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At least 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Confronting the Challenge of Modeling Cloud and Precipitation Microphysics

In the atmosphere, microphysics refers to the microscale processes that affect cloud and precipitation particles and is a key linkage among the various components of Earth’s atmospheric water and energy cycles. The representation of microphysical processes in models continues to pose a major challenge leading to uncertainty in numerical weather forecasts and climate simulations. In this paper, the problem of treating microphysics in models is divided into two parts: i) how to represent the population of cloud and precipitation particles, given the impossibility of simulating all particles individually within a cloud, and ii) uncertainties in the microphysical process rates owing to fundamental gaps in knowledge of cloud physics. The recently-developed Lagrangian particle-based method is advocated as a way to address several conceptual and practical challenges of representing particle populations using traditional bulk and bin microphysics parameterization schemes. For addressing critical gaps in cloud physics knowledge, sustained investment for observational advances from laboratory experiments, new probe development, and next-generation instruments in space is needed. Greater emphasis on laboratory work, which has apparently declined over the past several decades relative to other areas of cloud physics research, is argued to be an essential ingredient for improving process-level understanding. More systematic use of natural cloud and precipitation observations to constrain microphysics schemes is also advocated. Because it is generally difficult to quantify individual microphysical process rates from these observations directly, this presents an inverse problem that can be viewed from the standpoint of Bayesian statistics. Following this idea, a probabilistic framework is proposed that combines elements from statistical and physical modeling. Besides providing rigorous constraint of schemes, there is an added benefit of quantifying uncertainty systematically. Finally, a broader hierarchical approach is proposed to accelerate improvements in microphysics schemes, leveraging the advances described in this paper related to process modeling (using Lagrangian particle-based schemes), laboratory experimentation, cloud and precipitation observations, and statistical methods.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

On the curvature effect of a relativistic spherical shell

We consider a relativistic spherical shell and calculate its spectral flux as received by a distant observer. Using two different methods, we derive a simple analytical expression of the observed spectral flux and show that the well-known relation α-hat =2+ β-hat (between temporal index α-hat and spectral index β-hat ) of the high-latitude emission is naturally achieved in our derivation but holds only when the shell moves with a constant Lorentz factor Γ. Presenting numerical models in which the shell is undergoing acceleration or deceleration, we show that the simple α-hat =2+ β-hat relation does indeed deviate as long as Γ is not constant. For the models under acceleration, we find that the light curves produced purely by the high-latitude emission initially exhibit much steeper decay than in the constant Γ case and gradually resume the α-hat =2+ β-hat relation in about one and a half orders of magnitude in observer time. For the models under deceleration, the trend is opposite. The light curves made purely by the high-latitude emission initially exhibit a shallower decay than in the constant Γ case and gradually resume the relation α-hat =2+ β-hat in a similar order of magnitude in observer time. We also show that how fast the Lorentz factor Γ of the shell increases or decreases is the main ingredient determining the initial steepness or shallowness of the light curves.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Explosion Discrimination Using Seismic Gradiometry and Spectral Filtering of Data

Here, we present a new method to discriminate between earthquakes and buried explosions using observed seismic data. The method is different from previous seismic discrimination algorithms in two main ways. First, we use seismic spatial gradients, as well as the wave attributes estimated from them (referred to as gradiometric attributes), rather than the conventional three-component seismograms recorded on a distributed array. The primary advantage of this is that a gradiometer is only a fraction of a wavelength in aperture compared with a conventional seismic array or network. Second, we use the gradiometric attributes as input data into a machine learning algorithm. The resulting discrimination algorithm uses the norms of truncated principal components obtained from the gradiometric data to distinguish the two classes of seismic events. Using high-fidelity synthetic data, we show that the data and gradiometric attributes recorded by a single seismic gradiometer performs as well as a conventional distributed array at the event type discrimination task.

