Reassessing the effect of cloud type on Earth's energy balance

NASA Astrophysics Data System (ADS)

Hang, A.; L'Ecuyer, T.

2017-12-01

Cloud feedbacks depend critically on the characteristics of the clouds that change, their location and their environment. As a result, accurately predicting the impact of clouds on future climate requires a better understanding of individual cloud types and their spatial and temporal variability. This work revisits the problem of documenting the effects of distinct cloud regimes on Earth's radiation budget distinguishing cloud types according to their signatures in spaceborne active observations. Using CloudSat's multi-sensor radiative fluxes product that leverages high-resolution vertical cloud information from CloudSat, CALIPSO, and MODIS observations to provide the most accurate estimates of vertically-resolved radiative fluxes available to date, we estimate the global annual mean net cloud radiative effect at the top of the atmosphere to be -17.1 W m-2 (-44.2 W m-2 in the shortwave and 27.1 W m-2 in the longwave), slightly weaker than previous estimates from passive sensor observations. Multi-layered cloud systems, that are often misclassified using passive techniques but are ubiquitous in both hemispheres, contribute about -6.2 W m-2 of the net cooling effect, particularly at ITCZ and higher latitudes. Another unique aspect of this work is the ability of CloudSat and CALIPSO to detect cloud boundary information providing an improved capability to accurately discern the impact of cloud-type variations on surface radiation balance, a critical factor in modulating the disposition of excess energy in the climate system. The global annual net cloud radiative effect at the surface is estimated to be -24.8 W m-2 (-51.1 W m-2 in the shortwave and 26.3 W m-2 in the longwave), dominated by shortwave heating in multi-layered and stratocumulus clouds. Corresponding estimates of the effects of clouds on atmospheric heating suggest that clouds redistribute heat from poles to equator enhancing the general circulation.

Cloud vertical profiles derived from CALIPSO and CloudSat and a comparison with MODIS derived clouds

NASA Astrophysics Data System (ADS)

Kato, S.; Sun-Mack, S.; Miller, W. F.; Rose, F. G.; Minnis, P.; Wielicki, B. A.; Winker, D. M.; Stephens, G. L.; Charlock, T. P.; Collins, W. D.; Loeb, N. G.; Stackhouse, P. W.; Xu, K.

2008-05-01

CALIPSO and CloudSat from the a-train provide detailed information of vertical distribution of clouds and aerosols. The vertical distribution of cloud occurrence is derived from one month of CALIPSO and CloudSat data as a part of the effort of merging CALIPSO, CloudSat and MODIS with CERES data. This newly derived cloud profile is compared with the distribution of cloud top height derived from MODIS on Aqua from cloud algorithms used in the CERES project. The cloud base from MODIS is also estimated using an empirical formula based on the cloud top height and optical thickness, which is used in CERES processes. While MODIS detects mid and low level clouds over the Arctic in April fairly well when they are the topmost cloud layer, it underestimates high- level clouds. In addition, because the CERES-MODIS cloud algorithm is not able to detect multi-layer clouds and the empirical formula significantly underestimates the depth of high clouds, the occurrence of mid and low-level clouds is underestimated. This comparison does not consider sensitivity difference to thin clouds but we will impose an optical thickness threshold to CALIPSO derived clouds for a further comparison. The effect of such differences in the cloud profile to flux computations will also be discussed. In addition, the effect of cloud cover to the top-of-atmosphere flux over the Arctic using CERES SSF and FLASHFLUX products will be discussed.

Ten Years of Cloud Optical and Microphysical Retrievals from MODIS

NASA Technical Reports Server (NTRS)

Platnick, Steven; King, Michael D.; Wind, Galina; Hubanks, Paul; Arnold, G. Thomas; Amarasinghe, Nandana

2010-01-01

The MODIS cloud optical properties algorithm (MOD06/MYD06 for Terra and Aqua MODIS, respectively) has undergone extensive improvements and enhancements since the launch of Terra. These changes have included: improvements in the cloud thermodynamic phase algorithm; substantial changes in the ice cloud light scattering look up tables (LUTs); a clear-sky restoral algorithm for flagging heavy aerosol and sunglint; greatly improved spectral surface albedo maps, including the spectral albedo of snow by ecosystem; inclusion of pixel-level uncertainty estimates for cloud optical thickness, effective radius, and water path derived for three error sources that includes the sensitivity of the retrievals to solar and viewing geometries. To improve overall retrieval quality, we have also implemented cloud edge removal and partly cloudy detection (using MOD35 cloud mask 250m tests), added a supplementary cloud optical thickness and effective radius algorithm over snow and sea ice surfaces and over the ocean, which enables comparison with the "standard" 2.1 11m effective radius retrieval, and added a multi-layer cloud detection algorithm. We will discuss the status of the MOD06 algorithm and show examples of pixellevel (Level-2) cloud retrievals for selected data granules, as well as gridded (Level-3) statistics, notably monthly means and histograms (lD and 2D, with the latter giving correlations between cloud optical thickness and effective radius, and other cloud product pairs).

Cloud retrievals from satellite data using optimal estimation: evaluation and application to ATSR

NASA Astrophysics Data System (ADS)

Poulsen, C. A.; Siddans, R.; Thomas, G. E.; Sayer, A. M.; Grainger, R. G.; Campmany, E.; Dean, S. M.; Arnold, C.; Watts, P. D.

2012-08-01

Clouds play an important role in balancing the Earth's radiation budget. Hence, it is vital that cloud climatologies are produced that quantify cloud macro and micro physical parameters and the associated uncertainty. In this paper, we present an algorithm ORAC (Oxford-RAL retrieval of Aerosol and Cloud) which is based on fitting a physically consistent cloud model to satellite observations simultaneously from the visible to the mid-infrared, thereby ensuring that the resulting cloud properties provide both a good representation of the short-wave and long-wave radiative effects of the observed cloud. The advantages of the optimal estimation method are that it enables rigorous error propagation and the inclusion of all measurements and any a priori information and associated errors in a rigorous mathematical framework. The algorithm provides a measure of the consistency between retrieval representation of cloud and satellite radiances. The cloud parameters retrieved are the cloud top pressure, cloud optical depth, cloud effective radius, cloud fraction and cloud phase. The algorithm can be applied to most visible/infrared satellite instruments. In this paper, we demonstrate the applicability to the Along-Track Scanning Radiometers ATSR-2 and AATSR. Examples of applying the algorithm to ATSR-2 flight data are presented and the sensitivity of the retrievals assessed, in particular the algorithm is evaluated for a number of simulated single-layer and multi-layer conditions. The algorithm was found to perform well for single-layer cloud except when the cloud was very thin; i.e., less than 1 optical depths. For the multi-layer cloud, the algorithm was robust except when the upper ice cloud layer is less than five optical depths. In these cases the retrieved cloud top pressure and cloud effective radius become a weighted average of the 2 layers. The sum of optical depth of multi-layer cloud is retrieved well until the cloud becomes thick, greater than 50 optical depths, where the cloud begins to saturate. The cost proved a good indicator of multi-layer scenarios. Both the retrieval cost and the error need to be considered together in order to evaluate the quality of the retrieval. This algorithm in the configuration described here has been applied to both ATSR-2 and AATSR visible and infrared measurements in the context of the GRAPE (Global Retrieval and cloud Product Evaluation) project to produce a 14 yr consistent record for climate research.

NASA/MSFC multilayer diffusion models and computer program for operational prediction of toxic fuel hazards

NASA Technical Reports Server (NTRS)

Dumbauld, R. K.; Bjorklund, J. R.; Bowers, J. F.

1973-01-01

The NASA/MSFC multilayer diffusion models are discribed which are used in applying meteorological information to the estimation of toxic fuel hazards resulting from the launch of rocket vehicle and from accidental cold spills and leaks of toxic fuels. Background information, definitions of terms, description of the multilayer concept are presented along with formulas for determining the buoyant rise of hot exhaust clouds or plumes from conflagrations, and descriptions of the multilayer diffusion models. A brief description of the computer program is given, and sample problems and their solutions are included. Derivations of the cloud rise formulas, users instructions, and computer program output lists are also included.

Merging Sounder and Imager Data for Improved Cloud Depiction on SNPP and JPSS.

NASA Astrophysics Data System (ADS)

Heidinger, A. K.; Holz, R.; Li, Y.; Platnick, S. E.; Wanzong, S.

2017-12-01

Under the NOAA GOES-R Algorithm Working Group (AWG) Program, NOAA supports the development of an Infrared (IR) Optimal Estimation (OE) Cloud Height Algorithm (ACHA). ACHA is an enterprise solution that supports many geostationary and polar orbiting imager sensors. ACHA is operational at NOAA on SNPP VIIRS and has been adopted as the cloud height algorithm for the NASA NPP Atmospheric Suite of products. Being an OE algorithm, ACHA is flexible and capable of using additional observations and constraints. We have modified ACHA to use sounder (CriS) observations to improve the cloud detection, typing and height estimation. Specifically, these improvements include retrievals in multi-layer scenarios and improved performance in polar regions. This presentation will describe the process for merging VIIRS and CrIS and a demonstration of the improvements.

Experimental measurements of the ground cloud effluents and cloud growth for the May 20, 1975, Titan 3C launch at Air Force Eastern Test Range, Florida

NASA Technical Reports Server (NTRS)

Gregory, G. L.; Storey, R. W., Jr.

1977-01-01

The experiment included surface level and airborne in situ cloud measurements of the exhaust effluents from the Titan IIIC solid rocket boosters. Simultaneous visible spectrum photographic pictures of the ground cloud as well as infrared imaging of the cloud were obtained to study the cloud rise, growth, and direction of travel within the earth's surface mixing layer. The NASA multilayer diffusion model predictions of cloud growth, direction of travel, and expected surface level effluent concentrations were made prior to launch and after launch using measured meteorological conditions. Prelaunch predictions were used to position the effluent monitoring instruments, and the postlaunch predictions were compared with the measured data. Measurement results showed that surface level effluent values were low, often below the detection limits of the instrumentation. The maximum surface level hydrogen chloride concentration measured 50 parts per billion at about 8 km from the launch pad. The maximum observed in-cloud (airborne measurement) hydrogen chloride concentration was 7 per million.

Preliminary Analysis of X-Band and Ka-Band Radar for Use in the Detection of Icing Conditions Aloft

NASA Technical Reports Server (NTRS)

Reehorst, Andrew L.; Koenig, George G.

2004-01-01

NASA and the U.S. Army Cold Regions Research and Engineering Laboratory (CRREL) have an on-going activity to develop remote sensing technologies for the detection and measurement of icing conditions aloft. Radar has been identified as a strong tool for this work. However, since the remote detection of icing conditions with the intent to identify areas of icing hazard is a new and evolving capability, there are no set requirements for radar sensitivity. This work is an initial attempt to quantify, through analysis, the sensitivity requirements for an icing remote sensing radar. The primary radar of interest for cloud measurements is Ka-band, however, since NASA is currently using an X-band unit, this frequency is also examined. Several aspects of radar signal analysis were examined. Cloud reflectivity was calculated for several forms of cloud using two different techniques. The Air Force Geophysical Laboratory (AFGL) cloud models, with different drop spectra represented by a modified gamma distribution, were utilized to examine several categories of cloud formation. Also a fundamental methods approach was used to allow manipulation of the cloud droplet size spectra. And an analytical icing radar simulator was developed to examine the complete radar system response to a configurable multi-layer cloud environment. Also discussed is the NASA vertical pointing X-band radar. The radar and its data system are described, and several summer weather events are reviewed.

MOD06 Optical and Microphysical Retrievals

NASA Technical Reports Server (NTRS)

King, Michael D.; Platnick, Steven; Arnold, G. T.; Dinsick, J.; Gatebe, C. K.; Gray, M. A.; Hubanks, P. A.; Moody, E. G.; Wind, B.; Wind, G.

2003-01-01

Major efforts over the past six months included: (1) submission of MOD06 Optical and Microphysical Retrieval recompetition proposal, (2) delivery of a MODIS Atmosphere Level-3 update, (3) delivery of the MODIS Atmosphere s new combined Level-2 product, (4) development of an above-cloud precipitable water research algorithm and a multi-layer cloud detection algorithm, (5) continued development of a Fortran 90 version of the retrieval code for use with MAS as well as operational MODIS processing, (6) preliminary analysis of CRYSTAL-FACE field experiment in July 2002, (7) continued analysis of data obtained during the SAFARI 2000 dry season campaign in southern Africa, and the Arctic FIRE-ACE experiment.

Remote Sensing of Cloud Top Heights Using the Research Scanning Polarimeter

NASA Technical Reports Server (NTRS)

Sinclair, Kenneth; van Diedenhoven, Bastiaan; Cairns, Brian; Yorks, John; Wasilewski, Andrzej

2015-01-01

Clouds cover roughly two thirds of the globe and act as an important regulator of Earth's radiation budget. Of these, multilayered clouds occur about half of the time and are predominantly two-layered. Changes in cloud top height (CTH) have been predicted by models to have a globally averaged positive feedback, however observational changes in CTH have shown uncertain results. Additional CTH observations are necessary to better and quantify the effect. Improved CTH observations will also allow for improved sub-grid parameterizations in large-scale models and accurate CTH information is important when studying variations in freezing point and cloud microphysics. NASA's airborne Research Scanning Polarimeter (RSP) is able to measure cloud top height using a novel multi-angular contrast approach. RSP scans along the aircraft track and obtains measurements at 152 viewing angles at any aircraft location. The approach presented here aggregates measurements from multiple scans to a single location at cloud altitude using a correlation function designed to identify the location-distinct features in each scan. During NASAs SEAC4RS air campaign, the RSP was mounted on the ER-2 aircraft along with the Cloud Physics Lidar (CPL), which made simultaneous measurements of CTH. The RSPs unique method of determining CTH is presented. The capabilities of using single and combinations of channels within the approach are investigated. A detailed comparison of RSP retrieved CTHs with those of CPL reveal the accuracy of the approach. Results indicate a strong ability for the RSP to accurately identify cloud heights. Interestingly, the analysis reveals an ability for the approach to identify multiple cloud layers in a single scene and estimate the CTH of each layer. Capabilities and limitations of identifying single and multiple cloud layers heights are explored. Special focus is given to sources of error in the method including optically thin clouds, physically thick clouds, multi-layered clouds as well as cloud phase. When determining multi-layered CTHs, limits on the upper clouds opacity are assessed.

Multi-layer Clouds Over the South Indian Ocean

NASA Image and Video Library

2003-05-07

The complex structure and beauty of polar clouds are highlighted by these images acquired by NASA Terra spacecraft on April 23, 2003. These clouds occur at multiple altitudes and exhibit a noticeable cyclonic circulation over the Southern Indian Ocean,

Development of module for neural network identification of attacks on applications and services in multi-cloud platforms

NASA Astrophysics Data System (ADS)

Parfenov, D. I.; Bolodurina, I. P.

2018-05-01

The article presents the results of developing an approach to detecting and protecting against network attacks on the corporate infrastructure deployed on the multi-cloud platform. The proposed approach is based on the combination of two technologies: a softwareconfigurable network and virtualization of network functions. The approach for searching for anomalous traffic is to use a hybrid neural network consisting of a self-organizing Kohonen network and a multilayer perceptron. The study of the work of the prototype of the system for detecting attacks, the method of forming a learning sample, and the course of experiments are described. The study showed that using the proposed approach makes it possible to increase the effectiveness of the obfuscation of various types of attacks and at the same time does not reduce the performance of the network

Remote Sensing of Cloud Top Height from SEVIRI: Analysis of Eleven Current Retrieval Algorithms

NASA Technical Reports Server (NTRS)

Hamann, U.; Walther, A.; Baum, B.; Bennartz, R.; Bugliaro, L.; Derrien, M.; Francis, P. N.; Heidinger, A.; Joro, S.; Kniffka, A.;

Observations of Aircraft Dissipation Trails from GOES

NASA Technical Reports Server (NTRS)

Duda, David P.; Minnis, Patrick

2002-01-01

Two cases of distrails (aircraft dissipation trails) with associated fall streak clouds were analyzed using multispectral geostationary satellite data. One distrail was observed on 23 July 2000 in a single cloud layer over southeastern Virginia and the Chesapeake Bay. Another set of trails developed on 6 January 2000 at the top of multilayer clouds off the coasts of Georgia and South Carolina. The distrails on both days formed in optically thin, midlevel stratified clouds with cloud-top heights between 7.6 and 9.1 km. The distrail features remained intact and easily visible from satellite images for 1-2 h in spite of winds near 50 km at cloud level. The width of the distrails spread as far as 20 km within 90 min or less. Differences between the optical properties of the clouds surrounding the trails and those of the fall streak particles inside the distrails allowed for easy identification of the fall streak clouds in either the 3.9-micrometer brightness temperature imagery, or the 10.7-micrometer - 12.0-micrometer brightness temperature difference. Although the three-channel infrared retrieval was better at retrieving cloud properties in the multilayer cloud case, two independent remote sensing retrievals of both distrail cases showed that the fall streaks had larger particle sizes than the clouds outside of the trails.

Complex Clouds

Atmospheric Science Data Center

2013-04-16

... article title:  Multi-layer Clouds Over the South Indian Ocean     View Larger Image ... System-2 path 155. MISR was built and is managed by NASA's Jet Propulsion Laboratory, Pasadena, CA, for NASA's Science Mission ...

Optimum efficiency lidar sensing of multilayer hydrometeors through a turbid atmosphere

NASA Astrophysics Data System (ADS)

Evgenieva, Ts T.; Gurdev, L. L.

2018-03-01

The detected lidar return power is a basic factor determining the brightness of the detected lidar images and the signal-to-noise ratio (SNR) of a given measurement. At equal other characteristics, the laser radiation wavelength should influence the lidar return signal and assume an optimum value depending on the specificity of the objects investigated. As such a problem had not been considered systematically, we recently began developing a modeling approach to solving it, based on evaluating the mean and the noisy lidar profiles and the SNR profile of the measurement along the lidar line of sight by using the lidar equation and well known realistic models of the atmospheric objects and background. The main purpose of the present work is to estimate by numerical modeling the detectability of the lidar return from different distances and multilayer cirrus clouds, depending on the laser radiation wavelengths. The results obtained confirm the expectations that at a higher atmospheric turbidity, a relatively higher sensing efficiency (return power) is achievable by longer-wavelength laser radiation, within the NIR range.

On Cirrus Cloud Fields Measured by the Atmospheric Infrared Sounder

NASA Technical Reports Server (NTRS)

Kahn, Brian H.; Eldering, Annmarie; Liou, Kuo Nan

2006-01-01

A viewgraph presentation showing trends in clouds measured by the Atmospheric Infrared Sounder (AIRS) is given. The topics include: 1) Trends in clouds measured by AIRS: Are they reasonable? 2) Single and multilayered cloud trends; 3) Retrievals of thin cirrus D(sub e) and tau: Single-layered cloud only; 4) Relationships between ECF, D(sub e), tau, and T(sub CLD); and 5) MODIS vs. AIRS retrievals.

Adaptive Weibull Multiplicative Model and Multilayer Perceptron Neural Networks for Dark-Spot Detection from SAR Imagery

PubMed Central

Taravat, Alireza; Oppelt, Natascha

2014-01-01

Oil spills represent a major threat to ocean ecosystems and their environmental status. Previous studies have shown that Synthetic Aperture Radar (SAR), as its recording is independent of clouds and weather, can be effectively used for the detection and classification of oil spills. Dark formation detection is the first and critical stage in oil-spill detection procedures. In this paper, a novel approach for automated dark-spot detection in SAR imagery is presented. A new approach from the combination of adaptive Weibull Multiplicative Model (WMM) and MultiLayer Perceptron (MLP) neural networks is proposed to differentiate between dark spots and the background. The results have been compared with the results of a model combining non-adaptive WMM and pulse coupled neural networks. The presented approach overcomes the non-adaptive WMM filter setting parameters by developing an adaptive WMM model which is a step ahead towards a full automatic dark spot detection. The proposed approach was tested on 60 ENVISAT and ERS2 images which contained dark spots. For the overall dataset, an average accuracy of 94.65% was obtained. Our experimental results demonstrate that the proposed approach is very robust and effective where the non-adaptive WMM & pulse coupled neural network (PCNN) model generates poor accuracies. PMID:25474376

Retrieval of radiative and microphysical properties of clouds from multispectral infrared measurements

NASA Astrophysics Data System (ADS)

Iwabuchi, Hironobu; Saito, Masanori; Tokoro, Yuka; Putri, Nurfiena Sagita; Sekiguchi, Miho

2016-12-01

Satellite remote sensing of the macroscopic, microphysical, and optical properties of clouds are useful for studying spatial and temporal variations of clouds at various scales and constraining cloud physical processes in climate and weather prediction models. Instead of using separate independent algorithms for different cloud properties, a unified, optimal estimation-based cloud retrieval algorithm is developed and applied to moderate resolution imaging spectroradiometer (MODIS) observations using ten thermal infrared bands. The model considers sensor configurations, background surface and atmospheric profile, and microphysical and optical models of ice and liquid cloud particles and radiative transfer in a plane-parallel, multilayered atmosphere. Measurement and model errors are thoroughly quantified from direct comparisons of clear-sky observations over the ocean with model calculations. Performance tests by retrieval simulations show that ice cloud properties are retrieved with high accuracy when cloud optical thickness (COT) is between 0.1 and 10. Cloud-top pressure is inferred with uncertainty lower than 10 % when COT is larger than 0.3. Applying the method to a tropical cloud system and comparing the results with the MODIS Collection 6 cloud product shows good agreement for ice cloud optical thickness when COT is less than about 5. Cloud-top height agrees well with estimates obtained by the CO2 slicing method used in the MODIS product. The present algorithm can detect optically thin parts at the edges of high clouds well in comparison with the MODIS product, in which these parts are recognized as low clouds by the infrared window method. The cloud thermodynamic phase in the present algorithm is constrained by cloud-top temperature, which tends not to produce results with an ice cloud that is too warm and liquid cloud that is too cold.

Users' instructions for the NASA/MSFC cloud-rise preprocessor program, version 6, and the NASA/MSFC multilayer diffusion program, version 6: Research version for Univac 1108 system

NASA Technical Reports Server (NTRS)

Bjorklund, J. R.

1978-01-01

The cloud-rise preprocessor and multilayer diffusion computer programs were used by NASA in predicting concentrations and dosages downwind from normal and abnormal launches of rocket vehicles. These programs incorporated: (1) the latest data for the heat content and chemistry of rocket exhaust clouds; (2) provision for the automated calculation of surface water pH due to deposition of HCl from precipitation scavenging; (3) provision for automated calculation of concentration and dosage parameters at any level within the vertical grounds for which meteorological inputs have been specified; and (4) provision for execution of multiple cases of meteorological data. Procedures used to automatically calculate wind direction shear in a layer were updated.

Comparison of Cloud Properties from CALIPSO-CloudSat and Geostationary Satellite Data

NASA Technical Reports Server (NTRS)

Nguyen, L.; Minnis, P.; Chang, F.; Winker, D.; Sun-Mack, S.; Spangenberg, D.; Austin, R.

2007-01-01

Cloud properties are being derived in near-real time from geostationary satellite imager data for a variety of weather and climate applications and research. Assessment of the uncertainties in each of the derived cloud parameters is essential for confident use of the products. Determination of cloud amount, cloud top height, and cloud layering is especially important for using these real -time products for applications such as aircraft icing condition diagnosis and numerical weather prediction model assimilation. Furthermore, the distribution of clouds as a function of altitude has become a central component of efforts to evaluate climate model cloud simulations. Validation of those parameters has been difficult except over limited areas where ground-based active sensors, such as cloud radars or lidars, have been available on a regular basis. Retrievals of cloud properties are sensitive to the surface background, time of day, and the clouds themselves. Thus, it is essential to assess the geostationary satellite retrievals over a variety of locations. The availability of cloud radar data from CloudSat and lidar data from CALIPSO make it possible to perform those assessments over each geostationary domain at 0130 and 1330 LT. In this paper, CloudSat and CALIPSO data are matched with contemporaneous Geostationary Operational Environmental Satellite (GOES), Multi-functional Transport Satellite (MTSAT), and Meteosat-8 data. Unlike comparisons with cloud products derived from A-Train imagers, this study considers comparisons of nadir active sensor data with off-nadir retrievals. These matched data are used to determine the uncertainties in cloud-top heights and cloud amounts derived from the geostationary satellite data using the Clouds and the Earth s Radiant Energy System (CERES) cloud retrieval algorithms. The CERES multi-layer cloud detection method is also evaluated to determine its accuracy and limitations in the off-nadir mode. The results will be useful for constraining the use of the passive retrieval data in models and for improving the accuracy of the retrievals.

A comparison between CloudSat and aircraft data for a multilayer, mixed phase cloud system during the Canadian CloudSat-CALIPSO Validation Project

NASA Astrophysics Data System (ADS)

Barker, H. W.; Korolev, A. V.; Hudak, D. R.; Strapp, J. W.; Strawbridge, K. B.; Wolde, M.

2008-04-01

Reflectivities recorded by the W-band Cloud Profiling Radar (CPR) aboard NASA's CloudSat satellite and some of CloudSat's retrieval products are compared to Ka-band radar reflectivities and in situ cloud properties gathered by instrumentation on the NRC's Convair-580 aircraft. On 20 February 2007, the Convair flew several transects along a 60 nautical mile stretch of CloudSat's afternoon ground track over southern Quebec. On one of the transects it was well within CloudSat's radar's footprint while in situ sampling a mixed phase boundary layer cloud. A cirrus cloud was also sampled before and after overpass. Air temperature and humidity profiles from ECMWF reanalyses, as employed in CloudSat's retrieval stream, agree very well with those measured by the Convair. The boundary layer cloud was clearly visible, to the eye and lidar, and dominated the region's solar radiation budget. It was, however, often below or near the Ka-band's distance-dependent minimum detectable signal. In situ samples at overpass revealed it to be composed primarily of small, supercooled droplets at the south end and increasingly intermixed with ice northward. Convair and CloudSat CPR reflectivities for the low cloud agree well, but while CloudSat properly ascribed it as overcast, mixed phase, and mostly liquid near the south end, its estimates of liquid water content LWC (and visible extinction coefficient κ) and droplet effective radii are too small and large, respectively. The cirrus consisted largely of irregular crystals with typical effective radii ˜150 μm. While both CPR reflectivities agree nicely, CloudSat's estimates of crystal number concentrations are too large by a factor of 5. Nevertheless, distributions of ice water content and κ deduced from in situ data agree quite well with values retrieved from CloudSat algorithms.

Application of the SRI cloud-tracking technique to rapid-scan GOES observations

NASA Technical Reports Server (NTRS)

Wolf, D. E.; Endlich, R. M.

1980-01-01

An automatic cloud tracking system was applied to multilayer clouds associated with severe storms. The method was tested using rapid scan observations of Hurricane Eloise obtained by the GOES satellite on 22 September 1975. Cloud tracking was performed using clustering based either on visible or infrared data. The clusters were tracked using two different techniques. The data of 4 km and 8 km resolution of the automatic system yielded comparable in accuracy and coverage to those obtained by NASA analysts using the Atmospheric and Oceanographic Information Processing System.

Virtual Sensors: Using Data Mining to Efficiently Estimate Spectra

NASA Technical Reports Server (NTRS)

Srivastava, Ashok; Oza, Nikunj; Stroeve, Julienne

2004-01-01

Detecting clouds within a satellite image is essential for retrieving surface geophysical parameters, such as albedo and temperature, from optical and thermal imagery because the retrieval methods tend to be valid for clear skies only. Thus, routine satellite data processing requires reliable automated cloud detection algorithms that are applicable to many surface types. Unfortunately, cloud detection over snow and ice is difficult due to the lack of spectral contrast between clouds and snow. Snow and clouds are both highly reflective in the visible wavelen,ats and often show little contrast in the thermal Infrared. However, at 1.6 microns, the spectral signatures of snow and clouds differ enough to allow improved snow/ice/cloud discrimination. The recent Terra and Aqua Moderate Resolution Imaging Spectro-Radiometer (MODIS) sensors have a channel (channel 6) at 1.6 microns. Presently the most comprehensive, long-term information on surface albedo and temperature over snow- and ice-covered surfaces comes from the Advanced Very High Resolution Radiometer ( AVHRR) sensor that has been providing imagery since July 1981. The earlier AVHRR sensors (e.g. AVHRR/2) did not however have a channel designed for discriminating clouds from snow, such as the 1.6 micron channel available on the more recent AVHRR/3 or the MODIS sensors. In the absence of the 1.6 micron channel, the AVHRR Polar Pathfinder (APP) product performs cloud detection using a combination of time-series analysis and multispectral threshold tests based on the satellite's measuring channels to produce a cloud mask. The method has been found to work reasonably well over sea ice, but not so well over the ice sheets. Thus, improving the cloud mask in the APP dataset would be extremely helpful toward increasing the accuracy of the albedo and temperature retrievals, as well as extending the time-series of albedo and temperature retrievals from the more recent sensors to the historical ones. In this work, we use data mining methods to construct a model of MODIS channel 6 as a function of other channels that are common to both MODIS and AVHRR. The idea is to use the model to generate the equivalent of MODIS channel 6 for AVHRR as a function of the AVHRR equivalents to MODIS channels. We call this a Virtual Sensor because it predicts unmeasured spectra. The goal is to use this virtual channel 6. to yield a cloud mask superior to what is currently used in APP . Our results show that several data mining methods such as multilayer perceptrons (MLPs), ensemble methods (e.g., bagging), and kernel methods (e.g., support vector machines) generate channel 6 for unseen MODIS images with high accuracy. Because the true channel 6 is not available for AVHRR images, we qualitatively assess the virtual channel 6 for several AVHRR images.

An Integrated Cloud-Aerosol-Radiation Product Using CERES, MODIS, CALIPSO and CloudSat Data

NASA Astrophysics Data System (ADS)

Sun-Mack, S.; Gibson, S.; Chen, Y.; Wielicki, B.; Minnis, P.

2006-12-01

The goal of this paper is to provide the first integrated data set of global vertical profiles of aerosols, clouds, and radiation using the combined NASA A-Train data from Aqua CERES and MODIS, CALIPSO, and CloudSat. All of these instruments are flying in formation as part of the Aqua Train, or A-Train. This paper will present the preliminary results of merging aerosol and cloud data from the CALIPSO active lidar, cloud data from CloudSat, integrated column aerosol and cloud data from the MODIS CERES analyses, and surface and top-of-atmosphere broadband radiation fluxes from CERES. These new data will provide unprecedented ability to test and improve global cloud and aerosol models, to investigate aerosol direct and indirect radiative forcing, and to validate the accuracy of global aerosol, cloud, and radiation data sets especially in polar regions and for multi-layered cloud conditions.

Validation of POLDER/ADEOS data using a ground-based lidar network: Preliminary results for semi-transparent and cirrus clouds

NASA Technical Reports Server (NTRS)

Chepfer, H.; Sauvage, L.; Flamant, P. H.; Pelon, J.; Goloub, P.; Brogniez, G.; spinhirne, J.; Lavorato, M.; Sugimoto, N.

1998-01-01

At mid and tropical latitudes, cirrus clouds are present more than 50% of the time in satellites observations. Due to their large spatial and temporal coverage, and associated low temperatures, cirrus clouds have a major influence on the Earth-Ocean-Atmosphere energy balance through their effects on the incoming solar radiation and outgoing infrared radiation. At present the impact of cirrus clouds on climate is well recognized but remains to be asserted more precisely, for their optical and radiative properties are not very well known. In order to understand the effects of cirrus clouds on climate, their optical and radiative characteristics of these clouds need to be determined accurately at different scales in different locations i.e. latitude. Lidars are well suited to observe cirrus clouds, they can detect very thin and semi-transparent layers, and retrieve the clouds geometrical properties i.e. altitude and multilayers, as well as radiative properties i.e. optical depth, backscattering phase functions of ice crystals. Moreover the linear depolarization ratio can give information on the ice crystal shape. In addition, the data collected with an airborne version of POLDER (POLarization and Directionality of Earth Reflectances) instrument have shown that bidirectional polarized measurements can provide information on cirrus cloud microphysical properties (crystal shapes, preferred orientation in space). The spaceborne version of POLDER-1 has been flown on ADEOS-1 platform during 8 months (October 96 - June 97), and the next POLDER-2 instrument will be launched in 2000 on ADEOS-2. The POLDER-1 cloud inversion algorithms are currently under validation. For cirrus clouds, a validation based on comparisons between cloud properties retrieved from POLDER-1 data and cloud properties inferred from a ground-based lidar network is currently under consideration. We present the first results of the validation.

Parameterization of cloud lidar backscattering profiles by means of asymmetrical Gaussians

NASA Astrophysics Data System (ADS)

del Guasta, Massimo; Morandi, Marco; Stefanutti, Leopoldo

1995-06-01

A fitting procedure for cloud lidar data processing is shown that is based on the computation of the first three moments of the vertical-backscattering (or -extinction) profile. Single-peak clouds or single cloud layers are approximated to asymmetrical Gaussians. The algorithm is particularly stable with respect to noise and processing errors, and it is much faster than the equivalent least-squares approach. Multilayer clouds can easily be treated as a sum of single asymmetrical Gaussian peaks. The method is suitable for cloud-shape parametrization in noisy lidar signatures (like those expected from satellite lidars). It also permits an improvement of cloud radiative-property computations that are based on huge lidar data sets for which storage and careful examination of single lidar profiles can't be carried out.

A New Methodology for Simultaneous Multi-layer Retrievals of Ice and Liquid Water Cloud Properties

NASA Astrophysics Data System (ADS)

Sourdeval, O.; Labonnote, L.; Baran, A. J.; Brogniez, G.

2014-12-01

It is widely recognized that the study of clouds has nowadays become one of the major concern of the climate research community. Consequently, a multitude of retrieval methodologies have been developed during the last decades in order to obtain accurate retrievals of cloud properties that can be supplied to climate models. Most of the current methodologies have proven to be satisfactory for separately retrieving ice or liquid cloud properties, but very few of them have attempted simultaneous retrievals of these two cloud types. Recent studies nevertheless show that the omission of one of these layers can have strong consequences on the retrievals and their accuracy. In this study, a new methodology that simultaneously retrieves the properties of ice and liquid clouds is presented. The optical thickness and the effective radius of up to two liquid cloud layers and the ice water path of one ice cloud layer are simultaneously retrieved, along with an accurate estimation of their uncertainties. Radiometric measurements ranging from the visible to the thermal infrared are used for performing the retrievals. In order to quantify the capabilities and limitations of our methodology, the results of a theoretical information content analysis are first presented. This analysis allows obtaining an a priori understanding of how much information should be expected on each of the retrieval parameters in different atmospheric conditions, and which set of channels is likely to provide this information. After such theoretical considerations, global retrievals corresponding to several months of A-Train data are presented. Comparisons of our retrievals with operational products from active and passive instruments are effectuated and show good global agreements. These comparisons are useful for validating our retrievals but also for testing how operational products can be influenced by multi-layer configurations.

Global Distribution and Vertical Structure of Clouds Revealed by CALIPSO

NASA Astrophysics Data System (ADS)

Yi, Y.; Minnis, P.; Winker, D.; Huang, J.; Sun-Mack, S.; Ayers, K.

2007-12-01

Understanding the effects of clouds on Earth's radiation balance, especially on longwave fluxes within the atmosphere, depends on having accurate knowledge of cloud vertical location within the atmosphere. The Cloud- Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite mission provides the opportunity to measure the vertical distribution of clouds at a greater detail than ever before possible. The CALIPSO cloud layer products from June 2006 to June 2007 are analyzed to determine the occurrence frequency and thickness of clouds as functions of time, latitude, and altitude. In particular, the latitude-longitude and vertical distributions of single- and multi-layer clouds and the latitudinal movement of cloud cover with the changing seasons are examined. The seasonal variablities of cloud frequency and geometric thickness are also analyzed and compared with similar quantities derived from the Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) using the Clouds and the Earth's Radiant Energy System (CERES) cloud retrieval algorithms. The comparisons provide an estimate of the errors in cloud fraction, top height, and thickness incurred by passive algorithms.

Radiative transfer in shallow cumulus cloud fields: Observations and first analysis with the Diram instrument during the BBC-2 field campaign in May 2003

NASA Astrophysics Data System (ADS)

van Dop, Han; Wilson, Keith M.

2006-11-01

The cloud albedo is a crucial parameter in radiation budget studies, and is one of the main forcings in climate. We have designed and made a device, Diram (directional radiance distribution measurement device), which not only measures reflection and transmission of solar radiation through clouds, but which also determines the radiance distribution. The construction contains 42 sensors, consisting of a collimation system and a detector, which are mounted in two domes (21 in each). The collimators reduce the field of view of each sensor to ˜7°. The domes were mounted on top and below of the Meteo France Merlin IV research aircraft. The 42 signals were continuously logged with a frequency of 10 Hz during a number of flights in the framework of the Baltex Bridge-2 campaign at Cabauw (The Netherlands) in May 2003. The Diram instrument provided radiances during in situ observations of cumulus and (broken) stratocumulus clouds and detected anisotropic effects in solar radiation scattered by clouds which are due to different cloud geometries and which are related to microphysical cloud properties. Microphysical cloud properties were obtained from the Gerber PVM100A optical sensor aboard the aircraft. Liquid water content and particle surface area were logged with a frequency of 200 Hz. Data have been collected from a total of 10 days in different weather conditions (clear sky, broken cumulus, stratocumulus and multilayered cloud). A clear sky test of the Diram indicated that the device was able to reproduce the Rayleigh scattering pattern. During flights in stratocumulus fields, strongly anisotropic patterns were observed. The DIRAM observations confirm that in thin clouds a strong preference for forward scattering is observed in the transmitted radiation field while for thicker clouds the pattern becomes more isotropic, with a slightly brighter centre relative to the limb direction.

Ice Cloud Properties in Ice-Over-Water Cloud Systems Using TRMM VIRS and TMI Data

NASA Technical Reports Server (NTRS)

Minnis, Patrick; Huang, Jianping; Lin, Bing; Yi, Yuhong; Arduini, Robert F.; Fan, Tai-Fang; Ayers, J. Kirk; Mace, Gerald G.

2007-01-01

A multi-layered cloud retrieval system (MCRS) is updated and used to estimate ice water path in maritime ice-over-water clouds using Visible and Infrared Scanner (VIRS) and TRMM Microwave Imager (TMI) measurements from the Tropical Rainfall Measuring Mission spacecraft between January and August 1998. Lookup tables of top-of-atmosphere 0.65- m reflectance are developed for ice-over-water cloud systems using radiative transfer calculations with various combinations of ice-over-water cloud layers. The liquid and ice water paths, LWP and IWP, respectively, are determined with the MCRS using these lookup tables with a combination of microwave (MW), visible (VIS), and infrared (IR) data. LWP, determined directly from the TMI MW data, is used to define the lower-level cloud properties to select the proper lookup table. The properties of the upper-level ice clouds, such as optical depth and effective size, are then derived using the Visible Infrared Solar-infrared Split-window Technique (VISST), which matches the VIRS IR, 3.9- m, and VIS data to the multilayer-cloud lookup table reflectances and a set of emittance parameterizations. Initial comparisons with surface-based radar retrievals suggest that this enhanced MCRS can significantly improve the accuracy and decrease the IWP in overlapped clouds by 42% and 13% compared to using the single-layer VISST and an earlier simplified MW-VIS-IR (MVI) differencing method, respectively, for ice-over-water cloud systems. The tropical distribution of ice-over-water clouds is the same as derived earlier from combined TMI and VIRS data, but the new values of IWP and optical depth are slightly larger than the older MVI values, and exceed those of single-layered layered clouds by 7% and 11%, respectively. The mean IWP from the MCRS is 8-14% greater than that retrieved from radar retrievals of overlapped clouds over two surface sites and the standard deviations of the differences are similar to those for single-layered clouds. Examples of a method for applying the MCRS over land without microwave data yield similar differences with the surface retrievals. By combining the MCRS with other techniques that focus primarily on optically thin cirrus over low water clouds, it will be possible to more fully assess the IWP in all conditions over ocean except for precipitating systems.

SGP and TWP (Manus) Ice Cloud Vertical Velocities

DOE Data Explorer

Kalesse, Heike

2013-06-27

Daily netcdf-files of ice-cloud dynamics observed at the ARM sites at SGP (Jan1997-Dec2010) and Manus (Jul1999-Dec2010). The files include variables at different time resolution (10s, 20min, 1hr). Profiles of radar reflectivity factor (dbz), Doppler velocity (vel) as well as retrieved vertical air motion (V_air) and reflectivity-weighted particle terminal fall velocity (V_ter) are given at 10s, 20min and 1hr resolution. Retrieved V_air and V_ter follow radar notation, so positive values indicate downward motion. Lower level clouds are removed, however a multi-layer flag is included.

Geometric and optical properties of cirrus clouds inferred from three-year ground-based lidar and CALIOP measurements over Seoul, Korea

NASA Astrophysics Data System (ADS)

Kim, Yumi; Kim, Sang-Woo; Kim, Man-Hae; Yoon, Soon-Chang

2014-03-01

This study examines cirrus cloud top and bottom heights (CTH and CBH, respectively) and the associated optical properties revealed by ground-based lidar in Seoul (SNU-L), Korea, and space-borne Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), which were obtained during a three-year measurement period between July 2006 and June 2009. From two selected cases, we determined good agreement in CTH and CBH with cirrus cloud optical depth (COD) between ground-based lidar and space-borne CALIOP. In particular, CODs at a wavelength of 532 nm calculated from the three years of SNU-L and CALIOP measurements were 0.417 ± 0.394 and 0.425 ± 0.479, respectively. The fraction of COD lower than 0.1 was approximately 17% and 25% of the total SNU-L and CALIOP profiles, respectively, and approximately 50% of both lidar profiles were classified as sub-visual or optically thin such that COD was < 0.3. The mean depolarization ratio was estimated to be 0.30 ± 0.06 for SNU-L and 0.34 ± 0.08 for CALIOP. The monthly variation of CODs from SNU-L and CALIOP measurements was not distinct, whereas cirrus altitudes from both SNU-L and CALIOP showed distinct monthly variation. CALIOP observations showed that cirrus clouds reached the tropopause level in all months, whereas the up-looking SNU-L did not detect cirrus clouds near the tropopause in summer due to signal attenuation by underlying optically thick clouds. The cloud layer thickness (CLT) and COD showed a distinct linear relationship up to approximately 2 km of the CLT; however, the COD did not increase, but remained constant when the CLT was greater than 2.0 km. The ice crystal content, lidar signal attenuation, and the presence of multi-layered cirrus clouds may have contributed to this tendency.

Integrated Cloud-Aerosol-Radiation Product using CERES, MODIS, CALIPSO and CloudSat Data

NASA Technical Reports Server (NTRS)

Sun-Mack, Sunny; Minnis, Patrick; Chen, Yan; Gibson, Sharon; Yi, Yuhong; Trepte, Qing; Wielicki, Bruce; Kato, Seiji; Winker, Dave

2007-01-01

This paper documents the development of the first integrated data set of global vertical profiles of clouds, aerosols, and radiation using the combined NASA A-Train data from the Aqua Clouds and Earth's Radiant Energy System (CERES) and Moderate Resolution Imaging Spectroradiometer (MODIS), Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), and CloudSat. As part of this effort, cloud data from the CALIPSO lidar and the CloudSat radar are merged with the integrated column cloud properties from the CERES-MODIS analyses. The active and passive datasets are compared to determine commonalities and differences in order to facilitate the development of a 3- dimensional cloud and aerosol dataset that will then be integrated into the CERES broadband radiance footprint. Preliminary results from the comparisons for April 2007 reveal that the CERES-MODIS global cloud amounts are, on average, 0.14 less and 0.15 greater than those from CALIPSO and CloudSat, respectively. These new data will provide unprecedented ability to test and improve global cloud and aerosol models, to investigate aerosol direct and indirect radiative forcing, and to validate the accuracy of global aerosol, cloud, and radiation data sets especially in polar regions and for multi-layered cloud conditions.

Integrated cloud-aerosol-radiation product using CERES, MODIS, CALIPSO, and CloudSat data

NASA Astrophysics Data System (ADS)

Sun-Mack, Sunny; Minnis, Patrick; Chen, Yan; Gibson, Sharon; Yi, Yuhong; Trepte, Qing; Wielicki, Bruce; Kato, Seiji; Winker, Dave; Stephens, Graeme; Partain, Philip

2007-10-01

This paper documents the development of the first integrated data set of global vertical profiles of clouds, aerosols, and radiation using the combined NASA A-Train data from the Aqua Clouds and Earth's Radiant Energy System (CERES) and Moderate Resolution Imaging Spectroradiometer (MODIS), Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO), and CloudSat. As part of this effort, cloud data from the CALIPSO lidar and the CloudSat radar are merged with the integrated column cloud properties from the CERES-MODIS analyses. The active and passive datasets are compared to determine commonalities and differences in order to facilitate the development of a 3-dimensional cloud and aerosol dataset that will then be integrated into the CERES broadband radiance footprint. Preliminary results from the comparisons for April 2007 reveal that the CERES-MODIS global cloud amounts are, on average, 0.14 less and 0.15 greater than those from CALIPSO and CloudSat, respectively. These new data will provide unprecedented ability to test and improve global cloud and aerosol models, to investigate aerosol direct and indirect radiative forcing, and to validate the accuracy of global aerosol, cloud, and radiation data sets especially in polar regions and for multi-layered cloud conditions.

Determination of ice water path in ice-over-water cloud systems using combined MODIS and AMSR-E measurements

NASA Astrophysics Data System (ADS)

Huang, Jianping; Minnis, Patrick; Lin, Bing; Yi, Yuhong; Fan, T.-F.; Sun-Mack, Sunny; Ayers, J. K.

2006-11-01

To provide more accurate ice cloud microphysical properties, the multi-layered cloud retrieval system (MCRS) is used to retrieve ice water path (IWP) in ice-over-water cloud systems globally over oceans using combined instrument data from Aqua. The liquid water path (LWP) of lower-layer water clouds is estimated from the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) measurements. The properties of the upper-level ice clouds are then derived from Moderate Resolution Imaging Spectroradiometer (MODIS) measurements by matching simulated radiances from a two-cloud-layer radiative transfer model. The results show that the MCRS can significantly improve the accuracy and reduce the over-estimation of optical depth and IWP retrievals for ice-over-water cloud systems. The mean daytime ice cloud optical depth and IWP for overlapped ice-over-water clouds over oceans from Aqua are 7.6 and 146.4 gm-2, respectively, down from the initial single-layer retrievals of 17.3 and 322.3 gm-2. The mean IWP for actual single-layer clouds is 128.2 gm-2.

Application of a Gaussian multilayer diffusion model to characterize dispersion of vertical HCl column density in rocket exhaust clouds

NASA Technical Reports Server (NTRS)

Pellett, G. L.; Staton, W. L.

1981-01-01

Solid rocket exhaust cloud dispersion cases, based on seven meteorological regimes for overland advection in the Cape Canaveral, Florida, area, are examined for launch vehicle environmental impacts. They include a space shuttle case and all seven meteorological cases for the Titan 3, which exhausts 60% less HC1. The C(HC1) decays are also compared with recent in cloud peak HC1 data from eight Titan 3 launches. It is stipulated that while good overall agreement provides validation of the model, its limitations are considerable and a dynamics model is needed to handle local convective situations.

Cloud Retrieval Intercomparisons Between SEVIRI, MODIS and VIIRS with CHIMAERA PGE06 Data Collection 6 Products

NASA Technical Reports Server (NTRS)

Wind, Galina; Riedi, Jerome; Platnick, Steven; Heidinger, Andrew

2014-01-01

The Cross-platform HIgh resolution Multi-instrument AtmosphEric Retrieval Algorithms (CHIMAERA) system allows us to perform MODIS-like cloud top, optical and microphysical properties retrievals on any sensor that possesses a minimum set of common spectral channels. The CHIMAERA system uses a shared-core architecture that takes retrieval method out of the equation when intercomparisons are made. Here we show an example of such retrieval and a comparison of simultaneous retrievals done using SEVIRI, MODIS and VIIRS sensors. All sensor retrievals are performed using CLAVR-x (or CLAVR-x based) cloud top properties algorithm. SEVIRI uses the SAF_NWC cloud mask. MODIS and VIIRS use the IFF-based cloud mask that is a shared algorithm between MODIS and VIIRS. The MODIS and VIIRS retrievals are performed using a VIIRS branch of CHIMAERA that limits available MODIS channel set. Even though in that mode certain MODIS products such as multilayer cloud map are not available, the cloud retrieval remains fully equivalent to operational Data Collection 6.

Rocket exhaust ground cloud/atmospheric interactions

NASA Technical Reports Server (NTRS)

Hwang, B.; Gould, R. K.

1978-01-01

An attempt to identify and minimize the uncertainties and potential inaccuracies of the NASA Multilayer Diffusion Model (MDM) is performed using data from selected Titan 3 launches. The study is based on detailed parametric calculations using the MDM code and a comparative study of several other diffusion models, the NASA measurements, and the MDM. The results are discussed and evaluated. In addition, the physical/chemical processes taking place during the rocket cloud rise are analyzed. The exhaust properties and the deluge water effects are evaluated. A time-dependent model for two aerosol coagulations is developed and documented. Calculations using this model for dry deposition during cloud rise are made. A simple model for calculating physical properties such as temperature and air mass entrainment during cloud rise is also developed and incorporated with the aerosol model.

Parametric studies with an atmospheric diffusion model that assesses toxic fuel hazards due to the ground clouds generated by rocket launches

NASA Technical Reports Server (NTRS)

Stewart, R. B.; Grose, W. L.

1975-01-01

Parametric studies were made with a multilayer atmospheric diffusion model to place quantitative limits on the uncertainty of predicting ground-level toxic rocket-fuel concentrations. Exhaust distributions in the ground cloud, cloud stabilized geometry, atmospheric coefficients, the effects of exhaust plume afterburning of carbon monoxide CO, assumed surface mixing-layer division in the model, and model sensitivity to different meteorological regimes were studied. Large-scale differences in ground-level predictions are quantitatively described. Cloud alongwind growth for several meteorological conditions is shown to be in error because of incorrect application of previous diffusion theory. In addition, rocket-plume calculations indicate that almost all of the rocket-motor carbon monoxide is afterburned to carbon dioxide CO2, thus reducing toxic hazards due to CO. The afterburning is also shown to have a significant effect on cloud stabilization height and on ground-level concentrations of exhaust products.

Graphene-based electrochemical sensor for detection of 2,4,6-trinitrotoluene (TNT) in seawater: the comparison of single-, few-, and multilayer graphene nanoribbons and graphite microparticles.

PubMed

Goh, Madeline Shuhua; Pumera, Martin

2011-01-01

The detection of explosives in seawater is of great interest. We compared response single-, few-, and multilayer graphene nanoribbons and graphite microparticle-based electrodes toward the electrochemical reduction of 2,4,6-trinitrotoluene (TNT). We optimized parameters such as accumulation time, accumulation potential, and pH. We found that few-layer graphene exhibits about 20% enhanced signal for TNT after accumulation when compared to multilayer graphene nanoribbons. However, graphite microparticle-modified electrode provides higher sensitivity, and there was no significant difference in the performance of single-, few-, and multilayer graphene nanoribbons and graphite microparticles for the electrochemical detection of TNT. We established the limit of detection of TNT in untreated seawater at 1 μg/mL.

Study of atmospheric parameters measurements using MM-wave radar in synergy with LITE-2

NASA Technical Reports Server (NTRS)

Andrawis, Madeleine Y.

1994-01-01

The Lidar In-Space Technology Experiment, (LITE), has been developed, designed, and built by NASA Langley Research Center, to be flown on the space shuttle 'Discovery' on September 9, 1994. Lidar, which stands for light detecting and ranging, is a radar system that uses short pulses of laser light instead of radio waves in the case of the common radar. This space-based lidar offers atmospheric measurements of stratospheric and tropospheric aerosols, the planetary boundary layer, cloud top heights, and atmospheric temperature and density in the 10-40 km altitude range. A study is being done on the use, advantages, and limitations of a millimeterwave radar to be utilized in synergy with the Lidar system, for the LITE-2 experiment to be flown on a future space shuttle mission. The lower atmospheric attenuation, compared to infrared and optical frequencies, permits the millimeter-wave signals to penetrate through the clouds and measure multi-layered clouds, cloud thickness, and cloud-base height. These measurements would provide a useful input to radiation computations used in the operational numerical weather prediction models, and for forecasting. High power levels, optimum modulation, data processing, and high antenna gain are used to increase the operating range, while space environment, radar tradeoffs, and power availability are considered. Preliminary, numerical calculations are made, using the specifications of an experimental system constructed at Georgia Tech. The noncoherent 94 GHz millimeter-wave radar system has a pulsed output with peak value of 1 kW. The backscatter cross section of the particles to be measured, that are present in the volume covered by the beam footprint, is also studied.

Cloud Properties of CERES-MODIS Edition 4 and CERES-VIIRS Edition 1

NASA Technical Reports Server (NTRS)

Sun-Mack, Sunny; Minnis, Patrick; Chang, Fu-Lung; Hong, Gang; Arduini, Robert; Chen, Yan; Trepte, Qing; Yost, Chris; Smith, Rita; Brown, Ricky;

Satellite and Surface Data Synergy for Developing a 3D Cloud Structure and Properties Characterization Over the ARM SGP. Stage 1: Cloud Amounts, Optical Depths, and Cloud Heights Reconciliation

NASA Technical Reports Server (NTRS)

Genkova, I.; Long, C. N.; Heck, P. W.; Minnis, P.

2003-01-01

One of the primary Atmospheric Radiation Measurement (ARM) Program objectives is to obtain measurements applicable to the development of models for better understanding of radiative processes in the atmosphere. We address this goal by building a three-dimensional (3D) characterization of the cloud structure and properties over the ARM Southern Great Plains (SGP). We take the approach of juxtaposing the cloud properties as retrieved from independent satellite and ground-based retrievals, and looking at the statistics of the cloud field properties. Once these retrievals are well understood, they will be used to populate the 3D characterization database. As a first step we determine the relationship between surface fractional sky cover and satellite viewing angle dependent cloud fraction (CF). We elaborate on the agreement intercomparing optical depth (OD) datasets from satellite and ground using available retrieval algorithms with relation to the CF, cloud height, multi-layer cloud presence, and solar zenith angle (SZA). For the SGP Central Facility, where output from the active remote sensing cloud layer (ARSCL) valueadded product (VAP) is available, we study the uncertainty of satellite estimated cloud heights and evaluate the impact of this uncertainty for radiative studies.

Determination of Ice Water Path in Ice-over-Water Cloud Systems Using Combined MODIS and AMSR-E Measurements

NASA Technical Reports Server (NTRS)

Huang, Jianping; Minnis, Patrick; Lin, Bing; Yi, Yuhong; Fan, T.-F.; Sun-Mack, Sunny; Ayers, J. K.

2006-01-01

To provide more accurate ice cloud properties for evaluating climate models, the updated version of multi-layered cloud retrieval system (MCRS) is used to retrieve ice water path (IWP) in ice-over-water cloud systems over global ocean using combined instrument data from the Aqua satellite. The liquid water path (LWP) of lower layer water clouds is estimated from the Advanced Microwave Scanning Radiometer for EOS (AMSR-E) measurements. With the lower layer LWP known, the properties of the upper-level ice clouds are then derived from Moderate Resolution Imaging Spectroradiometer measurements by matching simulated radiances from a two-cloud layer radiative transfer model. Comparisons with single-layer cirrus systems and surface-based radar retrievals show that the MCRS can significantly improve the accuracy and reduce the over-estimation of optical depth and ice water path retrievals for ice over-water cloud systems. During the period from December 2004 through February 2005, the mean daytime ice cloud optical depth and IWP for overlapped ice-over-water clouds over ocean from Aqua are 7.6 and 146.4 gm(sup -2), respectively, significantly less than the initial single layer retrievals of 17.3 and 322.3 gm(sup -2). The mean IWP for actual single-layer clouds was 128.2 gm(sup -2).

A Study of the Vertical Structure of Tropical (20 deg S-20 deg N) Optically Thin Clouds from SAGE II Observations

NASA Technical Reports Server (NTRS)

Wang, Pi-Huan; Minnis, Patrick; McCormick, M. Patrick; Kent, Geoffrey S.; Yue, Glenn K.; Young, David F.; Skeens, Kristi M.

1998-01-01

The tropical cloud data obtained by the satellite instrument of the Stratospheric Aerosol and Gas Experiment (SAGE) II from October 1984 to May 1991 have been used to study cloud vertical distribution, including thickness and multilayer structure, and to estimate cloud optical depth. The results indicate that the SAGE-II-observed clouds are generally optically thin clouds, corresponding to a range of optical depth between approximately 8 x 10(exp -4) and 3 x 10(exp -1) with a mean of about 0.035. Two-thirds are classified as subvisual cirrus and one-third thin cirrus. Clouds between 2- to 3-km thick occur most frequently. Approximately 30% of the SAGE II cloud measurements are isolated single-layer clouds, while 65% are high clouds contiguous with an underlying opaque cloud that terminates the SAGE II profile. Thin clouds above detached opaque clouds at altitudes greater than 6.5 km occur less often. Only about 3% of the SAGE II single-layer clouds are located above the tropopause, while 58% of the cloud layers never reach the tropopause. More than one-third of the clouds appear at the tropopause. This study also shows that clouds occur more frequently and extend higher above the tropopause over the western Pacific than than over the eastern Pacific, especially during northern winter. The uncertainty of the derived results due to the SAGE II sampling constraints, data processing, and cloud characteristics is discussed.

THz Pulse Detection by Multilayered GeTe/Sb2Te3.

PubMed

Makino, Kotaro; Kuromiya, Shota; Takano, Keisuke; Kato, Kosaku; Nakajima, Makoto; Saito, Yuta; Tominaga, Junji; Iida, Hitoshi; Kinoshita, Moto; Nakano, Takashi

2016-11-30

We proposed and demonstrated terahertz (THz) pulse detection by means of multilayered GeTe/Sb 2 Te 3 phase-change memory materials that are also known as a multilayer topological insulator-normal insulator (MTN) system. THz time-domain spectroscopy measurement was performed for MTN films with different multilayer repetitions as well as a conventional as-grown Ge-Te-Sb (GST) alloy film. It was found that MTNs absorb THz waves and that the absorption coefficient depends on the number of layers, while the as-grown GST alloy film was almost transparent for THz waves. Simple MTN-based THz detection devices were fabricated, and the THz-induced change in the current signal was measured when a DC bias voltage was applied between the electrodes. We confirmed that irradiation of THz pulse causes a decrease in the resistance of the MTNs. This result indicates that our devices are capable of THz detection.

OMMYDCLD: a New A-train Cloud Product that Co-locates OMI and MODIS Cloud and Radiance Parameters onto the OMI Footprint

NASA Technical Reports Server (NTRS)

Fisher, Brad; Joiner, Joanna; Vasilkov, Alexander; Veefkind, Pepijn; Platnick, Steven; Wind, Galina

2014-01-01

Clouds cover approximately 60% of the earth's surface. When obscuring the satellite's field of view (FOV), clouds complicate the retrieval of ozone, trace gases and aerosols from data collected by earth observing satellites. Cloud properties associated with optical thickness, cloud pressure, water phase, drop size distribution (DSD), cloud fraction, vertical and areal extent can also change significantly over short spatio-temporal scales. The radiative transfer models used to retrieve column estimates of atmospheric constituents typically do not account for all these properties and their variations. The OMI science team is preparing to release a new data product, OMMYDCLD, which combines the cloud information from sensors on board two earth observing satellites in the NASA A-Train: Aura/OMI and Aqua/MODIS. OMMYDCLD co-locates high resolution cloud and radiance information from MODIS onto the much larger OMI pixel and combines it with parameters derived from the two other OMI cloud products: OMCLDRR and OMCLDO2. The product includes histograms for MODIS scientific data sets (SDS) provided at 1 km resolution. The statistics of key data fields - such as effective particle radius, cloud optical thickness and cloud water path - are further separated into liquid and ice categories using the optical and IR phase information. OMMYDCLD offers users of OMI data cloud information that will be useful for carrying out OMI calibration work, multi-year studies of cloud vertical structure and in the identification and classification of multi-layer clouds.

Cirrus cloud spectra and layers observed during the FIRE and GASP projects

NASA Technical Reports Server (NTRS)

Flatau, Piotr J.; Gultepe, I.; Nastrom, G.; Cotton, William R.; Heymsfield, A. J.

1990-01-01

A general characterization is developed for cirrus clouds in terms of their spectra, shapes, optical thicknesses, and radiative properties for use in numerical models. Data sets from the Global Atmospheric Sampling Project (GASP) of the upper troposphere and the First ISCCP Regional Experiment (FIRE) are combined and analyzed to study general traits of cirrus clouds. A definition is given for 2D turbulence, and the GASP and FIRE data sets are examined with respect to cirrus layers and entrainment and to dominant turbulent scales. The approach employs conditional sampling in cloudy and clear air, power-spectral analysis, and mixing-line-type diagrams. Evidence is given for a well mixed cloud deck and for the tendency of cirrus to be formed in multilayer structures. The results are of use in mesoscale and global circulation models which predict cirrus, in small-scale cirrus modeling, and in studying the role of gravity waves in the horizontal structure of upper tropospheric clouds.

Designing multilayered nanoplatforms for SERS-based detection of genetically modified organisms

NASA Astrophysics Data System (ADS)

Uluok, Saadet; Guven, Burcu; Eksi, Haslet; Ustundag, Zafer; Tamer, Ugur; Boyaci, Ismail Hakki

2015-01-01

In this study, the multilayered surface-enhanced Raman spectroscopy (SERS) platforms were developed for the analysis of genetically modified organisms (GMOs). For this purpose, two molecules [11-mercaptoundecanoic acid (11-MUA) and 2-mercaptoethylamine (2-MEA)] were attached with Aurod and Auspherical nanoparticles to form multilayered constructions on the gold (Au)slide surface. The best multilayered platform structure was chosen depending on SERS enhancement, and this surface was characterised with atomic force microscopy (AFM) and attenuated total reflectance Fourier transform infrared spectroscopy. After the optimum multilayered SERS platform and nanoparticle interaction was identified, the oligonucleotides on the Aurod nanoparticles and Auslide were combined to determine target concentrations from the 5,5'-dithiobis (2-nitrobenzoic acid) (DTNB) signals using SERS. The correlation between the SERS intensities for DTNB and target concentrations was found to be linear within a range of 10 pM to 1 µM, and with a detection limit of 34 fM. The selectivity and specificity of the developed sandwich assay were tested using negative and positive controls, and nonsense and real sample studies. The obtained results showed that the multilayered SERS sandwich method allows for sensitive, selective, and specific detection of oligonucleotide sequences.

Prediction of engine exhaust concentrations downwind from the Delta-Thor Telsat-A launch of 9 November 1972

NASA Technical Reports Server (NTRS)

Kaufman, J. W.; Susko, M.; Hill, C. K.

1973-01-01

Results are presented of the downwind concentrations of engine exhaust by-products from the Delta-Thor Telsat-A vehicle launched from Cape Kennedy, Florida on November 9, 1972 (2014 EST). The meteorological conditions which existed are identified as well as the exhaust cloud rise and the results from the MSFC Multilayer Diffusion Model calculations. These predictions are compared to exhaust cloud sampled data acquired by the Langley Research Center personnel. Values of the surface level concentrations show that very little hydrochloric acid, carbon monoxide, or aluminum oxide reached the ground.

A 19-Month Climatology of Marine Aerosol-Cloud-Radiation Properties Derived From DOE ARM AMF Deployment at the Azores: Part I: Cloud Fraction and Single-Layered MBL Cloud Properties

NASA Technical Reports Server (NTRS)

Dong, Xiquan; Xi, Baike; Kennedy, Aaron; Minnis, Patrick; Wood, Robert

2013-01-01

A 19-month record of total, and single-layered low (0-3 km), middle (3-6 km), and high (> 6 km) cloud fractions (CFs), and the single-layered marine boundary layer (MBL) cloud macrophysical and microphysical properties has been generated from ground-based measurements taken at the ARM Azores site between June 2009 and December 2010. It documents the most comprehensive and longest dataset on marine cloud fraction and MBL cloud properties to date. The annual means of total CF, and single-layered low, middle, and high CFs derived from ARM radar-lidar observations are 0.702, 0.271, 0.01 and 0.106, respectively. More total and single-layered high CFs occurred during winter, while single-layered low CFs were greatest during summer. The diurnal cycles for both total and low CFs are stronger during summer than during winter. The CFs are bimodally distributed in the vertical with a lower peak at approx. 1 km and higher one between 8 and 11 km during all seasons, except summer, when only the low peak occurs. The persistent high pressure and dry conditions produce more single-layered MBL clouds and fewer total clouds during summer, while the low pressure and moist air masses during winter generate more total and multilayered-clouds, and deep frontal clouds associated with midlatitude cyclones.

Surface plasmon aided high sensitive non-enzymatic glucose sensor using Au/NiAu multilayered nanowire arrays.

PubMed

Wang, Lanfang; Zhu, Weiqi; Lu, Wenbo; Qin, Xiufang; Xu, Xiaohong

2018-07-15

A novel plasmon aided non-enzymatic glucose sensor was first constructed based on the unique half-rough Au/NiAu multilayered nanowire arrays. These multilayered and half-rough nanowires provide high chemical activity and large surface area for glucose oxidation in an alkaline solution. Under visible light irradiation, the surface plasmons originated from Au part enhance the electron transfer in the vertically aligned nanowires, leading to high sensitivity and wide detection range. The resulting sensor exhibits a wide glucose detection concentration range, low detection limit, and high sensitivity for plasmon aided non-enzymatic glucose sensor. Moreover, the detection sensitivity is enhanced by almost 2 folds compared to that in the dark, which significantly enhanced the performance of Au/NiAu multilayered nanowire arrays sensor. An excellent selectivity and acceptable stability were also achieved. These results indicate that surface plasmon aided nanostructures are promising new platforms for the construction of non-enzymatic glucose sensors. Copyright © 2018 Elsevier B.V. All rights reserved.

A cloud shadow detection method combined with cloud height iteration and spectral analysis for Landsat 8 OLI data

NASA Astrophysics Data System (ADS)

Sun, Lin; Liu, Xinyan; Yang, Yikun; Chen, TingTing; Wang, Quan; Zhou, Xueying

2018-04-01

Although enhanced over prior Landsat instruments, Landsat 8 OLI can obtain very high cloud detection precisions, but for the detection of cloud shadows, it still faces great challenges. Geometry-based cloud shadow detection methods are considered the most effective and are being improved constantly. The Function of Mask (Fmask) cloud shadow detection method is one of the most representative geometry-based methods that has been used for cloud shadow detection with Landsat 8 OLI. However, the Fmask method estimates cloud height employing fixed temperature rates, which are highly uncertain, and errors of large area cloud shadow detection can be caused by errors in estimations of cloud height. This article improves the geometry-based cloud shadow detection method for Landsat OLI from the following two aspects. (1) Cloud height no longer depends on the brightness temperature of the thermal infrared band but uses a possible dynamic range from 200 m to 12,000 m. In this case, cloud shadow is not a specific location but a possible range. Further analysis was carried out in the possible range based on the spectrum to determine cloud shadow location. This effectively avoids the cloud shadow leakage caused by the error in the height determination of a cloud. (2) Object-based and pixel spectral analyses are combined to detect cloud shadows, which can realize cloud shadow detection from two aspects of target scale and pixel scale. Based on the analysis of the spectral differences between the cloud shadow and typical ground objects, the best cloud shadow detection bands of Landsat 8 OLI were determined. The combined use of spectrum and shape can effectively improve the detection precision of cloud shadows produced by thin clouds. Several cloud shadow detection experiments were carried out, and the results were verified by the results of artificial recognition. The results of these experiments indicated that this method can identify cloud shadows in different regions with correct accuracy exceeding 80%, approximately 5% of the areas were wrongly identified, and approximately 10% of the cloud shadow areas were missing. The accuracy of this method is obviously higher than the recognition accuracy of Fmask, which has correct accuracy lower than 60%, and the missing recognition is approximately 40%.

