Use of spatially refined satellite remote sensing fire detection data to initialize and evaluate coupled weather‐wildfire growth model simulations
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The National Aeronautics and Space Administration (NASA) acquires and distributes an abundance of Earth science data on a daily basis to a diverse user community worldwide. The NASA Big Earth Data Initiative (BEDI) is an effort to make the acquired science data more discoverable, accessible, and usable. This presentation will provide a brief introduction to the Earth Observing System Data and Information System (EOSDIS) project and the nature of advances that have been made by BEDI to other Federal Users.
A digital soils data base established for inclusion of soil reflectance data, physical, chemical, and engineering measurements, and site information is discussed. Initial data are taken from 500 soil samples covering the spectral range of 0.5 to 2.3 microns. Information obtained from each observation includes spectral data, and identification records with the soil and spectral observation parameters. The LARSPEC software system is available to retrieve and manipulate information, and scattergrams of identification and spectral data allow the initiation of statistical analyses of soil data. In addition, soil characteristics, graphical displays of reflectance spectra, and identification information examples are given.
The exchange of energy and moisture between the Earth's surface and the atmospheric boundary layer plays a critical role in many meteorological processes. High-resolution, accurate representations of surface properties such as sea-surface temperature (SST), soil temperature and moisture content, ground fluxes, and vegetation are necessary to better understand the Earth-atmosphere interactions and improve numerical predictions of sensible weather. The NASA Short-term Prediction Research and Transition (SPoRT) Center has been conducting separate studies to examine the impacts of high-resolution land-surface initialization data from the Goddard Space Flight Center Land Information System (LIS) on subsequent WRF forecasts, as well as the influence of initializing WRF with SST composites derived from the MODIS instrument. This current project addresses the combined impacts of using high-resolution lower boundary data over both land (LIS data) and water (MODIS SSTs) on the subsequent daily WRF forecasts over Florida during May 2004. For this experiment, the WRF model is configured to run on a nested domain with 9- km and 3-kin grid spacing, centered on the Florida peninsula and adjacent coastal waters of the Gulf of Mexico and Atlantic Ocean. A control configuration of WRF is established to take all initial condition data from the NCEP Eta model. Meanwhile, two WRF experimental runs are configured to use high-resolution initialization data from (1) LIS land-surface data only, and (2) a combination of LIS data and high-resolution MODIS SST composites. The experiment involves running 24-hour simulations of the control WRF configuration, the MS-initialized WRF, and the LIS+MODIS-initialized WRF daily for the entire month of May 2004. All atmospheric data for initial and boundary conditions for the Control, LIS, and LIS+MODIS runs come from the NCEP Eta model on a 40-km grid. Verification statistics are generated at land surface observation sites and buoys, and the impacts of the high-resolution lower boundary data on the development and evolution of mesoscale circulations such as sea and land breezes are examined, This paper will present the results of these WRF modeling experiments using LIS and MODIS lower boundary datasets over the Florida peninsula during May 2004.
The first year of research to provide NASA support in predicting operational and support parameters and costs of proposed space systems is reported. Some of the specific research objectives were (1) to develop a methodology for deriving reliability and maintainability parameters and, based upon their estimates, determine the operational capability and support costs, and (2) to identify data sources and establish an initial data base to implement the methodology. Implementation of the methodology is accomplished through the development of a comprehensive computer model. While the model appears to work reasonably well when applied to aircraft systems, it was not accurate when used for space systems. The model is dynamic and should be updated as new data become available. It is particularly important to integrate the current aircraft data base with data obtained from the Space Shuttle and other space systems since subsystems unique to a space vehicle require data not available from aircraft. This research only addressed the major subsystems on the vehicle.
A large amount of effort has recently been put into understanding the barren plateau phenomenon. In this perspective article, we face the increasingly loud elephant in the room and ask a question that has been hinted at by many but not explicitly addressed: Can the structure that allows one to avoid barren plateaus also be leveraged to efficiently simulate the loss classically? We collect evidence-on a case-by-case basis-that many commonly used models whose loss landscapes avoid barren plateaus can also admit classical simulation, provided that one can collect some classical data from quantum devices during an initial data acquisition phase. This follows from the observation that barren plateaus result from a curse of dimensionality, and that current approaches for solving them end up encoding the problem into some small, classically simulable, subspaces. Thus, while stressing that quantum computers can be essential for collecting data, our analysis sheds doubt on the information processing capabilities of many parametrized quantum circuits with provably barren plateau-free landscapes. We end by discussing the (many) caveats in our arguments including the limitations of average case arguments, the role of smart initializations, models that fall outside our assumptions, the potential for provably superpolynomial advantages and the possibility that, once larger devices become available, parametrized quantum circuits could heuristically outperform our analytic expectations.