58 GEOSCIENCES↗
DOE OSTI2014

Evaluation of advanced automatic PET segmentation methods using nonspherical thin-wall inserts

Purpose: The use of positron emission tomography (PET) within radiotherapy treatment planning requires the availability of reliable and accurate segmentation tools. PET automatic segmentation (PET-AS) methods have been recommended for the delineation of tumors, but there is still a lack of thorough validation and cross-comparison of such methods using clinically relevant data. In particular, studies validating PET segmentation tools mainly use phantoms with thick plastic walls inserts of simple spherical geometry and have not specifically investigated the effect of the target object geometry on the delineation accuracy. Our work therefore aimed at generating clinically realistic data using nonspherical thin-wall plastic inserts, for the evaluation and comparison of a set of eight promising PET-AS approaches. Methods: Sixteen nonspherical inserts were manufactured with a plastic wall of 0.18 mm and scanned within a custom plastic phantom. These included ellipsoids and toroids derived with different volumes, as well as tubes, pear- and drop-shaped inserts with different aspect ratios. A set of six spheres of volumes ranging from 0.5 to 102 ml was used for a baseline study. A selection of eight PET-AS methods, written in house, was applied to the images obtained. The methods represented promising segmentation approaches such as adaptive iterative thresholding, region-growing, clustering and gradient-based schemes. The delineation accuracy was measured in terms of overlap with the computed tomography reference contour, using the dice similarity coefficient (DSC), and error in dimensions. Results: The delineation accuracy was lower for nonspherical inserts than for spheres of the same volume in 88% cases. Slice-by-slice gradient-based methods, showed particularly lower DSC for tori (DSC < 0.5), caused by a failure to recover the object geometry. The region-growing method reached high levels of accuracy for most inserts (DSC > 0.76 except for tori) but showed the largest errors in the recovery of pears and drops dimensions (higher than 10% and 30% of the true length, respectively). Large errors were visible for one of the gradient-based contouring methods when delineating drop-shaped inserts. Low DSC due to systematic underestimation of the volumes was observed for our fuzzy clustering method when using nonspherical inserts. The adaptive iterative thresholding method produced the highest DSC score on our nonspherical dataset (DSC > 0.83, except for tori) and showed robustness to the insert geometry. Conclusions: This study investigated the accuracy of eight PET-AS methods for the delineation of objects with a range of nonspherical geometries. The authors’ results confirmed the robustness of some segmentation approaches, but also showed the weaknesses of some of the other methods implemented, which were not observed with spherical inserts. This work therefore highlights the importance of using a variety of thin-wall inserts with complex geometries for the validation of PET-AS methods and provided useful information for further development of the methods tested.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
NASA NTRS1987

Experience in grid optimization

Two optimization methods for solving a variational problem in grid generation are described and evaluated. The smoothness, cell volumes, and orthogonality of the variational integrals are examined. The Jacobi-Newton iterative method is compared to the Fletcher-Reeves conjugate gradient method. It is observed that a combination of the Jacobi-Newton iteration and the direct solution of the variational problem produces an algorithm which is easy to program and requires less storage and computer time/iteration than the conjugate gradient method.

Mastin, C. W.↗
NASA NTRSDate not supplied

Wall-Modeled LES of a Swept Wing with Leading-Edge Ice Using LAVA Curvilinear, Unstructured, and Cartesian Solvers

Wall-modeled large-eddy simulation (LES) of a swept wing with leading-edge ice build up is performed using three mesh paradigms and associated flow solvers and compared to experimental results. The study focuses on an 8.9% scale model of the CRM65 swept wing featuring both high-fidelity and smooth leading-edge ice shapes. The assessment is conducted using the Launch, Ascent, and Vehicle Aerodynamics (LAVA) framework using the three actively supported meshing paradigms in LAVA: structured curvilinear overset, unstructured, andCartesian. For the iced configurations, these paradigms use hybrid body-fitted/source-term immersed-boundary, body-fitted, and ghost-cell immersed-boundary strategies, respectively.The unstructured and Cartesian mesh paradigms are particularly attractive for complex ice shapes as they avoid the manual mesh generation effort associated with the curvilinear approach. For the high-fidelity ice shape, good agreement with the experiment can be obtained with all three strategies; however, the curvilinear method is particularly sensitive to the source-term immersed-boundary timescale and span wise mesh resolution, and the Cartesian implementation is sensitive to the choice of numerical flux. For the smooth ice, larger discrepancies are observed across all methods. However, a mesh refinement study guided by flow visualizations leads to an improved comparison with the experiment that is particularly pronounced for the unstructured mesh paradigm.