Multilayered nonuniform sampling for three-dimensional scene representation

NASA Astrophysics Data System (ADS)

Lin, Huei-Yung; Xiao, Yu-Hua; Chen, Bo-Ren

2015-09-01

The representation of a three-dimensional (3-D) scene is essential in multiview imaging technologies. We present a unified geometry and texture representation based on global resampling of the scene. A layered data map representation with a distance-dependent nonuniform sampling strategy is proposed. It is capable of increasing the details of the 3-D structure locally and is compact in size. The 3-D point cloud obtained from the multilayered data map is used for view rendering. For any given viewpoint, image synthesis with different levels of detail is carried out using the quadtree-based nonuniformly sampled 3-D data points. Experimental results are presented using the 3-D models of reconstructed real objects.

Thin Cloud Detection Method by Linear Combination Model of Cloud Image

NASA Astrophysics Data System (ADS)

Liu, L.; Li, J.; Wang, Y.; Xiao, Y.; Zhang, W.; Zhang, S.

2018-04-01

The existing cloud detection methods in photogrammetry often extract the image features from remote sensing images directly, and then use them to classify images into cloud or other things. But when the cloud is thin and small, these methods will be inaccurate. In this paper, a linear combination model of cloud images is proposed, by using this model, the underlying surface information of remote sensing images can be removed. So the cloud detection result can become more accurate. Firstly, the automatic cloud detection program in this paper uses the linear combination model to split the cloud information and surface information in the transparent cloud images, then uses different image features to recognize the cloud parts. In consideration of the computational efficiency, AdaBoost Classifier was introduced to combine the different features to establish a cloud classifier. AdaBoost Classifier can select the most effective features from many normal features, so the calculation time is largely reduced. Finally, we selected a cloud detection method based on tree structure and a multiple feature detection method using SVM classifier to compare with the proposed method, the experimental data shows that the proposed cloud detection program in this paper has high accuracy and fast calculation speed.

a Cloud Boundary Detection Scheme Combined with Aslic and Cnn Using ZY-3, GF-1/2 Satellite Imagery

NASA Astrophysics Data System (ADS)

Guo, Z.; Li, C.; Wang, Z.; Kwok, E.; Wei, X.

2018-04-01

Remote sensing optical image cloud detection is one of the most important problems in remote sensing data processing. Aiming at the information loss caused by cloud cover, a cloud detection method based on convolution neural network (CNN) is presented in this paper. Firstly, a deep CNN network is used to extract the multi-level feature generation model of cloud from the training samples. Secondly, the adaptive simple linear iterative clustering (ASLIC) method is used to divide the detected images into superpixels. Finally, the probability of each superpixel belonging to the cloud region is predicted by the trained network model, thereby generating a cloud probability map. The typical region of GF-1/2 and ZY-3 were selected to carry out the cloud detection test, and compared with the traditional SLIC method. The experiment results show that the average accuracy of cloud detection is increased by more than 5 %, and it can detected thin-thick cloud and the whole cloud boundary well on different imaging platforms.

The Mixed-Phase Arctic Cloud Experiment (M-PACE)

NASA Technical Reports Server (NTRS)

Verlinde, J.; Harrington, J. Y.; McFarquhar, G. M.; Yannuzzi, V. T.; Avramov, A.; Greenberg, S.; Johnson, N.; Zhang, G.; Poellot, M. R.; Mather, J. H.;

Ultrahigh photo-responsivity and detectivity in multilayer InSe nanosheets phototransistors with broadband response

DOE PAGES

Feng, Wei; Wu, Jing-Bin; Li, Xiaoli; ...

2015-05-20

In this paper, we demonstrate the strategies and principles for the performance improvement of layered semiconductor based photodetectors using multilayer indium selenide (InSe) as the model material. It is discovered that multiple reflection interference at the interfaces in the phototransistor device leads to a thickness-dependent photo-response, which provides a guideline to improve the performance of layered semiconductor based phototransistors. The responsivity and detectivity of InSe nanosheet phototransistor can be adjustable using applied gate voltage. Our InSe nanosheet phototransistor exhibits ultrahigh responsivity and detectivity. An ultrahigh external photo-responsivity of ~10 4 A W -1 can be achieved from broad spectra rangingmore » from UV to near infrared wavelength using our InSe nanosheet photodetectors. The detectivity of multilayer InSe devices is ~10 12 to 10 13 Jones, which surpasses that of the currently exploited InGaAs photodetectors (10 11 to 10 12 Jones). Finally, this research shows that multilayer InSe nanosheets are promising materials for high performance photodetectors.« less

A Survey on Personal Data Cloud

PubMed Central

Wang, Jiaqiu; Wang, Zhongjie

2014-01-01

Personal data represent the e-history of a person and are of great significance to the person, but they are essentially produced and governed by various distributed services and there lacks a global and centralized view. In recent years, researchers pay attention to Personal Data Cloud (PDC) which aggregates the heterogeneous personal data scattered in different clouds into one cloud, so that a person could effectively store, acquire, and share their data. This paper makes a short survey on PDC research by summarizing related papers published in recent years. The concept, classification, and significance of personal data are elaborately introduced and then the semantics correlation and semantics representation of personal data are discussed. A multilayer reference architecture of PDC, including its core components and a real-world operational scenario showing how the reference architecture works, is introduced in detail. Existing commercial PDC products/prototypes are listed and compared from several perspectives. Five open issues to improve the shortcomings of current PDC research are put forward. PMID:25165753

Aptamer based surface enhanced Raman scattering detection of vasopressin using multilayer nanotube arrays

PubMed Central

Huh, Yun Suk; Erickson, David

2009-01-01

Here we present an optofluidic surface enhanced Raman spectroscopy (SERS) device for on-chip detection of vasopressin using an aptamer based binding assay. To create the SERS-active substrate, densely packed, 200 nm diameter, metal nanotube arrays were fabricated using an anodized alumina nanoporous membrane as a template for shadow evaporation. We explore the use of both single layer Au structures and multilayer Au/Ag/Au structures and also demonstrate a facile technique for integrating the membranes with all polydimethylsiloxane (PDMS) microfluidic devices. Using the integrated device, we demonstrate a linear response in the main detection peak intensity to solution phase concentration and a limit of detection on the order of 5.2 μU/mL. This low limit of detection is obtained with device containing the multilayer SERS substrate which we show exhibits a stronger Raman enhancement while maintaining biocompatibility and ease or surface reactivity with the capture probe. PMID:19857952

Enhanced Detectability of Community Structure in Multilayer Networks through Layer Aggregation.

PubMed

Taylor, Dane; Shai, Saray; Stanley, Natalie; Mucha, Peter J

2016-06-03

Many systems are naturally represented by a multilayer network in which edges exist in multiple layers that encode different, but potentially related, types of interactions, and it is important to understand limitations on the detectability of community structure in these networks. Using random matrix theory, we analyze detectability limitations for multilayer (specifically, multiplex) stochastic block models (SBMs) in which L layers are derived from a common SBM. We study the effect of layer aggregation on detectability for several aggregation methods, including summation of the layers' adjacency matrices for which we show the detectability limit vanishes as O(L^{-1/2}) with increasing number of layers, L. Importantly, we find a similar scaling behavior when the summation is thresholded at an optimal value, providing insight into the common-but not well understood-practice of thresholding pairwise-interaction data to obtain sparse network representations.

Temperature-dependent optical properties of gold nanoparticles coated with a charged diblock copolymer and an uncharged triblock copolymer.

PubMed

Volden, Sondre; Kjøniksen, Anna-Lena; Zhu, Kaizheng; Genzer, Jan; Nyström, Bo; Glomm, Wilhelm R

2010-02-23

We demonstrate that the optical properties of gold nanoparticles can be used to detect and follow stimuli-induced changes in adsorbed macromolecules. Specifically, we investigate thermal response of anionic diblock and uncharged triblock copolymers based on poly(N-isopropylacrylamide) (PNIPAAM) blocks adsorbed onto gold nanoparticles and planar gold surfaces in a temperature range between 25 and 60 degrees C. By employing a palette of analytical probes, including UV-visible spectroscopy, dynamic light scattering, fluorescence, and quartz crystal microbalance with dissipation monitoring, we establish that while the anionic copolymer forms monolayers at both low and high temperature, the neutral copolymer adsorbs as a monolayer at low temperatures and forms multilayers above the cloud point (T(C)). Raising the temperature above T(C) severely affects the optical properties of the gold particle/polymer composites, expelling associated water and altering the immediate surroundings of the gold nanoparticles. This effect, stronger for the uncharged polymer, is related to the amount of polymer adsorbed on the surface, where a denser shell influences the surface plasmon band to a greater degree. This is corroborated with light scattering experiments, which reveal that flocculation of the neutral polymer-coated particles occurs at high temperatures. The flocculation behavior of the neutral copolymer on planar gold surfaces results in multilayer formation. The observed effects are discussed within the framework of the Mie-Drude theory.

Cloud Detection by Fusing Multi-Scale Convolutional Features

NASA Astrophysics Data System (ADS)

Li, Zhiwei; Shen, Huanfeng; Wei, Yancong; Cheng, Qing; Yuan, Qiangqiang

2018-04-01

Clouds detection is an important pre-processing step for accurate application of optical satellite imagery. Recent studies indicate that deep learning achieves best performance in image segmentation tasks. Aiming at boosting the accuracy of cloud detection for multispectral imagery, especially for those that contain only visible and near infrared bands, in this paper, we proposed a deep learning based cloud detection method termed MSCN (multi-scale cloud net), which segments cloud by fusing multi-scale convolutional features. MSCN was trained on a global cloud cover validation collection, and was tested in more than ten types of optical images with different resolution. Experiment results show that MSCN has obvious advantages over the traditional multi-feature combined cloud detection method in accuracy, especially when in snow and other areas covered by bright non-cloud objects. Besides, MSCN produced more detailed cloud masks than the compared deep cloud detection convolution network. The effectiveness of MSCN make it promising for practical application in multiple kinds of optical imagery.

Radiative Impacts of Cloud Heterogeneity and Overlap in an Atmospheric General Circulation Model

NASA Technical Reports Server (NTRS)

Oreopoulos, L.; Lee, D.; Sud, Y. C.; Suarez, M. J.

2012-01-01

The radiative impacts of introducing horizontal heterogeneity of layer cloud condensate, and vertical overlap of condensate and cloud fraction are examined with the aid of a new radiation package operating in the GEOS-5 Atmospheric General Circulation Model. The impacts are examined in terms of diagnostic top-of-the-atmosphere shortwave (SW) and longwave (LW) cloud radiative effect (CRE) calculations for a range of assumptions and parameter specifications about the overlap. The investigation is conducted for two distinct cloud schemes, the one that comes with the standard GEOS-5 distribution, and another which has been recently used experimentally for its enhanced GEOS-5 distribution, and another which has been recently used experimentally for its enhanced cloud microphysical capabilities; both are coupled to a cloud generator allowing arbitrary cloud overlap specification. We find that cloud overlap radiative impacts are significantly stronger for the operational cloud scheme for which a change of cloud fraction overlap from maximum-random to generalized results to global changes of SW and LW CRE of approximately 4 Watts per square meter, and zonal changes of up to approximately 10 Watts per square meter. This is because of fewer occurrences compared to the other scheme of large layer cloud fractions and of multi-layer situations with large numbers of atmospheric being simultaneously cloudy, conditions that make overlap details more important. The impact on CRE of the details of condensate distribution overlap is much weaker. Once generalized overlap is adopted, both cloud schemes are only modestly sensitive to the exact values of the overlap parameters. We also find that if one of the CRE components is overestimated and the other underestimated, both cannot be driven towards observed values by adjustments to cloud condensate heterogeneity and overlap alone.

Characterization of AVHRR global cloud detection sensitivity based on CALIPSO-CALIOP cloud optical thickness information: demonstration of results based on the CM SAF CLARA-A2 climate data record

NASA Astrophysics Data System (ADS)

Karlsson, Karl-Göran; Håkansson, Nina

2018-02-01

The sensitivity in detecting thin clouds of the cloud screening method being used in the CM SAF cloud, albedo and surface radiation data set from AVHRR data (CLARA-A2) cloud climate data record (CDR) has been evaluated using cloud information from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) onboard the CALIPSO satellite. The sensitivity, including its global variation, has been studied based on collocations of Advanced Very High Resolution Radiometer (AVHRR) and CALIOP measurements over a 10-year period (2006-2015). The cloud detection sensitivity has been defined as the minimum cloud optical thickness for which 50 % of clouds could be detected, with the global average sensitivity estimated to be 0.225. After using this value to reduce the CALIOP cloud mask (i.e. clouds with optical thickness below this threshold were interpreted as cloud-free cases), cloudiness results were found to be basically unbiased over most of the globe except over the polar regions where a considerable underestimation of cloudiness could be seen during the polar winter. The overall probability of detecting clouds in the polar winter could be as low as 50 % over the highest and coldest parts of Greenland and Antarctica, showing that a large fraction of optically thick clouds also remains undetected here. The study included an in-depth analysis of the probability of detecting a cloud as a function of the vertically integrated cloud optical thickness as well as of the cloud's geographical position. Best results were achieved over oceanic surfaces at mid- to high latitudes where at least 50 % of all clouds with an optical thickness down to a value of 0.075 were detected. Corresponding cloud detection sensitivities over land surfaces outside of the polar regions were generally larger than 0.2 with maximum values of approximately 0.5 over the Sahara and the Arabian Peninsula. For polar land surfaces the values were close to 1 or higher with maximum values of 4.5 for the parts with the highest altitudes over Greenland and Antarctica. It is suggested to quantify the detection performance of other CDRs in terms of a sensitivity threshold of cloud optical thickness, which can be estimated using active lidar observations. Validation results are proposed to be used in Cloud Feedback Model Intercomparison Project (CFMIP) Observation Simulation Package (COSP) simulators for cloud detection characterization of various cloud CDRs from passive imagery.

Direct Detection of Potential Pyrethroids in Yangtze River via an Imprinted Multilayer Phosphorescence Probe.

PubMed

Chen, Li; Lv, Xiaodong; Dai, Jiangdong; Sun, Lin; Huo, Pengwei; Li, Chunxiang; Yan, Yongsheng

2018-01-01

A novel tailored multilayer probe for monitoring potential pyrethroids in the Yangtze River was proposed. The room-temperature phosphorescence method was applied to realize a detection strategy that is superior to the fluorescence method. Efficient Mn-doped ZnS quantum dots with uniform size of 4.6 nm were firstly coated with a mesoporous silica to obtain a suitable intermediate transition layer, then an imprinted layer containing bifenthrin specific recognition sites was anchored. Characterizations verified the multilayer structure convincingly and the detection process relied on the electron transfer-induced fluorescence quenching mechanism. Optional detection time and standard detection curve were obtained within a concentration range from 5.0 to 50 μmol L -1 . The stability was verified to be good after 12 replicates. Feasibility of the probe was proved by monitoring water samples from the Zhenjiang reach of the Yangtze River. The probe offers promise for direct bifenthrin detection in unknown environmental water with an accurate and stable phosphorescence analysis strategy.

Some basic mathematical methods of diffusion theory. [emphasis on atmospheric applications

NASA Technical Reports Server (NTRS)

Giere, A. C.

1977-01-01

An introductory treatment of the fundamentals of diffusion theory is presented, starting with molecular diffusion and leading up to the statistical methods of turbulent diffusion. A multilayer diffusion model, designed to permit concentration and dosage calculations downwind of toxic clouds from rocket vehicles, is described. The concepts and equations of diffusion are developed on an elementary level, with emphasis on atmospheric applications.

An assessment of thin cloud detection by applying bidirectional reflectance distribution function model-based background surface reflectance using Geostationary Ocean Color Imager (GOCI): A case study for South Korea

NASA Astrophysics Data System (ADS)

Kim, Hye-Won; Yeom, Jong-Min; Shin, Daegeun; Choi, Sungwon; Han, Kyung-Soo; Roujean, Jean-Louis

2017-08-01

In this study, a new assessment of thin cloud detection with the application of bidirectional reflectance distribution function (BRDF) model-based background surface reflectance was undertaken by interpreting surface spectra characterized using the Geostationary Ocean Color Imager (GOCI) over a land surface area. Unlike cloud detection over the ocean, the detection of cloud over land surfaces is difficult due to the complicated surface scattering characteristics, which vary among land surface types. Furthermore, in the case of thin clouds, in which the surface and cloud radiation are mixed, it is difficult to detect the clouds in both land and atmospheric fields. Therefore, to interpret background surface reflectance, especially underneath cloud, the semiempirical BRDF model was used to simulate surface reflectance by reflecting solar angle-dependent geostationary sensor geometry. For quantitative validation, Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) data were used to make a comparison with the proposed cloud masking result. As a result, the new cloud masking scheme resulted in a high probability of detection (POD = 0.82) compared with the Moderate Resolution Imaging Spectroradiometer (MODIS) (POD = 0.808) for all cloud cases. In particular, the agreement between the CALIPSO cloud product and new GOCI cloud mask was over 94% when detecting thin cloud (e.g., altostratus and cirrus) from January 2014 to June 2015. This result is relatively high in comparison with the result from the MODIS Collection 6 cloud mask product (MYD35).

Use of Field Observations for Understanding Controls of Polar Low Cloud Microphysical Properties

NASA Astrophysics Data System (ADS)

McFarquhar, G. M.

2016-12-01

Although arctic clouds have a net warming effect on the Arctic surface, their radiative effect is sensitive to cloud microphysical properties, namely the sizes, phases and shapes of cloud particles. Such cloud properties are influenced by the numbers, compositions and sizes of aerosols, meteorological conditions, and surface characteristics. Uncertainty in representing cloud-aerosol interactions in varying environmental conditions and associated feedbacks is a major cause in our lack of understanding of why the Arctic is warming faster than the rest of the Earth. Here, the understanding of cloud-aerosol interactions gained from past arctic field experiments is reviewed. Such studies have characterized the structure of single-layer mixed phase clouds that are ubiquitous in the Arctic and investigated different aerosol indirect effect mechanisms acting in these clouds. But, it is still unknown what controls the amount of supercooled water in arctic clouds (especially in complex frequently occurring multi-layer clouds), how probability distributions of cloud properties and radiative heating and their subsequent impact on temperature profiles and underlying snow and sea ice cover vary with aerosol loading and composition in different surface and meteorological conditions, how the composition and concentration of arctic aerosols and cloud microphysical properties vary annually and interannually, and how cloud-aerosol-radiative interactions can be better represented in models with varying temporal and spatial scales. These needs can be addressed in two ways. First, there is a need for comprehensive and routine aircraft, UAV and tethered balloon measurements in the presence of ground, air or space-based remote sensors over a variety of surface and meteorological conditions. Second, planned observational campaigns (the Measurements of Aerosols Radiation and Clouds over the Southern Oceans MARCUS and the Southern Oceans Cloud Radiation Transport Experimental Study SOCRATES) should provide cloud, aerosol, radiative and precipitation observations over the pristine and continually cloudy Southern Oceans that are remote from natural and continental anthropogenic aerosol sources should provide a process-oriented understanding of cloud-aerosol interactions in liquid and ice clouds.

Automated Detection of Clouds in Satellite Imagery

NASA Technical Reports Server (NTRS)

Jedlovec, Gary

2010-01-01

Many different approaches have been used to automatically detect clouds in satellite imagery. Most approaches are deterministic and provide a binary cloud - no cloud product used in a variety of applications. Some of these applications require the identification of cloudy pixels for cloud parameter retrieval, while others require only an ability to mask out clouds for the retrieval of surface or atmospheric parameters in the absence of clouds. A few approaches estimate a probability of the presence of a cloud at each point in an image. These probabilities allow a user to select cloud information based on the tolerance of the application to uncertainty in the estimate. Many automated cloud detection techniques develop sophisticated tests using a combination of visible and infrared channels to determine the presence of clouds in both day and night imagery. Visible channels are quite effective in detecting clouds during the day, as long as test thresholds properly account for variations in surface features and atmospheric scattering. Cloud detection at night is more challenging, since only courser resolution infrared measurements are available. A few schemes use just two infrared channels for day and night cloud detection. The most influential factor in the success of a particular technique is the determination of the thresholds for each cloud test. The techniques which perform the best usually have thresholds that are varied based on the geographic region, time of year, time of day and solar angle.

Features of clouds and convection during the pre- and post-onset periods of the Asian summer monsoon

NASA Astrophysics Data System (ADS)

Wang, Yi; Wang, Chenghai

2016-02-01

The statistical characteristics of the vertical structure of clouds in the Asian summer monsoon region are investigated using two CloudSat standard products (Geometrical Profiling Product (GEOPROF) and GEOPROF-lidar) during the pre- and post-onset periods of the Asian summer monsoon, from April to August in 2007-2010. The characteristics of the vertical structure of clouds are analyzed and compared for different underlying surfaces in four subregions during this period. Also analyzed are the evolution of precipitation and hydrometeors with the northward advance of the Asian summer monsoon, and different hydrometeor characteristics attributed to the underlying surface features. The results indicate that the vertical cloud amounts increase significantly after the summer monsoon onset; this increase occurs first in the upper troposphere and then at lower altitudes over tropical regions (South Asian and tropical Northwest Pacific regions). The heights of the cloud top ascend, and the vertical height between the top and the base of the whole cloud increases. Single-layer (SL) and double-layer (DL) hydrometeors contribute over half and one third of the cloudiness in these 5 months (April to August), respectively. The multilayer frequencies increase in four different regions, and cloud layer depths (CLD) increase after the summer monsoon onset. These changes are stronger in tropical regions than in subtropical regions, while the vertical distance between cloud layers (VDCL) deceases in tropical regions and increases in subtropical regions.

Improving Scene Classifications with Combined Active/Passive Measurements

NASA Astrophysics Data System (ADS)

Hu, Y.; Rodier, S.; Vaughan, M.; McGill, M.

The uncertainties in cloud and aerosol physical properties derived from passive instruments such as MODIS are not insignificant And the uncertainty increases when the optical depths decrease Lidar observations do much better for the thin clouds and aerosols Unfortunately space-based lidar measurements such as the one onboard CALIPSO satellites are limited to nadir view only and thus have limited spatial coverage To produce climatologically meaningful thin cloud and aerosol data products it is necessary to combine the spatial coverage of MODIS with the highly sensitive CALIPSO lidar measurements Can we improving the quality of cloud and aerosol remote sensing data products by extending the knowledge about thin clouds and aerosols learned from CALIPSO-type of lidar measurements to a larger portion of the off-nadir MODIS-like multi-spectral pixels To answer the question we studied the collocated Cloud Physics Lidar CPL with Modis-Airborne-Simulation MAS observations and established an effective data fusion technique that will be applied in the combined CALIPSO MODIS cloud aerosol product algorithms This technique performs k-mean and Kohonen self-organized map cluster analysis on the entire swath of MAS data as well as on the combined CPL MAS data at the nadir track Interestingly the clusters generated from the two approaches are almost identical It indicates that the MAS multi-spectral data may have already captured most of the cloud and aerosol scene types such as cloud ice water phase multi-layer information aerosols

Environmental Effects of Space Shuttle Solid Rocket Motor Exhaust Plumes

NASA Technical Reports Server (NTRS)

Hwang, B.; Pergament, H. S.

1976-01-01

The deposition of NOx and HCl in the stratosphere from the space shuttle solid rocket motors (SRM) and exhaust plume is discussed. A detailed comparison between stratospheric deposition rates using the baseline SRM propellant and an alternate propellant, which replaces ammonium perchlorate by ammonium nitrate, shows the total NOx deposition rate to be approximately the same for each propellant. For both propellants the ratio of the deposition rates of NOx to total chlorine-containing species is negligibly small. Rocket exhaust ground cloud transport processes in the troposphere are also examined. A brief critique of the multilayer diffusion models (presently used for predicting pollutant deposition in the troposphere) is presented, and some detailed cloud rise calculations are compared with data for Titan 3C launches. The results show that, when launch time meteorological data are used as input, the model can reasonably predict measured cloud stabilization heights.

Influence of daylight and noise current on cloud and aerosol observations by spaceborne elastic scattering lidar.

PubMed

Nakajima, T Y; Imai, T; Uchino, O; Nagai, T

1999-08-20

The influence of daylight and noise current on cloud and aerosol observations by realistic spaceborne lidar was examined by computer simulations. The reflected solar radiations, which contaminate the daytime return signals of lidar operations, were strictly and explicitly estimated by accurate radiative transfer calculations. It was found that the model multilayer cirrus clouds and the boundary layer aerosols could be observed during the daytime and the nighttime with only a few laser shots. However, high background noise and noise current make it difficult to observe volcanic aerosols in middle and upper atmospheric layers. Optimal combinations of the laser power and receiver field of view are proposed to compensate for the negative influence that is due to these noises. For the computer simulations, we used a realistic set of lidar parameters similar to the Experimental Lidar in-Space Equipment of the National Space Development Agency of Japan.

Impact of combustion products from Space Shuttle launches on ambient air quality

NASA Technical Reports Server (NTRS)

Dumbauld, R. K.; Bowers, J. F.; Cramer, H. E.

1974-01-01

The present work describes some multilayer diffusion models and a computer program for these models developed to predict the impact of ground clouds formed during Space Shuttle launches on ambient air quality. The diffusion models are based on the Gaussian plume equation for an instantaneous volume source. Cloud growth is estimated on the basis of measurable meteorological parameters: standard deviation of the wind azimuth angle, standard deviation of wind elevation angle, vertical wind-speed shear, vertical wind-direction shear, and depth of the surface mixing layer. Calculations using these models indicate that Space Shuttle launches under a variety of meteorological regimes at Kennedy Space Center and Vandenberg AFB are unlikely to endanger the exposure standards for HCl; similar results have been obtained for CO and Al2O3. However, the possibility that precipitation scavenging of the ground cloud might result in an acidic rain that could damage vegetation has not been investigated.

[Polarization Modeling and Analysis of Light Scattering Properties of Multilayer Films on Slightly Rough Substrate].

PubMed

Gao, Hui; Gao, Jun; Wang, Ling-mei; Wang, Chi

2016-03-01

To satisfy the demand of multilayer films on polarization detection, polarized bidirectional reflectance distribution function of multilayer films on slightly rough substrate is established on the basis of first-order vector perturbation theory and polarization transfer matrix. Due to the function, light scattering polarization properties are studied under multi-factor impacts of two typical targets-monolayer anti-reflection film and multilayer high-reflection films. The result shows that for monolayer anti-reflection film, observing positions have a great influence on the degree of polarization, for the left of the peak increased and right decreased compared with the substrate target. Film target and bare substrate can be distinguished by the degree of polarization in different observation angles. For multilayer high-reflection films, the degree of polarization is significantly associated with the number and optical thickness of layers at different wavelengths of incident light and scattering angles. With the increase of the layer number, the degree of polarization near the mirror reflection area decreases. It reveals that the calculated results coincide with the experimental data, which validates the correctness and rationality of the model. This paper provides a theoretical method for polarization detection of multilayer films target and reflection stealth technology.

Single-footprint retrievals for AIRS using a fast TwoSlab cloud-representation model and the SARTA all-sky infrared radiative transfer algorithm

NASA Astrophysics Data System (ADS)

DeSouza-Machado, Sergio; Larrabee Strow, L.; Tangborn, Andrew; Huang, Xianglei; Chen, Xiuhong; Liu, Xu; Wu, Wan; Yang, Qiguang

2018-01-01

One-dimensional variational retrievals of temperature and moisture fields from hyperspectral infrared (IR) satellite sounders use cloud-cleared radiances (CCRs) as their observation. These derived observations allow the use of clear-sky-only radiative transfer in the inversion for geophysical variables but at reduced spatial resolution compared to the native sounder observations. Cloud clearing can introduce various errors, although scenes with large errors can be identified and ignored. Information content studies show that, when using multilayer cloud liquid and ice profiles in infrared hyperspectral radiative transfer codes, there are typically only 2-4 degrees of freedom (DOFs) of cloud signal. This implies a simplified cloud representation is sufficient for some applications which need accurate radiative transfer. Here we describe a single-footprint retrieval approach for clear and cloudy conditions, which uses the thermodynamic and cloud fields from numerical weather prediction (NWP) models as a first guess, together with a simple cloud-representation model coupled to a fast scattering radiative transfer algorithm (RTA). The NWP model thermodynamic and cloud profiles are first co-located to the observations, after which the N-level cloud profiles are converted to two slab clouds (TwoSlab; typically one for ice and one for water clouds). From these, one run of our fast cloud-representation model allows an improvement of the a priori cloud state by comparing the observed and model-simulated radiances in the thermal window channels. The retrieval yield is over 90 %, while the degrees of freedom correlate with the observed window channel brightness temperature (BT) which itself depends on the cloud optical depth. The cloud-representation and scattering package is benchmarked against radiances computed using a maximum random overlap (RMO) cloud scheme. All-sky infrared radiances measured by NASA's Atmospheric Infrared Sounder (AIRS) and NWP thermodynamic and cloud profiles from the European Centre for Medium-Range Weather Forecasts (ECMWF) forecast model are used in this paper.

Cloud detection method for Chinese moderate high resolution satellite imagery (Conference Presentation)

NASA Astrophysics Data System (ADS)

Zhong, Bo; Chen, Wuhan; Wu, Shanlong; Liu, Qinhuo

2016-10-01

Cloud detection of satellite imagery is very important for quantitative remote sensing research and remote sensing applications. However, many satellite sensors don't have enough bands for a quick, accurate, and simple detection of clouds. Particularly, the newly launched moderate to high spatial resolution satellite sensors of China, such as the charge-coupled device on-board the Chinese Huan Jing 1 (HJ-1/CCD) and the wide field of view (WFV) sensor on-board the Gao Fen 1 (GF-1), only have four available bands including blue, green, red, and near infrared bands, which are far from the requirements of most could detection methods. In order to solve this problem, an improved and automated cloud detection method for Chinese satellite sensors called OCM (Object oriented Cloud and cloud-shadow Matching method) is presented in this paper. It firstly modified the Automatic Cloud Cover Assessment (ACCA) method, which was developed for Landsat-7 data, to get an initial cloud map. The modified ACCA method is mainly based on threshold and different threshold setting produces different cloud map. Subsequently, a strict threshold is used to produce a cloud map with high confidence and large amount of cloud omission and a loose threshold is used to produce a cloud map with low confidence and large amount of commission. Secondly, a corresponding cloud-shadow map is also produced using the threshold of near-infrared band. Thirdly, the cloud maps and cloud-shadow map are transferred to cloud objects and cloud-shadow objects. Cloud and cloud-shadow are usually in pairs; consequently, the final cloud and cloud-shadow maps are made based on the relationship between cloud and cloud-shadow objects. OCM method was tested using almost 200 HJ-1/CCD images across China and the overall accuracy of cloud detection is close to 90%.

Comparison of Cloud and Aerosol Detection between CERES Edition 3 Cloud Mask and CALIPSO Version 2 Data Products

NASA Astrophysics Data System (ADS)

Trepte, Qing; Minnis, Patrick; Sun-Mack, Sunny; Trepte, Charles

Clouds and aerosol play important roles in the global climate system. Accurately detecting their presence, altitude, and properties using satellite radiance measurements is a crucial first step in determining their influence on surface and top-of-atmosphere radiative fluxes. This paper presents a comparison analysis of a new version of the Clouds and Earth's Radiant Energy System (CERES) Edition 3 cloud detection algorithms using Aqua MODIS data with the recently released Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) Version 2 Vertical Feature Mask (VFM). Improvements in CERES Edition 3 cloud mask include dust detection, thin cirrus tests, enhanced low cloud detection at night, and a smoother transition from mid-latitude to polar regions. For the CALIPSO Version 2 data set, changes to the lidar calibration can result in significant improvements to its identification of optically thick aerosol layers. The Aqua and CALIPSO satellites, part of the A-train satellite constellation, provide a unique opportunity for validating passive sensor cloud and aerosol detection using an active sensor. In this paper, individual comparison cases will be discussed for different types of clouds and aerosols over various surfaces, for daytime and nighttime conditions, and for regions ranging from the tropics to the poles. Examples will include an assessment of the CERES detection algorithm for optically thin cirrus, marine stratus, and polar night clouds as well as its ability to characterize Saharan dust plumes off the African coast. With the CALIPSO lidar's unique ability to probe the vertical structure of clouds and aerosol layers, it provides an excellent validation data set for cloud detection algorithms, especially for polar nighttime clouds.

Near-Real Time Cloud Retrievals from Operational and Research Meteorological Satellites

NASA Technical Reports Server (NTRS)

Minnis, Patrick; Nguyen, Louis; Palilonda, Rabindra; Heck, Patrick W.; Spangenberg, Douglas A.; Doelling, David R.; Ayers, J. Kirk; Smith, William L., Jr.; Khaiyer, Mandana M.; Trepte, Qing Z.;

Enhanced softgoods structures for spacesuit micrometeoroid/debris protective systems

NASA Technical Reports Server (NTRS)

Remington, Brian; Cadogan, David; Kosmo, Joseph

1992-01-01

A lightweight, flexible thermal micrometeoroid garment (TMG) design for enhanced space suit micrometeoroid/debris (M/D) protection is described. It will consist of an outer layer comprised of orthofabric, multilayers of aluminized Mylar, and a layer of silicone rubber loaded with micron sized particles of tungsten. The shield layers would fragment and/or vaporize the M/D projectile while the backup sheet would stop the resultant debris cloud.

Overlap Properties of Clouds Generated by a Cloud Resolving Model

NASA Technical Reports Server (NTRS)

Oreopoulos, L.; Khairoutdinov, M.

2002-01-01

In order for General Circulation Models (GCMs), one of our most important tools to predict future climate, to correctly describe the propagation of solar and thermal radiation through the cloudy atmosphere a realistic description of the vertical distribution of cloud amount is needed. Actually, one needs not only the cloud amounts at different levels of the atmosphere, but also how these cloud amounts are related, in other words, how they overlap. Currently GCMs make some idealized assumptions about cloud overlap, for example that contiguous cloud layers overlap maximally and non-contiguous cloud layers overlap in a random fashion. Since there are difficulties in obtaining the vertical profile of cloud amount from observations, the realism of the overlap assumptions made in GCMs has not been yet rigorously investigated. Recently however, cloud observations from a relatively new type of ground radar have been used to examine the vertical distribution of cloudiness. These observations suggest that the GCM overlap assumptions are dubious. Our study uses cloud fields from sophisticated models dedicated to simulate cloud formation, maintenance, and dissipation called Cloud Resolving Models . These models are generally considered capable of producing realistic three-dimensional representation of cloudiness. Using numerous cloud fields produced by such a CRM we show that the degree of overlap between cloud layers is a function of their separation distance, and is in general described by a combination of the maximum and random overlap assumption, with random overlap dominating as separation distances increase. We show that it is possible to parameterize this behavior in a way that can eventually be incorporated in GCMs. Our results seem to have a significant resemblance to the results from the radar observations despite the completely different nature of the datasets. This consistency is encouraging and will promote development of new radiative transfer codes that will estimate the radiation effects of multi-layer cloud fields more accurately.

Analysis of the VIIRS cloud mask, comparison with the NAVOCEANO cloud mask, and how they complement each other

NASA Astrophysics Data System (ADS)

Cayula, Jean-François P.; May, Douglas A.; McKenzie, Bruce D.

2014-05-01

The Visible Infrared Imaging Radiometer Suite (VIIRS) Cloud Mask (VCM) Intermediate Product (IP) has been developed for use with Suomi National Polar-orbiting Partnership (NPP) VIIRS Environmental Data Record (EDR) products. In particular, the VIIRS Sea Surface Temperature (SST) EDR relies on VCM to identify cloud contaminated observations. Unfortunately, VCM does not appear to perform as well as cloud detection algorithms for SST. This may be due to similar but different goals of the two algorithms. VCM is concerned with detecting clouds while SST is interested in identifying clear observations. The result is that in undetermined cases VCM defaults to "clear," while the SST cloud detection defaults to "cloud." This problem is further compounded because classic SST cloud detection often flags as "cloud" all types of corrupted data, thus making a comparison with VCM difficult. The Naval Oceanographic Office (NAVOCEANO), which operationally produces a VIIRS SST product, relies on cloud detection from the NAVOCEANO Cloud Mask (NCM), adapted from cloud detection schemes designed for SST processing. To analyze VCM, the NAVOCEANO SST process was modified to attach the VCM flags to all SST retrievals. Global statistics are computed for both day and night data. The cases where NCM and/or VCM tag data as cloud-contaminated or clear can then be investigated. By analyzing the VCM individual test flags in conjunction with the status of NCM, areas where VCM can complement NCM are identified.

Enhancement of Fluorescence-Based Sandwich Immunoassay Using Multilayered Microplates Modified with Plasma-Polymerized Films

PubMed Central

Yano, Kazuyoshi; Iwasaki, Akira

2016-01-01

A functional modification of the surface of a 96-well microplate coupled with a thin layer deposition technique is demonstrated for enhanced fluorescence-based sandwich immunoassays. The plasma polymerization technique enabling the deposition of organic thin films was employed for the modification of the well surface of a microplate. A silver layer and a plasma-polymerized film were consecutively deposited on the microplate as a metal mirror and the optical interference layer, respectively. When Cy3-labeled antibody was applied to the wells of the resulting multilayered microplate without any immobilization step, greatly enhanced fluorescence was observed compared with that obtained with the unmodified one. The same effect could be also exhibited for an immunoassay targeting antigen directly adsorbed on the multilayered microplate. Furthermore, a sandwich immunoassay for the detection of interleukin 2 (IL-2) was performed with the multilayered microplates, resulting in specific and 88-fold–enhanced fluorescence detection. PMID:28029144

Development of a multilayered polymeric DNA biosensor using radio frequency technology with gold and magnetic nanoparticles.

PubMed

Yang, Cheng-Hao; Kuo, Long-Sheng; Chen, Ping-Hei; Yang, Chii-Rong; Tsai, Zuo-Min

2012-01-15

This study utilized the radio frequency (RF) technology to develop a multilayered polymeric DNA sensor with the help of gold and magnetic nanoparticles. The flexible polymeric materials, poly (p-xylylene) (Parylene) and polyethylene naphtholate (PEN), were used as substrates to replace the conventional rigid substrates such as glass and silicon wafers. The multilayered polymeric RF biosensor, including the two polymer layers and two copper transmission structure layers, was developed to reduce the total sensor size and further enhance the sensitivity of the biochip in the RF DNA detection. Thioglycolic acid (TGA) was used on the surface of the proposed biochip to form a thiolate-modified sensing surface for DNA hybridization. Gold nanoparticles (AuNPs) and magnetic nanoparticles (MNPs) were used to immobilize on the surface of the biosensor to enhance overall detection sensitivity. In addition to gold nanoparticles, the magnetic nanoparticles has been demonstrated the applicability for RF DNA detection. The performance of the proposed biosensor was evaluated by the shift of the center frequency of the RF biosensor because the electromagnetic characteristic of the biosensors can be altered by the immobilized multilayer nanoparticles on the biosensor. The experimental results show that the detection limit of the DNA concentration can reach as low as 10 pM, and the largest shift of the center frequency with triple-layer AuNPs and MNPs can approach 0.9 and 0.7 GHz, respectively. Such the achievement implies that the developed biosensor can offer an alternative inexpensive, disposable, and highly sensitive option for application in biomedicine diagnostic systems because the price and size of each biochip can be effectively reduced by using fully polymeric materials and multilayer-detecting structures. Copyright © 2011 Elsevier B.V. All rights reserved.

Testing cloud microphysics parameterizations in NCAR CAM5 with ISDAC and M-PACE observations

NASA Astrophysics Data System (ADS)

Liu, Xiaohong; Xie, Shaocheng; Boyle, James; Klein, Stephen A.; Shi, Xiangjun; Wang, Zhien; Lin, Wuyin; Ghan, Steven J.; Earle, Michael; Liu, Peter S. K.; Zelenyuk, Alla

2011-01-01

Arctic clouds simulated by the National Center for Atmospheric Research (NCAR) Community Atmospheric Model version 5 (CAM5) are evaluated with observations from the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Indirect and Semi-Direct Aerosol Campaign (ISDAC) and Mixed-Phase Arctic Cloud Experiment (M-PACE), which were conducted at its North Slope of Alaska site in April 2008 and October 2004, respectively. Model forecasts for the Arctic spring and fall seasons performed under the Cloud-Associated Parameterizations Testbed framework generally reproduce the spatial distributions of cloud fraction for single-layer boundary-layer mixed-phase stratocumulus and multilayer or deep frontal clouds. However, for low-level stratocumulus, the model significantly underestimates the observed cloud liquid water content in both seasons. As a result, CAM5 significantly underestimates the surface downward longwave radiative fluxes by 20-40 W m-2. Introducing a new ice nucleation parameterization slightly improves the model performance for low-level mixed-phase clouds by increasing cloud liquid water content through the reduction of the conversion rate from cloud liquid to ice by the Wegener-Bergeron-Findeisen process. The CAM5 single-column model testing shows that changing the instantaneous freezing temperature of rain to form snow from -5°C to -40°C causes a large increase in modeled cloud liquid water content through the slowing down of cloud liquid and rain-related processes (e.g., autoconversion of cloud liquid to rain). The underestimation of aerosol concentrations in CAM5 in the Arctic also plays an important role in the low bias of cloud liquid water in the single-layer mixed-phase clouds. In addition, numerical issues related to the coupling of model physics and time stepping in CAM5 are responsible for the model biases and will be explored in future studies.

GOES Cloud Detection at the Global Hydrology and Climate Center

NASA Technical Reports Server (NTRS)

Laws, Kevin; Jedlovec, Gary J.; Arnold, James E. (Technical Monitor)

2002-01-01

The bi-spectral threshold (BTH) for cloud detection and height assignment is now operational at NASA's Global Hydrology and Climate Center (GHCC). This new approach is similar in principle to the bi-spectral spatial coherence (BSC) method with improvements made to produce a more robust cloud-filtering algorithm for nighttime cloud detection and subsequent 24-hour operational cloud top pressure assignment. The method capitalizes on cloud and surface emissivity differences from the GOES 3.9 and 10.7-micrometer channels to distinguish cloudy from clear pixels. Separate threshold values are determined for day and nighttime detection, and applied to a 20-day minimum composite difference image to better filter background effects and enhance differences in cloud properties. A cloud top pressure is assigned to each cloudy pixel by referencing the 10.7-micrometer channel temperature to a thermodynamic profile from a locally -run regional forecast model. This paper and supplemental poster will present an objective validation of nighttime cloud detection by the BTH approach in comparison with previous methods. The cloud top pressure will be evaluated by comparing to the NESDIS operational CO2 slicing approach.

Self-Tuning Method for Increased Obstacle Detection Reliability Based on Internet of Things LiDAR Sensor Models

PubMed Central

2018-01-01

On-chip LiDAR sensors for vehicle collision avoidance are a rapidly expanding area of research and development. The assessment of reliable obstacle detection using data collected by LiDAR sensors has become a key issue that the scientific community is actively exploring. The design of a self-tuning methodology and its implementation are presented in this paper, to maximize the reliability of LiDAR sensors network for obstacle detection in the ‘Internet of Things’ (IoT) mobility scenarios. The Webots Automobile 3D simulation tool for emulating sensor interaction in complex driving environments is selected in order to achieve that objective. Furthermore, a model-based framework is defined that employs a point-cloud clustering technique, and an error-based prediction model library that is composed of a multilayer perceptron neural network, and k-nearest neighbors and linear regression models. Finally, a reinforcement learning technique, specifically a Q-learning method, is implemented to determine the number of LiDAR sensors that are required to increase sensor reliability for obstacle localization tasks. In addition, a IoT driving assistance user scenario, connecting a five LiDAR sensor network is designed and implemented to validate the accuracy of the computational intelligence-based framework. The results demonstrated that the self-tuning method is an appropriate strategy to increase the reliability of the sensor network while minimizing detection thresholds. PMID:29748521

Self-Tuning Method for Increased Obstacle Detection Reliability Based on Internet of Things LiDAR Sensor Models.

PubMed

Castaño, Fernando; Beruvides, Gerardo; Villalonga, Alberto; Haber, Rodolfo E

2018-05-10

On-chip LiDAR sensors for vehicle collision avoidance are a rapidly expanding area of research and development. The assessment of reliable obstacle detection using data collected by LiDAR sensors has become a key issue that the scientific community is actively exploring. The design of a self-tuning methodology and its implementation are presented in this paper, to maximize the reliability of LiDAR sensors network for obstacle detection in the 'Internet of Things' (IoT) mobility scenarios. The Webots Automobile 3D simulation tool for emulating sensor interaction in complex driving environments is selected in order to achieve that objective. Furthermore, a model-based framework is defined that employs a point-cloud clustering technique, and an error-based prediction model library that is composed of a multilayer perceptron neural network, and k-nearest neighbors and linear regression models. Finally, a reinforcement learning technique, specifically a Q-learning method, is implemented to determine the number of LiDAR sensors that are required to increase sensor reliability for obstacle localization tasks. In addition, a IoT driving assistance user scenario, connecting a five LiDAR sensor network is designed and implemented to validate the accuracy of the computational intelligence-based framework. The results demonstrated that the self-tuning method is an appropriate strategy to increase the reliability of the sensor network while minimizing detection thresholds.

Using Information From Prior Satellite Scans to Improve Cloud Detection Near the Day-Night Terminator

NASA Technical Reports Server (NTRS)

Yost, Christopher R.; Minnis, Patrick; Trepte, Qing Z.; Palikonda, Rabindra; Ayers, Jeffrey K.; Spangenberg, Doulas A.

2012-01-01

With geostationary satellite data it is possible to have a continuous record of diurnal cycles of cloud properties for a large portion of the globe. Daytime cloud property retrieval algorithms are typically superior to nighttime algorithms because daytime methods utilize measurements of reflected solar radiation. However, reflected solar radiation is difficult to accurately model for high solar zenith angles where the amount of incident radiation is small. Clear and cloudy scenes can exhibit very small differences in reflected radiation and threshold-based cloud detection methods have more difficulty setting the proper thresholds for accurate cloud detection. Because top-of-atmosphere radiances are typically more accurately modeled outside the terminator region, information from previous scans can help guide cloud detection near the terminator. This paper presents an algorithm that uses cloud fraction and clear and cloudy infrared brightness temperatures from previous satellite scan times to improve the performance of a threshold-based cloud mask near the terminator. Comparisons of daytime, nighttime, and terminator cloud fraction derived from Geostationary Operational Environmental Satellite (GOES) radiance measurements show that the algorithm greatly reduces the number of false cloud detections and smoothes the transition from the daytime to the nighttime clod detection algorithm. Comparisons with the Geoscience Laser Altimeter System (GLAS) data show that using this algorithm decreases the number of false detections by approximately 20 percentage points.

Global cloud top height retrieval using SCIAMACHY limb spectra: model studies and first results

NASA Astrophysics Data System (ADS)

Eichmann, Kai-Uwe; Lelli, Luca; von Savigny, Christian; Sembhi, Harjinder; Burrows, John P.

2016-03-01

Cloud top heights (CTHs) are retrieved for the period 1 January 2003 to 7 April 2012 using height-resolved limb spectra measured with the SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY (SCIAMACHY) on board ENVISAT (ENVIronmental SATellite). In this study, we present the retrieval code SCODA (SCIAMACHY cloud detection algorithm) based on a colour index method and test the accuracy of the retrieved CTHs in comparison to other methods. Sensitivity studies using the radiative transfer model SCIATRAN show that the method is capable of detecting cloud tops down to about 5 km and very thin cirrus clouds up to the tropopause. Volcanic particles can be detected that occasionally reach the lower stratosphere. Upper tropospheric ice clouds are observable for a nadir cloud optical thickness (COT) ≥ 0.01, which is in the subvisual range. This detection sensitivity decreases towards the lowermost troposphere. The COT detection limit for a water cloud top height of 5 km is roughly 0.1. This value is much lower than thresholds reported for passive cloud detection methods in nadir-viewing direction. Low clouds at 2 to 3 km can only be retrieved under very clean atmospheric conditions, as light scattering of aerosol particles interferes with the cloud particle scattering. We compare co-located SCIAMACHY limb and nadir cloud parameters that are retrieved with the Semi-Analytical CloUd Retrieval Algorithm (SACURA). Only opaque clouds (τN,c > 5) are detected with the nadir passive retrieval technique in the UV-visible and infrared wavelength ranges. Thus, due to the frequent occurrence of thin clouds and subvisual cirrus clouds in the tropics, larger CTH deviations are detected between both viewing geometries. Zonal mean CTH differences can be as high as 4 km in the tropics. The agreement in global cloud fields is sufficiently good. However, the land-sea contrast, as seen in nadir cloud occurrence frequency distributions, is not observed in limb geometry. Co-located cloud top height measurements of the limb-viewing Michelson Interferometer for Passive Atmospheric Sounding (MIPAS) on ENVISAT are compared for the period from January 2008 to March 2012. The global CTH agreement of about 1 km is observed, which is smaller than the vertical field of view of both instruments. Lower stratospheric aerosols from volcanic eruptions occasionally interfere with the cloud retrieval and inhibit the detection of tropospheric clouds. The aerosol impact on cloud retrievals was studied for the volcanoes Kasatochi (August 2008), Sarychev Peak (June 2009), and Nabro (June 2011). Long-lasting aerosol scattering is detected after these events in the Northern Hemisphere for heights above 12.5 km in tropical and polar latitudes. Aerosol top heights up to about 22 km are found in 2009 and the enhanced lower stratospheric aerosol layer persisted for about 7 months. In August 2009 about 82 % of the lower stratosphere between 30 and 70° N was filled with scattering particles and nearly 50 % in October 2008.

Radiative Transfer and Satellite Remote Sensing of Cirrus Clouds Using FIRE-2-IFO Data

NASA Technical Reports Server (NTRS)

2000-01-01

Under the support of the NASA grant, we have developed a new geometric-optics model (GOM2) for the calculation of the single-scattering and polarization properties for arbitrarily oriented hexagonal ice crystals. From comparisons with the results computed by the finite difference time domain (FDTD) method, we show that the novel geometric-optics can be applied to the computation of the extinction cross section and single-scattering albedo for ice crystals with size parameters along the minimum dimension as small as approximately 6. We demonstrate that the present model converges to the conventional ray tracing method for large size parameters and produces single-scattering results close to those computed by the FDTD method for size parameters along the minimum dimension smaller than approximately 20. We demonstrate that neither the conventional geometric optics method nor the Lorenz-Mie theory can be used to approximate the scattering, absorption, and polarization features for hexagonal ice crystals with size parameters from approximately 5 to 20. On the satellite remote sensing algorithm development and validation, we have developed a numerical scheme to identify multilayer cirrus cloud systems using AVHRR data. We have applied this scheme to the satellite data collected over the FIRE-2-IFO area during nine overpasses within seven observation dates. Determination of the threshold values used in the detection scheme are based on statistical analyses of these satellite data.

A Cloud Mask for AIRS

NASA Technical Reports Server (NTRS)

Brubaker, N.; Jedlovec, G. J.

2004-01-01

With the preliminary release of AIRS Level 1 and 2 data to the scientific community, there is a growing need for an accurate AIRS cloud mask for data assimilation studies and in producing products derived from cloud free radiances. Current cloud information provided with the AIRS data are limited or based on simplified threshold tests. A multispectral cloud detection approach has been developed for AIRS that utilizes the hyper-spectral capabilities to detect clouds based on specific cloud signatures across the short wave and long wave infrared window regions. This new AIRS cloud mask has been validated against the existing AIRS Level 2 cloud product and cloud information derived from MODIS. Preliminary results for both day and night applications over the continental U.S. are encouraging. Details of the cloud detection approach and validation results will be presented at the conference.

Polaron-like vortices, dissociation transition, and self-induced pinning in magnetic superconductors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bulaevskii, L. N., E-mail: lnb@lanl.gov; Lin, S.-Z.

2013-09-15

Vortices in magnetic superconductors polarize spins nonuniformly and repolarize them when moving. At a low spin relaxation rate and at low bias currents, vortices carrying magnetic polarization clouds become polaron-like and their velocities are determined by the effective drag coefficient that is significantly bigger than the Bardeen-Stephen (BS) one. As the current increases, vortices release polarization clouds and the velocity as well as the voltage in the I-V characteristics jump to values corresponding to the BS drag coefficient at a critical current J{sub c}. The nonuniform components of the magnetic field and magnetization drop as the velocity increases, resulting inmore » weaker polarization and a discontinuous dynamic dissociation depinning transition. Experimentally, the jump shows up as a depinning transition and the corresponding current at the jump is the depinning current. As the current decreases, on the way back, vortices are retrapped by polarization clouds at the current J{sub r} < J{sub c}. As a result, the polaronic effect suppresses dissipation and enhances the critical current. Borocarbides (RE)Ni{sub 2}B{sub 2}C with a short penetration length and highly polarizable rare earth spins seem to be optimal systems for a detailed study of vortex polaron formation by measuring I-V characteristics. We also propose to use a superconductor-magnet multilayer structure to study polaronic mechanism of pinning with the goal to achieve high critical currents. The magnetic layers should have large magnetic susceptibility to enhance the coupling between vortices and magnetization in magnetic layers while the relaxation of the magnetization should be slow. For Nb and a proper magnet multilayer structure, we estimate the critical current density J{sub c} {approx} 10{sup 9} A/m{sup 2} at the magnetic field B Almost-Equal-To 1 T.« less

Improvements in Night-Time Low Cloud Detection and MODIS-Style Cloud Optical Properties from MSG SEVIRI

NASA Technical Reports Server (NTRS)

Wind, Galina (Gala); Platnick, Steven; Riedi, Jerome

2011-01-01

The MODIS cloud optical properties algorithm (MOD06IMYD06 for Terra and Aqua MODIS, respectively) slated for production in Data Collection 6 has been adapted to execute using available channels on MSG SEVIRI. Available MODIS-style retrievals include IR Window-derived cloud top properties, using the new Collection 6 cloud top properties algorithm, cloud optical thickness from VISINIR bands, cloud effective radius from 1.6 and 3.7Jlm and cloud ice/water path. We also provide pixel-level uncertainty estimate for successful retrievals. It was found that at nighttime the SEVIRI cloud mask tends to report unnaturally low cloud fraction for marine stratocumulus clouds. A correction algorithm that improves detection of such clouds has been developed. We will discuss the improvements to nighttime low cloud detection for SEVIRI and show examples and comparisons with MODIS and CALIPSO. We will also show examples of MODIS-style pixel-level (Level-2) cloud retrievals for SEVIRI with comparisons to MODIS.

Construction of photoelectrochemical thrombin aptasensor via assembling multilayer of graphene-CdS nanocomposites.

PubMed

Shangguan, Li; Zhu, Wei; Xue, Yanchun; Liu, Songqin

2015-02-15

A photoelectrochemical (PEC) aptasensor for highly sensitive and specific detection of thrombin was developed by using graphene–CdS nanocomposites multilayer as photoactive species and electroactive mediator hexaammineruthenium(III) chloride (Ru(NH(3))(6)(3+)) as signal enhancer. Graphene–CdS nanocomposites (G–CdS) were synthesized by one-pot reduction of oxide graphene and CdCl2 with thioacetamide. The photoactive multilayer was prepared by alternative assembly of the negatively charged 3-mercaptopropionic acid modified graphene–CdS nanocomposites (MPA-G–CdS) and the positively charged polyethylenimine (PEI) on ITO electrode. This layer-by-layer assembly method enhanced the stability and homogeneity of the photocurrent readout of G–CdS. Thrombin aptamer was covalently bound to the multilayer by using glutaraldehyde as cross-linking. Electroactive mediator (Ru(NH(3))(6)(3+)) could interact with the DNA phosphate backbone and thus facilitated the electron transfer between G–CdS multilayer and electrode and enhanced the photocurrent. Hybridizing of a long complementary DNA with thrombin aptamer could increase the adsorption amount of (Ru(NH(3))(6)(3+)), which in turn boosted the signal readout. In the presence of target thrombin, the affinity interaction between thrombin and its aptamer resulted in the long complementary DNA releasing from the G–CdS multilayer and decreasing of photocurrent signal. On the basis of G–CdS multilayer as the photoactive species, (Ru (NH(3))(6)(3+)) as an electroactive mediator, and aptamer as a recognition module, a high sensitive PEC aptasensor for thrombin detection was proposed. The thrombin aptasensor displayed a linear range from 2.0 pM to 600.0 pM and a detection limit of 1.0 pM. The present strategy provided a promising ideology for the future development of PEC biosensor. Copyright © 2014 Elsevier B.V. All rights reserved.

A New Cloud and Aerosol Layer Detection Method Based on Micropulse Lidar Measurements

NASA Astrophysics Data System (ADS)

Wang, Q.; Zhao, C.; Wang, Y.; Li, Z.; Wang, Z.; Liu, D.

2014-12-01

A new algorithm is developed to detect aerosols and clouds based on micropulse lidar (MPL) measurements. In this method, a semi-discretization processing (SDP) technique is first used to inhibit the impact of increasing noise with distance, then a value distribution equalization (VDE) method is introduced to reduce the magnitude of signal variations with distance. Combined with empirical threshold values, clouds and aerosols are detected and separated. This method can detect clouds and aerosols with high accuracy, although classification of aerosols and clouds is sensitive to the thresholds selected. Compared with the existing Atmospheric Radiation Measurement (ARM) program lidar-based cloud product, the new method detects more high clouds. The algorithm was applied to a year of observations at both the U.S. Southern Great Plains (SGP) and China Taihu site. At SGP, the cloud frequency shows a clear seasonal variation with maximum values in winter and spring, and shows bi-modal vertical distributions with maximum frequency at around 3-6 km and 8-12 km. The annual averaged cloud frequency is about 50%. By contrast, the cloud frequency at Taihu shows no clear seasonal variation and the maximum frequency is at around 1 km. The annual averaged cloud frequency is about 15% higher than that at SGP.

Analysis of multilayer and single layer X-ray detectors for contrast-enhanced mammography using imaging task

NASA Astrophysics Data System (ADS)

Allec, Nicholas; Abbaszadeh, Shiva; Karim, Karim S.

2011-03-01

A multilayer (single-shot) detector has previously been proposed for contrast-enhanced mammography. The multilayer detector has the benefit of avoiding motion artifacts due to simultaneous acquisition of both high and low energy images. A single layer (dual-shot) detector has the benefit of better control over the energy separation since the incident beams can be produced and filtered separately. In this paper the performance of the multilayer detector is compared to that of a single layer detector using an ideal observer detectability index which is determined from an extended cascaded systems model and a defined imaging task. The detectors are assumed to have amorphous selenium direct conversion layers, however the same theoretical techniques used here may be applied to other types of integrating detectors. The anatomical noise caused by variation of glandularity within the breast is known to dominate the noise power spectrum at low frequencies due to its inverse power law dependence and is thus taken into account in our model to provide an accurate estimate of the detectability index. The conditions leading to the optimal detectability index, such as tube voltage, filtration, and weight factor are reported for both detector designs.

An efficient cloud detection method for high resolution remote sensing panchromatic imagery

NASA Astrophysics Data System (ADS)

Li, Chaowei; Lin, Zaiping; Deng, Xinpu

2018-04-01

In order to increase the accuracy of cloud detection for remote sensing satellite imagery, we propose an efficient cloud detection method for remote sensing satellite panchromatic images. This method includes three main steps. First, an adaptive intensity threshold value combined with a median filter is adopted to extract the coarse cloud regions. Second, a guided filtering process is conducted to strengthen the textural features difference and then we conduct the detection process of texture via gray-level co-occurrence matrix based on the acquired texture detail image. Finally, the candidate cloud regions are extracted by the intersection of two coarse cloud regions above and we further adopt an adaptive morphological dilation to refine them for thin clouds in boundaries. The experimental results demonstrate the effectiveness of the proposed method.

MSG SEVIRI Applications for Weather and Climate: Cloud Properties and Calibrations

NASA Technical Reports Server (NTRS)

Minnis, Patrick; Nguyen, Louis; Smith, William L.; Palikonda, Rabindra; Doelling, David R.; Ayers, J. Kirk; Trepte, Qing Z.; Chang, Fu-Lung

2006-01-01

SEVIRI data are cross-calibrated against the corresponding Aqua and Terra MODIS channels. Compared to Terra MODIS, no significant trends are evident in the 0.65, 0.86, and 1.6 micron channel gains between May 2004 and May 2006, indicating excellent stability in the solar-channel sensors. On average, the corresponding Terra reflectances are 12, 14, and 1% greater than the their SEVIRI counterparts. The Terra 3.8- micron channel brightness temperatures T are 7 and 4 K greater than their SEVIRI counterparts during day and night, respectively. The average differences between T for MODIS and SEVIRI 8.6, 10.8, 12.0, and 13.3- micron channels are between 0.5 and 2 K. The cloud properties are being derived hourly over Europe and, in initial comparisons, agree well with surface observations. Errors caused by residual calibration uncertainties, terminator conditions, and inaccurate temperature and humidity profiles are still problematic. Future versions will address those errors and the effects of multilayered clouds.

Comparison of Cloud Detection Using the CERES-MODIS Ed4 and LaRC AVHRR Cloud Masks and CALIPSO Vertical Feature Mask

NASA Astrophysics Data System (ADS)

Trepte, Q. Z.; Minnis, P.; Palikonda, R.; Bedka, K. M.; Sun-Mack, S.

2011-12-01

Accurate detection of cloud amount and distribution using satellite observations is crucial in determining cloud radiative forcing and earth energy budget. The CERES-MODIS (CM) Edition 4 cloud mask is a global cloud detection algorithm for application to Terra and Aqua MODIS data with the aid of other ancillary data sets. It is used operationally for the NASA's Cloud and Earth's Radiant Energy System (CERES) project. The LaRC AVHRR cloud mask, which uses only five spectral channels, is based on a subset of the CM cloud mask which employs twelve MODIS channels. The LaRC mask is applied to AVHRR data for the NOAA Climate Data Record Program. Comparisons among the CM Ed4, and LaRC AVHRR cloud masks and the CALIPSO Vertical Feature Mask (VFM) constitute a powerful means for validating and improving cloud detection globally. They also help us understand the strengths and limitations of the various cloud retrievals which use either active and passive satellite sensors. In this paper, individual comparisons will be presented for different types of clouds over various surfaces, including daytime and nighttime, and polar and non-polar regions. Additionally, the statistics of the global, regional, and zonal cloud occurrence and amount from the CERES Ed4, AVHRR cloud masks and CALIPSO VFM will be discussed.

Electrical spin injection and detection in molybdenum disulfide multilayer channel

PubMed Central

Liang, Shiheng; Yang, Huaiwen; Renucci, Pierre; Tao, Bingshan; Laczkowski, Piotr; Mc-Murtry, Stefan; Wang, Gang; Marie, Xavier; George, Jean-Marie; Petit-Watelot, Sébastien; Djeffal, Abdelhak; Mangin, Stéphane; Jaffrès, Henri; Lu, Yuan

2017-01-01

Molybdenum disulfide has recently emerged as a promising two-dimensional semiconducting material for nano-electronic, opto-electronic and spintronic applications. However, the demonstration of an electron spin transport through a semiconducting MoS2 channel remains challenging. Here we show the evidence of the electrical spin injection and detection in the conduction band of a multilayer MoS2 semiconducting channel using a two-terminal spin-valve configuration geometry. A magnetoresistance around 1% has been observed through a 450 nm long, 6 monolayer thick MoS2 channel with a Co/MgO tunnelling spin injector and detector. It is found that keeping a good balance between the interface resistance and channel resistance is mandatory for the observation of the two-terminal magnetoresistance. Moreover, the electron spin-relaxation is found to be greatly suppressed in the multilayer MoS2 channel with an in-plane spin polarization. The long spin diffusion length (approximately ∼235 nm) could open a new avenue for spintronic applications using multilayer transition metal dichalcogenides. PMID:28387252

Label-Free Detection of Live Cancer Cells and DNA Hybridization using 3D Multilayered Plasmonic Biosensor.

PubMed

Zhu, Shuyan; Li, Hualin; Yang, Mengsu; Pang, Stella W

2018-05-31

Three-dimensional (3D) multilayered plasmonic structures consisting of Au submicrometric squares on top of SU-8 submicrometric pillars, Au asymmetrical submicrometric structures in the middle, and Au asymmetrical submicrometric holes at the bottom were fabricated through reversal nanoimprint technology. Compared with two-dimensional and quasi-3D plasmonic structures, the 3D multilayered plasmonic structures showed higher electromagnetic field intensity, longer plasmon decay length and larger plasmon sensing area, which are desirable for highly sensitive localized surface plasmonic resonance biosensors. The sensitivity and resonance peak wavelength of the 3D multilayered plasmonic structures could be adjusted by varying the offset between the top and bottom SU-8 submicrometric pillars from 31% to 56%, and the highest sensitivity of 382 and 442 nm/refractive index unit were observed for resonance peaks at 581 and 805 nm, respectively. Live lung cancer A549 cells with a low concentration of 5×103 cells/ml and a low sample volume of 2 µl could be detected by the 3D multilayered plasmonic structures integrated in a microfluidic system. The 3D plasmonic biosensors also had the advantages of detecting DNA hybridization by capturing the complementary target DNA in the low concentration range of 10-14 to 10-7 M, and providing a large peak shift of 82 nm for capturing 10-7 M complementary target DNA without additional signal amplification. Creative Commons Attribution license.

Ground-based Nighttime Cloud Detection Using a Commercial Digital Camera: Observations at Manila Observatory (14.64N, 121.07E)

NASA Astrophysics Data System (ADS)

Gacal, G. F. B.; Tan, F.; Antioquia, C. T.; Lagrosas, N.