Iterative clustering technique for minimizing probability of differences between binary data reconstructions from cluster codes and initial data
Several alternative methods for solving the group height equation are presented. Three of these are now in operation at Ames Research Center and use data contained in a single ionogram trace. From the data an electron density profile N(h) is computed. If the ionogram also exhibits other traces, reverse ionogram traces are computed, using the N(h) profile, for comparison with the redundant data. When agreement is poor, the initial data trace is reinterpreted, another N(h) profile computed, and the reverse traces generated once again. This process is repeated until a desired degree of consistency is achieved. To reduce the necessity for human intervention and eliminate decision making required in conjunction with the preceding methods, a method is proposed that accepts as input, all data from a single ionogram. In general, no electron density function will satisfy these data exactly, but a best N(h) profile can be computed. Finally, a method is described that eliminates the need to assume that the ionosphere is spherically stratified. Horizontal gradients in electron density are detected and accounted for by processing several ionograms from the same satellite pass simultaneously. This idea is derived as an extension of one of the basic methods.
A major component of the 1988 Mojave Field Experiment involved the simultaneous acquisition of quad-polarization multifrequency airborne Synthetic Aperture Radar (SAR) imaging radar data and ground measurements thought to be relevant to the radar scattering behavior of a variety of desert surfaces. In preparation for the Magellan mission to Venus, the experiment was designed to explore the ability of SAR to distinguish types of geological surfaces, and the effects of varying incidence angles on the appearance of such surfaces. The airborne SAR system acquired images at approx. 10 m resolution, at 3 incidence angles (30, 40, 50 degs) and at 3 wavelengths (P:68 cm, L:24 cm, C:5.6 cm). The polarimetric capabilities of the instrument allow the simulation of any combination of transmit and receive polarizations during data reduction. Calibrated trihedral corner reflectors were deployed within each scene to permit absolute radiometric calibration of the image data. Initial analyses of this comprehensive radar data set is reported, with emphasis on implications for interpretation of Magellan data.
For ground-based space physiological research, the choice of terrestrial analog must carefully match the system of interest. Antarctica winter-over at the European Concordia Station is potentially a superior ground-analog for spaceflight-associated immune dysregulation (SAID). Concordia missions consist of prolonged durations in an extreme/dangerous environment, station-based habitation, isolation, disrupted circadian rhythms and international crews. The ESA-NASA CHOICE study assesses innate and adaptive immunity, viral reactivation and stress factors during Concordia winterover deployment. Initial data obtained from the first study deployment (2009 mission; 'n' of 6) will be presented, and logistical challenges regarding analog usage for biological studies will also be discussed. The total WBC increased, and alterations in some peripheral leukocyte populations were observed during winterover at Concordia Station. Percentages of lymphocytes and monocytes increased, and levels of senescent CD8+ T cells were increased during deployment. Transient increases in constitutively activated T cell subsets were observed, at mission time points associated with endemic disease outbreaks. T cell function (early blastogenesis response) was increased near the entry/exit deployment phases, and production of most measured cytokines increased during deployment. Salivary cortisol demonstrated high variability during winterover, but was generally increased. A 2-point circadian rhythm of cortisol measurement (morning/evening) was unaltered during winterover. Perceived stress was mildly elevated during winterover. Other measures, including in-vitro DTH assessment, viral specific T cell number/function and latent herpesvirus reactivation have not yet been completed for the 2009 winterover subjects. Based on the preliminary data, alterations in immune cell distribution and function appear to persist during Antarctic winterover at Concordia Station. Some of these changes are similar to those observed in Astronauts, either during or immediately following spaceflight. Based on the initial immune data and environmental conditions, Concordia winterover may be an appropriate analog for some flight-associated immune changes.
The response of high explosives to shock loading is traditionally measured with a steady loading pressure. In many accident scenarios involving fragment impact, however, a loading duration that is shorter than the build up to detonation may occur. Fragments passing through multiple materials before reaching a high explosive charge may produce loading that is comprised of more than one shock wave. Additionally, the build up to detonation in high explosive corner turning loads the explosive a short duration pressure pulse, since rarefactions can often rapidly overtake the reactive wave. For these reasons, we have studied the response of the insensitive high explosive (IHE) materials PBX 9502 and LX-17 to complex loadings of varied intensity and duration. We refer to a single loading of limited duration as a “thin pulse”, whereas more complex scenarios were studied with an impactor that produces a double shock in the explosive. The following report presents experimental data and analyses of thin pulse shock initiation and double shock experiments designed to guide development of models of Insensitive High Explosives (IHEs) under controlled one-dimensional conditions relevant to accident scenarios and corner turning. Thin pulse shock initiation data on PBX 9502 and LX-17 were obtained under varied pulse duration, pressed density, and temperature conditions in order to probe various parameters essential for the development of a physics-based Cheetah reactive flow hotspot model. In situ pressure gauges provide insight into the degree of reaction in the explosive that are not obtainable with optical PDV measurements or distance measurements such as run to detonation. Double shock data was obtained to inform a Composition Aware Cheetah model which can be applied to any TATB-based IHEs. This model supports efforts to find a new IHE formulation and potentially incorporate new binders into IHE formulations. Simulations of each experiment are included to demonstrate the utility of these focused experiments to developing models of HE behavior. One-dimensional gas gun experiments are essential for characterizing shocked HE behavior and informing HE models.