TTT↗
NASA NTRS1992

On potential field models of the solar corona

It is shown that the line-of-sight matching procedure involved in potential field models of the solar corona do not make good use of the available data because there is strong evidence that the magnetic field is nearly radial, and therefore nonpotential, at the photosphere. It is argued that the observed photospheric field should first be corrected for line-of-sight projection and then matched to the radial component of the potential field. It is shown that this procedure yields much stronger polar fields than the standard method and produces better agreement with high-latitude coronal holes and with white-light structures in the outer corona. The relationship of both methods to the observed inclination angles of polar plumes is also discussed.

Wang, Y.-M.↗
NASA NTRS2016

Demonstrating the Error Budget for the Climate Absolute Radiance and Refractivity Observatory Through Solar Irradiance Measurements

The Climate Absolute Radiance and Refractivity Observatory (CLARREO) mission addresses the need to observe highaccuracy, long-term climate change trends and to use decadal change observations as a method to determine the accuracy of climate change. A CLARREO objective is to improve the accuracy of SI-traceable, absolute calibration at infrared and reflected solar wavelengths to reach on-orbit accuracies required to allow climate change observations to survive data gaps and observe climate change at the limit of natural variability. Such an effort will also demonstrate National Institute of Standards and Technology (NIST) approaches for use in future spaceborne instruments. The current work describes the results of laboratory and field measurements with the Solar, Lunar for Absolute Reflectance Imaging Spectroradiometer (SOLARIS) which is the calibration demonstration system (CDS) for the reflected solar portion of CLARREO. SOLARIS allows testing and evaluation of calibration approaches, alternate design and/or implementation approaches and components for the CLARREO mission. SOLARIS also provides a test-bed for detector technologies, non-linearity determination and uncertainties, and application of future technology developments and suggested spacecraft instrument design modifications. Results of laboratory calibration measurements are provided to demonstrate key assumptions about instrument behavior that are needed to achieve CLARREO's climate measurement requirements. Absolute radiometric response is determined using laser-based calibration sources and applied to direct solar views for comparison with accepted solar irradiance models to demonstrate accuracy values giving confidence in the error budget for the CLARREO reflectance retrieval.

CLARREO↗
DOE OSTI2019

Constraining the neutron-matter equation of state with gravitational waves

We demonstrate how observations of gravitational waves from binary neutron star (BNS) mergers over the next few years can be combined with insights from nuclear physics to obtain useful constraints on the equation of state (EoS) of dense matter. In particular, the neutron-matter EoS between 1 and 2 times the nuclear saturation density $n_0$ ≈ 0.16 fm –3 can be constrained to within 20%, given the simulated data from about 15 merger events. Using Fisher information methods, we combine observational constraints from simulated BNS merger events drawn from various population models with independent measurements of the neutron star radii expected from x-ray astronomy [the Neutron Star Interior Composition Explorer observations in particular] to directly constrain nuclear physics parameters. To parametrize the nuclear EoS, we use a different approach, expanding from pure nuclear matter rather than from symmetric nuclear matter to make use of recent quantum Monte Carlo calculations. This method eschews the need to invoke the so-called parabolic approximation to extrapolate from symmetric nuclear matter, allowing us to directly constrain the neutron-matter EoS. Using a principal component analysis, we identify the combination of parameters most tightly constrained by observational data. We discuss sensitivity to various effects such as different component masses through population-model sensitivity, phase transitions in the core EoS, and large deviations from the central parameter values.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2016

