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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

Space-Time Error Representation and Estimation in Navier-Stokes Calculations

The mathematical framework for a-posteriori error estimation of functionals elucidated by Eriksson et al. [7] and Becker and Rannacher [3] is revisited in a space-time context. Using these theories, a hierarchy of exact and approximate error representation formulas are presented for use in error estimation and mesh adaptivity. Numerical space-time results for simple model problems as well as compressible Navier-Stokes flow at Re = 300 over a 2D circular cylinder are then presented to demonstrate elements of the error representation theory for time-dependent problems.

Barth, Timothy J.↗
NASA NTRS2000

Adjoints and Low-rank Covariance Representation

Quantitative measures of the uncertainty of Earth System estimates can be as important as the estimates themselves. Second moments of estimation errors are described by the covariance matrix, whose direct calculation is impractical when the number of degrees of freedom of the system state is large. Ensemble and reduced-state approaches to prediction and data assimilation replace full estimation error covariance matrices by low-rank approximations. The appropriateness of such approximations depends on the spectrum of the full error covariance matrix, whose calculation is also often impractical. Here we examine the situation where the error covariance is a linear transformation of a forcing error covariance. We use operator norms and adjoints to relate the appropriateness of low-rank representations to the conditioning of this transformation. The analysis is used to investigate low-rank representations of the steady-state response to random forcing of an idealized discrete-time dynamical system.

Tippett, Michael K.↗
NASA NTRS2009

Conversion from Tree to Graph Representation of Requirements

A procedure and software to implement the procedure have been devised to enable conversion from a tree representation to a graph representation of the requirements governing the development and design of an engineering system. The need for this procedure and software and for other requirements-management tools arises as follows: In systems-engineering circles, it is well known that requirements- management capability improves the likelihood of success in the team-based development of complex systems involving multiple technological disciplines. It is especially desirable to be able to visualize (in order to identify and manage) requirements early in the system- design process, when errors can be corrected most easily and inexpensively.

Mayank, Vimal↗
NASA NTRS2009

Planning Complex Sequences Using Compressed Representations

A method that notably includes the use of compressed representations interleaved with non-compressed (time-line) representations of a general scheduling problem has been conceived as a means of increasing, by orders of magnitude, the speeds of computations needed for scheduling complex sequences of activities that include cycles wherein subsets of the activities and/or sequences are repeated. The method was originally intended to be used in scheduling large campaigns of scientific observations by instruments aboard a spacecraft. A typical such campaign could include observations of millions of targets, many observations to be made during long repeated passes. The method would also be useful on Earth for scheduling complex sequences of activities that include cycles.

Chien, Steve↗
NASA NTRS2007

Representation-Independent Iteration of Sparse Data Arrays

An approach is defined that describes a method of iterating over massively large arrays containing sparse data using an approach that is implementation independent of how the contents of the sparse arrays are laid out in memory. What is unique and important here is the decoupling of the iteration over the sparse set of array elements from how they are internally represented in memory. This enables this approach to be backward compatible with existing schemes for representing sparse arrays as well as new approaches. What is novel here is a new approach for efficiently iterating over sparse arrays that is independent of the underlying memory layout representation of the array. A functional interface is defined for implementing sparse arrays in any modern programming language with a particular focus for the Chapel programming language. Examples are provided that show the translation of a loop that computes a matrix vector product into this representation for both the distributed and not-distributed cases. This work is directly applicable to NASA and its High Productivity Computing Systems (HPCS) program that JPL and our current program are engaged in. The goal of this program is to create powerful, scalable, and economically viable high-powered computer systems suitable for use in national security and industry by 2010. This is important to NASA for its computationally intensive requirements for analyzing and understanding the volumes of science data from our returned missions.

