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At least 739 records · Page 41

A study of the effect of synoptic scale processes in GCM modelling

Research was conducted to help modeling groups at NASA to develop better weather forecasting and general circulation models (GCM) for activities relating to the meteorological uses of satellite data. The focus was on the physical processes that were being simulated by models: radiative effects and latent heat release associated with clouds; orographic influences; and heat transfer at the ocean and ice surfaces. An attempt was made to deduce the role of diabatic heating in North Atlantic cyclogenesis and in the global heat budget. Inferences were made in four studies: heat budget statistics from GCM assimilations; dynamics of north Atlantic cyclones; Cage-type energy budget calculations; and grid scale cloud formation. Mechanisms that were responsible for the variability and structure of the atmospheric on a hemispheric scale were studied by a hybrid of statistical analysis and theoretical modeling. Variability and structure are both related to synoptic scale processes through baroclinic and barotropic energy transformations.

Herman, Gerald F.↗

Evolution of the 1997-98 El Nino and La Nina: the Role of Altimetry in ENSO Studies and Prediction

El Nino and the Southern Oscillation (ENSO) are known to be a quasi-periodic coupled ocean-atmosphere phenomenon occurring roughly every 3-7 years. Its largest oceanic manifestations are found in the equatorial Pacific, but it is of global climatic significance. During the flight of the TOPEX]Poseidon altimeter, the equatorial Pacific was in the midst of an unusual period of prolonged ENSO warming in the mid-1990's. In 1997, the tropical Pacific witnessed the development of a major El Nino event, rivaling in strength the 1982-83 El Nino. The intensity of this El Nino, and its rapid intensification early in the calendar year, caught the scientific community by surprise. None of the forecast models, statistical or dynamical, captured these features of the 1997 El Nino, although those models that assimilated in situ ocean observations did better than most in predicting that the event would occur in 1997. The onset of the El Nino coincided with the occurrence of several westerly wind events in the western Pacific rather than to delayed oscillator physics. However, western Pacific sea levels were anomalously elevated a year and a half prior to the onset, which may have helped precondition the system to a particularly strong ENSO episode. The coming of La Nina was foreshadowed by large-scale drops in sea level in the western tropical Pacific and cyclonic wind stress curl anomalies far beyond the +\- 8 degrees latitude bounds of the TAO mooring array. In past El Nino events, the evolution of the coupled system could only be studied from the perspective of in situ observations. The 1997-1998 El Nino event will be the first time a major El Nino event will have been observed from start to finish via remotely-sensed measurements of sea surface topography, sea surface temperature, sea surface winds, ocean color, and precipitation. These observations have considerable potential for advancing coupled climate forecasts on time scales from seasons to decades. This presentation will address questions along the lines of: (1) What are the scientific problems in ENSO that can benefit most from altimetry data? (2) Are there any precursors in the global ocean-atmosphere system for the 1997-98 extreme event? (3) Is there a unique role of altimetry in detecting potential precursors?(4) Has Topex/Poseidon data been adequately used to improve ENSO forecasts? Is there any firm evidence? (6) What is the status of the transition of El Nino into a La Nina?

