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At least 127 records · Page 7

Characterization and classification of sea ice in polarimetric SAR data

A more detailed characterization of the apparent thin ice types in the multifrequency, multipolarization synthetic aperture radar (SAR) dataset acquired during a campaign for validation of the DMSP SSM/I radiometer ice products is given. The emphasis is on providing a more detailed characterization of the signatures of apparent thin ice types observed in this data and the utility of these signatures for ice type classification purposes. The statistical characteristics of these signatures and their dependence on system calibration are summarized. Implications of these observations for sea ice scattering models are briefly discussed.

Kwok, R.↗

Software For Analysis Of SAR Data

MacSigmaO is interactive program for Macintosh computer enabling user to display and make computations from data collected by JPL AIR-SAR, ERS-1, JERS-1, and Magellan radar systems. Provides four basic functions: synthesis of images (if necessary), statistical analysis of selected areas, analysis of corner reflectors as calibration measure (if appropriate and possible), and informative mouse tracking. Written in C for use on Macintosh series of computers.

Norikane, Lynne↗

Heterodyne efficiency for a coherent laser radar with diffuse or aerosol targets

The performance of a Coherent Laser Radar is determined by the statistics of the coherent Doppler signal. The heterodyne efficiency is an excellent indication of performance because it is an absolute measure of beam alignment and is independent of the transmitter power, the target backscatter coefficient, the atmospheric attenuation, and the detector quantum efficiency and gain. The theoretical calculation of heterodyne efficiency for an optimal monostatic lidar with a circular aperture and Gaussian transmit laser is presented including beam misalignment in the far-field and near-field regimes. The statistical behavior of estimates of the heterodyne efficiency using a calibration hard target are considered. For space based applications, a biased estimate of heterodyne efficiency is proposed that removes the variability due to the random surface return but retains the sensitivity to misalignment. Physical insight is provided by simulation of the fields on the detector surface. The required detector calibration is also discussed.

Frehlich, R. G.↗

Uncertainties in Upper Stratospheric Ozone Trends from 1979 to 1996

The time series of differences in coincident measurements of ozone by Stratospheric Aerosol and Gas Experiment (SAGE) and by Solar Backscattered Ultraviolet (SBUV), SBUV/2, Umkehr and Microwave Limb Sounder (MLS) are analyzed, and the slopes in the differences are calculated. SAGE ozone measurements are also compared against those by HALOE. The purpose of these comparisons is to look for statistically significant nonzero slopes which could indicate long-term calibration problems in one or more of the measurement systems. It is found that the slopes are remarkably similar between the Northern and Southern Hemisphere midlatitudes, and, apart from a few exceptions, the slopes are also similar in the tropics. Slopes of MLS-SAGE differences and HALOE-SAGE trends from approximately 1992 to 1996 have values of approximately -0.5 +/- 0.4%/yr (95% confidence limits) in Umkehr layers 7-9 (which are centered at approx. 37, 42, and 47 km altitude). Umkehr-SAGE slopes for 1979-1996, however, are almost all positive and in the range -0.1 - 0.41%/yr for Umkehr layers 4 - 8, while SBUV-SAGE slopes for 1979-1989 are essentially zero in layers 4 - 7 and 0.3-0.4%/yr in layers 8 and 9. Averaging all these results with SBUV-SAGE 11 slopes from 1985 to 1989, the other sensors minus SAGE slopes are most likely between 0.2 and -0.2%/yr1 from approx. 20 to 40 km altitude. The results indicate slightly negative slopes in Umkehr layers 5-7 and positive slopes in the other three layers. There thus appears to be no overall drift in the SAGE ozone measurements from 1979 to 1996, but SAGE sunrise/sunset trend differences greater than 40 km altitude, combined with the more accurate SBUV-SAGE slopes for 1979-1989, suggest a most likely slope range of 0.4 to -0.4%/yr between 40 and 50 km altitude. SBUV/2 measurements from 1989 to 1994 have an upward trend with respect to SAGE measurements of approx. 0.7% /yr with some altitudinal structure; this slope exceeds the estimated 95% uncertainties on the SBUV/2 trends.