The data acquisition, distribution, processing, and archiving requirements of NASA and other U.S. Government data centers present significant data management challenges that must be met in the 1990's. The Earth Observing System (EOS) project alone is expected to generate daily data volumes greater than 2 Terabytes (2 x 10(exp 12) Bytes). As the scientific community makes use of this data, their work will result in larger, increasingly complex data sets to be further exploited and managed. The challenge for data storage systems is to satisfy the initial data management requirements with cost effective solutions that provide for planned growth. The expendable architecture of the E-Systems Modular Automated Storage System (EMASS(TM)), a mass storage system which is designed to support NASA's data capture, storage, distribution, and management requirements into the 21st century is described.
The data acquisition, distribution, processing, and archiving requirements of NASA and other U.S. Government data centers present significant data management challenges that must be met in the 1990's. The Earth Observing System (EOS) project alone is expected to generate daily data volumes greater than 2 Terabytes (2(10)(exp 12) Bytes). As the scientific community makes use of this data their work product will result in larger, increasingly complex data sets to be further exploited and managed. The challenge for data storage systems is to satisfy the initial data management requirements with cost effective solutions that provide for planned growth. This paper describes the expandable architecture of the E-Systems Modular Automated Storage System (EMASS (TM)), a mass storage system which is designed to support NASA's data capture, storage, distribution, and management requirements into the 21st century.
The objective is to develop a uniform environmental data gathering and distribution system to support (1) emergency management for environmental disasters, and (2) the calibration and validation of remotely sensed data. Initial activities will be to select a data test site and to demonstrate multi-discipline applications using simulated or satellite data in a non real-time mode. Rainfall and flooding are chosen as the testbeds for the SAMS concept because of the abundance of data and the availability of models. The capability to display and process GOES data and analyze GOES generated rain-rate maps will be integrated into SAMS.
The effort to resolve data quality issues and improve on the initial data evaluation methodologies of the SeaWiFS Project was an extensive one. These evaluations have resulted, to date, in three major reprocessings of the entire data set where each reprocessing addressed the data quality issues that could be identified up to the time of the reprocessing. Three volumes of the SeaWiFS Postlaunch Technical Report Series (Volumes 9, 10, and 11) are needed to document the improvements implemented since launch. Volume 10 continues the sequential presentation of postlaunch data analysis and algorithm descriptions begun in Volume 9. Chapter 1 of Volume 10 describes an absorbing aerosol index, similar to that produced by the Total Ozone Mapping Spectrometer (TOMS) Project, which is used to flag pixels contaminated by absorbing aerosols, such as, dust and smoke. Chapter 2 discusses the algorithm being used to remove SeaWiFS out-of-band radiance from the water-leaving radiances. Chapter 3 provides an itemization of all significant changes in the processing algorithms for each of the first three reprocessings. Chapter 4 shows the time series of global clear water and deep-water (depths greater than 1,000m) bio-optical and atmospheric properties (normalized water-leaving radiances, chlorophyll, atmospheric optical depth, etc.) based on the eight-day composites as a check on the sensor calibration stability. Chapter 5 examines the variation in the derived products with scan angle using high resolution data around Hawaii to test for residual scan modulation effects and atmospheric correction biases. Chapter 6 provides a methodology for evaluating the atmospheric correction algorithm and atmospheric derived products using ground-based observations. Similarly, Chapter 7 presents match-up comparisons of coincident satellite and in situ data to determine the accuracy of the water-leaving radiances, chlorophyll a, and K(490) products.
