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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Differing Air Traffic Controller Responses to Similar Trajectory Prediction Errors: An Interrupted Time-Series Analysis of Controller Behavior

A Human-In-The-Loop simulation was conducted in January of 2013 in the Airspace Operations Laboratory at NASAs Ames Research Center. The simulation airspace included two en route sectors feeding the northwest corner of Atlantas Terminal Radar Approach Control. The focus of this paper is on how uncertainties in the studys trajectory predictions impacted the controllers ability to perform their duties. Of particular interest is how the controllers interacted with the delay information displayed in the meter list and data block while managing the arrival flows. Due to wind forecasts with 20-knot over-predictions and 20-knot under-predictions, delay value computations included errors of similar magnitude, albeit in opposite directions. However, when performing their duties in the presence of these errors, did the controllers issue clearances of similar magnitude, albeit in opposite directions?

human-automation interaction↗
NASA NTRS1978

Modeling of a latent fault detector in a digital system

Methods of modeling the detection time or latency period of a hardware fault in a digital system are proposed that explain how a computer detects faults in a computational mode. The objectives were to study how software reacts to a fault, to account for as many variables as possible affecting detection and to forecast a given program's detecting ability prior to computation. A series of experiments were conducted on a small emulated microprocessor with fault injection capability. Results indicate that the detecting capability of a program largely depends on the instruction subset used during computation and the frequency of its use and has little direct dependence on such variables as fault mode, number set, degree of branching and program length. A model is discussed which employs an analog with balls in an urn to explain the rate of which subsequent repetitions of an instruction or instruction set detect a given fault.

Nagel, P. M.↗
NASA NTRS1982

The climatic effect of explosive volcanic activity: Analysis of the historical data

By using the most complete available records of direct beam radiation and volcanic eruptions, an historical analysis of the role of the latter in modulating the former was made. A very simple fallout and dispersion model was applied to the historical chronology of explosive eruptions. The resulting time series explains about 77 percent of the radiation variance, as well as suggests that tropical and subpolar eruptions are more important than mid-latitude eruptions in their impact on the stratospheric aerosol optical depth. The simpler climatic models indicate that past hemispheric temperature can be stimulated very well with volcanic and CO2 inputs and suggest that climate forecasting will also require volcano forecasting. There is some evidence that this is possible some years in advance.

Bryson, R. A.↗
NASA NTRS2011

Numerical Model Sensitivity to Heterogeneous Satellite Derived Vegetation Roughness

The sensitivity of a mesoscale weather prediction model to a 1 km satellite-based vegetation roughness initialization is investigated for a domain within the south central United States. Three different roughness databases are employed: i) a control or standard lookup table roughness that is a function only of land cover type, ii) a spatially heterogeneous roughness database, specific to the domain, that was previously derived using a physically based procedure and Moderate Resolution Imaging Spectroradiometer (MODIS) imagery, and iii) a MODIS climatologic roughness database that like (i) is a function only of land cover type, but possesses domain specific mean values from (ii). The model used is the Weather Research and Forecast Model (WRF) coupled to the Community Land Model within the Land Information System (LIS). For each simulation, a statistical comparison is made between modeled results and ground observations within a domain including Oklahoma, Eastern Arkansas, and Northwest Louisiana during a 4-day period within IHOP 2002. Sensitivity analysis compares the impact the three roughness initializations on time-series temperature, precipitation probability of detection (POD), average wind speed, boundary layer height, and turbulent kinetic energy (TKE). Overall, the results indicate that, for the current investigation, replacement of the standard look-up table values with the satellite-derived values statistically improves model performance for most observed variables. Such natural roughness heterogeneity enhances the surface wind speed, PBL height and TKE production up to 10 percent, with a lesser effect over grassland, and greater effect over mixed land cover domains.

Jasinski, Michael↗
NASA NTRSDate not supplied

Global Landslide Hazard Assessment for Situational Awareness (LHASA) Version 2: New Activities and Future Plans