James, Mark↗
NASA NTRS2010

Improving the Representation of Snow Crystal Properties with a Single-Moment Mircophysics Scheme

Single-moment microphysics schemes are utilized in an increasing number of applications and are widely available within numerical modeling packages, often executed in near real-time to aid in the issuance of weather forecasts and advisories. In order to simulate cloud microphysical and precipitation processes, a number of assumptions are made within these schemes. Snow crystals are often assumed to be spherical and of uniform density, and their size distribution intercept may be fixed to simplify calculation of the remaining parameters. Recently, the Canadian CloudSat/CALIPSO Validation Project (C3VP) provided aircraft observations of snow crystal size distributions and environmental state variables, sampling widespread snowfall associated with a passing extratropical cyclone on 22 January 2007. Aircraft instrumentation was supplemented by comparable surface estimations and sampling by two radars: the C-band, dual-polarimetric radar in King City, Ontario and the NASA CloudSat 94 GHz Cloud Profiling Radar. As radar systems respond to both hydrometeor mass and size distribution, they provide value when assessing the accuracy of cloud characteristics as simulated by a forecast model. However, simulation of the 94 GHz radar signal requires special attention, as radar backscatter is sensitive to the assumed crystal shape. Observations obtained during the 22 January 2007 event are used to validate assumptions of density and size distribution within the NASA Goddard six-class single-moment microphysics scheme. Two high resolution forecasts are performed on a 9-3-1 km grid, with C3VP-based alternative parameterizations incorporated and examined for improvement. In order to apply the CloudSat 94 GHz radar to model validation, the single scattering characteristics of various crystal types are used and demonstrate that the assumption of Mie spheres is insufficient for representing CloudSat reflectivity derived from winter precipitation. Furthermore, snow density and size distribution characteristics are allowed to vary with height, based upon direct aircraft estimates obtained from C3VP data. These combinations improve the representation of modeled clouds versus their radar-observed counterparts, based on profiles and vertical distributions of reflectivity. These meteorological events are commonplace within the mid-latitude cold season and present a challenge to operational forecasters. This study focuses on one event, likely representative of others during the winter season, and aims to improve the representation of snow for use in future operational forecasts.

Molthan, Andrew L.↗
NASA NTRS2010

Radiation Dose Assessments of Solar Particle Events with Spectral Representation at High Energies for the Improvement of Radiation Protection

For radiation dose assessments of major solar particle events (SPEs), spectral functional forms of SPEs have been made by fitting available satellite measurements up to approx.100 MeV. However, very high-energy protons (above ~500 MeV) have been observed with neutron monitors (NMs) in ground level enhancements (GLEs), which generally present the most severe radiation hazards to astronauts. Due to technical difficulties in converting NM data into absolutely normalized fluence measurements, those functional forms were made with little or no use of NM data. A new analysis of NM data has found that a double power law in rigidity (the so-called Band function) generally provides a satisfactory representation of the combined satellite and NM data from approx.10 MeV to approx.10 GeV in major SPEs (Tylka & Dietrich 2009). We use the Band function fits to re-assess human exposures from large SPEs. Using different spectral representations of large SPEs, variations of exposure levels were compared. The results can be applied to the development of approaches of improved radiation protection for astronauts, as well as the optimization of mission planning and shielding for future space missions.

Kim, Myung-Hee↗
NASA NTRS2006

Generating a 2D Representation of a Complex Data Structure

A computer program, designed to assist in the development and debugging of other software, generates a two-dimensional (2D) representation of a possibly complex n-dimensional (where n is an integer >2) data structure or abstract rank-n object in that other software. The nature of the 2D representation is such that it can be displayed on a non-graphical output device and distributed by non-graphical means.

James, Mark↗
NASA NTRS2012

A Discussion on Uncertainty Representation and Interpretation in Model-Based Prognostics Algorithms based on Kalman Filter Estimation Applied to Prognostics of Electronics Components

This article discusses several aspects of uncertainty representation and management for model-based prognostics methodologies based on our experience with Kalman Filters when applied to prognostics for electronics components. In particular, it explores the implications of modeling remaining useful life prediction as a stochastic process and how it relates to uncertainty representation, management, and the role of prognostics in decision-making. A distinction between the interpretations of estimated remaining useful life probability density function and the true remaining useful life probability density function is explained and a cautionary argument is provided against mixing interpretations for the two while considering prognostics in making critical decisions.

