Soil Moisture Data Assimilation in the NASA Land Information System (LIS) for Local Modeling Applications and Improved Situational Awareness
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The Goldstone Solar System RADAR (GSSR) group at JPL produced a Digital Elevation Model (DEM) of the lunar south pole using data obtained in 2006. This model has 40-meter horizontal resolution and about 5-meter relative vertical accuracy. This paper uses that Digital Elevation Model to compute average solar illumination and Earth visibility near the lunar south pole. This data quantifies solar power and Earth communications resources at proposed lunar base locations. The elevation data were converted into local terrain horizon masks, then converted into selenographic latitude and longitude coordinates. The horizon masks were compared to latitude, longitude regions bounding the maximum Sun and Earth motions relative to the moon. Proposed lunar south pole base sites were examined in detail, with the best site showing multi-year averages of solar power availability of 92% and Direct-To-Earth (DTE) communication availability of about 50%. Results are compared with a theoretical model, and with actual sun and Earth visibility averaged over the years 2009 to 2028. Results for the lunar North pole were computed using the GSSR DEM of the lunar North pole produced in 1997. The paper also explores using a heliostat to reduce the photovoltaic power system mass and complexity.
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A Digital Elevation Model of the lunar south pole was produced using Goldstone Solar System RADAR (GSSR) data obtained in 2006.12 This model has 40-meter horizontal resolution and about 5-meter relative vertical accuracy. This Digital Elevation Model was used to compute average solar illumination and Earth visibility with 100 kilometers of the lunar south pole. The elevation data were converted into local terrain horizon masks, then converted into lunar-centric latitude and longitude coordinates. The horizon masks were compared to latitude, longitude regions bounding the maximum Sun and Earth motions relative to the moon. Estimates of Earth visibility were computed by integrating the area of the region bounding the Earth's motion that was below the horizon mask. Solar illumination and other metrics were computed similarly. Proposed lunar south pole base sites were examined in detail, with the best site showing yearly solar power availability of 92 percent and Direct-To-Earth (DTE) communication availability of about 50 percent. Similar analysis of the lunar south pole used an older GSSR Digital Elevation Model with 600-meter horizontal resolution. The paper also explores using a heliostat to reduce the photovoltaic power system mass and complexity.
Nuclear detection methods are being used to understand the radiation environment at Mars. JPL (Jet Propulsion Laboratory) assets on Mars include: Orbiter -2001 Mars Odyssey [High Energy Neutron Detector (HEND)]; Mars Science Laboratory Rover -Curiosity [(Radiation Assessment Detector (RAD); Dynamic Albedo Neutron (DAN))]. Spacecraft have instruments able to detect ionizing and non-ionizing radiation. Instrument response on orbit and on the surface of Mars to space weather and local conditions [is discussed] - Data available at NASA-PDS (Planetary Data System).
We address problem of on-line scheduling of the aircraft descent and approach trajectory. We formulate a general multiphase optimal control problem for optimization of the descent trajectory and review available methods of its solution. We develop a fast algorithm for solution of this problem using two key components: (i) fast inference of the dynamical and control variables of the descending trajectory from the low dimensional flight profile data and (ii) efficient local search for the resulting reduced dimensionality non-linear optimization problem. We compare the performance of the proposed algorithm with numerical solution obtained using optimal control toolbox General Pseudospectral Optimal Control Software. We present results of the solution of the scheduling problem for aircraft descent using novel fast algorithm and discuss its future applications.
