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

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At least 217 records · Page 12
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NASA NTRS1999

Sensitivity of High-Resolution Simulations of Hurricane Bob (1991) to Planetary Boundary Layer Parameterizations

The MM5 mesoscale model is used to simulate Hurricane Bob (1991) using grids nested to high resolution (4 km). Tests are conducted to determine the sensitivity of the simulation to the available planetary boundary layer parameterizations, including the bulk-aerodynamic, Blackadar, Medium-RanGe Forecast (MRF) model, and Burk-Thompson boundary-layer schemes. Significant sensitivity is seen, with minimum central pressures varying by up to 17 mb. The Burk-Thompson and bulk-aerodynamic boundary-layer schemes produced the strongest storms while the MRF scheme produced the weakest storm. Precipitation structure of the simulated hurricanes also varied substantially with the boundary layer parameterizations. Diagnostics of boundary-layer variables indicated that the intensity of the simulated hurricanes generally increased as the ratio of the surface exchange coefficients for heat and momentum, C(sub h)/C(sub M), although the manner in which the vertical mixing takes place was also important. Findings specific to the boundary-layer schemes include: 1) the MRF scheme produces mixing that is too deep and causes drying of the lower boundary layer in the inner-core region of the hurricane; 2) the bulk-aerodynamic scheme produces mixing that is probably too shallow, but results in a strong hurricane because of a large value of C(sub h)/C(sub M) (approximately 1.3); 3) the MRF and Blackadar schemes are weak partly because of smaller surface moisture fluxes that result in a reduced value of C(sub h)/C(sub M) (approximately 0.7); 4) the Burk-Thompson scheme produces a strong storm with C(sub h)/C(sub M) approximately 1; and 5) the formulation of the wind-speed dependence of the surface roughness parameter, z(sub 0), is important for getting appropriate values of the surface exchange coefficients in hurricanes based upon current estimates of these parameters.

Braun, Scott A.↗
NASA NTRS2002

Use of TRMM Data to Test an Improved Parameterization of Stratiform Precipitation

We successfully implemented our EAUcup parameterization of convection in our most recent geodesic-grid version of the Colorado State University General Circulation Model (CSU GCM). Tendencies due to convection and large-scale cloud microphysics are computed using the same time-step, allowing smoother interactions between convective and large-scale moist processes. Figures illustrate our most recent progress on the simulation of convective and stratiform precipitations for January. Comparisons against TRMM precipitation radar (PR) data would reveal a systematic overestimation of the simulated monthly-mean convective rainfall over well-known areas of deep convection. One major deficiency in the global distribution of stratiform precipitation simulated in the CSU GCM is the lack of stratiform precipitation over land in the tropics. This result strongly disagree with Fowler and Randall who show that convective and stratiform precipitations always coexist and that their ratio to the total precipitation is about 0.5. We believe that stratiform precipitation over land evaporates before reaching the ground because the lower troposphere remains too dry in response to the lack of convective detrainment occurring immediately above the Planetary Boundary Layer (PBL). This issue is further investigated at present. We made significant progress in the development of our parameterization of fractional cloudiness. As an example of our ongoing research effort, a figure shows the global distribution of the cloud ice mixing ratio and corresponding fractional area of ice clouds at 250 hPa. These results were obtained using our latitude-longitude grid version of the CSU GCM. There is a nice correspondence between areas of high (low) values of the cloud ice mixing ratio and the cloud fraction. A nice correspondence between the global distribution of the cloud water mixing ratio and fraction of water clouds in the lower troposphere can also be found. We are pursuing this effort, but in the geodesic version of the GCM. We hope to be able to make comparison of the simulated precipitation against TRMM precipitation data in the near future.

Randall, David A.↗
NASA NTRS2002

Summary of Cumulus Parameterization Workshop

A workshop on cumulus parameterization took place at the NASA Goddard Space Flight Center from December 3-5, 2001. The major objectives of this workshop were (1) to review the problem of representation of moist processes in large-scale models (mesoscale models, Numerical Weather Prediction models and Atmospheric General Circulation Models), (2) to review the state-of-the-art in cumulus parameterization schemes, and (3) to discuss the need for future research and applications. There were a total of 31 presentations and about 100 participants from the United States, Japan, the United Kingdom, France and South Korea. The specific presentations and discussions during the workshop are summarized in this paper.