Cunnold, D. M.↗

Receiver Gain Modulation Circuit

A receiver gain modulation circuit (RGMC) was developed that modulates the power gain of the output of a radiometer receiver with a test signal. As the radiometer receiver switches between calibration noise references, the test signal is mixed with the calibrated noise and thus produces an ensemble set of measurements from which ensemble statistical analysis can be used to extract statistical information about the test signal. The RGMC is an enabling technology of the ensemble detector. As a key component for achieving ensemble detection and analysis, the RGMC has broad aeronautical and space applications. The RGMC can be used to test and develop new calibration algorithms, for example, to detect gain anomalies, and/or correct for slow drifts that affect climate-quality measurements over an accelerated time scale. A generalized approach to analyzing radiometer system designs yields a mathematical treatment of noise reference measurements in calibration algorithms. By treating the measurements from the different noise references as ensemble samples of the receiver state, i.e. receiver gain, a quantitative description of the non-stationary properties of the underlying receiver fluctuations can be derived. Excellent agreement has been obtained between model calculations and radiometric measurements. The mathematical formulation is equivalent to modulating the gain of a stable receiver with an externally generated signal and is the basis for ensemble detection and analysis (EDA). The concept of generating ensemble data sets using an ensemble detector is similar to the ensemble data sets generated as part of ensemble empirical mode decomposition (EEMD) with exception of a key distinguishing factor. EEMD adds noise to the signal under study whereas EDA mixes the signal with calibrated noise. It is mixing with calibrated noise that permits the measurement of temporal-functional variability of uncertainty in the underlying process. The RGMC permits the evaluation of EDA by modulating the receiver gain using an external signal. Without the RGMC, samples of calibrated references from radiometers form an ensemble data set of the natural occurring fluctuations within a receiver. By driving the gain of an otherwise stable receiver with an external signal, the conceptual framework and generalization of the mathematics of EDA can be tested. A series of measurements was conducted to evaluate and characterize the performance of the RGMC. Test signals stepped the RGMC across its dynamic range of performance using a radiometer that sampled four noise references; analysis indicates that the RGMC successfully modulated the receiver gain with an external signal. Calibration algorithms applied to four noise references demonstrate the RGMC produced ensemble data sets of the external signal.

Jones, Hollis↗

(abstract) A VLBI Test of Tropospheric Delay Calibration with WVRs

Dual frequency (S/X band) very long baseline interferometry (VLBI) observations were used to test troposphere calibration by water vapor radiometers (WVRs). Comparison of the VLBI and WVR measurements show a statistical agreement (specifically, their structure functions agree) on time scales less than 700 seconds. On longer time scales, VLBI instrumental errors become important. The improvement in VLBI residual delays from WVR calibration was consistent with the measured level of tropospheric fluctuations.

VLBI water vapor radiometers troposphere interfero↗

Analyzing Responses of Chemical Sensor Arrays

NASA is developing a third-generation electronic nose (ENose) capable of continuous monitoring of the International Space Station s cabin atmosphere for specific, harmful airborne contaminants. Previous generations of the ENose have been described in prior NASA Tech Briefs issues. Sensor selection is critical in both (prefabrication) sensor material selection and (post-fabrication) data analysis of the ENose, which detects several analytes that are difficult to detect, or that are at very low concentration ranges. Existing sensor selection approaches usually include limited statistical measures, where selectivity is more important but reliability and sensitivity are not of concern. When reliability and sensitivity can be major limiting factors in detecting target compounds reliably, the existing approach is not able to provide meaningful selection that will actually improve data analysis results. The approach and software reported here consider more statistical measures (factors) than existing approaches for a similar purpose. The result is a more balanced and robust sensor selection from a less than ideal sensor array. The software offers quick, flexible, optimal sensor selection and weighting for a variety of purposes without a time-consuming, iterative search by performing sensor calibrations to a known linear or nonlinear model, evaluating the individual sensor s statistics, scoring the individual sensor s overall performance, finding the best sensor array size to maximize class separation, finding optimal weights for the remaining sensor array, estimating limits of detection for the target compounds, evaluating fingerprint distance between group pairs, and finding the best event-detecting sensors.