A remote sensing-based system has been developed to characterize the potential for rainfall-triggered landslides across the globe in near real-time. The Landslide Hazard Assessment for Situational Awareness (LHASA) model uses a decision tree framework to combine a static susceptibility map derived from information on slope, rock characteristics, forest loss, distance to fault zones and distance to road networks with satellite precipitation estimates from the Global Precipitation Measurement (GPM) mission. Since 2016, the LHASA model has been providing near real-time and retrospective estimates of potential landslide activity. Results of this work are available at https://landslides.nasa.gov. In order to advance LHASA’s capabilities to characterize landslide hazards and impacts dynamically, we have implemented a new approach that leverages machine learning, new parameters, and new inventories. LHASA 2.0 uses the XGBoost machine learning model to bring in dynamic variables as well as additional static variables to better represent landslide hazard globally. Global rainfall forecasts are also being evaluated to provide a 1-3 day forecast of potential landslide activity. Additional factors such as recent seismicity and burned areas are also being considered to represent the preconditioning or changing interactions with subsequent rainfall over affected areas. A series of parameters are being tested within this structure using NASA’s Global Landslide Catalog as well as many other event-based and multi-temporal inventories mapped by the project team or provided by project partners. In addition to estimates of landslide hazard, LHASA Version 2 will incorporate dynamic estimates of exposure including population, roads and infrastructure to highlight the potential impacts that rainfall-triggered landslides. The ultimate goal of LHASA Version 2.0 is to approximate the relative probabilities of landslide hazard and exposure across different space and time scales to inform hazard assessment retrospectively over the past 20 years, in near real-time, and in the future. In addition to the hazard. This presentation will outline the new activities for LHASA Version 2.0 and present some next steps for this system.

Dalia Kirschbaum↗
NASA NTRS2010

Influence of Satellite-Based Heterogeneous Vegetation Momentum Roughness on Mesoscale Model Dynamics During IHOP 2002

The sensitivity of mesoscale weather prediction model to a vegetation roughness initialization is investigated for the south central United States. Three different roughness databases are employed: i) a control or standard lookup table roughness that is a function only of land cover type, ii) a spatially heterogeneous roughness database previously derived using a physically based procedure and MODIS imagery, and iii) a MODIS climatologic roughness database that possesses the same spatial heterogeneity as (i) but with mean land class values from (ii). The model used is the Weather Research and Forecast Model (WRF) coupled to the Community Land Model within the Land Information System (LIS). For each simulation, a statistical comparison is made between modeled results and ground observations from meteorological stations within the Oklahoma mesonet and surrounding region during IHOP20O2. A sensitivity analysis on the impact the MODIS-based roughness fields is also made through a time-series intercomparison of temperature bias, probability of detection (POD), average wind speed, boundary layer height, and turbulent kinetic energy (TKE) the results that, for the current replacement of the standard land-cover type based roughness values with the satellite-derived fields statistically improves model performance for most of the observed variables. Further, the satellite-based roughness enhances the surface wind speed, PBL height and TKE production on the order of 3 to l0 percent, with a lesser effect over grassland and cropland domains, and the greater effect over mixed land cover domains

Jasinski, Michael↗
NASA NTRS2009

Forecasting Lightning Threat using Cloud-resolving Model Simulations

As numerical forecasts capable of resolving individual convective clouds become more common, it is of interest to see if quantitative forecasts of lightning flash rate density are possible, based on fields computed by the numerical model. Previous observational research has shown robust relationships between observed lightning flash rates and inferred updraft and large precipitation ice fields in the mixed phase regions of storms, and that these relationships might allow simulated fields to serve as proxies for lightning flash rate density. It is shown in this paper that two simple proxy fields do indeed provide reasonable and cost-effective bases for creating time-evolving maps of predicted lightning flash rate density, judging from a series of diverse simulation case study events in North Alabama for which Lightning Mapping Array data provide ground truth. One method is based on the product of upward velocity and the mixing ratio of precipitating ice hydrometeors, modeled as graupel only, in the mixed phase region of storms at the -15\dgc\ level, while the second method is based on the vertically integrated amounts of ice hydrometeors in each model grid column. Each method can be calibrated by comparing domainwide statistics of the peak values of simulated flash rate proxy fields against domainwide peak total lightning flash rate density data from observations. Tests show that the first method is able to capture much of the temporal variability of the lightning threat, while the second method does a better job of depicting the areal coverage of the threat. A blended solution is designed to retain most of the temporal sensitivity of the first method, while adding the improved spatial coverage of the second. Weather Research and Forecast Model simulations of selected North Alabama cases show that this model can distinguish the general character and intensity of most convective events, and that the proposed methods show promise as a means of generating quantitatively realistic fields of lightning threat. However, because models tend to have more difficulty in correctly predicting the instantaneous placement of storms, forecasts of the detailed location of the lightning threat based on single simulations can be in error. Although these model shortcomings presently limit the precision of lightning threat forecasts from individual runs of current generation models, the techniques proposed herein should continue to be applicable as newer and more accurate physically-based model versions, physical parameterizations, initialization techniques and ensembles of cloud-allowing forecasts become available.

