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At least 235 records · Page 13

Inclusion of Linearized Moist Physics in Nasa's Goddard Earth Observing System Data Assimilation Tools

Inclusion of moist physics in the linearized version of a weather forecast model is beneficial in terms of variational data assimilation. Further, it improves the capability of important tools, such as adjoint-based observation impacts and sensitivity studies. A linearized version of the relaxed Arakawa-Schubert (RAS) convection scheme has been developed and tested in NASA's Goddard Earth Observing System data assimilation tools. A previous study of the RAS scheme showed it to exhibit reasonable linearity and stability. This motivates the development of a linearization of a near-exact version of the RAS scheme. Linearized large-scale condensation is included through simple conversion of supersaturation into precipitation. The linearization of moist physics is validated against the full nonlinear model for 6- and 24-h intervals, relevant to variational data assimilation and observation impacts, respectively. For a small number of profiles, sudden large growth in the perturbation trajectory is encountered. Efficient filtering of these profiles is achieved by diagnosis of steep gradients in a reduced version of the operator of the tangent linear model. With filtering turned on, the inclusion of linearized moist physics increases the correlation between the nonlinear perturbation trajectory and the linear approximation of the perturbation trajectory. A month-long observation impact experiment is performed and the effect of including moist physics on the impacts is discussed. Impacts from moist-sensitive instruments and channels are increased. The effect of including moist physics is examined for adjoint sensitivity studies. A case study examining an intensifying Northern Hemisphere Atlantic storm is presented. The results show a significant sensitivity with respect to moisture.

Convection↗

Catalog of infrared observations. Part 1: Data

The Catalog of Infrared Observations (CIO) is a compilation of infrared astronomical observational data obtained from an extensive literature search of astronomical journals and major astronomical catalogs and surveys. The literature searches are complete for 1965 through 1986 in this Second Edition. The Catalog is published in two parts, with the observational data (roughly 200,000 observations of 20,000 individual sources) listed in Part I, and supporting appendices in Part II. The expanded Second Edition contains a new feature: complete IRAS 4-band data for all CIO sources detected, listed with the main Catalog observations, as well as in complete detail in the Appendix. The appendices include an atlas of infrared source positions, two bibliographies of infrared literature upon which the search was based, and, keyed to the main Catalog listings (organized alphabetically by author and then chronologically), an atlas of infrared spectral ranges, and IRAS data from the CIO sources. The complete CIO database is available to qualified users in printed microfiche and magnetic tape formats.

Gezari, Daniel Y.↗

Analyzing the impact of reaction models on the production of hydrocarbons from thermally upgraded oil shales

Reaction parameters significantly affect oil production from shales by means of heating and in-situ upgrading. In this work, we perform numerical simulations of two chemical reaction models, which are mainly used in the research of kerogen pyrolysis and subsequent hydrocarbon decomposition in organic-rich porous media. They are the Braun and Burnham model and Wellington model. In these forward numerical simulations, we present the influence of the two reaction models on hydrocarbon production. The Braun and Burnham reaction model shows more vigorous kerogen and subsequent decomposition reactions and more hydrocarbon production than the Wellington model. A local sensitivity analysis identifies the reaction parameters with the highest influence on productivity, and the most sensitive outputs. A data-worth analysis identifies the most valuable observation data to be measured for the best prediction of total hydrocarbon production. We find that the most valuable observation data is the cumulative production of heavy oil in the Braun and Burnham model and of light oil in the Wellington model, respectively. Finally, once we determine the maximum allowable prediction uncertainty and the expected measurement uncertainty, the observation data to be measured for the minimization of prediction uncertainty can be obtained.

04 OIL SHALES AND TAR SANDS↗

Elastic functional changepoint detection of climate impacts from localized sources

Detecting changepoints in functional data has become an important problem as interest in monitoring of climate phenomenon has increased, where the data is functional in nature. Here, the observed data often contains both amplitude (y-axis) and phase (x-axis) variability. If not accounted for properly, true changepoints may be undetected, and the estimated underlying mean change functions will be incorrect. In this article, an elastic functional changepoint method is developed which properly accounts for these types of variability. The method can detect amplitude and phase changepoints which current methods in the literature do not, as they focus solely on the amplitude changepoint. This method can easily be implemented using the functions directly or can be computed via functional principal component analysis to ease the computational burden. We apply the method and its nonelastic competitors to both simulated data and observed data to show its efficiency in handling data with phase variation with both amplitude and phase changepoints. We use the method to evaluate potential changes in stratospheric temperature due to the eruption of Mt. Pinatubo in the Philippines in June 1991. Using an epidemic changepoint model, we find evidence of a increase in stratospheric temperature during a period that contains the immediate aftermath of Mt. Pinatubo, with most detected changepoints occurring in the tropics as expected.