The ARM Climate Research Facility program maintains a number of climatically representative sites, which provide long-term cloud- and climate-monitoring records via ground-based instrumentation. These measurements provide a valuable data record over a localized region, but can be greatly enhanced by use of satellite monitoring. Satellite analyses over larger domains can provide parameters helpful for monitoring climate and evaluating models. The NASA/Langley Cloud group routinely derives such cloud and radiative parameters, from various geostationary and polar-orbiting satellite coverage over ARM sites; the group provides near-realtime analyses covering the 3 ARM fixed sites, as well as the GO-Amazon AMF site. This is accomplished by employing a suite of algorithms including VISST (Visible Infrared Solar Split-Window Technique), SIST (Solar Infrared Split-Window Technique), and SINT (Solar-infrared Infrared Near-Infrared Technique), now collectively called SatCORPS (Satellite Cloud Observations and Radiative Property retrieval System). An overview and catalog of SatCORPS-derived datasets processed for ASR, and available from both the ARM archive and the NASA/Langley Cloud group website, is provided. Specific improvements included in recently added datasets such as GO-Amazon and Azores are highlighted, including an improved cloud-detection mask, as well as improvements in derived Top-of-Atmosphere (TOA) SW albedoes and LW fluxes. New narrowband-to-broadband (NB-BB) fits and corrections for improved TOA fluxes are illustrated, including MTSAT-1/CERES Aqua NB-BB fits for the TWPICE field campaign, as well as new fits covering the Azores region which incorporate GERB TOA fluxes (Geostationery Earth Radiation Budget). Finally, validation of the reprocessed SatCORPS datasets is shown.
This paper reports computational analyses of testsin a high enthalpy arc-jet facility at NASA Ames Research Center. These tests were conducted using 55-deg sphere-cone models placed in a free jet downstream of the 13-inch diameter conical nozzle in the Ames 60-MW Interaction Heating Facility. Some of the sphere-cone models include surface features such as manufactured fences and gaps intended to simulate effects of differential recession, all of which disturb the flow, producing augmented heating locally and downstream.Test calibration data were obtained using slug and Gardon gage stagnation calorimeters, and a sphere-cone calorimeter model with six Gardon gages and five pressure tabs.The present analysis comprises computational fluid dynamics simulations of the nonequilibrium flowfield in the facility nozzle and test box, including the models tested, and comparisons with the experimental measurements. These simulations take into account nonuniform total enthalpy and mass flux profiles at the nozzle inlet as well as the expansion waves emanating from the nozzle exit and their effects on the model flowfields.
We present an extension of the PatchworkMHD code [1], itself an MHD-capable extension of thePatch-workcode [2], for which several algorithms presented here were co-developed. Its purpose is to create a“multipatch” scheme compatible with numerical simulations of arbitrary equations of motion at any dis-cretization order in space and time. In thePatchworkframework, the global simulation is comprised of anarbitrary number of moving, local meshes, or “patches”, which are free to employ their own resolution, co-ordinate system/topology, physics equations, reference frame, and in our new approach, numerical method.Each local patch exchanges boundary data with a single global patch on which all other patches residethrough a client-router-server parallelization model. In generalizingPatchworkto be compatible witharbitrary order time integration,PatchworkMHDandPatchworkWavehave significantly improved theinterpatch interpolation accuracy by removing an interpolation of interpolated data feedback present in theoriginalPatchworkcode. Furthermore, we extendPatchworkto bemultimethodby allowing multiplestate vectors to be updated simultaneously, with each state vector providing its own interpatch interpolationand transformation procedures. As such, our scheme is compatible with nearly any set of hyperbolic partialdifferential equations. We demonstrate our changes through the implementation of a scalar wave toy-modelthat is evolved on arbitrary, time dependent patch configurations at 4th order accuracy.