2014-12-01

Cloud detection during nighttime poses a real problem to researchers because of a lack of optimum sensors that can specifically detect clouds during this time of the day. Hence, lidars and satellites are currently some of the instruments that are being utilized to determine cloud presence in the atmosphere. These clouds play a significant role in the night weather system for the reason that they serve as barriers of thermal radiation from the Earth and thereby reflecting this radiation back to the Earth. This effectively lowers the rate of decreasing temperature in the atmosphere at night. The objective of this study is to detect cloud occurrences at nighttime for the purpose of studying patterns of cloud occurrence and the effects of clouds on local weather. In this study, a commercial camera (Canon Powershot A2300) is operated continuously to capture nighttime clouds. The camera is situated inside a weather-proof box with a glass cover and is placed on the rooftop of the Manila Observatory building to gather pictures of the sky every 5min to observe cloud dynamics and evolution in the atmosphere. To detect pixels with clouds, the pictures are converted from its native JPEG to grayscale format. The pixels are then screened for clouds by looking at the values of pixels with and without clouds. In grayscale format, pixels with clouds have greater pixel values than pixels without clouds. Based on the observations, 0.34 of the maximum pixel value is enough to discern pixels with clouds from pixels without clouds. Figs. 1a & 1b are sample unprocessed pictures of cloudless night (May 22-23, 2014) and cloudy skies (May 23-24, 2014), respectively. Figs.1c and 1d show percentage of occurrence of nighttime clouds on May 22-23 and May 23-24, 2014, respectively. The cloud occurrence in a pixel is defined as the ratio of the number times when the pixel has clouds to the total number of observations. Fig. 1c shows less than 50% cloud occurrence while Fig. 1d shows cloud occurrence more than what is shown in Fig. 1c. These graphs show the capability of the camera to detect and measure the cloud occurrence at nighttime. Continuous collection of nighttime pictures is currently implemented. In regions where there is a dearth of scientific data, the measured nighttime cloud occurrence will serve as a baseline for future cloud studies in this part of the world.

Spatially Varying Spectrally Thresholds for MODIS Cloud Detection

NASA Technical Reports Server (NTRS)

Haines, S. L.; Jedlovec, G. J.; Lafontaine, F.

2004-01-01

The EOS science team has developed an elaborate global MODIS cloud detection procedure, and the resulting MODIS product (MOD35) is used in the retrieval process of several geophysical parameters to mask out clouds. While the global application of the cloud detection approach appears quite robust, the product has some shortcomings on the regional scale, often over determining clouds in a variety of settings, particularly at night. This over-determination of clouds can cause a reduction in the spatial coverage of MODIS derived clear-sky products. To minimize this problem, a new regional cloud detection method for use with MODIS data has been developed at NASA's Global Hydrology and Climate Center (GHCC). The approach is similar to that used by the GHCC for GOES data over the continental United States. Several spatially varying thresholds are applied to MODIS spectral data to produce a set of tests for detecting clouds. The thresholds are valid for each MODIS orbital pass, and are derived from 20-day composites of GOES channels with similar wavelengths to MODIS. This paper and accompanying poster will introduce the GHCC MODIS cloud mask, provide some examples, and present some preliminary validation.

Water adsorption on goethite: Application of multilayer adsorption models

NASA Astrophysics Data System (ADS)

Hatch, C. D.; Tumminello, R.; Meredith, R.

2016-12-01

Adsorbed water on the surface of atmospheric mineral dust has recently been shown to significantly affect the ability of mineral dust aerosol to act as cloud condensation nuclei. We have studied water adsorption as a function of relative humidity (RH) on goethite (α-FeO(OH)), a common component of atmospheric mineral dust. The goethite surface area and particle size was determined using BET analysis and with N2 as an adsorbate and scanning electron microscopy, respectively. Water adsorption on the sample was monitored using horizontal attenuated total reflectance Fourier transform infrared (HATR-FTIR) spectroscopy equipped with a flow cell. Water content was determined using Beer's law and the optical constants for bulk water. The results were analyzed using Type II adsorption isotherms to model multilayer adsorption, including BET (Brunauer, Emmet and Teller), FHH (Frenkel, Halsey and Hill) and Freundlich. BET fits to experimental data provide parameters of monolayer coverage, while the FHH and Freundlich isotherms provide insights into multilayer adsorption mechanisms. Results indicate that goethite contains 5% H2O by mass at 50% RH, which increases to 12% by mass at 90% RH. Adsorption parameters and experimental results will be presented.

Automated cloud and shadow detection and filling using two-date Landsat imagery in the United States

USGS Publications Warehouse

Jin, Suming; Homer, Collin G.; Yang, Limin; Xian, George; Fry, Joyce; Danielson, Patrick; Townsend, Philip A.

2013-01-01

A simple, efficient, and practical approach for detecting cloud and shadow areas in satellite imagery and restoring them with clean pixel values has been developed. Cloud and shadow areas are detected using spectral information from the blue, shortwave infrared, and thermal infrared bands of Landsat Thematic Mapper or Enhanced Thematic Mapper Plus imagery from two dates (a target image and a reference image). These detected cloud and shadow areas are further refined using an integration process and a false shadow removal process according to the geometric relationship between cloud and shadow. Cloud and shadow filling is based on the concept of the Spectral Similarity Group (SSG), which uses the reference image to find similar alternative pixels in the target image to serve as replacement values for restored areas. Pixels are considered to belong to one SSG if the pixel values from Landsat bands 3, 4, and 5 in the reference image are within the same spectral ranges. This new approach was applied to five Landsat path/rows across different landscapes and seasons with various types of cloud patterns. Results show that almost all of the clouds were captured with minimal commission errors, and shadows were detected reasonably well. Among five test scenes, the lowest producer's accuracy of cloud detection was 93.9% and the lowest user's accuracy was 89%. The overall cloud and shadow detection accuracy ranged from 83.6% to 99.3%. The pixel-filling approach resulted in a new cloud-free image that appears seamless and spatially continuous despite differences in phenology between the target and reference images. Our methods offer a straightforward and robust approach for preparing images for the new 2011 National Land Cover Database production.

Modeling and Prediction of Monthly Total Ozone Concentrations by Use of an Artificial Neural Network Based on Principal Component Analysis

NASA Astrophysics Data System (ADS)

Chattopadhyay, Surajit; Chattopadhyay, Goutami

2012-10-01

In the work discussed in this paper we considered total ozone time series over Kolkata (22°34'10.92″N, 88°22'10.92″E), an urban area in eastern India. Using cloud cover, average temperature, and rainfall as the predictors, we developed an artificial neural network, in the form of a multilayer perceptron with sigmoid non-linearity, for prediction of monthly total ozone concentrations from values of the predictors in previous months. We also estimated total ozone from values of the predictors in the same month. Before development of the neural network model we removed multicollinearity by means of principal component analysis. On the basis of the variables extracted by principal component analysis, we developed three artificial neural network models. By rigorous statistical assessment it was found that cloud cover and rainfall can act as good predictors for monthly total ozone when they are considered as the set of input variables for the neural network model constructed in the form of a multilayer perceptron. In general, the artificial neural network has good potential for predicting and estimating monthly total ozone on the basis of the meteorological predictors. It was further observed that during pre-monsoon and winter seasons, the proposed models perform better than during and after the monsoon.

A cloud-evaporation parameterization for general ciculation models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schlesinger, M.E.; Oh, J.H.

1993-04-01

An evaporation-zone (EZ) model for cloud evaporation is developed. In this model a cloud consists of I [open quotes]cloudlets,[close quotes] each comprising cloud droplets with radii from zero to r[sub max], the latter value depending on the drop size distribution (DSD). Evaporation occurs only within the EZ comprised of J[le]I cloudlets. When the cloudlet at cloud edge evaporates, the EZ progresses one cloudlet into the cloud's interior. This eventually results in evaporation of the cloud in time t[sub E] = K(H/h)r[sup 2][sub max](1[minus]S[sub e])[sup [minus]1] where H is the cloud thickness, h the EZ thickness, S[sub e] the environmental saturationmore » ratio, and K a constant. Values of t[sub E](1[minus]S[sub e]) versus h are presented for eight observed DSDs. For use in atmospheric general circulation models (GCMs), the cloud evaporation process is represented by dm/dt=[minus](1[minus]S[sub e])m/[tau], where m is the cloud-water mixing ratio and [tau]=K(H/h)r[sup 2][sub max]n[sup [minus]1]. With parameter n chosen sufficiently large, a GCM cloud will evaporate virtually entirely in time t[sub E], for example, 99.3% for n = 5. Values of [tau] for use in the multilayer atmospheric CRCM have been determined by performing ten perpetual-January simulations and ten perpetual-July simulations, each set of ten for prescribed pairs of [tau] values for stratiform ([tau][sub s]) and cumuloform ([tau][sub c]) clouds. An optimum choice of [tau][sub s] and [tau][sub c], based on minimizing the errors of the model's simulated cloudiness, planetary albedo, outgoing longwave radiation, and precipitation, is [tau][sub s]=[tau][sub c] = 3 min. This corresponds to t[sub E](1-S[sub e]) = 15 min for both stratiform and cumuloform clouds; hence, to an EZ thickness of about 0.6-0.8 m for stratus, stratocumulus, and altostratus clouds, 2-3 m for nimbostratus and cumulus clouds, and 17 m for cumulonimbus clouds. 18 refs., 6 figs.« less

Detecting Super-Thin Clouds With Polarized Light

NASA Technical Reports Server (NTRS)

Sun, Wenbo; Videen, Gorden; Mishchenko, Michael I.

2014-01-01

We report a novel method for detecting cloud particles in the atmosphere. Solar radiation backscattered from clouds is studied with both satellite data and a radiative transfer model. A distinct feature is found in the angle of linear polarization of solar radiation that is backscattered from clouds. The dominant backscattered electric field from the clear-sky Earth-atmosphere system is nearly parallel to the Earth surface. However, when clouds are present, this electric field can rotate significantly away from the parallel direction. Model results demonstrate that this polarization feature can be used to detect super-thin cirrus clouds having an optical depth of only 0.06 and super-thin liquid water clouds having an optical depth of only 0.01. Such clouds are too thin to be sensed using any current passive satellite instruments.

Detecting Super-Thin Clouds with Polarized Sunlight

NASA Technical Reports Server (NTRS)

Sun, Wenbo; Videen, Gorden; Mishchenko, Michael I.

2014-01-01

We report a novel method for detecting cloud particles in the atmosphere. Solar radiation backscattered from clouds is studied with both satellite data and a radiative transfer model. A distinct feature is found in the angle of linear polarization of solar radiation that is backscattered from clouds. The dominant backscattered electric field from the clear-sky Earth-atmosphere system is nearly parallel to the Earth surface. However, when clouds are present, this electric field can rotate significantly away from the parallel direction. Model results demonstrate that this polarization feature can be used to detect super-thin cirrus clouds having an optical depth of only 0.06 and super-thin liquid water clouds having an optical depth of only 0.01. Such clouds are too thin to be sensed using any current passive satellite instruments.

Comparison of monthly nighttime cloud fraction products from MODIS and AIRS and ground-based camera over Manila Observatory (14.64N, 121.07E)

NASA Astrophysics Data System (ADS)

Gacal, G. F. B.; Lagrosas, N.

2017-12-01

Cloud detection nowadays is primarily achieved by the utilization of various sensors aboard satellites. These include MODIS Aqua, MODIS Terra, and AIRS with products that include nighttime cloud fraction. Ground-based instruments are, however, only secondary to these satellites when it comes to cloud detection. Nonetheless, these ground-based instruments (e.g., LIDARs, ceilometers, and sky-cameras) offer significant datasets about a particular region's cloud cover values. For nighttime operations of cloud detection instruments, satellite-based instruments are more reliably and prominently used than ground-based ones. Therefore if a ground-based instrument for nighttime operations is operated, it ought to produce reliable scientific datasets. The objective of this study is to do a comparison between the results of a nighttime ground-based instrument (sky-camera) and that of MODIS Aqua and MODIS Terra. A Canon Powershot A2300 is placed ontop of Manila Observatory (14.64N, 121.07E) and is configured to take images of the night sky at 5min intervals. To detect pixels with clouds, the pictures are converted to grayscale format. Thresholding technique is used to screen pixels with cloud and pixels without clouds. If the pixel value is greater than 17, it is considered as a cloud; otherwise, a noncloud (Gacal et al., 2016). This algorithm is applied to the data gathered from Oct 2015 to Oct 2016. A scatter plot between satellite cloud fraction in the area covering the area 14.2877N, 120.9869E, 14.7711N and 121.4539E and ground cloud cover is graphed to find the monthly correlation. During wet season (June - November), the satellite nighttime cloud fraction vs ground measured cloud cover produce an acceptable R2 (Aqua= 0.74, Terra= 0.71, AIRS= 0.76). However, during dry season, poor R2 values are obtained (AIRS= 0.39, Aqua & Terra = 0.01). The high correlation during wet season can be attributed to a high probability that the camera and satellite see the same clouds. However during dry season, the satellite sees high altitude clouds and the camera can not detect these clouds from the ground as it relies on city lights reflected from low level clouds. With this acknowledged disparity, the ground-based camera has the advantage of detecting haze and thin clouds near the ground that are hardly or not detected by the satellites.

Molecular clouds without detectable CO

NASA Technical Reports Server (NTRS)

Blitz, Leo; Bazell, David; Desert, F. Xavier

1990-01-01

The clouds identified by Desert, Bazell, and Boulanger (DBB clouds) in their search for high-latitude molecular clouds were observed in the CO (J = 1-0) line, but only 13 percent of the sample was detected. The remaining 87 percent are diffuse molecular clouds with CO abundances of about 10 to the -6th, a typical value for diffuse clouds. This hypothesis is shown to be consistent with Copernicus data. The DBB clouds are shown to ben an essentially complete catalog of diffuse molecular clouds in the solar vicinity. The total molecular surface density in the vicinity of the sun is then only about 20 percent greater than the 1.3 solar masses/sq pc determined by Dame et al. (1987). Analysis of the CO detections indicates that there is a sharp threshold in extinction of 0.25 mag before CO is detectable and is derived from the IRAS I(100) micron threshold of 4 MJy/sr. This threshold is presumably where the CO abundance exhibits a sharp increase

Molecular clouds without detectable CO

DOE Office of Scientific and Technical Information (OSTI.GOV)

Blitz, L.; Bazell, D.; Desert, F.X.

1990-03-01

The clouds identified by Desert, Bazell, and Boulanger (DBB clouds) in their search for high-latitude molecular clouds were observed in the CO (J = 1-0) line, but only 13 percent of the sample was detected. The remaining 87 percent are diffuse molecular clouds with CO abundances of about 10 to the -6th, a typical value for diffuse clouds. This hypothesis is shown to be consistent with Copernicus data. The DBB clouds are shown to be an essentially complete catalog of diffuse molecular clouds in the solar vicinity. The total molecular surface density in the vicinity of the sun is thenmore » only about 20 percent greater than the 1.3 solar masses/sq pc determined by Dame et al. (1987). Analysis of the CO detections indicates that there is a sharp threshold in extinction of 0.25 mag before CO is detectable and is derived from the IRAS I(100) micron threshold of 4 MJy/sr. This threshold is presumably where the CO abundance exhibits a sharp increase 18 refs.« less

The Dependence of Cloud Property Trend Detection on Absolute Calibration Accuracy of Passive Satellite Sensors

NASA Astrophysics Data System (ADS)

Shea, Y.; Wielicki, B. A.; Sun-Mack, S.; Minnis, P.; Zelinka, M. D.

2016-12-01

Detecting trends in climate variables on global, decadal scales requires highly accurate, stable measurements and retrieval algorithms. Trend uncertainty depends on its magnitude, natural variability, and instrument and retrieval algorithm accuracy and stability. We applied a climate accuracy framework to quantify the impact of absolute calibration on cloud property trend uncertainty. The cloud properties studied were cloud fraction, effective temperature, optical thickness, and effective radius retrieved using the Clouds and the Earth's Radiant Energy System (CERES) Cloud Property Retrieval System, which uses Moderate-resolution Imaging Spectroradiometer measurements (MODIS). Modeling experiments from the fifth phase of the Climate Model Intercomparison Project (CMIP5) agree that net cloud feedback is likely positive but disagree regarding its magnitude, mainly due to uncertainty in shortwave cloud feedback. With the climate accuracy framework we determined the time to detect trends for instruments with various calibration accuracies. We estimated a relationship between cloud property trend uncertainty, cloud feedback, and Equilibrium Climate Sensitivity and also between effective radius trend uncertainty and aerosol indirect effect trends. The direct relationship between instrument accuracy requirements and climate model output provides the level of instrument absolute accuracy needed to reduce climate model projection uncertainty. Different cloud types have varied radiative impacts on the climate system depending on several attributes, such as their thermodynamic phase, altitude, and optical thickness. Therefore, we also conducted these studies by cloud types for a clearer understanding of instrument accuracy requirements needed to detect changes in their cloud properties. Combining this information with the radiative impact of different cloud types helps to prioritize among requirements for future satellite sensors and understanding the climate detection capabilities of existing sensors.

Comparison of cloud optical depth and cloud mask applying BRDF model-based background surface reflectance

NASA Astrophysics Data System (ADS)

Kim, H. W.; Yeom, J. M.; Woo, S. H.

2017-12-01

Over the thin cloud region, satellite can simultaneously detect the reflectance from thin clouds and land surface. Since the mixed reflectance is not the exact cloud information, the background surface reflectance should be eliminated to accurately distinguish thin cloud such as cirrus. In the previous research, Kim et al (2017) was developed the cloud masking algorithm using the Geostationary Ocean Color Imager (GOCI), which is one of significant instruments for Communication, Ocean, and Meteorology Satellite (COMS). Although GOCI has 8 spectral channels including visible and near infra-red spectral ranges, the cloud masking has quantitatively reasonable result when comparing with MODIS cloud mask (Collection 6 MYD35). Especially, we noticed that this cloud masking algorithm is more specialized in thin cloud detections through the validation with Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) data. Because this cloud masking method was concentrated on eliminating background surface effects from the top-of-atmosphere (TOA) reflectance. Applying the difference between TOA reflectance and the bi-directional reflectance distribution function (BRDF) model-based background surface reflectance, cloud areas both thick cloud and thin cloud can be discriminated without infra-red channels which were mostly used for detecting clouds. Moreover, when the cloud mask result was utilized as the input data when simulating BRDF model and the optimized BRDF model-based surface reflectance was used for the optimized cloud masking, the probability of detection (POD) has higher value than POD of the original cloud mask. In this study, we examine the correlation between cloud optical depth (COD) and its cloud mask result. Cloud optical depths mostly depend on the cloud thickness, the characteristic of contents, and the size of cloud contents. COD ranges from less than 0.1 for thin clouds to over 1000 for the huge cumulus due to scattering by droplets. With the cloud optical depth of CALIPSO, the cloud masking result can be more improved since we can figure out how deep cloud is. To validate the cloud mask and the correlation result, the atmospheric retrieval will be computed to compare the difference between TOA reflectance and the simulated surface reflectance.

A cloud detection algorithm using the downwelling infrared radiance measured by an infrared pyrometer of the ground-based microwave radiometer

DOE PAGES

Ahn, M. H.; Han, D.; Won, H. Y.; ...

2015-02-03

For better utilization of the ground-based microwave radiometer, it is important to detect the cloud presence in the measured data. Here, we introduce a simple and fast cloud detection algorithm by using the optical characteristics of the clouds in the infrared atmospheric window region. The new algorithm utilizes the brightness temperature (Tb) measured by an infrared radiometer installed on top of a microwave radiometer. The two-step algorithm consists of a spectral test followed by a temporal test. The measured Tb is first compared with a predicted clear-sky Tb obtained by an empirical formula as a function of surface air temperaturemore » and water vapor pressure. For the temporal test, the temporal variability of the measured Tb during one minute compares with a dynamic threshold value, representing the variability of clear-sky conditions. It is designated as cloud-free data only when both the spectral and temporal tests confirm cloud-free data. Overall, most of the thick and uniform clouds are successfully detected by the spectral test, while the broken and fast-varying clouds are detected by the temporal test. The algorithm is validated by comparison with the collocated ceilometer data for six months, from January to June 2013. The overall proportion of correctness is about 88.3% and the probability of detection is 90.8%, which are comparable with or better than those of previous similar approaches. Two thirds of discrepancies occur when the new algorithm detects clouds while the ceilometer does not, resulting in different values of the probability of detection with different cloud-base altitude, 93.8, 90.3, and 82.8% for low, mid, and high clouds, respectively. Finally, due to the characteristics of the spectral range, the new algorithm is found to be insensitive to the presence of inversion layers.« less

Fabrication, characterization, and biological assessment of multilayer laminin γ2 DNA coatings on titanium surfaces.

PubMed

Yang, Guoli; Zhang, Jing; Dong, Wenjing; Liu, Li; Shi, Jue; Wang, Huiming

2016-03-21

The purpose of this work was to fabricate a multilayer laminin γ2 DNA coating on a titanium surface and evaluate its biological properties. A multilayer laminin γ2 DNA coating was fabricated on titanium using a layer-by-layer assembly technique. The rate of coating degradation was evaluated by detecting the amount of cDNA remaining. Surface analysis using X-ray photoelectron spectroscopy, atomic force microscopy, and surface contact angle measurements revealed the multilayer structure to consist of cationic lipid and confirmed that a laminin γ2 DNA layer could be fabricated on titanium via the layer-by-layer assembly process. The transfection efficiency was highest for five layers in the multilayer structure. HEK293 cells cultured on the multilayer films displayed significantly higher adhesion activity than the control group. The expression of laminin γ2 and the co-localization of integrin β4 and plectin were more obvious in HN4 cells cultured on the multilayer laminin γ2 DNA coating, while weak immunoreactivities were observed in the control group. We concluded that the DNA-loaded multilayer provided a surface with good biocompatibility and that the multilayer laminin γ2 DNA coating might be effective in improving cell adhesion and the formation of hemidesmosomes on titanium surfaces.

Fabrication, characterization, and biological assessment of multilayer laminin γ2 DNA coatings on titanium surfaces

PubMed Central

Yang, Guoli; Zhang, Jing; Dong, Wenjing; Liu, Li; Shi, Jue; Wang, Huiming

2016-01-01

The purpose of this work was to fabricate a multilayer laminin γ2 DNA coating on a titanium surface and evaluate its biological properties. A multilayer laminin γ2 DNA coating was fabricated on titanium using a layer-by-layer assembly technique. The rate of coating degradation was evaluated by detecting the amount of cDNA remaining. Surface analysis using X-ray photoelectron spectroscopy, atomic force microscopy, and surface contact angle measurements revealed the multilayer structure to consist of cationic lipid and confirmed that a laminin γ2 DNA layer could be fabricated on titanium via the layer-by-layer assembly process. The transfection efficiency was highest for five layers in the multilayer structure. HEK293 cells cultured on the multilayer films displayed significantly higher adhesion activity than the control group. The expression of laminin γ2 and the co-localization of integrin β4 and plectin were more obvious in HN4 cells cultured on the multilayer laminin γ2 DNA coating, while weak immunoreactivities were observed in the control group. We concluded that the DNA-loaded multilayer provided a surface with good biocompatibility and that the multilayer laminin γ2 DNA coating might be effective in improving cell adhesion and the formation of hemidesmosomes on titanium surfaces. PMID:26996815

Fabrication, characterization, and biological assessment of multilayer laminin γ2 DNA coatings on titanium surfaces

NASA Astrophysics Data System (ADS)

Yang, Guoli; Zhang, Jing; Dong, Wenjing; Liu, Li; Shi, Jue; Wang, Huiming

2016-03-01

The purpose of this work was to fabricate a multilayer laminin γ2 DNA coating on a titanium surface and evaluate its biological properties. A multilayer laminin γ2 DNA coating was fabricated on titanium using a layer-by-layer assembly technique. The rate of coating degradation was evaluated by detecting the amount of cDNA remaining. Surface analysis using X-ray photoelectron spectroscopy, atomic force microscopy, and surface contact angle measurements revealed the multilayer structure to consist of cationic lipid and confirmed that a laminin γ2 DNA layer could be fabricated on titanium via the layer-by-layer assembly process. The transfection efficiency was highest for five layers in the multilayer structure. HEK293 cells cultured on the multilayer films displayed significantly higher adhesion activity than the control group. The expression of laminin γ2 and the co-localization of integrin β4 and plectin were more obvious in HN4 cells cultured on the multilayer laminin γ2 DNA coating, while weak immunoreactivities were observed in the control group. We concluded that the DNA-loaded multilayer provided a surface with good biocompatibility and that the multilayer laminin γ2 DNA coating might be effective in improving cell adhesion and the formation of hemidesmosomes on titanium surfaces.

Detecting Water Bodies in LANDSAT8 Oli Image Using Deep Learning

NASA Astrophysics Data System (ADS)

Jiang, W.; He, G.; Long, T.; Ni, Y.

2018-04-01

Water body identifying is critical to climate change, water resources, ecosystem service and hydrological cycle. Multi-layer perceptron(MLP) is the popular and classic method under deep learning framework to detect target and classify image. Therefore, this study adopts this method to identify the water body of Landsat8. To compare the performance of classification, the maximum likelihood and water index are employed for each study area. The classification results are evaluated from accuracy indices and local comparison. Evaluation result shows that multi-layer perceptron(MLP) can achieve better performance than the other two methods. Moreover, the thin water also can be clearly identified by the multi-layer perceptron. The proposed method has the application potential in mapping global scale surface water with multi-source medium-high resolution satellite data.

Validation of VIIRS Cloud Base Heights at Night Using Ground and Satellite Measurements over Alaska

NASA Astrophysics Data System (ADS)

NOH, Y. J.; Miller, S. D.; Seaman, C.; Forsythe, J. M.; Brummer, R.; Lindsey, D. T.; Walther, A.; Heidinger, A. K.; Li, Y.

2016-12-01

Knowledge of Cloud Base Height (CBH) is critical to describing cloud radiative feedbacks in numerical models and is of practical significance to aviation communities. We have developed a new CBH algorithm constrained by Cloud Top Height (CTH) and Cloud Water Path (CWP) by performing a statistical analysis of A-Train satellite data. It includes an extinction-based method for thin cirrus. In the algorithm, cloud geometric thickness is derived with upstream CTH and CWP input and subtracted from CTH to generate the topmost layer CBH. The CBH information is a key parameter for an improved Cloud Cover/Layers product. The algorithm has been applied to the Visible Infrared Imaging Radiometer Suite (VIIRS) onboard the Suomi NPP spacecraft. Nighttime cloud optical properties for CWP are retrieved from the nighttime lunar cloud optical and microphysical properties (NLCOMP) algorithm based on a lunar reflectance model for the VIIRS Day/Night Band (DNB) measuring nighttime visible light such as moonlight. The DNB has innovative capabilities to fill the polar winter and nighttime gap of cloud observations which has been an important shortfall from conventional radiometers. The CBH products have been intensively evaluated against CloudSat data. The results showed the new algorithm yields significantly improved performance over the original VIIRS CBH algorithm. However, since CloudSat is now operational during daytime only due to a battery anomaly, the nighttime performance has not been fully assessed. This presentation will show our approach to assess the performance of the CBH algorithm at night. VIIRS CBHs are retrieved over the Alaska region from October 2015 to April 2016 using the Clouds from AVHRR Extended (CLAVR-x) processing system. Ground-based measurements from ceilometer and micropulse lidar at the Atmospheric Radiation Measurement (ARM) site on the North Slope of Alaska are used for the analysis. Local weather conditions are checked using temperature and precipitation observations at the site. CALIPSO data with near-simultaneous colocation are added for multi-layered cloud cases which may have high clouds aloft beyond the ground measurements. Multi-month statistics of performance and case studies will be shown. Additional efforts for algorithm refinements will be also discussed.

MR-based detection of individual histotripsy bubble clouds formed in tissues and phantoms.

PubMed

Allen, Steven P; Hernandez-Garcia, Luis; Cain, Charles A; Hall, Timothy L

2016-11-01

To demonstrate that MR sequences can detect individual histotripsy bubble clouds formed inside intact tissues. A line-scan and an EPI sequence were sensitized to histotripsy by inserting a bipolar gradient whose lobes bracketed the lifespan of a histotripsy bubble cloud. Using a 7 Tesla, small-bore scanner, these sequences monitored histotripsy clouds formed in an agar phantom and in vitro porcine liver and brain. The bipolar gradients were adjusted to apply phase with k-space frequencies of 10, 300 or 400 cm -1 . Acoustic pressure amplitude was also varied. Cavitation was simultaneously monitored using a passive cavitation detection system. Each image captured local signal loss specific to an individual bubble cloud. In the agar phantom, this signal loss appeared only when the transducer output exceeded the cavitation threshold pressure. In tissues, bubble clouds were immediately detected when the gradients created phase with k-space frequencies of 300 and 400 cm -1 . When the gradients created phase with a k-space frequency of 10 cm -1 , individual bubble clouds were not detectable until many acoustic pulses had been applied to the tissue. Cavitation-sensitive MR-sequences can detect single histotripsy bubble clouds formed in biologic tissue. Detection is influenced by the sensitizing gradients and treatment history. Magn Reson Med 76:1486-1493, 2016. © 2015 International Society for Magnetic Resonance in Medicine. © 2015 International Society for Magnetic Resonance in Medicine.

Evaluating the cloud radiative forcing over East Asia during summer simulated by CMIP5 models

NASA Astrophysics Data System (ADS)

Lin, Z.; Wang, Y.; Liu, X.

2017-12-01

A large degree of uncertainty in global climate models (GCMs) can be attributed to the representation of clouds and its radiative forcing (CRF). In this study, the simulated CRFs, total cloud fraction (CF) and cloud properties over East Asia from 20 CMIP5 AMIP models are evaluated and compared with multiple satellite observations, and the possible causes for the CRF bias in the CMIP5 models are then investigated. Based on the satellite observation, strong Long wave CRF (LWCRF) and Short wave CRF (SWCRF) are found to be located over Southwestern China, with minimum SWCRF less than -130Wm-2 and this is associated with the large amount of cloud in the region. By contrast, weak CRFs are located over Northwest China and Western Pacific region because of less cloud amount. In Northeastern China, the strong SWCRF and week LWCRF can be found due to the dominant low-level cloud. In Eastern China, the CRFs is moderate due to the co-existence of the multi-layer cloud. CMIP5 models can basically capture the structure of CRFs in East Asia, with the spatial correlation coefficient between 0.5 and 0.9. But most models underestimate CRFs in East Asia, which is highly associated with the underestimation of cloud amount in the region. The performance of CMIP5 models varies in different part of East Asian region, with a larger deviation in Eastern China (EC). Further investigation suggests that, underestimation of the cloud amount in EC can lead to the weak bias of CRFs in EC, however, this CRF bias can be cancelled out by the overestimation effect of CRF due to excessive cloud optical depth (COD) simulated by the models. The annual cycle of simulated CRF over Eastern China is also examined, and it is found, CMIP models are unable to reproduce the northward migration of CRF in summer monsoon season, which is closely related with northward shift of East Asian summer monsoon rain belt.

The Radiative Consistency of Atmospheric Infrared Sounder and Moderate Resolution Imaging Spectroradiometer Cloud Retrievals

NASA Technical Reports Server (NTRS)

Kahn, Brian H.; Fishbein, Evan; Nasiri, Shaima L.; Eldering, Annmarie; Fetzer, Eric J.; Garay, Michael J.; Lee, Sung-Yung

2007-01-01

The consistency of cloud top temperature (Tc) and effective cloud fraction (f) retrieved by the Atmospheric Infrared Sounder (AIRS)/Advanced Microwave Sounding Unit (AMSU) observation suite and the Moderate Resolution Imaging Spectroradiometer (MODIS) on the EOS-Aqua platform are investigated. Collocated AIRS and MODIS TC and f are compared via an 'effective scene brightness temperature' (Tb,e). Tb,e is calculated with partial field of view (FOV) contributions from TC and surface temperature (TS), weighted by f and 1-f, respectively. AIRS reports up to two cloud layers while MODIS reports up to one. However, MODIS reports TC, TS, and f at a higher spatial resolution than AIRS. As a result, pixel-scale comparisons of TC and f are difficult to interpret, demonstrating the need for alternatives such as Tb,e. AIRS-MODIS Tb,e differences ((Delta)Tb,e) for identical observing scenes are useful as a diagnostic for cloud quantity comparisons. The smallest values of DTb,e are for high and opaque clouds, with increasing scatter in (Delta)Tb,e for clouds of smaller opacity and lower altitude. A persistent positive bias in DTb,e is observed in warmer and low-latitude scenes, characterized by a mixture of MODIS CO2 slicing and 11-mm window retrievals. These scenes contain heterogeneous cloud cover, including mixtures of multilayered cloudiness and misplaced MODIS cloud top pressure. The spatial patterns of (Delta)Tb,e are systematic and do not correlate well with collocated AIRS-MODIS radiance differences, which are more random in nature and smaller in magnitude than (Delta)Tb,e. This suggests that the observed inconsistencies in AIRS and MODIS cloud fields are dominated by retrieval algorithm differences, instead of differences in the observed radiances. The results presented here have implications for the validation of cloudy satellite retrieval algorithms, and use of cloud products in quantitative analyses.

Automated detection of cloud and cloud-shadow in single-date Landsat imagery using neural networks and spatial post-processing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hughes, Michael J.; Hayes, Daniel J

2014-01-01

Use of Landsat data to answer ecological questions is contingent on the effective removal of cloud and cloud shadow from satellite images. We develop a novel algorithm to identify and classify clouds and cloud shadow, \\textsc{sparcs}: Spacial Procedures for Automated Removal of Cloud and Shadow. The method uses neural networks to determine cloud, cloud-shadow, water, snow/ice, and clear-sky membership of each pixel in a Landsat scene, and then applies a set of procedures to enforce spatial rules. In a comparison to FMask, a high-quality cloud and cloud-shadow classification algorithm currently available, \\textsc{sparcs} performs favorably, with similar omission errors for cloudsmore » (0.8% and 0.9%, respectively), substantially lower omission error for cloud-shadow (8.3% and 1.1%), and fewer errors of commission (7.8% and 5.0%). Additionally, textsc{sparcs} provides a measure of uncertainty in its classification that can be exploited by other processes that use the cloud and cloud-shadow detection. To illustrate this, we present an application that constructs obstruction-free composites of images acquired on different dates in support of algorithms detecting vegetation change.« less

Superconducting nanowire single-photon detectors with non-periodic dielectric multilayers.

PubMed

Yamashita, Taro; Waki, Kentaro; Miki, Shigehito; Kirkwood, Robert A; Hadfield, Robert H; Terai, Hirotaka

2016-10-24

We present superconducting nanowire single-photon detectors (SSPDs) on non-periodic dielectric multilayers, which enable us to design a variety of wavelength dependences of optical absorptance by optimizing the dielectric multilayer. By adopting a robust simulation to optimize the dielectric multilayer, we designed three types of SSPDs with target wavelengths of 500 nm, 800 nm, and telecom range respectively. We fabricated SSPDs based on the optimized designs for 500 and 800 nm, and evaluated the system detection efficiency at various wavelengths. The results obtained confirm that the designed SSPDs with non-periodic dielectric multilayers worked well. This versatile device structure can be effective for multidisciplinary applications in fields such as the life sciences and remote sensing that require high efficiency over a precise spectral range and strong signal rejection at other wavelengths.

A cloud masking algorithm for EARLINET lidar systems

NASA Astrophysics Data System (ADS)

Binietoglou, Ioannis; Baars, Holger; D'Amico, Giuseppe; Nicolae, Doina

2015-04-01

Cloud masking is an important first step in any aerosol lidar processing chain as most data processing algorithms can only be applied on cloud free observations. Up to now, the selection of a cloud-free time interval for data processing is typically performed manually, and this is one of the outstanding problems for automatic processing of lidar data in networks such as EARLINET. In this contribution we present initial developments of a cloud masking algorithm that permits the selection of the appropriate time intervals for lidar data processing based on uncalibrated lidar signals. The algorithm is based on a signal normalization procedure using the range of observed values of lidar returns, designed to work with different lidar systems with minimal user input. This normalization procedure can be applied to measurement periods of only few hours, even if no suitable cloud-free interval exists, and thus can be used even when only a short period of lidar measurements is available. Clouds are detected based on a combination of criteria including the magnitude of the normalized lidar signal and time-space edge detection performed using the Sobel operator. In this way the algorithm avoids misclassification of strong aerosol layers as clouds. Cloud detection is performed using the highest available time and vertical resolution of the lidar signals, allowing the effective detection of low-level clouds (e.g. cumulus humilis). Special attention is given to suppress false cloud detection due to signal noise that can affect the algorithm's performance, especially during day-time. In this contribution we present the details of algorithm, the effect of lidar characteristics (space-time resolution, available wavelengths, signal-to-noise ratio) to detection performance, and highlight the current strengths and limitations of the algorithm using lidar scenes from different lidar systems in different locations across Europe.

Secure and robust cloud computing for high-throughput forensic microsatellite sequence analysis and databasing.

PubMed

Bailey, Sarah F; Scheible, Melissa K; Williams, Christopher; Silva, Deborah S B S; Hoggan, Marina; Eichman, Christopher; Faith, Seth A

2017-11-01

Next-generation Sequencing (NGS) is a rapidly evolving technology with demonstrated benefits for forensic genetic applications, and the strategies to analyze and manage the massive NGS datasets are currently in development. Here, the computing, data storage, connectivity, and security resources of the Cloud were evaluated as a model for forensic laboratory systems that produce NGS data. A complete front-to-end Cloud system was developed to upload, process, and interpret raw NGS data using a web browser dashboard. The system was extensible, demonstrating analysis capabilities of autosomal and Y-STRs from a variety of NGS instrumentation (Illumina MiniSeq and MiSeq, and Oxford Nanopore MinION). NGS data for STRs were concordant with standard reference materials previously characterized with capillary electrophoresis and Sanger sequencing. The computing power of the Cloud was implemented with on-demand auto-scaling to allow multiple file analysis in tandem. The system was designed to store resulting data in a relational database, amenable to downstream sample interpretations and databasing applications following the most recent guidelines in nomenclature for sequenced alleles. Lastly, a multi-layered Cloud security architecture was tested and showed that industry standards for securing data and computing resources were readily applied to the NGS system without disadvantageous effects for bioinformatic analysis, connectivity or data storage/retrieval. The results of this study demonstrate the feasibility of using Cloud-based systems for secured NGS data analysis, storage, databasing, and multi-user distributed connectivity. Copyright © 2017 Elsevier B.V. All rights reserved.

An Automated Cloud-edge Detection Algorithm Using Cloud Physics and Radar Data

NASA Technical Reports Server (NTRS)

Ward, Jennifer G.; Merceret, Francis J.; Grainger, Cedric A.

2003-01-01

An automated cloud edge detection algorithm was developed and extensively tested. The algorithm uses in-situ cloud physics data measured by a research aircraft coupled with ground-based weather radar measurements to determine whether the aircraft is in or out of cloud. Cloud edges are determined when the in/out state changes, subject to a hysteresis constraint. The hysteresis constraint prevents isolated transient cloud puffs or data dropouts from being identified as cloud boundaries. The algorithm was verified by detailed manual examination of the data set in comparison to the results from application of the automated algorithm.

Enhancing a Simple MODIS Cloud Mask Algorithm for the Landsat Data Continuity Mission

NASA Technical Reports Server (NTRS)

Wilson, Michael J.; Oreopoulos, Lazarous

2011-01-01

The presence of clouds in images acquired by the Landsat series of satellites is usually an undesirable, but generally unavoidable fact. With the emphasis of the program being on land imaging, the suspended liquid/ice particles of which clouds are made of fully or partially obscure the desired observational target. Knowing the amount and location of clouds in a Landsat scene is therefore valuable information for scene selection, for making clear-sky composites from multiple scenes, and for scheduling future acquisitions. The two instruments in the upcoming Landsat Data Continuity Mission (LDCM) will include new channels that will enhance our ability to detect high clouds which are often also thin in the sense that a large fraction of solar radiation can pass through them. This work studies the potential impact of these new channels on enhancing LDCM's cloud detection capabilities compared to previous Landsat missions. We revisit a previously published scheme for cloud detection and add new tests to capture more of the thin clouds that are harder to detect with the more limited arsenal channels. Since there are no Landsat data yet that include the new LDCM channels, we resort to data from another instrument, MODIS, which has these bands, as well as the other bands of LDCM, to test the capabilities of our new algorithm. By comparing our revised scheme's performance against the performance of the official MODIS cloud detection scheme, we conclude that the new scheme performs better than the earlier scheme which was not very good at thin cloud detection.

Apperception of Clouds in AIRS Data

NASA Technical Reports Server (NTRS)

Huang, Hung-Lung; Smith, William L.

2005-01-01

Our capacity to simulate the radiative characteristics of the Earth system has advanced greatly over the past decade. However, new space based measurements show that idealized simulations might not adequately represent the complexity of nature. For example, AIRS simulated multi-layer cloud clearing research provides an excellent groundwork for early Atmospheric Infra-Red Sounder (AIRS) operational cloud clearing and atmospheric profile retrieval. However, it doesn't reflect the complicated reality of clouds over land and coastal areas. Thus far, operational AIRS/AMSU (Advanced Microwave Sounding Unit) cloud clearing is not only of low yield but also of unsatisfying quality. This is not an argument for avoiding this challenging task, rather a powerful argument for exploring other synergistic approaches, and for adapting these strategies toward improving both indirect and direct use of cloudy infrared sounding data. Ample evidence is shown in this paper that the indirect use of cloudy sounding data by way of cloud clearing is sub-optimal for data assimilation. Improvements are needed in quality control, retrieval yield, and overall cloud clearing retrieval performance. For example, cloud clearing over land, especially over the desert surface, has led to much degraded retrieval quality and often a very low yield of quality controlled cloud cleared radiances. If these indirect cloud cleared radiances are instead to be directly assimilated into NWP models, great caution must be used. Our limited and preliminary cloud clearing results from AIRS/AMSU (with the use of MODIS data) and an AIRS/MODIS synergistic approach have, however, shown that higher spatial resolution multispectral imagery data can provide much needed quality control of the AIRS/AMSU cloud clearing retrieval. When AIRS and Moderate Resolution Imaging Spectroradiometer (MODIS) are used synergistically, a higher spatial resolution over difficult terrain (especially desert areas) can be achieved and with a much improved accuracy. Preliminary statistical analyses of cloud cleared radiances derived from (1) operational AIRS/AMSU, (2) operational AIRS/AMSU plus the use of MODIS data as quality control, and (3) AIRS/MODIS synergistic single channel and two field of views cloud clearing are Our capacity to simulate the radiative characteristics of the Earth system has

A conjugate gradients/trust regions algorithms for training multilayer perceptrons for nonlinear mapping

NASA Technical Reports Server (NTRS)

Madyastha, Raghavendra K.; Aazhang, Behnaam; Henson, Troy F.; Huxhold, Wendy L.

1992-01-01

This paper addresses the issue of applying a globally convergent optimization algorithm to the training of multilayer perceptrons, a class of Artificial Neural Networks. The multilayer perceptrons are trained towards the solution of two highly nonlinear problems: (1) signal detection in a multi-user communication network, and (2) solving the inverse kinematics for a robotic manipulator. The research is motivated by the fact that a multilayer perceptron is theoretically capable of approximating any nonlinear function to within a specified accuracy. The algorithm that has been employed in this study combines the merits of two well known optimization algorithms, the Conjugate Gradients and the Trust Regions Algorithms. The performance is compared to a widely used algorithm, the Backpropagation Algorithm, that is basically a gradient-based algorithm, and hence, slow in converging. The performances of the two algorithms are compared with the convergence rate. Furthermore, in the case of the signal detection problem, performances are also benchmarked by the decision boundaries drawn as well as the probability of error obtained in either case.

The potential influence of multiple scattering on longwave flux and heating rate simulations with clouds

NASA Astrophysics Data System (ADS)

Kuo, C. P.; Yang, P.; Huang, X.; Feldman, D.; Flanner, M.; Kuo, C.; Mlawer, E. J.

2017-12-01

Clouds, which cover approximately 67% of the globe, serve as one of the major modulators in adjusting radiative energy on the Earth. Since rigorous radiative transfer computations including multiple scattering are costly, only absorption is considered in the longwave spectral bands in the radiation sub-models of the general circulation models (GCMs). Quantification of the effect of ignoring longwave scattering for flux and heating rate simulations is performed by using the GCM version of the Longwave Rapid Radiative Transfer Model (RRTMG_LW) with an implementation with the 16-stream Discrete Ordinates Radiative Transfer (DISORT) Program for a Multi-Layered Plane-Parallel Medium in conjunction with the 2010 CCCM products that merge satellite observations from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), the CloudSat, the Clouds and the Earth's Radiant Energy System (CERES) and the Moderate Resolution Imaging Spectrometer (MODIS). One-year global simulations show that neglecting longwave scattering overestimates upward flux at the top of the atmosphere (TOA) and underestimates downward flux at the surface by approximately 2.63 and 1.15 W/m2, respectively. Furthermore, when longwave scattering is included in the simulations, the tropopause is cooled by approximately 0.018 K/day and the surface is heated by approximately 0.028 K/day. As a result, the radiative effects of ignoring longwave scattering and doubling CO2 are comparable in magnitude.

Algorithm for Automated Detection of Edges of Clouds

NASA Technical Reports Server (NTRS)

Ward, Jennifer G.; Merceret, Francis J.

2006-01-01

An algorithm processes cloud-physics data gathered in situ by an aircraft, along with reflectivity data gathered by ground-based radar, to determine whether the aircraft is inside or outside a cloud at a given time. A cloud edge is deemed to be detected when the in/out state changes, subject to a hysteresis constraint. Such determinations are important in continuing research on relationships among lightning, electric charges in clouds, and decay of electric fields with distance from cloud edges.

Improvements to GOES Twilight Cloud Detection over the ARM SGP

NASA Technical Reports Server (NTRS)

Yost, c. R.; Trepte, Q.; Khaiyer, M. M.; Palikonda, R.; Nguyen, L.

2007-01-01

The current ARM satellite cloud products derived from Geostationary Operational Environmental Satellite (GOES) data provide continuous coverage of many cloud properties over the ARM Southern Great Plains domain. However, discontinuities occur during daylight near the terminator, a time period referred to here as twilight. This poster presentation will demonstrate the improvements in cloud detection provided by the improved cloud mask algorithm as well as validation of retrieved cloud properties using surface observations from the Atmospheric Radiation Measurement Southern Great Plains (ARM SGP) site.

Observed aerosol effects on marine cloud nucleation and supersaturation

NASA Astrophysics Data System (ADS)

Russell, Lynn M.; Sorooshian, Armin; Seinfeld, John H.; Albrecht, Bruce A.; Nenes, Athanasios; Leaitch, W. Richard; Macdonald, Anne Marie; Ahlm, Lars; Chen, Yi-Chun; Coggon, Matthew; Corrigan, Ashley; Craven, Jill S.; Flagan, Richard C.; Frossard, Amanda A.; Hawkins, Lelia N.; Jonsson, Haflidi; Jung, Eunsil; Lin, Jack J.; Metcalf, Andrew R.; Modini, Robin; Mülmenstädt, Johannes; Roberts, Greg C.; Shingler, Taylor; Song, Siwon; Wang, Zhen; Wonaschütz, Anna

2013-05-01

Aerosol particles in the marine boundary layer include primary organic and salt particles from sea spray and combustion-derived particles from ships and coastal cities. These particle types serve as nuclei for marine cloud droplet activation, although the particles that activate depend on the particle size and composition as well as the supersaturation that results from cloud updraft velocities. The Eastern Pacific Emitted Aerosol Cloud Experiment (EPEACE) 2011 was a targeted aircraft campaign to assess how different particle types nucleate cloud droplets. As part of E-PEACE 2011, we studied the role of marine particles as cloud droplet nuclei and used emitted particle sources to separate particle-induced feedbacks from dynamical variability. The emitted particle sources included shipboard smoke-generated particles with 0.05-1 μm diameters (which produced tracks measured by satellite and had drop composition characteristic of organic smoke) and combustion particles from container ships with 0.05-0.2 μm diameters (which were measured in a variety of conditions with droplets containing both organic and sulfate components) [1]. Three central aspects of the collaborative E-PEACE results are: (1) the size and chemical composition of the emitted smoke particles compared to ship-track-forming cargo ship emissions as well as background marine particles, with particular attention to the role of organic particles, (2) the characteristics of cloud track formation for smoke and cargo ships, as well as the role of multi-layered low clouds, and (3) the implications of these findings for quantifying aerosol indirect effects. For comparison with the E-PEACE results, the preliminary results of the Stratocumulus Observations of Los-Angeles Emissions Derived Aerosol-Droplets (SOLEDAD) 2012 provided evidence of the cloud-nucleating roles of both marine organic particles and coastal urban pollution, with simultaneous measurements of the effective supersaturations of the clouds in the California coastal region.

Improved Thin Cirrus and Terminator Cloud Detection in CERES Cloud Mask

NASA Technical Reports Server (NTRS)

Trepte, Qing; Minnis, Patrick; Palikonda, Rabindra; Spangenberg, Doug; Haeffelin, Martial

2006-01-01

Thin cirrus clouds account for about 20-30% of the total cloud coverage and affect the global radiation budget by increasing the Earth's albedo and reducing infrared emissions. Thin cirrus, however, are often underestimated by traditional satellite cloud detection algorithms. This difficulty is caused by the lack of spectral contrast between optically thin cirrus and the surface in techniques that use visible (0.65 micron ) and infrared (11 micron ) channels. In the Clouds and the Earth s Radiant Energy System (CERES) Aqua Edition 1 (AEd1) and Terra Edition 3 (TEd3) Cloud Masks, thin cirrus detection is significantly improved over both land and ocean using a technique that combines MODIS high-resolution measurements from the 1.38 and 11 micron channels and brightness temperature differences (BTDs) of 11-12, 8.5-11, and 3.7-11 micron channels. To account for humidity and view angle dependencies, empirical relationships were derived with observations from the 1.38 micron reflectance and the 11-12 and 8.5-11 micron BTDs using 70 granules of MODIS data in 2002 and 2003. Another challenge in global cloud detection algorithms occurs near the day/night terminator where information from the visible 0.65 micron channel and the estimated solar component of 3.7 micron channel becomes less reliable. As a result, clouds are often underestimated or misidentified near the terminator over land and ocean. Comparisons between the CLAVR-x (Clouds from Advanced Very High Resolution Radiometer [AVHRR]) cloud coverage and Geoscience Laser Altimeter System (GLAS) measurements north of 60 N indicate significant amounts of missing clouds from CLAVR-x because this part of the world was near the day/night terminator viewed by AVHRR. Comparisons between MODIS cloud products (MOD06) and GLAS in the same region also show similar difficulties with MODIS cloud retrievals. The consistent detection of clouds through out the day is needed to provide reliable cloud and radiation products for CERES and other research efforts involving the modeling of clouds and their interaction with the radiation budget.

Alignment of a multilayer-coated imaging system using extreme ultraviolet Foucault and Ronchi interferometric testing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ray-Chaudhuri, A.K.; Ng, W.; Cerrina, F.

1995-11-01

Multilayer-coated imaging systems for extreme ultraviolet (EUV) lithography at 13 nm represent a significant challenge for alignment and characterization. The standard practice of utilizing visible light interferometry fundamentally provides an incomplete picture since this technique fails to account for phase effects induced by the multilayer coating. Thus the development of optical techniques at the functional EUV wavelength is required. We present the development of two EUV optical tests based on Foucault and Ronchi techniques. These relatively simple techniques are extremely sensitive due to the factor of 50 reduction in wavelength. Both techniques were utilized to align a Mo--Si multilayer-coated Schwarzschildmore » camera. By varying the illumination wavelength, phase shift effects due to the interplay of multilayer coating and incident angle were uniquely detected. {copyright} {ital 1995} {ital American} {ital Vacuum} {ital Society}« less

1-D grating based SPR biosensor for the detection of lung cancer biomarkers using Vroman effect

NASA Astrophysics Data System (ADS)

Teotia, Pradeep Kumar; Kaler, R. S.

2018-01-01

Grating based surface plasmon resonance waveguide biosensor have been reported for the detection of lung cancer biomarkers using Vroman effect. The proposed grating based multilayered biosensor is designed with high detection accuracy for Epidermal growth factor receptor (EGFR) and also analysed to show high detection accuracy with acceptable sensitivity for both cancer biomarkers. The introduction of periodic grating with multilayer metals generates a good resonance that make it possible for early detection of cancerous cells. Using finite difference time domain method, it is observed wavelength of biosensor get red-shifted on variations of the refractive index due to the presence of both the cancerous bio-markers. The reported detection accuracy and sensitivity of proposed biosensor is quite acceptable for both lung cancer biomarkers i.e. Carcinoembryonic antigen (CEA) and Epidermal growth factor receptor (EGFR) which further offer us label free early detection of lung cancer using these biomarkers.

A satellite-based 13-year climatology of net cloud radiative forcing over the Indian monsoon region

NASA Astrophysics Data System (ADS)

Saud, Trailokya; Dey, Sagnik; Das, Sushant; Dutta, Soumi

2016-12-01

We present a satellite-based 13-year (Mar. 2000-Feb. 2013) climatology of net cloud radiative forcing (CRF) over the Indian monsoon region (0-40°N, 60-100°E) using the Clouds and Earth's Radiant Energy System (CERES) radiation data and explained the net CRF variability in terms of cloud properties retrieved by Moderate Resolution Imaging Spectroradiometer (MODIS). Mean (± 1σ) seasonal shortwave (SW) CRF values averaged over the region are - 82.7 ± 24.5, - 32.1 ± 12.1, - 17.2 ± 5.3 and - 30.2 ± 16.2 W m- 2 respectively for the monsoon (JJAS), post-monsoon (ON), winter (DJF) and pre-monsoon (MAM) seasons; while the corresponding longwave (LW) CRF values are 53.7 ± 14.2, 27.9 ± 10.0, 15.8 ± 7.0 and 25.2 ± 9.1 W m- 2. Regional analysis reveals the largest (least) negative net CRF over the northeast (northwest) rainfall homogeneous zone throughout the year due to the dominance of optically thick high clouds (low cloud fraction, fc). Mean JJAS fc is found to increase (by > 0.01 per year) over large parts of the Arabian Sea, Bay of Bengal and the northwest region. Mean annual net CRF values for cumulus, stratocumulus and stratus (low level), altocumulus, altostratus and nimbostratus (mid-level clouds) and cirrus, cirrostratus and deep-convective (high level) clouds over the Indian monsoon region are estimated to be - 0.8, - 4.7, - 6.9, + 3.3, - 6.3, - 23.3, + 5.4, - 23.3 and - 42.1 W m- 2 respectively. Across a wide range of cloud optical depth (COD) and fc < 0.6, near cancellation of SW cooling by LW warming, is observed for low clouds. Net CRF drops below - 15 W m- 2 for clouds evolving above 400 hPa, mainly in the monsoon season. Our results demonstrate that net CRF variability in the Indian monsoon region can be explained by variability in Cloud Top Pressure (CTP), COD and fc. The study highlights the need for resolving a multi-layer cloud field in the future.

Ice Cloud Optical Thickness and Extinction Estimates from Radar Measurements.

NASA Astrophysics Data System (ADS)

Matrosov, Sergey Y.; Shupe, Matthew D.; Heymsfield, Andrew J.; Zuidema, Paquita

2003-11-01

A remote sensing method is proposed to derive vertical profiles of the visible extinction coefficients in ice clouds from measurements of the radar reflectivity and Doppler velocity taken by a vertically pointing 35-GHz cloud radar. The extinction coefficient and its vertical integral, optical thickness τ, are among the fundamental cloud optical parameters that, to a large extent, determine the radiative impact of clouds. The results obtained with this method could be used as input for different climate and radiation models and for comparisons with parameterizations that relate cloud microphysical parameters and optical properties. An important advantage of the proposed method is its potential applicability to multicloud situations and mixed-phase conditions. In the latter case, it might be able to provide the information on the ice component of mixed-phase clouds if the radar moments are dominated by this component. The uncertainties of radar-based retrievals of cloud visible optical thickness are estimated by comparing retrieval results with optical thicknesses obtained independently from radiometric measurements during the yearlong Surface Heat Budget of the Arctic Ocean (SHEBA) field experiment. The radiometric measurements provide a robust way to estimate τ but are applicable only to optically thin ice clouds without intervening liquid layers. The comparisons of cloud optical thicknesses retrieved from radar and from radiometer measurements indicate an uncertainty of about 77% and a bias of about -14% in the radar estimates of τ relative to radiometric retrievals. One possible explanation of the negative bias is an inherently low sensitivity of radar measurements to smaller cloud particles that still contribute noticeably to the cloud extinction. This estimate of the uncertainty is in line with simple theoretical considerations, and the associated retrieval accuracy should be considered good for a nonoptical instrument, such as radar. This paper also presents relations between radar-derived characteristic cloud particle sizes and effective sizes used in models. An average relation among τ, cloud ice water path, and the layer mean value of cloud particle characteristic size is also given. This relation is found to be in good agreement with in situ measurements. Despite a high uncertainty of radar estimates of extinction, this method is useful for many clouds where optical measurements are not available because of cloud multilayering or opaqueness.

Validation of Satellite-Based Objective Overshooting Cloud-Top Detection Methods Using CloudSat Cloud Profiling Radar Observations

NASA Technical Reports Server (NTRS)

Bedka, Kristopher M.; Dworak, Richard; Brunner, Jason; Feltz, Wayne

2012-01-01

Two satellite infrared-based overshooting convective cloud-top (OT) detection methods have recently been described in the literature: 1) the 11-mm infrared window channel texture (IRW texture) method, which uses IRW channel brightness temperature (BT) spatial gradients and thresholds, and 2) the water vapor minus IRW BT difference (WV-IRW BTD). While both methods show good performance in published case study examples, it is important to quantitatively validate these methods relative to overshooting top events across the globe. Unfortunately, no overshooting top database currently exists that could be used in such study. This study examines National Aeronautics and Space Administration CloudSat Cloud Profiling Radar data to develop an OT detection validation database that is used to evaluate the IRW-texture and WV-IRW BTD OT detection methods. CloudSat data were manually examined over a 1.5-yr period to identify cases in which the cloud top penetrates above the tropopause height defined by a numerical weather prediction model and the surrounding cirrus anvil cloud top, producing 111 confirmed overshooting top events. When applied to Moderate Resolution Imaging Spectroradiometer (MODIS)-based Geostationary Operational Environmental Satellite-R Series (GOES-R) Advanced Baseline Imager proxy data, the IRW-texture (WV-IRW BTD) method offered a 76% (96%) probability of OT detection (POD) and 16% (81%) false-alarm ratio. Case study examples show that WV-IRW BTD.0 K identifies much of the deep convective cloud top, while the IRW-texture method focuses only on regions with a spatial scale near that of commonly observed OTs. The POD decreases by 20% when IRW-texture is applied to current geostationary imager data, highlighting the importance of imager spatial resolution for observing and detecting OT regions.

Development of nondestructive testing techniques for plated-through holes in multilayer printed circuit boards

NASA Technical Reports Server (NTRS)

Anthony, P. L.; Mcmurtrey, J. E.

1971-01-01

The development of a nondestructive test with the capability to interrogate plated-through holes as small as 0.51 millimeters inside diameter is discussed. The system can detect defects such as holes, voids, cracks, and thin spots that reduce the current carrying capability of plates-through interconnects by 20 percent or more. Efforts were directed toward the design and fabrication of magnetic circuitry mutual coupling probes and to evaluate the effectiveness of these devices for detecting in multilayer board plated-through holes.

Automated, per pixel Cloud Detection from High-Resolution VNIR Data

NASA Technical Reports Server (NTRS)

Varlyguin, Dmitry L.

2007-01-01

CASA is a fully automated software program for the per-pixel detection of clouds and cloud shadows from medium- (e.g., Landsat, SPOT, AWiFS) and high- (e.g., IKONOS, QuickBird, OrbView) resolution imagery without the use of thermal data. CASA is an object-based feature extraction program which utilizes a complex combination of spectral, spatial, and contextual information available in the imagery and the hierarchical self-learning logic for accurate detection of clouds and their shadows.

Cloud-based MOTIFSIM: Detecting Similarity in Large DNA Motif Data Sets.

PubMed

Tran, Ngoc Tam L; Huang, Chun-Hsi

2017-05-01

We developed the cloud-based MOTIFSIM on Amazon Web Services (AWS) cloud. The tool is an extended version from our web-based tool version 2.0, which was developed based on a novel algorithm for detecting similarity in multiple DNA motif data sets. This cloud-based version further allows researchers to exploit the computing resources available from AWS to detect similarity in multiple large-scale DNA motif data sets resulting from the next-generation sequencing technology. The tool is highly scalable with expandable AWS.

Finding overlapping communities in multilayer networks

PubMed Central

Liu, Weiyi; Suzumura, Toyotaro; Ji, Hongyu; Hu, Guangmin

2018-01-01

Finding communities in multilayer networks is a vital step in understanding the structure and dynamics of these layers, where each layer represents a particular type of relationship between nodes in the natural world. However, most community discovery methods for multilayer networks may ignore the interplay between layers or the unique topological structure in a layer. Moreover, most of them can only detect non-overlapping communities. In this paper, we propose a new community discovery method for multilayer networks, which leverages the interplay between layers and the unique topology in a layer to reveal overlapping communities. Through a comprehensive analysis of edge behaviors within and across layers, we first calculate the similarities for edges from the same layer and the cross layers. Then, by leveraging these similarities, we can construct a dendrogram for the multilayer networks that takes both the unique topological structure and the important interplay into consideration. Finally, by introducing a new community density metric for multilayer networks, we can cut the dendrogram to get the overlapping communities for these layers. By applying our method on both synthetic and real-world datasets, we demonstrate that our method has an accurate performance in discovering overlapping communities in multilayer networks. PMID:29694387

Finding overlapping communities in multilayer networks.

PubMed

Liu, Weiyi; Suzumura, Toyotaro; Ji, Hongyu; Hu, Guangmin

2018-01-01

Finding communities in multilayer networks is a vital step in understanding the structure and dynamics of these layers, where each layer represents a particular type of relationship between nodes in the natural world. However, most community discovery methods for multilayer networks may ignore the interplay between layers or the unique topological structure in a layer. Moreover, most of them can only detect non-overlapping communities. In this paper, we propose a new community discovery method for multilayer networks, which leverages the interplay between layers and the unique topology in a layer to reveal overlapping communities. Through a comprehensive analysis of edge behaviors within and across layers, we first calculate the similarities for edges from the same layer and the cross layers. Then, by leveraging these similarities, we can construct a dendrogram for the multilayer networks that takes both the unique topological structure and the important interplay into consideration. Finally, by introducing a new community density metric for multilayer networks, we can cut the dendrogram to get the overlapping communities for these layers. By applying our method on both synthetic and real-world datasets, we demonstrate that our method has an accurate performance in discovering overlapping communities in multilayer networks.

Invisible Cirrus Clouds

NASA Technical Reports Server (NTRS)

2002-01-01

The Moderate-resolution Imaging Spectroradiometer's (MODIS') cloud detection capability is so sensitive that it can detect clouds that would be indistinguishable to the human eye. This pair of images highlights MODIS' ability to detect what scientists call 'sub-visible cirrus.' The image on top shows the scene using data collected in the visible part of the electromagnetic spectrum-the part our eyes can see. Clouds are apparent in the center and lower right of the image, while the rest of the image appears to be relatively clear. However, data collected at 1.38um (lower image) show that a thick layer of previously undetected cirrus clouds obscures the entire scene. These kinds of cirrus are called 'sub-visible' because they can't be detected using only visible light. MODIS' 1.38um channel detects electromagnetic radiation in the infrared region of the spectrum. These images were made from data collected on April 4, 2000. Image courtesy Mark Gray, MODIS Atmosphere Team

Tiny, Dusty, Galactic HI Clouds: The GALFA-HI Compact Cloud Catalog

NASA Astrophysics Data System (ADS)

Saul, Destry R.; Putman, M. E.; Peek, J. G.

2013-01-01

The recently published GALFA-HI Compact Cloud Catalog contains 2000 nearby neutral hydrogen clouds under 20' in angular size detected with a machine-vision algorithm in the Galactic Arecibo L-Band Feed Array HI survey (GALFA-HI). At a distance of 1kpc, the compact clouds would typically be 1 solar mass and 1pc in size. We observe that nearly all of the compact clouds that are classified as high velocity (> 90 km/s) are near previously-identified high velocity complexes. We separate the compact clouds into populations based on velocity, linewidth, and position. We have begun to search for evidence of dust in these clouds using IRIS and have detections in several populations.

DeepSAT's CloudCNN: A Deep Neural Network for Rapid Cloud Detection from Geostationary Satellites

NASA Astrophysics Data System (ADS)

Kalia, S.; Li, S.; Ganguly, S.; Nemani, R. R.

2017-12-01

Cloud and cloud shadow detection has important applications in weather and climate studies. It is even more crucial when we introduce geostationary satellites into the field of terrestrial remotesensing. With the challenges associated with data acquired in very high frequency (10-15 mins per scan), the ability to derive an accurate cloud/shadow mask from geostationary satellite data iscritical. The key to the success for most of the existing algorithms depends on spatially and temporally varying thresholds, which better capture local atmospheric and surface effects.However, the selection of proper threshold is difficult and may lead to erroneous results. In this work, we propose a deep neural network based approach called CloudCNN to classifycloud/shadow from Himawari-8 AHI and GOES-16 ABI multispectral data. DeepSAT's CloudCNN consists of an encoder-decoder based architecture for binary-class pixel wise segmentation. We train CloudCNN on multi-GPU Nvidia Devbox cluster, and deploy the prediction pipeline on NASA Earth Exchange (NEX) Pleiades supercomputer. We achieved an overall accuracy of 93.29% on test samples. Since, the predictions take only a few seconds to segment a full multi-spectral GOES-16 or Himawari-8 Full Disk image, the developed framework can be used for real-time cloud detection, cyclone detection, or extreme weather event predictions.

Optical Algorithm for Cloud Shadow Detection Over Water

DTIC Science & Technology

2013-02-01

REPORT DATE (DD-MM-YYYY) 05-02-2013 2. REPORT TYPE Journal Article 3. DATES COVERED (From ■ To) 4. TITLE AND SUBTITLE Optical Algorithm for Cloud...particularly over humid tropical regions. Throughout the year, about two-thirds of the Earth’s surface is always covered by clouds [1]. The problem...V. Khlopenkov and A. P. Trishchenko, "SPARC: New cloud, snow , cloud shadow detection scheme for historical I-km AVHHR data over Canada," / Atmos

Improvements to the CERES Cloud Detection Algorithm using Himawari 8 Data and Validation using CALIPSO and CATS Lidar Observations

NASA Astrophysics Data System (ADS)

Trepte, Q.; Minnis, P.; Palikonda, R.; Yost, C. R.; Rodier, S. D.; Trepte, C. R.; McGill, M. J.

2016-12-01

Geostationary satellites provide continuous cloud and meteorological observations important for weather forecasting and for understanding climate processes. The Himawari-8 satellite represents a new generation of measurement capabilities with significantly improved resolution and enhanced spectral information. The satellite was launched in October 2014 by the Japanese Meteorological Agency and is centered at 140° E to provide coverage over eastern Asia and the western Pacific region. A cloud detection algorithm was developed as part of the CERES Cloud Mask algorithm using the Advanced Himawari Imager (AHI), a 16 channel multi-spectral imager. The algorithm was originally designed for use with Meteosat Second Generation (MSG) data and has been adapted for Himawari-8 AHI measurements. This paper will describe the improvements in the Himawari cloud mask including daytime ocean low cloud and aerosol discrimination, nighttime thin cirrus detection, and Australian desert and coastal cloud detection. The statistics from matched CERES Himawari cloud mask results with CALIPSO lidar data and with new observations from the CATS lidar will also be presented. A feature of the CATS instrument on board the International Space Station is that it gives information at different solar viewing times to examine the diurnal variation of clouds and this provides an ability to evaluate the performance of the cloud mask for different sun angles.