McCaul, E. W., Jr.↗
NASA NTRS2007

Observational Evidence of a Hemispheric-wide Ice-ocean Albedo Feedback Effect on Antarctic Sea-ice Decay

The effect of ice-ocean albedo feedback (a kind of ice-albedo feedback) on sea-ice decay is demonstrated over the Antarctic sea-ice zone from an analysis of satellite-derived hemispheric sea ice concentration and European Centre for Medium-Range Weather Forecasts (ERA-40) atmospheric data for the period 1979-2001. Sea ice concentration in December (time of most active melt) correlates better with the meridional component of the wind-forced ice drift (MID) in November (beginning of the melt season) than the MID in December. This 1 month lagged correlation is observed in most of the Antarctic sea-ice covered ocean. Daily time series of ice , concentration show that the ice concentration anomaly increases toward the time of maximum sea-ice melt. These findings can be explained by the following positive feedback effect: once ice concentration decreases (increases) at the beginning of the melt season, solar heating of the upper ocean through the increased (decreased) open water fraction is enhanced (reduced), leading to (suppressing) a further decrease in ice concentration by the oceanic heat. Results obtained fi-om a simple ice-ocean coupled model also support our interpretation of the observational results. This positive feedback mechanism explains in part the large interannual variability of the sea-ice cover in summer.

Nihashi, Sohey↗
NASA NTRS2012

JPL Genesis and Rapid Intensification Processes (GRIP) Portal

Satellite observations can play a very important role in airborne field campaigns, since they provide a comprehensive description of the environment that is essential for the experiment design, flight planning, and post-experiment scientific data analysis. In the past, it has been difficult to fully utilize data from multiple NASA satellites due to the large data volume, the complexity of accessing NASA s data in near-real-time (NRT), as well as the lack of software tools to interact with multi-sensor information. The JPL GRIP Portal is a Web portal that serves a comprehensive set of NRT observation data sets from NASA and NOAA satellites describing the atmospheric and oceanic environments related to the genesis and intensification of the tropical storms in the North Atlantic Ocean. Together with the model forecast data from four major global atmospheric models, this portal provides a useful tool for the scientists and forecasters in planning and monitoring the NASA GRIP field campaign during the 2010 Atlantic Ocean hurricane season. This portal uses the Google Earth plug-in to visualize various types of data sets, such as 2D maps, wind vectors, streamlines, 3D data sets presented at series of vertical cross-sections or pointwise vertical profiles, and hurricane best tracks and forecast tracks. Additionally, it allows users to overlap multiple data sets, change the opacity of each image layer, generate animations on the fly with selected data sets, and compare the observation data with the model forecast using two independent calendars. The portal also provides the capability to identify the geographic location of any point of interest. In addition to supporting the airborne mission planning, the NRT data and portal will serve as a very rich source of information during the post-field campaign analysis stage of the airborne experiment. By including a diverse set of satellite observations and model forecasts, it provides a good spatial and temporal context for the high-resolution, but limited in space and time, airborne observations.

Knosp, Brian W.↗
NASA NTRS1984

Interannual variability of Indian monsoon rainfall

The interannual variability of the Indian summer monsoon and its relationships with other atmospheric fluctuations were studied in hopes of gaining some insight into the predicability of the rainfall. Rainfall data for 31 meteorological subdivisions over India were provided by the India Meteorological Department (IMD). Fifty-three years of seasonal mean anomaly sea-level pressure (SLP) fields were used to determine if any relationships could be detected between fluctuations in Northern Hemisphere surface pressure and Indian monsoon rainfall. Three month running mean sea-level pressure anomalies at Darwin (close to one of the centers of the Southern Oscillation) were compiled for months preceding and following extreme years for rainfall averaged over all of India. Anomalies are small before the monsoon, but are quite large in months following the summer season. However, there is a large decrease in Darwin pressure for months preceding a heavy monsoon, while a deficient monsoon is preceded by a sharp increase in Darwin pressure. If a time series is constructed of the tendency of Darwin SLP between the Northern Hemisphere winter (DJF) and spring (MAM) and a correlation coefficient is computed between it and 81 years of rainfall average over all of India, one gets a C. C. of -.46, which is higher than any other previously computed predictor of the monsoon rainfall. This relationship can also be used to make a qualitative forecast for rainfall over the whole of India by considering the sign of the tendency in extreme monsoon years.