Zhou, Hanying↗

Inter-Calibration of Nine UV Sensing Instruments Over Antarctica and Greenland Since 1980

Nadir-viewed intensities (radiances) from nine UV sensing satellite instruments are calibrated over the East Antarctic Plateau and Greenland during summer. The calibrated radiances from these UV instruments ultimately will provide a global long-term record of cloud trends and cloud response from ENSO events since 1980. We first remove the strong solar zenith angle dependence from the intensities using an empirical approach rather than a radiative trans-fer model. Then small multiplicative adjustments are made to these solar zenith angle normalized intensities in order to minimize differences when two or more instruments tempo-rally overlap. While the calibrated intensities show a negligible long-term trend over Antarctica and a statistically in-significant UV albedo trend of−0.05 % per decade over the interior of Greenland, there are small episodic reductions in intensities which are often seen by multiple instruments. Three of these darkening events are explained by boreal forest. Other events are caused by surface melting or volcanoes. We estimate a 2-sigma uncertainty of 0.35% for the calibrated radiances

Nadir-viewed intensities (radiances) from nine UV ↗

Charge Resolution of the Silicon Matrix of the ATIC Experiment

ATIC (Advanced Thin Ionization Calorimeter) is a balloon borne experiment designed to measure the cosmic ray composition for elements from hydrogen to iron and their energy spectra from approx.50 GeV to near 100 TeV. It consists of a Si-matrix detector to determine the charge of a CRT particle, a scintillator hodoscope for tracking, carbon interaction targets and a fully active BGO calorimeter. ATIC had its first flight from McMurdo, Antarctica from 28/12/2000 to 13/01/2001. The ATIC flight collected approximately 25 million events. The silicon matrix of the ATIC spectrometer is designed to resolve individual elements from proton to iron. To provide this resolution careful calibration of each pixel of the silicon matrix is required. Firstly, for each electronic channel of the matrix the pedestal value was subtracted taking into account its drift during the flight. The muon calibration made before the flight was used then to convert electric signals (in ADC channel number) to energy deposits in each pixel. However, the preflight muon calibration was not accurate enough for the purpose, because of lack of statistics in each pixel. To improve charge resolution the correction was done for the position of Helium peak in each pixel during the flight . The other way to set electric signals in electronics channels of the Si-matrix to one scale was correction for electric channel gains accurately measured in laboratory. In these measurements it was found that small different nonlinearities for different channels are present in the region of charge Z > 20. The correction for these non-linearities was not done yet. In linear approximation the method provides practically the same resolution as muon calibration plus He-peak correction. For searching a pixel with the signal of primary particle an indication from the cascade in the calorimeter was used. For this purpose a trajectory was reconstructed using weight centers of energy deposits in BGO layers. The point of intersection of this trajectory with Si-matrix and its RMS was determined. The pixel with maximal signal in 3sigma region was taken as sought. The signal in this pixel was corrected by trajectory zenith angle. The preliminary results on charge resolution of the Si-matrix in the range from protons to iron are presented.

Zatsepin, V. I.↗

Signal Processing and Calibration of Continuous-Wave Focused CO2 Doppler Lidars for Atmospheric Backscatter Measurement

Two continuous-wave(CW)focused C02 Doppler lidars (9.1 and 10.6 micrometers) were developed for airborne in situ aerosol backscatter measurements. The complex path of reliably calibrating these systems, with different signal processors, for accurate derivation of atmospheric backscatter coefficients is documented. Lidar calibration for absolute backscatter measurement for both lidars is based on range response over the lidar sample volume, not solely at focus. Both lidars were calibrated with a new technique using well-characterized aerosols as radiometric standard targets and related to conventional hard-target calibration. A digital signal processor (DSP), a surface acoustic and spectrum analyzer and manually tuned spectrum analyzer signal analyzers were used. The DSP signals were analyzed with an innovative method of correcting for systematic noise fluctuation; the noise statistics exhibit the chi-square distribution predicted by theory. System parametric studies and detailed calibration improved the accuracy of conversion from the measured signal-to-noise ratio to absolute backscatter. The minimum backscatter sensitivity is approximately 3 x 10(exp -12)/m/sr at 9.1 micrometers and approximately 9 x 10(exp -12)/m/sr at 10.6 micrometers. Sample measurements are shown for a flight over the remote Pacific Ocean in 1990 as part of the NASA Global Backscatter Experiment (GLOBE) survey missions, the first time to our knowledge that 9.1-10.6 micrometer lidar intercomparisons were made. Measurements at 9.1 micrometers, a potential wavelength for space-based lidar remote-sensing applications, are to our knowledge the first based on the rare isotope C-12 O(2)-18 gas.

