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At least 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

An Assessment of the Influence of Uncertainty in Temporally Evolving Streamflow Forecasts on Riverine Inundation Modeling

Continental-scale river forecasting platforms forecast streamflow at reaches that can be used as boundary conditions to drive a local-scale flood inundation model. Uncertainty accumulated during this process stems not only from any part of the forecasting chain but can also be caused by the daily variations in weather forcing that keeps evolving as the event advances. This work aims to examine the influence of the evolving forecast streamflow on predicting the maximum inundation for extreme floods. A diagnostic case study was made on the basis of a hindcast of Hurricane Matthew striking the eastern U.S. in 2016. The U.S. National Water Model was one-way coupled to a hydrodynamic inundation model through a developed automated workflow. Although the river forcing has significantly mismatched hydrographs versus observations, the simulated peak water surface elevations and maximum extents were validated to be comparable with the observations, which indicates that the inundation model may not be sensitive to the inherited uncertainty from the weather forcing. Moreover, the uncertainty of the forecast streamflow time series caused only one order of magnitude fewer variations in inundation prediction; this dampening effect may become clearer for extreme events with large areas inundated. In addition, the forecast total volume of stream discharge appears to be an important metric for assessing the performance of river forcing for inundation mapping, as a linear correlation between the total volume and the accuracy of the predicted peak water surface elevation and maximum extent was found, with the coefficients of determination all above 0.8. Extra best-practice experience of running similar operational tasks demonstrated the tradeoff between the cost and accuracy gain.

flood, national water model, RIFT↗
DOE OSTI2025

A new metrics framework for quantifying and intercomparing atmospheric rivers in observations, reanalyses, and climate models

We present a new atmospheric river (AR) analysis and benchmarking tool, namely Atmospheric River Metrics Package (ARMP). It includes a suite of new AR metrics that are designed for quick analysis of AR characteristics via statistics in gridded climate datasets such as model output and reanalysis. This package can be used for climate model evaluation in comparison with reanalysis and observational products. Integrated metrics such as mean bias and spatial pattern correlation are efficient for diagnosing systematic AR biases in climate models. For example, the package identifies the fact that, in CMIP5 and CMIP6 (Coupled Model Intercomparison Project Phases 5 and 6) models, AR tracks in the South Atlantic are positioned farther poleward compared to ERA5 reanalysis, while in the South Pacific, tracks are generally biased towards the Equator. For the landfalling AR peak season, we find that most climate models simulate a completely opposite seasonal cycle over western Africa. This tool can also be used for identifying and characterizing structural differences among different AR detectors (ARDTs). For example, ARs detected with the Mundhenk algorithm exhibit systematically larger size, width, and length compared to the TempestExtremes (TE) method. The AR metrics developed from this work can be routinely applied for model benchmarking and during the development cycle to trace performance evolution across model versions or generations and set objective targets for the improvement of models. They can also be used by operational centers to perform near-real-time climate and extreme event impact assessments as part of their forecast cycle.

58 GEOSCIENCES↗
NASA NTRS1975

An overview of NASA's remote sensing program

The present status of NASA's remote sensing program and its future plans are reviewed, and some investigations into the possible uses of remotely sensed data are briefly summarized. Landsat-1 photographs are presented to demonstrate how such data can be employed for monitoring and forecasting of agricultural production, for watershed management and flood control, and for mineral exploration. The performance of Landsat-2 and expectations for Landsat-C are evaluated. High-priority problems which should be the driving forces for designing space observation systems for the 1980's are outlined, including the problem of world food supply and the relationship between land use and climatic changes. The design of the modular Landsat-D spacecraft, which will fly a thematic mapper for agricultural observations, is described.

Thome, P. G.↗
NASA NTRS1981

Assessment of historical and projected segments of US and world civil and military rotorcraft markets, 1960 - 1990

The geographic climatic, political, economic and demographic environment of 75 countries was analyzed with respect to helicopter procurement history and usage. Key environmental indicators which are variables were projected into strengths and weaknesses of U.S. technology are reviewed. The civil market sensitivity to new technology is forecast with selected premises as to vehicle life, noise standards, fuel costs, GNP expansion and traffic growth. The forecast is based on a scenario of helicopter technology improvements resulting in increased size and performance.

