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NASA NTRS1992

Ground-based microwave monitoring of stratospheric ozone

A microwave instrument developed for operational measurements of ozone for the Network for Detection of Stratospheric Change is discussed. The instrument observes two spectral lines near 3-mm wavelength with a bandwidth of 630 MHz, allowing profile retrieval from 20 to 70 km. The observing technique and calibration procedures are described. The measurement forward model and retrieval algorithm are formulated. Preliminary comparisons with a colocated ground-based lidar and the SAGE II instrument are presented. The measurements are shown to typically agree to within 5 to 10 percent.

Parrish, A.↗

NASA NTRS1992

Assimilation of a knowledge base and physical models to reduce errors in passive-microwave classifications of sea ice

An expert system framework has been developed to classify sea ice types using satellite passive microwave data, an operational classification algorithm, spatial and temporal information, ice types estimated from a dynamic-thermodynamic model, output from a neural network that detects the onset of melt, and knowledge about season and region. The rule base imposes boundary conditions upon the ice classification, modifies parameters in the ice algorithm, determines a `confidence' measure for the classified data, and under certain conditions, replaces the algorithm output with model output. Results demonstrate the potential power of such a system for minimizing overall error in the classification and for providing non-expert data users with a means of assessing the usefulness of the classification results for their applications.

Maslanik, J. A.↗

NASA NTRS1993

Acoustic target detection and classification using neural networks

A neural network approach to the classification of acoustic emissions of ground vehicles and helicopters is demonstrated. Data collected during the Joint Acoustic Propagation Experiment conducted in July of l991 at White Sands Missile Range, New Mexico was used to train a classifier to distinguish between the spectrums of a UH-1, M60, M1 and M114. An output node was also included that would recognize background (i.e. no target) data. Analysis revealed specific hidden nodes responding to the features input into the classifier. Initial results using the neural network were encouraging with high correct identification rates accompanied by high levels of confidence.

Robertson, James A.↗

NASA NTRS1994

Neural networks: Application to medical imaging

The research mission is the development of computer assisted diagnostic (CAD) methods for improved diagnosis of medical images including digital x-ray sensors and tomographic imaging modalities. The CAD algorithms include advanced methods for adaptive nonlinear filters for image noise suppression, hybrid wavelet methods for feature segmentation and enhancement, and high convergence neural networks for feature detection and VLSI implementation of neural networks for real time analysis. Other missions include (1) implementation of CAD methods on hospital based picture archiving computer systems (PACS) and information networks for central and remote diagnosis and (2) collaboration with defense and medical industry, NASA, and federal laboratories in the area of dual use technology conversion from defense or aerospace to medicine.

Clarke, Laurence P.↗

NASA NTRS1994

The effect of the Mt. Pinatubo aerosol on the NHO3 column over Mauna Loa, Hawaii

A very high resolution infrared solar spectrometer system for the Network for Detection of Stratospheric Change has been routinely operated at the Mauna Loa Observatory in Hawaii since November, 1991. Solar absorption spectra are normally taken one day a week at sunrise. We report the analysis of these spectra for the vertical column amount of nitric acid (HNO3) vapor. The observations began four months after the arrival of volcanic aerosols from Mt. Pinatubo over the site. Although quite variable, total HNO3 columns were initially about 7 x 10(exp 15) molecules/sq cm and have decreased about 30% in the following two years.

David, Shelle J.↗

NASA NTRS1995

Ground-based microwave monitoring of middle atmosphere ozone: Comparison to lidar and Stratospheric and Gas Experiment 2 satellite observations

A dedicated ground-based microwave radiometer was in operation to monitor the middle atmospheric ozone concentration at Table Mountain Facility (TMF) of the Jet Propulsion Laboratory (JPL), California (34.4 deg N, 117.7 deg W) from July 1989 to June 1992, as a part of the Network for Detection of Stratospheric Change. Ozone profiles from 56 to 0.04 mbar (approximately 20 - 70 km) were retrieved from the microwave data. The focus in this paper is to validate the microwave ozone observations from 56 to 1 mbar by comparing the results from a JPL ground-based lidar located at the same site and from the Stratospheric Aerosol and Gas Experiment 2 (SAGE 2) satellite overpasses within 1000 km of TMF and to examine the ability of these instruments to detect short-term, seasonal, and annual variations in ozone. The profile comparison results show that the mean differences of microwave ozone from lidar and SAGE 2 are about 5% or less and the root-mean-square scatter about the mean is mainly from the precision of the instruments. A correlation analysis of ozone time series suggests highly significant correlations up to 2.4 mbar between lidar and microwave measurements and up to 1 mbar between SAGE 2 and microwave. The short-term and seasonal variation of the ozone profile seen in the microwave measurements is shown to be consistent with the observations of lidar and SAGE 2, and the interannual variation of ozone appears to be detectable within an accuracy of a few percent with the microwave instrument.