The effort to resolve data quality issues and improve on the initial data evaluation methodologies of the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Project was an extensive one. These evaluations have resulted, to date, in three major reprocessings of the entire data set where each reprocessing addressed the data quality issues that could be identified up to the time of each reprocessing. The number of chapters (21) needed to document this extensive work in the SeaWiFS Postlaunch Technical Report Series requires three volumes. The chapters in Volumes 9, 10, and 11 are in a logical order sequencing through sensor calibration, atmospheric correction, masks and flags, product evaluations, and bio-optical algorithms. The first chapter of Volume 9 is an overview of the calibration and validation program, including a table of activities from the inception of the SeaWiFS Project. Chapter 2 describes the fine adjustments of sensor detector knee radiances, i.e., radiance levels where three of the four detectors in each SeaWiFS band saturate. Chapters 3 and 4 describe the analyses of the lunar and solar calibration time series, respectively, which are used to track the temporal changes in radiometric sensitivity in each band. Chapter 5 outlines the procedure used to adjust band 7 relative to band 8 to derive reasonable aerosol radiances in band 7 as compared to those in band 8 in the vicinity of Lanai, Hawaii, the vicarious calibration site. Chapter 6 presents the procedure used to estimate the vicarious calibration gain adjustment factors for bands 1-6 using the waterleaving radiances from the Marine Optical Buoy (MOBY) offshore of Lanai. Chapter 7 provides the adjustments to the coccolithophore flag algorithm which were required for improved performance over the prelaunch version. Chapter 8 is an overview of the numerous modifications to the atmospheric correction algorithm that have been implemented. Chapter 9 describes the methodology used to remove artifacts of sun glint contamination for portions of the imagery outside the sun glint mask. Finally, Chapter 10 explains a modification to the ozone interpolation method to account for actual time differences between the SeaWiFS and Total Ozone Mapping Spectrometer (TOMS) orbits.
During NASA's Tropical Rainfall Measuring Mission (TRMM) field campaigns Large Scale Biosphere Atmosphere (LBA) held in Amazonia (Brazil) in the period January- February, 1999, and the Kwajalein Experiment (KWAJEX) held in the Republic of Marshall Islands in the period between August-September, 1999, extensive radiosonde observations (raob) were collected using VIZ and Vaisala sondes which have different response characteristics. In all, 320 raob for LBA and 972 fixed raob for KWAJEX have been obtained and are being processed. Most atmospheric sensible heat source (Q1) and apparent moisture sink (Q2) budget studies are based on sounding data, and the accuracy of the raob is important especially in regions of deep moist convection. A data quality control (QC) project has been initiated at GSFC by the principal investigator (JBH), and this paper addresses some of the quantitative findings for the level I and II QC procedures. Based on these quantitative assessment of sensor (or system) biases associated with each type of sonde, the initial data repair work will be started. Evidence of moisture biases between the two different sondes (VIZ and Vaisala) has been shown earlier by Halverson et al. (2000). Vaisala humidity sensors are found to have a low-level dry bias in the boundary layer, whereas above 600 mb the VIZ sensor tends to register a dryer atmosphere. All raob data were subjected to a limit check based on an algorithm already well tested for the raob data obtained during the Tropical Ocean Global Atmosphere (TOGA-COARE).
One of the most challenging weather forecast problems in the southeastern U.S. is daily summertime pulse convection. During the summer, atmospheric flow and forcing are generally weak in this region; thus, convection typically initiates in response to local forcing along sea/lake breezes, and other discontinuities often related to horizontal gradients in surface heating rates. Numerical simulations of pulse convection usually have low skill, even in local predictions at high resolution, due to the inherent chaotic nature of these precipitation systems. Forecast errors can arise from assumptions within physics parameterizations, model resolution limitations, as well as uncertainties in both the initial state of the atmosphere and land surface variables such as soil moisture and temperature. For this study, it is hypothesized that high-resolution, consistent representations of surface properties such as soil moisture and temperature, ground fluxes, and vegetation are necessary to better simulate the interactions between the land surface and atmosphere, and ultimately improve predictions of local circulations and summertime pulse convection. The NASA Short-term Prediction Research and Transition (SPORT) Center has been conducting studies to examine the impacts of high-resolution land surface initialization data generated by offline simulations of the NASA Land Informatiot~ System (LIS) on subsequent numerical forecasts using the Weather Research and Forecasting (WRF) model (Case et al. 2008, to appear in the Journal of Hydrometeorology). Case et al. presents improvements to simulated sea breezes and surface verification statistics over Florida by initializing WRF with land surface variables from an offline LIS spin-up run, conducted on the exact WRF domain and resolution. The current project extends the previous work over Florida, focusing on selected case studies of typical pulse convection over the southeastern U.S., with an emphasis on improving local short-term WRF simulations over the Mobile, AL and Miami, FL NWS county warning areas. Future efforts may involve examining the impacts of assimilating remotely-sensed soil moisture data, and/or introducing weekly greenness vegetation fraction composites (as opposed to monthly climatologies) into ol'fline NASA LIS runs. Based on positive impacts, the offline LIS runs could be transitioned into an operational mode, providing land surface initialization data to NWS forecast offices in real time.