Yates, W. J.↗
NASA NTRS1990

TEJAS

The Telerobotics/EVA Joint Analysis System (TEJAS) is a hypermedia information system that provides a clear, consistent, repeatable, interactive, and exchangeable multilevel mechanism for telerobotics technology development planning, based on a realistic understanding of the following: (1) Task description, assumptions, and open issues; (2) Specific task primitives (derived from generic primitives); (3) Technologies required to perform on-orbit telerobotics; (4) Planned telerobotics systems' use of those technologies; and (5) Forecast for each technology in terms of time and money. TEJAS was created in HyperCard on a Macintosh 2 personal workstation, with HyperTalk scripts providing action and relational capability. Version 1.0, consisting of more than a dozen interrelated files, will be released in Jan. 1990.

Drews, Michael↗
NASA NTRS2001

Implementation of an Eta Belt Domain on Parallel Systems

We extend the Eta weather model from a regional domain into a belt domain that does not require meridional boundary conditions. We describe how the extension is achieved and the parallel implementation of the code on the Cray T3E and the SGI Origin 2000. We validate the forecast results on the two platforms and examine how the removal of the meridional boundary conditions affects these forecasts. In addition, using several domains of different sizes and resolutions, we present the scaling performance of the code on both systems.

Kouatchou, Jules↗
NASA NTRS2004

Polar Processes in a 50-year Simulation of Stratospheric Chemistry and Transport

The unique chemical, dynamical, and microphysical processes that occur in the winter polar lower stratosphere are expected to interact strongly with changing climate and trace gas abundances. Significant changes in ozone have been observed and prediction of future ozone and climate interactions depends on modeling these processes successfully. We have conducted an off-line model simulation of the stratosphere for trace gas conditions representative of 1975-2025 using meteorology from the NASA finite-volume general circulation model. The objective of this simulation is to examine the sensitivity of stratospheric ozone and chemical change to varying meteorology and trace gas inputs. This presentation will examine the dependence of ozone and related processes in polar regions on the climatological and trace gas changes in the model. The model past performance is base-lined against available observations, and a future ozone recovery scenario is forecast. Overall the model ozone simulation is quite realistic, but initial analysis of the detailed evolution of some observable processes suggests systematic shortcomings in our description of the polar chemical rates and/or mechanisms. Model sensitivities, strengths, and weaknesses will be discussed with implications for uncertainty and confidence in coupled climate chemistry predictions.

Kawa, S.R.↗
NASA NTRS2000

Supercooled Large Droplet Icing Flight Research Program

During the past three winters, the NASA Glenn Research Center at Lewis Field conducted icing research flights throughout the Great Lakes region to measure the characteristics of a severe icing condition having Supercooled Large Droplets (SLD). SLD was implicated in the 1994 crash of the ATR-72 commuter aircraft. This accident focused attention on the safety hazard associated with SLD, and it led the Federal Aviation Administration (FAA) to identify the need for a better understanding of the atmospheric characteristics of this icing condition. In response to this need, Glenn developed a cooperative icing flight research program with the FAA, the National Center for Atmospheric Research, and the Atmospheric Environment Service of Canada. The primary objectives were to (1) characterize the SLD icing condition in terms of important icing-related parameters (such as cloud droplet size, cloud water content, and temperature), (2) develop and refine SLD icing weather forecast products, and (3) document and measure the effects of SLD ice accretions on aircraft performance.

Miller, Dean R.↗
NASA NTRS2005

STS-114: Discovery Launch Readiness Press Conference

Michael Griffin, NASA Administrator; Wayne Hale, Space Shuttle Deputy Program Manager; Mike Wetmore, Director of Shuttle Processing; and 1st Lieutenant Mindy Chavez, Launch Weather Officer-United States Air Force 45th Weather Squadron are in attendance for this STS-114 Discovery launch readiness press conference. The discussion begins with Wayne Hale bringing to the table a low level sensor device for everyone to view. He talks in detail about all of the extensive tests that were performed on these sensors and the completion of these ambient tests. Chavez presents her weather forecast for the launch day of July 26th 2005. Michael Griffin and Wayne Hale answer questions from the news media pertaining to the sensors and launch readiness. The video ends with footage of Pilot Jim Kelly and Commander Eileen Collins conducting test flights in a Shuttle Training Aircraft (STA) that simulates Space Shuttle landing.