Celaya, Jose R.↗
NASA NTRS2012

Representation of Probability Density Functions from Orbit Determination using the Particle Filter

Statistical orbit determination enables us to obtain estimates of the state and the statistical information of its region of uncertainty. In order to obtain an accurate representation of the probability density function (PDF) that incorporates higher order statistical information, we propose the use of nonlinear estimation methods such as the Particle Filter. The Particle Filter (PF) is capable of providing a PDF representation of the state estimates whose accuracy is dependent on the number of particles or samples used. For this method to be applicable to real case scenarios, we need a way of accurately representing the PDF in a compressed manner with little information loss. Hence we propose using the Independent Component Analysis (ICA) as a non-Gaussian dimensional reduction method that is capable of maintaining higher order statistical information obtained using the PF. Methods such as the Principal Component Analysis (PCA) are based on utilizing up to second order statistics, hence will not suffice in maintaining maximum information content. Both the PCA and the ICA are applied to two scenarios that involve a highly eccentric orbit with a lower apriori uncertainty covariance and a less eccentric orbit with a higher a priori uncertainty covariance, to illustrate the capability of the ICA in relation to the PCA.

Mashiku, Alinda K.↗
NASA NTRS2012

Uncertainty Representation and Interpretation in Model-Based Prognostics Algorithms Based on Kalman Filter Estimation

This article discusses several aspects of uncertainty representation and management for model-based prognostics methodologies based on our experience with Kalman Filters when applied to prognostics for electronics components. In particular, it explores the implications of modeling remaining useful life prediction as a stochastic process, and how it relates to uncertainty representation, management and the role of prognostics in decision-making. A distinction between the interpretations of estimated remaining useful life probability density function is explained and a cautionary argument is provided against mixing interpretations for two while considering prognostics in making critical decisions.

Galvan, Jose Ramon↗
NASA NTRS2012

A Generalized Timeline Representation, Services, and Interface for Automating Space Mission Operations

Most use a timeline based representation for operations modeling. Most model a core set of state, resource types. Most provide similar capabilities on this modeling to enable (semi) automated schedule generation. In this paper we explore the commonality of : representation and services for these timelines. These commonalities offer potential to be harmonized to enable interoperability, re-use.

timeline-based systems↗
NASA NTRS2013

Representation of Nucleation Mode Microphysics in a Global Aerosol Model with Sectional Microphysics

In models, nucleation mode (1 nm<Dp <10 nm) particle microphysics can be represented explicitly with aerosol microphysical processes or can be parameterized to obtain the growth and survival of nuclei to the model's lower size boundary. This study investigates how the representation of nucleation mode microphysics impacts aerosol number predictions in the TwO-Moment Aerosol Sectional (TOMAS) aerosol microphysics model running with the GISS GCM II-prime by varying its lowest diameter boundary: 1 nm, 3 nm, and 10 nm. The model with the 1 nm boundary simulates the nucleation mode particles with fully resolved microphysical processes, while the model with the 10 nm and 3 nm boundaries uses a nucleation mode dynamics parameterization to account for the growth of nucleated particles to 10 nm and 3 nm, respectively.We also investigate the impact of the time step for aerosol microphysical processes (a 10 min versus a 1 h time step) to aerosol number predictions in the TOMAS models with explicit dynamics for the nucleation mode particles (i.e., 3 nm and 1 nm boundary). The model with the explicit microphysics (i.e., 1 nm boundary) with the 10 min time step is used as a numerical benchmark simulation to estimate biases caused by varying the lower size cutoff and the time step. Different representations of the nucleation mode have a significant effect on the formation rate of particles larger than 10 nm from nucleated particles (J10) and the burdens and lifetimes of ultrafinemode (10 nm≤Dp ≤70 nm) particles but have less impact on the burdens and lifetimes of CCN-sized particles. The models using parameterized microphysics (i.e., 10 nm and 3 nm boundaries) result in higher J10 and shorter coagulation lifetimes of ultrafine-mode particles than the model with explicit dynamics (i.e., 1 nm boundary). The spatial distributions of CN10 (Dp ≥10 nm) and CCN(0.2 %) (i.e., CCN concentrations at 0.2%supersaturation) are moderately affected, especially CN10 predictions above ∼700 hPa where nucleation contributes most strongly to CN10 concentrations. The lowermost-layer CN10 is substantially improved with the 3 nm boundary (compared to 10 nm) in most areas. The overprediction in CN10 with the 3 nm and 10 nm boundaries can be explained by the overprediction of J10 or J3 with the parameterized microphysics, possibly due to the instantaneous growth rate assumption in the survival and growth parameterization. The errors in CN10 predictions are sensitive to the choice of the lower size boundary but not to the choice of the time step applied to the microphysical processes. The spatial distribution of CCN(0.2 %) with the 3 nm boundary is almost identical to that with the 1 nm boundary, but that with the 10 nm boundary can differ more than 10-40% in some areas. We found that the deviation in the 10 nm simulations is partly due to the longer time step (i.e., 1 h time step used in the 10 nm simulations compared to 10 min time step used in the benchmark simulations), but, even with the same time step, the 10 nm cutoff showed noticeably higher errors than the 3 nm cutoff. In conclusion, we generally recommend using a lower diameter boundary of 3 nm for studies focused on aerosol indirect effects but down to 1 nm boundary for studies focused on CN10 predictions or nucleation.