Tao, Wei-Kuo↗
NASA NTRS2004

Synthesizing 3D Surfaces from Parameterized Strip Charts

We believe 3D information visualization has the power to unlock new levels of productivity in the monitoring and control of complex processes. Our goal is to provide visual methods to allow for rapid human insight into systems consisting of thousands to millions of parameters. We explore this hypothesis in two complex domains: NASA program management and NASA International Space Station (ISS) spacecraft computer operations. We seek to extend a common form of visualization called the strip chart from 2D to 3D. A strip chart can display the time series progression of a parameter and allows for trends and events to be identified. Strip charts can be overlayed when multiple parameters need to visualized in order to correlate their events. When many parameters are involved, the direct overlaying of strip charts can become confusing and may not fully utilize the graphing area to convey the relationships between the parameters. We provide a solution to this problem by generating 3D surfaces from parameterized strip charts. The 3D surface utilizes significantly more screen area to illustrate the differences in the parameters and the overlayed strip charts, and it can rapidly be scanned by humans to gain insight. The selection of the third dimension must be a parallel or parameterized homogenous resource in the target domain, defined using a finite, ordered, enumerated type, and not a heterogeneous type. We demonstrate our concepts with examples from the NASA program management domain (assessing the state of many plans) and the computers of the ISS (assessing the state of many computers). We identify 2D strip charts in each domain and show how to construct the corresponding 3D surfaces. The user can navigate the surface, zooming in on regions of interest, setting a mark and drilling down to source documents from which the data points have been derived. We close by discussing design issues, related work, and implementation challenges.

Robinson, Peter I.↗
NASA NTRS2000

Parameterization of Model Validating Sets for Uncertainty Bound Optimizations

Given measurement data, a nominal model and a linear fractional transformation uncertainty structure with an allowance on unknown but bounded exogenous disturbances, easily computable tests for the existence of a model validating uncertainty set are given. Under mild conditions, these tests are necessary and sufficient for the case of complex, nonrepeated, block-diagonal structure. For the more general case which includes repeated and/or real scalar uncertainties, the tests are only necessary but become sufficient if a collinearity condition is also satisfied. With the satisfaction of these tests, it is shown that a parameterization of all model validating sets of plant models is possible. The new parameterization is used as a basis for a systematic way to construct or perform uncertainty tradeoff with model validating uncertainty sets which have specific linear fractional transformation structure for use in robust control design and analysis. An illustrative example which includes a comparison of candidate model validating sets is given.

Lim, K. B.↗
NASA NTRS2004

An Empirical Cumulus Parameterization Scheme for a Global Spectral Model

Realistic vertical heating and drying profiles in a cumulus scheme is important for obtaining accurate weather forecasts. A new empirical cumulus parameterization scheme based on a procedure to improve the vertical distribution of heating and moistening over the tropics is developed. The empirical cumulus parameterization scheme (ECPS) utilizes profiles of Tropical Rainfall Measuring Mission (TRMM) based heating and moistening derived from the European Centre for Medium- Range Weather Forecasts (ECMWF) analysis. A dimension reduction technique through rotated principal component analysis (RPCA) is performed on the vertical profiles of heating (Q1) and drying (Q2) over the convective regions of the tropics, to obtain the dominant modes of variability. Analysis suggests that most of the variance associated with the observed profiles can be explained by retaining the first three modes. The ECPS then applies a statistical approach in which Q1 and Q2 are expressed as a linear combination of the first three dominant principal components which distinctly explain variance in the troposphere as a function of the prevalent large-scale dynamics. The principal component (PC) score which quantifies the contribution of each PC to the corresponding loading profile is estimated through a multiple screening regression method which yields the PC score as a function of the large-scale variables. The profiles of Q1 and Q2 thus obtained are found to match well with the observed profiles. The impact of the ECPS is investigated in a series of short range (1-3 day) prediction experiments using the Florida State University global spectral model (FSUGSM, T126L14). Comparisons between short range ECPS forecasts and those with the modified Kuo scheme show a very marked improvement in the skill in ECPS forecasts. This improvement in the forecast skill with ECPS emphasizes the importance of incorporating realistic vertical distributions of heating and drying in the model cumulus scheme. This also suggests that in the absence of explicit models for convection, the proposed statistical scheme improves the modeling of the vertical distribution of heating and moistening in areas of deep convection.