Source record↗
NASA NTRS2003

Software for Allocating Resources in the Deep Space Network

TIGRAS 2.0 is a computer program designed to satisfy a need for improved means for analyzing the tracking demands of interplanetary space-flight missions upon the set of ground antenna resources of the Deep Space Network (DSN) and for allocating those resources. Written in Microsoft Visual C++, TIGRAS 2.0 provides a single rich graphical analysis environment for use by diverse DSN personnel, by connecting to various data sources (relational databases or files) based on the stages of the analyses being performed. Notable among the algorithms implemented by TIGRAS 2.0 are a DSN antenna-load-forecasting algorithm and a conflict-aware DSN schedule-generating algorithm. Computers running TIGRAS 2.0 can also be connected using SOAP/XML to a Web services server that provides analysis services via the World Wide Web. TIGRAS 2.0 supports multiple windows and multiple panes in each window for users to view and use information, all in the same environment, to eliminate repeated switching among various application programs and Web pages. TIGRAS 2.0 enables the use of multiple windows for various requirements, trajectory-based time intervals during which spacecraft are viewable, ground resources, forecasts, and schedules. Each window includes a time navigation pane, a selection pane, a graphical display pane, a list pane, and a statistics pane.

Wang, Yeou-Fang↗
NASA NTRS2017

Venus Global Reference Atmospheric Model

Venus Global Reference Atmospheric Model (Venus-GRAM) is an engineering-level atmospheric model developed by MSFC that is widely used for diverse mission applications including: Systems design; Performance analysis; Operations planning for aerobraking, Entry, Descent and Landing, and aerocapture; Is not a forecast model; Outputs include density, temperature, pressure, wind components, and chemical composition; Provides dispersions of thermodynamic parameters, winds, and density; Optional trajectory and auxiliary profile input files Has been used in multiple studies and proposals including NASA Engineering and Safety Center (NESC) Autonomous Aerobraking and various Discovery proposals; Released in 2005; Available at: https://software.nasa.gov/software/MFS-32314-1.

Justh, Hilary L.↗
NASA NTRS2021

Evaluation of Global Surface Water Temperature Data Sets for use in Passive Remote Sensing of Soil Moisture

Inland open water bodies often pose a systematic error source in the passive remote sensing retrievals of soil moisture. Water temperature is a necessary variable used to compute water emissions that is required to be subtracted from satellite observation to yield actual emissions from the land portion, which in turn generates accurate soil moisture retrievals. Therefore, overestimation of soil moisture can often be corrected using concurrent water temperature data in the overall mitigation procedure. In recent years, several data sets of lake water temperature have become available, but their specifications and accuracy have rarely been investigated in the context of passive soil moisture remote sensing on a global scale. For this reason, three lake temperature products were evaluated against in-situ measurements from 2007 to 2011. The data sets include the lake surface water temperature (LSWT) from Global Observatory of Lake Responses to Environmental Change (GloboLakes), the Copernicus Global Land Operations Cryosphere and Water (C-GLOPS), as well as the lake mix-layer temperature (LMLT) from the European Centers for Medium-Range Weather Forecast (ECMWF) ERA5 Land Reanalysis. GloboLakes, C-GLOPS, and ERA5 Land have overall comparable performance with Pearson correlations (R) of 0.87, 0.92 and 0.88 in comparison with in-situ measurements. LSWT products exhibit negative median biases of −0.27 K (GloboLakes) and −0.31 K (C-GLOPS), whereas the median bias of LMLT is 1.56 K. When mapped from their respective native resolutions to a common 9 km Equal-Area Scalable Earth (EASE) Grid 2.0 projection, similar relative performance was observed. LMLT and LSWT data are closer in performance over the 9 km grid cells that exhibit a small range of lake cover fractions (0.05–0.5). Despite comparable relative performance, ERA5 Land shows great advantages in spatial coverage and temporal resolution. In summary, an integrated evaluation on data accuracy, long-term availability, global coverage, temporal resolution, and regular forward processing with modest data latency led us to conclude that LMLT from the ERA5 Land Reanalysis product represents the most optimal path for use in the development of a long-term soil moisture product.