A holistic image segmentation framework for cloud detection and extraction

NASA Astrophysics Data System (ADS)

Shen, Dan; Xu, Haotian; Blasch, Erik; Horvath, Gregory; Pham, Khanh; Zheng, Yufeng; Ling, Haibin; Chen, Genshe

2013-05-01

Atmospheric clouds are commonly encountered phenomena affecting visual tracking from air-borne or space-borne sensors. Generally clouds are difficult to detect and extract because they are complex in shape and interact with sunlight in a complex fashion. In this paper, we propose a clustering game theoretic image segmentation based approach to identify, extract, and patch clouds. In our framework, the first step is to decompose a given image containing clouds. The problem of image segmentation is considered as a "clustering game". Within this context, the notion of a cluster is equivalent to a classical equilibrium concept from game theory, as the game equilibrium reflects both the internal and external (e.g., two-player) cluster conditions. To obtain the evolutionary stable strategies, we explore three evolutionary dynamics: fictitious play, replicator dynamics, and infection and immunization dynamics (InImDyn). Secondly, we use the boundary and shape features to refine the cloud segments. This step can lower the false alarm rate. In the third step, we remove the detected clouds and patch the empty spots by performing background recovery. We demonstrate our cloud detection framework on a video clip provides supportive results.

Contemporary ultrasonic signal processing approaches for nondestructive evaluation of multilayered structures

NASA Astrophysics Data System (ADS)

Zhang, Guang-Ming; Harvey, David M.

2012-03-01

Various signal processing techniques have been used for the enhancement of defect detection and defect characterisation. Cross-correlation, filtering, autoregressive analysis, deconvolution, neural network, wavelet transform and sparse signal representations have all been applied in attempts to analyse ultrasonic signals. In ultrasonic nondestructive evaluation (NDE) applications, a large number of materials have multilayered structures. NDE of multilayered structures leads to some specific problems, such as penetration, echo overlap, high attenuation and low signal-to-noise ratio. The signals recorded from a multilayered structure are a class of very special signals comprised of limited echoes. Such signals can be assumed to have a sparse representation in a proper signal dictionary. Recently, a number of digital signal processing techniques have been developed by exploiting the sparse constraint. This paper presents a review of research to date, showing the up-to-date developments of signal processing techniques made in ultrasonic NDE. A few typical ultrasonic signal processing techniques used for NDE of multilayered structures are elaborated. The practical applications and limitations of different signal processing methods in ultrasonic NDE of multilayered structures are analysed.

Suitable combination of noble/ferromagnetic metal multilayers for enhanced magneto-plasmonic biosensing.

PubMed

Regatos, David; Sepúlveda, Borja; Fariña, David; Carrascosa, Laura G; Lechuga, Laura M

2011-04-25

We present a theoretical and experimental study on the biosensing sensitivity of Au/Co/Au multilayers as transducers of the magneto-optic surface-plasmon-resonance (MOSPR) sensor. We demonstrate that the sensing response of these magneto-plasmonic (MP) transducers is a trade-off between the optical absorption and the magneto-optical activity, observing that the MP multilayer with larger MO effect does not provide the best sensing response. We show that it is possible to design highly-sensitive MP transducers able to largely surpass the limit of detection of the conventional surface-plasmon-resonance (SPR) sensor. This was proved comparing the biosensing performance of both sensors for the label-free detection of short DNA chains hybridization. For this purpose, we used and tested a novel label-free biofunctionalization protocol based on polyelectrolytes, which increases the resistance of MP transducers in aqueous environments.

Analysis of cloud top height and cloud coverage from satellites using the O2 A and B bands

NASA Technical Reports Server (NTRS)

Kuze, Akihiko; Chance, Kelly V.

1994-01-01

Cloud height and cloud coverage detection are important for total ozone retrieval using ultraviolet and visible scattered light. Use of the O2 A and B bands, around 761 and 687 nm, by a satellite-borne instrument of moderately high spectral resolution viewing in the nadir makes it possible to detect cloud top height and related parameters, including fractional coverage. The measured values of a satellite-borne spectrometer are convolutions of the instrument slit function and the atmospheric transmittance between cloud top and satellite. Studies here determine the optical depth between a satellite orbit and the Earth or cloud top height to high accuracy using FASCODE 3. Cloud top height and a cloud coverage parameter are determined by least squares fitting to calculated radiance ratios in the oxygen bands. A grid search method is used to search the parameter space of cloud top height and the coverage parameter to minimize an appropriate sum of squares of deviations. For this search, nonlinearity of the atmospheric transmittance (i.e., leverage based on varying amounts of saturation in the absorption spectrum) is important for distinguishing between cloud top height and fractional coverage. Using the above-mentioned method, an operational cloud detection algorithm which uses minimal computation time can be implemented.

The Cloud Detection and UV Monitoring Experiment (CLUE)

NASA Technical Reports Server (NTRS)

Barbier, L.; Loh, E.; Sokolsky, P.; Streitmatter, R.

2004-01-01

We propose a large-area, low-power instrument to perform CLoud detection and Ultraviolet monitoring, CLUE. CLUE will combine the W detection capabilities of the NIGHTGLOW payload, with an array of infrared sensors to perform cloud slicing measurements. Missions such as EUSO and OWL which seek to measure UHE cosmic-rays at 1W20 eV use the atmosphere as a fluorescence detector. CLUE will provide several important correlated measurements for these missions, including: monitoring the atmospheric W emissions &om 330 - 400 nm, determining the ambient cloud cover during those W measurements (with active LIDAR), measuring the optical depth of the clouds (with an array of narrow band-pass IR sensors), and correlating LIDAR and IR cloud cover measurements. This talk will describe the instrument as we envision it.

Detection of hydrogen sulfide above the clouds in Uranus's atmosphere

NASA Astrophysics Data System (ADS)

Irwin, Patrick G. J.; Toledo, Daniel; Garland, Ryan; Teanby, Nicholas A.; Fletcher, Leigh N.; Orton, Glenn A.; Bézard, Bruno

2018-04-01

Visible-to-near-infrared observations indicate that the cloud top of the main cloud deck on Uranus lies at a pressure level of between 1.2 bar and 3 bar. However, its composition has never been unambiguously identified, although it is widely assumed to be composed primarily of either ammonia or hydrogen sulfide (H2S) ice. Here, we present evidence of a clear detection of gaseous H2S above this cloud deck in the wavelength region 1.57-1.59 μm with a mole fraction of 0.4-0.8 ppm at the cloud top. Its detection constrains the deep bulk sulfur/nitrogen abundance to exceed unity (>4.4-5.0 times the solar value) in Uranus's bulk atmosphere, and places a lower limit on the mole fraction of H2S below the observed cloud of (1.0 -2.5 ) ×1 0-5. The detection of gaseous H2S at these pressure levels adds to the weight of evidence that the principal constituent of 1.2-3-bar cloud is likely to be H2S ice.

Detection of hydrogen sulfide above the clouds in Uranus's atmosphere

NASA Astrophysics Data System (ADS)

Irwin, Patrick G. J.; Toledo, Daniel; Garland, Ryan; Teanby, Nicholas A.; Fletcher, Leigh N.; Orton, Glenn A.; Bézard, Bruno

2018-05-01

Visible-to-near-infrared observations indicate that the cloud top of the main cloud deck on Uranus lies at a pressure level of between 1.2 bar and 3 bar. However, its composition has never been unambiguously identified, although it is widely assumed to be composed primarily of either ammonia or hydrogen sulfide (H2S) ice. Here, we present evidence of a clear detection of gaseous H2S above this cloud deck in the wavelength region 1.57-1.59 μm with a mole fraction of 0.4-0.8 ppm at the cloud top. Its detection constrains the deep bulk sulfur/nitrogen abundance to exceed unity (>4.4-5.0 times the solar value) in Uranus's bulk atmosphere, and places a lower limit on the mole fraction of H2S below the observed cloud of (1.0 -2.5 ) ×1 0-5. The detection of gaseous H2S at these pressure levels adds to the weight of evidence that the principal constituent of 1.2-3-bar cloud is likely to be H2S ice.

APOLLO_NG - a probabilistic interpretation of the APOLLO legacy for AVHRR heritage channels

NASA Astrophysics Data System (ADS)

Klüser, L.; Killius, N.; Gesell, G.

2015-04-01

The cloud processing scheme APOLLO (Avhrr Processing scheme Over cLouds, Land and Ocean) has been in use for cloud detection and cloud property retrieval since the late 1980s. The physics of the APOLLO scheme still build the backbone of a range of cloud detection algorithms for AVHRR (Advanced Very High Resolution Radiometer) heritage instruments. The APOLLO_NG (APOLLO_NextGeneration) cloud processing scheme is a probabilistic interpretation of the original APOLLO method. While building upon the physical principles having served well in the original APOLLO a couple of additional variables have been introduced in APOLLO_NG. Cloud detection is not performed as a binary yes/no decision based on these physical principals but is expressed as cloud probability for each satellite pixel. Consequently the outcome of the algorithm can be tuned from clear confident to cloud confident depending on the purpose. The probabilistic approach allows to retrieving not only the cloud properties (optical depth, effective radius, cloud top temperature and cloud water path) but also their uncertainties. APOLLO_NG is designed as a standalone cloud retrieval method robust enough for operational near-realtime use and for the application with large amounts of historical satellite data. Thus the radiative transfer solution is approximated by the same two stream approach which also had been used for the original APOLLO. This allows the algorithm to be robust enough for being applied to a wide range of sensors without the necessity of sensor-specific tuning. Moreover it allows for online calculation of the radiative transfer (i.e. within the retrieval algorithm) giving rise to a detailed probabilistic treatment of cloud variables. This study presents the algorithm for cloud detection and cloud property retrieval together with the physical principles from the APOLLO legacy it is based on. Furthermore a couple of example results from on NOAA-18 are presented.

Comparing airborne and satellite retrievals of cloud optical thickness and particle effective radius using a spectral radiance ratio technique: two case studies for cirrus and deep convective clouds

NASA Astrophysics Data System (ADS)

Krisna, Trismono C.; Wendisch, Manfred; Ehrlich, André; Jäkel, Evelyn; Werner, Frank; Weigel, Ralf; Borrmann, Stephan; Mahnke, Christoph; Pöschl, Ulrich; Andreae, Meinrat O.; Voigt, Christiane; Machado, Luiz A. T.

2018-04-01

Solar radiation reflected by cirrus and deep convective clouds (DCCs) was measured by the Spectral Modular Airborne Radiation Measurement System (SMART) installed on the German High Altitude and Long Range Research Aircraft (HALO) during the Mid-Latitude Cirrus (ML-CIRRUS) and the Aerosol, Cloud, Precipitation, and Radiation Interaction and Dynamic of Convective Clouds System - Cloud Processes of the Main Precipitation Systems in Brazil: A Contribution to Cloud Resolving Modelling and to the Global Precipitation Measurement (ACRIDICON-CHUVA) campaigns. On particular flights, HALO performed measurements closely collocated with overpasses of the Moderate Resolution Imaging Spectroradiometer (MODIS) aboard the Aqua satellite. A cirrus cloud located above liquid water clouds and a DCC topped by an anvil cirrus are analyzed in this paper. Based on the nadir spectral upward radiance measured above the two clouds, the optical thickness τ and particle effective radius reff of the cirrus and DCC are retrieved using a radiance ratio technique, which considers the cloud thermodynamic phase, the vertical profile of cloud microphysical properties, the presence of multilayer clouds, and the heterogeneity of the surface albedo. For the cirrus case, the comparison of τ and reff retrieved on the basis of SMART and MODIS measurements yields a normalized mean absolute deviation of up to 1.2 % for τ and 2.1 % for reff. For the DCC case, deviations of up to 3.6 % for τ and 6.2 % for reff are obtained. The larger deviations in the DCC case are mainly attributed to the fast cloud evolution and three-dimensional (3-D) radiative effects. Measurements of spectral upward radiance at near-infrared wavelengths are employed to investigate the vertical profile of reff in the cirrus. The retrieved values of reff are compared with corresponding in situ measurements using a vertical weighting method. Compared to the MODIS observations, measurements of SMART provide more information on the vertical distribution of particle sizes, which allow reconstructing the profile of reff close to the cloud top. The comparison between retrieved and in situ reff yields a normalized mean absolute deviation, which ranges between 1.5 and 10.3 %, and a robust correlation coefficient of 0.82.

Multi-Layer Arctic Mixed-Phase Clouds Simulated by a Cloud-Resolving Model: Comparison with ARM Observations and Sensitivity Experiments

NASA Technical Reports Server (NTRS)

Luo, Yali; Xu, Kuan-Man; Morrison, Hugh; McFarquhar, Greg M.; Wang, Zhien; Zhang, Gong

2007-01-01

A cloud-resolving model (CRM) is used to simulate the multiple-layer mixed-phase stratiform (MPS) clouds that occurred during a three-and-a-half day subperiod of the Department of Energy-Atmospheric Radiation Measurement Program s Mixed-Phase Arctic Cloud Experiment (M-PACE). The CRM is implemented with an advanced two-moment microphysics scheme, a state-of-the-art radiative transfer scheme, and a complicated third-order turbulence closure. Concurrent meteorological, aerosol, and ice nucleus measurements are used to initialize the CRM. The CRM is prescribed by time-varying large-scale advective tendencies of temperature and moisture and surface turbulent fluxes of sensible and latent heat. The CRM reproduces the occurrences of the single- and double-layer MPS clouds as revealed by the M-PACE observations. However, the simulated first cloud layer is lower and the second cloud layer thicker compared to observations. The magnitude of the simulated liquid water path agrees with that observed, but its temporal variation is more pronounced than that observed. As in an earlier study of single-layer cloud, the CRM also captures the major characteristics in the vertical distributions and temporal variations of liquid water content (LWC), total ice water content (IWC), droplet number concentration and ice crystal number concentration (nis) as suggested by the aircraft observations. However, the simulated mean values differ significantly from the observed. The magnitude of nis is especially underestimated by one order of magnitude. Sensitivity experiments suggest that the lower cloud layer is closely related to the surface fluxes of sensible and latent heat; the upper cloud layer is probably initialized by the large-scale advective cooling/moistening and maintained through the strong longwave (LW) radiative cooling near the cloud top which enhances the dynamical circulation; artificially turning off all ice-phase microphysical processes results in an increase in LWP by a factor of 3 due to interactions between the excessive LW radiative cooling and extra cloud water; heating caused by phase change of hydrometeors could affect the LWC and cloud top height by partially canceling out the LW radiative cooling. It is further shown that the resolved dynamical circulation appears to contribute more greatly to the evolution of the MPS cloud layers than the parameterized subgrid-scale circulation.

Delamination Defect Detection Using Ultrasonic Guided Waves in Advanced Hybrid Structural Elements

NASA Astrophysics Data System (ADS)

Yan, Fei; Qi, Kevin ``Xue''; Rose, Joseph L.; Weiland, Hasso

2010-02-01

Nondestructive testing for multilayered structures is challenging because of increased numbers of layers and plate thicknesses. In this paper, ultrasonic guided waves are applied to detect delamination defects inside a 23-layer Alcoa Advanced Hybrid Structural plate. A semi-analytical finite element (SAFE) method generates dispersion curves and wave structures in order to select appropriate wave structures to detect certain defects. One guided wave mode and frequency is chosen to achieve large in-plane displacements at regions of interest. The interactions of the selected mode with defects are simulated using finite element models. Experiments are conducted and compared with bulk wave measurements. It is shown that guided waves can detect deeply embedded damages inside thick multilayer fiber-metal laminates with suitable mode and frequency selection.

Using deep recurrent neural network for direct beam solar irradiance cloud screening

NASA Astrophysics Data System (ADS)

Chen, Maosi; Davis, John M.; Liu, Chaoshun; Sun, Zhibin; Zempila, Melina Maria; Gao, Wei

2017-09-01

Cloud screening is an essential procedure for in-situ calibration and atmospheric properties retrieval on (UV-)MultiFilter Rotating Shadowband Radiometer [(UV-)MFRSR]. Previous study has explored a cloud screening algorithm for direct-beam (UV-)MFRSR voltage measurements based on the stability assumption on a long time period (typically a half day or a whole day). To design such an algorithm requires in-depth understanding of radiative transfer and delicate data manipulation. Recent rapid developments on deep neural network and computation hardware have opened a window for modeling complicated End-to-End systems with a standardized strategy. In this study, a multi-layer dynamic bidirectional recurrent neural network is built for determining the cloudiness on each time point with a 17-year training dataset and tested with another 1-year dataset. The dataset is the daily 3-minute cosine corrected voltages, airmasses, and the corresponding cloud/clear-sky labels at two stations of the USDA UV-B Monitoring and Research Program. The results show that the optimized neural network model (3-layer, 250 hidden units, and 80 epochs of training) has an overall test accuracy of 97.87% (97.56% for the Oklahoma site and 98.16% for the Hawaii site). Generally, the neural network model grasps the key concept of the original model to use data in the entire day rather than short nearby measurements to perform cloud screening. A scrutiny of the logits layer suggests that the neural network model automatically learns a way to calculate a quantity similar to total optical depth and finds an appropriate threshold for cloud screening.

Study and Application on Cloud Covered Rate for Agroclimatical Distribution Using In Guangxi Based on Modis Data

NASA Astrophysics Data System (ADS)

Yang, Xin; Zhong, Shiquan; Sun, Han; Tan, Zongkun; Li, Zheng; Ding, Meihua

Based on analyzing of the physical characteristics of cloud and importance of cloud in agricultural production and national economy, cloud is a very important climatic resources such as temperature, precipitation and solar radiation. Cloud plays a very important role in agricultural climate division .This paper analyzes methods of cloud detection based on MODIS data in China and Abroad . The results suggest that Quanjun He method is suitable to detect cloud in Guangxi. State chart of cloud cover in Guangxi is imaged by using Quanjun He method .We find out the approach of calculating cloud covered rate by using the frequency spectrum analysis. At last, the Guangxi is obtained. Taking Rongxian County Guangxi as an example, this article analyze the preliminary application of cloud covered rate in distribution of Rong Shaddock pomelo . Analysis results indicate that cloud covered rate is closely related to quality of Rong Shaddock pomelo.

Evaluation and Applications of Cloud Climatologies from CALIOP

NASA Technical Reports Server (NTRS)

Winker, David; Getzewitch, Brian; Vaughan, Mark

2008-01-01

Clouds have a major impact on the Earth radiation budget and differences in the representation of clouds in global climate models are responsible for much of the spread in predicted climate sensitivity. Existing cloud climatologies, against which these models can be tested, have many limitations. The CALIOP lidar, carried on the CALIPSO satellite, has now acquired over two years of nearly continuous cloud and aerosol observations. This dataset provides an improved basis for the characterization of 3-D global cloudiness. Global average cloud cover measured by CALIOP is about 75%, significantly higher than for existing cloud climatologies due to the sensitivity of CALIOP to optically thin cloud. Day/night biases in cloud detection appear to be small. This presentation will discuss detection sensitivity and other issues associated with producing a cloud climatology, characteristics of cloud cover statistics derived from CALIOP data, and applications of those statistics.

Flow cytometry of HEK 293T cells interacting with polyelectrolyte multilayer capsules containing fluorescein-labeled poly(acrylic acid) as a pH sensor.

PubMed

Reibetanz, Uta; Halozan, David; Brumen, Milan; Donath, Edwin

2007-06-01

Polyelectrolyte multilayer sensor capsules, 5 microm in diameter, which contained fluorescein-labeled poly(acrylic acid) (PAAAF) as pH-sensitive reporter molecules, were fabricated and employed to explore their endocytotic uptake into HEK 293T cells by flow cytometry. The percentage of capsules residing in the endolysosomal compartment was estimated from the fluorescence intensity decrease caused by acidification. Capsules attached to the extracellular surface of the plasma membrane were identified by trypan blue quenching. The number of capsules in the cytoplasm was rather small, being below the detection limit of the method. The advantages of polyelectrolyte multilayer capsules are that the fluorophore is protected from interaction with cellular compartments and that the multilayer can be equipped with additional functions.

Introducing two Random Forest based methods for cloud detection in remote sensing images

NASA Astrophysics Data System (ADS)

Ghasemian, Nafiseh; Akhoondzadeh, Mehdi

2018-07-01

Cloud detection is a necessary phase in satellite images processing to retrieve the atmospheric and lithospheric parameters. Currently, some cloud detection methods based on Random Forest (RF) model have been proposed but they do not consider both spectral and textural characteristics of the image. Furthermore, they have not been tested in the presence of snow/ice. In this paper, we introduce two RF based algorithms, Feature Level Fusion Random Forest (FLFRF) and Decision Level Fusion Random Forest (DLFRF) to incorporate visible, infrared (IR) and thermal spectral and textural features (FLFRF) including Gray Level Co-occurrence Matrix (GLCM) and Robust Extended Local Binary Pattern (RELBP_CI) or visible, IR and thermal classifiers (DLFRF) for highly accurate cloud detection on remote sensing images. FLFRF first fuses visible, IR and thermal features. Thereafter, it uses the RF model to classify pixels to cloud, snow/ice and background or thick cloud, thin cloud and background. DLFRF considers visible, IR and thermal features (both spectral and textural) separately and inserts each set of features to RF model. Then, it holds vote matrix of each run of the model. Finally, it fuses the classifiers using the majority vote method. To demonstrate the effectiveness of the proposed algorithms, 10 Terra MODIS and 15 Landsat 8 OLI/TIRS images with different spatial resolutions are used in this paper. Quantitative analyses are based on manually selected ground truth data. Results show that after adding RELBP_CI to input feature set cloud detection accuracy improves. Also, the average cloud kappa values of FLFRF and DLFRF on MODIS images (1 and 0.99) are higher than other machine learning methods, Linear Discriminate Analysis (LDA), Classification And Regression Tree (CART), K Nearest Neighbor (KNN) and Support Vector Machine (SVM) (0.96). The average snow/ice kappa values of FLFRF and DLFRF on MODIS images (1 and 0.85) are higher than other traditional methods. The quantitative values on Landsat 8 images show similar trend. Consequently, while SVM and K-nearest neighbor show overestimation in predicting cloud and snow/ice pixels, our Random Forest (RF) based models can achieve higher cloud, snow/ice kappa values on MODIS and thin cloud, thick cloud and snow/ice kappa values on Landsat 8 images. Our algorithms predict both thin and thick cloud on Landsat 8 images while the existing cloud detection algorithm, Fmask cannot discriminate them. Compared to the state-of-the-art methods, our algorithms have acquired higher average cloud and snow/ice kappa values for different spatial resolutions.

Detecting Distributed SQL Injection Attacks in a Eucalyptus Cloud Environment

NASA Technical Reports Server (NTRS)

Kebert, Alan; Barnejee, Bikramjit; Solano, Juan; Solano, Wanda

2013-01-01

The cloud computing environment offers malicious users the ability to spawn multiple instances of cloud nodes that are similar to virtual machines, except that they can have separate external IP addresses. In this paper we demonstrate how this ability can be exploited by an attacker to distribute his/her attack, in particular SQL injection attacks, in such a way that an intrusion detection system (IDS) could fail to identify this attack. To demonstrate this, we set up a small private cloud, established a vulnerable website in one instance, and placed an IDS within the cloud to monitor the network traffic. We found that an attacker could quite easily defeat the IDS by periodically altering its IP address. To detect such an attacker, we propose to use multi-agent plan recognition, where the multiple source IPs are considered as different agents who are mounting a collaborative attack. We show that such a formulation of this problem yields a more sophisticated approach to detecting SQL injection attacks within a cloud computing environment.

Improving the Accuracy of Cloud Detection Using Machine Learning

NASA Astrophysics Data System (ADS)

Craddock, M. E.; Alliss, R. J.; Mason, M.

2017-12-01

Cloud detection from geostationary satellite imagery has long been accomplished through multi-spectral channel differencing in comparison to the Earth's surface. The distinction of clear/cloud is then determined by comparing these differences to empirical thresholds. Using this methodology, the probability of detecting clouds exceeds 90% but performance varies seasonally, regionally and temporally. The Cloud Mask Generator (CMG) database developed under this effort, consists of 20 years of 4 km, 15minute clear/cloud images based on GOES data over CONUS and Hawaii. The algorithms to determine cloudy pixels in the imagery are based on well-known multi-spectral techniques and defined thresholds. These thresholds were produced by manually studying thousands of images and thousands of man-hours to determine the success and failure of the algorithms to fine tune the thresholds. This study aims to investigate the potential of improving cloud detection by using Random Forest (RF) ensemble classification. RF is the ideal methodology to employ for cloud detection as it runs efficiently on large datasets, is robust to outliers and noise and is able to deal with highly correlated predictors, such as multi-spectral satellite imagery. The RF code was developed using Python in about 4 weeks. The region of focus selected was Hawaii and includes the use of visible and infrared imagery, topography and multi-spectral image products as predictors. The development of the cloud detection technique is realized in three steps. First, tuning of the RF models is completed to identify the optimal values of the number of trees and number of predictors to employ for both day and night scenes. Second, the RF models are trained using the optimal number of trees and a select number of random predictors identified during the tuning phase. Lastly, the model is used to predict clouds for an independent time period than used during training and compared to truth, the CMG cloud mask. Initial results show 97% accuracy during the daytime, 94% accuracy at night, and 95% accuracy for all times. The total time to train, tune and test was approximately one week. The improved performance and reduced time to produce results is testament to improved computer technology and the use of machine learning as a more efficient and accurate methodology of cloud detection.

Spectral sideband produced by a hemispherical concave multilayer on the African shield-bug Calidea panaethiopica (Scutelleridae)

NASA Astrophysics Data System (ADS)

Vigneron, Jean Pol; Ouedraogo, Moussa; Colomer, Jean-François; Rassart, Marie

2009-02-01

The African shield-backed bug Calidea panaethiopica is a very colorful insect which produces a range of iridescent yellow, green, and blue reflections. The cuticle of the dorsal side of the insect, on the shield, the prothorax and part of the head, is pricked of uniformly distributed hemispherical hollow cavities a few tens micrometers deep. Under normal illumination and viewing the insect’s muffin-tin shaped surface gives rise to two distinct colors: a yellow spot arising from the bottom of the well and a blue annular cloud that appears to float around the yellow spot. This effect is explained by multiple reflections on a hemispherical Bragg mirror with a mesoscopic curvature. A multiscale computing methodology was found to be needed to evaluate the reflection spectrum for such a curved multilayer. This multiscale approach is very general and should be useful for dealing with visual effects in many natural and artificial systems.

Does spectroscopic evidence require two scattering layers in the Venus atmosphere.

NASA Technical Reports Server (NTRS)

Regas, J. L.; Boese, R. W.; Giver, L. P.; Miller, J. H.

1973-01-01

Comments on Hunt's (1972) conclusion that the phase variation of lines in the 7820- and 7883-A CO2 bands is due to the presence of two scattering layers in the Venusian atmosphere. It is shown that the increase of equivalent width with phase between 0 and 90 deg noted by Hunt in the data by Gray Young et al. (1971) does not necessarily require a two-layer model of scattering in the Venusian atmosphere and that this increase may be due to the strong backward lobe in the Venusian cloud phase function. Hunt, in a reply, notes that Regas et al. incorrectly use in their analysis Hansen's (1969) data which are for a homogeneous planetary atmosphere, while Hunt used an inhomogeneous model of the Venusian atmosphere. In addition, further evidence to support Hunt's claim for a multilayered structure of the upper Venusian clouds is presented.

APOLLO_NG - a probabilistic interpretation of the APOLLO legacy for AVHRR heritage channels

NASA Astrophysics Data System (ADS)

Klüser, L.; Killius, N.; Gesell, G.

2015-10-01

The cloud processing scheme APOLLO (AVHRR Processing scheme Over cLouds, Land and Ocean) has been in use for cloud detection and cloud property retrieval since the late 1980s. The physics of the APOLLO scheme still build the backbone of a range of cloud detection algorithms for AVHRR (Advanced Very High Resolution Radiometer) heritage instruments. The APOLLO_NG (APOLLO_NextGeneration) cloud processing scheme is a probabilistic interpretation of the original APOLLO method. It builds upon the physical principles that have served well in the original APOLLO scheme. Nevertheless, a couple of additional variables have been introduced in APOLLO_NG. Cloud detection is no longer performed as a binary yes/no decision based on these physical principles. It is rather expressed as cloud probability for each satellite pixel. Consequently, the outcome of the algorithm can be tuned from being sure to reliably identify clear pixels to conditions of reliably identifying definitely cloudy pixels, depending on the purpose. The probabilistic approach allows retrieving not only the cloud properties (optical depth, effective radius, cloud top temperature and cloud water path) but also their uncertainties. APOLLO_NG is designed as a standalone cloud retrieval method robust enough for operational near-realtime use and for application to large amounts of historical satellite data. The radiative transfer solution is approximated by the same two-stream approach which also had been used for the original APOLLO. This allows the algorithm to be applied to a wide range of sensors without the necessity of sensor-specific tuning. Moreover it allows for online calculation of the radiative transfer (i.e., within the retrieval algorithm) giving rise to a detailed probabilistic treatment of cloud variables. This study presents the algorithm for cloud detection and cloud property retrieval together with the physical principles from the APOLLO legacy it is based on. Furthermore a couple of example results from NOAA-18 are presented.

Detection of supercooled liquid water-topped mixed-phase clouds >from shortwave-infrared satellite observations

NASA Astrophysics Data System (ADS)

NOH, Y. J.; Miller, S. D.; Heidinger, A. K.

2015-12-01

Many studies have demonstrated the utility of multispectral information from satellite passive radiometers for detecting and retrieving the properties of cloud globally, which conventionally utilizes shortwave- and thermal-infrared bands. However, the satellite-derived cloud information comes mainly from cloud top or represents a vertically integrated property. This can produce a large bias in determining cloud phase characteristics, in particular for mixed-phase clouds which are often observed to have supercooled liquid water at cloud top but a predominantly ice phase residing below. The current satellite retrieval algorithms may report these clouds simply as supercooled liquid without any further information regarding the presence of a sub-cloud-top ice phase. More accurate characterization of these clouds is very important for climate models and aviation applications. In this study, we present a physical basis and preliminary results for the algorithm development of supercooled liquid-topped mixed-phase cloud detection using satellite radiometer observations. The detection algorithm is based on differential absorption properties between liquid and ice particles in the shortwave-infrared bands. Solar reflectance data in narrow bands at 1.6 μm and 2.25 μm are used to optically probe below clouds for distinction between supercooled liquid-topped clouds with and without an underlying mixed phase component. Varying solar/sensor geometry and cloud optical properties are also considered. The spectral band combination utilized for the algorithm is currently available on Suomi NPP Visible/Infrared Imaging Radiometer Suite (VIIRS), Himawari-8 Advanced Himawari Imager (AHI), and the future GOES-R Advance Baseline Imager (ABI). When tested on simulated cloud fields from WRF model and synthetic ABI data, favorable results were shown with reasonable threat scores (0.6-0.8) and false alarm rates (0.1-0.2). An ARM/NSA case study applied to VIIRS data also indicated promising potential of the algorithm.

Orbital Debris: Quarterly News, Volume 14, Issue 2

NASA Technical Reports Server (NTRS)

Liou, J. C. (Editor); Shoots, Debi (Editor)

2010-01-01

This bulletin contains articles from the Orbital Debris Program office. This issue's articles are: "Orbital Debris Success Story --A Decade in the Making", "Old and New Satellite Breakups Identified," "Update on Three Major Debris Clouds," and "MMOD Inspection of the HST Bay 5 Multi-Layer Insulation Panel" about micrometeoroid and orbital debris (MMOD) inspection of the Hubble Space Telescope (HST) insulation panel. A project review is also included (i.e., "Small Debris Observations from the Iridium 33/Cosmos 2251 Collision.") There are also abstra cts of conference papers from the staff of the program office.

Improvements in Near-Terminator and Nocturnal Cloud Masks using Satellite Imager Data over the Atmospheric Radiation Measurement Sites

DOE Office of Scientific and Technical Information (OSTI.GOV)

Trepte, Q.Z.; Minnis, P.; Heck, P.W.

2005-03-18

Cloud detection using satellite measurements presents a big challenge near the terminator where the visible (VIS; 0.65 {micro}m) channel becomes less reliable and the reflected solar component of the solar infrared 3.9-{micro}m channel reaches very low signal-to-noise ratio levels. As a result, clouds are underestimated near the terminator and at night over land and ocean in previous Atmospheric Radiation Measurement (ARM) Program cloud retrievals using Geostationary Operational Environmental Satellite (GOES) imager data. Cloud detection near the terminator has always been a challenge. For example, comparisons between the CLAVR-x (Clouds from Advanced Very High Resolution Radiometer [AVHRR]) cloud coverage and Geosciencemore » Laser Altimeter System (GLAS) measurements north of 60{sup o}N indicate significant amounts of missing clouds from AVHRR because this part of the world was near the day/night terminator viewed by AVHRR. Comparisons between MODIS cloud products and GLAS at the same regions also shows the same difficulty in the MODIS cloud retrieval (Pavolonis and Heidinger 2005). Consistent detection of clouds at all times of day is needed to provide reliable cloud and radiation products for ARM and other research efforts involving the modeling of clouds and their interaction with the radiation budget. To minimize inconsistencies between daytime and nighttime retrievals, this paper develops an improved twilight and nighttime cloud mask using GOES-9, 10, and 12 imager data over the ARM sites and the continental United States (CONUS).« less

Improvements in Near-Terminator and Nocturnal Cloud Masks using Satellite Image Data over the Atmospheric Radiation Measurement Sites

NASA Technical Reports Server (NTRS)

Trepte, Q. Z.; Minnis, P.; Heck, R. W.; Palikonda, R.

2005-01-01

Cloud detection using satellite measurements presents a big challenge near the terminator where the visible (VIS; 0.65 (micro)m) channel becomes less reliable and the reflected solar component of the solar infrared 3.9-(micro)m channel reaches very low signal-to-noise ratio levels. As a result, clouds are underestimated near the terminator and at night over land and ocean in previous Atmospheric Radiation Measurement (ARM) Program cloud retrievals using Geostationary Operational Environmental Satellite (GOES) imager data. Cloud detection near the terminator has always been a challenge. For example, comparisons between the CLAVR-x (Clouds from Advanced Very High Resolution Radiometer (AVHRR)) cloud coverage and Geoscience Laser Altimeter System (GLAS) measurements north of 60 degrees N indicate significant amounts of missing clouds from AVHRR because this part of the world was near the day/night terminator viewed by AVHRR. Comparisons between MODIS cloud products and GLAS at the same regions also shows the same difficulty in the MODIS cloud retrieval (Pavolonis and Heidinger 2005). Consistent detection of clouds at all times of day is needed to provide reliable cloud and radiation products for ARM and other research efforts involving the modeling of clouds and their interaction with the radiation budget. To minimize inconsistencies between daytime and nighttime retrievals, this paper develops an improved twilight and nighttime cloud mask using GOES-9, 10, and 12 imager data over the ARM sites and the continental United States (CONUS).

A new cloud and aerosol layer detection method based on micropulse lidar measurements

NASA Astrophysics Data System (ADS)

Zhao, Chuanfeng; Wang, Yuzhao; Wang, Qianqian; Li, Zhanqing; Wang, Zhien; Liu, Dong

2014-06-01

This paper introduces a new algorithm to detect aerosols and clouds based on micropulse lidar measurements. A semidiscretization processing technique is first used to inhibit the impact of increasing noise with distance. The value distribution equalization method which reduces the magnitude of signal variations with distance is then introduced. Combined with empirical threshold values, we determine if the signal waves indicate clouds or aerosols. This method can separate clouds and aerosols with high accuracy, although differentiation between aerosols and clouds are subject to more uncertainties depending on the thresholds selected. Compared with the existing Atmospheric Radiation Measurement program lidar-based cloud product, the new method appears more reliable and detects more clouds with high bases. The algorithm is applied to a year of observations at both the U.S. Southern Great Plains (SGP) and China Taihu sites. At the SGP site, the cloud frequency shows a clear seasonal variation with maximum values in winter and spring and shows bimodal vertical distributions with maximum occurrences at around 3-6 km and 8-12 km. The annual averaged cloud frequency is about 50%. The dominant clouds are stratiform in winter and convective in summer. By contrast, the cloud frequency at the Taihu site shows no clear seasonal variation and the maximum occurrence is at around 1 km. The annual averaged cloud frequency is about 15% higher than that at the SGP site. A seasonal analysis of cloud base occurrence frequency suggests that stratiform clouds dominate at the Taihu site.

Random ensemble learning for EEG classification.

PubMed

Hosseini, Mohammad-Parsa; Pompili, Dario; Elisevich, Kost; Soltanian-Zadeh, Hamid

2018-01-01

Real-time detection of seizure activity in epilepsy patients is critical in averting seizure activity and improving patients' quality of life. Accurate evaluation, presurgical assessment, seizure prevention, and emergency alerts all depend on the rapid detection of seizure onset. A new method of feature selection and classification for rapid and precise seizure detection is discussed wherein informative components of electroencephalogram (EEG)-derived data are extracted and an automatic method is presented using infinite independent component analysis (I-ICA) to select independent features. The feature space is divided into subspaces via random selection and multichannel support vector machines (SVMs) are used to classify these subspaces. The result of each classifier is then combined by majority voting to establish the final output. In addition, a random subspace ensemble using a combination of SVM, multilayer perceptron (MLP) neural network and an extended k-nearest neighbors (k-NN), called extended nearest neighbor (ENN), is developed for the EEG and electrocorticography (ECoG) big data problem. To evaluate the solution, a benchmark ECoG of eight patients with temporal and extratemporal epilepsy was implemented in a distributed computing framework as a multitier cloud-computing architecture. Using leave-one-out cross-validation, the accuracy, sensitivity, specificity, and both false positive and false negative ratios of the proposed method were found to be 0.97, 0.98, 0.96, 0.04, and 0.02, respectively. Application of the solution to cases under investigation with ECoG has also been effected to demonstrate its utility. Copyright © 2017 Elsevier B.V. All rights reserved.

A one year Landsat 8 conterminous United States study of spatial and temporal patterns of cirrus and non-cirrus clouds and implications for the long term Landsat archive.

NASA Astrophysics Data System (ADS)

Kovalskyy, V.; Roy, D. P.

2014-12-01

The successful February 2013 launch of the Landsat 8 satellite is continuing the 40+ year legacy of the Landsat mission. The payload includes the Operational Land Imager (OLI) that has a new 1370 mm band designed to monitor cirrus clouds and the Thermal Infrared Sensor (TIRS) that together provide 30m low, medium and high confidence cloud detections and 30m low and high confidence cirrus cloud detections. A year of Landsat 8 data over the Conterminous United States (CONUS), composed of 11,296 acquisitions, was analyzed comparing the spatial and temporal incidence of these cloud and cirrus states. This revealed (i) 36.5% of observations were detected with high confidence cloud with spatio-temporal patterns similar to those observed by previous Landsat 7 cloud analyses, (ii) 29.2% were high confidence cirrus, (iii) 20.9% were both high confidence cloud and high confidence cirrus, (iv) 8.3% were detected as high confidence cirrus but not as high confidence cloud. The results illustrate the value of the cirrus band for improved Landsat 8 terrestrial monitoring but imply that the historical CONUS Landsat archive has a similar 8% of undetected cirrus contaminated pixels. The implications for long term Landsat time series records, including the global Web Enabled Landsat Data (WELD) product record, are discussed.

H31G-1596: DeepSAT's CloudCNN: A Deep Neural Network for Rapid Cloud Detection from Geostationary Satellites

NASA Technical Reports Server (NTRS)

Kalia, Subodh; Ganguly, Sangram; Li, Shuang; Nemani, Ramakrishna R.

2017-01-01

Cloud and cloud shadow detection has important applications in weather and climate studies. It is even more crucial when we introduce geostationary satellites into the field of terrestrial remote sensing. With the challenges associated with data acquired in very high frequency (10-15 mins per scan), the ability to derive an accurate cloud shadow mask from geostationary satellite data is critical. The key to the success for most of the existing algorithms depends on spatially and temporally varying thresholds,which better capture local atmospheric and surface effects.However, the selection of proper threshold is difficult and may lead to erroneous results. In this work, we propose a deep neural network based approach called CloudCNN to classify cloudshadow from Himawari-8 AHI and GOES-16 ABI multispectral data. DeepSAT's CloudCNN consists of an encoderdecoder based architecture for binary-class pixel wise segmentation. We train CloudCNN on multi-GPU Nvidia Devbox cluster, and deploy the prediction pipeline on NASA Earth Exchange (NEX) Pleiades supercomputer. We achieved an overall accuracy of 93.29% on test samples. Since, the predictions take only a few seconds to segment a full multispectral GOES-16 or Himawari-8 Full Disk image, the developed framework can be used for real-time cloud detection, cyclone detection, or extreme weather event predictions.

Evolution of topological skyrmions across the spin reorientation transition in Pt/Co/Ta multilayers

NASA Astrophysics Data System (ADS)

He, Min; Li, Gang; Zhu, Zhaozhao; Zhang, Ying; Peng, Licong; Li, Rui; Li, Jianqi; Wei, Hongxiang; Zhao, Tongyun; Zhang, X.-G.; Wang, Shouguo; Lin, Shi-Zeng; Gu, Lin; Yu, Guoqiang; Cai, J. W.; Shen, Bao-gen

2018-05-01

Magnetic skyrmions in multilayers are particularly appealing as next generation memory devices due to their topological compact size, the robustness against external perturbations, the capability of electrical driving and detection, and the compatibility with the existing spintronic technologies. To date, Néel-type skyrmions at room temperature (RT) have been studied mostly in multilayers with easy-axis magnetic anisotropy. Here, we systematically broadened the evolution of magnetic skyrmions with sub-50-nm size in a series of Pt/Co/Ta multilayers where the magnetic anisotropy is tuned continuously from easy axis to easy plane by increasing the ferromagnetic Co layer thickness. The existence of nontrivial skyrmions is identified via the combination of in situ Lorentz transmission electron microscopy (L-TEM) and Hall transport measurements. A high density of magnetic skyrmions over a wide temperature range is observed in the multilayers with easy-plane anisotropy, which will stimulate further exploration for new materials and accelerate the development of skyrmion-based spintronic devices.

Modeling the Diffuse Cloud-Top Optical Emissions from Ground and Cloud Flashes

NASA Technical Reports Server (NTRS)

Solakiewicz, Richard; Koshak, William

2008-01-01

A number of studies have indicated that the diffuse cloud-top optical emissions from intra-cloud (IC) lightning are brighter than that from normal negative cloud-to-ground (CG) lightning, and hence would be easier to detect from a space-based sensor. The primary reason provided to substantiate this claim has been that the IC is at a higher altitude within the cloud and therefore is less obscured by the cloud multiple scattering medium. CGs at lower altitudes embedded deep within the cloud are more obscured, so CG detection is thought to be more difficult. However, other authors claim that because the CG source current (and hence luminosity) is typically substantially larger than IC currents, the greater CG source luminosity is large enough to overcome the effects of multiple scattering. These investigators suggest that the diffuse cloud top emissions from CGs are brighter than from ICs, and hence are easier to detect from space. Still other investigators claim that the detection efficiency of CGs and ICs is about the same because modern detector sensitivity is good enough to "see" either flash type no matter which produces a brighter cloud top emission. To better assess which of these opinions should be accepted, we introduce an extension of a Boltzmann lightning radiative transfer model previously developed. It considers characteristics of the cloud (geometry, dimensions, scattering properties) and specific lightning channel properties (length, geometry, location, current, optical wave front propagation speed/direction). As such, it represents the most detailed modeling effort to date. At least in the few cases studied thus far, it was found that IC flashes appear brighter at cloud top than the lower altitude negative ground flashes, but additional model runs are to be examined before finalizing our general conclusions.

Cloud Statistics and Discrimination in the Polar Regions

NASA Astrophysics Data System (ADS)

Chan, M.; Comiso, J. C.

2012-12-01

Despite their important role in the climate system, cloud cover and their statistics are poorly known, especially in the polar regions, where clouds are difficult to discriminate from snow covered surfaces. The advent of the A-train, which included Aqua/MODIS, CALIPSO/CALIOP and CloudSat/CPR sensors has provided an opportunity to improve our ability to accurately characterize the cloud cover. MODIS provides global coverage at a relatively good temporal and spatial resolution while CALIOP and CPR provide limited nadir sampling but accurate characterization of the vertical structure and phase of the cloud cover. Over the polar regions, cloud detection from a passive sensors like MODIS is challenging because of the presence of cold and highly reflective surfaces such as snow, sea-ice, glaciers, and ice-sheet, which have surface signatures similar to those of clouds. On the other hand, active sensors such as CALIOP and CPR are not only very sensitive to the presence of clouds but can also provide information about its microphysical characteristics. However, these nadir-looking sensors have sparse spatial coverage and their global data can have data spatial gaps of up to 100 km. We developed a polar cloud detection system for MODIS that is trained using collocated data from CALIOP and CPR. In particular, we employ a machine learning system that reads the radiative profile observed by MODIS and determine whether the field of view is cloudy or clear. Results have shown that the improved cloud detection scheme performs better than typical cloud mask algorithms using a validation data set not used for training. A one-year data set was generated and results indicate that daytime cloud detection accuracies improved from 80.1% to 92.6% (over sea-ice) and 71.2% to 87.4% (over ice-sheet) with CALIOP data used as the baseline. Significant improvements are also observed during nighttime, where cloud detection accuracies increase by 19.8% (over sea-ice) and 11.6% (over ice-sheet). The immediate impact of the new algorithm is that it can minimize large biases of MODIS-derived cloud amount over the Polar Regions and thus a more realistic and high quality global cloud statistics. In particular, our results show that cloud fraction in the Arctic is typically 81.2 % during daytime and 84.0% during nighttime. This is significantly higher than the 71.8% and 58.5%, respectively, derived from standard MODIS cloud product.

Testing a polarimetric cloud imager aboard research vessel Polarstern: comparison of color-based and polarimetric cloud detection algorithms.

PubMed

Barta, András; Horváth, Gábor; Horváth, Ákos; Egri, Ádám; Blahó, Miklós; Barta, Pál; Bumke, Karl; Macke, Andreas

2015-02-10

Cloud cover estimation is an important part of routine meteorological observations. Cloudiness measurements are used in climate model evaluation, nowcasting solar radiation, parameterizing the fluctuations of sea surface insolation, and building energy transfer models of the atmosphere. Currently, the most widespread ground-based method to measure cloudiness is based on analyzing the unpolarized intensity and color distribution of the sky obtained by digital cameras. As a new approach, we propose that cloud detection can be aided by the additional use of skylight polarization measured by 180° field-of-view imaging polarimetry. In the fall of 2010, we tested such a novel polarimetric cloud detector aboard the research vessel Polarstern during expedition ANT-XXVII/1. One of our goals was to test the durability of the measurement hardware under the extreme conditions of a trans-Atlantic cruise. Here, we describe the instrument and compare the results of several different cloud detection algorithms, some conventional and some newly developed. We also discuss the weaknesses of our design and its possible improvements. The comparison with cloud detection algorithms developed for traditional nonpolarimetric full-sky imagers allowed us to evaluate the added value of polarimetric quantities. We found that (1) neural-network-based algorithms perform the best among the investigated schemes and (2) global information (the mean and variance of intensity), nonoptical information (e.g., sun-view geometry), and polarimetric information (e.g., the degree of polarization) improve the accuracy of cloud detection, albeit slightly.

Lightning studies using LDAR and LLP data

NASA Technical Reports Server (NTRS)

Forbes, Gregory S.

1993-01-01

This study intercompared lightning data from LDAR and LLP systems in order to learn more about the spatial relationships between thunderstorm electrical discharges aloft and lightning strikes to the surface. The ultimate goal of the study is to provide information that can be used to improve the process of real-time detection and warning of lightning by weather forecasters who issue lightning advisories. The Lightning Detection and Ranging (LDAR) System provides data on electrical discharges from thunderstorms that includes cloud-ground flashes as well as lightning aloft (within cloud, cloud-to-cloud, and sometimes emanating from cloud to clear air outside or above cloud). The Lightning Location and Protection (LLP) system detects primarily ground strikes from lightning. Thunderstorms typically produce LDAR signals aloft prior to the first ground strike, so that knowledge of preferred positions of ground strikes relative to the LDAR data pattern from a thunderstorm could allow advance estimates of enhanced ground strike threat. Studies described in the report examine the position of LLP-detected ground strikes relative to the LDAR data pattern from the thunderstorms. The report also describes other potential approaches to the use of LDAR data in the detection and forecasting of lightning ground strikes.

A New Algorithm for Detecting Cloud Height using OMPS/LP Measurements

NASA Technical Reports Server (NTRS)

Chen, Zhong; DeLand, Matthew; Bhartia, Pawan K.

2016-01-01

The Ozone Mapping and Profiler Suite Limb Profiler (OMPS/LP) ozone product requires the determination of cloud height for each event to establish the lower boundary of the profile for the retrieval algorithm. We have created a revised cloud detection algorithm for LP measurements that uses the spectral dependence of the vertical gradient in radiance between two wavelengths in the visible and near-IR spectral regions. This approach provides better discrimination between clouds and aerosols than results obtained using a single wavelength. Observed LP cloud height values show good agreement with coincident Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) measurements.

Multi-layer cube sampling for liver boundary detection in PET-CT images.

PubMed

Liu, Xinxin; Yang, Jian; Song, Shuang; Song, Hong; Ai, Danni; Zhu, Jianjun; Jiang, Yurong; Wang, Yongtian

2018-06-01

Liver metabolic information is considered as a crucial diagnostic marker for the diagnosis of fever of unknown origin, and liver recognition is the basis of automatic diagnosis of metabolic information extraction. However, the poor quality of PET and CT images is a challenge for information extraction and target recognition in PET-CT images. The existing detection method cannot meet the requirement of liver recognition in PET-CT images, which is the key problem in the big data analysis of PET-CT images. A novel texture feature descriptor called multi-layer cube sampling (MLCS) is developed for liver boundary detection in low-dose CT and PET images. The cube sampling feature is proposed for extracting more texture information, which uses a bi-centric voxel strategy. Neighbour voxels are divided into three regions by the centre voxel and the reference voxel in the histogram, and the voxel distribution information is statistically classified as texture feature. Multi-layer texture features are also used to improve the ability and adaptability of target recognition in volume data. The proposed feature is tested on the PET and CT images for liver boundary detection. For the liver in the volume data, mean detection rate (DR) and mean error rate (ER) reached 95.15 and 7.81% in low-quality PET images, and 83.10 and 21.08% in low-contrast CT images. The experimental results demonstrated that the proposed method is effective and robust for liver boundary detection.

Looking Down Through the Clouds – Optical Attenuation through Real-Time Clouds

NASA Astrophysics Data System (ADS)

Burley, J.; Lazarewicz, A.; Dean, D.; Heath, N.

Detecting and identifying nuclear explosions in the atmosphere and on the surface of the Earth is critical for the Air Force Technical Applications Center (AFTAC) treaty monitoring mission. Optical signals, from surface or atmospheric nuclear explosions detected by satellite sensors, are attenuated by the atmosphere and clouds. Clouds present a particularly complex challenge as they cover up to seventy percent of the earth's surface. Moreover, their highly variable and diverse nature requires physics-based modeling. Determining the attenuation for each optical ray-path is uniquely dependent on the source geolocation, the specific optical transmission characteristics along that ray path, and sensor detection capabilities. This research details a collaborative AFTAC and AFIT effort to fuse worldwide weather data, from a variety of sources, to provide near-real-time profiles of atmospheric and cloud conditions and the resulting radiative transfer analysis for virtually any wavelength(s) of interest from source to satellite. AFIT has developed a means to model global clouds using the U.S. Air Force’s World Wide Merged Cloud Analysis (WWMCA) cloud data in a new toolset that enables radiance calculations through clouds from UV to RF wavelengths.

Cloud Detection of Optical Satellite Images Using Support Vector Machine

NASA Astrophysics Data System (ADS)

Lee, Kuan-Yi; Lin, Chao-Hung

2016-06-01

Cloud covers are generally present in optical remote-sensing images, which limit the usage of acquired images and increase the difficulty of data analysis, such as image compositing, correction of atmosphere effects, calculations of vegetation induces, land cover classification, and land cover change detection. In previous studies, thresholding is a common and useful method in cloud detection. However, a selected threshold is usually suitable for certain cases or local study areas, and it may be failed in other cases. In other words, thresholding-based methods are data-sensitive. Besides, there are many exceptions to control, and the environment is changed dynamically. Using the same threshold value on various data is not effective. In this study, a threshold-free method based on Support Vector Machine (SVM) is proposed, which can avoid the abovementioned problems. A statistical model is adopted to detect clouds instead of a subjective thresholding-based method, which is the main idea of this study. The features used in a classifier is the key to a successful classification. As a result, Automatic Cloud Cover Assessment (ACCA) algorithm, which is based on physical characteristics of clouds, is used to distinguish the clouds and other objects. In the same way, the algorithm called Fmask (Zhu et al., 2012) uses a lot of thresholds and criteria to screen clouds, cloud shadows, and snow. Therefore, the algorithm of feature extraction is based on the ACCA algorithm and Fmask. Spatial and temporal information are also important for satellite images. Consequently, co-occurrence matrix and temporal variance with uniformity of the major principal axis are used in proposed method. We aim to classify images into three groups: cloud, non-cloud and the others. In experiments, images acquired by the Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and images containing the landscapes of agriculture, snow area, and island are tested. Experiment results demonstrate the detection accuracy of the proposed method is better than related methods.

Investigation of multilayer magnetic domain lattice file

NASA Technical Reports Server (NTRS)

Torok, E. J.; Kamin, M.; Tolman, C. H.

1980-01-01

The feasibility of the self structured multilayered bubble domain memory as a mass memory medium for satellite applications is examined. Theoretical considerations of multilayer bubble supporting materials are presented, in addition to the experimental evaluation of current accessed circuitry for various memory functions. The design, fabrication, and test of four device designs is described, and a recommended memory storage area configuration is presented. Memory functions which were demonstrated include the current accessed propagation of bubble domains and stripe domains, pinning of stripe domain ends, generation of single and double bubbles, generation of arrays of coexisting strip and bubble domains in a single garnet layer, and demonstration of different values of the strip out field for single and double bubbles indicating adequate margins for data detection. All functions necessary to develop a multilayer self structured bubble memory device were demonstrated in individual experiments.

Detection of long duration cloud contamination in hyper-temporal NDVI imagery

NASA Astrophysics Data System (ADS)

Ali, A.; de Bie, C. A. J. M.; Skidmore, A. K.; Scarrott, R. G.

2012-04-01

NDVI time series imagery are commonly used as a reliable source for land use and land cover mapping and monitoring. However long duration cloud can significantly influence its precision in areas where persistent clouds prevails. Therefore quantifying errors related to cloud contamination are essential for accurate land cover mapping and monitoring. This study aims to detect long duration cloud contamination in hyper-temporal NDVI imagery based land cover mapping and monitoring. MODIS-Terra NDVI imagery (250 m; 16-day; Feb'03-Dec'09) were used after necessary pre-processing using quality flags and upper envelope filter (ASAVOGOL). Subsequently stacked MODIS-Terra NDVI image (161 layers) was classified for 10 to 100 clusters using ISODATA. After classifications, 97 clusters image was selected as best classified with the help of divergence statistics. To detect long duration cloud contamination, mean NDVI class profiles of 97 clusters image was analyzed for temporal artifacts. Results showed that long duration clouds affect the normal temporal progression of NDVI and caused anomalies. Out of total 97 clusters, 32 clusters were found with cloud contamination. Cloud contamination was found more prominent in areas where high rainfall occurs. This study can help to stop error propagation in regional land cover mapping and monitoring, caused by long duration cloud contamination.

Aircraft-based investigation of Dynamics-Aerosol-Chemistry-Cloud Interactions in Southern West Africa

NASA Astrophysics Data System (ADS)

Flamant, Cyrille

2017-04-01

The EU-funded project DACCIWA (Dynamics-Aerosol-Chemistry-Cloud Interactions in West Africa, http://www.dacciwa.eu) is investigating the relationship between weather, climate and air pollution in southern West Africa. The air over the coastal region of West Africa is a unique mixture of natural and anthropogenic gases, liquids and particles, emitted in an environment, in which multi-layer cloud decks frequently form. These exert a large influence on the local weather and climate, mainly due to their impact on radiation, the surface energy balance and thus the diurnal cycle of the atmospheric boundary layer. The main objective for the aircraft detachment was to build robust statistics of cloud properties in southern West Africa in different chemical landscapes to investigate the physical processes involved in their life cycle in such a complex chemical environment. As part of the DACCIWA field campaigns, three European aircraft (the German DLR Falcon 20, the French SAFIRE ATR 42 and the British BAS Twin Otter) conducted a total of 50 research flights across Ivory Coast, Ghana, Togo, and Benin from 27 June to 16 July 2016 for a total of 155 flight hours, including hours sponsored through 3 EUFAR projects. The aircraft were used in different ways based on their strengths, but all three had comparable instrumentation with the the capability to do gas-phase chemistry, aerosol and clouds, thereby generating a rich dataset of atmospheric conditions across the region. Eight types of flight objectives were conducted to achieve the goals of the DACCIWA: (i) Stratus clouds, (ii) Land-sea breeze clouds, (iii) Mid-level clouds, (iv) Biogenic emission, (v) City emissions, (vi) Flaring and ship emissions, (vii) Dust and biomass burning aerosols, and (viii) air-sea interactions. An overview of the DACCIWA aircraft campaign as well as first highlights from the airborne observations will be presented.

Mass transport on adsorbate multilayers studied by surface plasmon polariton wave excitation

NASA Astrophysics Data System (ADS)

Wang, X.; Fei, Y. Y.; Zhu, X. D.

2011-12-01

We excited surface-plasmon polariton waves (SPPW) on Cu(111) by coupling a monochromatic optical beam with a xenon multilayer thickness grating on the metal. The SPPW excitation was detected with an angle-resolved oblique-incidence reflectivity difference technique (OI-RD). The amplitude of the resonance OI-RD signal was a quadratic function of the grating modulation depth. By monitoring the decay of the resonance OI-RD signal as a function of time and temperature, we were able to study the mass transport of xenon that plays a key role in the annealing of a "rough" Xe multilayer crystalline film.

Powerful Hurricane Irma Seen in 3D by NASA's CloudSat

NASA Image and Video Library

2017-09-08

NASA's CloudSat satellite flew over Hurricane Irma on Sept. 6, 2017 at 1:45 p.m. EDT (17:45 UTC) as the storm was approaching Puerto Rico in the Atlantic Ocean. Hurricane Irma contained estimated maximum sustained winds of 185 miles per hour (160 knots) with a minimum pressure of 918 millibars. CloudSat transected the eastern edge of Hurricane Irma's eyewall, revealing details of the storm's cloud structure beneath its thick canopy of cirrus clouds. The CloudSat Cloud Profiling Radar excels in detecting the organization and placement of cloud layers beneath a storm's cirrus canopy, which are not readily detected by other satellite sensors. The CloudSat overpass reveals the inner details beneath the cloud tops of this large system; intense areas of convection with moderate to heavy rainfall (deep red and pink colors), cloud-free areas (moats) in between the inner and outer cloud bands of Hurricane Irma and cloud top heights averaging around 9 to 10 miles (15 to 16 kilometers). Lower values of reflectivity (areas of green and blue) denote smaller-sized ice and water particle sizes typically located at the top of a storm system (in the anvil area). The Cloud Profiling Radar loses signal at around 3 miles (5 kilometers) in height (in the melting layer) due to water (ice) particles larger than 0.12 inches (3 millimeters) in diameter. Moderate to heavy rainfall occurs in these areas where signal weakening is detectable. Smaller cumulus and cumulonimbus cloud types are evident as CloudSat moves farther south, beneath the thick cirrus canopy. An animation is available at https://photojournal.jpl.nasa.gov/catalog/PIA21947

Comparison of multilayer formation between different cellulose nanofibrils and cationic polymers.

PubMed

Eronen, Paula; Laine, Janne; Ruokolainen, Janne; Osterberg, Monika

2012-05-01

The multilayer formation between polyelectrolytes of opposite charge offers possibility for creating new tailored materials. Exchanging one or both components for charged nanofibrillated cellulose (NFC) further increases the variety of achievable properties. We explored this by introducing unmodified, low charged NFC and high charged TEMPO-oxidized NFC. Systematic evaluation of the effect of both NFC charge and properties of cationic polyelectrolytes on the structure of the multilayers was performed. As the cationic component cationic NFC was compared with two different cationic polyelectrolytes, poly(dimethyldiallylammoniumchloride) and cationic starch. Quartz crystal microbalance with dissipation (QCM-D) was used to monitor the multilayer formation and AFM colloidal probe microscopy (CPM) was further applied to probe surface interactions in order to gain information about fundamental interactions and layer properties. Generally, the results verified the characteristic multilayer formation between NFC of different charge and how the properties of formed multilayers can be tuned. However, the strong nonelectrostatic affinity between cellulosic fibrils was observed. CPM measurements revealed monotonically repulsive forces, which were in good correspondence with the QCM-D observations. Significant increase in adhesive forces was detected between the swollen high charged NFC. Copyright © 2011 Elsevier Inc. All rights reserved.

A Study of Global Cirrus Cloud Morphology with AIRS Cloud-clear Radiances (CCRs)

NASA Technical Reports Server (NTRS)

Wu, Dong L.; Gong, Jie

2012-01-01

Version 6 (V6) AIRS cloud-clear radiances (CCR) are used to derive cloud-induced radiance (Tcir=Tb-CCR) at the infrared frequencies of weighting functions peaked in the middle troposphere. The significantly improved V 6 CCR product allows a more accurate estimation of the expected clear-sky radiance as if clouds are absent. In the case where strong cloud scattering is present, the CCR becomes unreliable, which is reflected by its estimated uncertainty, and interpolation is employed to replace this CCR value. We find that Tcir derived from this CCR method are much better than other methods and detect more clouds in the upper and lower troposphere as well as in the polar regions where cloud detection is particularly challenging. The cloud morphology derived from the V6 test month, as well as some artifacts, will be shown.

Cloud Detection from Satellite Imagery: A Comparison of Expert-Generated and Automatically-Generated Decision Trees

NASA Technical Reports Server (NTRS)

Shiffman, Smadar

2004-01-01

Automated cloud detection and tracking is an important step in assessing global climate change via remote sensing. Cloud masks, which indicate whether individual pixels depict clouds, are included in many of the data products that are based on data acquired on- board earth satellites. Many cloud-mask algorithms have the form of decision trees, which employ sequential tests that scientists designed based on empirical astrophysics studies and astrophysics simulations. Limitations of existing cloud masks restrict our ability to accurately track changes in cloud patterns over time. In this study we explored the potential benefits of automatically-learned decision trees for detecting clouds from images acquired using the Advanced Very High Resolution Radiometer (AVHRR) instrument on board the NOAA-14 weather satellite of the National Oceanic and Atmospheric Administration. We constructed three decision trees for a sample of 8km-daily AVHRR data from 2000 using a decision-tree learning procedure provided within MATLAB(R), and compared the accuracy of the decision trees to the accuracy of the cloud mask. We used ground observations collected by the National Aeronautics and Space Administration Clouds and the Earth s Radiant Energy Systems S COOL project as the gold standard. For the sample data, the accuracy of automatically learned decision trees was greater than the accuracy of the cloud masks included in the AVHRR data product.

Very high cloud detection in more than two decades of HIRS data

NASA Astrophysics Data System (ADS)

Kolat, Utkan; Menzel, W. Paul; Olson, Erik; Frey, Richard

2013-04-01

This paper reports on the use of High-resolution Infrared Radiation Sounder (HIRS) measurements to infer the presence of upper tropospheric and lower stratospheric (UT/LS) clouds. UT/LS cloud detection is based on the fact that, when viewing an opaque UT/LS cloud that fills the sensor field of view, positive lapse rates above the tropopause cause a more absorbing CO2 or H2O-sensitive spectral band to measure a brightness temperature warmer than that of a less absorbing or nearly transparent infrared window spectral band. The HIRS sensor has flown on 16 polar-orbiting satellites from TIROS-N through NOAA-19 and Metop-A and -B, forming the only 30 year record that includes H2O and CO2-sensitive spectral bands enabling the detection of these UT/LS clouds. Comparison with collocated Cloud-Aerosol Lidar with Orthogonal Polarization data reveals that 97% of the HIRS UT/LS cloud determinations are within 2.5 km of the tropopause (defined as the coldest level in the National Centers for Environmental Prediction Global Data Assimilation System); more clouds are found above the tropopause than below. From NOAA-14 data spanning 1995 through 2005, we find indications of UT/LS clouds in 0.7% of the observations from 60N to 60S using CO2 absorption bands; however, in the region of the Inter-Tropical Convergence Zone (ITCZ), this increases to 1.7%. During El Niño years, UT/LS clouds shift eastward out of their normal location in the western Pacific region. Monthly trends from 1987 through 2011 using data from NOAA-10 onwards show decreases in UT/LS cloud detection in the region of the ITCZ from 1987 until 1996, increases until 2001, and decreases thereafter.

External Influences on Modeled and Observed Cloud Trends

NASA Technical Reports Server (NTRS)

Marvel, Kate; Zelinka, Mark; Klein, Stephen A.; Bonfils, Celine; Caldwell, Peter; Doutriaux, Charles; Santer, Benjamin D.; Taylor, Karl E.

2015-01-01

Understanding the cloud response to external forcing is a major challenge for climate science. This crucial goal is complicated by intermodel differences in simulating present and future cloud cover and by observational uncertainty. This is the first formal detection and attribution study of cloud changes over the satellite era. Presented herein are CMIP5 (Coupled Model Intercomparison Project - Phase 5) model-derived fingerprints of externally forced changes to three cloud properties: the latitudes at which the zonally averaged total cloud fraction (CLT) is maximized or minimized, the zonal average CLT at these latitudes, and the height of high clouds at these latitudes. By considering simultaneous changes in all three properties, the authors define a coherent multivariate fingerprint of cloud response to external forcing and use models from phase 5 of CMIP (CMIP5) to calculate the average time to detect these changes. It is found that given perfect satellite cloud observations beginning in 1983, the models indicate that a detectable multivariate signal should have already emerged. A search is then made for signals of external forcing in two observational datasets: ISCCP (International Satellite Cloud Climatology Project) and PATMOS-x (Advanced Very High Resolution Radiometer (AVHRR) Pathfinder Atmospheres - Extended). The datasets are both found to show a poleward migration of the zonal CLT pattern that is incompatible with forced CMIP5 models. Nevertheless, a detectable multivariate signal is predicted by models over the PATMOS-x time period and is indeed present in the dataset. Despite persistent observational uncertainties, these results present a strong case for continued efforts to improve these existing satellite observations, in addition to planning for new missions.

[A cloud detection algorithm for MODIS images combining Kmeans clustering and multi-spectral threshold method].

