Parameter rankings differ between local SA and DGSA, due to nonlinear effects of individual parameters and interaction effects between parameters. DGSA results show that fluid residence time, which is controlled by aquifer permeability, generally exerts a stronger control on redox conditions than do geochemical reaction rates. Sensitivity indices also demonstrate that sulfate reduction is key for establishing and maintaining reducing conditions throughout the aquifer. Furthermore, these results provide insights into the key drivers of heterogeneous redox processes within floodplain aquifers, as well as the main sources of uncertainty when modeling complex subsurface systems.
Satellite observations from UARS and TOMS have provided unique data sets for studying seasonal and interannual stratospheric constituent variability during the 1990's. The corresponding meteorological variability is also well represented by the partly satellite-based UKMO assimilation winds and temperatures. In this study, we use the UKMO meteorological fields to derive zonal mean transport components (residual circulation, horizontal eddy diffusion) for each year, 1992-1998. These fields are then used in our GSFC two-dimensional chemistry and transport model to simulate the year to year changes in ozone and long lived tracers in the equatorial stratosphere due to interannual dynamical variability. The resulting model simulation of ozone and CH4 compares reasonably well with UARS data in reproducing a dominant QBO signal in the lower stratosphere, and a dominant semiannual signature in the upper stratosphere which appears to be modulated by the lower stratospheric QBO. The model also compares well with TOMS data in simulating the phase of the QBO in total ozone, although the model QBO amplitude is somewhat underestimated relative to TOMS. These comparisons illustrate that the general zonal mean transport characteristics in the equatorial stratosphere can be reasonably well simulated using an empirically-based residual circulation.
Attribution of observed atmospheric carbon concentrations to emissions on the country, state or city level is often inferred using "inversion" techniques. Such computations are often performed using advanced mathematical techniques, such as synthesis inversion or four-dimensional variational analysis, that invoke tracing observed atmospheric concentrations backwards through a transport model to a source region. It is, to date, not well understood how well such techniques can represent fine spatial (and temporal) structure in the inverted flux fields. This question is addressed using forward-model computations with idealized tracers emitted at the surface in a large number of grid boxes over selected regions and examining how distinctly these emitted tracers can be detected downstream. Initial results show that tracers emitted in half-degree grid boxes over a large region of the Eastern USA cannot be distinguished from each other, even at short distances over the Atlantic Ocean, when they are emitted in grid boxes separated by less than five degrees of latitude - especially when only total-column observations are available. A large number of forward model simulations, with varying meteorological conditions, are used to assess how distinctly three types observations (total column, upper tropospheric column, and surface mixing ratio) can separate emissions from different sources. Inferences inverse modeling and source attribution will be drawn.
A tape drive called the Mass Memory Unit (MMU) stores software used by Spacelab computers. MMU tape motion must be minimized during typical flight operations to avoid a loss of scientific data. A projection of the tape motion is needed for evaluation of candidate tape layouts. A computer simulation of the scheduled and unscheduled MMU tape accesses is developed for this purpose. This simulation permits evaluations of candidate tape layouts by tracking and summarizing tape movements. The factors that affect tape travel are investigated and a heuristic is developed to find a good tape layout. An improved tape layout for Spacelab I is selected after the evaluation of fourteen candidates. The simulation model will provide the ability to determine MMU layouts that substantially decrease the tape travel on future Spacelab flights.
In an initial effort in regional numerical weather prediction, results from the University of Wisconsin isentropic-sigma (UW theta-sigma) hybrid model and an 'identical' sigma model are compared. The two main objectives are to demonstrate the capability of the UW theta-sigma model for regional numerical weather prediction and to identify advantages of the hybrid model in simulating atmospheric water vapor transport and precipitation relative to the sigma model. The 72-h simulations produced by the two models extend over a region covering the western Pacific Ocean, North America, and the western Atlantic Ocean. The simulations begin at 0000 UTC 13 January 1979, a period during which an intense Chicago blizzard develops over the central United States. This period also includes the rapid development of a cyclone in the western Pacific Ocean. Results using the Global Weather Experiment (GWE) ECMWF level IIIB data as initial and verification data indicate that both models produce reasonable and similar 72-h simulations, with the UW theta-sigma model mass and momentum distributions being slightly more accurate than the sigma model. Of particular importance for the Chicago blizzard is that the UW theta-sigma model more accurately simulates water vapor transport northward from the Gulf of Mexico and westward from the Atlantic Ocean. As a result, the hybrid model more accurately simulates observed precipitation, especially over the northeastern U.S. and southeastern Canada.