54 ENVIRONMENTAL SCIENCES↗

NASA Earth Observing System Data and Information System (EOSDIS): A U.S. Network of Data Centers Serving Earth Science Data: A Network Member of ICSU WDS

NASA's Earth Observing System Data and Information System (EOSDIS) has been in operation since August 1994, and serving a diverse user community around the world with Earth science data from satellites, aircraft, field campaigns and research investigations. The ESDIS Project, responsible for EOSDIS is a Network Member of the International Council for Sciences (ICSU) World Data System (WDS). Nine of the 12 Distributed Active Archive Centers (DAACs), which are part of EOSDIS, are Regular Members of the ICSUWDS. This poster presents the EOSDIS mission objectives, key characteristics of the DAACs that make them world class Earth science data centers, successes, challenges and best practices of EOSDIS focusing on the years 2014-2016, and illustrates some highlights of accomplishments of EOSDIS. The highlights include: high customer satisfaction, growing archive and distribution volumes, exponential growth in number of products distributed to users around the world, unified metadata model and common metadata repository, flexibility provided to uses by supporting data transformations to suit their applications, near-real-time capabilities to support various operational and research applications, and full resolution image browse capabilities to help users select data of interest. The poster also illustrates how the ESDIS Project is actively involved in several US and international data system organizations.

Earth Science↗

Kalman filter data assimilation: Targeting observations and parameter estimation

This paper studies the effect of targeted observations on state and parameter estimates determined with Kalman filter data assimilation (DA) techniques. We first provide an analytical result demonstrating that targeting observations within the Kalman filter for a linear model can significantly reduce state estimation error as opposed to fixed or randomly located observations. We next conduct observing system simulation experiments for a chaotic model of meteorological interest, where we demonstrate that the local ensemble transform Kalman filter (LETKF) with targeted observations based on largest ensemble variance is skillful in providing more accurate state estimates than the LETKF with randomly located observations. Additionally, we find that a hybrid ensemble Kalman filter parameter estimation method accurately updates model parameters within the targeted observation context to further improve state estimation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

The GOES-G and -H spacecraft design

The design of the Geostationary Operational Environmental Satellites (GOES) uses newer technology and has expanded capability relative to the predecessor GOES series of satellites. The satellite directly transmits day and night observations of hemispheric-scale weather, hurricanes, and other more localized severe storms and relays processed high-resolution observation data along with weather facsimile (WEFAX) data. Weather observations are generated in the visible and infrared spin scan radiometer (VISSR) atmospheric sounder (VAS). The VAS performs visible and infrared imaging as well as multispectral imaging (MSI) and temperature sounding of the atmosphere. The satellite provides direct interrogation and simultaneous relay transmission between the command data acquisition station (CDAS) and the multiple, widely dispersed data collection platforms (DCP). The satellites also monitor the condition of the earth's magnetic field, energetic particle flux, and X-ray emissions from the sun. The satellite performs all communications functions by means of a multifunction communications system that operates on S-band and uhf frequencies at rates varying from 100 bit/s to 28 megabit/s. An experimental capability for the detection of the emergency locator transmitter beacons is included in the GOES-GH design as a part of the international satellite-aided search and rescue system.

Fermelia, L. R.↗

Baycal

Bayesian Model Calibration (BayCal) toolkit is a software plugin for Risk Analysis Virtual Environment (RAVEN) framework, arming at inversely quantifying the uncertainties associated with simulation model parameters based on available experiment data. BayCal seeks statistical inference of the uncertain input parameters that are consistent with the available measurement data or observed data. The unique feature of BayCal is the capability to be linked with RAVEN to build corresponding calibration workflows for complex multi-physics simulations. In addition to be able to use the machine learning capability of RAVEN to significantly reduce the computational cost of expensive simulation models, another distinctive feature of BayCal is the capability to deal with high-dimensional correlated model outputs, such as time series observations at multiple locations, via principal component analysis (PCA) technique.