Rothermel, Jeffry↗

Statistical Process Control and Capability Study on the Water Content Measurements in NASA Glenn's Icing Research Tunnel

The Icing Research Tunnel (IRT) at NASA Glenn Research Center follows the recommended practice for icing tunnel calibration outlined in SAE's ARP5905 document. The calibration team has followed the schedule of a full calibration every five years with a check calibration done every six months following. The liquid water content of the IRT has maintained stability within in the specifications presented to customers that the variation is within +/- 10% of the calibrated, target measurement. With recent measurements and instrumentation errors, a more thorough assessment of error source was desired. By constructing statistical process control charts, the ability to determine how the instrument varies in the short term, mid term, and long term was gained. The control charts offer a view of instrument error, facility error, or installation changes. It was discovered that there was a shift from target to mean baseline thus leading to the study of the overall capability indices of the liquid water content measuring instrument to perform within specifications defined in the IRT. This presentation describes data processing procedures for the Multi-Element Sensor in the IRT, including collision efficiency corrections, canonical correlation analysis, Chauvenet's Criterion for rejection of data, distribution check of data, and mean, median and mode for construction of control charts. Further data is presented to describe the repeatability of the IRT with the Multi-Element Sensor and the ability to maintain a stable process for the defined calibration schedule.

Timko, Emily N.↗

Crossed hot-wire data acquisition and reduction system

The report describes a system for rapid computerized calibration acquisition, and processing of data from a crossed hot-wire anemometer is described. Advantages of the system are its speed, minimal use of analog electronics, and improved accuracy of the resulting data. Two components of mean velocity and turbulence statistics up to third order are provided by the data reduction. Details of the hardware, calibration procedures, response equations, software, and sample results from measurements in a turbulent plane mixing layer are presented.

Westphal, R. V.↗

Computer program for analysis of vectorcardiograms (VECTAN II)

VECTAN II accepts as input digitized three-lead VCG data sampled at 320 samples/second/lead, analyzing one VCG complex in each 5-second interval for experiments of up to 25 minutes duration. Program calibrates these data, locates major waveforms, performs waveform analyses, and produces statistical summary of analyzed data.

Hoffler, G. W.↗

Capella: Structure and Abundances

This grant covers the analysis of EUVE spectra of the cool star binary system Capella. This project has also required the analysis of simultaneous Advanced Satellite for Cosmology and Astrophysics (ASCA) data. The ASCA spectrum of Capella could not be fit with standard models; by imposing models based on strong lines observed with EUVE, a problem wavelength region was identified. Correcting the problem required calculations of atomic collision strengths of higher principal quantum number than had ever been calculated. With these new models applied to the ASCA spectrum, better fits were obtained. Findings are that: (1) ASCA and EUVE spectra are both dominated by a region at 6 x 10(exp 6) K. (2) The high energy cut-off of the ASCA spectrum is consistent with emission from the highest ionization stages of EUVE, namely Fe XXIV. (3) EUVE requires a continuous emission measure distribution with more than two temperatures. (4) The ASCA spectra are of such high statistical significance that systematic uncertainties dominate, including atomic physics issues and calibration issues. (5) While the ASCA spectral fits achieve lower Chi(exp 2 with two-temperature fits, the EUVE-derived emission measure distribution models are also consistent with the spectra. (6) The Fe/H ratio obtained from the ASCA fit is within 20 % of the Fe/H abundance obtained from the summed spectra of Capella over 5 EUVE pointings, as well as the 1996 EUVE data. This result confirms our claims that quasi-continua composed of weak emission lines in the short wavelength spectrometer of EUVE are not major contributors to the measured Capella continuum. Other abundance ratios are also determined from the ASCA data, using models derived with EUVE. Si, Si, and Mg appear to be close to solar photospheric values, while the ratio of Ne/Fe is three to four times lower than solar photospheric values. Whether there is a general First Ionization Potential (FIP) effect or a specific neon anomaly cannot be determined from these data. (8) EUVE line ratios indicating low optical depth place limits on the extent to which the X-ray lines are optically, thick. While the brightest lines may be marginally thick, the ASCA spectrum is not of sufficient resolution to determine the optical depth in these lines.