Rajendran, K.↗
NASA NTRS2006

Multiscale Modeling of Grain-Boundary Fracture: Cohesive Zone Models Parameterized From Atomistic Simulations

A multiscale modeling strategy is developed to study grain boundary fracture in polycrystalline aluminum. Atomistic simulation is used to model fundamental nanoscale deformation and fracture mechanisms and to develop a constitutive relationship for separation along a grain boundary interface. The nanoscale constitutive relationship is then parameterized within a cohesive zone model to represent variations in grain boundary properties. These variations arise from the presence of vacancies, intersticies, and other defects in addition to deviations in grain boundary angle from the baseline configuration considered in the molecular dynamics simulation. The parameterized cohesive zone models are then used to model grain boundaries within finite element analyses of aluminum polycrystals.

Glaessgen, Edward H.↗
NASA NTRS2009

Cold Season QPF: Sensitivities to Snow Parameterizations and Comparisons to NASA CloudSat Observations

As operational numerical weather prediction is performed at increasingly finer spatial resolution, precipitation traditionally represented by sub-grid scale parameterization schemes is now being calculated explicitly through the use of single- or multi-moment, bulk water microphysics schemes. As computational resources grow, the real-time application of these schemes is becoming available to a broader audience, ranging from national meteorological centers to their component forecast offices. A need for improved quantitative precipitation forecasts has been highlighted by the United States Weather Research Program, which advised that gains in forecasting skill will draw upon improved simulations of clouds and cloud microphysical processes. Investments in space-borne remote sensing have produced the NASA A-Train of polar orbiting satellites, specially equipped to observe and catalog cloud properties. The NASA CloudSat instrument, a recent addition to the A-Train and the first 94 GHz radar system operated in space, provides a unique opportunity to compare observed cloud profiles to their modeled counterparts. Comparisons are available through the use of a radiative transfer model (QuickBeam), which simulates 94 GHz radar returns based on the microphysics of cloudy model profiles and the prescribed characteristics of their constituent hydrometeor classes. CloudSat observations of snowfall are presented for a case in the central United States, with comparisons made to precipitating clouds as simulated by the Weather Research and Forecasting Model and the Goddard single-moment microphysics scheme. An additional forecast cycle is performed with a temperature-based parameterization of the snow distribution slope parameter, with comparisons to CloudSat observations provided through the QuickBeam simulator.

Molthan, A. L.↗
NASA NTRS2009

Demonstration of Effects on Tropical Cyclone Forecasts with a High Resolution Global Model from Variation in Cumulus Convection Parameterization

The Goddard Earth Observing System Model, Version 5 (GEOS-5) is a system of models that have been developed at Goddard Space Flight Center to support NASA's earth science research in data analysis, observing system modeling and design, climate and weather prediction, and basic research. The work presented used GEOS-5 with 0.25o horizontal resolution and 72 vertical levels (up to 0.01 hP) resolving both the troposphere and stratosphere, with closer packing of the levels close to the surface. The model includes explicit (grid-scale) moist physics, as well as convective parameterization schemes. Results will be presented that will demonstrate strong dependence in the results of modeling of a strong hurricane on the type of convective parameterization scheme used. The previous standard (default) option in the model was the Relaxed Arakawa-Schubert (RAS) scheme, which uses a quasi-equilibrium closure. In the cases shown, this scheme does not permit the efficient development of a strong storm in comparison with observations. When this scheme is replaced by a modified version of the Kain-Fritsch scheme, which was originally developed for use on grids with intervals of order 25 km such as the present one, the storm is able to develop to a much greater extent, closer to that of reality. Details of the two cases will be shown in order to elucidate the differences in the two modeled storms.