microphysics↗
NASA NTRS2014

Recent Advances in Registration, Integration and Fusion of Remotely Sensed Data: Redundant Representations and Frames

In recent years, sophisticated mathematical techniques have been successfully applied to the field of remote sensing to produce significant advances in applications such as registration, integration and fusion of remotely sensed data. Registration, integration and fusion of multiple source imagery are the most important issues when dealing with Earth Science remote sensing data where information from multiple sensors, exhibiting various resolutions, must be integrated. Issues ranging from different sensor geometries, different spectral responses, differing illumination conditions, different seasons, and various amounts of noise need to be dealt with when designing an image registration, integration or fusion method. This tutorial will first define the problems and challenges associated with these applications and then will review some mathematical techniques that have been successfully utilized to solve them. In particular, we will cover topics on geometric multiscale representations, redundant representations and fusion frames, graph operators, diffusion wavelets, as well as spatial-spectral and operator-based data fusion. All the algorithms will be illustrated using remotely sensed data, with an emphasis on current and operational instruments.

Fusion↗
NASA NTRS2018

Carbon-Nitrogen Coupling Under Three Schemes of Model Representation: A Traceability Analysis

The interaction between terrestrial carbon (C) and nitrogen (N) cycles has been incorporated into more and more land surface models. However, the scheme of C-N coupling differs greatly among models, and how these diverse representations of C-N interactions will affect C-cycle modeling remains unclear. In this study, we explored how the simulated ecosystem C storage capacity in the terrestrial ecosystem (TECO) model varied with three different commonly used schemes of C-N coupling. The three schemes (SM1, SM2, and SM3) have been used in three different coupled C-N models (i.e., TECO-CN, CLM 4.5, and O-CN, respectively). They differ mainly in the stoichiometry of C and N in vegetation and soils, plant N uptake strategies, down regulation of photosynthesis, and the pathways of N import. We incorporated the three C-N coupling schemes into the C-only version of the TECO model and evaluated their impacts on the C cycle with a traceability framework. Our results showed that all three of the C-N schemes caused significant reductions in steady-state C storage capacity compared with the C-only version with magnitudes of −23%, −30%, and −54% for SM1, SM2, and SM3, respectively. This reduced C storage capacity was mainly derived from the combined effects of decreases in net primary productivity (NPP; −29%, −15%, and −45%) and changes in mean C residence time (MRT; 9%, −17%, and −17%) for SM1, SM2, and SM3, respectively. The differences in NPP are mainly attributed to the different assumptions on plant N uptake, plant tissue C : N ratio, down regulation of photosynthesis, and biological N fixation. In comparison, the alternative representations of the plant vs. microbe competition strategy and the plant N uptake, combined with the flexible C : N ratio in vegetation and soils, led to a notable spread in MRT. These results highlight the fact that the diverse assumptions on N processes represented by different C-N coupled models could cause additional uncertainty for land surface models. Understanding their difference can help us improve the capability of models to predict future biogeochemical cycles of terrestrial ecosystems.