Busalacchi, Antonio J.↗

Impacts of NASA's Earth Observations on Subseasonal and Seasonal Forecasts

NASA's suite of Earth-observing satellites provides a unique view of many processes on Earth, with relevance on timescales ranging from hours to weeks and even years. NASA's observations span all parts of the Earth system: atmospheric, ocean, land and cryosphere, and include physical, chemical and biological components. This presentation explores use of NASA observations in extended-range prediction, from many days to months, using the Goddard Earth Observing System (GEOS) assimilation and predictive modeling capabilities. The skill of a weather forecast is linked to the fidelity of the initialization process (data assimilation) and the realistic representation of "fast" physical processes in the model. At longer time horizons, the slower "feedback" processes in the Earth System begin to take a more prominent role in the accuracy of the forecast. Simultaneously, forecast-skill attribution transitions away from feature-based metrics that emphasize smaller scales (e.g., representations of fronts and vortices) to metrics that emphasize the statistical distributions of large-scale features (e.g., ENSO diagnostics and teleconnections). This presentation will summarize studies performed using the GEOS-S2S (subseasonal to seasonal) system that explore the impacts of NASA observations on the fidelity of the forecasts. The GEOS-S2S system is configured for the atmosphere-ocean-land-ice model and is initialized using in-situ and space-based observations, including atmospheric aerosols and ozone which are not typically analyzed in such systems. The GEOS-S2S model routinely includes aerosol feedbacks, which systematically impact the realism of the forecasts, providing a first example of how suitable NASA observations impact the performance of the GEOS-S2S system. Studies in which a stratospheric chemistry module is activated in the GEOS-S2S system allow the impacts of ozone radiative feedbacks to be isolated. Space-based observations of sea-surface temperature and altimetry are routinely analyzed for the initialization of the GEOS-S2S system; recent advances allow the use of NASA's sea-surface salinity data, which are shown to impact the long-range skill of the forecasts.

Pawson, Steven↗

Feasibility of Coherent and Incoherent Backscatter Experiments from the AMPS Laboratory. Technical Section

A computer program simulated the spectrum which resulted when a radar signal was transmitted into the ionosphere for a finite time and received for an equal finite interval. The spectrum derived from this signal is statistical in nature because the signal is scattered from the ionosphere, which is statistical in nature. Many estimates of any property of the ionosphere can be made. Their average value will approach the average property of the ionosphere which is being measured. Due to the statistical nature of the spectrum itself, the estimators will vary about this average. The square root of the variance about this average is called the standard deviation, an estimate of the error which exists in any particular radar measurement. In order to determine the feasibility of the space shuttle radar, the magnitude of these errors for measurements of physical interest must be understood.

Mozer, F. S.↗

Modeling Stellar Jitter and its Effects on the Stellar Spectrum for More Precise Radial Velocity Measurements

Detection of Earth-size exoplanets is a technological and data analysis challenge. Future progress in Earth-mass exoplanet detection is expected from the development of extreme precision radial velocity (EPRV) measurements. The required precision of these measurements necessitates developing a new physics-based data analysis methodology to discriminate planetary signals from host-star-related effects, taking stellar variability and instrumental uncertainties into account. In this work, we investigate and quantify stellar disturbances of the planet-hosting solar-type star HD121504 from 3D radiative modeling obtained with the StellarBox code. The model was used to determine the statistical properties of the turbulent plasma and to obtain synthetic spectroscopic observations for several Fe I lines at different locations on the stellar disk to mimic high-resolution spectroscopic observations. Presented are the initial results of our effort to characterize stellar jitter properties as well as future objectives.

SMD↗

Evaluation Marcelling in Composites using Ultrasonic Guided Wave

Thermoplastic composite (TPC) material seldom manifests in-plane fiber waviness during manufacturing. In-plane fiber waviness is called marcelling. Marcelling com-promises the composite strength and performance. When present in a structure, marcelling is not only a surface defect but can extend partially along the thickness of the composite. There is no established nondestructive evaluation (NDE) method to detect and quantify marcelling in composite. Ultrasonic guided waves can saturate the complete thickness of a composite structure. Thus, physics of guided wave creates an opportunity to detect and quantify the marcelling in composites. Before guided waves could be used to detect marcelling, it is necessary to quantify the marcelling in the structure and identify the marcelling affected zones (MAZE). In this research first, high frequency scanning acoustic microscopy (SAM) was performed to quantify the marcelling and statistical distribution of the defects at different MAZE was obtained. Next the MAZE with known statistical distribution of quantified marcelling (marcelling wavelength and marcelling amplitude) was inspected using ultrasonic guided wave setup. The method quantified the guided wave feature as a function of quantitative degree of marcelling. The overarching objective of this research is to implement post process NDE inspection of TPC large structures where in plane fiber waviness or marcelling can be detected and MAZEs could be identified. Primary fining is that the reduction of wave velocity and amplitude of ultrasonic guided wave could be good indicators of MAZE. However, more rigorous calibration is necessary where inspection direction is carefully devised with respect to the marcelling.

