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NASA NTRSDate not supplied

Do Better Satellite Precipitation Algorithms Improve Landslide Hazard Assessment?

Satellites make it possible to estimate precipitation in near real time. Given the challenges of achieving global coverage by other means, these data are used widely. However, few systems for landslide hazard assessment rely on satellite precipitation estimates. This could be due in part to perceptions of accuracy, although latency, spatial resolution, and other factors may also be important. We test whether recent changes to data streams from the Global Precipitation Measurement mission (GPM) have improved its potential for use in landslide prediction. Specifically, we examine data produced by the Integrated Multi-satellitERetrievals for the GPM (IMERG) algorithm, which was upgraded to version 7 this year. IMERG relies upon other algorithms, including the Goddard Profiling Algorithm (GPROF) and the GPM Combined Radar-Radiometer Algorithm (CORRA). Many changes have been made during the switch from IMERG version 6 to version 7. These include upgrading CORRA and GPROF to version 7, to improve the accuracy of precipitation in frozen, mountainous, and coastal areas. The measured intensity of some storms has been enhanced with a new algorithm, the Scheme for Histogram Adjustment with Ranked Precipitation Estimates in the Neighborhood. Combined with many others, these changes to IMERG should improve its utility for landslide hazard assessment in a variety of contexts. To test this idea, we retrain the global Landslide Hazard Assessment for Situational Awareness (LHASA) model twice—first with data from IMERG version 6B and second with 7B. Since current daily rainfall is the most important variable in determining outcomes predicted by LHASA, it should reflect changes made to that input. First, we grid the landslides at a daily, thirty-arcsecond resolution. This serves as the response variable. At each of these sites current and antecedent rainfall are extracted, along with antecedent snow mass and soil moisture, slope, and PGA. In addition, one million grid cells are selected at random points to represent conditions under which landslides (probably) do not occur. After merging these data, we hold back 20% of the dataset for validation purposes and train a machine-learning model with the rest. We assess both the model’s overall ability to identify landslides and its ability to predict specific large landslide disasters.

Thomas A Stanley↗
NASA NTRS1988

A 4.8 kbps code-excited linear predictive coder

A secure voice system STU-3 capable of providing end-to-end secure voice communications (1984) was developed. The terminal for the new system will be built around the standard LPC-10 voice processor algorithm. The performance of the present STU-3 processor is considered to be good, its response to nonspeech sounds such as whistles, coughs and impulse-like noises may not be completely acceptable. Speech in noisy environments also causes problems with the LPC-10 voice algorithm. In addition, there is always a demand for something better. It is hoped that LPC-10's 2.4 kbps voice performance will be complemented with a very high quality speech coder operating at a higher data rate. This new coder is one of a number of candidate algorithms being considered for an upgraded version of the STU-3 in late 1989. The problems of designing a code-excited linear predictive (CELP) coder to provide very high quality speech at a 4.8 kbps data rate that can be implemented on today's hardware are considered.