Brickhouse, Nancy S.↗

Electrostatics of Granular Material (EGM): Space Station Experiment

Aggregates were observed to form very suddenly in a lab-contained dust cloud, transforming (within seconds) an opaque monodispersed cloud into a clear volume containing rapidly-settling, long hair-like aggregates. The implications of such a "phase change" led to a series of experiments progressing from the lab, to KC-135, followed by micro-g flights on USML-1 and USML-2, and now EGM slated for Space Station. We attribute the sudden "collapse" of a cloud to the effect of dipoles. This has significant ramifications for all types of cloud systems, and additionally implicates dipoles in the processes of cohesion and adhesion of granular matter. Notably, there is the inference that like-charged grains need not necessarily repel if they are close enough together: attraction or repulsion depends on intergranular distance (the dipole being more powerful at short range), and the D/M ratio for each grain, where D is the dipole moment and M is the net charge. We discovered that these ideas about dipoles, the likely pervasiveness of them in granular material, the significance of the D/M ratio, and the idea of mixed charges on individual grains resulting from tribological processes --are not universally recognized in electrostatics, granular material studies, and aerosol science, despite some early seminal work in the literature, and despite commercial applications of dipoles in such modern uses as "Krazy Glue", housecleaning dust cloths, and photocopying. The overarching goal of EGM is to empirically prove that (triboelectrically) charged dielectric grains of material have dipole moments that provide an "always attractive" intergranular force as a result of both positive and negative charges residing on the surfaces of individual grains. Microgravity is required for this experiment because sand grains can be suspended as a cloud for protracted periods, the grains are free to rotate to express their electrostatic character, and Coulombic forces are unmasked. Suspended grains will be "interrogated" by applied electrical fields. In one module, grains will be immersed in an inhomogeneous electric field and allowed to be attracted towards or repelled from the central electrode of the module: part of the grain's speed will be a function of its net charge (monopole), part will be a function of the dipole. Observed grain position vs. time will provide a curve that can be deconvolved into the dipole and monopole forces responsible, since both have distinctive radial dependencies. In a second approach, the inhomogeneous field will be alternated at low frequency (e.g., every 5-10 seconds) so that the grains are alternately attracted and repelled from the center of the field. The resulting "zigzag" grain motion will gradually drift inwards, then suddenly change to a unidirectional inward path when a critical radial distance is encountered (a sort of "Coulombic event horizon") at which the dipole strength supersedes the monopole strength --thus proving the presence of a dipole, while also quantifying the D/M ratio. In a second module, an homogeneous electric field eliminates dipole effects (both Coulombic and induced) to provide calibration of the monopole and to more readily evaluate net charge statistical variance. In both modules, the e-fields will be exponentially step-ramped in voltage during the experiment, so that the field "nominalizes" grain speed while spreading the response time --effectively forcing each grain to "wait its turn" to be measured. In addition to rigorously quantifying M, D, and the D/M ratio for many hundreds of grains, the experiment will also observe gross electrometric and RF discharge phenomena associated with grain activity. The parameter space will encompass grain charging levels (via intentional triboelectrification), grain size, cloud density, and material type. Results will prove or disprove the dipole hypothesis. In either case, light will be shed on the role of electrostatic forces in governing granular systems. Knowledge so gained can be applied to natural clouds such as protostellar and protoplanetary dust and debris systems, planetary rings, planetary dust palls and aerosols created by volcanic, impact, aeolian, firestorm, or nuclear winter processes. The data are also directly applicable to adhesion, cohesion, transport, dispersion, and collection of granular materials in industrial, agricultural, pharmaceutical applications, and in fields as diverse as dust contamination of space suits on Mars and crop spraying on Earth.