PubMed

Wang, Wei; Song, Wei-Guo; Liu, Shi-Xing; Zhang, Yong-Ming; Zheng, Hong-Yang; Tian, Wei

2011-04-01

An improved method for detecting cloud combining Kmeans clustering and the multi-spectral threshold approach is described. On the basis of landmark spectrum analysis, MODIS data is categorized into two major types initially by Kmeans method. The first class includes clouds, smoke and snow, and the second class includes vegetation, water and land. Then a multi-spectral threshold detection is applied to eliminate interference such as smoke and snow for the first class. The method is tested with MODIS data at different time under different underlying surface conditions. By visual method to test the performance of the algorithm, it was found that the algorithm can effectively detect smaller area of cloud pixels and exclude the interference of underlying surface, which provides a good foundation for the next fire detection approach.

Anomalous Signal Detection in ELF Band Electromagnetic Wave using Multi-layer Neural Network with Wavelet Decomposition

NASA Astrophysics Data System (ADS)

Itai, Akitoshi; Yasukawa, Hiroshi; Takumi, Ichi; Hata, Masayasu

It is well known that electromagnetic waves radiated from the earth's crust are useful for predicting earthquakes. We analyze the electromagnetic waves received at the extremely low frequency band of 223Hz. These observed signals contain the seismic radiation from the earth's crust, but also include several undesired signals. Our research focuses on the signal detection technique to identify an anomalous signal corresponding to the seismic radiation in the observed signal. Conventional anomalous signal detections lack a wide applicability due to their assumptions, e.g. the digital data have to be observed at the same time or the same sensor. In order to overcome the limitation related to the observed signal, we proposed the anomalous signals detection based on a multi-layer neural network which is trained by digital data observed during a span of a day. In the neural network approach, training data do not need to be recorded at the same place or the same time. However, some noises, which have a large amplitude, are detected as the anomalous signal. This paper develops a multi-layer neural network to decrease the false detection of the anomalous signal from the electromagnetic wave. The training data for the proposed network is the decomposed signal of the observed signal during several days, since the seismic radiations are often recorded from several days to a couple of weeks. Results show that the proposed neural network is useful to achieve the accurate detection of the anomalous signal that indicates seismic activity.

Retrievals of Cloud Droplet Size from the RSP Data: Validation Using in Situ Measurements

NASA Technical Reports Server (NTRS)

Alexandrov, Mikhail D.; Cairns, Brian; Sinclair, Kenneth; Wasilewski, Andrzej P.; Ziemba, Luke; Crosbie, Ewan; Hair, John; Hu, Yongxiang; Hostetler, Chris; Stamnes, Snorre

2016-01-01

We present comparisons of cloud droplet size distributions retrieved from the Research Scanning Polarimeter (RSP) data with correlative in situ measurements made during the North Atlantic Aerosols and Marine Ecosystems Study (NAAMES). This field experiment was based at St. Johns airport, Newfoundland, Canada with the latest deployment in May - June 2016. RSP was onboard the NASA C-130 aircraft together with an array of in situ and other remote sensing instrumentation. The RSP is an along-track scanner measuring polarized and total reflectances in9 spectral channels. Its unique high angular resolution allows for characterization of liquid water droplet size using the rainbow structure observed in the polarized reflectances in the scattering angle range between 135 and 165 degrees. A parametric fitting algorithm applied to the polarized reflectances provides retrievals of the droplet effective radius and variance assuming a prescribed size distribution shape (gamma distribution). In addition to this, we use a non-parametric method, Rainbow Fourier Transform (RFT), which allows us to retrieve the droplet size distribution (DSD) itself. The latter is important in the case of clouds with complex structure, which results in multi-modal DSDs. During NAAMES the aircraft performed a number of flight patterns specifically designed for comparison of remote sensing retrievals and in situ measurements. These patterns consisted of two flight segments above the same straight ground track. One of these segments was flown above clouds allowing for remote sensing measurements, while the other was at the cloud top where cloud droplets were sampled. We compare the DSDs retrieved from the RSP data with in situ measurements made by the Cloud Droplet Probe (CDP). The comparisons show generally good agreement with deviations explainable by the position of the aircraft within cloud and by presence of additional cloud layers in RSP view that do not contribute to the in situ DSDs. In the latter case the distributions retrieved from the RSP data were consistent with the multi-layer cloud structures observed in the correlative High Spectral Resolution Lidar (HSRL) profiles. The comparison results provide a rare validation of polarimetric droplet size retrieval techniques, which can be used for analysis of satellite data on global scale.

Person detection and tracking with a 360° lidar system

NASA Astrophysics Data System (ADS)

Hammer, Marcus; Hebel, Marcus; Arens, Michael

2017-10-01

Today it is easily possible to generate dense point clouds of the sensor environment using 360° LiDAR (Light Detection and Ranging) sensors which are available since a number of years. The interpretation of these data is much more challenging. For the automated data evaluation the detection and classification of objects is a fundamental task. Especially in urban scenarios moving objects like persons or vehicles are of particular interest, for instance in automatic collision avoidance, for mobile sensor platforms or surveillance tasks. In literature there are several approaches for automated person detection in point clouds. While most techniques show acceptable results in object detection, the computation time is often crucial. The runtime can be problematic, especially due to the amount of data in the panoramic 360° point clouds. On the other hand, for most applications an object detection and classification in real time is needed. The paper presents a proposal for a fast, real-time capable algorithm for person detection, classification and tracking in panoramic point clouds.

Wheatstone bridge-giant magnetoresistance (GMR) sensors based on Co/Cu multilayers for bio-detection applications

NASA Astrophysics Data System (ADS)

Antarnusa, G.; Elda Swastika, P.; Suharyadi, E.

2018-04-01

A Wheatstone bridge-giant magnetoresistance (GMR) sensor was successfully developed for a potential biomaterial detection. In order to achieve this, a giant magnetoresistive [Co(1.5nm/Cu(1.0nm)]20 multilayer structures have been fabricated by DC magnetron sputtering method, showing a magnetoresistance (MR) of 2.7%. The X-Ray diffraction (XRD) patterns showed that Co/Cu film multilayer has a high degree of crystallinity with a single peak corresponding to face-centered cubic (111) structure at 2θ = 44.1°. Co/Cu multilayers exhibit a soft magnetic behavior with the saturation magnetization (Ms) of 1489 emu/cc and the coercivity (Hc) of 11.2 Oe. The magnetite Fe3O4 nanoparticles used as a bimolecular labels (nanotags) were synthesized via co-precipitation method, exhibiting a soft magnetic behavior with Ms of 77.16 emu/g and Hc of 49 Oe. XRD patterns and transmission electron microscopy (TEM) images showed that Fe3O4 was well crystallized and it grew in their inverse spinel structure with an average size of around 10 nm. The GMR sensor design was used to detect a biomolecules of streptavidin magnetic particles with concentration 10, 20, 30, and 40 μl/ml and α-amylase enzyme with consentration 10, 20, 30, and 40 μl/ml captured using polyethylene glycol (PEG)/Fe3O4 nanoparticles. Various applied magnetic fields of 0-650 Gauss have been performed using electromagnetic with the various currents of 0-5 A. Here, the final value of the output voltage signals for the streptavidin magnetic particles concentration is 1.2 mV (10 μl/ml). The output voltage changes with the increase of concentration. It was reported that the output voltage signal of the Wheatstone bridge exhibits log-linear function in real time measurement of the concentration of streptavidin magnetic particles and α-amylase enzyme respectively, making the sensor suitable for use as a biomolecule concentration detector. Thus, the combination of Co/Cu multilayer, Wheatstone bridge, magnetite and PEG polymer has potential application to be used in bio-detection applications where ultra-small bio-labels are needed.

Automatic Detection of Clouds and Shadows Using High Resolution Satellite Image Time Series

NASA Astrophysics Data System (ADS)

Champion, Nicolas

2016-06-01

Detecting clouds and their shadows is one of the primaries steps to perform when processing satellite images because they may alter the quality of some products such as large-area orthomosaics. The main goal of this paper is to present the automatic method developed at IGN-France for detecting clouds and shadows in a sequence of satellite images. In our work, surface reflectance orthoimages are used. They were processed from initial satellite images using a dedicated software. The cloud detection step consists of a region-growing algorithm. Seeds are firstly extracted. For that purpose and for each input ortho-image to process, we select the other ortho-images of the sequence that intersect it. The pixels of the input ortho-image are secondly labelled seeds if the difference of reflectance (in the blue channel) with overlapping ortho-images is bigger than a given threshold. Clouds are eventually delineated using a region-growing method based on a radiometric and homogeneity criterion. Regarding the shadow detection, our method is based on the idea that a shadow pixel is darker when comparing to the other images of the time series. The detection is basically composed of three steps. Firstly, we compute a synthetic ortho-image covering the whole study area. Its pixels have a value corresponding to the median value of all input reflectance ortho-images intersecting at that pixel location. Secondly, for each input ortho-image, a pixel is labelled shadows if the difference of reflectance (in the NIR channel) with the synthetic ortho-image is below a given threshold. Eventually, an optional region-growing step may be used to refine the results. Note that pixels labelled clouds during the cloud detection are not used for computing the median value in the first step; additionally, the NIR input data channel is used to perform the shadow detection, because it appeared to better discriminate shadow pixels. The method was tested on times series of Landsat 8 and Pléiades-HR images and our first experiments show the feasibility to automate the detection of shadows and clouds in satellite image sequences.

Hypervelocity Impact (HVI). Volume 2; WLE Small-Scale Fiberglass Panel Flat Multi-Layer Targets A-1, A-2, and B-1

NASA Technical Reports Server (NTRS)

Gorman, Michael R.; Ziola, Steven M.

2007-01-01

During 2003 and 2004, the Johnson Space Center's White Sands Testing Facility in Las Cruces, New Mexico conducted hypervelocity impact tests on the space shuttle wing leading edge. Hypervelocity impact tests were conducted to determine if Micro-Meteoroid/Orbital Debris impacts could be reliably detected and located using simple passive ultrasonic methods. The objective of Targets A-1, A-2, and B-2 was to study hypervelocity impacts through multi-layered panels simulating Whipple shields on spacecraft. Impact damage was detected using lightweight, low power instrumentation capable of being used in flight.

Results from the Two-Year Infrared Cloud Imager Deployment at ARM's NSA Observatory in Barrow, Alaska

NASA Astrophysics Data System (ADS)

Shaw, J. A.; Nugent, P. W.

2016-12-01

Ground-based longwave-infrared (LWIR) cloud imaging can provide continuous cloud measurements in the Arctic. This is of particular importance during the Arctic winter when visible wavelength cloud imaging systems cannot operate. This method uses a thermal infrared camera to observe clouds and produce measurements of cloud amount and cloud optical depth. The Montana State University Optical Remote Sensor Laboratory deployed an infrared cloud imager (ICI) at the Atmospheric Radiation Monitoring North Slope of Alaska site at Barrow, AK from July 2012 through July 2014. This study was used to both understand the long-term operation of an ICI in the Arctic and to study the consistency of the ICI data products in relation to co-located active and passive sensors. The ICI was found to have a high correlation (> 0.92) with collocated cloud instruments and to produce an unbiased data product. However, the ICI also detects thin clouds that are not detected by most operational cloud sensors. Comparisons with high-sensitivity actively sensed cloud products confirm the existence of these thin clouds. Infrared cloud imaging systems can serve a critical role in developing our understanding of cloud cover in the Arctic by provided a continuous annual measurement of clouds at sites of interest.

A multi-layer steganographic method based on audio time domain segmented and network steganography

NASA Astrophysics Data System (ADS)

Xue, Pengfei; Liu, Hanlin; Hu, Jingsong; Hu, Ronggui

2018-05-01

Both audio steganography and network steganography are belong to modern steganography. Audio steganography has a large capacity. Network steganography is difficult to detect or track. In this paper, a multi-layer steganographic method based on the collaboration of them (MLS-ATDSS&NS) is proposed. MLS-ATDSS&NS is realized in two covert layers (audio steganography layer and network steganography layer) by two steps. A new audio time domain segmented steganography (ATDSS) method is proposed in step 1, and the collaboration method of ATDSS and NS is proposed in step 2. The experimental results showed that the advantage of MLS-ATDSS&NS over others is better trade-off between capacity, anti-detectability and robustness, that means higher steganographic capacity, better anti-detectability and stronger robustness.

GPU based cloud system for high-performance arrhythmia detection with parallel k-NN algorithm.

PubMed

Tae Joon Jun; Hyun Ji Park; Hyuk Yoo; Young-Hak Kim; Daeyoung Kim

2016-08-01

In this paper, we propose an GPU based Cloud system for high-performance arrhythmia detection. Pan-Tompkins algorithm is used for QRS detection and we optimized beat classification algorithm with K-Nearest Neighbor (K-NN). To support high performance beat classification on the system, we parallelized beat classification algorithm with CUDA to execute the algorithm on virtualized GPU devices on the Cloud system. MIT-BIH Arrhythmia database is used for validation of the algorithm. The system achieved about 93.5% of detection rate which is comparable to previous researches while our algorithm shows 2.5 times faster execution time compared to CPU only detection algorithm.

Green Bank Telescope Detection of HI Clouds in the Fermi Bubble Wind

NASA Astrophysics Data System (ADS)

Lockman, Felix; Di Teodoro, Enrico M.; McClure-Griffiths, Naomi M.

2018-01-01

We used the Robert C. Byrd Green Bank Telescope to map HI 21cm emission in two large regions around the Galactic Center in a search for HI clouds that might be entrained in the nuclear wind that created the Fermi bubbles. In a ~160 square degree region at |b|>4 deg. and |long|<10 deg we detect 106 HI clouds that have large non-circular velocities consistent with their acceleration by the nuclear wind. Rapidly moving clouds are found as far as 1.5 kpc from the center; there are no detectable asymmetries in the cloud populations above and below the Galactic Center. The cloud kinematics is modeled as a population with an outflow velocity of 330 km/s that fills a cone with an opening angle ~140 degrees. The total mass in the clouds is ~10^6 solar masses and we estimate cloud lifetimes to be between 2 and 8 Myr, implying a cold gas mass-loss rate of about 0.1 solar masses per year into the nuclear wind.The Green Bank Telescope is a facility of the National Science Foundation, operated under a cooperative agreement by Associated Universities, Inc.

3D cloud detection and tracking system for solar forecast using multiple sky imagers

DOE PAGES

Peng, Zhenzhou; Yu, Dantong; Huang, Dong; ...

2015-06-23

We propose a system for forecasting short-term solar irradiance based on multiple total sky imagers (TSIs). The system utilizes a novel method of identifying and tracking clouds in three-dimensional space and an innovative pipeline for forecasting surface solar irradiance based on the image features of clouds. First, we develop a supervised classifier to detect clouds at the pixel level and output cloud mask. In the next step, we design intelligent algorithms to estimate the block-wise base height and motion of each cloud layer based on images from multiple TSIs. Thus, this information is then applied to stitch images together intomore » larger views, which are then used for solar forecasting. We examine the system’s ability to track clouds under various cloud conditions and investigate different irradiance forecast models at various sites. We confirm that this system can 1) robustly detect clouds and track layers, and 2) extract the significant global and local features for obtaining stable irradiance forecasts with short forecast horizons from the obtained images. Finally, we vet our forecasting system at the 32-megawatt Long Island Solar Farm (LISF). Compared with the persistent model, our system achieves at least a 26% improvement for all irradiance forecasts between one and fifteen minutes.« less

Using sky radiances measured by ground based AERONET Sun-Radiometers for cirrus cloud detection

NASA Astrophysics Data System (ADS)

Sinyuk, A.; Holben, B. N.; Eck, T. F.; Slutsker, I.; Lewis, J. R.

2013-12-01

Screening of cirrus clouds using observations of optical depth (OD) only has proven to be a difficult task due mostly to some clouds having temporally and spatially stable OD. On the other hand, the sky radiances measurements which in AERONET protocol are taken throughout the day may contain additional cloud information. In this work the potential of using sky radiances for cirrus cloud detection is investigated. The detection is based on differences in the angular shape of sky radiances due to cirrus clouds and aerosol (see Figure). The range of scattering angles from 3 to 6 degrees was selected due to two primary reasons: high sensitivity to cirrus clouds presence, and close proximity to the Sun. The angular shape of sky radiances was parametrized by its curvature, which is a parameter defined as a combination of the first and second derivatives as a function of scattering angle. We demonstrate that a slope of the logarithm of curvature versus logarithm of scattering angle in this selected range of scattering angles is sensitive to cirrus cloud presence. We also demonstrate that restricting the values of the slope below some threshold value can be used for cirrus cloud screening. The threshold value of the slope was estimated using collocated measurements of AERONET data and MPLNET lidars.

Efficient Flame Detection and Early Warning Sensors on Combustible Materials Using Hierarchical Graphene Oxide/Silicone Coatings.

PubMed

Wu, Qian; Gong, Li-Xiu; Li, Yang; Cao, Cheng-Fei; Tang, Long-Cheng; Wu, Lianbin; Zhao, Li; Zhang, Guo-Dong; Li, Shi-Neng; Gao, Jiefeng; Li, Yongjin; Mai, Yiu-Wing

2018-01-23

Design and development of smart sensors for rapid flame detection in postcombustion and early fire warning in precombustion situations are critically needed to improve the fire safety of combustible materials in many applications. Herein, we describe the fabrication of hierarchical coatings created by assembling a multilayered graphene oxide (GO)/silicone structure onto different combustible substrate materials. The resulting coatings exhibit distinct temperature-responsive electrical resistance change as efficient early warning sensors for detecting abnormal high environmental temperature, thus enabling fire prevention below the ignition temperature of combustible materials. After encountering a flame attack, we demonstrate extremely rapid flame detection response in 2-3 s and excellent flame self-extinguishing retardancy for the multilayered GO/silicone structure that can be synergistically transformed to a multiscale graphene/nanosilica protection layer. The hierarchical coatings developed are promising for fire prevention and protection applications in various critical fire risk and related perilous circumstances.

Multilayer Statistical Intrusion Detection in Wireless Networks

NASA Astrophysics Data System (ADS)

Hamdi, Mohamed; Meddeb-Makhlouf, Amel; Boudriga, Noureddine

2008-12-01

The rapid proliferation of mobile applications and services has introduced new vulnerabilities that do not exist in fixed wired networks. Traditional security mechanisms, such as access control and encryption, turn out to be inefficient in modern wireless networks. Given the shortcomings of the protection mechanisms, an important research focuses in intrusion detection systems (IDSs). This paper proposes a multilayer statistical intrusion detection framework for wireless networks. The architecture is adequate to wireless networks because the underlying detection models rely on radio parameters and traffic models. Accurate correlation between radio and traffic anomalies allows enhancing the efficiency of the IDS. A radio signal fingerprinting technique based on the maximal overlap discrete wavelet transform (MODWT) is developed. Moreover, a geometric clustering algorithm is presented. Depending on the characteristics of the fingerprinting technique, the clustering algorithm permits to control the false positive and false negative rates. Finally, simulation experiments have been carried out to validate the proposed IDS.

Constructing a Merged Cloud-Precipitation Radar Dataset for Tropical Convective Clouds during the DYNAMO/AMIE Experiment at Addu Atoll

DOE Office of Scientific and Technical Information (OSTI.GOV)

Feng, Zhe; McFarlane, Sally A.; Schumacher, Courtney

2014-05-16

To improve understanding of the convective processes key to the Madden-Julian-Oscillation (MJO) initiation, the Dynamics of the MJO (DYNAMO) and Atmospheric Radiation Measurement MJO Investigation Experiment (AMIE) collected four months of observations from three radars, the S-band Polarization Radar (S-Pol), the C-band Shared Mobile Atmospheric Research & Teaching Radar (SMART-R), and Ka-band Zenith Radar (KAZR) on Addu Atoll in the tropical Indian Ocean. This study compares the measurements from the S-Pol and SMART-R to those from the more sensitive KAZR in order to characterize the hydrometeor detection capabilities of the two scanning precipitation radars. Frequency comparisons for precipitating convective cloudsmore » and non-precipitating high clouds agree much better than non-precipitating low clouds for both scanning radars due to issues in ground clutter. On average, SMART-R underestimates convective and high cloud tops by 0.3 to 1.1 km, while S-Pol underestimates cloud tops by less than 0.4 km for these cloud types. S-Pol shows excellent dynamic range in detecting various types of clouds and therefore its data are well suited for characterizing the evolution of the 3D cloud structures, complementing the profiling KAZR measurements. For detecting non-precipitating low clouds and thin cirrus clouds, KAZR remains the most reliable instrument. However, KAZR is attenuated in heavy precipitation and underestimates cloud top height due to rainfall attenuation 4.3% of the time during DYNAMO/AMIE. An empirical method to correct the KAZR cloud top heights is described, and a merged radar dataset is produced to provide improved cloud boundary estimates, microphysics and radiative heating retrievals.« less

A threshold-based cloud mask for the high-resolution visible channel of Meteosat Second Generation SEVIRI

NASA Astrophysics Data System (ADS)

Bley, S.; Deneke, H.

2013-10-01

A threshold-based cloud mask for the high-resolution visible (HRV) channel (1 × 1 km2) of the Meteosat SEVIRI (Spinning Enhanced Visible and Infrared Imager) instrument is introduced and evaluated. It is based on operational EUMETSAT cloud mask for the low-resolution channels of SEVIRI (3 × 3 km2), which is used for the selection of suitable thresholds to ensure consistency with its results. The aim of using the HRV channel is to resolve small-scale cloud structures that cannot be detected by the low-resolution channels. We find that it is of advantage to apply thresholds relative to clear-sky reflectance composites, and to adapt the threshold regionally. Furthermore, the accuracy of the different spectral channels for thresholding and the suitability of the HRV channel are investigated for cloud detection. The case studies show different situations to demonstrate the behavior for various surface and cloud conditions. Overall, between 4 and 24% of cloudy low-resolution SEVIRI pixels are found to contain broken clouds in our test data set depending on considered region. Most of these broken pixels are classified as cloudy by EUMETSAT's cloud mask, which will likely result in an overestimate if the mask is used as an estimate of cloud fraction. The HRV cloud mask aims for small-scale convective sub-pixel clouds that are missed by the EUMETSAT cloud mask. The major limit of the HRV cloud mask is the minimum cloud optical thickness (COT) that can be detected. This threshold COT was found to be about 0.8 over ocean and 2 over land and is highly related to the albedo of the underlying surface.

Analysis of geostationary satellite-derived cloud parameters associated with environments with high ice water content

NASA Astrophysics Data System (ADS)

de Laat, Adrianus; Defer, Eric; Delanoë, Julien; Dezitter, Fabien; Gounou, Amanda; Grandin, Alice; Guignard, Anthony; Fokke Meirink, Jan; Moisselin, Jean-Marc; Parol, Frédéric

2017-04-01

We present an evaluation of the ability of passive broadband geostationary satellite measurements to detect high ice water content (IWC > 1 g m-3) as part of the European High Altitude Ice Crystals (HAIC) project for detection of upper-atmospheric high IWC, which can be a hazard for aviation. We developed a high IWC mask based on measurements of cloud properties using the Cloud Physical Properties (CPP) algorithm applied to the geostationary Meteosat Second Generation (MSG) Spinning Enhanced Visible and Infrared Imager (SEVIRI). Evaluation of the high IWC mask with satellite measurements of active remote sensors of cloud properties (CLOUDSAT/CALIPSO combined in the DARDAR (raDAR-liDAR) product) reveals that the high IWC mask is capable of detecting high IWC values > 1 g m-3 in the DARDAR profiles with a probability of detection of 60-80 %. The best CPP predictors of high IWC were the condensed water path, cloud optical thickness, cloud phase, and cloud top height. The evaluation of the high IWC mask against DARDAR provided indications that the MSG-CPP high IWC mask is more sensitive to cloud ice or cloud water in the upper part of the cloud, which is relevant for aviation purposes. Biases in the CPP results were also identified, in particular a solar zenith angle (SZA) dependence that reduces the performance of the high IWC mask for SZAs > 60°. Verification statistics show that for the detection of high IWC a trade-off has to be made between better detection of high IWC scenes and more false detections, i.e., scenes identified by the high IWC mask that do not contain IWC > 1 g m-3. However, the large majority of these detections still contain IWC values between 0.1 and 1 g m-3. Comparison of the high IWC mask against results from the Rapidly Developing Thunderstorm (RDT) algorithm applied to the same geostationary SEVIRI data showed that there are similarities and differences with the high IWC mask: the RDT algorithm is very capable of detecting young/new convective cells and areas, whereas the high IWC mask appears to be better capable of detecting more mature and ageing convection as well as cirrus remnants. The lack of detailed understanding of what causes aviation hazards related to high IWC, as well as the lack of clearly defined user requirements, hampers further tuning of the high IWC mask. Future evaluation of the high IWC mask against field campaign data, as well as obtaining user feedback and user requirements from the aviation industry, should provide more information on the performance of the MSG-CPP high IWC mask and contribute to improving the practical use of the high IWC mask.

Global Measurements of Optically Thin Ice Clouds Using CALIOP

NASA Technical Reports Server (NTRS)

Ryan, R.; Avery, M.; Tackett, J.

2017-01-01

Optically thin ice clouds have been shown to have a net warming effect on the globe but, because passive instruments are not sensitive to optically thin clouds, the occurrence frequency of this class of clouds is greatly underestimated in historical passive sensor cloud climatology. One major strength of CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization), onboard the CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations) spacecraft, is its ability to detect these thin clouds, thus filling an important missing piece in the historical data record. This poster examines the full mission of CALIPSO Level 2 data, focusing on those CALIOP retrievals identified as thin ice clouds according to the definition shown to the right. Using this definition, thin ice clouds are identified and counted globally and vertically for each season. By examining the spatial and seasonal distributions of these thin clouds we hope to gain a better understanding these thin ice clouds and how their global distribution has changed over the mission. This poster showcases when and where CALIOP detects thin ice clouds and examines a case study of the eastern pacific and the effects seen from the El Nino-Southern Oscillation (ENSO).

The response of the Seasat and Magsat infrared horizon scanners to cold clouds

NASA Technical Reports Server (NTRS)

Bilanow, S.; Phenneger, M.

1980-01-01

Cold clouds over the Earth are shown to be the principal cause of pitch and roll measurement noise in flight data from the infrared horizon scanners onboard Seasat and Magsat. The observed effects of clouds on the fixed threshold horizon detection logic of the Magsat scanner and on the variable threshold detection logic of the Seasat scanner are discussed. National Oceanic and Atmospheric Administration (NOAA) Earth photographs marked with the scanner ground trace clearly confirm the relationship between measurement errors and Earth clouds. A one to one correspondence can be seen between excursion in the pitch and roll data and cloud crossings. The characteristics of the cloud-induced noise are discussed, and the response of the satellite control systems to the cloud errors is described. Changes to the horizon scanner designs that would reduce the effects of clouds are noted.

Fast Self-Healing of Polyelectrolyte Multilayer Nanocoating and Restoration of Super Oxygen Barrier.

PubMed

Song, Yixuan; Meyers, Kevin P; Gerringer, Joseph; Ramakrishnan, Ramesh K; Humood, Mohammad; Qin, Shuang; Polycarpou, Andreas A; Nazarenko, Sergei; Grunlan, Jaime C

2017-05-01

A self-healable gas barrier nanocoating, which is fabricated by alternate deposition of polyethyleneimine (PEI) and polyacrylic acid (PAA) polyelectrolytes, is demonstrated in this study. This multilayer film, with high elastic modulus, high glass transition temperature, and small free volume, has been shown to be a super oxygen gas barrier. An 8-bilayer PEI/PAA multilayer assembly (≈700 nm thick) exhibits an oxygen transmission rate (OTR) undetectable to commercial instrumentation (<0.005 cc (m -2 d -1 atm -1 )). The barrier property of PEI/PAA nanocoating is lost after a moderate amount of stretching due to its rigidity, which is then completely restored after high humidity exposure, therefore achieving a healing efficiency of 100%. The OTR of the multilayer nanocoating remains below the detection limit after ten stretching-healing cycles, which proves this healing process to be highly robust. The high oxygen barrier and self-healing behavior of this polymer multilayer nanocoating makes it ideal for packaging (food, electronics, and pharmaceutical) and gas separation applications. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The first observed cloud echoes and microphysical parameter retrievals by China's 94-GHz cloud radar

NASA Astrophysics Data System (ADS)

Wu, Juxiu; Wei, Ming; Hang, Xin; Zhou, Jie; Zhang, Peichang; Li, Nan

2014-06-01

By using the cloud echoes first successfully observed by China's indigenous 94-GHz SKY cloud radar, the macrostructure and microphysical properties of drizzling stratocumulus clouds in Anhui Province on 8 June 2013 are analyzed, and the detection capability of this cloud radar is discussed. The results are as follows. (1) The cloud radar is able to observe the time-varying macroscopic and microphysical parameters of clouds, and it can reveal the microscopic structure and small-scale changes of clouds. (2) The velocity spectral width of cloud droplets is small, but the spectral width of the cloud containing both cloud droplets and drizzle is large. When the spectral width is more than 0.4 m s-1, the radar reflectivity factor is larger (over -10 dBZ). (3) The radar's sensitivity is comparatively higher because the minimum radar reflectivity factor is about -35 dBZ in this experiment, which exceeds the threshold for detecting the linear depolarized ratio (LDR) of stratocumulus (commonly -11 to -14 dBZ; decreases with increasing turbulence). (4) After distinguishing of cloud droplets from drizzle, cloud liquid water content and particle effective radius are retrieved. The liquid water content of drizzle is lower than that of cloud droplets at the same radar reflectivity factor.

Detection of nitric oxide in the dark cloud L134N

NASA Technical Reports Server (NTRS)

Mcgonagle, D.; Irvine, W. M.; Minh, Y. C.; Ziurys, L. M.

1990-01-01

The first detection of interstellar nitric oxide (NO) in a cold dark cloud, L134N is reported. Nitric oxide was observed by means of its two 2 Pi 1/2, J = 3/2 - 1/2, rotational transitions at 150.2 and 150.5 GHz, which occur because of Lambda-doubling. The inferred column density for L134N is about 5 x 10 to the 14th/sq cm toward the SO peak in that cloud. This value corresponds to a fractional abundance relative to molecular hydrogen of about 6 x 10 to the -8th and is in good agreement with predictions of quiescent cloud ion-molecule chemistry. NO was not detected toward the dark cloud TMC-1 at an upper limit of 3 x 10 to the -8th or less.

A hybrid wavelet analysis-cloud model data-extending approach for meteorologic and hydrologic time series

NASA Astrophysics Data System (ADS)

Wang, Dong; Ding, Hao; Singh, Vijay P.; Shang, Xiaosan; Liu, Dengfeng; Wang, Yuankun; Zeng, Xiankui; Wu, Jichun; Wang, Lachun; Zou, Xinqing

2015-05-01

For scientific and sustainable management of water resources, hydrologic and meteorologic data series need to be often extended. This paper proposes a hybrid approach, named WA-CM (wavelet analysis-cloud model), for data series extension. Wavelet analysis has time-frequency localization features, known as "mathematics microscope," that can decompose and reconstruct hydrologic and meteorologic series by wavelet transform. The cloud model is a mathematical representation of fuzziness and randomness and has strong robustness for uncertain data. The WA-CM approach first employs the wavelet transform to decompose the measured nonstationary series and then uses the cloud model to develop an extension model for each decomposition layer series. The final extension is obtained by summing the results of extension of each layer. Two kinds of meteorologic and hydrologic data sets with different characteristics and different influence of human activity from six (three pairs) representative stations are used to illustrate the WA-CM approach. The approach is also compared with four other methods, which are conventional correlation extension method, Kendall-Theil robust line method, artificial neural network method (back propagation, multilayer perceptron, and radial basis function), and single cloud model method. To evaluate the model performance completely and thoroughly, five measures are used, which are relative error, mean relative error, standard deviation of relative error, root mean square error, and Thiel inequality coefficient. Results show that the WA-CM approach is effective, feasible, and accurate and is found to be better than other four methods compared. The theory employed and the approach developed here can be applied to extension of data in other areas as well.

Detection and monitoring of H2O and CO2 ice clouds on Mars

USGS Publications Warehouse

Bell, J.F.; Calvin, W.M.; Ockert-Bell, M. E.; Crisp, D.; Pollack, James B.; Spencer, J.

1996-01-01

We have developed an observational scheme for the detection and discrimination of Mars atmospheric H2O and CO2 clouds using ground-based instruments in the near infrared. We report the results of our cloud detection and characterization study using Mars near IR images obtained during the 1990 and 1993 oppositions. We focused on specific wavelengths that have the potential, based on previous laboratory studies of H2O and CO2 ices, of yielding the greatest degree of cloud detectability and compositional discriminability. We have detected and mapped absorption features at some of these wavelengths in both the northern and southern polar regions of Mars. Compositional information on the nature of these absorption features was derived from comparisons with laboratory ice spectra and with a simplified radiative transfer model of a CO2 ice cloud overlying a bright surface. Our results indicate that both H2O and CO2 ices can be detected and distinguished in the polar hood clouds. The region near 3.00 ??m is most useful for the detection of water ice clouds because there is a strong H2O ice absorption at this wavelength but only a weak CO2 ice band. The region near 3.33 ??m is most useful for the detection of CO2 ice clouds because there is a strong, relatively narrow CO2 ice band at this wavelength but only broad "continuum" H2O ice absorption. Weaker features near 2.30 ??m could arise from CO2 ice at coarse grain sizes, or surface/dust minerals. Narrow features near 2.00 ??m, which could potentially be very diagnostic of CO2 ice clouds, suffer from contamination by Mars atmospheric CO2 absorptions and are difficult to interpret because of the rather poor knowledge of surface elevation at high latitudes. These results indicate that future ground-based, Earth-orbital, and spacecraft studies over a more extended span of the seasonal cycle should yield substantial information on the style and timing of volatile transport on Mars, as well as a more detailed understanding of the role of CO2 condensation in the polar heat budget. Copyright 1996 by the American Geophysical Union.

Bayesian cloud detection for MERIS, AATSR, and their combination

NASA Astrophysics Data System (ADS)

Hollstein, A.; Fischer, J.; Carbajal Henken, C.; Preusker, R.

2015-04-01

A broad range of different of Bayesian cloud detection schemes is applied to measurements from the Medium Resolution Imaging Spectrometer (MERIS), the Advanced Along-Track Scanning Radiometer (AATSR), and their combination. The cloud detection schemes were designed to be numerically efficient and suited for the processing of large numbers of data. Results from the classical and naive approach to Bayesian cloud masking are discussed for MERIS and AATSR as well as for their combination. A sensitivity study on the resolution of multidimensional histograms, which were post-processed by Gaussian smoothing, shows how theoretically insufficient numbers of truth data can be used to set up accurate classical Bayesian cloud masks. Sets of exploited features from single and derived channels are numerically optimized and results for naive and classical Bayesian cloud masks are presented. The application of the Bayesian approach is discussed in terms of reproducing existing algorithms, enhancing existing algorithms, increasing the robustness of existing algorithms, and on setting up new classification schemes based on manually classified scenes.

A P2P Botnet detection scheme based on decision tree and adaptive multilayer neural networks.

PubMed

Alauthaman, Mohammad; Aslam, Nauman; Zhang, Li; Alasem, Rafe; Hossain, M A

2018-01-01

In recent years, Botnets have been adopted as a popular method to carry and spread many malicious codes on the Internet. These malicious codes pave the way to execute many fraudulent activities including spam mail, distributed denial-of-service attacks and click fraud. While many Botnets are set up using centralized communication architecture, the peer-to-peer (P2P) Botnets can adopt a decentralized architecture using an overlay network for exchanging command and control data making their detection even more difficult. This work presents a method of P2P Bot detection based on an adaptive multilayer feed-forward neural network in cooperation with decision trees. A classification and regression tree is applied as a feature selection technique to select relevant features. With these features, a multilayer feed-forward neural network training model is created using a resilient back-propagation learning algorithm. A comparison of feature set selection based on the decision tree, principal component analysis and the ReliefF algorithm indicated that the neural network model with features selection based on decision tree has a better identification accuracy along with lower rates of false positives. The usefulness of the proposed approach is demonstrated by conducting experiments on real network traffic datasets. In these experiments, an average detection rate of 99.08 % with false positive rate of 0.75 % was observed.

Traffic sign detection in MLS acquired point clouds for geometric and image-based semantic inventory

NASA Astrophysics Data System (ADS)

Soilán, Mario; Riveiro, Belén; Martínez-Sánchez, Joaquín; Arias, Pedro

2016-04-01

Nowadays, mobile laser scanning has become a valid technology for infrastructure inspection. This technology permits collecting accurate 3D point clouds of urban and road environments and the geometric and semantic analysis of data became an active research topic in the last years. This paper focuses on the detection of vertical traffic signs in 3D point clouds acquired by a LYNX Mobile Mapper system, comprised of laser scanning and RGB cameras. Each traffic sign is automatically detected in the LiDAR point cloud, and its main geometric parameters can be automatically extracted, therefore aiding the inventory process. Furthermore, the 3D position of traffic signs are reprojected on the 2D images, which are spatially and temporally synced with the point cloud. Image analysis allows for recognizing the traffic sign semantics using machine learning approaches. The presented method was tested in road and urban scenarios in Galicia (Spain). The recall results for traffic sign detection are close to 98%, and existing false positives can be easily filtered after point cloud projection. Finally, the lack of a large, publicly available Spanish traffic sign database is pointed out.

Polarized View of Supercooled Liquid Water Clouds

NASA Technical Reports Server (NTRS)

Alexandrov, Mikhail D.; Cairns, Brian; Van Diedenhoven, Bastiaan; Ackerman, Andrew S.; Wasilewski, Andrzej P.; McGill, Matthew J.; Yorks, John E.; Hlavka, Dennis L.; Platnick, Steven E.; Arnold, G. Thomas

2016-01-01

Supercooled liquid water (SLW) clouds, where liquid droplets exist at temperatures below 0 C present a well known aviation hazard through aircraft icing, in which SLW accretes on the airframe. SLW clouds are common over the Southern Ocean, and climate-induced changes in their occurrence is thought to constitute a strong cloud feedback on global climate. The two recent NASA field campaigns POlarimeter Definition EXperiment (PODEX, based in Palmdale, California, January-February 2013) and Studies of Emissions and Atmospheric Composition, Clouds and Climate Coupling by Regional Surveys (SEAC4RS, based in Houston, Texas in August- September 2013) provided a unique opportunity to observe SLW clouds from the high-altitude airborne platform of NASA's ER-2 aircraft. We present an analysis of measurements made by the Research Scanning Polarimeter (RSP) during these experiments accompanied by correlative retrievals from other sensors. The RSP measures both polarized and total reflectance in 9 spectral channels with wavelengths ranging from 410 to 2250 nm. It is a scanning sensor taking samples at 0.8deg intervals within 60deg from nadir in both forward and backward directions. This unique angular resolution allows for characterization of liquid water droplet size using the rainbow structure observed in the polarized reflectances in the scattering angle range between 135deg and 165deg. Simple parametric fitting algorithms applied to the polarized reflectance provide retrievals of the droplet effective radius and variance assuming a prescribed size distribution shape (gamma distribution). In addition to this, we use a non-parametric method, Rainbow Fourier Transform (RFT),which allows retrieval of the droplet size distribution without assuming a size distribution shape. We present an overview of the RSP campaign datasets available from the NASA GISS website, as well as two detailed examples of the retrievals. In these case studies we focus on cloud fields with spatial features varying between glaciated and liquid phases at altitudes as high as 10 km, which correspond to temperatures close to the homogeneous freezing temperature of pure water drops (about -35 C or colder). The multimodal droplet size distributions retrieved from RSP data in these cases are consistent with the multi-layer cloud structure observed by correlative Cloud Physics Lidar (CPL) measurements.

Comparasion of Cloud Cover restituted by POLDER and MODIS

NASA Astrophysics Data System (ADS)

Zeng, S.; Parol, F.; Riedi, J.; Cornet, C.; Thieuxleux, F.

2009-04-01

PARASOL and AQUA are two sun-synchronous orbit satellites in the queue of A-Train satellites that observe our earth within a few minutes apart from each other. Aboard these two platforms, POLDER and MODIS provide coincident observations of the cloud cover with very different characteristics. These give us a good opportunity to study the clouds system and evaluate strengths and weaknesses of each dataset in order to provide an accurate representation of global cloud cover properties. This description is indeed of outermost importance to quantify and understand the effect of clouds on global radiation budget of the earth-atmosphere system and their influence on the climate changes. We have developed a joint dataset containing both POLDER and MODIS level 2 cloud products collocated and reprojected on a common sinusoidal grid in order to make the data comparison feasible and veracious. Our foremost work focuses on the comparison of both spatial distribution and temporal variation of the global cloud cover. This simple yet critical cloud parameter need to be clearly understood to allow further comparison of the other cloud parameters. From our study, we demonstrate that on average these two sensors both detect the clouds fairly well. They provide similar spatial distributions and temporal variations:both sensors see high values of cloud amount associated with deep convection in ITCZ, over Indonesia, and in west-central Pacific Ocean warm pool region; they also provide similar high cloud cover associated to mid-latitude storm tracks, to Indian monsoon or to the stratocumulus along the west coast of continents; on the other hand small cloud amounts that typically present over subtropical oceans and deserts in subsidence aeras are well identified by both POLDER and MODIS. Each sensor has its advantages and inconveniences for the detection of a particular cloud types. With higher spatial resolution, MODIS can better detect the fractional clouds thus explaining as one part of a positive bias in any latitude and in any viewing angle with an order of 10% between the POLDER cloud amount and the so-called MODIS "combined" cloud amount. Nevertheless it is worthy to note that a negative bias of about 10% is obtained between the POLDER cloud amount and the MODIS "day-mean" cloud amount. Main differences between the two MODIS cloud amount values are known to be due to the filtering of remaining aerosols or cloud edges. due to both this high spatial resolution of MODIS and the fact that "combined" cloud amount filters cloud edges, we can also explain why appear the high positive bias regions over subtropical ocean in south hemisphere and over east Africa in summer. Thanks to several channels in the thermal infrared spectral domain, MODIS detects probably much better the thin cirrus especially over land, thus causing a general negative bias for ice clouds. The multi-spectral capability of MODIS also allows for a better detection of low clouds over snow or ice, Hence the (POLDER-MODIS) cloud amount difference is often negative over Greenland, Antarctica, and over the continents at middle-high latitudes in spring and autumn associated to the snow coverage. The multi-spectral capability of MODIS also makes the discrimination possible between the biomass burning aerosols and the fractional clouds over the continents. Thus a positive bias appears in central Africa in summer and autumn associated to important biomass burning events. Over transition region between desert and non-desert, the presence of large negative bias (POLDER-MODIS) of cloud amount maybe partly due to MODIS pixel falsely labeled the desert as cloudy, where MODIS algorithm uses static desert mask. This is clearly highlighted in south of Sahara in spring and summer where we find a bias negative with an order of -0.1. What is more, thanks to its multi-angular capability, POLDER can discriminate the sun-glint region thus minimizing the dependence of cloud amount on view angle. It makes the detection of high clouds easier over a black surface thanks to its polarization character.

Cloud Coverage and Height Distribution from the GLAS Polar Orbiting Lidar: Comparison to Passive Cloud Retrievals

NASA Technical Reports Server (NTRS)

Spinhime, J. D.; Palm, S. P.; Hlavka, D. L.; Hart, W. D.; Mahesh, A.

2004-01-01

The Geoscience Laser Altimeter System (GLAS) began full on orbit operations in September 2003. A main application of the two-wavelength GLAS lidar is highly accurate detection and profiling of global cloud cover. Initial analysis indicates that cloud and aerosol layers are consistently detected on a global basis to cross-sections down to 10(exp -6) per meter. Images of the lidar data dramatically and accurately show the vertical structure of cloud and aerosol to the limit of signal attenuation. The GLAS lidar has made the most accurate measurement of global cloud coverage and height to date. In addition to the calibrated lidar signal, GLAS data products include multi level boundaries and optical depth of all transmissive layers. Processing includes a multi-variable separation of cloud and aerosol layers. An initial application of the data results is to compare monthly cloud means from several months of GLAS observations in 2003 to existing cloud climatologies from other satellite measurement. In some cases direct comparison to passive cloud retrievals is possible. A limitation of the lidar measurements is nadir only sampling. However monthly means exhibit reasonably good global statistics and coverage results, at other than polar regions, compare well with other measurements but show significant differences in height distribution. For polar regions where passive cloud retrievals are problematic and where orbit track density is greatest, the GLAS results are particularly an advance in cloud cover information. Direct comparison to MODIS retrievals show a better than 90% agreement in cloud detection for daytime, but less than 60% at night. Height retrievals are in much less agreement. GLAS is a part of the NASA EOS project and data products are thus openly available to the science community (see http://glo.gsfc.nasa.gov).

Detection of ground fog in mountainous areas from MODIS (Collection 051) daytime data using a statistical approach

NASA Astrophysics Data System (ADS)

Schulz, Hans Martin; Thies, Boris; Chang, Shih-Chieh; Bendix, Jörg

2016-03-01

The mountain cloud forest of Taiwan can be delimited from other forest types using a map of the ground fog frequency. In order to create such a frequency map from remotely sensed data, an algorithm able to detect ground fog is necessary. Common techniques for ground fog detection based on weather satellite data cannot be applied to fog occurrences in Taiwan as they rely on several assumptions regarding cloud properties. Therefore a new statistical method for the detection of ground fog in mountainous terrain from MODIS Collection 051 data is presented. Due to the sharpening of input data using MODIS bands 1 and 2, the method provides fog masks in a resolution of 250 m per pixel. The new technique is based on negative correlations between optical thickness and terrain height that can be observed if a cloud that is relatively plane-parallel is truncated by the terrain. A validation of the new technique using camera data has shown that the quality of fog detection is comparable to that of another modern fog detection scheme developed and validated for the temperate zones. The method is particularly applicable to optically thinner water clouds. Beyond a cloud optical thickness of ≈ 40, classification errors significantly increase.

Using Himawari-8, estimation of SO2 cloud altitude at Aso volcano eruption, on October 8, 2016

NASA Astrophysics Data System (ADS)

Ishii, Kensuke; Hayashi, Yuta; Shimbori, Toshiki

2018-02-01

It is vital to detect volcanic plumes as soon as possible for volcanic hazard mitigation such as aviation safety and the life of residents. Himawari-8, the Japan Meteorological Agency's (JMA's) geostationary meteorological satellite, has high spatial resolution and sixteen observation bands including the 8.6 μm band to detect sulfur dioxide (SO2). Therefore, Ash RGB composite images (RED: brightness temperature (BT) difference between 12.4 and 10.4 μm, GREEN: BT difference between 10.4 and 8.6 μm, BLUE: 10.4 μm) discriminate SO2 clouds and volcanic ash clouds from meteorological clouds. Since the Himawari-8 has also high temporal resolution, the real-time monitoring of ash and SO2 clouds is of great use. A phreatomagmatic eruption of Aso volcano in Kyushu, Japan, occurred at 01:46 JST on October 8, 2016. For this eruption, the Ash RGB could detect SO2 cloud from Aso volcano immediately after the eruption and track it even 12 h after. In this case, the Ash RGB images every 2.5 min could clearly detect the SO2 cloud that conventional images such as infrared and split window could not detect sufficiently. Furthermore, we could estimate the height of the SO2 cloud by comparing the Ash RGB images and simulations of the JMA Global Atmospheric Transport Model with a variety of height parameters. As a result of comparison, the top and bottom height of the SO2 cloud emitted from the eruption was estimated as 7 and 13-14 km, respectively. Assuming the plume height was 13-14 km and eruption duration was 160-220 s (as estimated by seismic observation), the total emission mass of volcanic ash from the eruption was estimated as 6.1-11.8 × 108 kg, which is relatively consistent with 6.0-6.5 × 108 kg from field survey. [Figure not available: see fulltext.

Automated retrieval of cloud and aerosol properties from the ARM Raman lidar, part 1: feature detection

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thorsen, Tyler J.; Fu, Qiang; Newsom, Rob K.

A Feature detection and EXtinction retrieval (FEX) algorithm for the Atmospheric Radiation Measurement (ARM) program’s Raman lidar (RL) has been developed. Presented here is part 1 of the FEX algorithm: the detection of features including both clouds and aerosols. The approach of FEX is to use multiple quantities— scattering ratios derived using elastic and nitro-gen channel signals from two fields of view, the scattering ratio derived using only the elastic channel, and the total volume depolarization ratio— to identify features using range-dependent detection thresholds. FEX is designed to be context-sensitive with thresholds determined for each profile by calculating the expectedmore » clear-sky signal and noise. The use of multiple quantities pro-vides complementary depictions of cloud and aerosol locations and allows for consistency checks to improve the accuracy of the feature mask. The depolarization ratio is shown to be particularly effective at detecting optically-thin features containing non-spherical particles such as cirrus clouds. Improve-ments over the existing ARM RL cloud mask are shown. The performance of FEX is validated against a collocated micropulse lidar and observations from the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite over the ARM Darwin, Australia site. While we focus on a specific lidar system, the FEX framework presented here is suitable for other Raman or high spectral resolution lidars.« less

THOR: Cloud Thickness from Off beam Lidar Returns

NASA Technical Reports Server (NTRS)

Cahalan, Robert F.; McGill, Matthew; Kolasinski, John; Varnai, Tamas; Yetzer, Ken

2004-01-01

Conventional wisdom is that lidar pulses do not significantly penetrate clouds having optical thickness exceeding about tau = 2, and that no returns are detectable from more than a shallow skin depth. Yet optically thicker clouds of tau much greater than 2 reflect a larger fraction of visible photons, and account for much of Earth s global average albedo. As cloud layer thickness grows, an increasing fraction of reflected photons are scattered multiple times within the cloud, and return from a diffuse concentric halo that grows around the incident pulse, increasing in horizontal area with layer physical thickness. The reflected halo is largely undetected by narrow field-of-view (FoV) receivers commonly used in lidar applications. THOR - Thickness from Off-beam Returns - is an airborne wide-angle detection system with multiple FoVs, capable of observing the diffuse halo, detecting wide-angle signal from which physical thickness of optically thick clouds can be retrieved. In this paper we describe the THOR system, demonstrate that the halo signal is stronger for thicker clouds, and validate physical thickness retrievals for clouds having z > 20, from NASA P-3B flights over the Department of Energy/Atmospheric Radiation Measurement/Southern Great Plains site, using the lidar, radar and other ancillary ground-based data.

Characteristics of cloud occurrence using ceilometer measurements and its relationship to precipitation over Seoul

NASA Astrophysics Data System (ADS)

Lee, Sanghee; Hwang, Seung-On; Kim, Jhoon; Ahn, Myoung-Hwan

2018-03-01

Clouds are an important component of the atmosphere that affects both climate and weather, however, their contributions can be very difficult to determine. Ceilometer measurements can provide high resolution information on atmospheric conditions such as cloud base height (CBH) and vertical frequency of cloud occurrence (CVF). This study presents the first comprehensive analysis of CBH and CVF derived using Vaisala CL51 ceilometers at two urban stations in Seoul, Korea, during a three-year period from January 2014 to December 2016. The average frequency of cloud occurrence detected by the ceilometers is 54.3%. It is found that the CL51 is better able to capture CBH as compared to another ceilometer CL31 at a nearby meteorological station because it could detect high clouds more accurately. Frequency distributions for CBH up to 13,000 m providing detailed vertical features with 500-m interval show 55% of CBHs below 2 km for aggregated CBHs. A bimodal frequency distribution was observed for three-layers CBHs. A monthly variation of CVF reveals that frequency concentration of lower clouds is found in summer and winter, and higher clouds more often detected in spring and autumn. Monthly distribution features of cloud occurrence and precipitation are depending on seasons and it might be easy to define their relationship due to higher degree of variability of precipitation than cloud occurrence. However, a fluctuation of cloud occurrence frequency in summer is similar to precipitation in trend, whereas clouds in winter are relatively frequent but precipitation is not accompanied. In addition, recent decrease of summer precipitation could be mostly explained by a decrease of cloud occurrence. Anomalous precipitation recorded sometimes is considerably related to corresponding cloud occurrence. The diurnal and daily variations of CBH and CVF from ceilometer observations and the analysis of microwave radiometer measurements for two typical cloudiness cases are also reviewed in parallel. This analysis in finer temporal scale exhibits that utilization of ground-based observations together could help to analyze the cloud behaviors.

The EOS CERES Global Cloud Mask

NASA Technical Reports Server (NTRS)

Berendes, T. A.; Welch, R. M.; Trepte, Q.; Schaaf, C.; Baum, B. A.

1996-01-01

To detect long-term climate trends, it is essential to produce long-term and consistent data sets from a variety of different satellite platforms. With current global cloud climatology data sets, such as the International Satellite Cloud Climatology Experiment (ISCCP) or CLAVR (Clouds from Advanced Very High Resolution Radiometer), one of the first processing steps is to determine whether an imager pixel is obstructed between the satellite and the surface, i.e., determine a cloud 'mask.' A cloud mask is essential to studies monitoring changes over ocean, land, or snow-covered surfaces. As part of the Earth Observing System (EOS) program, a series of platforms will be flown beginning in 1997 with the Tropical Rainfall Measurement Mission (TRMM) and subsequently the EOS-AM and EOS-PM platforms in following years. The cloud imager on TRMM is the Visible/Infrared Sensor (VIRS), while the Moderate Resolution Imaging Spectroradiometer (MODIS) is the imager on the EOS platforms. To be useful for long term studies, a cloud masking algorithm should produce consistent results between existing (AVHRR) data, and future VIRS and MODIS data. The present work outlines both existing and proposed approaches to detecting cloud using multispectral narrowband radiance data. Clouds generally are characterized by higher albedos and lower temperatures than the underlying surface. However, there are numerous conditions when this characterization is inappropriate, most notably over snow and ice of the cloud types, cirrus, stratocumulus and cumulus are the most difficult to detect. Other problems arise when analyzing data from sun-glint areas over oceans or lakes over deserts or over regions containing numerous fires and smoke. The cloud mask effort builds upon operational experience of several groups that will now be discussed.

Cloud cover detection combining high dynamic range sky images and ceilometer measurements

NASA Astrophysics Data System (ADS)

Román, R.; Cazorla, A.; Toledano, C.; Olmo, F. J.; Cachorro, V. E.; de Frutos, A.; Alados-Arboledas, L.

2017-11-01

This paper presents a new algorithm for cloud detection based on high dynamic range images from a sky camera and ceilometer measurements. The algorithm is also able to detect the obstruction of the sun. This algorithm, called CPC (Camera Plus Ceilometer), is based on the assumption that under cloud-free conditions the sky field must show symmetry. The symmetry criteria are applied depending on ceilometer measurements of the cloud base height. CPC algorithm is applied in two Spanish locations (Granada and Valladolid). The performance of CPC retrieving the sun conditions (obstructed or unobstructed) is analyzed in detail using as reference pyranometer measurements at Granada. CPC retrievals are in agreement with those derived from the reference pyranometer in 85% of the cases (it seems that this agreement does not depend on aerosol size or optical depth). The agreement percentage goes down to only 48% when another algorithm, based on Red-Blue Ratio (RBR), is applied to the sky camera images. The retrieved cloud cover at Granada and Valladolid is compared with that registered by trained meteorological observers. CPC cloud cover is in agreement with the reference showing a slight overestimation and a mean absolute error around 1 okta. A major advantage of the CPC algorithm with respect to the RBR method is that the determined cloud cover is independent of aerosol properties. The RBR algorithm overestimates cloud cover for coarse aerosols and high loads. Cloud cover obtained only from ceilometer shows similar results than CPC algorithm; but the horizontal distribution cannot be obtained. In addition, it has been observed that under quick and strong changes on cloud cover ceilometers retrieve a cloud cover fitting worse with the real cloud cover.

Partial Information Community Detection in a Multilayer Network

DTIC Science & Technology

2016-06-01

Network was taken from the CORE Lab at the Naval Postgraduate School [27]. Facebook dataset We will use a subgraph of the Facebook network to build a...larger synthetic multilayer network. We want to use this Facebook data as a way to introduce a real world example of a network into our synthetic network...This data is provided by the Standford Large Network Dataset Collection [28]. This is a large anonymous subgraph of Facebook . It contains over 4,000

Layer by layer assembled films between hemoglobin and multiwall carbon nanotubes for pH-switchable biosensing.

PubMed

Pan, Zhongqin; Liu, Xiaojun; Xie, Jing; Bao, Ning; He, Hong; Li, Xiaodong; Zeng, Jiang; Gu, Haiying

2015-05-01

Although pH-switchable behaviors have been reported based on multilayer films modified electrodes, their pH-switchable biosensing is still difficult due to the existence of the electroactive mediator. In this study, we report the pH-dependable determination of hydrogen peroxide (H2O2) based on a four-bilayer film fabricated through layer by layer assembly between hemoglobin (Hb) and multiwall carbon nanotubes (MWCNTs). We observed that response of electroactive probe Fe(CN)6(3-) at the multilayer films was very sensitive and reversible to pH values of phosphate buffer solutions phosphate buffer solution with cyclic voltammetry. The reduction peak height of Fe(CN)6(3-) at the multilayer film could reach ∼221μA at pH 3.0 while 0μA at pH 9.0. The linear range for the detection of H2O2 at pH 3.0 was from 12.5μM to 10.4mM, which was much wider than that at pH 9.0. Our results demonstrated that the detection of H2O2 with the proposed modified electrode is dependent on pH values of phosphate buffer solution. Moreover, the component of multilayer films has impacts on the performance of biosensors with pH-switchable behaviors. Copyright © 2015 Elsevier B.V. All rights reserved.

High-frequency guided ultrasonic waves for hidden defect detection in multi-layered aircraft structures.

PubMed

Masserey, Bernard; Raemy, Christian; Fromme, Paul

2014-09-01

Aerospace structures often contain multi-layered metallic components where hidden defects such as fatigue cracks and localized disbonds can develop, necessitating non-destructive testing. Employing standard wedge transducers, high frequency guided ultrasonic waves that penetrate through the complete thickness were generated in a model structure consisting of two adhesively bonded aluminium plates. Interference occurs between the wave modes during propagation along the structure, resulting in a frequency dependent variation of the energy through the thickness with distance. The wave propagation along the specimen was measured experimentally using a laser interferometer. Good agreement with theoretical predictions and two-dimensional finite element simulations was found. Significant propagation distance with a strong, non-dispersive main wave pulse was achieved. The interaction of the high frequency guided ultrasonic waves with small notches in the aluminium layer facing the sealant and on the bottom surface of the multilayer structure was investigated. Standard pulse-echo measurements were conducted to verify the detection sensitivity and the influence of the stand-off distance predicted from the finite element simulations. The results demonstrated the potential of high frequency guided waves for hidden defect detection at critical and difficult to access locations in aerospace structures from a stand-off distance. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

Multilayer Markov Random Field models for change detection in optical remote sensing images

NASA Astrophysics Data System (ADS)

Benedek, Csaba; Shadaydeh, Maha; Kato, Zoltan; Szirányi, Tamás; Zerubia, Josiane

2015-09-01

In this paper, we give a comparative study on three Multilayer Markov Random Field (MRF) based solutions proposed for change detection in optical remote sensing images, called Multicue MRF, Conditional Mixed Markov model, and Fusion MRF. Our purposes are twofold. On one hand, we highlight the significance of the focused model family and we set them against various state-of-the-art approaches through a thematic analysis and quantitative tests. We discuss the advantages and drawbacks of class comparison vs. direct approaches, usage of training data, various targeted application fields and different ways of Ground Truth generation, meantime informing the Reader in which roles the Multilayer MRFs can be efficiently applied. On the other hand we also emphasize the differences between the three focused models at various levels, considering the model structures, feature extraction, layer interpretation, change concept definition, parameter tuning and performance. We provide qualitative and quantitative comparison results using principally a publicly available change detection database which contains aerial image pairs and Ground Truth change masks. We conclude that the discussed models are competitive against alternative state-of-the-art solutions, if one uses them as pre-processing filters in multitemporal optical image analysis. In addition, they cover together a large range of applications, considering the different usage options of the three approaches.

Ship detection from high-resolution imagery based on land masking and cloud filtering

NASA Astrophysics Data System (ADS)

Jin, Tianming; Zhang, Junping

2015-12-01

High resolution satellite images play an important role in target detection application presently. This article focuses on the ship target detection from the high resolution panchromatic images. Taking advantage of geographic information such as the coastline vector data provided by NOAA Medium Resolution Coastline program, the land region is masked which is a main noise source in ship detection process. After that, the algorithm tries to deal with the cloud noise which appears frequently in the ocean satellite images, which is another reason for false alarm. Based on the analysis of cloud noise's feature in frequency domain, we introduce a windowed noise filter to get rid of the cloud noise. With the help of morphological processing algorithms adapted to target detection, we are able to acquire ship targets in fine shapes. In addition, we display the extracted information such as length and width of ship targets in a user-friendly way i.e. a KML file interpreted by Google Earth.

Monte Carlo model of light transport in multi-layered tubular organs

NASA Astrophysics Data System (ADS)

Zhang, Yunyao; Zhu, Jingping; Zhang, Ning

2017-02-01

We present a Monte Carlo static light migration model (Endo-MCML) to simulate endoscopic optical spectroscopy for tubular organs such as esophagus and colon. The model employs multi-layered hollow cylinder which emitting and receiving light both from the inner boundary to meet the conditions of endoscopy. Inhomogeneous sphere can be added in tissue layers to model cancer or other abnormal changes. The 3D light distribution and exit angle would be recorded as results. The accuracy of the model has been verified by Multi-layered Monte Carlo(MCML) method and NIRFAST. This model can be used for the forward modeling of light transport during endoscopically diffuse optical spectroscopy, light scattering spectroscopy, reflectance spectroscopy and other static optical detection or imaging technologies.

Road traffic sign detection and classification from mobile LiDAR point clouds

NASA Astrophysics Data System (ADS)

Weng, Shengxia; Li, Jonathan; Chen, Yiping; Wang, Cheng

2016-03-01

Traffic signs are important roadway assets that provide valuable information of the road for drivers to make safer and easier driving behaviors. Due to the development of mobile mapping systems that can efficiently acquire dense point clouds along the road, automated detection and recognition of road assets has been an important research issue. This paper deals with the detection and classification of traffic signs in outdoor environments using mobile light detection and ranging (Li- DAR) and inertial navigation technologies. The proposed method contains two main steps. It starts with an initial detection of traffic signs based on the intensity attributes of point clouds, as the traffic signs are always painted with highly reflective materials. Then, the classification of traffic signs is achieved based on the geometric shape and the pairwise 3D shape context. Some results and performance analyses are provided to show the effectiveness and limits of the proposed method. The experimental results demonstrate the feasibility and effectiveness of the proposed method in detecting and classifying traffic signs from mobile LiDAR point clouds.

Cloud detection algorithm comparison and validation for operational Landsat data products

USGS Publications Warehouse

Foga, Steven Curtis; Scaramuzza, Pat; Guo, Song; Zhu, Zhe; Dilley, Ronald; Beckmann, Tim; Schmidt, Gail L.; Dwyer, John L.; Hughes, MJ; Laue, Brady

2017-01-01

Clouds are a pervasive and unavoidable issue in satellite-borne optical imagery. Accurate, well-documented, and automated cloud detection algorithms are necessary to effectively leverage large collections of remotely sensed data. The Landsat project is uniquely suited for comparative validation of cloud assessment algorithms because the modular architecture of the Landsat ground system allows for quick evaluation of new code, and because Landsat has the most comprehensive manual truth masks of any current satellite data archive. Currently, the Landsat Level-1 Product Generation System (LPGS) uses separate algorithms for determining clouds, cirrus clouds, and snow and/or ice probability on a per-pixel basis. With more bands onboard the Landsat 8 Operational Land Imager (OLI)/Thermal Infrared Sensor (TIRS) satellite, and a greater number of cloud masking algorithms, the U.S. Geological Survey (USGS) is replacing the current cloud masking workflow with a more robust algorithm that is capable of working across multiple Landsat sensors with minimal modification. Because of the inherent error from stray light and intermittent data availability of TIRS, these algorithms need to operate both with and without thermal data. In this study, we created a workflow to evaluate cloud and cloud shadow masking algorithms using cloud validation masks manually derived from both Landsat 7 Enhanced Thematic Mapper Plus (ETM +) and Landsat 8 OLI/TIRS data. We created a new validation dataset consisting of 96 Landsat 8 scenes, representing different biomes and proportions of cloud cover. We evaluated algorithm performance by overall accuracy, omission error, and commission error for both cloud and cloud shadow. We found that CFMask, C code based on the Function of Mask (Fmask) algorithm, and its confidence bands have the best overall accuracy among the many algorithms tested using our validation data. The Artificial Thermal-Automated Cloud Cover Algorithm (AT-ACCA) is the most accurate nonthermal-based algorithm. We give preference to CFMask for operational cloud and cloud shadow detection, as it is derived from a priori knowledge of physical phenomena and is operable without geographic restriction, making it useful for current and future land imaging missions without having to be retrained in a machine-learning environment.

[The application of wavelet analysis of remote detection of pollution clouds].

PubMed

Zhang, J; Jiang, F

2001-08-01

The discrete wavelet transform (DWT) is used to analyse the spectra of pollution clouds in complicated environment and extract the small-features. The DWT is a time-frequency analysis technology, which detects the subtle small changes in the target spectrum. The results show that the DWT is a quite effective method to extract features of target-cloud and improve the reliability of monitoring alarm system.

MPLNET V3 Cloud and Planetary Boundary Layer Detection

NASA Technical Reports Server (NTRS)

Lewis, Jasper R.; Welton, Ellsworth J.; Campbell, James R.; Haftings, Phillip C.

2016-01-01

The NASA Micropulse Lidar Network Version 3 algorithms for planetary boundary layer and cloud detection are described and differences relative to the previous Version 2 algorithms are highlighted. A year of data from the Goddard Space Flight Center site in Greenbelt, MD consisting of diurnal and seasonal trends is used to demonstrate the results. Both the planetary boundary layer and cloud algorithms show significant improvement of the previous version.

Object Detection using the Kinect

DTIC Science & Technology

2012-03-01

Kinect camera and point cloud data from the Kinect’s structured light stereo system (figure 1). We obtain reasonable results using a single prototype...same manner we present in this report. For example, at Willow Garage , Steder uses a 3-D feature he developed to classify objects directly from point...detecting backpacks using the data available from the Kinect sensor. 4 3.1 Point Cloud Filtering Dense point clouds derived from stereo are notoriously

C+ detection of warm dark gas in diffuse clouds

NASA Astrophysics Data System (ADS)

Langer, W. D.; Velusamy, T.; Pineda, J. L.; Goldsmith, P. F.; Li, D.; Yorke, H. W.