Wang, Congjian↗

Identification of interactions in fractional-order systems with high dimensions

This article proposes an approach to identify fractional-order systems with sparse interaction structures and high dimensions when observation data are supposed to be experimentally available. This approach includes two steps: first, it is to estimate the value of the fractional order by taking into account the solution properties of fractional-order systems; second, it is to identify the interaction coefficients among the system variables by employing the compressed sensing technique. An error analysis is provided analytically for this approach and a further improved approach is also proposed. Moreover, the applicability of the proposed approach is fully illustrated by two examples: one is to estimate the mutual interactions in a complex dynamical network described by fractional-order systems, and the other is to identify a high fractional-order and homogeneous sequential differential equation, which is frequently used to describe viscoelastic phenomena. All the results demonstrate the feasibility of figuring out the system mechanisms behind the data experimentally observed in physical or biological systems with viscoelastic evolution characters.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Scaling relations of halo cores for self-interacting dark matter

Using a simple analytic formalism, we demonstrate that significant dark matter self-interactions produce halo cores that obey scaling relations nearly independent of the underlying particle physics parameters such as the annihilation cross section and the mass of the dark matter particle. For dwarf galaxies, we predict that the core density ρ{sub c} and the core radius r{sub c} should obey ρ{sub c} r{sub c} ≈ 41 M{sub ⊙} pc{sup −2} with a weak mass dependence ∼ M{sup 0.2}. Remarkably, such a scaling relation has recently been empirically inferred. Scaling relations involving core mass, core radius, and core velocity dispersion are predicted and agree well with observational data. By calibrating against numerical simulations, we predict the scatter in these relations and find them to be in excellent agreement with existing data. Future observations can test our predictions for different halo masses and redshifts.

79 ASTRONOMY AND ASTROPHYSICS↗

An Operational evaluation of head up displays for civil transport operations. NASA/FAA phase 3 report

The advantages and disadvantages of head-up displays (HUDs) in commercial jet transport approach and landing operations was evaluated. Ten airline captains currently qualified in the B-727 aircraft flew a series of instrument landing system (ILS) and nonprecision approaches in a motion base simulator using both a flight director HUD concept and a flightpath HUD concept as well as conventional head-down instruments under a variety of environmental and operational conditions to assess: (1) the potential benefits of these HUDs in airline operations; (2) problems which might be associated with their use; and (3) flight crew training requirements and flight crew operating procedures suitable for use with the HUDs. Results are presented in terms of objective simulator based performance measures, subject pilot opinion and rating data, and observer data.

Lauber, J. K.↗

Space Technologies for Enhancing the Resilience and Sustainability of Indigenous Reindeer Husbandry in the Russian Arctic

To adapt successfully to the major changes - climate, environment, economic, social and industrial - which have taken place across the Arctic. in recent years, indigenous communities such as reindeer herders must become increasingly empowered with the best available technologies to add to their storehouse of traditional knowledge. Remotely-sensed data and observations are providing increased capabilities for monitoring, risk mapping, and surveillance of parameters critical to the characterization of pasture quality and migratory routes, such as vegetation distribution, snow cover, infrastructure development, and pasture damages due to fires. This paper describes a series of remote sensing capabilities, which are useful to reindeer husbandry, and gives the results of the first year of a project, "Reindeer Mapper", which is a remote sensing and GIs-based system to bring together space technologies with indigenous knowledge for sustainable reindeer husbandry in the Russian Arctic. In this project, reindeer herders and scientists are joining together to utilize technologies to create a system for collecting and sharing space-based and indigenous knowledge in the Russian Arctic. The "Reindeer Mapper" system will help make technologies more readily available to the herder community for observing, data collection and analysis, monitoring, sharing, communications, and dissemination of information - to be integrated with traditional, local knowledge. This paper describes some of the technologies which comprise the system including an intranet system to enable to the team members to work together and share information electronically, remote sensing data for monitoring environmental parameters important to reindeer husbandry (e.g., SAR, Landsat, AVHRR, MODIS), indigenous knowledge about important environmental parameters, acquisition of ground- based measurements, and the integration of all useful data sets for more informed decision-making.