Tremain, Thomas E.↗
NASA NTRS2018

A Prognostics Framework Development for Swarm Satellite Formations

Prognostics is the science of predicting the failure(s) of a component or a system and understanding how the performance will change in the event of a failure or degradation mechanism. With accurate predictions of possible failures, autonomous mitigative actions can be taken to correct/repair any issues or alert human operators of a failure threshold exceedance requiring condition-based maintenance. Although there is extensive research on failure predictions for a component or a system, there are significantly more opportunities to foray into failure predictions and prognostics for a system of systems such as an airspace consisting of multiple aircraft, a fleet of unmanned aerial vehicles, and a swarm of intelligent satellite systems. Failure prediction and mitigation are particularly important in autonomous systems such as satellite swarm systems that need effective resource management and minimal human interactions. Based on NASA's decadal survey, there is a clear need to prioritize the development of satellite swarm technology for studies of space physics and Earth science. The science community will propose future missions that return in-situ measurements from a 3-D (three-dimensional) volume of space, with relative spacecraft motion and inter-satellite baselines controlled according to the mission objectives. For such multi-spacecraft missions, it is required that ground operations resources do not scale with the number of satellites, thus compromising the swarm or leading to inefficiencies in resource allocation. Swarms of tens or hundreds of small satellites will require autonomy in attitude control, navigation and failure. Although significant research has been conducted in the areas of autonomous formation flying algorithms, less attention has been given to the development of resilient systems robust to failures.The focus of this research paper is the integration of model-based prognostics into the swarm dynamics control and decision-making algorithms. We simulate swarm management strategies for a subsystem failure to demonstrate the importance of failure predictions by comparing two cases: (i) no health information is provided to the system and utilized in the decision-making process and (2) system health information is obtained using prognostics and employed by the control system. One example scenario presented is for the GPS (Global Positioning System) system of an individual satellite to perform off-nominally due to increasing estimated error. In this scenario, the keep-out zone for that satellite would become more conservative, thereby decreasing the risk of collision. This is achieved via tuning the individual artificial repulsive functions assigned to each satellite.This paper is structured as follows. First we provide an overview of current swarm technology development, where we specifically use the term swarm to define multiple satellites flying in formation in similar orbits, with cross-link communication and station-keeping capabilities. Second, we give an introduction to the Swarm Orbital Dynamics Advisor (SODA), a tool that accepts high-level configuration commands and provides the orbital maneuvers required to achieve the prescribed formation configuration. Third, we provide the details of the model-based prognostics algorithm implementation in SODA. Finally, we present different case studies for potential component/subsystem failures and the swarm responses based with and without failure prediction information.

prognostics↗
NASA NTRS2023

Maldives Climate II: Evaluating the Potential Impacts of Sea Level Rise on Human Development and Coastal Infrastructure

The Republic of the Maldives is a low-lying island nation in the Indian Ocean which has experienced rapid urbanization, landcover changes, and sea level rise over recent years. The growth of tourism, coastal erosion, and urbanization have all driven land reclamation efforts across many islands. As in-situ landcover change monitoring has proven difficult across the vast archipelago, the NASA DEVELOP team collaborated with the Maldives Ministry of Environment, Climate Change, and Technology; USAID; and the U.S. Department of State, to utilize Earth observations to predict sea level rise impacts on coastal infrastructure. The team used a supervised classification algorithm within Google Earth Engine to create land use maps and time series analyses of nine islands and atolls using imagery from Landsat 7 Enhanced Thematic Mapper Plus, Landsat 8 Operational Land Imager, Sentinel-2 Multispectral Instrument, and PlanetScope, covering a combined period of 2000 through 2023. Additionally, the team projected coastal inundation with a modified deterministic Bathtub model utilizing elevation data from CoastalDEM and 2050-2100 Shared Socioeconomic Pathway scenarios identified in the NASA Sea Level Rise Projection Tool. The team found that islands undergoing urban growth experienced a 23% decrease in vegetation between 2014 and 2022. Furthermore, the model predicted that 51–57% of the study area’s-built environment has a chance of inundation by 2100 under the low and high sea level scenarios. These analyses demonstrate how remote sensing can be used to both track land use changes over time and project how coastlines will be affected by sea level rise.

remote sensing↗
NASA NTRS1991

Frequency effects on the stability of a journal bearing for periodic loading

The stability of a journal bearing is numerically predicted when a unidirectional periodic external load is applied. The analysis is performed using a cavitation algorithm, which mimics the Jakobsson-Floberg and Olsson (JFO) theory by accounting for the mass balance through the complete bearing. Hence, the history of the film is taken into consideration. The loading pattern is taken to be sinusoidal and the frequency of the load cycle is varied. The results are compared with the predictions using Reynolds boundary conditions for both film rupture and reformation. With such comparisons, the need for accurately predicting the cavitation regions for complex loading patterns is clearly demonstrated. For a particular frequency of loading, the effects of mass, amplitude of load variation and frequency of journal speed are also investigated. The journal trajectories, transient variations in fluid film forces, net surface velocity and minimum film thickness, and pressure profiles are also presented.