Rainfall is a key link in the hydrologic cycle as well as the primary heat source for the atmosphere, The vertical distribution of convective latent-heat release modulates the large-scale circulations of the tropics, Furthermore, changes in the moisture distribution at middle and upper levels of the troposphere can affect cloud distributions and cloud liquid water and ice contents. How the incoming solar and outgoing longwave radiation respond to these changes in clouds is a major factor in assessing climate change. Present large-scale weather and climate models simulate cloud processes only crudely, reducing confidence in their predictions on both global and regional scales. One of the most promising methods to test physical parameterizations used in General Circulation Models (GCMS) and climate models is to use field observations together with Cloud Resolving Models (CRMs). The CRMs use more sophisticated and physically realistic parameterizations of cloud microphysical processes, and allow for their complex interactions with solar and infrared radiative transfer processes. The CRMs can reasonably well resolve the evolution, structure, and life cycles of individual clouds and cloud systems, The major objective of this paper is to investigate the latent heating, moisture and momenti,im budgets associated with several convective systems developed during the TOGA COARE IFA - westerly wind burst event (late December, 1992). The tool for this study is the Goddard Cumulus Ensemble (CCE) model which includes a 3-class ice-phase microphysical scheme, The model domain contains 256 x 256 grid points (using 2 km resolution) in the horizontal and 38 grid points (to a depth of 22 km depth) in the vertical, The 2D domain has 1024 grid points. The simulations are performed over a 7 day time period. We will examine (1) the precipitation processes (i.e., condensation/evaporation) and their interaction with warm pool; (2) the heating and moisture budgets in the convective and stratiform regions; (3) the cloud (upward-downward) mass fluxes in convective and stratiform regions; (4) characteristics of clouds (such as cloud size, updraft intensity and cloud lifetime) and the comparison of clouds with Radar observations. Differences and similarities in organization of convection between simulated 2D and 3D cloud systems. Preliminary results indicated that there is major differences between 2D and 3D simulated stratiform rainfall amount and convective updraft and downdraft mass fluxes.
Here, the water retention curve and relative permeability are critical to predict gas and water production from hydrate–bearing sediments. However, values for key parameters that characterize gas and water flows during hydrate dissociation have not been identified due to experimental challenges. This study utilizes the combined techniques of micro–focus X–ray computed tomography (CT) and pore–network model simulation to identify proper values for those key parameters, such as gas entry pressure, residual water saturation, and curve fitting values. Hydrates with various saturation and morphology are realized in the pore–network that was extracted from micron–resolution CT images of sediments recovered from the hydrate deposit at the Mallik site, and then the processes of gas invasion, hydrate dissociation, gas expansion, and gas and water permeability are simulated. Results show that greater hydrate saturation in sediments lead to higher gas entry pressure, higher residual water saturation, and steeper water retention curve. An increase in hydrate saturation decreases gas permeability but has marginal effects on water permeability in sediments with uniformly distributed hydrate. Hydrate morphology has more significant impacts than hydrate saturation on relative permeability. Sediments with heterogeneously distributed hydrate tend to result in lower residual water saturation and higher gas and water permeability. In this sense, the Brooks–Corey model that uses two fitting parameters individually for gas and water permeability properly capture the effect of hydrate saturation and morphology on gas and water flows in hydrate–bearing sediments.
Wildfire behavior is shaped by complex fire dynamics, with firebrands playing a critical role in spot fire ignition and fire spread. While previous studies have explored firebrand generation and transport, the specific role of towers and troughs from wildland fires in the lofting of firebrands remains unquantified. This study addresses that gap by using physics-based coupled fire-atmosphere model simulations to examine how wildfire towers (updrafts) and troughs (downdrafts) influence firebrand lofting. Our results show that the majority of firebrands (78.85%) are lofted from towers, where strong updrafts drive long-range transport. In contrast, only 21.15% of firebrands are lofted within troughs, where downdrafts cause most firebrands to fall near the fireline. We also find that firebrand size significantly influences lofting behavior, with smaller particles (1 mm radius) exhibiting the strongest correlation with updraft intensity. These findings highlight the dominant role of wildfire towers in promoting long-distance firebrand dispersal—an essential factor in rapid wildfire growth and wildland-urban interface (WUI) fire risks. By quantifying the relationship between firebrand lofting and fire-induced atmospheric features, this study provides critical insights to improve spot fire modeling, support mitigation planning, and enhance firefighter and WUI community safety in spot fire-prone regions.