Runze Zhang↗
NASA NTRS2009

Transitioning Models and Model Output to Space Weather Operations: Challenges and Opportunities

The transition of space weather models or of information derived from space weather models to space weather forecasting is the last step of the chain from model development to model deployment in forecasting operations. As such, it is an extremely important element of the quest to increase our national capability to forecast and mitigate space weather hazards. It involves establishing customer requirements, and analyses of available models, which are, in principle, capable of delivering the required product. Models will have to be verified and validated prior to a selection of the best performing model. Further considerations include operational hardware, and the availability of data streams to drive the model. The final steps include the education of forecasters, and the implementation on gateway hardware prior to operational use. This presentation will provide a discussion of opportunities for rapid progress from the viewpoint of the Community Coordinated Modeling Center.

Hesse, Michael↗
NASA NTRS2021

Ambient Performance Testing of the CubeSat Infrared Atmospheric Sounder (CIRAS)

Hyperspectral infrared measurements of Earth’s atmosphere from space have proven their value for weather forecasting, climate science and atmospheric composition. The CubeSat Infrared Atmospheric Sounder (CIRAS) instrument will demonstrate a fully functional infrared temperature, water vapor and carbon monoxide sounder in a CubeSat sized volume for at least an order of magnitude lower cost than legacy systems. Design for a CubeSat significantly reduces cost of access to space and enables flight in a constellation to reduce revisit time and enable new measurements including 3D winds. A technology demonstration of CIRAS is currently under development at JPL. The effort has completed integration and ambient testing of a high fidelity brassboard, complete with the flight configured optics assembly developed by Ball Aerospace with a JPL Immersion Grating and Black Silicon Entrance Slit. The brassboard includes a flight-configured High Operating Temperature Barrier Infrared Detector (HOT-BIRD) mounted in an Integrated Dewar Cryocooler Assembly (IDCA), enabling testing in the ambient environment. Ambient testing included radiometric testing of the system to characterize the instrument operability and NEdT. Spatial testing was performed to characterize the system line spread function (LSF) in two axes and report FWHM of the LSF. Spectral testing involved an air path test to characterize the spectral/spatial transformation matrix, and an etalon was used to measure the Spectral Response Functions (SRFs). Results of the testing show the CIRAS performs exceptionally well and meets the key performance required of the system. The end result of testing is the CIRAS instrument now meets TRL 4 with confidence in a brassboard configuration ready for thermal vacuum (TVac) testing necessary to achieve TRL 5 for the system.

Wilson, Robert C.↗
NASA NTRS2017

The MSFC Solar Activity Future Estimation (MSAFE) Model

The MSAFE model provides forecasts for the solar indices SSN, F10.7, and Ap. These solar indices are used as inputs to space environment models used in orbital spacecraft operations and space mission analysis. Forecasts from the MSAFE model are provided on the MSFC Natural Environments Branch's solar web page and are updated as new monthly observations become available. The MSAFE prediction routine employs a statistical technique that calculates deviations of past solar cycles from the mean cycle and performs a regression analysis to calculate the deviation from the mean cycle of the solar index at the next future time interval. The forecasts are initiated for a given cycle after about 8 to 9 monthly observations from the start of the cycle are collected. A forecast made at the beginning of cycle 24 using the MSAFE program captured the cycle fairly well with some difficulty in discerning the double peak that occurred at solar cycle maximum.

Suggs, Ron↗
NASA NTRS2000

Use of Geostationary Satellite Data to Force Land Surface Schemes within Atmospheric Mesoscale Models

A technique has been developed for assimilating GOES-derived skin temperature tendencies and insolation into the surface energy budget equation of a mesoscale model so that the simulated rate of temperature change closely agrees with the satellite observations. A critical assumption of the technique is that the availability of moisture (either from the soil or vegetation) is the least known term in the model's surface energy budget. Therefore, the simulated latent heat flux, which is a function of surface moisture availability, is adjusted based upon differences between the modeled and satellite-observed skin temperature tendencies. An advantage of this technique is that satellite temperature tendencies are assimilated in an energetically consistent manner that avoids energy imbalances and surface stability problems that arise from direct assimilation of surface shelter temperatures. The fact that the rate of change of the satellite skin temperature is used rather than the absolute temperature means that sensor calibration is not as critical. The technique has been employed on a semi-operational basis at the GHCC within the PSU/NCAR MM5. Assimilation has been performed on a grid centered over the Southeastern US since November 1998. Results from the past year show that assimilation of the satellite data reduces both the bias and RMSE for simulations of surface air temperature and relative humidity. These findings are based on comparison of assimilation runs with a control using the simple 5-layer soil model available in MM5. A significant development in the past several months was the inclusion of the detailed Oregon State University land surface model (OSU/LSM) as an option within MM5. One of our working hypotheses has been that the assimilation technique, although simple, may provide better short-term forecasts than a detailed LSM that requires significant number initialized parameters. Preliminary results indicate that the assimilation out performs the OSU/LSM as it is incorporated in MM5. Details will be presented at the symposium.