Zeldovich pancakes in observational data are cold

The present day universe consists of galaxies, galaxy clusters, one-dimensional filaments and two-dimensional sheets or pancakes, all of which combine to form the cosmic web. The so called ''Zeldovich pancakes' are very difficult to observe, because their overdensity is only slightly greater than the average density of the universe. Falco et al. [1] presented a method to identify Zeldovich pancakes in observational data, and these were used as a tool for estimating the mass of galaxy clusters. Here we expand and refine that observational detection method. We study two pancakes on scales of 10 Mpc, identified from spectroscopically observed galaxies near the Coma cluster, and compare with twenty numerical pancakes.We find that the observed structures have velocity dispersions of about 100 km/sec, which is relatively low compared to typical groups and filaments. These velocity dispersions are consistent with those found for the numerical pancakes. We also confirm that the identified structures are in fact two-dimensional structures. Finally, we estimate the stellar to total mass of the observational pancakes to be 2 · 10{sup −4}, within one order of magnitude, which is smaller than that of clusters of galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Spectral shape corrections for SDSS BOSS quasars

Modifications were made to the Sloan Digital Sky Survey’s Baryonic Oscillations Spectroscopic Survey (SDSS/BOSS) optical fibres assigned to quasar targets in order to improve the signal-to-noise ratio in the Ly-α forest. However, the consequence of these modifications is that quasars observed in this way require additional flux correction procedures in order to recover the correct spectral shapes. Here, in this paper, we describe such a procedure, based on the geometry of the problem, and other observational parameters. Applying several correction methods to four SDSS quasars with multiple observations permits a detailed verification of the relative performances of the different flux correction procedures. We contrast our method (which takes into account a wavelength-dependent seeing profile) with the BOSS pipeline approach (which does not). Our results provide independent confirmation that the geometric approach employed in the SDSS pipeline works well, although with room for improvement. By separating the contributions from four effects, we are able to quantify their relative importance. Most importantly, we demonstrate that wavelength dependence has a significant impact on the derived spectral shapes and thus should not be ignored.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Validation and quantification of uncertainty in coupled climate models using network analysis

We developed a fast, robust and scalable methodology to examine, quantify, and visualize climate patterns and their relationships. It is based on a set of notions, algorithms and metrics used in the study of graphs, referred to as complex network analysis. This approach can be applied to explain known climate phenomena in terms of an underlying network structure and to uncover regional and global linkages in the climate system, while comparing general circulation models outputs with observations. The proposed method is based on a two-layer network representation, and is substantially new within the available network methodologies developed for climate studies. At the first layer, gridded climate data are used to identify ‘‘areas’’, i.e., geographical regions that are highly homogeneous in terms of the given climate variable. At the second layer, the identified areas are interconnected with links of varying strength, forming a global climate network. The robustness of the method (i.e. the ability to separate between topological distinct fields, while identifying correctly similarities) has been extensively tested. It has been proved that it provides a reliable, fast framework for comparing and ranking the ability of climate models of reproducing observed climate patterns and their connectivity. We further developed the methodology to account for lags in the connectivity between climate patterns and refined our area identification algorithm to account for autocorrelation in the data. The new methodology based on complex network analysis has been applied to state-of-the-art climate model simulations that participated to the last IPCC (International Panel for Climate Change) assessment to verify their performances, quantify uncertainties, and uncover changes in global linkages between past and future projections. Network properties of modeled sea surface temperature and rainfall over 1956–2005 have been constrained towards observations or reanalysis data sets, and their differences quantified using two metrics. Projected changes from 2051 to 2300 under the scenario with the highest representative and extended concentration pathways (RCP8.5 and ECP8.5) have then been determined. The network of models capable of reproducing well major climate modes in the recent past, changes little during this century. In contrast, among those models the uncertainties in the projections after 2100 remain substantial, and primarily associated with divergences in the representation of the modes of variability, particularly of the El Niño Southern Oscillation (ENSO), and their connectivity, and therefore with their intrinsic predictability, more so than with differences in the mean state evolution. Additionally, we evaluated the relation between the size and the ‘strength’ of the area identified by the network analysis as corresponding to ENSO noting that only a small subset of models can reproduce realistically the observations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Observer-based H{sub ∞} control for nonlinear Markovian jump systems with time-delay and input saturation

This paper focus on the problem of observer-based H{sub ∞} control for uncertain nonlinear Markovian jump systems with time-delay and actuator saturation. A delay-dependent sufficient condition is proposed which guarantees that the uncertain nonlinear Markovian jump system with time-delay and input saturation is stochastically stable via Lyapunov theory and linear matrix inequality (LMI) approach. Then, with this condition, the estimation of stability region and the design method of observer-based H{sub ∞} controller are given by solving LMIs and convex optimization problems. Finally, numerical examples are exploited to illustrate the effectiveness of the proposed method.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1982