Tsou, J. J.↗

NASA NTRS1998

Temperature climatology of the middle atmosphere from long-term lidar measurements at mid- and low-latitudes

The temperature structure of the middle atmosphere has been studied for several decades using a variety of techniques. However, temperature profiles derived from lidar measurements can provide improved vertical resolution and accuracy. Lidars can also provide long-term data series relatively absent of instrumental drift, and integration of the measurements over several hours removes most of the gravity wave-like short-scale disturbances. This paper describes a seasonal climatology of the middle atmosphere temperature derived from lidar measurements obtained at several mid- and low-latitude locations. Results from the following lidars, which have all obtained a long-term measurement record, were used in this study: the two Rayleigh lidars of the Service d'Aeronomie du CNRS, France, located at the Observatoire de Haute Provence (OHP, 44.0 deg N) and at the Centre d'Essais des Landes (CEL, 44.0 deg N), the two Rayleigh/Raman lidars of the Jet Propulsion Laboratory, USA, located at Table Mountain, California (TMF, 34.4 deg N) and at Mauna Loa, Hawaii (MLO, 19.5 deg N), and the Colorado State University, USA, sodium lidar located at Fort Collins, Colorado (CSU, 40.6 deg N). The overall data set extends from 1978 to 1997 with different periods of measurements depending on the instrument. Three of the instruments are located at primary or complementary stations (OHP, TMF, MLO) within the Network for Detection of Stratospheric Change (NDSC). Several aspects of the temperature climatology obtained by lidar in the middle atmosphere are presented, including the climatological temperature average through the year; the annual and semi-annual components, and the differences compared to the CIRA-86 climatological model.

McDermid, I. Stuart↗

NASA NTRS1998

Evaluation and optimization of lidar temperature analysis algorithms using simulated data

The middle atmosphere (20 to 90 km altitude) ha received increasing interest from the scientific community during the last decades, especially since such problems as polar ozone depletion and climatic change have become so important. Temperature profiles have been obtained in this region using a variety of satellite-, rocket-, and balloon-borne instruments as well as some ground-based systems. One of the more promising of these instruments, especially for long-term high resolution measurements, is the lidar. Measurements of laser radiation Rayleigh backscattered, or Raman scattered, by atmospheric air molecules can be used to determine the relative air density profile and subsequently the temperature profile if it is assumed that the atmosphere is in hydrostatic equilibrium and follows the ideal gas law. The high vertical and spatial resolution make the lidar a well adapted instrument for the study of many middle atmospheric processes and phenomena as well as for the evaluation and validation of temperature measurements from satellites, such as the Upper Atmosphere Research Satellite (UARS). In the Network for Detection of Stratospheric Change (NDSC) lidar is the core instrument for measuring middle atmosphere temperature profiles. Using the best lidar analysis algorithm possible is therefore of crucial importance. In this work, the JPL and CNRS/SA lidar analysis software were evaluated. The results of this evaluation allowed the programs to be corrected and optimized and new production software versions were produced. First, a brief description of the lidar technique and the method used to simulate lidar raw-data profiles from a given temperature profile is presented. Evaluation and optimization of the JPL and CNRS/SA algorithms are then discussed.