The Energy Exascale Earth System Model (E3SM) Land Model (ELM) has been extended to kilometer-scale (km-ELM) resolutions, enabling high-fidelity simulations of terrestrial processes at 1 km x 1 km grid spacing. In ELM, domain decomposition partitions the computational domain across processors, ensuring efficient parallel execution. Currently, round-robin decomposition is applied, providing a straightforward way to distribute computational workload. As ELM continues evolving at the kilometer-scale (km-scale), particularly with integrating lateral flow modeling, decomposition strategies must also account for the increased workload and data movement. This paper introduces a flexible user-defined domain decomposition framework, allowing users to customize domain partitioning based on application requirements. The impact of different decomposition strategies is evaluated across various applications concerning computation, communication, and I/O. Results demonstrate that while 1D partitioning yields superior I/O performance, k-nearest neighbors (KNN) clustering effectively reduces inter-process communication overhead. This study lays the groundwork for scalable partitioning in large-scale land surface simulations, enhancing next-generation Earth system modeling.
Rainfall is a key link in the hydrologic cycle as well as the primary heat source for the atmosphere. The vertical distribution of convective latent-heat release modulates the large-scale circulations of the topics. Furthermore, changes in the moisture distribution at middle and upper levels of the troposphere can affect cloud distributions and cloud liquid water and ice contents. How the incoming solar and outgoing longwave radiation respond to these changes in clouds is a major factor in assessing climate change. Present large-scale weather and climate model simulate processes only crudely, reducing confidence in their predictions on both global and regional scales. One of the most promising methods to test physical parameterizations used in General Circulation Models (GCMs) and climate models is to use field observations together with Cloud Resolving Models (CRMs). The CRMs use more sophisticated and physically realistic parameterizations of cloud microphysical processes, and allow for their complex interactions with solar and infrared radiative transfer processes. The CRMs can reasonably well resolve the evolution, structure, and life cycles of individual clouds and clouds systems. The major objective of this paper is to investigate the latent heating, moisture and momentum budgets associated with several convective systems developed during the TOGA COARE IFA - westerly wind burst event (late December, 1992). The tool for this study is the Goddard Cumulus Ensemble (GCE) model which includes a 3-class ice-phase microphysics scheme.
Modeling of the Multi-mission Image Processing System (MIPS) will be described as an example of the use of a modeling tool to design a distributed system that supports multiple application scenarios. This paper examines: (a) modeling tool selection, capabilities, and operation (namely NETWORK 2.5 by CACl), (b) pointers for building or constructing a model and how the MIPS model was developed, (c) the importance of benchmarking or testing the performance of equipment/subsystems being considered for incorporation the design/architecture, (d) the essential step of model validation and/or calibration using the benchmark results, (e) sample simulation results from the MIPS model, and (f) how modeling and simulation analysis affected the MIPS design process by having a supportive and informative impact.
Abstract Closure is an important component of a mass flux‐based convective parameterization scheme, and it determines the amount of convection with the aid of a large‐scale variable (closure variable) that is sensitive to convection. In this study, we have evaluated and quantified the relationship between commonly used closure variables and convection for a range of global climate model (GCM) horizontal resolutions, taking convective precipitation and mass flux at 600 hPa as measures for deep convection. We have used cloud‐resolving model simulation data to create domain averages representing GCM horizontal resolutions of 128 km, 64 km, 32 km, 16 km, 8 km, and 4 km. Lead‐lag correlation analysis shows that except moisture convergence and turbulent kinetic energy, none of the other closure variables evaluated in this study show any relationship with convection for the six subdomain sizes. It is found that the correlation between moisture convergence and convective precipitation is largest when moisture convergence leads convection. This correlation weakens as the subdomain size decreases to 8 km or smaller. Although convective precipitation and mass flux increase with moisture convergence at a given subdomain size, as the subdomain size increases, the rate at which they increase becomes smaller. This suggests that moisture convergence‐based closure should scale down the predicted mass flux for a given moisture convergence as GCM resolution increases.