AVE/VAS 3: 25-mb sounding data

The rawinsonde sounding program for the AVE/VAS 3 experiment is described. Tabulated data are presented at 25-mb intervals for the 24 National Weather Service stations and 14 special stations participating in the experiment. Soundings were taken at 3-hr intervals, beginning at 1200 GMT on March 27, 1982, and ending at 0600 GMT on March 28, 1982 (7 sounding times). An additional sounding was taken at the National Weather Service stations at 1200 GMT on March 28, 1982, at the normal synoptic observation time. The method of processing soundings is briefly discussed, estimates of the RMS errors in the data are presented, and an example of contact data is given. Termination pressures of soundings taken in the mesos-beta-scale network are tabulated, as are observations of ground temperature at a depth of 2 cm.

Sienkiewicz, M. E.↗
NASA NTRS1993

Analysis of the GOES 6.7 micrometer channel observations during FIRE 2

Clouds form in moist environments. FIRE Phase II Cirrus Implementation Plan (August, 1990) noted the need for mesoscale measurements of upper tropospheric water vapor content. These measurements are needed for initializing and verifying numerical weather prediction models and for describing the environment in which cirrus clouds develop and dissipate. Various instruments where deployed to measure the water vapor amounts of the upper troposphere during FIRE II (e.g. Raman lidar, CLASS sonds and new cryogenic frost hygrometer on-board aircraft). The formation, maintenance and dissipation of cirrus clouds involve the time variation of the water budget of the upper troposphere. The GOES 6.7 mu m radiance observations are sensitive to the upper tropospheric relative humidity, and therefore proved extremely valuable in planning aircraft missions during the field phase of FIRE II. Warm 6.7 mu m equivalent black body temperatures indicate a relatively dry upper troposphere and were associated with regions generally free of cirrus clouds. Regions that were colder, implying more moisture was available may or may not have had cirrus clouds present. Animation of a time sequence of 6.7 mu m images was particularly useful in planning various FIRE missions. The 6.7 mu m observations can also be very valuable in the verification of model simulations and describing the upper tropospheric synoptic conditions. A quantitative analysis of the 6.7 mu m measurement is required to successfully incorporate these satellite observations into describing the upper tropospheric water vapor budget. Recently, Soden and Bretherton (1993) have proposed a method of deriving an upper tropospheric humidity based on observations from the GOES 6.7 mu m observations. The method is summarized in the next section. In their paper they compare their retrieval method to radiance simulations. Observations were also compared to ECMWF model output to assess the model performance. The FIRE experiment provides a unique opportunity to further verify the GOES upper tropospheric relative humidity retrieval scheme by providing (1) aircraft observations to cross-validate the calibration of the GOES 6.7 mu m channel, (2) accurate upper tropospheric water vapor concentrations for verification, and (3) veritical variability of upper tropospheric water vapor.

Soden, B. J.↗
DOE OSTI2023

Observations of Ocean Surface Wave Attenuation in Sea Ice Using Seafloor Cables

Abstract The attenuation of ocean surface waves during seasonal ice cover is an important control on the evolution of Arctic coastlines. The spatial and temporal variations in this process have been challenging to resolve with conventional sampling using sparse arrays of moorings or buoys. We demonstrate a novel method for persistent observation of wave‐ice interactions using distributed acoustic sensing (DAS) along existing seafloor fiber optic telecommunications cables. DAS measurements span a 36‐km cross‐shore cable on the Beaufort Shelf from Oliktok Point, Alaska. DAS optical sensing of fiber strain‐rate provides a proxy for seafloor pressure, which we calibrate with wave buoy measurements during the ice‐free season (August 2022). We apply this calibration during the ice formation season (November 2021) to obtain unprecedented resolution of variable wave attenuation rates in new, partial ice cover. The location and strength of wave attenuation serve as proxies for ice coverage and thickness, especially during rapidly evolving events.

Smith, Madison M.↗