Marshall, J.↗

Digital Signal Processing Techniques for the GIFTS SM EDU

The Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS) Sensor Module (SM) Engineering Demonstration Unit (EDU) is a high resolution spectral imager designed to measure infrared (IR) radiance using a Fourier transform spectrometer (FTS). The GIFTS instrument employs three Focal Plane Arrays (FPAs), which gather measurements across the long-wave IR (LWIR), short/mid-wave IR (SMWIR), and visible spectral bands. The raw interferogram measurements are radiometrically and spectrally calibrated to produce radiance spectra, which are further processed to obtain atmospheric profiles via retrieval algorithms. This paper describes several digital signal processing (DSP) techniques involved in the development of the calibration model. In the first stage, the measured raw interferograms must undergo a series of processing steps that include filtering, decimation, and detector nonlinearity correction. The digital filtering is achieved by employing a linear-phase even-length FIR complex filter that is designed based on the optimum equiripple criteria. Next, the detector nonlinearity effect is compensated for using a set of pre-determined detector response characteristics. In the next stage, a phase correction algorithm is applied to the decimated interferograms. This is accomplished by first estimating the phase function from the spectral phase response of the windowed interferogram, and then correcting the entire interferogram based on the estimated phase function. In the calibration stage, we first compute the spectral responsivity based on the previous results and the ideal Planck blackbody spectra at the given temperatures, from which, the calibrated ambient blackbody (ABB), hot blackbody (HBB), and scene spectra can be obtained. In the post-calibration stage, we estimate the Noise Equivalent Spectral Radiance (NESR) from the calibrated ABB and HBB spectra. The NESR is generally considered as a measure of the instrument noise performance, and can be estimated as the standard deviation of calibrated radiance spectra from multiple scans. To obtain an estimate of the FPA performance, we developed an efficient method of generating pixel performance assessments. In addition, a random pixel selection scheme is developed based on the pixel performance evaluation. This would allow us to perform the calibration procedures on a random pixel population that is a good statistical representation of the entire FPA. The design and implementation of each individual component will be discussed in details.

Tian, Jialin↗

COBE Final Report: Dirbe Celestial Calibration

We report the results of a comparative study of the COsmic Background Explorer/Diffuse InfraRed Background Experiment (COBE/DIRBE) photometric calibration over about 100 selected stellar and non-stellar calibration objects across a wide range of the DIRBE instrument dynamic range, wavelength coverage, and source temperature. A statistical comparison of the DIRBE-reported flux to the accepted values from the literature (as summarized in the CIO) provides an independent verification of the DIRBE point source calibration.

Burdick, Shawn V.↗

Chrono-Validation of Near-Real-Time Landslide Susceptibility Models via Plugin Statistical Simulations

The idea behind any validation scheme in landslide susceptibility studies is to test whether a model calibrated on a certain data can predict an unknown dataset of the same nature (landslide presences/absences and covariates). Almost the entirety of landslide susceptibility studies are validated by subsetting a single dataset into a training and test sets. This dataset usually corresponds either to event-specific or to historical inventories. Very rarely, a multi-temporal inventory is available and, in the few cases where this condition is met, the validation practices involve training a model on a specific landslide inventory, deriving a single predictive equation and validating it on a subsequent landslide inventory. This commonly leads landslide predictive studies, even those with a strong statistical rigor, to neglect the uncertainty estimation in their modeling scheme. In statistics, validation can also be performed via statistical simulations. This means that after fitting a given model, one can generate any number of predictive functions and test their predictive skills on any type and number of unknown datasets. In this work, we take a similar direction and we apply it to model and validate three separate co-seismic inventories, including an uncertainty estimation phase. We mapped these inventories within the same area in Indonesia, for three earthquakes occurred in 2012, 2017 and 2018. Specifically, we build three event-specific Bayesian Generalize Additive Models of the binomial family. From each model we then simulate 1000 predictive realizations over the remaining two inventories, by using a plug-in scheme where all the morphometric covariates are kept fixed and only the ground motion is replaced according to the prediction target. By doing so, we introduce a new analytical tool for near-real-time landslide predictive purposes, which is able to produce a probabilistic model which stands in between the definitions of susceptibility and hazard. In fact, our model is able to accurately estimate “where” and “when” - although not “how frequently” - landslide have occurred by featuring the multitemporal information of the trigger. In our findings, the simulations are quite similar to the fitted models; and the nine combinations we analyse produce excellent performance. This result confirms the assumption that “the past is the key to the future”, as we show that the relative contribution of each variable and their interactions in each probabilistic model remains practically the same across temporal replicates. This information is not trivial because it supports the routines implemented in global near-real-time applications.

Temporal validation↗