2010-10-01

We present the first results of the Herschel open time key program, Galactic Observations of Terahertz C+ (GOT C+) survey of the [CII] 2P3/2-2P1/2 fine-structure line at 1.9 THz (158 μm) using the HIFI instrument on Herschel. We detected 146 interstellar clouds along sixteen lines-of-sight towards the inner Galaxy. We also acquired HI and CO isotopologue data along each line-of-sight for analysis of the physical conditions in these clouds. Here we analyze 29 diffuse clouds (AV < 1.3 mag) in this sample characterized by having [CII] and HI emission, but no detectable CO. We find that [CII] emission is generally stronger than expected for diffuse atomic clouds, and in a number of sources is much stronger than anticipated based on their HI column density. We show that excess [CII] emission in these clouds is best explained by the presence of a significant diffuse warm H2, dark gas, component. This first [CII] 158 μm detection of warm dark gas demonstrates the value of this tracer for mapping this gas throughout the Milky Way and in galaxies. Herschel is an ESA space observatory with science instruments provided by European-led Principal Investigator consortia and with important participation from NASA.

Layer-Dependent Third-Harmonic Generation in Graphene

NASA Astrophysics Data System (ADS)

Yang, Hao; Guan, Honghua; Dadap, Jerry; Osgood, Richard; Richard Osgood Team

Graphene has become a subject of intense interest and study because of its remarkable 2D electronic properties. Multilayer graphene also offers an array of properties that are also of interest for optical physics and devices. Despite its second-order-nonlinear optical response is intrinsically weak, third-order nonlinear optical effects in graphene are symmetry-allowed thus leading to studies of several third-order process in few-layer graphene. In this work, we report third-harmonic generation in multilayer graphene mounted on fused silica and with thicknesses which approach the bulk continuum. THG signals show cubic power dependence with respect to the intensity of fundamental beam. Third-harmonic generation spectroscopy enables a good fit using linear optical detection, which shows strong contrast for different layer number graphene. The maximum THG efficiency appears at layer number around 30. Two models are used for describing this layer dependent phenomenon and shows absorption plays a key role in THG of multilayer graphene. This work also provides a new imaging technology for graphene detection and identification with better contrast and resolution. U.S. Department of Energy under Contract No. DE-FG 02-04-ER-46157.

Evaluation of Decision Trees for Cloud Detection from AVHRR Data

NASA Technical Reports Server (NTRS)

Shiffman, Smadar; Nemani, Ramakrishna

2005-01-01

Automated cloud detection and tracking is an important step in assessing changes in radiation budgets associated with global climate change via remote sensing. Data products based on satellite imagery are available to the scientific community for studying trends in the Earth's atmosphere. The data products include pixel-based cloud masks that assign cloud-cover classifications to pixels. Many cloud-mask algorithms have the form of decision trees. The decision trees employ sequential tests that scientists designed based on empirical astrophysics studies and simulations. Limitations of existing cloud masks restrict our ability to accurately track changes in cloud patterns over time. In a previous study we compared automatically learned decision trees to cloud masks included in Advanced Very High Resolution Radiometer (AVHRR) data products from the year 2000. In this paper we report the replication of the study for five-year data, and for a gold standard based on surface observations performed by scientists at weather stations in the British Islands. For our sample data, the accuracy of automatically learned decision trees was greater than the accuracy of the cloud masks p < 0.001.

OT1_mputman_1: ASCII: All Sky observations of Galactic CII

NASA Astrophysics Data System (ADS)

Putman, M.

2010-07-01

The Milky Way and other galaxies require a significant source of ongoing star formation fuel to explain their star formation histories. A new ubiquitous population of discrete, cold clouds have recently been discovered at the disk-halo interface of our Galaxy that could potentially provide this source of fuel. We propose to observe a small sample of these disk-halo clouds with HIFI to determine if the level of [CII] emission detected suggests they represent the cooling of warm clouds at the interface between the star forming disk and halo. These cooling clouds are predicted by simulations of warm clouds moving into the disk-halo interface region. We target 5 clouds in this proposal for which we have high resolution HI maps and can observe the densest core of the cloud. The results of our observations will also be used to interpret the surprisingly high detections of [CII] for low HI column density clouds in the Galactic Plane by the GOT C+ Key Program by extending the clouds probed to high latitude environments.

Sensitive colorimetric assay for uric acid and glucose detection based on multilayer-modified paper with smartphone as signal readout.

PubMed

Wang, Xu; Li, Fang; Cai, Ziqi; Liu, Kaifan; Li, Jing; Zhang, Boyang; He, Jianbo

2018-04-01

In this work, a multilayer-modified paper-based colorimetric sensing platform with improved color uniformity and intensity was developed for the sensitive and selective determination of uric acid and glucose with smartphone as signal readout. In detail, chitosan, different kinds of chromogenic reagents, and horseradish peroxidase (HRP) combined with a specific oxidase, e.g., uricase or glucose oxidase (GOD), were immoblized onto the paper substrate to form a multilayer-modified test paper. Hydrogen peroxide produced by the oxidases (uricase or GOD) reacts with the substrates (uric acid or glucose), and could oxidize the co-immoblized chromogenic reagents to form colored products with HRP as catalyst. A simple strategy by placing the test paper on top of a light-emitting diode lamp was adopted to efficiently prevent influence from the external light. The color images were recorded by the smartphone camera, and then the gray values of the color images were calculated for quantitative analysis. The developed method provided a wide linear response from 0.01 to 1.0 mM for uric acid detection and from 0.02 to 4.0 mM for glucose detection, with a limit of detection (LOD) as low as 0.003 and 0.014 mM, respectively, which was much lower than for previously reported paper-based colorimetric assays. The proposed assays were successfully applied to uric acid and glucose detection in real serum samples. Furthermore, the enhanced analytical performance of the proposed method allowed the non-invasive detection of glucose levels in tear samples, which holds great potential for point-of-care analysis. Graphical abstract ᅟ.

Application of low-coherence interferometry for in situ nondestructive evaluation of thin and thick multilayered transparent composites

NASA Astrophysics Data System (ADS)

Khomenko, Anton; Cloud, Gary Lee; Haq, Mahmoodul

2015-12-01

Multilayered transparent composites having laminates with polymer interlayers and backing sheets are commonly used in a wide range of applications where visibility, transparency, impact resistance, and safety are essential. Manufacturing flaws or damage during operation can seriously compromise both safety and performance. Most fabrication defects are not discernible until after the entire multilayered transparent composite assembly has been completed, and in-the-field inspection for damage is a problem not yet solved. A robust and reliable nondestructive evaluation (NDE) technique is needed to evaluate structural integrity and identify defects that result from manufacturing issues as well as in-service damage arising from extreme environmental conditions in addition to normal mechanical and thermal loads. Current optical techniques have limited applicability for NDE of such structures. This work presents a technique that employs a modified interferometer utilizing a laser diode or femtosecond fiber laser source to acquire in situ defect depth location inside a thin or thick multilayered transparent composite, respectively. The technique successfully located various defects inside examined composites. The results show great potential of the technique for defect detection, location, and identification in multilayered transparent composites.

Comparison Between CCCM and CloudSat Radar-Lidar (RL) Cloud and Radiation Products

NASA Technical Reports Server (NTRS)

Ham, Seung-Hee; Kato, Seiji; Rose, Fred G.; Sun-Mack, Sunny

2015-01-01

To enhance cloud properties, LaRC and CIRA developed each combination algorithm for obtained properties from passive, active and imager in A-satellite constellation. When comparing global cloud fraction each other, LaRC-produced CERES-CALIPSO-CloudSat-MODIS (CCCM) products larger low-level cloud fraction over tropic ocean, while CIRA-produced Radar-Lidar (RL) shows larger mid-level cloud fraction for high latitude region. The reason for different low-level cloud fraction is due to different filtering method of lidar-detected cloud layers. Meanwhile difference in mid-level clouds is occurred due to different priority of cloud boundaries from lidar and radar.

Automated detection of Martian water ice clouds: the Valles Marineris

NASA Astrophysics Data System (ADS)

Ogohara, Kazunori; Munetomo, Takafumi; Hatanaka, Yuji; Okumura, Susumu

2016-10-01

We need to extract water ice clouds from the large number of Mars images in order to reveal spatial and temporal variations of water ice cloud occurrence and to meteorologically understand climatology of water ice clouds. However, visible images observed by Mars orbiters for several years are too many to visually inspect each of them even though the inspection was limited to one region. Therefore, an automated detection algorithm of Martian water ice clouds is necessary for collecting ice cloud images efficiently. In addition, it may visualize new aspects of spatial and temporal variations of water ice clouds that we have never been aware. We present a method for automatically evaluating the presence of Martian water ice clouds using difference images and cross-correlation distributions calculated from blue band images of the Valles Marineris obtained by the Mars Orbiter Camera onboard the Mars Global Surveyor (MGS/MOC). We derived one subtracted image and one cross-correlation distribution from two reflectance images. The difference between the maximum and the average, variance, kurtosis, and skewness of the subtracted image were calculated. Those of the cross-correlation distribution were also calculated. These eight statistics were used as feature vectors for training Support Vector Machine, and its generalization ability was tested using 10-fold cross-validation. F-measure and accuracy tended to be approximately 0.8 if the maximum in the normalized reflectance and the difference of the maximum and the average in the cross-correlation were chosen as features. In the process of the development of the detection algorithm, we found many cases where the Valles Marineris became clearly brighter than adjacent areas in the blue band. It is at present unclear whether the bright Valles Marineris means the occurrence of water ice clouds inside the Valles Marineris or not. Therefore, subtracted images showing the bright Valles Marineris were excluded from the detection of water ice clouds

Analytical Modeling for the Bending Resonant Frequency of Multilayered Microresonators with Variable Cross-Section

PubMed Central

Herrera-May, Agustín L.; Aguilera-Cortés, Luz A.; Plascencia-Mora, Hector; Rodríguez-Morales, Ángel L.; Lu, Jian

2011-01-01

Multilayered microresonators commonly use sensitive coating or piezoelectric layers for detection of mass and gas. Most of these microresonators have a variable cross-section that complicates the prediction of their fundamental resonant frequency (generally of the bending mode) through conventional analytical models. In this paper, we present an analytical model to estimate the first resonant frequency and deflection curve of single-clamped multilayered microresonators with variable cross-section. The analytical model is obtained using the Rayleigh and Macaulay methods, as well as the Euler-Bernoulli beam theory. Our model is applied to two multilayered microresonators with piezoelectric excitation reported in the literature. Both microresonators are composed by layers of seven different materials. The results of our analytical model agree very well with those obtained from finite element models (FEMs) and experimental data. Our analytical model can be used to determine the suitable dimensions of the microresonator’s layers in order to obtain a microresonator that operates at a resonant frequency necessary for a particular application. PMID:22164071

Phase-partitioning in mixed-phase clouds - An approach to characterize the entire vertical column

NASA Astrophysics Data System (ADS)

Kalesse, H.; Luke, E. P.; Seifert, P.

2017-12-01

The characterization of the entire vertical profile of phase-partitioning in mixed-phase clouds is a challenge which can be addressed by synergistic profiling measurements with ground-based polarization lidars and cloud radars. While lidars are sensitive to small particles and can thus detect supercooled liquid (SCL) layers, cloud radar returns are dominated by larger particles (like ice crystals). The maximum lidar observation height is determined by complete signal attenuation at a penetrated optical depth of about three. In contrast, cloud radars are able to penetrate multiple liquid layers and can thus be used to expand the identification of cloud phase to the entire vertical column beyond the lidar extinction height, if morphological features in the radar Doppler spectrum can be related to the existence of SCL. Relevant spectral signatures such as bimodalities and spectral skewness can be related to cloud phase by training a neural network appropriately in a supervised learning scheme, with lidar measurements functioning as supervisor. The neural network output (prediction of SCL location) derived using cloud radar Doppler spectra can be evaluated with several parameters such as liquid water path (LWP) detected by microwave radiometer (MWR) and (liquid) cloud base detected by ceilometer or Raman lidar. The technique has been previously tested on data from Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) instruments in Barrow, Alaska and is in this study utilized for observations from the Leipzig Aerosol and Cloud Remote Observations System (LACROS) during the Analysis of the Composition of Clouds with Extended Polarization Techniques (ACCEPT) field experiment in Cabauw, Netherlands in Fall 2014. Comparisons to supercooled-liquid layers as classified by CLOUDNET are provided.

Optical property retrievals of subvisual cirrus clouds from OSIRIS limb-scatter measurements

NASA Astrophysics Data System (ADS)

Wiensz, J. T.; Degenstein, D. A.; Lloyd, N. D.; Bourassa, A. E.

2012-08-01

We present a technique for retrieving the optical properties of subvisual cirrus clouds detected by OSIRIS, a limb-viewing satellite instrument that measures scattered radiances from the UV to the near-IR. The measurement set is composed of a ratio of limb radiance profiles at two wavelengths that indicates the presence of cloud-scattering regions. Optical properties from an in-situ database are used to simulate scattering by cloud-particles. With appropriate configurations discussed in this paper, the SASKTRAN successive-orders of scatter radiative transfer model is able to simulate accurately the in-cloud radiances from OSIRIS. Configured in this way, the model is used with a multiplicative algebraic reconstruction technique (MART) to retrieve the cloud extinction profile for an assumed effective cloud particle size. The sensitivity of these retrievals to key auxiliary model parameters is shown, and it is demonstrated that the retrieved extinction profile models accurately the measured in-cloud radiances from OSIRIS. Since OSIRIS has an 11-yr record of subvisual cirrus cloud detections, the work described in this manuscript provides a very useful method for providing a long-term global record of the properties of these clouds.

[Application of single-band brightness variance ratio to the interference dissociation of cloud for satellite data].

PubMed

Qu, Wei-ping; Liu, Wen-qing; Liu, Jian-guo; Lu, Yi-huai; Zhu, Jun; Qin, Min; Liu, Cheng

2006-11-01

In satellite remote-sensing detection, cloud as an interference plays a negative role in data retrieval. How to discern the cloud fields with high fidelity thus comes as a need to the following research. A new method rooting in atmospheric radiation characteristics of cloud layer, in the present paper, presents a sort of solution where single-band brightness variance ratio is used to detect the relative intensity of cloud clutter so as to delineate cloud field rapidly and exactly, and the formulae of brightness variance ratio of satellite image, image reflectance variance ratio, and brightness temperature variance ratio of thermal infrared image are also given to enable cloud elimination to produce data free from cloud interference. According to the variance of the penetrating capability for different spectra bands, an objective evaluation is done on cloud penetration of them with the factors that influence penetration effect. Finally, a multi-band data fusion task is completed using the image data of infrared penetration from cirrus nothus. Image data reconstruction is of good quality and exactitude to show the real data of visible band covered by cloud fields. Statistics indicates the consistency of waveband relativity with image data after the data fusion.

Comparison of Monthly Mean Cloud Fraction and Cloud Optical depth Determined from Surface Cloud Radar, TOVS, AVHRR, and MODIS over Barrow, Alaska

NASA Technical Reports Server (NTRS)

Uttal, Taneil; Frisch, Shelby; Wang, Xuan-Ji; Key, Jeff; Schweiger, Axel; Sun-Mack, Sunny; Minnis, Patrick

2005-01-01

A one year comparison is made of mean monthly values of cloud fraction and cloud optical depth over Barrow, Alaska (71 deg 19.378 min North, 156 deg 36.934 min West) between 35 GHz radar-based retrievals, the TOVS Pathfinder Path-P product, the AVHRR APP-X product, and a MODIS based cloud retrieval product from the CERES-Team. The data sets represent largely disparate spatial and temporal scales, however, in this paper, the focus is to provide a preliminary analysis of how the mean monthly values derived from these different data sets compare, and determine how they can best be used separately, and in combination to provide reliable estimates of long-term trends of changing cloud properties. The radar and satellite data sets described here incorporate Arctic specific modifications that account for cloud detection challenges specific to the Arctic environment. The year 2000 was chosen for this initial comparison because the cloud radar data was particularly continuous and reliable that year, and all of the satellite retrievals of interest were also available for the year 2000. Cloud fraction was chosen as a comparison variable as accurate detection of cloud is the primary product that is necessary for any other cloud property retrievals. Cloud optical depth was additionally selected as it is likely the single cloud property that is most closely correlated to cloud influences on surface radiation budgets.

Seismic waveform modeling over cloud

NASA Astrophysics Data System (ADS)

Luo, Cong; Friederich, Wolfgang

2016-04-01

With the fast growing computational technologies, numerical simulation of seismic wave propagation achieved huge successes. Obtaining the synthetic waveforms through numerical simulation receives an increasing amount of attention from seismologists. However, computational seismology is a data-intensive research field, and the numerical packages usually come with a steep learning curve. Users are expected to master considerable amount of computer knowledge and data processing skills. Training users to use the numerical packages, correctly access and utilize the computational resources is a troubled task. In addition to that, accessing to HPC is also a common difficulty for many users. To solve these problems, a cloud based solution dedicated on shallow seismic waveform modeling has been developed with the state-of-the-art web technologies. It is a web platform integrating both software and hardware with multilayer architecture: a well designed SQL database serves as the data layer, HPC and dedicated pipeline for it is the business layer. Through this platform, users will no longer need to compile and manipulate various packages on the local machine within local network to perform a simulation. By providing users professional access to the computational code through its interfaces and delivering our computational resources to the users over cloud, users can customize the simulation at expert-level, submit and run the job through it.

Observations of temporal change of nighttime cloud cover from Himawari 8 and ground-based sky camera over Chiba, Japan

NASA Astrophysics Data System (ADS)

Lagrosas, N.; Gacal, G. F. B.; Kuze, H.

2017-12-01

Detection of nighttime cloud from Himawari 8 is implemented using the difference of digital numbers from bands 13 (10.4µm) and 7 (3.9µm). The digital number difference of -1.39x104 can be used as a threshold to separate clouds from clear sky conditions. To look at observations from the ground over Chiba, a digital camera (Canon Powershot A2300) is used to take images of the sky every 5 minutes at an exposure time of 5s at the Center for Environmental Remote Sensing, Chiba University. From these images, cloud cover values are obtained using threshold algorithm (Gacal, et al, 2016). Ten minute nighttime cloud cover values from these two datasets are compared and analyzed from 29 May to 05 June 2017 (20:00-03:00 JST). When compared with lidar data, the camera can detect thick high level clouds up to 10km. The results show that during clear sky conditions (02-03 June), both camera and satellite cloud cover values show 0% cloud cover. During cloudy conditions (05-06 June), the camera shows almost 100% cloud cover while satellite cloud cover values range from 60 to 100%. These low values can be attributed to the presence of low-level thin clouds ( 2km above the ground) as observed from National Institute for Environmental Studies lidar located inside Chiba University. This difference of cloud cover values shows that the camera can produce accurate cloud cover values of low level clouds that are sometimes not detected by satellites. The opposite occurs when high level clouds are present (01-02 June). Derived satellite cloud cover shows almost 100% during the whole night while ground-based camera shows cloud cover values that range from 10 to 100% during the same time interval. The fluctuating values can be attributed to the presence of thin clouds located at around 6km from the ground and the presence of low level clouds ( 1km). Since the camera relies on the reflected city lights, it is possible that the high level thin clouds are not observed by the camera but is observed by the satellite. Also, this condition constitutes layers of clouds that are not observed by each camera. The results of this study show that one instrument can be used to correct each other to provide better cloud cover values. These corrections is dependent on the height and thickness of the clouds. No correction is necessary when the sky is clear.

Introduction and analysis of several FY3C-MWHTS cloud/rain screening methods

NASA Astrophysics Data System (ADS)

Li, Xiaoqing

2017-04-01

Data assimilation of satellite microwave sounders are very important for numerical weather prediction. Fengyun-3C (FY-3C),launched in September, 2013, has two such sounders: MWTS (MicroWave Temperature Sounder) and MWHTS (MicroWave Humidity and Temperature Sounder). These data should be quality-controlled before assimilation and cloud/rain detection is one of the crucial steps. This paper introduced different cloud/rain detection methods based on MWHTS, VIRR (Visible and InfraRed Radiometer) and MWRI (Microwave Radiation Imager) observations. We designed 6 cloud/rain detection combinations and then analyzed the application effect of these schemes. The difference between observations and model simulations for FY-3C MWHTS channels were calculated as a parameter for analysis. Both RTTOV and CRTM were used to fast simulate radiances of MWHTS channels.

Volcanic eruption detection with TOMS

NASA Technical Reports Server (NTRS)

Krueger, Arlin J.

1987-01-01

The Nimbus 7 Total Ozone Mapping Spectrometer (TOMS) is designed for mapping of the atmospheric ozone distribution. Absorption by sulfur dioxide at the same ultraviolet spectral wavelengths makes it possible to observe and resolve the size of volcanic clouds. The sulfur dioxide absorption is discriminated from ozone and water clouds in the data processing by their spectral signatures. Thus, the sulfur dioxide can serve as a tracer which appears in volcanic eruption clouds because it is not present in other clouds. The detection limit with TOMS is close to the theoretical limit due to telemetry signal quantization of 1000 metric tons (5-sigma threshold) within the instrument field of view (50 by 50 km near the nadir). Requirements concerning the use of TOMS in detection of eruptions, geochemical cycles, and volcanic climatic effects are discussed.

IPRT polarized radiative transfer model intercomparison project - Three-dimensional test cases (phase B)

NASA Astrophysics Data System (ADS)

Emde, Claudia; Barlakas, Vasileios; Cornet, Céline; Evans, Frank; Wang, Zhen; Labonotte, Laurent C.; Macke, Andreas; Mayer, Bernhard; Wendisch, Manfred

2018-04-01

Initially unpolarized solar radiation becomes polarized by scattering in the Earth's atmosphere. In particular molecular scattering (Rayleigh scattering) polarizes electromagnetic radiation, but also scattering of radiation at aerosols, cloud droplets (Mie scattering) and ice crystals polarizes. Each atmospheric constituent produces a characteristic polarization signal, thus spectro-polarimetric measurements are frequently employed for remote sensing of aerosol and cloud properties. Retrieval algorithms require efficient radiative transfer models. Usually, these apply the plane-parallel approximation (PPA), assuming that the atmosphere consists of horizontally homogeneous layers. This allows to solve the vector radiative transfer equation (VRTE) efficiently. For remote sensing applications, the radiance is considered constant over the instantaneous field-of-view of the instrument and each sensor element is treated independently in plane-parallel approximation, neglecting horizontal radiation transport between adjacent pixels (Independent Pixel Approximation, IPA). In order to estimate the errors due to the IPA approximation, three-dimensional (3D) vector radiative transfer models are required. So far, only a few such models exist. Therefore, the International Polarized Radiative Transfer (IPRT) working group of the International Radiation Commission (IRC) has initiated a model intercomparison project in order to provide benchmark results for polarized radiative transfer. The group has already performed an intercomparison for one-dimensional (1D) multi-layer test cases [phase A, 1]. This paper presents the continuation of the intercomparison project (phase B) for 2D and 3D test cases: a step cloud, a cubic cloud, and a more realistic scenario including a 3D cloud field generated by a Large Eddy Simulation (LES) model and typical background aerosols. The commonly established benchmark results for 3D polarized radiative transfer are available at the IPRT website (http://www.meteo.physik.uni-muenchen.de/ iprt).

Saturn's Regional and Global Cloud Properties from Cassini/VIMS 4.5-5.1 Micron Spectroscopy

NASA Astrophysics Data System (ADS)

Fletcher, Leigh N.; Baines, K. H.; Momary, T. W.; Orton, G. S.; Roos-Serote, M.; Irwin, P. G. J.

2009-09-01

Exploiting a region of Saturn's thermal-IR spectrum between 4.5-5.1 microns where there is a dearth of opacity sources, Cassini/VIMS has revealed a wealth of dynamical phenomena in the 1-4 bar region that are transforming our understanding of the gas giant. Narrow dark lanes and discrete cloud features are observed in silhouette against the 5-micron background thermal glow of Saturn's deep atmosphere. The NEMESIS optimal-estimation retrieval algorithm (Irwin et al., JSQRT, 2008) is used to model the 4.5-5.1 micron region using the correlated-k approximation. We determine (a) the sensitivity and correlations associated with determinations of cloud properties and gaseous composition from the Cassini/VIMS dataset; (b) the meridional variation in opacity sources (a multi-layer cloud model, the abundances of phosphine and arsine); (c) the contribution of the thermal and reflected components to VIMS spectra and (d) the spatial variability of opacity sources associated with Saturn's string of pearls and ribbon wave features in the northern hemisphere. The meridional gradients in composition are compared to the Cassini/CIRS derivations of phosphine at higher altitudes (pressures less than 1 bar; Fletcher et al., Icarus, 2009). The seasonal origin of the north-south asymmetry in 5-micron opacity (Baines et al., BAAS, 2006) and the dynamical motions associated with Saturn's complex zonal wave activity will be discussed. The vertical distribution of cloud opacity demonstrates the necessity for aerosols at the 2-3 bar level to successfully replicate the VIMS data. Finally, we search Cassini/CIRS mapping observations at 15.0 cm-1 resolution for mid-IR counterparts (0.1-0.5 bar) to the zonal wave activity in the deeper troposphere (1-4 bars) to investigate the vertical coupling in Saturn's troposphere.

Comparison between SAGE II and ISCCP high-level clouds. 1: Global and zonal mean cloud amounts

NASA Technical Reports Server (NTRS)

Liao, Xiaohan; Rossow, William B.; Rind, David

1995-01-01

Global high-level clouds identified in Stratospheric Aerosol and Gas Experiment II (SAGE II) occultation measurements for January and July in the period 1985 to 1990 are compared with near-nadir-looking observations from the International Satellite Cloud Climatology Project (ISCCP). Global and zonal mean high-level cloud amounts from the two data sets agree very well, if clouds with layer extinction coefficients of less than 0.008/km at 1.02 micrometers wavelength are removed from the SAGE II results and all detected clouds are interpreted to have an average horizontal size of about 75 km along the 200 km transimission path length of the SAGE II observations. The SAGE II results are much more sensitive to variations of assumed cloud size than to variations of detection threshold. The geographical distribution of cloud fractions shows good agreement, but systematic regional differences also indicate that the average cloud size varies somewhat among different climate regimes. The more sensitive SAGE II results show that about one third of all high-level clouds are missed by ISCCP but that these clouds have very low optical thicknesses (less than 0.1 at 0.6 micrometers wavelength). SAGE II sampling error in monthly zonal cloud fraction is shown to produce no bias, to be less than the intraseasonal natural variability, but to be comparable with the natural variability at longer time scales.

Analysis of Counterfeit Coated Tablets and Multi-Layer Packaging Materials Using Infrared Microspectroscopic Imaging.

PubMed

Winner, Taryn L; Lanzarotta, Adam; Sommer, André J

2016-06-01

An effective method for detecting and characterizing counterfeit finished dosage forms and packaging materials is described in this study. Using attenuated total internal reflection Fourier transform infrared spectroscopic imaging, suspect tablet coating and core formulations as well as multi-layered foil safety seals, bottle labels, and cigarette tear tapes were analyzed and compared directly with those of a stored authentic product. The approach was effective for obtaining molecular information from structures as small as 6 μm.

Solutions of the heat conduction equation in multilayers for photothermal deflection experiments

NASA Technical Reports Server (NTRS)

Mcgahan, William A.; Cole, K. D.

1992-01-01

Analytical expressions for temperature and laser beam deflection in multilayer medium is derived using Green function techniques. The approach is based on calculation of the normal component of heat fluxes across the boundaries, from which either the beam deflections or the temperature anywhere in space can be found. A general expression for the measured signals for the case of four-quadrant detection is also presented and compared with previous calculations of detector response for finite probe beams.

Low-Frequency Carbon Recombination Lines in the Orion Molecular Cloud Complex

NASA Astrophysics Data System (ADS)

Tremblay, Chenoa D.; Jordan, Christopher H.; Cunningham, Maria; Jones, Paul A.; Hurley-Walker, Natasha

2018-05-01

We detail tentative detections of low-frequency carbon radio recombination lines from within the Orion molecular cloud complex observed at 99-129 MHz. These tentative detections include one alpha transition and one beta transition over three locations and are located within the diffuse regions of dust observed in the infrared at 100 μm, the Hα emission detected in the optical, and the synchrotron radiation observed in the radio. With these observations, we are able to study the radiation mechanism transition from collisionally pumped to radiatively pumped within the H ii regions within the Orion molecular cloud complex.

Newly detected molecules in dense interstellar clouds

NASA Astrophysics Data System (ADS)

Irvine, William M.; Avery, L. W.; Friberg, P.; Matthews, H. E.; Ziurys, L. M.

Several new interstellar molecules have been identified including C2S, C3S, C5H, C6H and (probably) HC2CHO in the cold, dark cloud TMC-1; and the discovery of the first interstellar phosphorus-containing molecule, PN, in the Orion "plateau" source. Further results include the observations of 13C3H2 and C3HD, and the first detection of HCOOH (formic acid) in a cold cloud.

Automatic detection of voice impairments by means of short-term cepstral parameters and neural network based detectors.

PubMed

Godino-Llorente, J I; Gómez-Vilda, P

2004-02-01

It is well known that vocal and voice diseases do not necessarily cause perceptible changes in the acoustic voice signal. Acoustic analysis is a useful tool to diagnose voice diseases being a complementary technique to other methods based on direct observation of the vocal folds by laryngoscopy. Through the present paper two neural-network based classification approaches applied to the automatic detection of voice disorders will be studied. Structures studied are multilayer perceptron and learning vector quantization fed using short-term vectors calculated accordingly to the well-known Mel Frequency Coefficient cepstral parameterization. The paper shows that these architectures allow the detection of voice disorders--including glottic cancer--under highly reliable conditions. Within this context, the Learning Vector quantization methodology demonstrated to be more reliable than the multilayer perceptron architecture yielding 96% frame accuracy under similar working conditions.

Electrochemical sensing of bisphenol using a multilayer graphene nanobelt modified photolithography patterned platinum electrode

NASA Astrophysics Data System (ADS)

Karthick Kannan, Padmanathan; Hu, Chunxiao; Morgan, Hywel; Moshkalev, Stanislav A.; Sekhar Rout, Chandra

2016-09-01

An electrochemical sensor has been developed for the detection of Bisphenol-A (BPA) using photolithographically patterned platinum electrodes modified with multilayer graphene nanobelts (GNB). Compared to bare electrodes, the GNB modified electrode exhibited enhanced BPA oxidation current, due to the high effective surface area and high adsorption capacity of the GNB. The sensor showed a linear response over the concentration range from 0.5 μM-9 μM with a very low limit of detection = 37.33 nM. In addition, the sensor showed very good stability and reproducibility with good specificity, demonstrating that GNB is potentially a new material for the development of a practical BPA electrochemical sensor with application in both industrial and plastic industries.

Using Hybrid Algorithm to Improve Intrusion Detection in Multi Layer Feed Forward Neural Networks

ERIC Educational Resources Information Center

Ray, Loye Lynn

2014-01-01

The need for detecting malicious behavior on a computer networks continued to be important to maintaining a safe and secure environment. The purpose of this study was to determine the relationship of multilayer feed forward neural network architecture to the ability of detecting abnormal behavior in networks. This involved building, training, and…

Diurnal cycle and seasonal variation of cloud cover over the Tibetan Plateau as determined from Himawari-8 new-generation geostationary satellite data.

PubMed

Shang, Huazhe; Letu, Husi; Nakajima, Takashi Y; Wang, Ziming; Ma, Run; Wang, Tianxing; Lei, Yonghui; Ji, Dabin; Li, Shenshen; Shi, Jiancheng

2018-01-18

Analysis of cloud cover and its diurnal variation over the Tibetan Plateau (TP) is highly reliant on satellite data; however, the accuracy of cloud detection from both polar-orbiting and geostationary satellites over this area remains unclear. The new-generation geostationary Himawari-8 satellites provide high-resolution spatial and temporal information about clouds over the Tibetan Plateau. In this study, the cloud detection of MODIS and AHI is investigated and validated against CALIPSO measurements. For AHI and MODIS, the false alarm rate of AHI and MODIS in cloud identification over the TP was 7.51% and 1.94%, respectively, and the cloud hit rate was 73.55% and 80.15%, respectively. Using hourly cloud-cover data from the Himawari-8 satellites, we found that at the monthly scale, the diurnal cycle in cloud cover over the TP tends to increase throughout the day, with the minimum and maximum cloud fractions occurring at 10:00 a.m. and 18:00 p.m. local time. Due to the limited time resolution of polar-orbiting satellites, the underestimation of MODIS daytime average cloud cover is approximately 4.00% at the annual scale, with larger biases during the spring (5.40%) and winter (5.90%).

A composite large-scale CO survey at high galactic latitudes in the second quadrant

NASA Technical Reports Server (NTRS)

Heithausen, A.; Stacy, J. G.; De Vries, H. W.; Mebold, U.; Thaddeus, P.

1993-01-01

Surveys undertaken in the 2nd quadrant of the Galaxy with the CfA 1.2 m telescope have been combined to produce a map covering about 620 sq deg in the 2.6 mm CO(J = 1 - 0) line at high galactic latitudes. There is CO emission from molecular 'cirrus' clouds in about 13 percent of the region surveyed. The CO clouds are grouped together into three major cloud complexes with 29 individual members. All clouds are associated with infrared emission at 100 micron, although there is no one-to-one correlation between the corresponding intensities. CO emission is detected in all bright and dark Lynds' nebulae cataloged in that region; however not all CO clouds are visible on optical photographs as reflection or absorption features. The clouds are probably local. At an adopted distance of 240 pc cloud sizes range from O.1 to 30 pc and cloud masses from 1 to 1600 solar masses. The molecular cirrus clouds contribute between 0.4 and 0.8 M solar mass/sq pc to the surface density of molecular gas in the galactic plane. Only 26 percent of the 'infrared-excess clouds' in the area surveyed actually show CO and about 2/3 of the clouds detected in CO do not show an infrared excess.

Radiative transfer model for aerosols at infrared wavelengths for passive remote sensing applications: revisited.

PubMed

Ben-David, Avishai; Davidson, Charles E; Embury, Janon F

2008-11-01

We introduced a two-dimensional radiative transfer model for aerosols in the thermal infrared [Appl. Opt.45, 6860-6875 (2006)APOPAI0003-693510.1364/AO.45.006860]. In that paper we superimposed two orthogonal plane-parallel layers to compute the radiance due to a two-dimensional (2D) rectangular aerosol cloud. In this paper we revisit the model and correct an error in the interaction of the two layers. We derive new expressions relating to the signal content of the radiance from an aerosol cloud based on the concept of five directional thermal contrasts: four for the 2D diffuse radiance and one for direct radiance along the line of sight. The new expressions give additional insight on the radiative transfer processes within the cloud. Simulations for Bacillus subtilis var. niger (BG) bioaerosol and dustlike kaolin aerosol clouds are compared and contrasted for two geometries: an airborne sensor looking down and a ground-based sensor looking up. Simulation results suggest that aerosol cloud detection from an airborne platform may be more challenging than for a ground-based sensor and that the detection of an aerosol cloud in emission mode (negative direct thermal contrast) is not the same as the detection of an aerosol cloud in absorption mode (positive direct thermal contrast).

Ice crystal characterization in cirrus clouds: a sun-tracking camera system and automated detection algorithm for halo displays

NASA Astrophysics Data System (ADS)

Forster, Linda; Seefeldner, Meinhard; Wiegner, Matthias; Mayer, Bernhard

2017-07-01

Halo displays in the sky contain valuable information about ice crystal shape and orientation: e.g., the 22° halo is produced by randomly oriented hexagonal prisms while parhelia (sundogs) indicate oriented plates. HaloCam, a novel sun-tracking camera system for the automated observation of halo displays is presented. An initial visual evaluation of the frequency of halo displays for the ACCEPT (Analysis of the Composition of Clouds with Extended Polarization Techniques) field campaign from October to mid-November 2014 showed that sundogs were observed more often than 22° halos. Thus, the majority of halo displays was produced by oriented ice crystals. During the campaign about 27 % of the cirrus clouds produced 22° halos, sundogs or upper tangent arcs. To evaluate the HaloCam observations collected from regular measurements in Munich between January 2014 and June 2016, an automated detection algorithm for 22° halos was developed, which can be extended to other halo types as well. This algorithm detected 22° halos about 2 % of the time for this dataset. The frequency of cirrus clouds during this time period was estimated by co-located ceilometer measurements using temperature thresholds of the cloud base. About 25 % of the detected cirrus clouds occurred together with a 22° halo, which implies that these clouds contained a certain fraction of smooth, hexagonal ice crystals. HaloCam observations complemented by radiative transfer simulations and measurements of aerosol and cirrus cloud optical thickness (AOT and COT) provide a possibility to retrieve more detailed information about ice crystal roughness. This paper demonstrates the feasibility of a completely automated method to collect and evaluate a long-term database of halo observations and shows the potential to characterize ice crystal properties.

STS-40 Spacelab Life Science 1 (SLS-1) module in OV-102's payload bay (PLB)

NASA Image and Video Library

1991-06-14

STS040-612-005 (5-14 June 1991) --- This view showing the Spacelab Life Sciences (SLS-1) module in Columbia's cargo bay was taken through windows on the aft flight deck. Under some lighting conditions the multi-layered Shuttle windows have internal reflections that provide a kaleidoscopic effect. In this image the sunrays as seen on the clouds also appear to be present in space. Note how the white sunlight toward the Sun at the Earth's limb becomes separated into the colors of the visible spectrum towards that part of the limb further into darkness due to atmosphere acting as a natural prism.

DSCOVR/EPIC observations of SO2 reveal dynamics of young volcanic eruption clouds

NASA Astrophysics Data System (ADS)

Carn, S. A.; Krotkov, N. A.; Taylor, S.; Fisher, B. L.; Li, C.; Bhartia, P. K.; Prata, F. J.

2017-12-01

Volcanic emissions of sulfur dioxide (SO2) and ash have been measured by ultraviolet (UV) and infrared (IR) sensors on US and European polar-orbiting satellites since the late 1970s. Although successful, the main limitation of these observations from low Earth orbit (LEO) is poor temporal resolution (once per day at low latitudes). Furthermore, most currently operational geostationary satellites cannot detect SO2, a key tracer of volcanic plumes, limiting our ability to elucidate processes in fresh, rapidly evolving volcanic eruption clouds. In 2015, the launch of the Earth Polychromatic Imaging Camera (EPIC) aboard the Deep Space Climate Observatory (DSCOVR) provided the first opportunity to observe volcanic clouds from the L1 Lagrange point. EPIC is a 10-band spectroradiometer spanning UV to near-IR wavelengths with two UV channels sensitive to SO2, and a ground resolution of 25 km. The unique L1 vantage point provides continuous observations of the sunlit Earth disk, from sunrise to sunset, offering multiple daily observations of volcanic SO2 and ash clouds in the EPIC field of view. When coupled with complementary retrievals from polar-orbiting UV and IR sensors such as the Ozone Monitoring Instrument (OMI), the Ozone Mapping and Profiler Suite (OMPS), and the Atmospheric Infrared Sounder (AIRS), we demonstrate how the increased observation frequency afforded by DSCOVR/EPIC permits more timely volcanic eruption detection and novel analyses of the temporal evolution of volcanic clouds. Although EPIC has detected several mid- to high-latitude volcanic eruptions since launch, we focus on recent eruptions of Bogoslof volcano (Aleutian Islands, AK, USA). A series of EPIC exposures from May 28-29, 2017, uniquely captures the evolution of SO2 mass in a young Bogoslof eruption cloud, showing separation of SO2- and ice-rich regions of the cloud. We show how analyses of these sequences of EPIC SO2 data can elucidate poorly understood processes in transient eruption clouds, such as the relative roles of H2S oxidation and ice scavenging in modifying volcanic SO2 emissions. Detection of these relatively small events also proves EPIC's ability to provide timely detection of volcanic clouds in the upper troposphere and lower stratosphere.

Harmonic regression based multi-temporal cloud filtering algorithm for Landsat 8

NASA Astrophysics Data System (ADS)

Joshi, P.

2015-12-01

Landsat data archive though rich is seen to have missing dates and periods owing to the weather irregularities and inconsistent coverage. The satellite images are further subject to cloud cover effects resulting in erroneous analysis and observations of ground features. In earlier studies the change detection algorithm using statistical control charts on harmonic residuals of multi-temporal Landsat 5 data have been shown to detect few prominent remnant clouds [Brooks, Evan B., et al, 2014]. So, in this work we build on this harmonic regression approach to detect and filter clouds using a multi-temporal series of Landsat 8 images. Firstly, we compute the harmonic coefficients using the fitting models on annual training data. This time series of residuals is further subjected to Shewhart X-bar control charts which signal the deviations of cloud points from the fitted multi-temporal fourier curve. For the process with standard deviation σ we found the second and third order harmonic regression with a x-bar chart control limit [Lσ] ranging between [0.5σ < Lσ < σ] as most efficient in detecting clouds. By implementing second order harmonic regression with successive x-bar chart control limits of L and 0.5 L on the NDVI, NDSI and haze optimized transformation (HOT), and utilizing the seasonal physical properties of these parameters, we have designed a novel multi-temporal algorithm for filtering clouds from Landsat 8 images. The method is applied to Virginia and Alabama in Landsat8 UTM zones 17 and 16 respectively. Our algorithm efficiently filters all types of cloud cover with an overall accuracy greater than 90%. As a result of the multi-temporal operation and the ability to recreate the multi-temporal database of images using only the coefficients of the fourier regression, our algorithm is largely storage and time efficient. The results show a good potential for this multi-temporal approach for cloud detection as a timely and targeted solution for the Landsat 8 research community, catering to the need for innovative processing solutions in the infant stage of the satellite.

Speeding Clouds May Reveal Invisible Black Holes

NASA Astrophysics Data System (ADS)

Kohler, Susanna

2017-07-01

Several small, speeding clouds have been discovered at the center of our galaxy. A new study suggests that these unusual objects may reveal the lurking presence of inactive black holes.Peculiar Cloudsa) Velocity-integrated intensity map showing the location of the two high-velocity compact clouds, HCN0.0090.044 and HCN0.0850.094, in the context of larger molecular clouds. b) and c) Latitude-velocity and longitude-velocity maps for HCN0.0090.044 and HCN0.0850.094, respectively. d) and e) spectra for the two compacts clouds, respectively. Click for a closer look. [Takekawa et al. 2017]Sgr A*, the supermassive black hole marking the center of our galaxy, is surrounded by a region roughly 650 light-years across known as the Central Molecular Zone. This area at the heart of our galaxy is filled with large amounts of warm, dense molecular gas that has a complex distribution and turbulent kinematics.Several peculiar gas clouds have been discovered within the Central Molecular Zone within the past two decades. These clouds, dubbed high-velocity compact clouds, are characterized by their compact sizes and extremely broad velocity widths.What created this mysterious population of energetic clouds? The recent discovery of two new high-velocity compact clouds, reported on in a paper led by Shunya Takekawa (Keio University, Japan), may help us to answer this question.Two More to the CountUsing the James Clerk Maxwell Telescope in Hawaii, Takekawa and collaborators detected the small clouds near the circumnuclear disk at the centermost part of our galaxy. These two clouds have velocity spreads of -80 to -20 km/s and -80 to 0 km/s and compact sizes of just over 1 light-year. The clouds similar appearances and physical properties suggest that they may both have been formed by the same process.Takekawa and collaborators explore and discard several possible origins for these clouds, such as outflows from massive protostars (no massive, luminous stars have been detected affiliated with these clouds), interaction with supernova remnants (no supernova remnants have been detected toward the clouds), and cloudcloud collisions (such collisions leave other signs, like cavities in the parent cloud, which are not detected here).Masses and velocities of black holes that could create the two high-velocity compact clouds fall above the red and blue lines here. [Takekawa et al. 2017]Revealed on the PlungeAs an alternative explanation, Takekawa and collaborators propose that these two small,speeding cloudswere each created when a massive compact object plunged into a nearby molecular cloud. Since we dont seeany luminous stellar counterparts to the high-velocity compact clouds, this suggests that the responsibleobjects were invisible black holes. As each black hole tore through a molecular cloud, it dragged some of the clouds gas along behind it to form the high-velocity compact cloud.Does this explanation make sense statistically? The authors point out that the number of black holes predicted to silently lurk in the central 30 light-years of the Milky Way is around 10,000. This makes it entirely plausible that we could have caught sight of two of them as they revealed their presence while plunging through molecular clouds.If the authors interpretation is correct, then high-velocity compact clouds provide an excellent opportunity: we can search for these speeding bodiesto potentially discover inactive black holes that would otherwise go undetected.CitationShunya Takekawa et al 2017 ApJL 843 L11. doi:10.3847/2041-8213/aa79ee

Geomorphological activity at a rock glacier front detected with a 3D density-based clustering algorithm

NASA Astrophysics Data System (ADS)

Micheletti, Natan; Tonini, Marj; Lane, Stuart N.

2017-02-01

Acquisition of high density point clouds using terrestrial laser scanners (TLSs) has become commonplace in geomorphic science. The derived point clouds are often interpolated onto regular grids and the grids compared to detect change (i.e. erosion and deposition/advancement movements). This procedure is necessary for some applications (e.g. digital terrain analysis), but it inevitably leads to a certain loss of potentially valuable information contained within the point clouds. In the present study, an alternative methodology for geomorphological analysis and feature detection from point clouds is proposed. It rests on the use of the Density-Based Spatial Clustering of Applications with Noise (DBSCAN), applied to TLS data for a rock glacier front slope in the Swiss Alps. The proposed methods allowed the detection and isolation of movements directly from point clouds which yield to accuracies in the following computation of volumes that depend only on the actual registered distance between points. We demonstrated that these values are more conservative than volumes computed with the traditional DEM comparison. The results are illustrated for the summer of 2015, a season of enhanced geomorphic activity associated with exceptionally high temperatures.

Retrieval of subvisual cirrus cloud optical thickness from limb-scatter measurements

NASA Astrophysics Data System (ADS)

Wiensz, J. T.; Degenstein, D. A.; Lloyd, N. D.; Bourassa, A. E.

2013-01-01

We present a technique for estimating the optical thickness of subvisual cirrus clouds detected by OSIRIS (Optical Spectrograph and Infrared Imaging System), a limb-viewing satellite instrument that measures scattered radiances from the UV to the near-IR. The measurement set is composed of a ratio of limb radiance profiles at two wavelengths that indicates the presence of cloud-scattering regions. Cross-sections and phase functions from an in situ database are used to simulate scattering by cloud-particles. With appropriate configurations discussed in this paper, the SASKTRAN successive-orders of scatter radiative transfer model is able to simulate accurately the in-cloud radiances from OSIRIS. Configured in this way, the model is used with a multiplicative algebraic reconstruction technique (MART) to retrieve the cloud extinction profile for an assumed effective cloud particle size. The sensitivity of these retrievals to key auxiliary model parameters is shown, and it is shown that the retrieved extinction profile, for an assumed effective cloud particle size, models well the measured in-cloud radiances from OSIRIS. The greatest sensitivity of the retrieved optical thickness is to the effective cloud particle size. Since OSIRIS has an 11-yr record of subvisual cirrus cloud detections, the work described in this manuscript provides a very useful method for providing a long-term global record of the properties of these clouds.

Global Analysis of Aerosol Properties Above Clouds

NASA Technical Reports Server (NTRS)

Waquet, F.; Peers, F.; Ducos, F.; Goloub, P.; Platnick, S. E.; Riedi, J.; Tanre, D.; Thieuleux, F.

2013-01-01

The seasonal and spatial varability of Aerosol Above Cloud (AAC) properties are derived from passive satellite data for the year 2008. A significant amount of aerosols are transported above liquid water clouds on the global scale. For particles in the fine mode (i.e., radius smaller than 0.3 m), including both clear sky and AAC retrievals increases the global mean aerosol optical thickness by 25(+/- 6%). The two main regions with man-made AAC are the tropical Southeast Atlantic, for biomass burning aerosols, and the North Pacific, mainly for pollutants. Man-made AAC are also detected over the Arctic during the spring. Mineral dust particles are detected above clouds within the so-called dust belt region (5-40 N). AAC may cause a warming effect and bias the retrieval of the cloud properties. This study will then help to better quantify the impacts of aerosols on clouds and climate.

Concept, Simulation, and Instrumentation for Radiometric Inflight Icing Detection

NASA Technical Reports Server (NTRS)

Ryerson, Charles; Koenig, George G.; Reehorst, Andrew L.; Scott, Forrest R.

2009-01-01

The multi-agency Flight in Icing Remote Sensing Team (FIRST), a consortium of the National Aeronautics and Space Administration (NASA), the Federal Aviation Administration (FAA), the National Center for Atmospheric Research (NCAR), the National Oceanographic and Atmospheric Administration (NOAA), and the Army Corps of Engineers (USACE), has developed technologies for remotely detecting hazardous inflight icing conditions. The USACE Cold Regions Research and Engineering Laboratory (CRREL) assessed the potential of onboard passive microwave radiometers for remotely detecting icing conditions ahead of aircraft. The dual wavelength system differences the brightness temperature of Space and clouds, with greater differences potentially indicating closer and higher magnitude cloud liquid water content (LWC). The Air Force RADiative TRANsfer model (RADTRAN) was enhanced to assess the flight track sensing concept, and a 'flying' RADTRAN was developed to simulate a radiometer system flying through simulated clouds. Neural network techniques were developed to invert brightness temperatures and obtain integrated cloud liquid water. In addition, a dual wavelength Direct-Detection Polarimeter Radiometer (DDPR) system was built for detecting hazardous drizzle drops. This paper reviews technology development to date and addresses initial polarimeter performance.

Snow cover detection algorithm using dynamic time warping method and reflectances of MODIS solar spectrum channels

NASA Astrophysics Data System (ADS)

Lee, Kyeong-sang; Choi, Sungwon; Seo, Minji; Lee, Chang suk; Seong, Noh-hun; Han, Kyung-Soo

2016-10-01

Snow cover is biggest single component of cryosphere. The Snow is covering the ground in the Northern Hemisphere approximately 50% in winter season and is one of climate factors that affects Earth's energy budget because it has higher reflectance than other land types. Also, snow cover has an important role about hydrological modeling and water resource management. For this reason, accurate detection of snow cover acts as an essential element for regional water resource management. Snow cover detection using satellite-based data have some advantages such as obtaining wide spatial range data and time-series observations periodically. In the case of snow cover detection using satellite data, the discrimination of snow and cloud is very important. Typically, Misclassified cloud and snow pixel can lead directly to error factor for retrieval of satellite-based surface products. However, classification of snow and cloud is difficult because cloud and snow have similar optical characteristics and are composed of water or ice. But cloud and snow has different reflectance in 1.5 1.7 μm wavelength because cloud has lower grain size and moisture content than snow. So, cloud and snow shows difference reflectance patterns change according to wavelength. Therefore, in this study, we perform algorithm for classifying snow cover and cloud with satellite-based data using Dynamic Time Warping (DTW) method which is one of commonly used pattern analysis such as speech and fingerprint recognitions and reflectance spectral library of snow and cloud. Reflectance spectral library is constructed in advance using MOD21km (MODIS Level1 swath 1km) data that their reflectance is six channels including 3 (0.466μm), 4 (0.554μm), 1 (0.647μm), 2 (0.857μm), 26 (1.382μm) and 6 (1.629μm). We validate our result using MODIS RGB image and MOD10 L2 swath (MODIS swath snow cover product). And we use PA (Producer's Accuracy), UA (User's Accuracy) and CI (Comparison Index) as validation criteria. The result of our study detect as snow cover in the several regions which are did not detected as snow in MOD10 L2 and detected as snow cover in MODIS RGB image. The result of our study can improve accuracy of other surface product such as land surface reflectance and land surface emissivity. Also it can use input data of hydrological modeling.

Improved ocean-color remote sensing in the Arctic using the POLYMER algorithm

NASA Astrophysics Data System (ADS)

Frouin, Robert; Deschamps, Pierre-Yves; Ramon, Didier; Steinmetz, François

2012-10-01

Atmospheric correction of ocean-color imagery in the Arctic brings some specific challenges that the standard atmospheric correction algorithm does not address, namely low solar elevation, high cloud frequency, multi-layered polar clouds, presence of ice in the field-of-view, and adjacency effects from highly reflecting surfaces covered by snow and ice and from clouds. The challenges may be addressed using a flexible atmospheric correction algorithm, referred to as POLYMER (Steinmetz and al., 2011). This algorithm does not use a specific aerosol model, but fits the atmospheric reflectance by a polynomial with a non spectral term that accounts for any non spectral scattering (clouds, coarse aerosol mode) or reflection (glitter, whitecaps, small ice surfaces within the instrument field of view), a spectral term with a law in wavelength to the power -1 (fine aerosol mode), and a spectral term with a law in wavelength to the power -4 (molecular scattering, adjacency effects from clouds and white surfaces). Tests are performed on selected MERIS imagery acquired over Arctic Seas. The derived ocean properties, i.e., marine reflectance and chlorophyll concentration, are compared with those obtained with the standard MEGS algorithm. The POLYMER estimates are more realistic in regions affected by the ice environment, e.g., chlorophyll concentration is higher near the ice edge, and spatial coverage is substantially increased. Good retrievals are obtained in the presence of thin clouds, with ocean-color features exhibiting spatial continuity from clear to cloudy regions. The POLYMER estimates of marine reflectance agree better with in situ measurements than the MEGS estimates. Biases are 0.001 or less in magnitude, except at 412 and 443 nm, where they reach 0.005 and 0.002, respectively, and root-mean-squared difference decreases from 0.006 at 412 nm to less than 0.001 at 620 and 665 nm. A first application to MODIS imagery is presented, revealing that the POLYMER algorithm is robust when pixels are contaminated by sea ice.

A robust threshold-based cloud mask for the HRV channel of MSG SEVIRI

NASA Astrophysics Data System (ADS)

Bley, S.; Deneke, H.

2013-03-01

A robust threshold-based cloud mask for the high-resolution visible (HRV) channel (1 × 1 km2) of the METEOSAT SEVIRI instrument is introduced and evaluated. It is based on operational EUMETSAT cloud mask for the low resolution channels of SEVIRI (3 × 3 km2), which is used for the selection of suitable thresholds to ensure consistency with its results. The aim of using the HRV channel is to resolve small-scale cloud structures which cannot be detected by the low resolution channels. We find that it is of advantage to apply thresholds relative to clear-sky reflectance composites, and to adapt the threshold regionally. Furthermore, the accuracy of the different spectral channels for thresholding and the suitability of the HRV channel are investigated for cloud detection. The case studies show different situations to demonstrate the behaviour for various surface and cloud conditions. Overall, between 4 and 24% of cloudy low-resolution SEVIRI pixels are found to contain broken clouds in our test dataset depending on considered region. Most of these broken pixels are classified as cloudy by EUMETSAT's cloud mask, which will likely result in an overestimate if the mask is used as estimate of cloud fraction.

Inhomogeneous models of the Venus clouds containing sulfur

NASA Technical Reports Server (NTRS)

Smith, S. M.; Pollack, J. B.; Giver, L. P.; Cuzzi, J. N.; Podolak, M.

1979-01-01

Based on the suggestion that elemental sulfur is responsible for the yellow color of Venus, calculations are compared at 3.4 microns of the reflectivity phase function of two sulfur containing inhomogeneous cloud models with that of a homogeneous model. Assuming reflectivity observations with 25% or less total error, comparison of the model calculations leads to a minimum detectable mass of sulfur equal to 7% of the mass of sulfuric acid for the inhomogeneous drop model. For the inhomogeneous cloud model the comparison leads to a minimum detectable mass of sulfur between 17% and 38% of the mass of the acid drops, depending upon the actual size of the large particles. It is concluded that moderately accurate 3.4 microns reflectivity observations are capable of detecting quite small amounts of elemental sulfur at the top of the Venus clouds.

Cirrus cloud retrieval from MSG/SEVIRI during day and night using artificial neural networks

NASA Astrophysics Data System (ADS)

Strandgren, Johan; Bugliaro, Luca

2017-04-01

By covering a large part of the Earth, cirrus clouds play an important role in climate as they reflect incoming solar radiation and absorb outgoing thermal radiation. Nevertheless, the cirrus clouds remain one of the largest uncertainties in atmospheric research and the understanding of the physical processes that govern their life cycle is still poorly understood, as is their representation in climate models. To monitor and better understand the properties and physical processes of cirrus clouds, it's essential that those tenuous clouds can be observed from geostationary spaceborne imagers like SEVIRI (Spinning Enhanced Visible and InfraRed Imager), that possess a high temporal resolution together with a large field of view and play an important role besides in-situ observations for the investigation of cirrus cloud processes. CiPS (Cirrus Properties from Seviri) is a new algorithm targeting thin cirrus clouds. CiPS is an artificial neural network trained with coincident SEVIRI and CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization) observations in order to retrieve a cirrus cloud mask along with the cloud top height (CTH), ice optical thickness (IOT) and ice water path (IWP) from SEVIRI. By utilizing only the thermal/IR channels of SEVIRI, CiPS can be used during day and night making it a powerful tool for the cirrus life cycle analysis. Despite the great challenge of detecting thin cirrus clouds and retrieving their properties from a geostationary imager using only the thermal/IR wavelengths, CiPS performs well. Among the cirrus clouds detected by CALIOP, CiPS detects 70 and 95 % of the clouds with an optical thickness of 0.1 and 1.0 respectively. Among the cirrus free pixels, CiPS classify 96 % correctly. For the CTH retrieval, CiPS has a mean absolute percentage error of 10 % or less with respect to CALIOP for cirrus clouds with a CTH greater than 8 km. For the IOT retrieval, CiPS has a mean absolute percentage error of 100 % or less with respect to CALIOP for cirrus clouds with an optical thickness down to 0.07. For such thin cirrus clouds an error of 100 % should be regarded as low from a geostationary imager like SEVIRI. The IWP retrieved by CiPS shows a similar performance, but has larger deviations for the thinner cirrus clouds.

Comparative Study of Aerosol and Cloud Detected by CALIPSO and OMI

NASA Technical Reports Server (NTRS)

Chen, Zhong; Torres, Omar; McCormick, M. Patrick; Smith, William; Ahn, Changwoo

2012-01-01

The Ozone Monitoring Instrument (OMI) on the Aura Satellite detects the presence of desert dust and smoke particles (also known as aerosols) in terms of a parameter known as the UV Aerosol Index (UV AI). The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) mission measures the vertical distribution of aerosols and clouds. Aerosols and clouds play important roles in the atmosphere and climate system. Accurately detecting their presence, altitude, and properties using satellite radiance measurements is a very important task. This paper presents a comparative analysis of the CALIPSO Version 2 Vertical Feature Mask (VFM) product with the (OMI) UV Aerosol Index (UV AI) and reflectivity datasets for a full year of 2007. The comparison is done at regional and global scales. Based on CALIPSO arid OMI observations, the vertical and horizontal extent of clouds and aerosols are determined and the effects of aerosol type selection, load, cloud fraction on aerosol identification are discussed. It was found that the spatial-temporal correlation found between CALIPSO and OMI observations, is strongly dependent on aerosol types and cloud contamination. CALIPSO is more sensitivity to cloud and often misidentifies desert dust aerosols as cloud, while some small scale aerosol layers as well as some pollution aerosols are unidentified by OMI UV AI. Large differences in aerosol distribution patterns between CALIPSO and OMI are observed, especially for the smoke and pollution aerosol dominated areas. In addition, the results found a significant correlation between CALIPSO lidar 1064 nm backscatter and the OMI UV AI over the study regions.

A Bispectral Composite Threshold Approach for Automatic Cloud Detection in VIIRS Imagery

NASA Technical Reports Server (NTRS)

LaFontaine Frank J.; Jedlovec, Gary J.

2015-01-01

The detection of clouds in satellite imagery has a number of important applications in weather and climate studies. The presence of clouds can alter the energy budget of the Earth-atmosphere system through scattering and absorption of shortwave radiation and the absorption and re-emission of infrared radiation at longer wavelengths. The scattering and absorption characteristics of clouds vary with the microphysical properties of clouds, hence the cloud type. Thus, detecting the presence of clouds over a region in satellite imagery is important in order to derive atmospheric or surface parameters that give insight into weather and climate processes. For many applications however, clouds are a contaminant whose presence interferes with retrieving atmosphere or surface information. In these cases, is important to isolate cloud-free pixels, used to retrieve atmospheric thermodynamic information or surface geophysical parameters, from cloudy ones. This abstract describes an application of a two-channel bispectral composite threshold (BCT) approach applied to VIIRS imagery. The simplified BCT approach uses only the 10.76 and 3.75 micrometer spectral channels from VIIRS in two spectral tests; a straight-forward infrared threshold test with the longwave channel and a shortwave - longwave channel difference test. The key to the success of this approach as demonstrated in past applications to GOES and MODIS data is the generation of temporally and spatially dependent thresholds used in the tests from a previous number of days at similar observations to the current data. The paper and subsequent presentation will present an overview of the approach and intercomparison results with other satellites, methods, and against verification data.

Applications of 3D-EDGE Detection for ALS Point Cloud

NASA Astrophysics Data System (ADS)

Ni, H.; Lin, X. G.; Zhang, J. X.

2017-09-01

Edge detection has been one of the major issues in the field of remote sensing and photogrammetry. With the fast development of sensor technology of laser scanning system, dense point clouds have become increasingly common. Precious 3D-edges are able to be detected from these point clouds and a great deal of edge or feature line extraction methods have been proposed. Among these methods, an easy-to-use 3D-edge detection method, AGPN (Analyzing Geometric Properties of Neighborhoods), has been proposed. The AGPN method detects edges based on the analysis of geometric properties of a query point's neighbourhood. The AGPN method detects two kinds of 3D-edges, including boundary elements and fold edges, and it has many applications. This paper presents three applications of AGPN, i.e., 3D line segment extraction, ground points filtering, and ground breakline extraction. Experiments show that the utilization of AGPN method gives a straightforward solution to these applications.

Indoor Modelling from Slam-Based Laser Scanner: Door Detection to Envelope Reconstruction

NASA Astrophysics Data System (ADS)

Díaz-Vilariño, L.; Verbree, E.; Zlatanova, S.; Diakité, A.

2017-09-01

Updated and detailed indoor models are being increasingly demanded for various applications such as emergency management or navigational assistance. The consolidation of new portable and mobile acquisition systems has led to a higher availability of 3D point cloud data from indoors. In this work, we explore the combined use of point clouds and trajectories from SLAM-based laser scanner to automate the reconstruction of building indoors. The methodology starts by door detection, since doors represent transitions from one indoor space to other, which constitutes an initial approach about the global configuration of the point cloud into building rooms. For this purpose, the trajectory is used to create a vertical point cloud profile in which doors are detected as local minimum of vertical distances. As point cloud and trajectory are related by time stamp, this feature is used to subdivide the point cloud into subspaces according to the location of the doors. The correspondence between subspaces and building rooms is not unambiguous. One subspace always corresponds to one room, but one room is not necessarily depicted by just one subspace, for example, in case of a room containing several doors and in which the acquisition is performed in a discontinue way. The labelling problem is formulated as combinatorial approach solved as a minimum energy optimization. Once the point cloud is subdivided into building rooms, envelop (conformed by walls, ceilings and floors) is reconstructed for each space. The connectivity between spaces is included by adding the previously detected doors to the reconstructed model. The methodology is tested in a real case study.

Optical cloud detection from a disposable airborne sensor

NASA Astrophysics Data System (ADS)

Nicoll, Keri; Harrison, R. Giles; Brus, David

2016-04-01

In-situ measurement of cloud droplet microphysical properties is most commonly made from manned aircraft platforms due to the size and weight of the instrumentation, which is both costly and typically limited to sampling only a few clouds. This work describes the development of a small, lightweight (<200g), disposable, optical cloud sensor which is designed for use on routine radiosonde balloon flights and also small unmanned aerial vehicle (UAV) platforms. The sensor employs the backscatter principle, using an ultra-bright LED as the illumination source, with a photodiode detector. Scattering of the LED light by cloud droplets generates a small optical signal which is separated from background light fluctuations using a lock-in technique. The signal to noise obtained permits cloud detection using the scattered LED light, even in daytime. During recent field tests in Pallas, Finland, the retrieved optical sensor signal has been compared with the DMT Cloud and Aerosol Spectrometer (CAS) which measures cloud droplets in the size range from 0.5 to 50 microns. Both sensors were installed at the hill top observatory of Sammaltunturi during a field campaign in October and November 2015, which experienced long periods of immersion inside cloud. Preliminary analysis shows very good agreement between the CAPS and the disposable cloud sensor for cloud droplets >5micron effective diameter. Such data and calibration of the sensor will be discussed here, as will simultaneous balloon launches of the optical cloud sensor through the same cloud layers.

Cloud Detection Using Measured and Modeled State Parameters

NASA Technical Reports Server (NTRS)

Yi, Y.; Minnis, P.; Huang, J.; Ayers, J. K.; Doelling, D. R.; Khaiyer, M. M.; Nordeen, M. L.

2004-01-01

In this study, hourly RUC analyses were used to examine the differences between RH and temperature values from RUC reanalysis data and from radiosonde atmospheric profiles obtained at the ARM SCF. The results show that the temperature observations from the SONDE and RUC are highly correlated. The RHs are also well-correlated, but the SONDE values generally exceed those from RUC. Inside cloud layers, the RH from RUC is 2-14% lower than the RH from SONDE for all RUC layers. Although the layer mean RH within clouds is much greater than the layer mean RH outside cloud or in the clear-sky, RH thresholds chosen as a function of temperature can more accurately diagnose cloud occurrence for either dataset. For overcast clouds, it was found that the 50% probability RH threshold for diagnosing a cloud, within a given upper tropospheric layer is roughly 90% for the Vaisala RS80-15LH radisonde and 80% for RUC data. While for the partial cloud (cloud amount is less than 90%), the RH thresholds of SONDE are close to RUC for a given probability in upper tropospheric layers. The probabilities of detecting clouds at a given RH and temperature should be useful for a variety of application such as the development of new cloud parameterizations or for estimating the vertical profile of cloudiness underneath a given cloud observed from the satellite to construct a 3-D cloud data set for computing atmospheric radiative heating profiles or determining potential aircraft icing conditions.

Outer satellite atmospheres: Their nature and planetary interactions. [atmospheric models for Amalthea, Ganymede, Callisto, and Titan are presented

NASA Technical Reports Server (NTRS)

Smyth, W. H.

1978-01-01

Results show that Amalthea is likely to form a tightly-bound partial toroidal-shaped hydrogen cloud about its planet, while Ganymede, Callisto and Titan may have rather large, complete and nearly symmetric toroidal-shaped clouds. The toroidal cloud for Amalthea compares favorably with spacecraft data of Pioneer 10 for a satellite escape flux of order 10 to the 11th power atoms/sq cm/sec. Model results for Ganymede, Callisto and Titan suggest that these extended hydrogen atmospheres are likely to be detected by the Voyager spacecrafts and that Titan's cloud might also be detected by the Pioneer 11 spacecraft. Ions created because of atoms lost through ionization processes from these four extended hydrogen atmospheres and from the sodium cloud of Io are discussed.