Miller, Timothy L.↗
NASA NTRS2012

Rapid Parameterization Schemes for Aircraft Shape Optimization

A rapid shape parameterization tool called PROTEUS is developed for aircraft shape optimization. This tool can be applied directly to any aircraft geometry that has been defined in PLOT3D format, with the restriction that each aircraft component must be defined by only one data block. PROTEUS has eight types of parameterization schemes: planform, wing surface, twist, body surface, body scaling, body camber line, shifting/scaling, and linear morphing. These parametric schemes can be applied to two types of components: wing-type surfaces (e.g., wing, canard, horizontal tail, vertical tail, and pylon) and body-type surfaces (e.g., fuselage, pod, and nacelle). These schemes permit the easy setup of commonly used shape modification methods, and each customized parametric scheme can be applied to the same type of component for any configuration. This paper explains the mathematics for these parametric schemes and uses two supersonic configurations to demonstrate the application of these schemes.

Li, Wu↗
NASA NTRS2011

Comparison of Four Mixed Layer Mesoscale Parameterizations and the Equation for an Arbitrary Tracer

In this paper we discuss two issues, the inter-comparison of four mixed layer mesoscale parameterizations and the search for the eddy induced velocity for an arbitrary tracer. It must be stressed that our analysis is limited to mixed layer mesoscales since we do not treat sub-mesoscales and small turbulent mixing. As for the first item, since three of the four parameterizations are expressed in terms of a stream function and a residual flux of the RMT formalism (residual mean theory), while the fourth is expressed in terms of vertical and horizontal fluxes, we needed a formalism to connect the two formulations. The standard RMT representation developed for the deep ocean cannot be extended to the mixed layer since its stream function does not vanish at the ocean's surface. We develop a new RMT representation that satisfies the surface boundary condition. As for the general form of the eddy induced velocity for an arbitrary tracer, thus far, it has been assumed that there is only the one that originates from the curl of the stream function. This is because it was assumed that the tracer residual flux is purely diffusive. On the other hand, we show that in the case of an arbitrary tracer, the residual flux has also a skew component that gives rise to an additional bolus velocity. Therefore, instead of only one bolus velocity, there are now two, one coming from the curl of the stream function and other from the skew part of the residual flux. In the buoyancy case, only one bolus velocity contributes to the mean buoyancy equation since the residual flux is indeed only diffusive.

Canuto, V. M.↗
NASA NTRS2011

The Impacts of an Observationally-Based Cloud Fraction and Condensate Overlap Parameterization on a GCM's Cloud Radiative Effect

It has been shown that the details of how cloud fraction overlap is treated in GCMs has substantial impact on shortwave and longwave fluxes. Because cloud condensate is also horizontally heterogeneous at GCM grid scales, another aspect of cloud overlap should in principle also be assessed, namely the vertical overlap of hydrometeor distributions. This type of overlap is usually examined in terms of rank correlations, i.e., linear correlations between hydrometeor amount ranks of the overlapping parts of cloud layers at specific separation distances. The cloud fraction overlap parameter and the rank correlation of hydrometeor amounts can be both expressed as inverse exponential functions of separation distance characterized by their respective decorrelation lengths (e-folding distances). Larger decorrelation lengths mean that hydrometeor fractions and probability distribution functions have high levels of vertical alignment. An analysis of CloudSat and CALIPSO data reveals that the two aspects of cloud overlap are related and their respective decorrelation lengths have a distinct dependence on latitude that can be parameterized and included in a GCM. In our presentation we will contrast the Cloud Radiative Effect (CRE) of the GEOS-5 atmospheric GCM (AGCM) when the observationally-based parameterization of decorrelation lengths is used to represent overlap versus the simpler cases of maximum-random overlap and globally constant decorrelation lengths. The effects of specific overlap representations will be examined for both diagnostic and interactive radiation runs in GEOS-5 and comparisons will be made with observed CREs from CERES and CloudSat (2B-FLXHR product). Since the radiative effects of overlap depend on the cloud property distributions of the AGCM, the availability of two different cloud schemes in GEOS-5 will give us the opportunity to assess a wide range of potential cloud overlap consequences on the model's climate.