Vijayaraghavan, D.↗
NASA NTRS2018

NASA Observations and Modeling During ICE-POP

Recap: NASA-Specific Objectives for ICE-POP: Provide real-time observational and NWP data in support of ICE-POP, participate in significant international science effort; GPM (Global Precipitation Measurement) Ground Validation and NASA Weather Program -Direct/physical validation of active/passive satellite-based snowfall retrieval algorithms over coastline and mountains; melting layer interaction with terrain -Physics of snow, coupling to snow water equivalent rate and satellite remote sensor retrieval algorithm assumptions - -Size distributions, types/habit, water equivalent, profiles -NU-WRF (NASA-Unified Weather Research and Forecasting) Model plus Observational analyses: Movement toward “level IV products” leverage intensive and multi-faceted NWP (Numerical Weather Prediction) component -Model precipitation processes (liquid, mixed phase and frozen); Build model testing database for further active/passive remote sensing algorithm development (e.g., satellite data simulators) -"Integrated" validation of products in operational context.

Precipitation Science↗
NASA NTRS1989

Computational fluid dynamics at the Lewis Research Center: An overview

Lewis is a multidisciplinary Center with strong research and development programs in aeronautical and space propulsion, power, space communications, space experiments and materials. Computational fluid dynamics (CFD) is playing an important and growing role in most of these areas. Described here is how CFD is integrated into these programs and highlights elements of the CFD activities. Examples are presented of codes developed to predict flow fields in advanced propulsion systems and several of the code validation experiments are described. The CFD effort at Lewis ranges from basic research on new and improved algorithms through code development to the application of these codes to specific engineering problems. Because of the substantial improvement in CFD's predictive capability, its use at Lewis is on a steep growth path, spreading rapidly into new areas which had not traditionally taken advantage of the techniques of numerical simulation. Multidisciplinary codes and the future direction of CFD at Lewis are discussed.

Stubbs, Robert M.↗
NASA NTRS1977

Integration schemes for climate prediction

To assure the conservation of total mass, momentum, energy, vorticity, etc., a method of modifying any given algorithm is presented. The modified scheme has at least the same order of accuracy as the given scheme.