Assessment of Cloud Screening with Apparent Surface Reflectance in Support of the ICESat-2 Mission

NASA Technical Reports Server (NTRS)

Yang, Yuekui; Marshak, Alexander; Palm, Stephen P.; Wang, Zhuosen; Schaaf, Crystal

2011-01-01

The separation of cloud and clear scenes is usually one of the first steps in satellite data analysis. Before deriving a geophysical product, almost every satellite mission requires a cloud mask to label a scene as either clear or cloudy through a cloud detection procedure. For clear scenes, products such as surface properties may be retrieved; for cloudy scenes, scientist can focus on studying the cloud properties. Hence the quality of cloud detection directly affects the quality of most satellite operational and research products. This is certainly true for the Ice, Cloud, and land Elevation Satellite-2 (lCESat-2), which is the successor to the ICESat-l. As a top priority mission, ICESat-2 will continue to provide measurements of ice sheets and sea ice elevation on a global scale. Studies have shown that clouds can significantly affect the accuracy of the retrieved results. For example, some of the photons (a photon is a basic unit of light) in the laser beam will be scattered by cloud particles on its way. So instead of traveling in a straight line, these photons are scattered sideways and have traveled a longer path. This will result in biases in ice sheet elevation measurements. Hence cloud screening must be done and be done accurately before the retrievals.

Analysis of Co-Located MODIS and CALIPSO Observations Near Clouds

NASA Technical Reports Server (NTRS)

Varnai, Tamas; Marshak, Alexander

2011-01-01

The purpose of this paper is to help researchers combine data from different satellites and thus gain new insights into two critical yet poorly understood aspects of anthropogenic climate change, aerosol-cloud interactions and aerosol radiative effects, For this, the paper explores whether cloud information from the Aqua satellite's MODIS instrument can help characterize systematic aerosol changes near clouds by refining earlier perceptions of these changes that were based on the CALIPSO satellite's CALIOP instrument. Similar to a radar but using visible and ncar-infrared light, CALIOP sends out laser pulses and provides aerosol and cloud information along a single line that tracks the satellite orbit by measuring the reflection of its pulses. In contrast, MODIS takes images of reflected sunlight and emitted infrared radiation at several wavelengths, and covers wide areas around the satellite track. This paper analyzes a year-long global dataset covering all ice-free oceans, and finds that MODIS can greatly help the interpretation of CALIOP observations, especially by detecting clouds that lie outside the line observed by CALlPSO. The paper also finds that complications such as differences in view direction or clouds drifting in the 72 seconds that elapse between MODIS and CALIOP observations have only a minor impact. The study also finds that MODIS data helps refine but does not qualitatively alter perceptions of the systematic aerosol changes that were detected in earlier studies using only CALIOP data. It then proposes a statistical approach to account for clouds lying outside the CALIOP track even when MODIS cannot as reliably detect low clouds, for example at night or over ice. Finally, the paper finds that, because of variations in cloud amount and type, the typical distance to clouds in maritime clear areas varies with season and location. The overall median distance to clouds in maritime clear areas around 4-5 km. The fact that half of all clear areas is closer than 5 km to clouds implies that pronounced near-cloud changes in aerosol properties have significant implications for overall clear-sky characteristics, including the radiative impact of aerosols.

Material optimization of multi-layered enhanced nanostructures

NASA Astrophysics Data System (ADS)

Strobbia, Pietro

The employment of surface enhanced Raman scattering (SERS)-based sensing in real-world scenarios will offer numerous advantages over current optical sensors. Examples of these advantages are the intrinsic and simultaneous detection of multiple analytes, among many others. To achieve such a goal, SERS substrates with throughput and reproducibility comparable to commonly used fluorescence sensors have to be developed. To this end, our lab has discovered a multi-layer geometry, based on alternating films of a metal and a dielectric, that amplifies the SERS signal (multi-layer enhancement). The advantage of these multi-layered structures is to amplify the SERS signal exploiting layer-to-layer interactions in the volume of the structures, rather than on its surface. This strategy permits an amplification of the signal without modifying the surface characteristics of a substrate, and therefore conserving its reproducibility. Multi-layered structures can therefore be used to amplify the sensitivity and throughput of potentially any previously developed SERS sensor. In this thesis, these multi-layered structures were optimized and applied to different SERS substrates. The role of the dielectric spacer layer in the multi-layer enhancement was elucidated by fabricating spacers with different characteristics and studying their effect on the overall enhancement. Thickness, surface coverage and physical properties of the spacer were studied. Additionally, the multi-layered structures were applied to commercial SERS substrates and to isolated SERS probes. Studies on the dependence of the multi-layer enhancement on the thickness of the spacer demonstrated that the enhancement increases as a function of surface coverage at sub-monolayer thicknesses, due to the increasing multi-layer nature of the substrates. For fully coalescent spacers the enhancement decreases as a function of thickness, due to the loss of interaction between proximal metallic films. The influence of the physical properties of the spacer on the multi-layer enhancement were also studied. The trends in Schottky barrier height, interfacial potential and dielectric constant were isolated by using different materials as spacers (i.e., TiO2, HfO2, Ag 2O and Al2O3). The results show that the bulk dielectric constant of the material can be used to predict the relative magnitude of the multi-layer enhancement, with low dielectric constant materials performing more efficiently as spacers. Optimal spacer layers were found to be ultrathin coalescent films (ideally a monolayer) of low dielectric constant materials. Finally, multi-layered structures were observed to be employable to amplify SERS in drastically different substrate geometries. The multi-layered structures were applied to disposable commercial SERS substrates (i.e., Klarite). This project involved the regeneration of the used substrates, by stripping and redepositing the gold coating layer, and their amplification, by using the multi-layer geometry. The latter was observed to amplify the sensitivity of the substrates. Additionally, the multi-layered structures were applied to probes dispersed in solution. Such probes were observed to yield stronger SERS signal when optically trapped and to reduce the background signal. The application of the multi-layered structures on trapped probes, not only further amplified the SERS signal, but also increased the maximum number of applicable layers for the structures.

Properties of CIRRUS Overlapping Clouds as Deduced from the GOES-12 Imagery Data

NASA Technical Reports Server (NTRS)

Chang, Fu-Lung; Minnis, Patrick; Lin, Bing; Sun-Mack, Sunny; Khaiyer, Mandana

2006-01-01

Understanding the impact of cirrus clouds on modifying both the solar reflected and terrestrial emitted radiations is crucial for climate studies. Unlike most boundary layer stratus and stratocumulus clouds that have a net cooling effect on the climate, high-level thin cirrus clouds can have a warming effect on our climate. Many research efforts have been devoted to retrieving cirrus cloud properties due to their ubiquitous presence. However, using satellite observations to detect and/or retrieve cirrus cloud properties faces two major challenges. First, they are often semitransparent at visible to infrared wavelengths; and secondly, they often occur over a lower cloud system. The overlapping of high-level cirrus and low-level stratus cloud poses a difficulty in determining the individual cloud top altitudes and optical properties, especially when the signals from cirrus clouds are overwhelmed by the signals of stratus clouds. Moreover, the operational satellite retrieval algorithms, which often assume only single layer cloud in the development of cloud retrieval techniques, cannot resolve the cloud overlapping situation properly. The new geostationary satellites, starting with the Twelfth Geostationary Operational Environmental Satellite (GOES-12), are providing a new suite of imager bands that have replaced the conventional 12-micron channel with a 13.3-micron CO2 absorption channel. The replacement of the 13.3-micron channel allows for the application of a CO2-slicing retrieval technique (Chahine et al. 1974; Smith and Platt 1978), which is one of the important passive satellite methods for remote sensing the altitudes of mid to high-level clouds. Using the CO2- slicing technique is more effective in detecting semitransparent cirrus clouds than using the conventional infrared-window method.

Examining the Impact of Overlying Aerosols on the Retrieval of Cloud Optical Properties from Passive Remote Sensing

NASA Technical Reports Server (NTRS)

Coddington, O. M.; Pilewskie, P.; Redemann, J.; Platnick, S.; Russell, P. B.; Schmidt, K. S.; Gore, W. J.; Livingston, J.; Wind, G.; Vukicevic, T.

2010-01-01

Haywood et al. (2004) show that an aerosol layer above a cloud can cause a bias in the retrieved cloud optical thickness and effective radius. Monitoring for this potential bias is difficult because space ]based passive remote sensing cannot unambiguously detect or characterize aerosol above cloud. We show that cloud retrievals from aircraft measurements above cloud and below an overlying aerosol layer are a means to test this bias. The data were collected during the Intercontinental Chemical Transport Experiment (INTEX-A) study based out of Portsmouth, New Hampshire, United States, above extensive, marine stratus cloud banks affected by industrial outflow. Solar Spectral Flux Radiometer (SSFR) irradiance measurements taken along a lower level flight leg above cloud and below aerosol were unaffected by the overlying aerosol. Along upper level flight legs, the irradiance reflected from cloud top was transmitted through an aerosol layer. We compare SSFR cloud retrievals from below ]aerosol legs to satellite retrievals from the Moderate Resolution Imaging Spectroradiometer (MODIS) in order to detect an aerosol ]induced bias. In regions of small variation in cloud properties, we find that SSFR and MODIS-retrieved cloud optical thickness compares within the uncertainty range for each instrument while SSFR effective radius tend to be smaller than MODIS values (by 1-2 microns) and at the low end of MODIS uncertainty estimates. In regions of large variation in cloud properties, differences in SSFR and MODIS ]retrieved cloud optical thickness and effective radius can reach values of 10 and 10 microns, respectively. We include aerosols in forward modeling to test the sensitivity of SSFR cloud retrievals to overlying aerosol layers. We find an overlying absorbing aerosol layer biases SSFR cloud retrievals to smaller effective radii and optical thickness while nonabsorbing aerosols had no impact.

Safety by design of printed multilayer materials intended for food packaging.

PubMed

Domeño, Celia; Aznar, Margarita; Nerín, Cristina; Isella, Francesca; Fedeli, Mauro; Bosetti, Osvaldo

2017-07-01

Printing inks are commonly used in multilayer plastics materials used for food packaging, and compounds present in inks can migrate to the food either by diffusion through the multilayers or because of set-off phenomena. To avoid this problem, the right design of the packaging is crucial. This paper studies the safety by design of multilayer materials. First, the migration from four different multilayers manufactured using polyethylene terephthalate (PET), aluminium (Al) and polyethylene (PE) was determined. The structural differences among materials such as the presence of inks or lacquer coatings as well as the differences in layers position allowed the study of a safety-by-design approach. Sixty-nine different compounds were detected and identified; 49 of them were not included in the positive list of Regulation EU/10/2011 or in Swiss legislation and 15 belong to Cramer class III, which means that they have a theoretical high toxicity. Some of the compounds related to ink composition were pyrene, a compound commercially used to make dyes and dye precursors and the antioxidant Irganox 1300. The application of external lacquers decreased the concentration of some migrants but also brought the potential for new migrants coming from its composition. A final risk assessment of the material allowed evaluating food safety for different food simulants and confirm it.

Clouds over the summertime Sahara: an evaluation of Met Office retrievals from Meteosat Second Generation using airborne remote sensing

NASA Astrophysics Data System (ADS)

Kealy, John C.; Marenco, Franco; Marsham, John H.; Garcia-Carreras, Luis; Francis, Pete N.; Cooke, Michael C.; Hocking, James

2017-05-01

Novel methods of cloud detection are applied to airborne remote sensing observations from the unique Fennec aircraft dataset, to evaluate the Met Office-derived products on cloud properties over the Sahara based on the Spinning Enhanced Visible and InfraRed Imager (SEVIRI) on-board the Meteosat Second Generation (MSG) satellite. Two cloud mask configurations are considered, as well as the retrievals of cloud-top height (CTH), and these products are compared to airborne cloud remote sensing products acquired during the Fennec campaign in June 2011 and June 2012. Most detected clouds (67 % of the total) have a horizontal extent that is smaller than a SEVIRI pixel (3 km × 3 km). We show that, when partially cloud-contaminated pixels are included, a match between the SEVIRI and aircraft datasets is found in 80 ± 8 % of the pixels. Moreover, under clear skies the datasets are shown to agree for more than 90 % of the pixels. The mean cloud field, derived from the satellite cloud mask acquired during the Fennec flights, shows that areas of high surface albedo and orography are preferred sites for Saharan cloud cover, consistent with published theories. Cloud-top height retrievals however show large discrepancies over the region, which are ascribed to limiting factors such as the cloud horizontal extent, the derived effective cloud amount, and the absorption by mineral dust. The results of the CTH analysis presented here may also have further-reaching implications for the techniques employed by other satellite applications facilities across the world.

Strategies for cloud-top phase determination: differentiation between thin cirrus clouds and snow in manual (ground truth) analyses

NASA Astrophysics Data System (ADS)

Hutchison, Keith D.; Etherton, Brian J.; Topping, Phillip C.

1996-12-01

Quantitative assessments on the performance of automated cloud analysis algorithms require the creation of highly accurate, manual cloud, no cloud (CNC) images from multispectral meteorological satellite data. In general, the methodology to create ground truth analyses for the evaluation of cloud detection algorithms is relatively straightforward. However, when focus shifts toward quantifying the performance of automated cloud classification algorithms, the task of creating ground truth images becomes much more complicated since these CNC analyses must differentiate between water and ice cloud tops while ensuring that inaccuracies in automated cloud detection are not propagated into the results of the cloud classification algorithm. The process of creating these ground truth CNC analyses may become particularly difficult when little or no spectral signature is evident between a cloud and its background, as appears to be the case when thin cirrus is present over snow-covered surfaces. In this paper, procedures are described that enhance the researcher's ability to manually interpret and differentiate between thin cirrus clouds and snow-covered surfaces in daytime AVHRR imagery. The methodology uses data in up to six AVHRR spectral bands, including an additional band derived from the daytime 3.7 micron channel, which has proven invaluable for the manual discrimination between thin cirrus clouds and snow. It is concluded that while the 1.6 micron channel remains essential to differentiate between thin ice clouds and snow. However, this capability that may be lost if the 3.7 micron data switches to a nighttime-only transmission with the launch of future NOAA satellites.

Q-factor control of multilayer micromembrane using PZT composite material

NASA Astrophysics Data System (ADS)

Čekas, Elingas; Janušas, Giedrius; Palevicius, Arvydas; Janušas, Tomas; Ciganas, Justas

2018-02-01

Cantilever and membrane based sensors, which are capable of providing accurate detection of target analytes have been always an important research topic of medical diagnostics, food testing, and environmental monitoring fields. Here, the mechanical detection is achieved by micro- and nano-scale cantilevers for stress sensing and mass sensing, or micro- and nano-scale plates or membranes. High sensitivity is a major issue for the active element and it could be achieved via increased Q-factor. The ability to control the Q factor expands the range of application of the device and allows to achieve more accurate results. The aim of this paper is to investigate the mechanical and electrical properties, as well as, the ability to control the Q factor of the membrane with PZT nanocomposite. This multilayered membrane was formatted using the n-type <100> silicon substrate by implementing the Low Pressure Chemical Vapor Deposition (LPCVD), photolithography by using photomask with defined dimensions, deep etching, and e-beam evaporation techniques. Dynamic and electrical characteristics of the membrane were numerically investigated using COMSOL Multiphysics software. The use of the multilayered membrane can range from simple monitoring of particles concentration in a closed environment to inspecting glucose levels in human fluids (blood, tears, sweat, etc.).

Community detection, link prediction, and layer interdependence in multilayer networks.

PubMed

De Bacco, Caterina; Power, Eleanor A; Larremore, Daniel B; Moore, Cristopher

2017-04-01

Complex systems are often characterized by distinct types of interactions between the same entities. These can be described as a multilayer network where each layer represents one type of interaction. These layers may be interdependent in complicated ways, revealing different kinds of structure in the network. In this work we present a generative model, and an efficient expectation-maximization algorithm, which allows us to perform inference tasks such as community detection and link prediction in this setting. Our model assumes overlapping communities that are common between the layers, while allowing these communities to affect each layer in a different way, including arbitrary mixtures of assortative, disassortative, or directed structure. It also gives us a mathematically principled way to define the interdependence between layers, by measuring how much information about one layer helps us predict links in another layer. In particular, this allows us to bundle layers together to compress redundant information and identify small groups of layers which suffice to predict the remaining layers accurately. We illustrate these findings by analyzing synthetic data and two real multilayer networks, one representing social support relationships among villagers in South India and the other representing shared genetic substring material between genes of the malaria parasite.

Community detection, link prediction, and layer interdependence in multilayer networks

NASA Astrophysics Data System (ADS)

De Bacco, Caterina; Power, Eleanor A.; Larremore, Daniel B.; Moore, Cristopher

2017-04-01

Complex systems are often characterized by distinct types of interactions between the same entities. These can be described as a multilayer network where each layer represents one type of interaction. These layers may be interdependent in complicated ways, revealing different kinds of structure in the network. In this work we present a generative model, and an efficient expectation-maximization algorithm, which allows us to perform inference tasks such as community detection and link prediction in this setting. Our model assumes overlapping communities that are common between the layers, while allowing these communities to affect each layer in a different way, including arbitrary mixtures of assortative, disassortative, or directed structure. It also gives us a mathematically principled way to define the interdependence between layers, by measuring how much information about one layer helps us predict links in another layer. In particular, this allows us to bundle layers together to compress redundant information and identify small groups of layers which suffice to predict the remaining layers accurately. We illustrate these findings by analyzing synthetic data and two real multilayer networks, one representing social support relationships among villagers in South India and the other representing shared genetic substring material between genes of the malaria parasite.

Self-Similar Spin Images for Point Cloud Matching

NASA Astrophysics Data System (ADS)

Pulido, Daniel

The rapid growth of Light Detection And Ranging (Lidar) technologies that collect, process, and disseminate 3D point clouds have allowed for increasingly accurate spatial modeling and analysis of the real world. Lidar sensors can generate massive 3D point clouds of a collection area that provide highly detailed spatial and radiometric information. However, a Lidar collection can be expensive and time consuming. Simultaneously, the growth of crowdsourced Web 2.0 data (e.g., Flickr, OpenStreetMap) have provided researchers with a wealth of freely available data sources that cover a variety of geographic areas. Crowdsourced data can be of varying quality and density. In addition, since it is typically not collected as part of a dedicated experiment but rather volunteered, when and where the data is collected is arbitrary. The integration of these two sources of geoinformation can provide researchers the ability to generate products and derive intelligence that mitigate their respective disadvantages and combine their advantages. Therefore, this research will address the problem of fusing two point clouds from potentially different sources. Specifically, we will consider two problems: scale matching and feature matching. Scale matching consists of computing feature metrics of each point cloud and analyzing their distributions to determine scale differences. Feature matching consists of defining local descriptors that are invariant to common dataset distortions (e.g., rotation and translation). Additionally, after matching the point clouds they can be registered and processed further (e.g., change detection). The objective of this research is to develop novel methods to fuse and enhance two point clouds from potentially disparate sources (e.g., Lidar and crowdsourced Web 2.0 datasets). The scope of this research is to investigate both scale and feature matching between two point clouds. The specific focus of this research will be in developing a novel local descriptor based on the concept of self-similarity to aid in the scale and feature matching steps. An open problem in fusion is how best to extract features from two point clouds and then perform feature-based matching. The proposed approach for this matching step is the use of local self-similarity as an invariant measure to match features. In particular, the proposed approach is to combine the concept of local self-similarity with a well-known feature descriptor, Spin Images, and thereby define "Self-Similar Spin Images". This approach is then extended to the case of matching two points clouds in very different coordinate systems (e.g., a geo-referenced Lidar point cloud and stereo-image derived point cloud without geo-referencing). The use of Self-Similar Spin Images is again applied to address this problem by introducing a "Self-Similar Keyscale" that matches the spatial scales of two point clouds. Another open problem is how best to detect changes in content between two point clouds. A method is proposed to find changes between two point clouds by analyzing the order statistics of the nearest neighbors between the two clouds, and thereby define the "Nearest Neighbor Order Statistic" method. Note that the well-known Hausdorff distance is a special case as being just the maximum order statistic. Therefore, by studying the entire histogram of these nearest neighbors it is expected to yield a more robust method to detect points that are present in one cloud but not the other. This approach is applied at multiple resolutions. Therefore, changes detected at the coarsest level will yield large missing targets and at finer levels will yield smaller targets.

Comparison of MISR and Meteosat-9 cloud-motion vectors

NASA Astrophysics Data System (ADS)

Lonitz, Katrin; HorváTh, ÁKos

2011-12-01

Stereo motion vectors (SMVs) from the Multiangle Imaging SpectroRadiometer (MISR) were evaluated against Meteosat-9 cloud-motion vectors (CMVs) over a one-year period. In general, SMVs had weaker westerlies and southerlies than CMVs at all latitudes and levels. The E-W wind comparison showed small vertical variations with a mean difference of -0.4 m s-1, -1 m s-1, -0.7 m s-1 and corresponding rmsd of 2.4 m s-1, 3.8 m s-1, 3.5 m s-1for low-, mid-, and high-level clouds, respectively. The N-S wind discrepancies were larger and steadily increased with altitude, having a mean difference of -0.8 m s-1, -2.9 m s-1, -4.4 m s-1 and rmsd of 3.5 m s-1, 6.9 m s-1, 9.5 m s-1at low, mid, and high levels. The best overall agreement was found in marine stratocumulus off Namibia, while differences were larger in the Tropics and convective clouds. The SMVs were typically assigned to higher altitudes than CMVs. Attributing each observed height difference to MISR and/or Meteosat-9 retrieval biases will require further research; nevertheless, we already identified a few regions and cloud types where CMV height assignment seemed to be the one in error. In thin mid- and high-level clouds over Africa and Arabia as well as in broken marine boundary layer clouds the 10.8-μm brightness temperature-based heights were often biased low due to radiance contributions from the warm surface. Contrarily, low-level CMVs in the South Atlantic were frequently assigned to mid levels by the CO2-slicing method in multilayer situations. We also noticed an apparent cross-swath dependence in SMVs, whereby retrievals were less accurate on the eastern side of the MISR swath than on the western side. This artifact was traced back to sub-pixel MISR co-registration errors, which introduced cross-swath biases in E-W wind, N-S wind, and height of 0.6 m s-1, 2.6 m s-1, and 210 m.

Detection of carbon monoxide pollution from cities and wildfires on regional and urban scales: the benefit of CO column retrievals from SCIAMACHY 2.3 µm measurements under cloudy conditions

NASA Astrophysics Data System (ADS)

Borsdorff, Tobias; Andrasec, Josip; aan de Brugh, Joost; Hu, Haili; Aben, Ilse; Landgraf, Jochen

2018-05-01

In the perspective of the upcoming TROPOMI Sentinel-5 Precursor carbon monoxide data product, we discuss the benefit of using CO total column retrievals from cloud-contaminated SCIAMACHY 2.3 µm shortwave infrared spectra to detect atmospheric CO enhancements on regional and urban scales due to emissions from cities and wildfires. The study uses the operational Sentinel-5 Precursor algorithm SICOR, which infers the vertically integrated CO column together with effective cloud parameters. We investigate its capability to detect localized CO enhancements distinguishing between clear-sky observations and observations with low (< 1.5 km) and medium-high clouds (1.5-5 km). As an example, we analyse CO enhancements over the cities Paris, Los Angeles and Tehran as well as the wildfire events in Mexico-Guatemala 2005 and Alaska-Canada 2004. The CO average of the SCIAMACHY full-mission data set of clear-sky observations can detect weak CO enhancements of less than 10 ppb due to air pollution in these cities. For low-cloud conditions, the CO data product performs similarly well. For medium-high clouds, the observations show a reduced CO signal both over Tehran and Los Angeles, while for Paris no significant CO enhancement can be detected. This indicates that information about the vertical distribution of CO can be obtained from the SCIAMACHY measurements. Moreover, for the Mexico-Guatemala fires, the low-cloud CO data captures a strong outflow of CO over the Gulf of Mexico and the Pacific Ocean and so provides complementary information to clear-sky retrievals, which can only be obtained over land. For both burning events, enhanced CO values are even detectable with medium-high-cloud retrievals, confirming a distinct vertical extension of the pollution. The larger number of additional measurements, and hence the better spatial coverage, significantly improve the detection of wildfire pollution using both the clear-sky and cloudy CO retrievals. Due to the improved instrument performance of the TROPOMI instrument with respect to its precursor SCIAMACHY, the upcoming Sentinel-5 Precursor CO data product will allow improved detection of CO emissions and their vertical extension over cities and fires, making new research applications possible.

Remote focusing for programmable multi-layer differential multiphoton microscopy

PubMed Central

Hoover, Erich E.; Young, Michael D.; Chandler, Eric V.; Luo, Anding; Field, Jeffrey J.; Sheetz, Kraig E.; Sylvester, Anne W.; Squier, Jeff A.

2010-01-01

We present the application of remote focusing to multiphoton laser scanning microscopy and utilize this technology to demonstrate simultaneous, programmable multi-layer imaging. Remote focusing is used to independently control the axial location of multiple focal planes that can be simultaneously imaged with single element detection. This facilitates volumetric multiphoton imaging in scattering specimens and can be practically scaled to a large number of focal planes. Further, it is demonstrated that the remote focusing control can be synchronized with the lateral scan directions, enabling imaging in orthogonal scan planes. PMID:21326641

MC-GenomeKey: a multicloud system for the detection and annotation of genomic variants.

PubMed

Elshazly, Hatem; Souilmi, Yassine; Tonellato, Peter J; Wall, Dennis P; Abouelhoda, Mohamed

2017-01-20

Next Generation Genome sequencing techniques became affordable for massive sequencing efforts devoted to clinical characterization of human diseases. However, the cost of providing cloud-based data analysis of the mounting datasets remains a concerning bottleneck for providing cost-effective clinical services. To address this computational problem, it is important to optimize the variant analysis workflow and the used analysis tools to reduce the overall computational processing time, and concomitantly reduce the processing cost. Furthermore, it is important to capitalize on the use of the recent development in the cloud computing market, which have witnessed more providers competing in terms of products and prices. In this paper, we present a new package called MC-GenomeKey (Multi-Cloud GenomeKey) that efficiently executes the variant analysis workflow for detecting and annotating mutations using cloud resources from different commercial cloud providers. Our package supports Amazon, Google, and Azure clouds, as well as, any other cloud platform based on OpenStack. Our package allows different scenarios of execution with different levels of sophistication, up to the one where a workflow can be executed using a cluster whose nodes come from different clouds. MC-GenomeKey also supports scenarios to exploit the spot instance model of Amazon in combination with the use of other cloud platforms to provide significant cost reduction. To the best of our knowledge, this is the first solution that optimizes the execution of the workflow using computational resources from different cloud providers. MC-GenomeKey provides an efficient multicloud based solution to detect and annotate mutations. The package can run in different commercial cloud platforms, which enables the user to seize the best offers. The package also provides a reliable means to make use of the low-cost spot instance model of Amazon, as it provides an efficient solution to the sudden termination of spot machines as a result of a sudden price increase. The package has a web-interface and it is available for free for academic use.

Airborne lidar and radiometric observations of PBL- and low clouds

NASA Technical Reports Server (NTRS)

Flamant, P. H.; Valentin, R.; Pelon, J.

1992-01-01

Boundary layer- and low altitude clouds over open ocean and continent areas have been studied during several field campaigns since mid-1990 using the French airborne backscatter lidar LEANDRE in conjunction with on-board IR and visible radiometers. LEANDRE is an automatic system, and a modification of the instrumental parameters, when airborne, is computer controlled through an operator keyboard. The vertical range squared lidar signals and instrument status are displayed in real time on two dedicated monitors. The lidar is used either down- or up-looking while the aircraft is flying above or below clouds. A switching of the viewing configuration takes about a minute. The lidar measurements provide a high resolution description of cloud morphology and holes in cloud layers. The flights were conducted during various meteorological conditions on single or multilayer stratocumulus and cumulus decks. Analysis on a single shot basis of cloud top (or bottom) altitude and a plot of the corresponding histogram allows one to determine a probability density function (PDF). The preliminary results show the PDFs for cloud top are not Gaussian and symmetric about the mean value. The skewness varies with atmospheric conditions. An example of results recorded over the Atlantic ocean near Biarritz is displayed, showing: (1) the range squared lidar signals as a function of time (here 100 s corresponds to about 8 km, 60 shots are averaged on horizontal); the Planetary Boundary Layer (PBL) - up to 600 m - is observed at the beginning of the leg as well as on surface returns, giving an indication of the porosity; (2) the cloud top altitude variation between 2.4 to 2.8 km during the 150 to 320 s section; and (3) the corresponding PDF. Similar results are obtained on stratocumulus over land. Single shot measurements can be used also to determine an optical porosity at a small scale as well as a fractional cloudiness at a larger scale. A comparison of cloud top altitude retrieved from lidar and narrowbeam IR radiometer is conducted to study the scale integration problem. A good agreement within less than 100 m relies on spatial uniformity and an optically thick layer. In the presence of holes, a discrepancy is observed. This is illustrated in figure 2, displaying as a function of time (1) the lidar signals; (2) the target temperature (either clouds or sea surface) retreived from a narrowbeam IR radiometer, 17 C is the sea surface temperature on that day; and (3) the visible flux, linked to cloud albedo, measured by a pyranometer. In preparation of ASTEX, down- and up-looking measurements where conducted on stratocumulus clouds over the Atlantic Ocean near Quimper in Brittany. Depending on the flight pattern orientation with respect to the wind, the top and bottom cloud morphologies are different. Preliminary results are given on cloud morphology, cloud top PDFs, optical porosity, fractional cloudiness, and comparison of lidar and radiometric measurements.

Intelligent cloud computing security using genetic algorithm as a computational tools

NASA Astrophysics Data System (ADS)

Razuky AL-Shaikhly, Mazin H.

2018-05-01

An essential change had occurred in the field of Information Technology which represented with cloud computing, cloud giving virtual assets by means of web yet awesome difficulties in the field of information security and security assurance. Currently main problem with cloud computing is how to improve privacy and security for cloud “cloud is critical security”. This paper attempts to solve cloud security by using intelligent system with genetic algorithm as wall to provide cloud data secure, all services provided by cloud must detect who receive and register it to create list of users (trusted or un-trusted) depend on behavior. The execution of present proposal has shown great outcome.

Computational Modeling of Bloch Surface Waves in One-Dimensional Periodic and Aperiodic Multilayer Structures

NASA Astrophysics Data System (ADS)

Koju, Vijay

Photonic crystals and their use in exciting Bloch surface waves have received immense attention over the past few decades. This interest is mainly due to their applications in bio-sensing, wave-guiding, and other optical phenomena such as surface field enhanced Raman spectroscopy. Improvement in numerical modeling techniques, state of the art computing resources, and advances in fabrication techniques have also assisted in growing interest in this field. The ability to model photonic crystals computationally has benefited both the theoretical as well as experimental communities. It helps the theoretical physicists in solving complex problems which cannot be solved analytically and helps to acquire useful insights that cannot be obtained otherwise. Experimentalists, on the other hand, can test different variants of their devices by changing device parameters to optimize performance before fabrication. In this dissertation, we develop two commonly used numerical techniques, namely transfer matrix method, and rigorous coupled wave analysis, in C++ and MATLAB, and use two additional software packages, one open-source and another commercial, to model one-dimensional photonic crystals. Different variants of one-dimensional multilayered structures such as perfectly periodic dielectric multilayers, quasicrystals, aperiodic multilayer are modeled, along with one-dimensional photonic crystals with gratings on the top layer. Applications of Bloch surface waves, along with new and novel aperiodic dielectric multilayer structures that support Bloch surface waves are explored in this dissertation. We demonstrate a slow light configuration that makes use of Bloch Surface Waves as an intermediate excitation in a double-prism tunneling configuration. This method is simple compared to the more usual techniques for slowing light using the phenomenon of electromagnetically induced transparency in atomic gases or doped ionic crystals operated at temperatures below 4K. Using a semi-numerical approach, we show that a 1D photonic crystal, a multilayer structure composed of alternating layers of TiO2 and SiO2 , can be used to slow down light by a factor of up to 400. The results also show that better control of the speed of light can be achieved by changing the number of bilayers and the air-gap thickness appropriately. The existence of Bloch surface waves in periodic dielectric multilayer structures with a surface defect is well-known. Not yet recognized is that quasi-crystals and aperiodic dielectric multilayers can also support Bloch-like surface waves. We numerically show the excitation of Bloch-like surface waves in Fibonacci quasi-crystals, Thue-Morse aperiodic dielectric multilayers using the prism coupling method. We report improved surface electric field intensity and penetration depth of Bloch-like surface waves in the air side in such structures compared to their periodic counterparts. Bloch surface waves have also demonstrated significant potential in the field of bios-ensing technology. We further extend our study into a new type of multilayer structure based on Maximal-length sequence, which is a pseudo random sequence. We study the characteristics of Bloch surface waves in a 32 layered Maximal-length sequence multilayer and perform angular, as well as spectral sensitivity analysis for refractive index change detection. We demonstrate numerically that Maximal-length sequence multilayers significantly enhance the sensitivity of Bloch surface waves. Another type of structure that support Bloch surface waves are dielectric multilayer structures with a grating profile on the top-most layer. The grating profile adds an additional degree of freedom to the phase matching conditions for Bloch surface wave excitation. In such structures, the conditions for Bloch surface wave coupling can also be achieved by rotating both polar and azimuthal angles. The generation of Bloch surface waves as a function of azimuthal angle have similar characteristics to conventional grating coupled Bloch surface waves. However, azimuthal generated Bloch surface waves have enhanced angular sensitivity compared to conventional polar angle coupled modes, which makes them appropriate for detecting tiny variations in surface refractive index due to the addition of nano-particles such as protein molecules.

Lidar Cloud Detection with Fully Convolutional Networks

NASA Astrophysics Data System (ADS)

Cromwell, E.; Flynn, D.

2017-12-01

The vertical distribution of clouds from active remote sensing instrumentation is a widely used data product from global atmospheric measuring sites. The presence of clouds can be expressed as a binary cloud mask and is a primary input for climate modeling efforts and cloud formation studies. Current cloud detection algorithms producing these masks do not accurately identify the cloud boundaries and tend to oversample or over-represent the cloud. This translates as uncertainty for assessing the radiative impact of clouds and tracking changes in cloud climatologies. The Atmospheric Radiation Measurement (ARM) program has over 20 years of micro-pulse lidar (MPL) and High Spectral Resolution Lidar (HSRL) instrument data and companion automated cloud mask product at the mid-latitude Southern Great Plains (SGP) and the polar North Slope of Alaska (NSA) atmospheric observatory. Using this data, we train a fully convolutional network (FCN) with semi-supervised learning to segment lidar imagery into geometric time-height cloud locations for the SGP site and MPL instrument. We then use transfer learning to train a FCN for (1) the MPL instrument at the NSA site and (2) for the HSRL. In our semi-supervised approach, we pre-train the classification layers of the FCN with weakly labeled lidar data. Then, we facilitate end-to-end unsupervised pre-training and transition to fully supervised learning with ground truth labeled data. Our goal is to improve the cloud mask accuracy and precision for the MPL instrument to 95% and 80%, respectively, compared to the current cloud mask algorithms of 89% and 50%. For the transfer learning based FCN for the HSRL instrument, our goal is to achieve a cloud mask accuracy of 90% and a precision of 80%.

Guided wave energy trapping to detect hidden multilayer delamination damage

NASA Astrophysics Data System (ADS)

Leckey, Cara A. C.; Seebo, Jeffrey P.

2015-03-01

Nondestructive Evaluation (NDE) and Structural Health Monitoring (SHM) simulation tools capable of modeling three-dimensional (3D) realistic energy-damage interactions are needed for aerospace composites. Current practice in NDE/SHM simulation for composites commonly involves over-simplification of the material parameters and/or a simplified two-dimensional (2D) approach. The unique damage types that occur in composite materials (delamination, microcracking, etc) develop as complex 3D geometry features. This paper discusses the application of 3D custom ultrasonic simulation tools to study wave interaction with multilayer delamination damage in carbon-fiber reinforced polymer (CFRP) composites. In particular, simulation based studies of ultrasonic guided wave energy trapping due to multilayer delamination damage were performed. The simulation results show changes in energy trapping at the composite surface as additional delaminations are added through the composite thickness. The results demonstrate a potential approach for identifying the presence of hidden multilayer delamination damage in applications where only single-sided access to a component is available. The paper also describes recent advancements in optimizing the custom ultrasonic simulation code for increases in computation speed.

Nanointaglio fabrication of optical lipid multilayer diffraction gratings with applications in biosensing

NASA Astrophysics Data System (ADS)

Lowry, Troy Warren

The dynamic self-organization of lipids in biological systems is a highly regulated process that enables the compartmentalization of living systems at microscopic and nanoscopic levels. Exploiting the self-organization and innate biofunctionality of lyotropic liquid crystalline phospholipids, a novel nanofabrication process called "nanointaglio" was invented in order to rapidly and scalably integrate lipid nanopatterns onto the surface. The work presented here focuses on using nanointaglio fabricated lipid diffraction micro- and nanopatterns for the development of new sensing and bioactivity studies. The lipids are patterned as diffraction gratings for sensor functionality. The lipid multilayer gratings operate as nanomechanical sensor elements that are capable of transducing molecular binding to fluid lipid multilayers into optical signals in a label free manner due to shape changes in the lipid nanostructures. To demonstrate the label free detection capabilities, lipid nanopatterns are shown to be suitable for the integration of chemically different lipid multilayer gratings into a sensor array capable of distinguishing vapors by means of an optical nose. Sensor arrays composed of six different lipid formulations are integrated onto a surface and their optical response to three different vapors (water, ethanol and acetone) in air as well as pH under water is monitored as a function of time. Principal component analysis of the array response results in distinct clustering, indicating the suitability of the arrays for distinguishing these analytes. Importantly, the nanointaglio process used is capable of producing lipid gratings out of different materials with sufficiently uniform heights for the fabrication of an optical nose. A second main application is demonstrated for the study of membrane binding proteins. Although in vitro methods for assaying the catalytic activity of individual enzymes are well established, quantitative methods for assaying the kinetics of supramolecular remodeling such as vesicle formation from planar lipid bilayers or multilayers are needed to understand cellular self-organization. Presented next is a nanointaglio based method for quantitative measurements of lipid-protein interactions and its suitability for quantifying the membrane binding, inflation, and budding activity of the membrane-remodeling protein Sar1. Optical diffraction gratings composed of lipids are printed on surfaces using nanointaglio, resulting in lipid multilayer gratings. Exposure of lipid multilayer gratings to Sar1 results in the inflation of lipid multilayers into unilamellar structures, the kinetics of which can be detected in a label-free manner by monitoring the diffraction of white light through an optical microscope. Local variations in lipid multilayer volume on the surface can be used to vary substrate availability in a microarray format, allowing kinetic and thermodynamic data to be obtained from a single experiment without the need for varying enzyme concentration. A quantitative model is developed and fits to the data allow measurements of both binding affinity (KD) and kinetics (kon and koff). Importantly, this assay is uniquely capable of quantifying membrane remodeling. Upon Sar1 induced inflation of single bilayers from surface supported multilayers, the semi-cylindrical grating lines are observed to remodel into semi-spherical buds when a critical radius of curvature equal to 300 nm is reached, which is explained in terms of a Rayleigh type instability.

Discrimination of Biomass Burning Smoke and Clouds in MAIAC Algorithm

NASA Technical Reports Server (NTRS)

Lyapustin, A.; Korkin, S.; Wang, Y.; Quayle, B.; Laszlo, I.

2012-01-01

The multi-angle implementation of atmospheric correction (MAIAC) algorithm makes aerosol retrievals from MODIS data at 1 km resolution providing information about the fine scale aerosol variability. This information is required in different applications such as urban air quality analysis, aerosol source identification etc. The quality of high resolution aerosol data is directly linked to the quality of cloud mask, in particular detection of small (sub-pixel) and low clouds. This work continues research in this direction, describing a technique to detect small clouds and introducing the smoke test to discriminate the biomass burning smoke from the clouds. The smoke test relies on a relative increase of aerosol absorption at MODIS wavelength 0.412 micrometers as compared to 0.47-0.67 micrometers due to multiple scattering and enhanced absorption by organic carbon released during combustion. This general principle has been successfully used in the OMI detection of absorbing aerosols based on UV measurements. This paper provides the algorithm detail and illustrates its performance on two examples of wildfires in US Pacific North-West and in Georgia/Florida of 2007.

Enhanced thermo-spin effects in iron-oxide/metal multilayers

NASA Astrophysics Data System (ADS)

Ramos, R.; Lucas, I.; Algarabel, P. A.; Morellón, L.; Uchida, K.; Saitoh, E.; Ibarra, M. R.

2018-06-01

Since the discovery of the spin Seebeck effect (SSE), much attention has been devoted to the study of the interaction between heat, spin, and charge in magnetic systems. The SSE refers to the generation of a spin current upon the application of a thermal gradient and detected by means of the inverse spin Hall effect. Conversely, the spin Peltier effect (SPE) refers to the generation of a heat current as a result of a spin current induced by the spin Hall effect. Here we report a strong enhancement of both the SSE and SPE in Fe3O4/Pt multilayered thin films at room temperature as a result of an increased thermo-spin conversion efficiency in the multilayers. These results open the possibility to design thin film heterostructures that may boost the application of thermal spin currents in spintronics.

O2 A Band Studies for Cloud Detection and Algorithm Improvement

NASA Technical Reports Server (NTRS)

Chance, K. V.

1996-01-01

Detection of cloud parameters from space-based spectrometers can employ the vibrational bands of O2 in the (sup b1)Sigma(sub +)(sub g) yields X(sub 3) Sigma(sup -)(sub g) spin-forbidden electronic transition manifold, particularly the Delta nu = 0 A band. The GOME instrument uses the A band in the Initial Cloud Fitting Algorithm (ICFA). The work reported here consists of making substantial improvements in the line-by-line spectral database for the A band, testing whether an additional correction to the line shape function is necessary in order to correctly model the atmospheric transmission in this band, and calculating prototype cloud and ground template spectra for comparison with satellite measurements.

Discovery of a Bright Equatorial Storm on Neptune

NASA Astrophysics Data System (ADS)

Molter, E. M.; De Pater, I.; Alvarez, C.; Tollefson, J.; Luszcz-Cook, S.

2017-12-01

Images of Neptune, taken with the NIRC2 instrument during testing of the new Twilight Zone observing program at Keck Observatory, revealed an extremely large bright storm system near Neptune's equator. The storm complex is ≈9,000 km across and brightened considerably between June 26 and July 2. Historically, very bright clouds have occasionally been seen on Neptune, but always in the midlatitude regions between ≈15° and ≈60° North or South. Voyager and HST observations have shown that cloud features large enough to dominate near-IR photometry are often "companion" clouds of dark anti-cyclonic vortices similar to Jupiter's Great Red Spot, interpreted as orographic clouds. In the past such clouds and their coincident dark vortices often persisted for one up to several years. However, the cloud complex we detect is unique: never before has a bright cloud been seen at, or so close to, the equator. The discovery points to a drastic departure in the dynamics of Neptune's atmosphere from what has been observed for the past several decades. Detections of the complex in multiple NIRC2 filters allows radiative transfer modeling to constrain the cloud's altitude and vertical extent.

Aviation response to a widely dispersed volcanic ash and gas cloud from the August 2008 eruption of Kasatochi, Alaska, USA

USGS Publications Warehouse

Guffanti, Marianne; Schneider, David J.; Wallace, Kristi L.; Hall, Tony; Bensimon, Dov R.; Salinas, Leonard J.

2010-01-01

The extensive volcanic cloud from Kasatochi's 2008 eruption caused widespread disruptions to aviation operations along Pacific oceanic, Canadian, and U.S. air routes. Based on aviation hazard warnings issued by the National Oceanic and Atmospheric Administration, U.S. Geological Survey, the Federal Aviation Administration, and Meteorological Service of Canada, air carriers largely avoided the volcanic cloud over a 5 day period by route modifications and flight cancellations. Comparison of time coincident GOES thermal infrared (TIR) data for ash detection with Ozone Monitoring Instrument (OMI) ultraviolet data for SO2 detection shows congruent areas of ash and gas in the volcanic cloud in the 2 days following onset of ash production. After about 2.5 days, the area of SO2 detected by OMI was more extensive than the area of ash indicated by TIR data, indicating significant ash depletion by fall out had occurred. Pilot reports of visible haze at cruise altitudes over Canada and the northern United States suggested that SO2 gas had converted to sulfate aerosols. Uncertain about the hazard potential of the aging cloud, airlines coped by flying over, under, or around the observed haze layer. Samples from a nondamaging aircraft encounter with Kasatochi's nearly 3 day old cloud contained volcanic silicate particles, confirming that some fine ash is present in predominantly gas clouds. The aircraft's exposure to ash was insufficient to cause engine damage; however, slightly damaging encounters with volcanic clouds from eruptions of Reventador in 2002 and Hekla in 2000 indicate the possibility of lingering hazards associated with old and/or diffuse volcanic clouds.

Cloud Detection with the Earth Polychromatic Imaging Camera (EPIC)

NASA Technical Reports Server (NTRS)

Meyer, Kerry; Marshak, Alexander; Lyapustin, Alexei; Torres, Omar; Wang, Yugie

2011-01-01

The Earth Polychromatic Imaging Camera (EPIC) on board the Deep Space Climate Observatory (DSCOVR) would provide a unique opportunity for Earth and atmospheric research due not only to its Lagrange point sun-synchronous orbit, but also to the potential for synergistic use of spectral channels in both the UV and visible spectrum. As a prerequisite for most applications, the ability to detect the presence of clouds in a given field of view, known as cloud masking, is of utmost importance. It serves to determine both the potential for cloud contamination in clear-sky applications (e.g., land surface products and aerosol retrievals) and clear-sky contamination in cloud applications (e.g., cloud height and property retrievals). To this end, a preliminary cloud mask algorithm has been developed for EPIC that applies thresholds to reflected UV and visible radiances, as well as to reflected radiance ratios. This algorithm has been tested with simulated EPIC radiances over both land and ocean scenes, with satisfactory results. These test results, as well as algorithm sensitivity to potential instrument uncertainties, will be presented.

Simulations of the observation of clouds and aerosols with the Experimental Lidar in Space Equipment system.

PubMed

Liu, Z; Voelger, P; Sugimoto, N

2000-06-20

We carried out a simulation study for the observation of clouds and aerosols with the Japanese Experimental Lidar in Space Equipment (ELISE), which is a two-wavelength backscatter lidar with three detection channels. The National Space Development Agency of Japan plans to launch the ELISE on the Mission Demonstrate Satellite 2 (MDS-2). In the simulations, the lidar return signals for the ELISE are calculated for an artificial, two-dimensional atmospheric model including different types of clouds and aerosols. The signal detection processes are simulated realistically by inclusion of various sources of noise. The lidar signals that are generated are then used as input for simulations of data analysis with inversion algorithms to investigate retrieval of the optical properties of clouds and aerosols. The results demonstrate that the ELISE can provide global data on the structures and optical properties of clouds and aerosols. We also conducted an analysis of the effects of cloud inhomogeneity on retrievals from averaged lidar profiles. We show that the effects are significant for space lidar observations of optically thick broken clouds.

Snow precipitation on Mars driven by cloud-induced night-time convection

NASA Astrophysics Data System (ADS)

Spiga, Aymeric; Hinson, David P.; Madeleine, Jean-Baptiste; Navarro, Thomas; Millour, Ehouarn; Forget, François; Montmessin, Franck

2017-09-01

Although it contains less water vapour than Earth's atmosphere, the Martian atmosphere hosts clouds. These clouds, composed of water-ice particles, influence the global transport of water vapour and the seasonal variations of ice deposits. However, the influence of water-ice clouds on local weather is unclear: it is thought that Martian clouds are devoid of moist convective motions, and snow precipitation occurs only by the slow sedimentation of individual particles. Here we present numerical simulations of the meteorology in Martian cloudy regions that demonstrate that localized convective snowstorms can occur on Mars. We show that such snowstorms--or ice microbursts--can explain deep night-time mixing layers detected from orbit and precipitation signatures detected below water-ice clouds by the Phoenix lander. In our simulations, convective snowstorms occur only during the Martian night, and result from atmospheric instability due to radiative cooling of water-ice cloud particles. This triggers strong convective plumes within and below clouds, with fast snow precipitation resulting from the vigorous descending currents. Night-time convection in Martian water-ice clouds and the associated snow precipitation lead to transport of water both above and below the mixing layers, and thus would affect Mars' water cycle past and present, especially under the high-obliquity conditions associated with a more intense water cycle.

Improvements in AVHRR Daytime Cloud Detection Over the ARM NSA Site

NASA Technical Reports Server (NTRS)

Chakrapani, V.; Spangenberg, D. A.; Doelling, D. R.; Minnis, P.; Trepte, Q. Z.; Arduini, R. F.

2001-01-01

Clouds play an important role in the radiation budget over Arctic and Antarctic. Because of limited surface observing capabilities, it is necessary to detect clouds over large areas using satellite imagery. At low and mid-latitudes, satellite-observed visible (VIS; 0.65 micrometers) and infrared (IR; 11 micrometers) radiance data are used to derive cloud fraction, temperature, and optical depth. However, the extreme variability in the VIS surface albedo makes the detection of clouds from satellite a difficult process in polar regions. The IR data often show that the surface is nearly the same temperature or even colder than clouds, further complicating cloud detection. Also, the boundary layer can have large areas of haze, thin fog, or diamond dust that are not seen in standard satellite imagery. Other spectral radiances measured by satellite imagers provide additional information that can be used to more accurately discriminate clouds from snow and ice. Most techniques currently use a fixed reflectance or temperature threshold to decide between clouds and clear snow. Using a subjective approach, Minnis et al. (2001) found that the clear snow radiance signatures vary as a function of viewing and illumination conditions as well as snow condition. To routinely process satellite imagery over polar regions with an automated algorithm, it is necessary to account for this angular variability and the change in the background reflectance as snow melts, vegetation grows over land, and melt ponds form on pack ice. This paper documents the initial satellite-based cloud product over the Atmospheric Radiation Measurement (ARM) North Slope of Alaska (NSA) site at Barrow for use by the modeling community. Cloud amount and height are determined subjectively using an adaptation of the methodology of Minnis et al. (2001) and the radiation fields arc determined following the methods of Doelling et al. (2001) as applied to data taken during the Surface Heat and Energy Budget of the Arctic (SHEBA). The procedures and data produced in this empirically based analysis will also facilitate the development of the automated algorithm for future processing of satellite data over the ARM NSA domain. Results are presented for May, June, and July 1998. ARM surface data are use to partially validate the results taken directly over the ARM site.

Estimation of radiative forcing and chore length of shallow convective clouds (SCC) based on broadband pyranometer measurement network

NASA Astrophysics Data System (ADS)

Shi, H.

2017-12-01

We presented a method to identify and calculate cloud radiative forcing (CRF) and horizontal chore length (L) of shallow convective clouds (SCC) using a network of 9 broadband pyranometers. The analyzing data was collected from the SCC campaign during two years summers (2015 2016) at Baiqi site over Inner Mongolia grassland. The network of pyranometers was operated across a spatial domain covering 42.16-42.30° N and 114.83-114.98° E. The SCC detection method was verified by observer reports and cameras, which showed that the detection method and human observations were in agreement about 75 %. The differences between the SCC detection method and human observations can be responsible for following factors: 1) small or dissipating clouds can be neglected for the value of 1 min of temporal resolution of pyranometer; 2) human observation recorded weather conditions four times every day; 3) SCC was indistinguishable from coexistence of SCC and Cirrus (Ci); 4) the SCC detection method is weighted toward clouds crossing the sun's path, while the human observer can view clouds over the entire sky. The deviation of L can be attributed to two factors: 1) the accuracy of wind speed at height of SCC and the ratio of horizontal and vertical length play a key role in determine values of L; 2) the effect of variance of solar zenith angle can be negligible. The downwelling shortwave CRF of SCC was -134.1 Wm-2. The average value of L of SCC was 1129 m. Besides, the distribution of normalized cloud chore length agreed well with power-law fit.

Mesospheric CO2 ice clouds on Mars observed by Planetary Fourier Spectrometer onboard Mars Express

NASA Astrophysics Data System (ADS)

Aoki, S.; Sato, Y.; Giuranna, M.; Wolkenberg, P.; Sato, T. M.; Nakagawa, H.; Kasaba, Y.

2018-03-01

We have investigated mesospheric CO2 ice clouds on Mars through analysis of near-infrared spectra acquired by Planetary Fourier Spectrometer (PFS) onboard the Mars Express (MEx) from MY 27 to MY 32. With the highest spectral resolution achieved thus far in the relevant spectral range among remote-sensing experiments orbiting Mars, PFS enables precise identification of the scattering peak of CO2 ice at the bottom of the 4.3 μm CO2 band. A total of 111 occurrences of CO2 ice cloud features have been detected over the period investigated. Data from the OMEGA imaging spectrometer onboard MEx confirm all of PFS detections from times when OMEGA operated simultaneously with PFS. The spatial and seasonal distributions of the CO2 ice clouds detected by PFS are consistent with previous observations by other instruments. We find CO2 ice clouds between Ls = 0° and 140° in distinct longitudinal corridors around the equatorial region (± 20°N). Moreover, CO2 ice clouds were preferentially detected at the observational LT range between 15-16 h in MY 29. However, observational biases prevent from distinguishing local time dependency from inter-annual variation. PFS also enables us to investigate the shape of mesospheric CO2 ice cloud spectral features in detail. In all cases, peaks were found between 4.240 and 4.265 μm. Relatively small secondary peaks were occasionally observed around 4.28 μm (8 occurrences). These spectral features cannot be reproduced using our radiative transfer model, which may be because the available CO2 ice refractive indices are inappropriate for the mesospheric temperatures of Mars, or because of the assumption in our model that the CO2 ice crystals are spherical and composed by pure CO2 ice.

Point Source Polarimetry with the Gemini Planet Imager: Sensitivity Characterization with T5.5 Dwarf Companion HD 19467 B

NASA Technical Reports Server (NTRS)

Jensen-Clem, Rebecca; Millar-Blanchaer, Max; Mawet, Dimitri; Graham, James R.; Wallace, J. Kent; Macintosh, Bruce; Hinkley, Sasha; Wiktorowicz, Sloane J.; Perrin, Marshall D.; Marley, Mark S.;

Method and apparatus for measuring purity of noble gases

DOEpatents

Austin, Robert

2008-04-01

A device for detecting impurities in a noble gas includes a detection chamber and a source of pulsed ultraviolet light. The pulse of the ultraviolet light is transferred into the detection chamber and onto a photocathode, thereby emitting a cloud of free electrons into the noble gas within the detection chamber. The cloud of electrons is attracted to the opposite end of the detection chamber by a high positive voltage potential at that end and focused onto a sensing anode. If there are impurities in the noble gas, some or all of the electrons within the cloud will bond with the impurity molecules and not reach the sensing anode. Therefore, measuring a lower signal at the sensing anode indicates a higher level of impurities while sensing a higher signal indicates fewer impurities. Impurities in the range of one part per billion can be measured by this device.

Point source polarimetry with the Gemini planet imager: Sensitivity characterization with T5.5 dwarf companion HD 19467 B

DOE PAGES

Jensen-Clem, Rebecca; Millar-Blanchaer, Max; Mawet, Dimitri; ...

2016-03-29

Detecting polarized light from self-luminous exoplanets has the potential to provide key information about rotation, surface gravity, cloud grain size, and cloud coverage. While field brown dwarfs with detected polarized emission are common, no exoplanet or substellar companion has yet been detected in polarized light. With the advent of high contrast imaging spectro-polarimeters such as GPI and SPHERE, such a detection may now be possible with careful treatment of instrumental polarization. In this paper, we present 28 minutes of H-band GPI polarimetric observations of the benchmark T5.5 companion HD 19467 B. We detect no polarization signal from the target, and place an upper limit on the degree of linear polarization ofmore » $${p}_{\\mathrm{CL}99.73\\%}\\leqslant 2.4\\%$$. In conclusion, we discuss our results in the context of T dwarf cloud models and photometric variability.« less

A compressive sensing based secure watermark detection and privacy preserving storage framework.

PubMed

Qia Wang; Wenjun Zeng; Jun Tian

2014-03-01

Privacy is a critical issue when the data owners outsource data storage or processing to a third party computing service, such as the cloud. In this paper, we identify a cloud computing application scenario that requires simultaneously performing secure watermark detection and privacy preserving multimedia data storage. We then propose a compressive sensing (CS)-based framework using secure multiparty computation (MPC) protocols to address such a requirement. In our framework, the multimedia data and secret watermark pattern are presented to the cloud for secure watermark detection in a CS domain to protect the privacy. During CS transformation, the privacy of the CS matrix and the watermark pattern is protected by the MPC protocols under the semi-honest security model. We derive the expected watermark detection performance in the CS domain, given the target image, watermark pattern, and the size of the CS matrix (but without the CS matrix itself). The correctness of the derived performance has been validated by our experiments. Our theoretical analysis and experimental results show that secure watermark detection in the CS domain is feasible. Our framework can also be extended to other collaborative secure signal processing and data-mining applications in the cloud.

Advanced Multilayer Composite Heavy-Oxide Scintillator Detectors for High Efficiency Fast Neutron Detection

NASA Astrophysics Data System (ADS)

Ryzhikov, Vladimir D.; Naydenov, Sergei V.; Pochet, Thierry; Onyshchenko, Gennadiy M.; Piven, Leonid A.; Smith, Craig F.

2018-01-01

We have developed and evaluated a new approach to fast neutron and neutron-gamma detection based on large-area multilayer composite heterogeneous detection media consisting of dispersed granules of small-crystalline scintillators contained in a transparent organic (plastic) matrix. Layers of the composite material are alternated with layers of transparent plastic scintillator material serving as light guides. The resulting detection medium - designated as ZEBRA - serves as both an active neutron converter and a detection scintillator which is designed to detect both neutrons and gamma-quanta. The composite layers of the ZEBRA detector consist of small heavy-oxide scintillators in the form of granules of crystalline BGO, GSO, ZWO, PWO and other materials. We have produced and tested the ZEBRA detector of sizes 100x100x41 mm and greater, and determined that they have very high efficiency of fast neutron detection (up to 49% or greater), comparable to that which can be achieved by large sized heavy-oxide single crystals of about Ø40x80 cm3 volume. We have also studied the sensitivity variation to fast neutron detection by using different types of multilayer ZEBRA detectors of 100 cm2 surface area and 41 mm thickness (with a detector weight of about 1 kg) and found it to be comparable to the sensitivity of a 3He-detector representing a total cross-section of about 2000 cm2 (with a weight of detector, including its plastic moderator, of about 120 kg). The measured count rate in response to a fast neutron source of 252Cf at 2 m for the ZEBRA-GSO detector of size 100x100x41 mm3 was 2.84 cps/ng, and this count rate can be doubled by increasing the detector height (and area) up to 200x100 mm2. In summary, the ZEBRA detectors represent a new type of high efficiency and low cost solid-state neutron detector that can be used for stationary neutron/gamma portals. They may represent an interesting alternative to expensive, bulky gas counters based on 3He or 10B neutron detection technologies.

Measured electric field intensities near electric cloud discharges detected by the Kennedy Space Center's Lightning Detection and Ranging System, LDAR

NASA Technical Reports Server (NTRS)

Poehler, H. A.

1977-01-01

For a summer thunderstorm, for which simultaneous, airborne electric field measurements and Lightning Detection and Ranging (LDAR) System data was available, measurements were coordinated to present a picture of the electric field intensity near cloud electrical discharges detected by the LDAR System. Radar precipitation echos from NOAA's 10 cm weather radar and measured airborne electric field intensities were superimposed on LDAR PPI plots to present a coordinated data picture of thunderstorm activity.

Optical biosensors using surface plasmon resonance

NASA Astrophysics Data System (ADS)

Homola, Jiri; Brynda, Eduard; Tobiska, Petr; Tichy, Ivo; Skvor, Jiri

1999-12-01

We present a surface plasmon resonance sensor base on prism excitation of surface plasmons and spectral interrogation. For specific detection of biomolecular analytes, multilayers of monoclonal antibodies are immobilized on the surface of the sensor. Detection of biomolecular analytes such as human (beta) -2)-microglobulin, choriogonadotropin, hepatitis B surface antigen, salmonella enteritidis is demonstrated.

A target detection multi-layer matched filter for color and hyperspectral cameras

NASA Astrophysics Data System (ADS)

Miyanishi, Tomoya; Preece, Bradley L.; Reynolds, Joseph P.

2018-05-01

In this article, a method for applying matched filters to a 3-dimentional hyperspectral data cube is discussed. In many applications, color visible cameras or hyperspectral cameras are used for target detection where the color or spectral optical properties of the imaged materials are partially known in advance. Therefore, the use of matched filtering with spectral data along with shape data is an effective method for detecting certain targets. Since many methods for 2D image filtering have been researched, we propose a multi-layer filter where ordinary spatially matched filters are used before the spectral filters. We discuss a way to layer the spectral filters for a 3D hyperspectral data cube, accompanied by a detectability metric for calculating the SNR of the filter. This method is appropriate for visible color cameras and hyperspectral cameras. We also demonstrate an analysis using the Night Vision Integrated Performance Model (NV-IPM) and a Monte Carlo simulation in order to confirm the effectiveness of the filtering in providing a higher output SNR and a lower false alarm rate.

Multi-layer Clouds Over the South Indian Ocean

NASA Technical Reports Server (NTRS)

2003-01-01

The complex structure and beauty of polar clouds are highlighted by these images acquired by the Multi-angle Imaging SpectroRadiometer (MISR) on April 23, 2003. These clouds occur at multiple altitudes and exhibit a noticeable cyclonic circulation over the Southern Indian Ocean, to the north of Enderbyland, East Antarctica.

The image at left was created by overlying a natural-color view from MISR's downward-pointing (nadir) camera with a color-coded stereo height field. MISR retrieves heights by a pattern recognition algorithm that utilizes multiple view angles to derive cloud height and motion. The opacity of the height field was then reduced until the field appears as a translucent wash over the natural-color image. The resulting purple, cyan and green hues of this aesthetic display indicate low, medium or high altitudes, respectively, with heights ranging from less than 2 kilometers (purple) to about 8 kilometers (green). In the lower right corner, the edge of the Antarctic coastline and some sea ice can be seen through some thin, high cirrus clouds.

The right-hand panel is a natural-color image from MISR's 70-degree backward viewing camera. This camera looks backwards along the path of Terra's flight, and in the southern hemisphere the Sun is in front of this camera. This perspective causes the cloud-tops to be brightly outlined by the sun behind them, and enhances the shadows cast by clouds with significant vertical structure. An oblique observation angle also enhances the reflection of light by atmospheric particles, and accentuates the appearance of polar clouds. The dark ocean and sea ice that were apparent through the cirrus clouds at the bottom right corner of the nadir image are overwhelmed by the brightness of these clouds at the oblique view.

The Multi-angle Imaging SpectroRadiometer observes the daylit Earth continuously from pole to pole, and every 9 days views the entire globe between 82 degrees north and 82 degrees south latitude. These data products were generated from a portion of the imagery acquired during Terra orbit 17794. The panels cover an area of 335 kilometers x 605 kilometers, and utilize data from blocks 142 to 145 within World Reference System-2 path 155.

MISR was built and is managed by NASA's Jet Propulsion Laboratory, Pasadena, CA, for NASA's Office of Earth Science, Washington, DC. The Terra satellite is managed by NASA's Goddard Space Flight Center, Greenbelt, MD. JPL is a division of the California Institute of Technology.

A laboratory investigation of the reflective properties of simulated, optically thick clouds

NASA Technical Reports Server (NTRS)

Mckee, T. B.; Cox, S. K.

1982-01-01

The Cloud Field Optical Simulator project includes work in the following areas: (1) improvement in the shape of the desired (visible) spectral response of the measurement, (2) selection of two usable materials for cloud simulation, (3) a means of assigning a visible optical depth to the simulated clouds, and (4) confirmation that the apparatus is capable of detecting basic finite cloud characteristics. A brief description of the accomplishments in each of these areas is presented.

Validation of a radiosonde-based cloud layer detection method against a ground-based remote sensing method at multiple ARM sites

NASA Astrophysics Data System (ADS)

Zhang, Jinqiang; Li, Zhanqing; Chen, Hongbin; Cribb, Maureen

2013-01-01

Cloud vertical structure is a key quantity in meteorological and climate studies, but it is also among the most difficult quantities to observe. In this study, we develop a long-term (10 years) radiosonde-based cloud profile product for the U.S. Department of Energy's Atmospheric Radiation Measurement (ARM) program Southern Great Plains (SGP), Tropical Western Pacific (TWP), and North Slope of Alaska (NSA) sites and a shorter-term product for the ARM Mobile Facility (AMF) deployed in Shouxian, Anhui Province, China (AMF-China). The AMF-China site was in operation from 14 May to 28 December 2008; the ARM sites have been collecting data for over 15 years. The Active Remote Sensing of Cloud (ARSCL) value-added product (VAP), which combines data from the 95-GHz W-band ARM Cloud Radar (WACR) and/or the 35-GHz Millimeter Microwave Cloud Radar (MMCR), is used in this study to validate the radiosonde-based cloud layer retrieval method. The performance of the radiosonde-based cloud layer retrieval method applied to data from different climate regimes is evaluated. Overall, cloud layers derived from the ARSCL VAP and radiosonde data agree very well at the SGP and AMF-China sites. At the TWP and NSA sites, the radiosonde tends to detect more cloud layers in the upper troposphere.

Bayesian cloud detection for MERIS, AATSR, and their combination

NASA Astrophysics Data System (ADS)

Hollstein, A.; Fischer, J.; Carbajal Henken, C.; Preusker, R.

2014-11-01

A broad range of different of Bayesian cloud detection schemes is applied to measurements from the Medium Resolution Imaging Spectrometer (MERIS), the Advanced Along-Track Scanning Radiometer (AATSR), and their combination. The cloud masks were designed to be numerically efficient and suited for the processing of large amounts of data. Results from the classical and naive approach to Bayesian cloud masking are discussed for MERIS and AATSR as well as for their combination. A sensitivity study on the resolution of multidimensional histograms, which were post-processed by Gaussian smoothing, shows how theoretically insufficient amounts of truth data can be used to set up accurate classical Bayesian cloud masks. Sets of exploited features from single and derived channels are numerically optimized and results for naive and classical Bayesian cloud masks are presented. The application of the Bayesian approach is discussed in terms of reproducing existing algorithms, enhancing existing algorithms, increasing the robustness of existing algorithms, and on setting up new classification schemes based on manually classified scenes.

A cloud-based system for automatic glaucoma screening.

PubMed

Fengshou Yin; Damon Wing Kee Wong; Ying Quan; Ai Ping Yow; Ngan Meng Tan; Gopalakrishnan, Kavitha; Beng Hai Lee; Yanwu Xu; Zhuo Zhang; Jun Cheng; Jiang Liu

2015-08-01

In recent years, there has been increasing interest in the use of automatic computer-based systems for the detection of eye diseases including glaucoma. However, these systems are usually standalone software with basic functions only, limiting their usage in a large scale. In this paper, we introduce an online cloud-based system for automatic glaucoma screening through the use of medical image-based pattern classification technologies. It is designed in a hybrid cloud pattern to offer both accessibility and enhanced security. Raw data including patient's medical condition and fundus image, and resultant medical reports are collected and distributed through the public cloud tier. In the private cloud tier, automatic analysis and assessment of colour retinal fundus images are performed. The ubiquitous anywhere access nature of the system through the cloud platform facilitates a more efficient and cost-effective means of glaucoma screening, allowing the disease to be detected earlier and enabling early intervention for more efficient intervention and disease management.