Leblanc, Thierry↗

NASA NTRS1998

Infrared Measurements of Atmospheric Constituents

This research program studies atmospheric trace gas concentrations and altitude distributions, particularly for those gases that are important in stratospheric chemistry and radiative balance. Measurements are made with infrared remote sensing instruments, either ground based or balloon-borne. Most of the ground based instruments are part of the Network for Detection of Stratospheric Change (NDSC), including a very high spectral resolution solar absorption spectrometer at Mauna Loa Observatory and similar system at McMurdo Station, Antarctica (operated in collaboration with the New Zealand NIWA). Additionally, we are deriving stratospheric constituent data from the spectra obtained at the DOE Atmospheric Radiation Measurements (ARM) program's site in north-central Oklahoma. We have an atmospheric emission spectrometer system at the South Pole (with additional support from NSF), and an identical NSF support instrument at Eureka, NWT, Canada. Our balloon-borne instruments include a very high resolution solar absorption spectrometer system, a smaller, slightly lower resolution solar spectrometer system, a high resolution atmospheric emission spectrometer, and several medium resolution emission spectrometers (CAESRs) that are usually flown piggyback. During the past year, we participated in the MANTRA balloon flight from Saskatoon, Saskatchewan, with the high resolution solar spectrometer system. Several of our instruments were extensively compared to (UARS) Upper Atmosphere Research Satellite observations, and so provide a data set with known connections to UARS. In the longer term, the data can be used to relate UARS data to (EOS) Earth Observing System and (ADEOS) Advanced Airborne Earth Observing System.

Frank J Murcray↗

NASA NTRS1991

Analysis of Atmospheric Trace Constituents from High Resolution Infrared Balloon-Borne and Ground-Based Solar Absorption Spectra

Recent results and ongoing studies of high resolution solar absorption spectra will be presented. The analysis of these spectra is aimed at the identification and quantification of trace constituents important in atmospheric chemistry of the stratosphere and upper troposphere. Analysis of balloon-borne and ground-based spectra obtained at 0.0025/ cm covering the 700-2200/ cm interval will be presented. Results from ground-based 0.02/ cm solar spectra, from several locations such as Denver, South Pole, M. Loa, and New Zealand will also be shown. The 0.0025/ cm spectra show many new spectroscopic features. The analysis of these spectra, along with corresponding laboratory spectra, improves the spectral line parameters, and thus the accuracy of trace constituents quantification. The combination of the recent balloon flights, with earlier flights data since 1978 at 0.02/ cm resolution, provides trends analysis of several stratospheric trace species. Results for COF2, F22, SF6, and other species will be presented. Analysis of several ground-based solar spectra provides trends for HCl, HF and other species. The retrieval methods used for total column density and altitude distribution for both ground-based and balloon-borne spectra will be presented. These are extended for the analysis of the ground-based spectra to be obtained by the high resolution interferometers of the Network for Detection of Stratospheric Change (NDSC). Progress or the University of Denver studies for the NDSC will be presented. This will include intercomparison of solar spectra and trace gases retrievals obtained from simultaneous scans by the high resolution (0.0025/ cm) interferometers of BRUKER and BOMEM.

Goldman, A.↗

NASA NTRS2001

Nutrient Stress Detection in Corn, Using Neural Networks and AVIRIS Hyperspectral Imagery

The US Department of Agriculture (USDA) Agricultural Research Service (ARS) Variable Rate (VRAT) Nitrogen Application site in Shelton, Nebraska, represents a well-documented, corn-growing quarter section. The USDA VRAT site is used to systematically study nutrient stress in corn by varying sub-plot application of fertilizer. The field has four replicates of five blocks that vary by nitrogen treatment from 0-kg/ha to 200-kg/ha in 50-kg/ha increments. The treatment blocks are set out in a randomized, complete block design. Typically, the VRAT is planted in a ridge till, monoculture corn and is watered by a central pivot irrigation system on a three-day period. Since water stress can increase spectral reflectance from corn leaves, it is important that the N-application plots be adequately watered so that only nutrient-related stress will predominate. A figure shows imagery of the USDA VRAT site with the fertilizer amounts for each block shown. Low-altitude Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) hyperspectral imagery was acquired over the Shelton, Nebraska, VRAT site on July 22, 1999. The overflight produced 3-meter pixels with 224 spectral bands. Ground personnel supported the mission with measurements at the time of the overflight. The image data was pre-processed at JPL before being sent out to an investigator. The data arrived radiometrically corrected, allowing ready application of an atmospheric correction procedure. The Atmosphere Removal Program (ATREM) was used to perform an atmospheric correction. The AVIRIS imagery after ATREM correction was output as relative reflectance. This relative reflectance file was scaled by an empirical line procedure to provide reflectances that matched closely those measured in the field.

Estep, Lee↗

NASA NTRS2003

Neural-Net Based Optical NDE Method for Structural Health Monitoring

This paper answers some performance and calibration questions about a non-destructive-evaluation (NDE) procedure that uses artificial neural networks to detect structural damage or other changes from sub-sampled characteristic patterns. The method shows increasing sensitivity as the number of sub-samples increases from 108 to 6912. The sensitivity of this robust NDE method is not affected by noisy excitations of the first vibration mode. A calibration procedure is proposed and demonstrated where the output of a trained net can be correlated with the outputs of the point sensors used for vibration testing. The calibration procedure is based on controlled changes of fastener torques. A heterodyne interferometer is used as a displacement sensor for a demonstration of the challenges to be handled in using standard point sensors for calibration.