This presentation will demonstrate a case study of interdisciplinary research done in the Amazon Web Services (AWS) cloud platform, in addition to in the local machine. We conduct data analysis next to data by leveraging various cloud-based data in NASA Earthdata Cloud, which are distributed by different missions/NASA Distributed Active Archive Centers (DAACs), and cloud computing resources at NASA. For instance, we directly access multiple datasets stored in the AWS Simple Storage Service (S3) buckets using a Python Jupyter notebook through a JupyterHub interface hosted in AWS (without having to download data), and conduct data analysis next to data in the cloud. We will also show how to share the research results following Open Source policy. This case study characterizes the change in wildfire events in the western United States during the past 20 years. In particular, we focus on the wildfires in California in 2021, one of the most severe wildfire years occurring in the most recent 20 years in California. We will analyze the possible causes of wildfires, such as drought conditions and climate variability, and examine the impacts of wildfires on air quality and atmospheric composition, and on land cover. We will examine the data distributed by the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC), including aerosols and meteorological data from the NASA Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2), precipitation from the Global Precipitation Measurement (GPM) and Global Precipitation Climate Project (GPCP), and aerosol index from Ozone Monitoring Instrument (OMI). We also utilize the data distributed by the Physical Oceanography (PO) DAAC, such as Sea Surface Temperature (SST) data from the Group for High Resolution Sea Surface Temperature (GHRSST), and the data distributed by Land Processes (LP) DAAC, such as Normalized Difference Vegetation Index (NDVI).
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An aerodynamic particle sizer spectrometer (APS, model 3321 by TSI Inc., Shoreview, Minnesota) was deployed at the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility Eastern North Atlantic (ENA) observatory during the second (winter) intensive operational period (IOP) of the Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) field campaign. Data were collected from January 9 through February 26, 2018, covering the second deployment of the ARM Aerial Facility (AAF) aircraft within ACE-ENA. The standard ENA instrument suite does not provide measurements of aerosol particle size distribution for diameters greater than one micron. Properties of coarse-mode (super-micron) aerosols are rarely measured, although super-micron particles can play an important role in the aerosol life cycle, affecting aerosol optical properties and cloud nuclei activity (e.g., Clarke et al. 2003). The APS was deployed to fill this gap in particle size measurements: it is capable of measuring size-resolved concentration of the aerosols in the 0.5-20 μm range (aerodynamic diameter). The APS was installed in the aerosol trailer to sample through the main stack. Special attention was given to selection of the instrument location (just below the main stack) to minimize particle losses in the connecting lines. Most atmospheric aerosols are hygroscopic, so the measurement of the aerosol size distributions should either be performed in a controlled humidity environment or accompanied by concurrent measurement of the temperature and humidity of the sample air. The latter strategy was used during this deployment: a high-precision humidity/temperature transmitter (model EE08 by E+E Elektonik GMBH, Engerwitzdorf, Germany) was mounted in the APS sampling line immediately upstream of the APS inlet. A dedicated laptop computer was used for data collection and communications. The APS was controlled with vendor-supplied software (Aerosol Instrument Manager, ver. 10.1, TSI); aerosol size distribution data were collected over a period of 55 seconds and converted to one-minute averages. Temperature and humidity analog signals were acquired via analog-to-digital converter (ADC) module (model WTAIN-M by Weeder Technologies, Fort Walton Beach, Florida) using vendor-supplied software (ModCom) with 1- sec resolution. In post-processing, the APS data were exported from TSI proprietary format into “comma-separated value” American Standard Code for Information Interchange (ASCII) files and matched with appropriately averaged temperature and humidity data. Two significant periods of missing data were caused by local power outages. Vendor-supplied software was not designed for unattended operation: it needs to be manually restarted including sensor configuration setup.
This case study spotlights Washington, D.C.'s successful implementation of DOE’s Unique Building ID (UBID) tool to leverage building-related datasets in support of their sustainability policies.
A number of trends are increasing the variability in electric power systems resulting in a need for new approaches in control. The increased variability is originating from distributed energy resources and an increasing demand for personalized energy choice from customers grid-edge. Electricity distribution systems continue to incorporate increasing numbers of intelligent end devices, automated switchgear, and sensing and measurement devices which are providing more visibility and control at the grid-edge. Traditional distribution system planning and operations techniques must evolve to meet the new complexity while continuing to deliver safe, reliable, and cost-effective energy. New technologies are enabling new capabilities at the grid-edge to respond to these needs. Distributed applications can deploy intelligence across the distribution grid with peer-to-peer communications and a shared data context for their local environment. These applications can cooperate with each other to respond quickly to changing grid conditions. This enables a layered coordination framework spanning the centralized Advanced Distribution Management System functions with wide area visibility to these new distributed applications running at intelligent devices and meters throughout the distribution system. This paper describes an open-architecture, open-source system approach for commercial scale integration of devices and intelligence at the grid-edge.