HiCAM↗

On the physical state of QSO Lyman-alpha absorption clouds

Arguments are presented that QSO Lyman-alpha absorption lines might arise in denser environments than is usually thought, with a larger neutral fraction in the gas than in the usual models of rarefied intergalactic clouds, and a much smaller total mean mass density in Lyman-alpha clouds. A model is sketched in which collapse or collision of thermally unstable protogalactic clouds forms shocks which trigger the collapse of cool thin sheets. The statistical properties of absorption lines formed in this way are consistent with those of the observed Lyman-alpha forest.

Hogan, Craig J.↗

Parametric and experimental analysis using a power flow approach

Having defined and developed a structural power flow approach for the analysis of structure-borne transmission of structural vibrations, the technique is used to perform an analysis of the influence of structural parameters on the transmitted energy. As a base for comparison, the parametric analysis is first performed using a Statistical Energy Analysis approach and the results compared with those obtained using the power flow approach. The advantages of using structural power flow are thus demonstrated by comparing the type of results obtained by the two methods. Additionally, to demonstrate the advantages of using the power flow method and to show that the power flow results represent a direct physical parameter that can be measured on a typical structure, an experimental investigation of structural power flow is also presented. Results are presented for an L-shaped beam for which an analytical solution has already been obtained. Furthermore, the various methods available to measure vibrational power flow are compared to investigate the advantages and disadvantages of each method.

Cuschieri, J. M.↗

Comets after Hyakutake and Hale-Bopp

Being icy, cometary nuclei are the most easily modified bodies in the solar system - even modest heating is sufficient to induce significant weight loss. This sublimative loss and longterm storage far from the sun protect the nucleus against internal warming and ensure that cometary nuclei today contain the least processed material remaining from the early nebula - or perhaps from the natal cloud. The chemical compositions of ices, low temperature-refractory organics, and refractory minerals (and their physical states) provide sensitive probes of the origin and history of this material. The fortunate appearance of Hyakutake and Hale-Bopp has provided a wealth of information on these Oort cloud comets, obtained with a wide range of astronomical approaches. I will review certain key results for these comets, such as chemical abundances, isotopic abundance ratios, nuclear spin statistics, and nuclear vs extended production of "parent volatiles", and will illustrate how these test the origins of cometary material. A comparison with 1P/Halley--a third comet from the giant planet nebular region--will be discussed in the context of heterogeneity among these bodies.

Mumma, Michael J.↗

Remote Sensing, Uncertainty Quantification, and a Theory of Data Systems; Workshop Report

The purpose of the workshop was to invite statisticians, applied mathematicians, computer scientists, data system architects, experts in remote sensing technology, and Climate and Earth System scientists to review, discuss, and plan research on issues related to large-scale, efficient analysis of distributed data using spatial statistical methods. Our motivation in organizing this event was to catalyze interchange among experts on the fast-emerging problem of analysis of distributed data. As part of SAMSI's 2017-2018 Program on Mathematical and Statistical Methods for Climate and the Earth System, a Working Group on Remote Sensing was established to address statistical and mathematical research problems in the analysis of remote sensing data. The Working Group has five subgroups: 1) Spatial Retrieval Methodology (the so-called \Spatial-X" subgroup); 2) Spatial Analysis for Hyperspectral Data (the so-called \Spatial-Y" subgroup); 3) Emulators for Complex Forward Models; 4) Optimization for Remote Sensing Retrievals; and 5) Theory of Data Systems (ToDS). The ToDS subgroup spent the first half of this academic year formulating a framework in which to consider the joint problem of a) optimizing statistical methods for environments where data are distributed and too large to move to a central location, and b) the design of data system infrastructures within which to implement those statistical methods. To x ideas, the Workshop focused on spatial statistical methods. To date there are many new spatial statistical methods designed with massive data sets in mind, in the literature. However, very few have been implemented for remote sensing data, and none have been implemented in operational settings like those used by NASA and NOAA. A major impediment to their use in these cases is that the data are not only massive, but are stored in different physical locations. These data must be brought together in some way in order to estimate spatial covariance functions, but moving data to a central location for analysis is tedious at best and impossible at worst. Some remote data reduction is almost certainly necessary, but how much? What are the consequences for inference? The fundamental issue underlying these questions is how to navigate the trade-space between costs and uncertainty in the estimates or inferences that are ultimately produced.