Oreopoulos, Lazaros↗
NASA NTRS2014

Natural Ocean Carbon Cycle Sensitivity to Parameterizations of the Recycling in a Climate Model

Sensitivities of the oceanic biological pump within the GISS (Goddard Institute for Space Studies ) climate modeling system are explored here. Results are presented from twin control simulations of the air-sea CO2 gas exchange using two different ocean models coupled to the same atmosphere. The two ocean models (Russell ocean model and Hybrid Coordinate Ocean Model, HYCOM) use different vertical coordinate systems, and therefore different representations of column physics. Both variants of the GISS climate model are coupled to the same ocean biogeochemistry module (the NASA Ocean Biogeochemistry Model, NOBM), which computes prognostic distributions for biotic and abiotic fields that influence the air-sea flux of CO2 and the deep ocean carbon transport and storage. In particular, the model differences due to remineralization rate changes are compared to differences attributed to physical processes modeled differently in the two ocean models such as ventilation, mixing, eddy stirring and vertical advection. GISSEH(GISSER) is found to underestimate mixed layer depth compared to observations by about 55% (10 %) in the Southern Ocean and overestimate it by about 17% (underestimate by 2%) in the northern high latitudes. Everywhere else in the global ocean, the two models underestimate the surface mixing by about 12-34 %, which prevents deep nutrients from reaching the surface and promoting primary production there. Consequently, carbon export is reduced because of reduced production at the surface. Furthermore, carbon export is particularly sensitive to remineralization rate changes in the frontal regions of the subtropical gyres and at the Equator and this sensitivity in the model is much higher than the sensitivity to physical processes such as vertical mixing, vertical advection and mesoscale eddy transport. At depth, GISSER, which has a significant warm bias, remineralizes nutrients and carbon faster thereby producing more nutrients and carbon at depth, which eventually resurfaces with the global thermohaline circulation especially in the Southern Ocean. Because of the reduced primary production and carbon export in GISSEH compared to GISSER, the biological pump efficiency, i.e., the ratio of primary production and carbon export at 75 m, is half in the GISSEH of that in GISSER, The Southern Ocean emerges as a key region where the CO2 flux is as sensitive to biological parameterizations as it is to physical parameterizations. The fidelity of ocean mixing in the Southern Ocean compared to observations is shown to be a good indicator of the magnitude of the biological pump efficiency regardless of physical model choice.

Antarctic Ocean↗
NASA NTRS2015

The Parameterization of Top-Hat Particle Sensors with Microchannel-Plate-Based Detection Systems and its Application to the Fast Plasma Investigation on NASA's Magnetospheric MultiScale Mission

The most common instrument for low energy plasmas consists of a top-hat electrostatic analyzer geometry coupled with a microchannel-plate (MCP)-based detection system. While the electrostatic optics for such sensors are readily simulated and parameterized during the laboratory calibration process, the detection system is often less well characterized. Furthermore, due to finite resources, for large sensor suites such as the Fast Plasma Investigation (FPI) on NASA's Magnetospheric Multiscale (MMS) mission, calibration data are increasingly sparse. Measurements must be interpolated and extrapolated to understand instrument behavior for untestable operating modes and yet sensor inter-calibration is critical to mission success. To characterize instruments from a minimal set of parameters we have developed the first comprehensive mathematical description of both sensor electrostatic optics and particle detection systems. We include effects of MCP efficiency, gain, scattering, capacitive crosstalk, and charge cloud spreading at the detector output. Our parameterization enables the interpolation and extrapolation of instrument response to all relevant particle energies, detector high voltage settings, and polar angles from a small set of calibration data. We apply this model to the 32 sensor heads in the Dual Electron Sensor (DES) and 32 sensor heads in the Dual Ion Sensor (DIS) instruments on the 4 MMS observatories and use least squares fitting of calibration data to extract all key instrument parameters. Parameters that will evolve in flight, namely MCP gain, will be determined daily through application of this model to specifically tailored in-flight calibration activities, providing a robust characterization of sensor suite performance throughout mission lifetime. Beyond FPI, our model provides a valuable framework for the simulation and evaluation of future detection system designs and can be used to maximize instrument understanding with minimal calibration resources.