Maynard, Nancy G.↗

Modeling Meteoroid Densities for Spacecraft Risk Assessment

This report describes the methodologies and algorithms that NASA’s Meteoroid Environment Office (MEO) currently utilizes to measure meteoroid densities. We discuss the needs for an accurate model for the meteoroid density distribution in its Meteoroid Engineering Model (MEM), and its potential implications for spacecraft design. The recently developed process is heavily derived from that of previous work, although subtle differences exist. A thorough comparison of the best-fit densities derived for sixty meteoroids in and with the process described here shows that discrepancies in final densities larger than a factor of two are measured for ∼ 20% of our test events. Such a level of discrepancy suggests that any density calculated using similar methods cannot be assumed to represent a unique fit to the data. Additional observational data for meteoroids beyond those utilized in this work will be essential for producing more reliable and repeatable density measurements.

Ehlert, Steven↗

The Celescope catalog of ultraviolet observations

Data obtained from approximately 7500 ultraviolet television pictures are used to compile a celescope catalog of ultraviolet observations. This catalog lists the magnitude as observed in each of celescope's four ultraviolet color bands, the standard deviations of the observed ultraviolet magnitudes, positions, identifications, and ground based magnitudes, colors, and spectral types for approximately 5000 stars.

Davis, R. J.↗

Earth observation image data format

A flexible format for computer compatable tape (CCT) containing multispectral earth observation sensor data is described. The driving functions which comprise the data format requirements are summarized and general data format guidelines are discussed.

Sos, J. Y.↗

Comparing Galactic Center MSSM dark matter solutions to the Reticulum II gamma-ray data

Observations with the Fermi Large Area Telescope (LAT) indicate a possible small photon signal originating from the dwarf galaxy Reticulum II that exceeds the expected background between 2 GeV and 10 GeV. We have investigated two specific scenarios for annihilating WIMP dark matter within the phenomenological Minimal Supersymmetric Standard Model (pMSSM) framework as a possible source for these photons. We find that the same parameter ranges in pMSSM as reported by an earlier paper to be consistent with the Galactic Center excess, are also consistent with the excess observed in Reticulum II, resulting in a J-factor of log{sub 10} (J(α{sub int}=0.5{sup ∘}))≃(20.3−20.5){sub −0.3}{sup +0.2} GeV{sup 2}cm{sup −5}. This J-factor is consistent with log{sub 10} (J(α{sub int}=0.5{sup ∘}))=19.6{sub −0.7}{sup +1.0} GeV{sup 2}cm{sup −5}, which was derived using an optimized spherical Jeans analysis of kinematic data obtained from the Michigan/Magellan Fiber System (M2FS)

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Regridding uncertainty for statistical downscaling of solar radiation

Abstract. Initial steps in statistical downscaling involve being able to compare observed data from regional climate models (RCMs). This prediction requires (1) regridding RCM outputs from their native grids and at differing spatial resolutions to a common grid in order to be comparable to observed data and (2) bias correcting RCM data, for example via quantile mapping, for future modeling and analysis. The uncertainty associated with (1) is not always considered for downstream operations in (2). This work examines this uncertainty, which is not often made available to the user of a regridded data product. This analysis is applied to RCM solar radiation data from the NA-CORDEX (North American Coordinated Regional Climate Downscaling Experiment) data archive and observed data from the National Solar Radiation Database housed at the National Renewable Energy Lab. A case study of the mentioned methods over California is presented.

14 SOLAR ENERGY↗

Smarter Earth Science Data System

The explosive growth in Earth observational data in the recent decade demands a better method of interoperability across heterogeneous systems. The Earth science data system community has mastered the art in storing large volume of observational data, but it is still unclear how this traditional method scale over time as we are entering the age of Big Data. Indexed search solutions such as Apache Solr (Smiley and Pugh, 2011) provides fast, scalable search via keyword or phases without any reasoning or inference. The modern search solutions such as Googles Knowledge Graph (Singhal, 2012) and Microsoft Bing, all utilize semantic reasoning to improve its accuracy in searches. The Earth science user community is demanding for an intelligent solution to help them finding the right data for their researches. The Ontological System for Context Artifacts and Resources (OSCAR) (Huang et al., 2012), was created in response to the DARPA Adaptive Vehicle Make (AVM) programs need for an intelligent context models management system to empower its terrain simulation subsystem. The core component of OSCAR is the Environmental Context Ontology (ECO) is built using the Semantic Web for Earth and Environmental Terminology (SWEET) (Raskin and Pan, 2005). This paper presents the current data archival methodology within a NASA Earth science data centers and discuss using semantic web to improve the way we capture and serve data to our users.

data center↗