Isaacson, E.↗
NASA NTRS2009

Developing Lightning Prediction Tools for the CCAFS Dual-Polarimetric Radar

NASA Marshall Space Flight Center and the University of Alabama Huntsville are collaborating with the 45th Weather Squadron (45WS) to develop improved lightning prediction capabilities for the new C-band dual-polarimetric weather radar being acquired for use by 45WS and launch weather forecasters at Cape Canaveral Air Force Station (CCAFS). In particular, these algorithms will focus on lightning onset, cessation and combined lightning-radar applications for convective winds assessment. Research using radar reflectivity (Z) data for prediction of lightning onset has been extensively discussed in the literature and subsequently applied by launch weather forecasters as it pertains to lightning nowcasting. Currently the forecasters apply a relatively straight forward but effective temperature-Z threshold algorithm for assessing the likelihood of lightning onset in a given storm. In addition, a layered VIL above the freezing level product is used as automated guidance for the onset of lightning. Only limited research and field work has been conducted on lightning cessation using Z and vertically-integrated Z for determining cessation. Though not used operationally vertically-integrated Z (basis for VIL) has recently shown promise as a tool for use in nowcasting lightning cessation. The work discussed herein leverages and expands upon these and similar reflectivity-threshold approaches via the application/addition of over two decades of polarimetric radar research focused on distinct multi-parameter radar signatures of ice/mixed-phase initiation and ice-crystal orientation in highly electrified convective clouds. Specifically, our approach is based on numerous previous studies that have observed repeatable patterns in the behavior of the vertical hydrometeor column as it relates to the temporal evolution of differential reflectivity and depolarization (manifested in either LDR or p(sub hv)), development of in-situ mixed and ice phase microphysics, electric fields, and ensuing lightning in the sub-tropical/tropical convection typical of the southeastern U.S., Maritime Continent, and southwestern Amazon. The polarimetric signatures detected in this setting provide a basis for automated 3-D detection of hydrometeor types in fuzzy logic hydrometeor identification algorithms (HID). Our working hypothesis is that improvement in lightning onset warning lead time and specificity for a given storm, relative to application of a Z-threshold algorithm, should arise as a consequence of the ability of dual-polarimetric radar to unambiguously detect and identify (through HID algorithms) the updraft elevation of rain-water cores above the freezing level and subsequent onset of drop freezing, riming, and robust mixed phase processes leading to significant charge separation and lightning. This type of algorithm, though dependent on the quality of the polarimetric data should be less susceptible to variable Z-calibration that can impact a given Z-threshold approach. To facilitate development of the algorithm while the 45WS dual-pol radar is in its current test stages and to evaluate the impact of polarimetric data quality (e.g., modified scan parameters and sampling) on the ensuing algorithms, we are using the ARMOR C-band dual-pol radar in Huntsville combined with N. Alabama LMA data and ARMOR HID algorithms [NCAR algorithm modified for application at C-band] in a testbed fashion. For lightning cessation we are revisiting the application of differential propagation phase variables for the monitoring of ice crystal alignment driven by in-cloud electric fields combined with metrics of ice water path (i.e., vertically integrated reflectivity). Importantly it should be noted that this approach is still very much a research topic and as such, we will explore operational applications that involve radar frequencies other than C-Band by using the UAH MAX X-band dual-pol radar in slow staring modes.

Petersen, W. A.↗
NASA NTRS2010

Dynamically Evolving Sectors for Convective Weather Impact

A new strategy for altering existing sector boundaries in response to blocking convective weather is presented. This method seeks to improve the reduced capacity of sectors directly affected by weather by moving boundaries in a direction that offers the greatest capacity improvement. The boundary deformations are shared by neighboring sectors within the region in a manner that preserves their shapes and sizes as much as possible. This reduces the controller workload involved with learning new sector designs. The algorithm that produces the altered sectors is based on a force-deflection mesh model that needs only nominal traffic patterns and the shape of the blocking weather for input. It does not require weather-affected traffic patterns that would have to be predicted by simulation. When compared to an existing optimal sector design method, the sectors produced by the new algorithm are more similar to the original sector shapes, resulting in sectors that may be more suitable for operational use because the change is not as drastic. Also, preliminary results show that this method produces sectors that can equitably distribute the workload of rerouted weather-affected traffic throughout the region where inclement weather is present. This is demonstrated by sector aircraft count distributions of simulated traffic in weather-affected regions.

Drew, Michael C.↗
NASA NTRS1987

A three-dimensional dual potential procedure with applications to wind tunnel inlets and interacting boundary layers

A dual potential decomposition of the velocity field into a scalar and a vector potential function is extended to three dimensions and used in the finite-difference simulation of steady three-dimensional inviscid rotational flows and viscous flow. The finite-difference procedure was used to simulate the flow through the 80 by 120 ft wind tunnel at NASA Ames Research Center. Rotational flow produced by the stagnation pressure drop across vanes and screens which are located at the entrance of the inlet is modeled using actuator disk theory. Results are presented for two different inlet vane and screen configurations. The numerical predictions are in good agreement with experimental data. The dual potential procedure was also applied to calculate the viscous flow along two and three dimensional troughs. Viscous effects are simulated by injecting vorticity which is computed from a boundary layer algorithm. For attached flow over a three dimensional trough, the present calculations are in good agreement with other numerical predictions. For separated flow, it is shown from a two dimensional analysis that the boundary layer approximation provides an accurate measure of the vorticity in regions close to the wall; whereas further away from the wall, caution has to be exercised in using the boundary-layer equations to supply vorticity to the dual potential formulation.