Lapenta, William M.↗
NASA NTRS2024

A High-Performance Computing Predictive GNSS Performance Monitor for Autonomous Air Vehicles in Urban Environments

This report offers analysis and design insights for leveraging High-Performance Computing (HPC) to predict line-of-sight (LOS) Global Navigation Satellite System (GNSS) availability in a city. This work is motivated by the emerging fields of Advanced and Urban Air Mobility (AAM/UAM), where regulatory authorities are seeking city-scale, meter-resolution risk forecasting in order to safely integrate new flight missions with existing urban life and infrastructure. This work addresses the technical challenge of efficiently computing urban GNSS satellite visibility to predict GNSS performance metrics under these requirements. We present a new HPC-optimized shadow casting algorithm variant as a ray-based approach to forecasting satellite visibility. We apply this algorithm variant in a software-defined prognostic service which generates a GNSS navigation risk-correlated map as a path planning-style potential field. We detail dominant computational burdens, viable simplifying assumptions, and different algorithmic implementations, intending to demonstrate a baseline of computation time needed by each stage in such a service. We conclude by analyzing the prototype service’s prediction accuracy compared to receiver data from Corpus Christi, Texas. This informs design trade-offs along the dimensions of hardware, computation time, and tolerable forecasting error (including proportions of false positives and false negatives).

GNSS↗
DOE OSTI2021

Assessment of Model Hub Height Wind Speed Performance Using DOE Lidar Buoy Data

As the offshore wind industry continues to gain momentum both in the U.S. and globally, reanalysis products remain essential tools for the lifecycle of a wind farm. From project siting and production estimates to determining construction and maintenance windows, reanalysis products play an important role. These regional and global long-term models also serve as inputs to higher resolution models. With such wide-ranging impacts on the offshore wind industry, the need for validation of reanalysis products is strong, particularly at typical turbine hub heights. Pacific Northwest National Laboratory (PNNL) operates two AXYS WindSentinelTM buoys for the U.S. Department of Energy (DOE) in order to collect meteorological and oceanographic data, including hub height wind speed, in areas of interest for offshore wind development. This work uses DOE buoy observations off the coasts of New Jersey and Virginia to evaluate the performance of Modern Era Retrospective Analysis for Research and Applications-2 (MERRA-2), the North American Regional Reanalysis (NARR), the European Center for Medium-Range Weather Forecasts (ECMWF) Reanalysis 5th generation (ERA5), and the National Oceanic and Atmospheric Administration (NOAA) assimilation system Rapid Refresh (RAP). Biases and degrees of correspondence are determined for each reanalysis product in order to provide insights on the performance and uncertainty for long-term wind resource characterization. With the baseline metrics determined, this work proceeds with an investigation into the sources of large deviations between the modeled and observed hub height wind speeds during the East Coast lidar buoy deployments. Consistent sources of reanalysis model error include stably stratified flow conditions, high wind shear, flow parallel to the coastline, and tropical and winter storms. For the near shore New Jersey location, offshore winds (i.e. blowing from land to water) tend to be associated with model overestimation of observed hub height wind speed, while winds parallel to the coastline are correlated with model underestimation of wind speed. Similarly, near the Virginia buoy, during southerly winds (parallel to the coastline) models underestimate the observed wind speed due to coastal upwelling. Reanalysis model wind speeds underestimate the hub height winds with increasing stable atmospheric stratification. Reanalysis model biases are seen when the observed wind speeds approach or exceed typical turbine cut-out speeds (around 20 m s-1). Large model errors during winter and tropical storm events, high wind speed events, and ramp events are often the result of wind speed timing and magnitude offsets. Overall, ERA5 provides the most successful representation of observed offshore hub height wind speeds at the U.S. East Coast buoy locations and is therefore best suited as an input boundary condition for model case studies. ERA5 performs well for a variety of atmospheric phenomena, including storms and sea breezes, however RAP, the next most successful reanalysis model, performs best in capturing the frequency of ramp events.

17 WIND ENERGY↗