Decker, Arthur J.↗

NASA NTRS2003

Sensitivity and Calibration of Non-Destructive Evaluation Method That Uses Neural-Net Processing of Characteristic Fringe Patterns

Decker, Arthur J.↗

NASA NTRS1999

Neural Networks Used to Compare Designed and Measured Time-Average Patterns

Electronic time-average holograms are convenient for comparing the measured vibration modes of fan blades with those calculated by finite-element models. At the NASA Lewis Research Center, neural networks recently were trained to perform what had been a simple visual comparison of the predictions of the design models with the measurements. Finite-element models were used to train neural networks to recognize damage and strain information encoded in subtle changes in the time-average patterns of cantilevers. But the design-grade finite element models were unable to train the neural networks to detect damage in complex blade shapes. The design-model-generated patterns simply did not agree well enough with the measured patterns. Instead, hybrid-training records, with measured time-average patterns as the input and model-generated strain information as the output, were used to effect successful training.

Decker, Arthur J.↗

NASA NTRS2005

Evaluation of Chemistry-Climate Model Results using Long-Term Satellite and Ground-Based Data

Chemistry-climate models attempt to bring together our best knowledge of the key processes that govern the composition of the atmosphere and its response to changes in forcing. We test these models on a process by process basis by comparing model results to data from many sources. A more difficult task is testing the model response to changes. One way to do this is to use the natural and anthropogenic experiments that have been done on the atmosphere and are continuing to be done. These include the volcanic eruptions of El Chichon and Pinatubo, the solar cycle, and the injection of chlorine and bromine from CFCs and methyl bromide. The test of the model's response to these experiments is their ability to produce the long-term variations in ozone and the trace gases that affect ozone. We now have more than 25 years of satellite ozone data. We have more than 15 years of satellite and ground-based data of HC1, HN03, and many other gases. I will discuss the testing of models using long-term satellite data sets, long-term measurements from the Network for Detection of Stratospheric Change (NDSC) , long-term ground-based measurements of ozone.

Stolarski, Richard S.↗

NASA NTRS2000

Lidar Measurements of Tropospheric and Stratospheric Ozone at Table Mountain Facility, California, and Mauna Loa Observatory, Hawaii: An Overview of 10 Years of Measurements

As part of the Network for Detection of Stratospheric Change (NDSC) three lidars are currently operated by the Jet Propulsion Laboratory (JPL).

atmospheric ozone lidar lidar measurements troposp↗

NASA NTRS2004

The NDSC ozone and temperature lidar alogorithm intercomparison ubutuatuve (A2I): project overview

In September 2003, the Lidar Working Group (LWG) of the Network for Detection of Stratospheric Change (NDSC) initiated an extensive project to compare the ozone and temperature algorithms used within NDSC. This initiative, referred to later as Algorithm Intercomparison Initiative (A2I), uses simulated lidar signals to test and compare various parts of the ozone and temperature lidar algorithms. In addition to the fact that it meets the requirement of the NDSC protocols, this exercise allows the detailed assessment, by all the participants, of some of the sources and magnitudes of various uncertainties associated with the algorithms, and/or with the theoretical assumptions made in these algorithms. The outcome of the A21 is to try to find common grounds in the way ozone and temperature can be retrieved in order to reduce and possibly eradicate discrepancies due to algorithm issues alone. Specific issues such as homogenizing the choice of Rayleigh extinction cross-sections, ozone absorption cross-sections, a priori information, and the definition of the vertical resolutions are among the primary targets of the A21 outcome.

lidar↗

NASA NTRS2006

Optimization of Training Sets For Neural-Net Processing of Characteristic Patterns From Vibrating Solids

An artificial neural network is disclosed that processes holography generated characteristic pattern of vibrating structures along with finite-element models. The present invention provides for a folding operation for conditioning training sets for optimally training forward-neural networks to process characteristic fringe pattern. The folding pattern increases the sensitivity of the feed-forward network for detecting changes in the characteristic pattern The folding routine manipulates input pixels so as to be scaled according to the location in an intensity range rather than the position in the characteristic pattern.

Decker, Arthur J.↗