A particle filter algorithm is presented to estimate the position, strength, and cardinality of an unknown number of radioactive point sources in an obstacle-rich environment using count measurements. The algorithm addresses gaps in the prior literature by incorporating two novel elements. The first is a precomputation step in which local terrain and obstacle data is processed to compute attenuation kernels throughout the search area. This enables rapid estimation performance in obstacle-rich environments as measurements are gathered. The second novel feature is a dynamic particle allocation technique in which the number of particles is adjusted in real time to meet convergence goals. This feature allows the algorithm to scale more efficiently to scenarios with a larger number of sources. A series of computational experiments using simulated data demonstrates the algorithm’s performance in a cluttered environment with up to eight sources.
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Neutrinos are elementary particles with many properties still unknown. Their masses so far have only upper and lower limits. Still, due to neutrino oscillations, it is clear that they are not massless, as stated by the Standard Model of Elementary Particles. Neutrinos are also present in the Universe in vast amounts, but they rarely interact with the surrounding matter. Their abundance makes them very interesting for many theories beyond the Standard Model, e.g., dark matter searches and CP symmetry violation in the leptonic sector, which could be (partially) responsible for the observed matter-antimatter asymmetry in today's Universe.\\ The Deep Underground Neutrino Experiment (DUNE) is a next-generation accelerator-based neutrino oscillation experiment that will study neutrinos with unprecedented precision and may answer many open questions. DUNE uses a powerful neutrino beam from Fermilab. It consists of a Near Detector (ND) complex to measure neutrinos before oscillat ion, and a Far Detector (FD) complex $1300\ \mathrm{km}$ away to measure them after oscillation. As part of the ND complex, measurements are also possible with different angles to the neutrino beam. This enables excellent control of systematic uncertainties of e.g., neutrino cross section measurements.\\ One detector in the near detector complex is The Muon Spectrometer (TMS), an extension of a Liquid Argon (LAr) detector that measures the charge and momentum of muons produced in neutrino interactions within the LAr. The design of this detector, which consists of alternating layers of steel and plastic scintillator bars, must be optimized for the expected muon energies.\\ In this thesis, a study of the optimal module orientation plan is presented, which is necessary for the physics performance of the near detector complex and, by extension, DUNE. As part of this study, the event reconstruction was also developed and improved. Simulated muons are then reconstructed, and the performan ce of different module orientation plans is tested.\\ As a second part, a study of neutron and gamma tagging using a Pulse Shape Discriminating (PSD) plastic scintillator is presented. The properties of this material allow particle differentiation based on the temporal distribution of emitted light. A novel approach to using the individual light signals was successfully tested using data from a small, local test setup.
The NASA Lewis Research Center supports many research facilities with many isolated buildings, including wind tunnels, test cells, and research laboratories. These facilities are all located on a 350 acre campus adjacent to the Cleveland Hopkins Airport. The function of NASA-Lewis is to do basic and applied research in all areas of aeronautics, fluid mechanics, materials and structures, space propulsion, and energy systems. These functions require a great variety of remote high speed, high volume data communications for computing and interactive graphic capabilities. In addition, new requirements for local distribution of intercenter video teleconferencing and data communications via satellite have developed. To address these and future communications requirements for the next 15 yrs, a project team was organized to design and implement a new high speed communication system that would handle both data and video information in a common lab-wide Local Area Network. The project team selected cable television broadband coaxial cable technology as the communications medium and first installation of in-ground cable began in the summer of 1980. The Lewis Information Network (LINK) became operational in August 1982 and has become the backbone of all data communications and video.