Du, Zhenggang↗
NASA NTRS2018

Impact of Assimilating AIRS Cloud-Cleared Radiances on Atmospheric Dynamics and Polar Low Representation at High Latitudes

This study explores the sensitivity of planetary boundary layer height and related atmospheric dynamics to the assimilation of cloud-cleared AIRS (Atmospheric Infrared Sounder) radiances in the Goddard Earth Observing System (GEOS, version 5) data assimilation and forecast system during the boreal fall 2014 season using observing system experiments (OSEs). Examined here are comparisons between the current, operational approach of assimilating AIRS clear-sky radiances against the assimilation of cloud-cleared radiances (CCR). In polar regions, assimilation of AIRS CCRs is particularly beneficial because of the sparsity of conventional observations and the prevalence of extended low-level stratus cloud cover, which limit the ingestion of clear-sky data. Assimilation of hyperspectral infrared information from AIRS over the Arctic region slightly modifies the lower midtropospheric temperature structure, which in turn contributes to adjustments in geopotential height, affecting the baroclinic instability properties over the entire hemisphere and explaining the overall improvement in global forecast skill. In addition, it is shown that the assimilation of CCRs benefits the representation of convectively-driven small-scale cyclones at high latitudes in the same way as previously noted for tropical cyclones. Specifically, assimilation of CCRs create a temperature dipole over the top of meteorologically active and strongly convective systems such as polar, arctic, and antarctic lows, which helps constrain the analyzed representation of their scale and vertical structure.

Mcgrath-Spangler, E. L.↗
NASA NTRS2019

The Effects of an Improved Dynamic Vegetation Phenology Representation in a Global Land Surface Model

Evapotranspiration (ET) is a major driver of the interaction between the land surface and the atmosphere through its component mechanisms, including plant transpiration (T) and soil evaporation. To accurately capture land-atmosphere interactions in global Earth System Models, it is thus critical that the underlying land surface models accurately model both the land hydrology as well as the dynamic response of vegetation to environmental drivers. In an effort to introduce a more realistic vegetation representation, the NASA Catchment land surface model, which is part of the Goddard Earth Observing System (GEOS), has previously been merged with the carbon and nitrogen physics modules of the Community Land Model version 4, resulting in the new Catchment-CN model. Catchment-CN has inherited the advanced treatment of land surface hydrology of Catchment, but is additionally able to dynamically model the response of vegetation to environmental drivers, in contrast to the fixed vegetation climatology that was prescribed in Catchment. Recently, the parameterization of Catchment-CN vegetation has been augmented to better account for variability of vegetation responses to external forcings within existing plant functional types, and vegetation parameters have been calibrated against Moderate Resolution Imaging Spectrometer observations of the fraction of absorbed photosynthetically radiation. These efforts have led to a significant reduction in the RMSE of modeled photosynthetic activity with respect to observations.This presentation investigates the effect of the improved vegetation representation on the partitioning of ET within Catchment-CN. Specifically, we compare global maps of the T:ET ratio across different temporal scales in (1) the original Catchment model, (2) the original Catchment-CN model, and (3) the augmented and calibrated Catchment-CN model. The modeled T and ET estimates are compared against a comprehensive set of ground observations from various field studies, as well as independent global T:ET estimates from different ET algorithms provided in the context of the Water Cycle Observation Multi-mission Strategy ? Evapotranspiration (WACMOS-ET) initiative.

Kolassa, J.↗
NASA NTRS2020

Representation of Modes of Variability in 6 U.S. Climate Models

We compare the performance of several modes of variability across six US climate modeling groups, with a focus on identifying robust improvements in recent models (including those participating in the Coupled Model Intercomparison Project (CMIP) Phase 6) compared to previous versions. In particular, we examine the representation of the Madden-Julian Oscillation (MJO), the El Ni˜no/Southern Oscillation (ENSO), the Pacific Decadal Oscillation (PDO), the Quasi-Biennial Oscillation (QBO) in the tropical stratosphere and the dominant modes of extra-tropical variability, including the Southern Annular Mode (SAM), the Northern Annular Mode (NAM) (and the closely related North Atlantic Oscillation (NAO)), and the Pacific-North American Pattern (PNA). Where feasible, we explore the processes driving these improvements through the use of “intermediary” experiments that utilize model versions between CMIP3/5 and CMIP6 as well as targeted sensitivity experiments in which individual modeling parameters are altered. We find clear and systematic improvements in the MJO and QBO and in the teleconnection patterns associated with the PDO and ENSO. Some gains arise from better process representation, while others (e.g. the QBO) from higher resolution that allows for a greater range of interactions. Our results demonstrate that the incremental development processes in multiple climate model groups lead to more realistic simulations over time.

Modes of variability↗