Braverman, Amy↗

Outlook for research on subtropical marine stratiform clouds

A detailed description of the goals and methodology of the First International Satellite Cloud Cover Project Regional Experiment (FIRE) is presented. The purpose of the experiment is to develop physical models and parameterizations of fractional cloud cover over the Pacific Basin. In order to determine fractional cloud cover parameters, satellite observations by radar and lidar instruments will be combined with in situ measurements of the cloud-capped marine boundary layer. A description of a candidate experiment for the program is presented, and some general problems connected with the statistical characterization of satellite imagery are discussed.

Randall, D. A.↗

Use of a minimum rate of change formalism to quantify variability of extragalactic X-ray sources

A method to obtain rigorous, quantitative constraints on the rate of variability is suggested. The method is motivated by the case when the existence of time variability is unequivocal, but the statistical uncertainties are too large to apply more direct methods such as power spectrum analysis. Conceptually the data are fitted to a function of time and a set of free parameters. The method of Lagrange multipliers is used to solve for that parameter set which minimizes the value of the derivative at time t(m). The result can be related physically to the minimum efficiency with which rest mass must be converted to radiation energy. Slightly different formulations of the general principal are used to estimate maximum source size scales associated with the variability.

Schwartz, Daniel A.↗

The sun's luminosity over a complete solar cycle

The Active Cavity Radiometer Irradiance Monitor (ACRIM I) measured the sun's luminosity from early 1980 to late 1989. The first account of the complete ACRIM I data set is presented and evidence is given which confirms that solar luminosity varies with the 11-yr solar cycle. This slow variation closely follows statistical measures of the distribution of magnetic and photospheric features on the solar surface. An exception to this correlation occurred in the form of a remarkable irradiance excess during 1980, at about the time of the sunspot maximum of solar cycle 21. The linkage, over a whole cycle, of luminosity variation to photospheric activity suggests the existence of an unknown physical mechanism other than the thermal diffusion model that explains luminosity deficits due to sunspots. Luminosity models connecting total irradiance to global indicators of solar activity are consistent with the gross features of the variability but fail to account for the 1980 irradiance excess.

Willson, Richard C.↗

The formation of cosmic structure in a texture-seeded cold dark matter cosmogony

The growth of density fluctuations induced by global texture in an Omega = 1 cold dark matter (CDM) cosmogony is calculated. The resulting power spectra are in good agreement with each other, with more power on large scales than in the standard inflation plus CDM model. Calculation of related statistics (two-point correlation functions, mass variances, cosmic Mach number) indicates that the texture plus CDM model compares more favorably than standard CDM with observations of large-scale structure. Texture produces coherent velocity fields on large scales, as observed. Excessive small-scale velocity dispersions, and voids less empty than those observed may be remedied by including baryonic physics. The topology of the cosmic structure agrees well with observation. The non-Gaussian texture induced density fluctuations lead to earlier nonlinear object formation than in Gaussian models and may also be more compatible with recent evidence that the galaxy density field is non-Gaussian on large scales. On smaller scales the density field is strongly non-Gaussian, but this appears to be primarily due to nonlinear gravitational clustering. The velocity field on smaller scales is surprisingly Gaussian.

Gooding, Andrew K.↗

Low-Flow-Rate Dry-Powder Feeder

Apparatus feeds small, precise flow of dry powder through laser beam of optical analyzer measuring patterns of light created by forward scattering (Fraunhofer diffraction) of laser beam from powder particles. From this optical measurement, statistical distribution of sizes of powder particles computed. Rates of flow optimized for measurement of particle-size distributions. Developed for analyzing particle-size distributions of solid-propellant powders. Also adapted to pharmaceutical industry, in manufacture of metal powder, and in other applications where particle-size distributions of materials used to control rates of chemical reactions and/or physical characteristics of processes.