Rao, K. V.↗
NASA NTRS2002

Sources of Uncertainty in the Prediction of LAI / fPAR from MODIS

To explicate the sources of uncertainty in the prediction of biophysical variables over space, consider the general equation: where z is a variable with values on some nominal, ordinal, interval or ratio scale; y is a vector of input variables; u is the spatial support of y and z ; x and u are the spatial locations of y and z , respectively; f is a model and B is the vector of the parameters of this model. Any y or z has a value and a spatial extent which is called its support. Viewed in this way, categories of uncertainty are from variable (e.g. measurement), parameter, positional. support and model (e.g. structural) sources. The prediction of Leaf Area Index (LAI) and the fraction of absorbed photosynthetically active radiation (fPAR) are examples of z variables predicted using model(s) as a function of y variables and spatially constant parameters. The MOD15 algorithm is an example of f, called f(sub 1), with parameters including those defined by one of six biome types and solar and view angles. The Leaf Canopy Model (LCM)2, a nested model that combines leaf radiative transfer with a full canopy reflectance model through the phase function, is a simpler though similar radiative transfer approach to f(sub 1). In a previous study, MOD15 and LCM2 gave similar results for the broadleaf forest biome. Differences between these two models can be used to consider the structural uncertainty in prediction results. In an effort to quantify each of the five sources of uncertainty and rank their relative importance for the LAI/fPAR prediction problem, we used recent data for an EOS Core Validation Site in the broadleaf biome with coincident surface reflectance, vegetation index, fPAR and LAI products from the Moderate Resolution Imaging Spectrometer (MODIS). Uncertainty due to support on the input reflectance variable was characterized using Landsat ETM+ data. Input uncertainties were propagated through the LCM2 model and compared with published uncertainties from the MOD15 algorithm.

Dungan, Jennifer L.↗
NASA NTRS2014

NASA Team 2 Sea Ice Concentration Algorithm Retrieval Uncertainty

Satellite microwave radiometers are widely used to estimate sea ice cover properties (concentration, extent, and area) through the use of sea ice concentration (IC) algorithms. Rare are the algorithms providing associated IC uncertainty estimates. Algorithm uncertainty estimates are needed to assess accurately global and regional trends in IC (and thus extent and area), and to improve sea ice predictions on seasonal to interannual timescales using data assimilation approaches. This paper presents a method to provide relative IC uncertainty estimates using the enhanced NASA Team (NT2) IC algorithm. The proposed approach takes advantage of the NT2 calculations and solely relies on the brightness temperatures (TBs) used as input. NT2 IC and its associated relative uncertainty are obtained for both the Northern and Southern Hemispheres using the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) TB. NT2 IC relative uncertainties estimated on a footprint-by-footprint swath-by-swath basis were averaged daily over each 12.5-km grid cell of the polar stereographic grid. For both hemispheres and throughout the year, the NT2 relative uncertainty is less than 5%. In the Southern Hemisphere, it is low in the interior ice pack, and it increases in the marginal ice zone up to 5%. In the Northern Hemisphere, areas with high uncertainties are also found in the high IC area of the Central Arctic. Retrieval uncertainties are greater in areas corresponding to NT2 ice types associated with deep snow and new ice. Seasonal variations in uncertainty show larger values in summer as a result of melt conditions and greater atmospheric contributions. Our analysis also includes an evaluation of the NT2 algorithm sensitivity to AMSR-E sensor noise. There is a 60% probability that the IC does not change (to within the computed retrieval precision of 1%) due to sensor noise, and the cumulated probability shows that there is a 90% chance that the IC varies by less than +/-3%. We also examined the daily IC variability, which is dominated by sea ice drift and ice formation/melt. Daily IC variability is the highest, year round, in the MIZ (often up to 20%, locally 30%). The temporal and spatial distributions of the retrieval uncertainties and the daily IC variability is expected to be useful for algorithm intercomparisons, climate trend assessments, and possibly IC assimilation in models.