Paolino, D. A.↗
NASA NTRS1991

Geostationary Operational Environmental Statellite(GEOS-N report)

The Advanced Missions Analysis Office (AMAO) of GSFC has completed a study of the Geostationary Operational Environmental Satellites (GOES-N) series. The feasibility, risks, schedules, and associated costs of advanced space and ground system concepts responsive to National Oceanic and Atmospheric Administration (NOAA) requirements were evaluated. The study is the first step in a multi-phased procurement effort that is expected to result in launch ready hardware in the post 2000 time frame. This represents the latest activity of GSFC in translating meteorological requirements of NOAA into viable space systems in geosynchronous earth orbits (GEO). GOES-N represents application of the latest spacecraft, sensor, and instrument technologies to enhance NOAA meteorological capabilities via remote and in-situ sensing from GEO. The GOES-N series, if successfully developed, could become another significant step in NOAA weather forecasting space systems, meeting increasingly complex emerging national needs for that agency's services.

Source record↗
NASA NTRS1990

An atlas of ECMWF analyses (1980-1987). Part 2: Second moment quantities

This document is an atlas based on European Center for Medium Range Weather Forecasts (ECMWF) initialized analyses for 1980-1987. Transports and variance are presented globally at 200 and 850 mb as well as zonally averaged for seasonal and annual averages. Selected fields are filtered to isolate the synoptic (2.5 days is less than periods is less than 6 days) and low frequency (10 days is less than periods is less than 90 days) regions of the spectrum. In addition, time series of the zonally and monthly averaged transports and variances are presented over the entire 8 year period.

Schubert, S.↗
NASA NTRS1990

A noise assessment and prediction system

A system has been designed to provide an assessment of noise levels that result from testing activities at Aberdeen Proving Ground, Md. The system receives meteorological data from surface stations and an upper air sounding system. The data from these systems are sent to a meteorological model, which provides forecasting conditions for up to three hours from the test time. The meteorological data are then used as input into an acoustic ray trace model which projects sound level contours onto a two-dimensional display of the surrounding area. This information is sent to the meteorological office for verification, as well as the range control office, and the environmental office. To evaluate the noise level predictions, a series of microphones are located off the reservation to receive the sound and transmit this information back to the central display unit. The computer models are modular allowing for a variety of models to be utilized and tested to achieve the best agreement with data. This technique of prediction and model validation will be used to improve the noise assessment system.

Olsen, Robert O.↗
NASA NTRS2010

One-Centimeter Orbits in Near-Real Time: The GPS Experience on OSTM/JASON-2

The advances in Precise Orbit Determination (POD) over the past three decades have been driven in large measure by the increasing demands of satellite altimetry missions. Since the launch of Seasat in 1978, both tracking-system technologies and orbit modeling capabilities have evolved considerably. The latest in a series of precise (TOPEX-class) altimeter missions is the Ocean Surface Topography Mission (OSTM, also Jason-2). GPS-based orbit solutions for this mission are accurate to 1-cm (radial RMS) within 3-5 hrs of real time. These GPS-based orbit products provide the basis for a near-real time sea-surface height product that supports increasingly diverse applications of operational oceanography and climate forecasting.

Ocean Surface Topography Mission (OSTM/Jason-2,)↗
NASA NTRS2019

Solar Activity Modeling: From Subgranular Dynamical Scales to the Solar Cycles

Dynamical effects of solar magnetoconvection span a wide range spatial and temporal scales that extends from the interior to the corona and from fast turbulent motions to the global-Sun magnetic activity. To study the solar activity on short temporal scales (from minutes to hours), we use 3D radiative MHD simulations that allow us to investigate complex turbulent interactions that drive various phenomena, such as plasma eruptions, spontaneous formation of magnetic structures, funnel-like structures and magnetic loops in the corona, and others. In particular, we focus on multi-scale processes of energy exchange across the different layers, which contribute to the corona heating and eruptive dynamics, as well as interlinks between different layers of the solar interior and atmosphere. For modeling the global-scale activity we use the data assimilation approach that has demonstrated great potential for building reliable long-term forecasts of solar activity. In particular, it has been shown that the Ensemble Kalman Filter (EnKF) method applied to the Parker-Kleeorin-Ruzmakin dynamo model is capable of predicting solar activity up to one sunspot cycle ahead in time, as well as estimating the properties of the next cycle a few years before it begins. In this presentation, using the available magnetogram data, we discuss development of the methodology and forecast quality criteria (including forecast uncertainties and sources of errors). We demonstrate the influence of observational limitation on the prediction accuracy. We present the EnKF predictions of the upcoming Solar Cycle 25 based on both the sunspot number series and observed magnetic fields, and discuss the uncertainties and potential of the data assimilation approach for modeling and forecasting the solar activity.