Ramsey, Keith E.↗

Early Results from the MODIS Atmosphere Cloud Algorithms

The Moderate Resolution Imaging Spectroradiometer (MODIS) is one of five instruments aboard the Terra Earth Observing System platform launched in December 1999. With 36 spectral bands from the visible through the infrared, and spatial resolution from 250m to 1km, the instrument provides an unprecedented opportunity for global cloud studies. A comprehensive set of remote sensing algorithms for cloud masking and retrieval of cloud physical and optical properties have been developed by members of the MODIS atmosphere team. The archived products from these algorithms have applications in climate change studies, climate modeling, numerical weather prediction, as well as fundamental atmospheric research. In addition to an extensive cloud mask, products include cloud top physical parameters (temperature, pressure, emissivity), cloud phase, cloud optical parameters (optical depth, effective particle radius, water path), visible cirrus reflectance, a contrail flag, and other derived parameters. All products are archived into two categories: pixel-level retrievals at a 1 km or 5 km spatial resolution at nadir (referred to as Level-2 products) and 1 degree global gridded statistics (Level-3 products). An overview of the MODIS atmosphere algorithms and products, their status, validation activities, and early level-2 and -3 results will be presented.

Platnick, S.↗

New Approaches to Quantifying Transport Model Error in Atmospheric CO2 Simulations

In recent years, much progress has been made in observing CO2 distributions from space. However, the use of these observations to infer source/sink distributions in inversion studies continues to be complicated by difficulty in quantifying atmospheric transport model errors. We will present results from several different experiments designed to quantify different aspects of transport error using the Goddard Earth Observing System, Version 5 (GEOS-5) Atmospheric General Circulation Model (AGCM). In the first set of experiments, an ensemble of simulations is constructed using perturbations to parameters in the model s moist physics and turbulence parameterizations that control sub-grid scale transport of trace gases. Analysis of the ensemble spread and scales of temporal and spatial variability among the simulations allows insight into how parameterized, small-scale transport processes influence simulated CO2 distributions. In the second set of experiments, atmospheric tracers representing model error are constructed using observation minus analysis statistics from NASA's Modern-Era Retrospective Analysis for Research and Applications (MERRA). The goal of these simulations is to understand how errors in large scale dynamics are distributed, and how they propagate in space and time, affecting trace gas distributions. These simulations will also be compared to results from NASA's Carbon Monitoring System Flux Pilot Project that quantified the impact of uncertainty in satellite constrained CO2 flux estimates on atmospheric mixing ratios to assess the major factors governing uncertainty in global and regional trace gas distributions.

Ott, L.↗

Premature Deaths in Africa Due to Particulate Matter Under High and Low Warming Scenarios

Sustainable development and climate change mitigation can provide enormous public health benefits via improved air quality, especially in polluted areas. We use the latest state-of-the-art composition-climate model simulations to contrast human exposure to fine particulate matter in Africa under a “baseline” scenario with high material consumption, population growth, and warming to that projected under a sustainability scenario with lower consumption, population growth, and warming. Evaluating the mortality impacts of these exposures, we find that under the low warming scenario annual premature deaths due to PM2.5 are reduced by roughly 515,000 by 2050 relative to the high warming scenario (100,000, 175,000, 55,000, 140,000, and 45,000 in Northern, West, Central, East, and Southern Africa, respectively). This reduction rises to ∼800,000 by the 2090s, though by that time much of the difference is attributable to the projected differences in population. By contrast, during the first half of the century benefits are driven predominantly by emissions changes. Depending on the region, we find large intermodel spreads of ∼25%–50% in projected future exposures owing to different physics across the ensemble of 6 global models. The spread of projected deaths attributable to exposure to fine particulate matter, including uncertainty in the exposure-response function, are reduced in every region to ∼20%–35% by the non-linear exposure-response function. Differences between the scenarios have an even narrower spread of ∼5%–25% and are highly statistically significant in all regions for all models. These results provide valuable information for policy-makers to consider when working toward climate change mitigation and sustainable development goals.

PM2.5↗