Sea Ice↗
NASA NTRS1986

Digital Filter Separates Signal From Noise

Variance of signal-estimation error minimized. Mathematical technique extracts best estimates of signal component from periodic digital samples of signal plus noise. Technique combines Kalman- and smoothingfilter algorithms to minimize mean-square estimation error based on past, present, and predicted samples of signal plus noise. Technique useful in image analysis and other applications involving processing of noisy signals.

Lear, W. M.↗
NASA NTRS1993

UARS in-flight jitter study for EOS

Response data collected from gyroscopes on board the Upper Atmosphere Research Satellite (UARS) provided a unique opportunity to analyze actual flight pointing jitter data. Flight modal frequencies and damping values are derived from the measured data using an Eigensystem Realization Algorithm (ERA). Flight frequencies at various solar array positions are compared to analytical predictions obtained with a Finite Element Model. The solar array modal frequencies change with position due to the modes acting about different spacecraft inertial axes. Higher order modes were difficult to identify due to the limited instrumentation. Future flight jitter studies on other spacecraft would be significantly aided by additional instrumentation. Spacecraft jitter due to continuous disturbance sources such as the 1.6 meter scanning microwave antenna, the solar array drive, and reaction wheels is presented. The solar array drive disturbance dominates the spacecraft response during normal operation.

Molnar, John↗
NASA NTRS1996

NEQAIR96,Nonequilibrium and Equilibrium Radiative Transport and Spectra Program: User's Manual

This document is the User's Manual for a new version of the NEQAIR computer program, NEQAIR96. The program is a line-by-line and a line-of-sight code. It calculates the emission and absorption spectra for atomic and diatomic molecules and the transport of radiation through a nonuniform gas mixture to a surface. The program has been rewritten to make it easy to use, run faster, and include many run-time options that tailor a calculation to the user's requirements. The accuracy and capability have also been improved by including the rotational Hamiltonian matrix formalism for calculating rotational energy levels and Hoenl-London factors for dipole and spin-allowed singlet, doublet, triplet, and quartet transitions. Three sample cases are also included to help the user become familiar with the steps taken to produce a spectrum. A new user interface is included that uses check location, to select run-time options and to enter selected run data, making NEQAIR96 easier to use than the older versions of the code. The ease of its use and the speed of its algorithms make NEQAIR96 a valuable educational code as well as a practical spectroscopic prediction and diagnostic code.

Whiting, Ellis E.↗
NASA NTRS1997

Comparison of Orbiter PRCS Plume Flow Fields Using CFD and Modified Source Flow Codes

The Space Shuttle Orbiter will use Reaction Control System (RCS) jets for docking with the planned International Space Station (ISS). During approach and backout maneuvers, plumes from these jets could cause high pressure, heating, and thermal loads on ISS components. The object of this paper is to present comparisons of RCS plume flow fields used to calculate these ISS environments. Because of the complexities of 3-D plumes with variable scarf-angle and multi-jet combinations, NASA/JSC developed a plume flow-field methodology for all of these Orbiter jets. The RCS Plume Model (RPM), which includes effects of scarfed nozzles and dual jets, was developed as a modified source-flow engineering tool to rapidly generate plume properties and impingement environments on ISS components. This paper presents flow-field properties from four PRCS jets: F3U low scarf-angle single jet, F3F high scarf-angle single jet, DTU zero scarf-angle dual jet, and F1F/F2F high scarf-angle dual jet. The RPM results compared well with plume flow fields using four CFD programs: General Aerodynamic Simulation Program (GASP), Cartesian (CART), Unified Solution Algorithm (USA), and Reacting and Multi-phase Program (RAMP). Good comparisons of predicted pressures are shown with STS 64 Shuttle Plume Impingement Flight Experiment (SPIFEX) data.

Rochelle, Wm. C.↗