Instrument-model↗
NASA NTRS2014

Seasonal Parameterizations of the Tau-Omega Model Using the ComRAD Ground-Based SMAP Simulator

NASA's Soil Moisture Active Passive (SMAP) mission is scheduled for launch in November 2014. In the prelaunch time frame, the SMAP team has focused on improving retrieval algorithms for the various SMAP baseline data products. The SMAP passive-only soil moisture product depends on accurate parameterization of the tau-omega model to achieve the required accuracy in soil moisture retrieval. During a field experiment (APEX12) conducted in the summer of 2012 under dry conditions in Maryland, the Combined Radar/Radiometer (ComRAD) truck-based SMAP simulator collected active/passive microwave time series data at the SMAP incident angle of 40 degrees over corn and soybeans throughout the crop growth cycle. A similar experiment was conducted only over corn in 2002 under normal moist conditions. Data from these two experiments will be analyzed and compared to evaluate how changes in vegetation conditions throughout the growing season in both a drought and normal year can affect parameterizations in the tau-omega model for more accurate soil moisture retrieval.

SMAP↗
NASA NTRS2019

Including a Cold Pool Representation in a Convection Parameterization and Simulating Its Impacts on the Spatial and Temporal Variability of the Precipitation in the NASA GEOS GCM

We developed and implemented a simple representation of a cold pool in the Grell-Freitas (GF) convection parameterization. The cold pool parameterization is based on the observation that convective-scale downdrafts produce a local ‘deficit’ of the moist static energy (MSE). This information is advected and becoming downwind available to trigger and intensify new convection. The cold pool is dissipated by a simple exponential decay using a lifetime of a few hours, or by interacting with the underneath surface by exchanging latent and sensible heat fluxes. Preliminary results show some improvement of the simulation of the diurnal cycle of the precipitation over the land, mainly during the nighttime.

Cold pools↗
NASA NTRS2015

Aerodynamic Shape Optimization Benchmarks with Error Control and Automatic Parameterization

Results are presented for four optimization benchmark problems posed by the AIAA Aerodynamic Design Optimization Discussion Group. The benchmarks are intended to exercise optimization frameworks on representative airfoil and wing design problems. All problems involve drag minimization subject to geometric and aerodynamic constraints. Our design approach involves two forms of adaptation. First, the shape parameterization is gradually and automatically enriched from an initially coarse search space. Second, adjoint solutions are used to drive adaptive mesh refinement to control discretization error. The error threshold is tailored so that the nest meshes, with the greatest accuracy, are used only when nearing the optimum. On the inviscid airfoil design problem, while reducing the drag by a factor of 10, we show how the combination of progressive parameterization and tiered discretization error control can dramatically accelerate the optimization. On the viscous airfoil design problem, we use inviscid analysis-driven optimization to reduce the total drag by a factor of two. Next, we improve the span efficiency factor of a wing by performing twist optimization. Finally, we optimize the Common Research Model wing, managing to hold drag roughly fixed, while targeting an initially-violated pitching moment constraint. Our approach aims to introduce greater complexity and accuracy only when necessary to improve the design, and also support a greater degree of automation.

Anderson, George R.↗
NASA NTRS2020

Impact of Resolution and Parameterized Convection on the Diurnal Cycle of Precipitation in a Global Nonhydrostatic Model

A series of 40-day non-hydrostatic global simulations was run with the NASA Goddard Earth Observing System (GEOS) model with horizontal grid spacing ranging from 50 km to 3.5 km. Here we evaluate the diurnal cycle of precipitation and organized convection as a function of resolution. For validation we use the TRMM 3B42 and IMERG precipitation products and 4 km Merged Infrared brightness temperature, focusing on three regions: the contiguous United States (CONUS), the Maritime Continent, and Amazonia. We find that higher resolution has mixed impacts on diurnal phase. Regions dominated by non-local propagating convection show the greatest improvement, with better representation of organized convective systems. Precipitation in regions dominated by local thermodynamic forcing tends to peak too early at high resolution. Diurnal amplitudes in all regions develop unrealistic small-scale variability at high resolution, while amplitudes tend to be underestimated at low resolution. The GEOS model uses the Grell-Freitas scale-aware convection scheme, which smoothly reduces parameterized deep convection with increasing resolution. We find that some parameterized convection is beneficial for the diurnal amplitude and phase even with a 3.5 km model grid, but only when throttled with the scale-aware approach. An additional 3.5 km experiment employing the GFDL microphysics scheme and higher vertical resolution shows further improvement in propagating convection, but an earlier rainfall peak in locally forced regions.

Nathan P. Arnold↗