Kitiashvili, I. N.↗
NASA NTRS2019

Solar Activity Modeling: From Subgranular Dynamical Scales to the Solar Cycles

The dynamical effects of solar magnetoconvection span a wide range spatial and temporal scales that extend from the interior to the corona and from fast turbulent motions to global magnetic activity. To study the solar activity on short temporal scales (from minutes to hours), we use 3D radiative MHD simulations that allow us to investigate complex turbulent interactions that drive various phenomena, such as plasma eruptions, spontaneous formation of magnetic structures, funnel-like structures and magnetic loops in the corona, and others. In particular, we focus on multi-scale processes of energy exchange across layers of the solar interior and atmosphere, which contribute to coronal heating and eruptive dynamics. For modeling global-scale activity, we use a data assimilation approach that has demonstrated great potential for building reliable long-term forecasts of solar activity. In particular, it has been shown that the Ensemble Kalman Filter (EnKF) method applied to the Parker-Kleeorin-Ruzmakin dynamo model is capable of predicting solar activity up to one sunspot cycle ahead in time, as well as estimating the properties of the next cycle a few years before it begins. In this presentation, using the available magnetogram data, we discuss development of the methodology and forecast quality criteria (including forecast uncertainties and sources of errors). We demonstrate the influence of observational limitations on prediction accuracy, and we present the EnKF predictions of the upcoming Solar Cycle (25) based on both the sunspot number series and observed magnetic fields and discuss the uncertainties and potential of the data assimilation approach for modeling and forecasting solar activity.

Kitiashvili, I. N.↗
NASA NTRS2005

Diverse Applications of Occultation Data in Ozone Assimilation

Ozone profiles from solar occultation instruments provide invaluable information that can be used to evaluate the quality of assimilated ozone fields, from case studies to long-term phenomena. Occultation data can also be applied to include physical constraints while developing components of an assimilation system. Conversely, assimilation of occultation data can help in their validation, and it provides a framework for evaluation of the impact of occultation data on constraining global ozone fields within models. We illustrate these diverse applications by a series of examples using the ozone assimilation system at NASA/Goddard. In a case study, low ozone in the lower stratosphere due to transport of air from the Tropics to northern high latitudes that was captured by assimilation of Aura Microwave Limb Sounder (MLS) and Solar Backscatter Ultraviolet (SBUV) data, was found to agree with SAGE III data. For long-term monitoring, the quality of a multi-year SBUV-only assimilation was evaluated using monthly-mean time series of POAM, HALOE, and SAGE I1 data. We found realism in the representation of the annual cycle in ozone and in some aspects of interannual variability. Assimilation of POAM data was shown to improve the representation of lower stratospheric ozone, especially over Antarctica. More recently, we assimilated ILAS II ozone data in order to help in their validation. Solar occultation data are used to estimate parameters in a new model for forecast error variances that is being developed. These examples demonstrate the importance of occultation data for ozone assimilation, and potential of assimilation to increase the impact and the value of occultation data.

Markowitz, A.↗
NASA NTRS2014

Early On-Orbit Performance of the Visible Infrared Imaging Radiometer Suite Onboard the Suomi National Polar-Orbiting Partnership (S-NPP) Satellite

The Visible Infrared Imaging Radiometer Suite (VIIRS) is one of the key environmental remote-sensing instruments onboard the Suomi National Polar-Orbiting Partnership spacecraft, which was successfully launched on October 28, 2011 from the Vandenberg Air Force Base, California. Following a series of spacecraft and sensor activation operations, the VIIRS nadir door was opened on November 21, 2011. The first VIIRS image acquired signifies a new generation of operational moderate resolution-imaging capabilities following the legacy of the advanced very high-resolution radiometer series on NOAA satellites and Terra and Aqua Moderate-Resolution Imaging Spectroradiometer for NASA's Earth Observing system. VIIRS provides significant enhancements to the operational environmental monitoring and numerical weather forecasting, with 22 imaging and radiometric bands covering wavelengths from 0.41 to 12.5 microns, providing the sensor data records for 23 environmental data records including aerosol, cloud properties, fire, albedo, snow and ice, vegetation, sea surface temperature, ocean color, and nigh-time visible-light-related applications. Preliminary results from the on-orbit verification in the postlaunch check-out and intensive calibration and validation have shown that VIIRS is performing well and producing high-quality images. This paper provides an overview of the onorbit performance of VIIRS, the calibration/validation (cal/val) activities and methodologies used. It presents an assessment of the sensor initial on-orbit calibration and performance based on the efforts from the VIIRS-SDR team. Known anomalies, issues, and future calibration efforts, including the long-term monitoring, and intercalibration are also discussed.

viirs↗