The Calipso Thermal Control Subsystem

NASA Technical Reports Server (NTRS)

Gasbarre, Joseph F.; Ousley, Wes; Valentini, Marc; Thomas, Jason; Dejoie, Joel

2007-01-01

The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) is a joint NASA-CNES mission to study the Earth s cloud and aerosol layers. The satellite is composed of a primary payload (built by Ball Aerospace) and a spacecraft platform bus (PROTEUS, built by Alcatel Alenia Space). The thermal control subsystem (TCS) for the CALIPSO satellite is a passive design utilizing radiators, multi-layer insulation (MLI) blankets, and both operational and survival surface heaters. The most temperature sensitive component within the satellite is the laser system. During thermal vacuum testing of the integrated satellite, the laser system s operational heaters were found to be inadequate in maintaining the lasers required set point. In response, a solution utilizing the laser system s survival heaters to augment the operational heaters was developed with collaboration between NASA, CNES, Ball Aerospace, and Alcatel-Alenia. The CALIPSO satellite launched from Vandenberg Air Force Base in California on April 26th, 2006. Evaluation of both the platform and payload thermal control systems show they are performing as expected and maintaining the critical elements of the satellite within acceptable limits.

The CALIPSO Integrated Thermal Control Subsystem

NASA Technical Reports Server (NTRS)

Gasbarre, Joseph F.; Ousley, Wes; Valentini, Marc; Thomas, Jason; Dejoie, Joel

2007-01-01

The Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) is a joint NASA-CNES mission to study the Earth's cloud and aerosol layers. The satellite is composed of a primary payload (built by Ball Aerospace) and a spacecraft platform bus (PROTEUS, built by Alcatel Alenia Space). The thermal control subsystem (TCS) for the CALIPSO satellite is a passive design utilizing radiators, multi-layer insulation (MLI) blankets, and both operational and survival surface heaters. The most temperature sensitive component within the satellite is the laser system. During thermal vacuum testing of the integrated satellite, the laser system's operational heaters were found to be inadequate in maintaining the lasers required set point. In response, a solution utilizing the laser system's survival heaters to augment the operational heaters was developed with collaboration between NASA, CNES, Ball Aerospace, and Alcatel-Alenia. The CALIPSO satellite launched from Vandenberg Air Force Base in California on April 26th, 2006. Evaluation of both the platform and payload thermal control systems show they are performing as expected and maintaining the critical elements of the satellite within acceptable limits.

Polarimetric scattering model for estimation of above ground biomass of multilayer vegetation using ALOS-PALSAR quad-pol data

NASA Astrophysics Data System (ADS)

Sai Bharadwaj, P.; Kumar, Shashi; Kushwaha, S. P. S.; Bijker, Wietske

Forests are important biomes covering a major part of the vegetation on the Earth, and as such account for seventy percent of the carbon present in living beings. The value of a forest's above ground biomass (AGB) is considered as an important parameter for the estimation of global carbon content. In the present study, the quad-pol ALOS-PALSAR data was used for the estimation of AGB for the Dudhwa National Park, India. For this purpose, polarimetric decomposition components and an Extended Water Cloud Model (EWCM) were used. The PolSAR data orientation angle shifts were compensated for before the polarimetric decomposition. The scattering components obtained from the polarimetric decomposition were used in the Water Cloud Model (WCM). The WCM was extended for higher order interactions like double bounce scattering. The parameters of the EWCM were retrieved using the field measurements and the decomposition components. Finally, the relationship between the estimated AGB and measured AGB was assessed. The coefficient of determination (R2) and root mean square error (RMSE) were 0.4341 and 119 t/ha respectively.

Robust Spacecraft Component Detection in Point Clouds.

PubMed

Wei, Quanmao; Jiang, Zhiguo; Zhang, Haopeng

2018-03-21

Automatic component detection of spacecraft can assist in on-orbit operation and space situational awareness. Spacecraft are generally composed of solar panels and cuboidal or cylindrical modules. These components can be simply represented by geometric primitives like plane, cuboid and cylinder. Based on this prior, we propose a robust automatic detection scheme to automatically detect such basic components of spacecraft in three-dimensional (3D) point clouds. In the proposed scheme, cylinders are first detected in the iteration of the energy-based geometric model fitting and cylinder parameter estimation. Then, planes are detected by Hough transform and further described as bounded patches with their minimum bounding rectangles. Finally, the cuboids are detected with pair-wise geometry relations from the detected patches. After successive detection of cylinders, planar patches and cuboids, a mid-level geometry representation of the spacecraft can be delivered. We tested the proposed component detection scheme on spacecraft 3D point clouds synthesized by computer-aided design (CAD) models and those recovered by image-based reconstruction, respectively. Experimental results illustrate that the proposed scheme can detect the basic geometric components effectively and has fine robustness against noise and point distribution density.

Robust Spacecraft Component Detection in Point Clouds

PubMed Central

Wei, Quanmao; Jiang, Zhiguo

2018-01-01

Automatic component detection of spacecraft can assist in on-orbit operation and space situational awareness. Spacecraft are generally composed of solar panels and cuboidal or cylindrical modules. These components can be simply represented by geometric primitives like plane, cuboid and cylinder. Based on this prior, we propose a robust automatic detection scheme to automatically detect such basic components of spacecraft in three-dimensional (3D) point clouds. In the proposed scheme, cylinders are first detected in the iteration of the energy-based geometric model fitting and cylinder parameter estimation. Then, planes are detected by Hough transform and further described as bounded patches with their minimum bounding rectangles. Finally, the cuboids are detected with pair-wise geometry relations from the detected patches. After successive detection of cylinders, planar patches and cuboids, a mid-level geometry representation of the spacecraft can be delivered. We tested the proposed component detection scheme on spacecraft 3D point clouds synthesized by computer-aided design (CAD) models and those recovered by image-based reconstruction, respectively. Experimental results illustrate that the proposed scheme can detect the basic geometric components effectively and has fine robustness against noise and point distribution density. PMID:29561828

Further Research on the Electrification of Pyrocumulus Clouds

NASA Technical Reports Server (NTRS)

Lang, Timothy J.; Laroche, Kendell; Baum, Bryan; Bateman, Monte; Mach, Douglas

2015-01-01

Past research on pyrocumulus electrification has demonstrated that a variety of lightning types can occur, including cloud-to-ground (CG) flashes, sometimes of dominant positive polarity, as well as small intra-cloud (IC) discharges in the upper levels of the pyro-cloud. In Colorado during summer 2012, the first combined polarimetric radar, multi-Doppler radar, and three-dimensional lightning mapping array (LMA) observations of lightning-producing pyrocumulus were obtained. These observations suggested that the National Lightning Detection Network (NLDN) was not sensitive enough to detect the small IC flashes that appear to be the dominant mode of lightning in these clouds. However, after an upgrade to the network in late 2012, the NLDN began detecting some of this pyrocumulus lightning. Multiple pyrocumulus clouds documented by the University of Wisconsin for various fires in 2013 and 2014 (including over the Rim, West Fork Complex, Yarnell Hill, Hardluck, and several other incidents) are examined and reported on here. This study exploits the increased-sensitivity NLDN as well as the new nationwide U.S. network of polarimetric Next-generation Radars (NEXRADs). These observations document the common occurrence of a polarimetric "dirty ice" signature - modest reflectivities (20-40+ dBZ), near-zero differential reflectivity, and reduced correlation coefficient (less than 0.9) - prior to the production of lightning. This signature is indicative of a mixture of ash and ice particles in the upper levels of the pyro-cloud (less than -20 C), with the ice interpreted as being necessary for pyro-cloud electrification. Pseudo-Geostationary Lightning Mapper (GLM) data will be produced from the 2012 LMA observations, and the ability of GLM to detect small pyrocumulus ICs will be assessed. The utility of lightning and polarimetric radar for documenting rapid wildfire growth, as well as for documenting pyrocumulus impacts on the composition of the upper troposphere/lower stratosphere (UTLS), will be discussed.

Low Clouds and Fog Characterization over Iberian Peninsula using Meteosat Second Generation Images

NASA Astrophysics Data System (ADS)

Sánchez, Beatriz; Maqueda, Gregorio

2014-05-01

Fog is defined as a collection of suspended water droplets or ice crystals in the air near the Earth's surface that lead to a reduction of horizontal visibility below 1 km (National Oceanic and Atmospheric Administration, 1995). Fog is a stratiform cloud with similar radiative characteristics, for this reason the difference between fog and low stratus clouds is of little importance for remote sensing applications. Fog and low clouds are important atmospheric phenomena, mainly because of their impact on traffic safety and air quality, acting as an obstruction to traffic at land, sea and in the air. The purpose of this work is to develop the method of fog/low clouds detection and analysis on nighttime using Meteosat Second Generation data. This study is focused on the characterization of these atmospheric phenomena in different study cases over the Iberian Peninsula with distinct orography. Firstly, fog/low clouds detection is implemented as a composition of three infrared channels 12.0, 10.8 and 3.9 µm from SEVIRI radiometer on board European geostationary satellite Meteosat (Meteosat-9). The algorithm of detection makes use of a combination of these channels and their differences by creating RGB composites images. On this way, it displays the spatial coverage and location of fog entities. Secondly, this technique allows separating pixels which are indicated as fog/low clouds from clear pixels, assessing the properties of individual pixels using appropriated thresholds of brightness temperature. Thus, it achieves a full analysis of the extent and distribution of fog and its evolution over time. The results of this study have been checked by using ground-based point measurements available as METAR data. Despite the flaws in this sort of inter-comparison approach, the outcome produces to accurate fog/low clouds detection. This work encompasses the way to obtain spatial information from this atmospheric phenomenon by means of satellite imagery.

Spatial and Temporal Varying Thresholds for Cloud Detection in Satellite Imagery

NASA Technical Reports Server (NTRS)

Jedlovec, Gary; Haines, Stephanie

2007-01-01

A new cloud detection technique has been developed and applied to both geostationary and polar orbiting satellite imagery having channels in the thermal infrared and short wave infrared spectral regions. The bispectral composite threshold (BCT) technique uses only the 11 micron and 3.9 micron channels, and composite imagery generated from these channels, in a four-step cloud detection procedure to produce a binary cloud mask at single pixel resolution. A unique aspect of this algorithm is the use of 20-day composites of the 11 micron and the 11 - 3.9 micron channel difference imagery to represent spatially and temporally varying clear-sky thresholds for the bispectral cloud tests. The BCT cloud detection algorithm has been applied to GOES and MODIS data over the continental United States over the last three years with good success. The resulting products have been validated against "truth" datasets (generated by the manual determination of the sky conditions from available satellite imagery) for various seasons from the 2003-2005 periods. The day and night algorithm has been shown to determine the correct sky conditions 80-90% of the time (on average) over land and ocean areas. Only a small variation in algorithm performance occurs between day-night, land-ocean, and between seasons. The algorithm performs least well. during he winter season with only 80% of the sky conditions determined correctly. The algorithm was found to under-determine clouds at night and during times of low sun angle (in geostationary satellite data) and tends to over-determine the presence of clouds during the day, particularly in the summertime. Since the spectral tests use only the short- and long-wave channels common to most multispectral scanners; the application of the BCT technique to a variety of satellite sensors including SEVERI should be straightforward and produce similar performance results.

Cloud-enabled microscopy and droplet microfluidic platform for specific detection of Escherichia coli in water.

PubMed

Golberg, Alexander; Linshiz, Gregory; Kravets, Ilia; Stawski, Nina; Hillson, Nathan J; Yarmush, Martin L; Marks, Robert S; Konry, Tania

2014-01-01

We report an all-in-one platform - ScanDrop - for the rapid and specific capture, detection, and identification of bacteria in drinking water. The ScanDrop platform integrates droplet microfluidics, a portable imaging system, and cloud-based control software and data storage. The cloud-based control software and data storage enables robotic image acquisition, remote image processing, and rapid data sharing. These features form a "cloud" network for water quality monitoring. We have demonstrated the capability of ScanDrop to perform water quality monitoring via the detection of an indicator coliform bacterium, Escherichia coli, in drinking water contaminated with feces. Magnetic beads conjugated with antibodies to E. coli antigen were used to selectively capture and isolate specific bacteria from water samples. The bead-captured bacteria were co-encapsulated in pico-liter droplets with fluorescently-labeled anti-E. coli antibodies, and imaged with an automated custom designed fluorescence microscope. The entire water quality diagnostic process required 8 hours from sample collection to online-accessible results compared with 2-4 days for other currently available standard detection methods.

Ten Years of Cloud Properties from MODIS: Global Statistics and Use in Climate Model Evaluation

NASA Technical Reports Server (NTRS)

Platnick, Steven E.

2011-01-01

The NASA Moderate Resolution Imaging Spectroradiometer (MODIS), launched onboard the Terra and Aqua spacecrafts, began Earth observations on February 24, 2000 and June 24,2002, respectively. Among the algorithms developed and applied to this sensor, a suite of cloud products includes cloud masking/detection, cloud-top properties (temperature, pressure), and optical properties (optical thickness, effective particle radius, water path, and thermodynamic phase). All cloud algorithms underwent numerous changes and enhancements between for the latest Collection 5 production version; this process continues with the current Collection 6 development. We will show example MODIS Collection 5 cloud climatologies derived from global spatial . and temporal aggregations provided in the archived gridded Level-3 MODIS atmosphere team product (product names MOD08 and MYD08 for MODIS Terra and Aqua, respectively). Data sets in this Level-3 product include scalar statistics as well as 1- and 2-D histograms of many cloud properties, allowing for higher order information and correlation studies. In addition to these statistics, we will show trends and statistical significance in annual and seasonal means for a variety of the MODIS cloud properties, as well as the time required for detection given assumed trends. To assist in climate model evaluation, we have developed a MODIS cloud simulator with an accompanying netCDF file containing subsetted monthly Level-3 statistical data sets that correspond to the simulator output. Correlations of cloud properties with ENSO offer the potential to evaluate model cloud sensitivity; initial results will be discussed.

Area X-ray or UV camera system for high-intensity beams

DOEpatents

Chapman, Henry N.; Bajt, Sasa; Spiller, Eberhard A.; Hau-Riege, Stefan , Marchesini, Stefano

2010-03-02

A system in one embodiment includes a source for directing a beam of radiation at a sample; a multilayer mirror having a face oriented at an angle of less than 90 degrees from an axis of the beam from the source, the mirror reflecting at least a portion of the radiation after the beam encounters a sample; and a pixellated detector for detecting radiation reflected by the mirror. A method in a further embodiment includes directing a beam of radiation at a sample; reflecting at least some of the radiation diffracted by the sample; not reflecting at least a majority of the radiation that is not diffracted by the sample; and detecting at least some of the reflected radiation. A method in yet another embodiment includes directing a beam of radiation at a sample; reflecting at least some of the radiation diffracted by the sample using a multilayer mirror; and detecting at least some of the reflected radiation.

Magnon detection using a ferroic collinear multilayer spin valve.

PubMed

Cramer, Joel; Fuhrmann, Felix; Ritzmann, Ulrike; Gall, Vanessa; Niizeki, Tomohiko; Ramos, Rafael; Qiu, Zhiyong; Hou, Dazhi; Kikkawa, Takashi; Sinova, Jairo; Nowak, Ulrich; Saitoh, Eiji; Kläui, Mathias

2018-03-14

Information transport and processing by pure magnonic spin currents in insulators is a promising alternative to conventional charge-current-driven spintronic devices. The absence of Joule heating and reduced spin wave damping in insulating ferromagnets have been suggested for implementing efficient logic devices. After the successful demonstration of a majority gate based on the superposition of spin waves, further components are required to perform complex logic operations. Here, we report on magnetization orientation-dependent spin current detection signals in collinear magnetic multilayers inspired by the functionality of a conventional spin valve. In Y 3 Fe 5 O 12 |CoO|Co, we find that the detection amplitude of spin currents emitted by ferromagnetic resonance spin pumping depends on the relative alignment of the Y 3 Fe 5 O 12 and Co magnetization. This yields a spin valve-like behavior with an amplitude change of 120% in our systems. We demonstrate the reliability of the effect and identify its origin by both temperature-dependent and power-dependent measurements.

Sombrero-shaped plasmonic nanoparticles with molecular-level sensitivity and multifunctionality.

PubMed

Wi, Jung-Sub; Barnard, Edward S; Wilson, Robert J; Zhang, Mingliang; Tang, Mary; Brongersma, Mark L; Wang, Shan X

2011-08-23

We demonstrate top-down synthesis of monodisperse plasmonic nanoparticles designed to contain internal Raman hot spots. Our Raman-active nanoparticles are fabricated using nanoimprint lithography and thin-film deposition and are composed of novel internal structures with sublithographic dimensions: a disk-shaped Ag core, a Petri-dish-shaped SiO(2) base whose inner surface is coated with Ag film, and a sub-10 nm scale circular gap between the core and the base. Confocal Raman measurements and electromagnetic simulations show that Raman hot spots appear at the inside perimeter of individual nanoparticles and serve as the source of a 1000-fold improvement of minimum molecular detection level that enables detection of signals from a few molecules near hot spots. A multimodality version of these nanoparticles, which includes the functionality offered by magnetic multilayers, is also demonstrated. These results illustrate the potential of direct fabrication for creating exotic monodisperse nanoparticles, which combine engineered internal nanostructures and multilayer composite materials, for use in nanoparticle-based molecular imaging and detection. © 2011 American Chemical Society

Opaque cloud detection

DOEpatents

Roskovensky, John K [Albuquerque, NM

2009-01-20

A method of detecting clouds in a digital image comprising, for an area of the digital image, determining a reflectance value in at least three discrete electromagnetic spectrum bands, computing a first ratio of one reflectance value minus another reflectance value and the same two values added together, computing a second ratio of one reflectance value and another reflectance value, choosing one of the reflectance values, and concluding that an opaque cloud exists in the area if the results of each of the two computing steps and the choosing step fall within three corresponding predetermined ranges.

Studies of extra-solar Oort Clouds and the Kuiper disk

NASA Technical Reports Server (NTRS)

Stern, S. Alan

1992-01-01

In 1991 we detected extended 1.1 mm emission around Fomalhaut (alpha PsA) at distances in order of magnitude beyond previous detections. This emission is plausibly related to the presence of an extended comet cloud, like our Oort Cloud, and may therefore represent indirect evidence for the formation of a planetary system at Fomalhaut. We propose now to extend this work to create a map of the angular and spatial extent of this emission. Fomalhaut is the only known main-sequence, submm-resolved IR excess source besides beta Pic.

Cloud properties inferred from 8-12 micron data

NASA Technical Reports Server (NTRS)

Strabala, Kathleen I.; Ackerman, Steven A.; Menzel, W. Paul

1994-01-01

A trispectral combination of observations at 8-, 11-, and 12-micron bands is suggested for detecting cloud and cloud properties in the infrared. Atmospheric ice and water vapor absorption peak in opposite halves of the window region so that positive 8-minus-11-micron brightness temperature differences indicate cloud, while near-zero or negative differences indicate clear regions. The absorption coefficient for water increases more between 11 and 12 microns than between 8 and 11 microns, while for ice, the reverse is true. Cloud phases is determined by a scatter diagram of 8-minus-11-micron versus 11-minus-12-micron brightness temperature differences; ice cloud shows a slope greater than 1 and water cloud less than 1. The trispectral brightness temperature method was tested upon high-resolution interferometer data resulting in clear-cloud and cloud-phase delineation. Simulations using differing 8-micron bandwidths revealed no significant degradation of cloud property detection. Thus, the 8-micron bandwidth for future satellites can be selected based on the requirements of other applications, such as surface characterization studies. Application of the technique to current polar-orbiting High-Resolution Infrared Sounder (HIRS)-Advanced Very High Resolution Radiometer (AVHRR) datasets is constrained by the nonuniformity of the cloud scenes sensed within the large HIRS field of view. Analysis of MAS (MODIS Airborne Simulator) high-spatial resolution (500 m) data with all three 8-, 11-, and 12-micron bands revealed sharp delineation of differing cloud and background scenes, from which a simple automated threshold technique was developed. Cloud phase, clear-sky, and qualitative differences in cloud emissivity and cloud height were identified on a case study segment from 24 November 1991, consistent with the scene. More rigorous techniques would allow further cloud parameter clarification. The opportunities for global cloud delineation with the Moderate-Resolution Imaging Spectrometer (MODIS) appear excellent. The spectral selection, the spatial resolution, and the global coverage are all well suited for significant advances.

The Cloud Detection and Ultraviolet Monitoring Experiment (CLUE)

NASA Technical Reports Server (NTRS)

Barbier, Louis M.; Loh, Eugene C.; Krizmanic, John F.; Sokolsky, Pierre; Streitmatter, Robert E.

2004-01-01

In this paper we describe a new balloon instrument - CLUE - which is designed to monitor ultraviolet (uv) nightglow levels and determine cloud cover and cloud heights with a CO2 slicing technique. The CO2 slicing technique is based on the MODIS instrument on NASA's Aqua and Terra spacecraft. CLUE will provide higher spatial resolution (0.5 km) and correlations between the uv and the cloud cover.

Boundary conditions for the paleoenvironment: Chemical and physical processes in the pre-solar nebula. [molecular clouds, interstellar matter, and abundance

NASA Technical Reports Server (NTRS)

Irvine, W. M.; Schloerb, F. P.

1985-01-01

Two additional hyperfine components of the interstellar radical C3H were detected. In addition, methanol was discovered in interstellar clouds. The abundance of HCCN and various chemical isomers in molecular clouds was investigated.

Refinement of the CALIOP cloud mask algorithm

NASA Astrophysics Data System (ADS)

Katagiri, Shuichiro; Sato, Kaori; Ohta, Kohei; Okamoto, Hajime

2018-04-01

A modified cloud mask algorithm was applied to the CALIOP data to have more ability to detect the clouds in the lower atmosphere. In this algorithm, we also adopt the fully attenuation discrimination and the remain noise estimation using the data obtained at an altitude of 40 km to avoid contamination of stratospheric aerosols. The new cloud mask shows an increase in the lower cloud fraction. Comparison of the results to the data observed with a PML ground observation was also made.

An Evaluation of Northern Hemisphere Merged Cloud Analyses from the United States Air Force Cloud Depiction Forecasting System II

DTIC Science & Technology

2013-03-01

layering and typing to provide a vertical stratification of the cloud-filled pixels detected in Level 2. Level 3 output is remapped to the standard AFWA...analyses are compared to one another to see if the most recent analysis also has the lowest estimated error. Optimum interpolation (OI) occurs when...NORTHERN HEMISPHERE MERGED CLOUD ANALYSES FROM THE UNITED STATES AIR FORCE CLOUD DEPICTION FORECASTING SYSTEM II by Chandra M. Pasillas March

Detection of mesoscale convective complexes using multispectral RGB technique of Himawari-8 (Case Study: Jakarta, 20 February 2017)

NASA Astrophysics Data System (ADS)

Fatkhuroyan; Wati, T.

2018-05-01

Mesoscale Convective Complexes (MCC) is a well-organized convective cloud that has big size and long lifetime. The aim of the study is to detect and to monitor the development of MCC around Jakarta on 20th February 2017 using satellite Himawari-8. This study uses the analyzing method of the infrared channel and multispectral imagery RGB Technique to monitor the development of radiative, morphology and cloud position which describe the cloud top microphysics, structure and movement of the MCC. On 20th February 2017, the result from Himawari-8 shows that there are many dense-clouds with small ice particle and cloud top temperature could be < -50°C which can be seen as red and yellow dot colour by RGB Technique. The MCC caused a severe storm at Jakarta and its surrounding area.

On-Board Cryospheric Change Detection By The Autonomous Sciencecraft Experiment

NASA Astrophysics Data System (ADS)

Doggett, T.; Greeley, R.; Castano, R.; Cichy, B.; Chien, S.; Davies, A.; Baker, V.; Dohm, J.; Ip, F.

2004-12-01

The Autonomous Sciencecraft Experiment (ASE) is operating on-board Earth Observing - 1 (EO-1) with the Hyperion hyper-spectral visible/near-IR spectrometer. ASE science activities include autonomous monitoring of cryopsheric changes, triggering the collection of additional data when change is detected and filtering of null data such as no change or cloud cover. This would have application to the study of cryospheres on Earth, Mars and the icy moons of the outer solar system. A cryosphere classification algorithm, in combination with a previously developed cloud algorithm [1] has been tested on-board ten times from March through August 2004. The cloud algorithm correctly screened out three scenes with total cloud cover, while the cryosphere algorithm detected alpine snow cover in the Rocky Mountains, lake thaw near Madison, Wisconsin, and the presence and subsequent break-up of sea ice in the Barrow Strait of the Canadian Arctic. Hyperion has 220 bands ranging from 400 to 2400 nm, with a spatial resolution of 30 m/pixel and a spectral resolution of 10 nm. Limited on-board memory and processing speed imposed the constraint that only partially processed Level 0.5 data with dark image subtraction and gain factors applied, but not full radiometric calibration. In addition, a maximum of 12 bands could be used for any stacked sequence of algorithms run for a scene on-board. The cryosphere algorithm was developed to classify snow, water, ice and land, using six Hyperion bands at 427, 559, 661, 864, 1245 and 1649 nm. Of these, only 427 nm does overlap with the cloud algorithm. The cloud algorithm was developed with Level 1 data, which introduces complications because of the incomplete calibration of SWIR in Level 0.5 data, including a high level of noise in the 1377 nm band used by the cloud algorithm. Development of a more robust cryosphere classifier, including cloud classification specifically adapted to Level 0.5, is in progress for deployment on EO-1 as part of continued ASE operations. [1] Griffin, M.K. et al., Cloud Cover Detection Algorithm For EO-1 Hyperion Imagery, SPIE 17, 2003.

Automatic Classification of Trees from Laser Scanning Point Clouds

NASA Astrophysics Data System (ADS)

Sirmacek, B.; Lindenbergh, R.

2015-08-01

Development of laser scanning technologies has promoted tree monitoring studies to a new level, as the laser scanning point clouds enable accurate 3D measurements in a fast and environmental friendly manner. In this paper, we introduce a probability matrix computation based algorithm for automatically classifying laser scanning point clouds into 'tree' and 'non-tree' classes. Our method uses the 3D coordinates of the laser scanning points as input and generates a new point cloud which holds a label for each point indicating if it belongs to the 'tree' or 'non-tree' class. To do so, a grid surface is assigned to the lowest height level of the point cloud. The grids are filled with probability values which are calculated by checking the point density above the grid. Since the tree trunk locations appear with very high values in the probability matrix, selecting the local maxima of the grid surface help to detect the tree trunks. Further points are assigned to tree trunks if they appear in the close proximity of trunks. Since heavy mathematical computations (such as point cloud organization, detailed shape 3D detection methods, graph network generation) are not required, the proposed algorithm works very fast compared to the existing methods. The tree classification results are found reliable even on point clouds of cities containing many different objects. As the most significant weakness, false detection of light poles, traffic signs and other objects close to trees cannot be prevented. Nevertheless, the experimental results on mobile and airborne laser scanning point clouds indicate the possible usage of the algorithm as an important step for tree growth observation, tree counting and similar applications. While the laser scanning point cloud is giving opportunity to classify even very small trees, accuracy of the results is reduced in the low point density areas further away than the scanning location. These advantages and disadvantages of two laser scanning point cloud sources are discussed in detail.

Progressive data transmission for anatomical landmark detection in a cloud.

PubMed

Sofka, M; Ralovich, K; Zhang, J; Zhou, S K; Comaniciu, D

2012-01-01

In the concept of cloud-computing-based systems, various authorized users have secure access to patient records from a number of care delivery organizations from any location. This creates a growing need for remote visualization, advanced image processing, state-of-the-art image analysis, and computer aided diagnosis. This paper proposes a system of algorithms for automatic detection of anatomical landmarks in 3D volumes in the cloud computing environment. The system addresses the inherent problem of limited bandwidth between a (thin) client, data center, and data analysis server. The problem of limited bandwidth is solved by a hierarchical sequential detection algorithm that obtains data by progressively transmitting only image regions required for processing. The client sends a request to detect a set of landmarks for region visualization or further analysis. The algorithm running on the data analysis server obtains a coarse level image from the data center and generates landmark location candidates. The candidates are then used to obtain image neighborhood regions at a finer resolution level for further detection. This way, the landmark locations are hierarchically and sequentially detected and refined. Only image regions surrounding landmark location candidates need to be trans- mitted during detection. Furthermore, the image regions are lossy compressed with JPEG 2000. Together, these properties amount to at least 30 times bandwidth reduction while achieving similar accuracy when compared to an algorithm using the original data. The hierarchical sequential algorithm with progressive data transmission considerably reduces bandwidth requirements in cloud-based detection systems.

Development of Eddy Current Techniques for Detection of Deep Fatigue Cracks in Multi-Layer Airframe Components

NASA Technical Reports Server (NTRS)

Wincheski, Russell A.

2008-01-01

Thick, multi-layer aluminum structure has been widely used in aircraft design in critical wing splice areas. The multi-layer structure generally consists of three or four aluminum layers with different geometry and varying thickness, which are held together with fasteners. The detection of cracks under fasteners with ultrasonic techniques in subsurface layers away from the skin is impeded primarily by interlayer bonds and faying sealant condition. Further, assessment of such sealant condition is extremely challenging in terms of complexity of structure, limited access, and inspection cost. Although Eddy current techniques can be applied on in-service aircraft from the exterior of the skin without knowing sealant condition, the current eddy current techniques are not able to detect defects with wanted sensitivity. In this work a series of low frequency eddy current probes have been designed, fabricated and tested for this application. A probe design incorporating a shielded magnetic field sensor concentrically located in the interior of a drive coil has been employed to enable a localized deep diffusion of the electromagnetic field into the part under test. Due to the required low frequency inspections, probes have been testing using a variety of magnetic field sensors (pickup coil, giant magneto-resistive, anisotropic magneto-resistive, and spin-dependent tunneling). The probe designs as well as capabilities based upon a target inspection for sub-layer cracking in an airframe wing spar joint is presented.

Biogenic, urban, and wildfire influences on the molecular composition of dissolved organic compounds in cloud water

NASA Astrophysics Data System (ADS)

Cook, Ryan D.; Lin, Ying-Hsuan; Peng, Zhuoyu; Boone, Eric; Chu, Rosalie K.; Dukett, James E.; Gunsch, Matthew J.; Zhang, Wuliang; Tolic, Nikola; Laskin, Alexander; Pratt, Kerri A.

2017-12-01

Organic aerosol formation and transformation occurs within aqueous aerosol and cloud droplets, yet little is known about the composition of high molecular weight organic compounds in cloud water. Cloud water samples collected at Whiteface Mountain, New York, during August-September 2014 were analyzed by ultra-high-resolution mass spectrometry to investigate the molecular composition of dissolved organic carbon, with a focus on sulfur- and nitrogen-containing compounds. Organic molecular composition was evaluated in the context of cloud water inorganic ion concentrations, pH, and total organic carbon concentrations to gain insights into the sources and aqueous-phase processes of the observed high molecular weight organic compounds. Cloud water acidity was positively correlated with the average oxygen : carbon ratio of the organic constituents, suggesting the possibility for aqueous acid-catalyzed (prior to cloud droplet activation or during/after cloud droplet evaporation) and/or radical (within cloud droplets) oxidation processes. Many tracer compounds recently identified in laboratory studies of bulk aqueous-phase reactions were identified in the cloud water. Organosulfate compounds, with both biogenic and anthropogenic volatile organic compound precursors, were detected for cloud water samples influenced by air masses that had traveled over forested and populated areas. Oxidation products of long-chain (C10-12) alkane precursors were detected during urban influence. Influence of Canadian wildfires resulted in increased numbers of identified sulfur-containing compounds and oligomeric species, including those formed through aqueous-phase reactions involving methylglyoxal. Light-absorbing aqueous-phase products of syringol and guaiacol oxidation were observed in the wildfire-influenced samples, and dinitroaromatic compounds were observed in all cloud water samples (wildfire, biogenic, and urban-influenced). Overall, the cloud water molecular composition depended on air mass source influence and reflected aqueous-phase reactions involving biogenic, urban, and biomass burning precursors.

Mass spectrometric determination of the composition of the Venus clouds

NASA Technical Reports Server (NTRS)

Herzog, R. F. K.

1973-01-01

The instrumentation is analyzed for determining the composition of the clouds on Venus. Direct analysis of the gas phase atmosphere, and the detection of ferrous chloride with a mass spectrometer are dicussed along with the mass analyzer, and the pre-separation of cloud particles from the ambient atmosphere.

Multilayer poly(3,4-ethylenedioxythiophene)-dexamethasone and poly(3,4-ethylenedioxythiophene)-polystyrene sulfonate-carbon nanotubes coatings on glassy carbon microelectrode arrays for controlled drug release.

PubMed

Castagnola, Elisa; Carli, Stefano; Vomero, Maria; Scarpellini, Alice; Prato, Mirko; Goshi, Noah; Fadiga, Luciano; Kassegne, Sam; Ricci, Davide

2017-07-13

The authors present an electrochemically controlled, drug releasing neural interface composed of a glassy carbon (GC) microelectrode array combined with a multilayer poly(3,4-ethylenedioxythiophene) (PEDOT) coating. The system integrates the high stability of the GC electrode substrate, ideal for electrical stimulation and electrochemical detection of neurotransmitters, with the on-demand drug-releasing capabilities of PEDOT-dexamethasone compound, through a mechanically stable interlayer of PEDOT-polystyrene sulfonate (PSS)-carbon nanotubes (CNT). The authors demonstrate that such interlayer improves both the mechanical and electrochemical properties of the neural interface, when compared with a single PEDOT-dexamethasone coating. Moreover, the multilayer coating is able to withstand 10 × 10 6 biphasic pulses and delamination test with negligible change to the impedance spectra. Cross-section scanning electron microscopy images support that the PEDOT-PSS-CNT interlayer significantly improves the adhesion between the GC substrate and PEDOT-dexamethasone coating, showing no discontinuities between the three well-interconnected layers. Furthermore, the multilayer coating has superior electrochemical properties, in terms of impedance and charge transfer capabilities as compared to a single layer of either PEDOT coating or the GC substrate alone. The authors verified the drug releasing capabilities of the PEDOT-dexamethasone layer when integrated into the multilayer interface through repeated stimulation protocols in vitro, and found a pharmacologically relevant release of dexamethasone.

Fabrication of graphene/polyaniline composite multilayer films by electrostatic layer-by-layer assembly

NASA Astrophysics Data System (ADS)

Cong, Jiaojiao; Chen, Yuze; Luo, Jing; Liu, Xiaoya

2014-10-01

A novel graphene/polyaniline composite multilayer film was fabricated by electrostatic interactions induced layer-by-layer self-assembly technique, using water dispersible and negatively charged chemically converted graphene (CCG) and positively charged polyaniline (PANI) as building blocks. CCG was achieved through partly reduced graphene oxide, which remained carboxyl group on its surface. The remaining carboxyl groups not only retain the dispersibility of CCG, but also allow the growth of the multilayer films via electrostatic interactions between graphene and PANI. The structure and morphology of the obtained CCG/PANI multilayer film are characterized by attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectroscopy, Ultraviolet-visible absorption spectrum (UV-vis), scanning electron microscopy (SEM), Raman spectroscopy and X-Ray Diffraction (XRD). The electrochemical properties of the resulting film are studied using cyclic voltammetry (CV), which showed that the resulting CCG/PANI multilayer film kept electroactivity in neutral solution and showed outstanding cyclic stability up to 100 cycles. Furthermore, the composite film exhibited good electrocatalytic ability toward ascorbic acid (AA) with a linear response from 1×10-4 to 1.2×10-3 M with the detect limit of 5×10-6 M. This study provides a facile and effective strategy to fabricate graphene/PANI nanocomposite film with good electrochemical property, which may find potential applications in electronic devices such as electrochemical sensor.

Nanoscale deformation mechanism of TiC/a-C nanocomposite thin films

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, C. Q.; Pei, Y. T.; Shaha, K. P.

2009-06-01

This paper concentrates on the deformation behavior of amorphous diamondlike carbon composite materials. Combined nanoindentation and ex situ cross-sectional transmission electron microscopy investigations are carried out on TiC/a-C nanocomposite films, with and without multilayered structures deposited by pulse dc magnetron sputtering. It is shown that by controlling the distribution of nanocrystallites forming nanoscale multilayers, the system can be used as a 'microstructural ruler' that is able to distinguish various deformation patterns, which can be hardly detected otherwise in a homogeneous structure. It is shown that rearrangement of nanocrystallites and displacement of a-C matrix occur at length scales from tens ofmore » nanometer down to 1 nm. At submicrometer scale homogeneous nucleation of multiple shear bands has been observed within the nanocomposites. The multilayered structure in the TiC/a-C nanocomposite film contributes to an enhanced toughness.« less

Application of Multilayer Perceptron with Automatic Relevance Determination on Weed Mapping Using UAV Multispectral Imagery

PubMed Central

Tamouridou, Afroditi A.; Lagopodi, Anastasia L.; Kashefi, Javid; Kasampalis, Dimitris; Kontouris, Georgios; Moshou, Dimitrios

2017-01-01

Remote sensing techniques are routinely used in plant species discrimination and of weed mapping. In the presented work, successful Silybum marianum detection and mapping using multilayer neural networks is demonstrated. A multispectral camera (green-red-near infrared) attached on a fixed wing unmanned aerial vehicle (UAV) was utilized for the acquisition of high-resolution images (0.1 m resolution). The Multilayer Perceptron with Automatic Relevance Determination (MLP-ARD) was used to identify the S. marianum among other vegetation, mostly Avena sterilis L. The three spectral bands of Red, Green, Near Infrared (NIR) and the texture layer resulting from local variance were used as input. The S. marianum identification rates using MLP-ARD reached an accuracy of 99.54%. Τhe study had an one year duration, meaning that the results are specific, although the accuracy shows the interesting potential of S. marianum mapping with MLP-ARD on multispectral UAV imagery. PMID:29019957

Non-contact XUV metrology of Ru/B4C multilayer optics by means of Hartmann wavefront analysis.

PubMed

Ruiz-Lopez, Mabel; Dacasa, Hugo; Mahieu, Benoit; Lozano, Magali; Li, Lu; Zeitoun, Philippe; Bleiner, Davide

2018-02-20

Short-wavelength imaging, spectroscopy, and lithography scale down the characteristic length-scale to nanometers. This poses tight constraints on the optics finishing tolerances, which is often difficult to characterize. Indeed, even a tiny surface defect degrades the reflectivity and spatial projection of such optics. In this study, we demonstrate experimentally that a Hartmann wavefront sensor for extreme ultraviolet (XUV) wavelengths is an effective non-contact analytical method for inspecting the surface of multilayer optics. The experiment was carried out in a tabletop laboratory using a high-order harmonic generation as an XUV source. The wavefront sensor was used to measure the wavefront errors after the reflection of the XUV beam on a spherical Ru/B 4 C multilayer mirror, scanning a large surface of approximately 40 mm in diameter. The results showed that the technique detects the aberrations in the nanometer range.

3D printing of tissue-simulating phantoms as a traceable standard for biomedical optical measurement

NASA Astrophysics Data System (ADS)

Dong, Erbao; Wang, Minjie; Shen, Shuwei; Han, Yilin; Wu, Qiang; Xu, Ronald

2016-01-01

Optical phantoms are commonly used to validate and calibrate biomedical optical devices in order to ensure accurate measurement of optical properties in biological tissue. However, commonly used optical phantoms are based on homogenous materials that reflect neither optical properties nor multi-layer heterogeneities of biological tissue. Using these phantoms for optical calibration may result in significant bias in biological measurement. We propose to characterize and fabricate tissue simulating phantoms that simulate not only the multi-layer heterogeneities but also optical properties of biological tissue. The tissue characterization module detects tissue structural and functional properties in vivo. The phantom printing module generates 3D tissue structures at different scales by layer-by-layer deposition of phantom materials with different optical properties. The ultimate goal is to fabricate multi-layer tissue simulating phantoms as a traceable standard for optimal calibration of biomedical optical spectral devices.

Surface-agnostic highly stretchable and bendable conductive MXene multilayers

PubMed Central

An, Hyosung; Habib, Touseef; Shah, Smit; Gao, Huili; Radovic, Miladin; Green, Micah J.; Lutkenhaus, Jodie L.

2018-01-01

Stretchable, bendable, and foldable conductive coatings are crucial for wearable electronics and biometric sensors. These coatings should maintain functionality while simultaneously interfacing with different types of surfaces undergoing mechanical deformation. MXene sheets as conductive two-dimensional nanomaterials are promising for this purpose, but it is still extremely difficult to form surface-agnostic MXene coatings that can withstand extreme mechanical deformation. We report on conductive and conformal MXene multilayer coatings that can undergo large-scale mechanical deformation while maintaining a conductivity as high as 2000 S/m. MXene multilayers are successfully deposited onto flexible polymer sheets, stretchable poly(dimethylsiloxane), nylon fiber, glass, and silicon. The coating shows a recoverable resistance response to bending (up to 2.5-mm bending radius) and stretching (up to 40% tensile strain), which was leveraged for detecting human motion and topographical scanning. We anticipate that this discovery will allow for the implementation of MXene-based coatings onto mechanically deformable objects. PMID:29536044

Application of Multilayer Perceptron with Automatic Relevance Determination on Weed Mapping Using UAV Multispectral Imagery.

PubMed

Tamouridou, Afroditi A; Alexandridis, Thomas K; Pantazi, Xanthoula E; Lagopodi, Anastasia L; Kashefi, Javid; Kasampalis, Dimitris; Kontouris, Georgios; Moshou, Dimitrios

2017-10-11

Remote sensing techniques are routinely used in plant species discrimination and of weed mapping. In the presented work, successful Silybum marianum detection and mapping using multilayer neural networks is demonstrated. A multispectral camera (green-red-near infrared) attached on a fixed wing unmanned aerial vehicle (UAV) was utilized for the acquisition of high-resolution images (0.1 m resolution). The Multilayer Perceptron with Automatic Relevance Determination (MLP-ARD) was used to identify the S. marianum among other vegetation, mostly Avena sterilis L. The three spectral bands of Red, Green, Near Infrared (NIR) and the texture layer resulting from local variance were used as input. The S. marianum identification rates using MLP-ARD reached an accuracy of 99.54%. Τhe study had an one year duration, meaning that the results are specific, although the accuracy shows the interesting potential of S. marianum mapping with MLP-ARD on multispectral UAV imagery.

Magneto-optical fingerprints of distinct graphene multilayers using the giant infrared Kerr effect

NASA Astrophysics Data System (ADS)

Ellis, Chase T.; Stier, Andreas V.; Kim, Myoung-Hwan; Tischler, Joseph G.; Glaser, Evan R.; Myers-Ward, Rachael L.; Tedesco, Joseph L.; Eddy, Charles R.; Gaskill, D. Kurt; Cerne, John

2013-11-01

The remarkable electronic properties of graphene strongly depend on the thickness and geometry of graphene stacks. This wide range of electronic tunability is of fundamental interest and has many applications in newly proposed devices. Using the mid-infrared, magneto-optical Kerr effect, we detect and identify over 18 interband cyclotron resonances (CR) that are associated with ABA and ABC stacked multilayers as well as monolayers that coexist in graphene that is epitaxially grown on 4H-SiC. Moreover, the magnetic field and photon energy dependence of these features enable us to explore the band structure, electron-hole band asymmetries, and mechanisms that activate a CR response in the Kerr effect for various multilayers that coexist in a single sample. Surprisingly, we find that the magnitude of monolayer Kerr effect CRs is not temperature dependent. This unexpected result reveals new questions about the underlying physics that makes such an effect possible.

Automatic telangiectasia analysis in dermoscopy images using adaptive critic design.

PubMed

Cheng, B; Stanley, R J; Stoecker, W V; Hinton, K

2012-11-01

Telangiectasia, tiny skin vessels, are important dermoscopy structures used to discriminate basal cell carcinoma (BCC) from benign skin lesions. This research builds off of previously developed image analysis techniques to identify vessels automatically to discriminate benign lesions from BCCs. A biologically inspired reinforcement learning approach is investigated in an adaptive critic design framework to apply action-dependent heuristic dynamic programming (ADHDP) for discrimination based on computed features using different skin lesion contrast variations to promote the discrimination process. Lesion discrimination results for ADHDP are compared with multilayer perception backpropagation artificial neural networks. This study uses a data set of 498 dermoscopy skin lesion images of 263 BCCs and 226 competitive benign images as the input sets. This data set is extended from previous research [Cheng et al., Skin Research and Technology, 2011, 17: 278]. Experimental results yielded a diagnostic accuracy as high as 84.6% using the ADHDP approach, providing an 8.03% improvement over a standard multilayer perception method. We have chosen BCC detection rather than vessel detection as the endpoint. Although vessel detection is inherently easier, BCC detection has potential direct clinical applications. Small BCCs are detectable early by dermoscopy and potentially detectable by the automated methods described in this research. © 2011 John Wiley & Sons A/S.

Correction of thin cirrus effects in AVIRIS images using the sensitive 1.375-micron cirrus detecting channel

NASA Technical Reports Server (NTRS)

Gao, Bo-Cai; Kaufman, Yorman J.

1995-01-01

Using spectral imaging data acquired with the Airborne Visible Infrared Imaging Spectrometer (AVIRIS) from an ER-2 aircraft at 20 km altitude during various field programs, it was found that narrow channels near the center of the strong 1.38-micrometer water vapor band are very effective in detecting think cirrus clouds. Based on this observation from AVIRIS data, Gao and Kaufman proposed to put a channel centered at 1.375 micrometers with a width of 30 nm on the Moderate Resolution Imaging Spectrometer (MODIS) for remote sensing of cirrus clouds from space. The sensitivity of the 1.375-micrometer MODIS channel to detect thin cirrus clouds during the day time is expected to be one to two orders of magnitude better than the current infrared emission techniques. As a result, much larger fraction of the satellite data is expected to be identified as being covered by cirrus clouds, some of them so thin that their obscuration of the surface is very small. In order to make better studies of surface reflectance properties, thin cirrus effects must be removed from satellite images. Therefore, there is a need to study radiative properties of thin cirrus clouds, so that a strategy for correction or removal of the thin cirrus effects, similar to the correction of atmospheric aerosol effect, can be formed. In this extended abstract, we describe an empirical approach for removing/correcting thin cirrus effects in AVIRIS images using channels near 1.375 microns - one step beyond the detection of cirrus clouds using these channels.

Technique for ship/wake detection

DOEpatents

Roskovensky, John K [Albuquerque, NM

2012-05-01

An automated ship detection technique includes accessing data associated with an image of a portion of Earth. The data includes reflectance values. A first portion of pixels within the image are masked with a cloud and land mask based on spectral flatness of the reflectance values associated with the pixels. A given pixel selected from the first portion of pixels is unmasked when a threshold number of localized pixels surrounding the given pixel are not masked by the cloud and land mask. A spatial variability image is generated based on spatial derivatives of the reflectance values of the pixels which remain unmasked by the cloud and land mask. The spatial variability image is thresholded to identify one or more regions within the image as possible ship detection regions.

A collaborative computing framework of cloud network and WBSN applied to fall detection and 3-D motion reconstruction.

PubMed

Lai, Chin-Feng; Chen, Min; Pan, Jeng-Shyang; Youn, Chan-Hyun; Chao, Han-Chieh

2014-03-01

As cloud computing and wireless body sensor network technologies become gradually developed, ubiquitous healthcare services prevent accidents instantly and effectively, as well as provides relevant information to reduce related processing time and cost. This study proposes a co-processing intermediary framework integrated cloud and wireless body sensor networks, which is mainly applied to fall detection and 3-D motion reconstruction. In this study, the main focuses includes distributed computing and resource allocation of processing sensing data over the computing architecture, network conditions and performance evaluation. Through this framework, the transmissions and computing time of sensing data are reduced to enhance overall performance for the services of fall events detection and 3-D motion reconstruction.

3D change detection at street level using mobile laser scanning point clouds and terrestrial images

NASA Astrophysics Data System (ADS)

Qin, Rongjun; Gruen, Armin

2014-04-01

Automatic change detection and geo-database updating in the urban environment are difficult tasks. There has been much research on detecting changes with satellite and aerial images, but studies have rarely been performed at the street level, which is complex in its 3D geometry. Contemporary geo-databases include 3D street-level objects, which demand frequent data updating. Terrestrial images provides rich texture information for change detection, but the change detection with terrestrial images from different epochs sometimes faces problems with illumination changes, perspective distortions and unreliable 3D geometry caused by the lack of performance of automatic image matchers, while mobile laser scanning (MLS) data acquired from different epochs provides accurate 3D geometry for change detection, but is very expensive for periodical acquisition. This paper proposes a new method for change detection at street level by using combination of MLS point clouds and terrestrial images: the accurate but expensive MLS data acquired from an early epoch serves as the reference, and terrestrial images or photogrammetric images captured from an image-based mobile mapping system (MMS) at a later epoch are used to detect the geometrical changes between different epochs. The method will automatically mark the possible changes in each view, which provides a cost-efficient method for frequent data updating. The methodology is divided into several steps. In the first step, the point clouds are recorded by the MLS system and processed, with data cleaned and classified by semi-automatic means. In the second step, terrestrial images or mobile mapping images at a later epoch are taken and registered to the point cloud, and then point clouds are projected on each image by a weighted window based z-buffering method for view dependent 2D triangulation. In the next step, stereo pairs of the terrestrial images are rectified and re-projected between each other to check the geometrical consistency between point clouds and stereo images. Finally, an over-segmentation based graph cut optimization is carried out, taking into account the color, depth and class information to compute the changed area in the image space. The proposed method is invariant to light changes, robust to small co-registration errors between images and point clouds, and can be applied straightforwardly to 3D polyhedral models. This method can be used for 3D street data updating, city infrastructure management and damage monitoring in complex urban scenes.

Contributions of Nimbus 7 TOMS Data to Volcanic Study and Hazard Mitigation

NASA Technical Reports Server (NTRS)

Krueger, Arlin J.; Bluth, G. J. S.; Schaefer, S. A.

1998-01-01

Nimbus TOMS data have led to advancements among many volcano-related scientific disciplines, from the initial ability to quantify SO2 clouds leading to derivations of eruptive S budgets and fluxes, to tracking of individual clouds, assessing global volcanism and atmospheric impacts. Some of the major aspects of TOMS-related research, listed below, will be reviewed and updated: (1) Measurement of volcanic SO2 clouds: Nimbus TOMS observed over 100 individual SO2 clouds during its mission lifetime; large explosive eruptions are now routinely and reliably measured by satellite. (2) Eruption processes: quantification of SO2 emissions have allowed assessments of eruption sulfur budgets, the evaluation of "excess" sulfur, and inferences of H2S emissions. (3) Detection of ash: TOMS data are now used to detect volcanic particulates in the atmosphere, providing complementary analyses to infrared methods of detection. Paired TOMS and AVHRR studies have provided invaluable information on volcanic cloud compositions and processes. (4) Cloud tracking and hazard mitigation: volcanic clouds can be considered gigantic tracers in the atmosphere, and studies of the fates of these clouds have led to new knowledge of their physical and chemical dispersion in the atmosphere for predictive models. (5) Global trends: the long term data set has provided researchers an unparalleled record of explosive volcanism, and forms a key component in assessing annual to decadal trends in global S emissions. (6) Atmospheric impacts: TOMS data have been linked to independent records of atmospheric change, in order to compare cause and effect processes following a massive injection of SO2 into the atmosphere. (7) Future TOMS instruments and applications: Nimbus TOMS has given way to new satellite platforms, with several wavelength and resolution modifications. New efforts to launch a geostationary TOMS could provide unprecedented observations of volcanic activity.

Cloud and Aerosol Retrieval for the 2001 GLAS Satellite Lidar Mission

NASA Technical Reports Server (NTRS)

Hart, William D.; Palm, Stephen P.; Spinhirne, James D.

2000-01-01

The Geoscience Laser Altimeter System (GLAS) is scheduled for launch in July of 2001 aboard the Ice, Cloud and Land Elevation Satellite (ICESAT). In addition to being a precision altimeter for mapping the height of the Earth's icesheets, GLAS will be an atmospheric lidar, sensitive enough to detect gaseous, aerosol, and cloud backscatter signals, at horizontal and vertical resolutions of 175 and 75m, respectively. GLAS will be the first lidar to produce temporally continuous atmospheric backscatter profiles with nearly global coverage (94-degree orbital inclination). With a projected operational lifetime of five years, GLAS will collect approximately six billion lidar return profiles. The large volume of data dictates that operational analysis algorithms, which need to keep pace with the data yield of the instrument, must be efficient. So, we need to evaluate the ability of operational algorithms to detect atmospheric constituents that affect global climate. We have to quantify, in a statistical manner, the accuracy and precision of GLAS cloud and aerosol observations. Our poster presentation will show the results of modeling studies that are designed to reveal the effectiveness and sensitivity of GLAS in detecting various atmospheric cloud and aerosol features. The studies consist of analyzing simulated lidar returns. Simulation cases are constructed either from idealized renditions of atmospheric cloud and aerosol layers or from data obtained by the NASA ER-2 Cloud Lidar System (CLS). The fabricated renditions permit quantitative evaluations of operational algorithms to retrieve cloud and aerosol parameters. The use of observational data permits the evaluations of performance for actual atmospheric conditions. The intended outcome of the presentation is that climatology community will be able to use the results of these studies to evaluate and quantify the impact of GLAS data upon atmospheric modeling efforts.

EVALUATING THE MORPHOLOGY OF THE LOCAL INTERSTELLAR MEDIUM: USING NEW DATA TO DISTINGUISH BETWEEN MULTIPLE DISCRETE CLOUDS AND A CONTINUOUS MEDIUM

DOE Office of Scientific and Technical Information (OSTI.GOV)

Redfield, Seth; Linsky, Jeffrey L., E-mail: sredfield@wesleyan.edu, E-mail: jlinsky@jila.colorado.edu

Ultraviolet and optical spectra of interstellar gas along the lines of sight to nearby stars have been interpreted by Redfield and Linsky and previous studies as a set of discrete warm, partially ionized clouds each with a different flow vector, temperature, and metal depletion. Recently, Gry and Jenkins proposed a fundamentally different model consisting of a single cloud with nonrigid flows filling space out to 9 pc from the Sun that they propose better describes the local ISM. Here we test these fundamentally different morphological models against the spatially unbiased Malamut et al. spectroscopic data set, and find that themore » multiple cloud morphology model provides a better fit to both the new and old data sets. The detection of three or more velocity components along the lines of sight to many nearby stars, the presence of nearby scattering screens, the observed thin elongated structures of warm interstellar gas, and the likely presence of strong interstellar magnetic fields also support the multiple cloud model. The detection and identification of intercloud gas and the measurement of neutral hydrogen density in clouds beyond the Local Interstellar Cloud could provide future morphological tests.« less

A statistical retrieval of cloud parameters for the millimeter wave Ice Cloud Imager on board MetOp-SG

NASA Astrophysics Data System (ADS)

Prigent, Catherine; Wang, Die; Aires, Filipe; Jimenez, Carlos

2017-04-01

The meteorological observations from satellites in the microwave domain are currently limited to below 190 GHz. However, the next generation of European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT) Polar System-Second Generation-EPS-SG will carry an instrument, the Ice Cloud Imager (ICI), with frequencies up to 664 GHz, to improve the characterization of the cloud frozen phase. In this paper, a statistical retrieval of cloud parameters for ICI is developed, trained on a synthetic database derived from the coupling of a mesoscale cloud model and radiative transfer calculations. The hydrometeor profiles simulated with the Weather Research and Forecasting model (WRF) for twelve diverse European mid-latitude situations are used to simulate the brightness temperatures with the Atmospheric Radiative Transfer Simulator (ARTS) to prepare the retrieval database. The WRF+ARTS simulations have been compared to the Special Sensor Microwave Imager/Sounder (SSMIS) observations up to 190 GHz: this successful evaluation gives us confidence in the simulations at the ICI channels from 183 to 664 GHz. Statistical analyses have been performed on this simulated retrieval database, showing that it is not only physically realistic but also statistically satisfactory for retrieval purposes. A first Neural Network (NN) classifier is used to detect the cloud presence. A second NN is developed to retrieve the liquid and ice integrated cloud quantities over sea and land separately. The detection and retrieval of the hydrometeor quantities (i.e., ice, snow, graupel, rain, and liquid cloud) are performed with ICI-only, and with ICI combined with observations from the MicroWave Imager (MWI, with frequencies from 19 to 190 GHz, also on board MetOp-SG). The ICI channels have been optimized for the detection and quantification of the cloud frozen phases: adding the MWI channels improves the performance of the vertically integrated hydrometeor contents, especially for the cloud liquid phases. The relative error for the retrieved integrated frozen water content (FWP, i.e., ice+snow+graupel) is below 40% for 0.1kg/m2 < FWP < 0.5kg/m2 and below 20% for FWP > 0.5 kg/m2.

Biologically inspired multi-layered synthetic skin for tactile feedback in prosthetic limbs.

PubMed

Osborn, Luke; Nguyen, Harrison; Betthauser, Joseph; Kaliki, Rahul; Thakor, Nitish

2016-08-01

The human body offers a template for many state-of-the-art prosthetic devices and sensors. In this work, we present a novel, sensorized synthetic skin that mimics the natural multi-layered nature of mechanoreceptors found in healthy glabrous skin to provide tactile information. The multi-layered sensor is made up of flexible piezoresistive textiles that act as force sensitive resistors (FSRs) to convey tactile information, which are embedded within a silicone rubber to resemble the compliant nature of human skin. The top layer of the synthetic skin is capable of detecting small loads less than 5 N whereas the bottom sensing layer responds reliably to loads over 7 N. Finite element analysis (FEA) of a simplified human fingertip and the synthetic skin was performed. Results suggest similarities in behavior during loading. A natural tactile event is simulated by loading the synthetic skin on a prosthetic limb. Results show the sensors' ability to detect applied loads as well as the ability to simulate neural spiking activity based on the derivative and temporal differences of the sensor response. During the tactile loading, the top sensing layer responded 0.24 s faster than the bottom sensing layer. A synthetic biologically-inspired skin such as this will be useful for enhancing the functionality of prosthetic limbs through tactile feedback.

Displacement Threshold Energy and Recovery in an Al-Ti Nanolayered System with Intrinsic Point Defect Partitioning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gerboth, Matthew D.; Setyawan, Wahyu; Henager, Charles H.

2014-01-07

A method is established and validated using molecular dynamics (MD) to determine the displacement threshold energies as Ed in nanolayered, multilayered systems of dissimilar metals. The method is applied to specifically oriented nanolayered films of Al-Ti where the crystal structure and interface orientations are varied in atomic models and Ed is calculated. Methods for defect detection are developed and discussed based on prior research in the literature and based on specific crystallographic directions available in the nanolayered systems. These are compared and contrasted to similar calculations in corresponding bulk materials, including fcc Al, fcc Ti, hcp Al, and hcp Ti.more » In all cases, the calculated Ed in the multilayers are intermediate to the corresponding bulk values but exhibit some important directionality. In the nanolayer, defect detection demonstrated systematic differences in the behavior of Ed in each layer. Importantly, collision cascade damage exhibits significant defect partitioning within the Al and Ti layers that is hypothesized to be an intrinsic property of dissimilar nanolayered systems. This type of partitioning could be partly responsible for observed asymmetric radiation damage responses in many multilayered systems. In addition, a pseudo-random direction was introduced to approximate the average Ed without performing numerous simulations with random directions.« less

A method for quantifying cloud immersion in a tropical mountain forest using time-lapse photography

USGS Publications Warehouse

Bassiouni, Maoya; Scholl, Martha A.; Torres-Sanchez, Angel J.; Murphy, Sheila F.

2017-01-01

Quantifying the frequency, duration, and elevation range of fog or cloud immersion is essential to estimate cloud water deposition in water budgets and to understand the ecohydrology of cloud forests. The goal of this study was to develop a low-cost and high spatial-coverage method to detect occurrence of cloud immersion within a mountain cloud forest by using time-lapse photography. Trail cameras and temperature/relative humidity sensors were deployed at five sites covering the elevation range from the assumed lifting condensation level to the mountain peaks in the Luquillo Mountains of Puerto Rico. Cloud-sensitive image characteristics (contrast, the coefficient of variation and the entropy of pixel luminance, and image colorfulness) were used with a k-means clustering approach to accurately detect cloud-immersed conditions in a time series of images from March 2014 to May 2016. Images provided hydrologically meaningful cloud-immersion information while temperature-relative humidity data were used to refine the image analysis using dew point information and provided temperature gradients along the elevation transect. Validation of the image processing method with human-judgment based classification generally indicated greater than 90% accuracy. Cloud-immersion frequency averaged 80% at sites above 900 m during nighttime hours and 49% during daytime hours, and was consistent with diurnal patterns of cloud immersion measured in a previous study. Results for the 617 m site demonstrated that cloud immersion in the Luquillo Mountains rarely occurs at the previously-reported cloud base elevation of about 600 m (11% during nighttime hours and 5% during daytime hours). The framework presented in this paper will be used to monitor at a low cost and high spatial resolution the long-term variability of cloud-immersion patterns in the Luquillo Mountains, and can be applied to ecohydrology research at other cloud-forest sites or in coastal ecosystems with advective sea fog.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cook, Ryan D.; Lin, Ying-Hsuan; Peng, Zhuoyu

Organic aerosol formation and transformation occurs within aqueous aerosol and cloud droplets, yet little is known about the composition of high molecular weight organic compounds in cloud water. Cloud water samples collected at Whiteface Mountain, New York, during August-September 2014 were analyzed by ultra-high-resolution mass spectrometry to investigate the molecular composition of dissolved organic carbon, with a focus on sulfur- and nitrogen-containing compounds. Organic molecular composition was evaluated in the context of cloud water inorganic ion concentrations, pH, and total organic carbon concentrations to gain insights into the sources and aqueous-phase processes of the observed high molecular weight organic compounds.more » Cloud water acidity was positively correlated with the average oxygen : carbon ratio of the organic constituents, suggesting the possibility for aqueous acid-catalyzed (prior to cloud droplet activation or during/after cloud droplet evaporation) and/or radical (within cloud droplets) oxidation processes. Many tracer compounds recently identified in laboratory studies of bulk aqueous-phase reactions were identified in the cloud water. Organosulfate compounds, with both biogenic and anthropogenic volatile organic compound precursors, were detected for cloud water samples influenced by air masses that had traveled over forested and populated areas. Oxidation products of long-chain (C 10-12) alkane precursors were detected during urban influence. Influence of Canadian wildfires resulted in increased numbers of identified sulfur-containing compounds and oligomeric species, including those formed through aqueous-phase reactions involving methylglyoxal. Light-absorbing aqueous-phase products of syringol and guaiacol oxidation were observed in the wildfire-influenced samples, and dinitroaromatic compounds were observed in all cloud water samples (wildfire, biogenic, and urban-influenced). Overall, the cloud water molecular composition depended on air mass source influence and reflected aqueous-phase reactions involving biogenic, urban, and biomass burning precursors.« less

Wonders in the Antarctic Sea and Sky

NASA Image and Video Library

2017-12-08

Wonders in the Antarctic Sea and Sky NASA aircraft and scientists have returned to the United States after a short ice-surveying mission to #Antarctica. Despite having only a week of flying time, the team returned with crucial scientific data and a trove of spectacular aerial photographs. The flights over Antarctica were part of Operation #IceBridge, a multi-year mission to monitor conditions in Antarctica and the Arctic until a new ice-monitoring satellite, ICESat-2, launches in 2016. ICESat-1 was decommissioned in 2009, and IceBridge aircraft have been flying ever since. Laser altimeter and radar data are the primary products of the mission, but IceBridge project scientist Michael Studinger almost always has his digital camera ready as well. On November 24, 2013, he took this photograph of a multi-layered lenticular cloud hovering near Mount Discovery, a volcano about 70 kilometers (44 miles) southwest of McMurdo. Lenticular #clouds are a type of wave cloud. They usually form when a layer of air near the surface encounters a topographic barrier, gets pushed upward, and flows over it as a series of atmospheric gravity waves. Lenticular clouds form at the crest of the waves, where the air is coolest and water vapor is most likely to condense into cloud droplets. The bulging sea ice in the foreground is a pressure ridge, which formed when separate ice floes collided and piled up on each other. Read more: 1.usa.gov/18lXIQS Photograph courtesy of Michael Studinger. Caption by Adam Voiland of NASA's Earth Observatory. NASA image use policy. NASA Goddard Space Flight Center enables NASA’s mission through four scientific endeavors: Earth Science, Heliophysics, Solar System Exploration, and Astrophysics. Goddard plays a leading role in NASA’s accomplishments by contributing compelling scientific knowledge to advance the Agency’s mission. Follow us on Twitter Like us on Facebook Find us on Instagram

Atmospheric Constraints on the Surface UV Environment of Mars at 3.9 Ga Relevant to Prebiotic Chemistry

NASA Astrophysics Data System (ADS)

Ranjan, Sukrit; Wordsworth, Robin; Sasselov, Dimitar D.

2017-08-01

Recent findings suggest that Mars may have been a clement environment for the emergence of life and may even have compared favorably to Earth in this regard. These findings have revived interest in the hypothesis that prebiotically important molecules or even nascent life may have formed on Mars and been transferred to Earth. UV light plays a key role in prebiotic chemistry. Characterizing the early martian surface UV environment is key to understanding how Mars compares to Earth as a venue for prebiotic chemistry. Here, we present two-stream, multilayer calculations of the UV surface radiance on Mars at 3.9 Ga to constrain the surface UV environment as a function of atmospheric state. We explore a wide range of atmospheric pressures, temperatures, and compositions that correspond to the diversity of martian atmospheric states consistent with available constraints. We include the effects of clouds and dust. We calculate dose rates to quantify the effect of different atmospheric states on UV-sensitive prebiotic chemistry. We find that, for normative clear-sky CO2-H2O atmospheres, the UV environment on young Mars is comparable to young Earth. This similarity is robust to moderate cloud cover; thick clouds (τcloud ≥ 100) are required to significantly affect the martian UV environment, because cloud absorption is degenerate with atmospheric CO2. On the other hand, absorption from SO2, H2S, and dust is nondegenerate with CO2, meaning that, if these constituents build up to significant levels, surface UV fluence can be suppressed. These absorbers have spectrally variable absorption, meaning that their presence affects prebiotic pathways in different ways. In particular, high SO2 environments may admit UV fluence that favors pathways conducive to abiogenesis over pathways unfavorable to it. However, better measurements of the spectral quantum yields of these pathways are required to evaluate this hypothesis definitively.

Detecting the building blocks of aromatics

NASA Astrophysics Data System (ADS)

Joblin, Christine; Cernicharo, José

2018-01-01

Interstellar clouds are sites of active organic chemistry (1). Many small, gasphase molecules are found in the dark parts of the clouds that are protected from ultraviolet (UV) photons, but these molecules photodissociate in the external layers of the cloud that are exposed to stellar radiation (see the photo). These irradiated regions are populated by large polycyclic aromatic hydrocarbons (PAHs) with characteristic infrared (IR) emission features. These large aromatics are expected to form from benzene (C6H6), which is, however, difficult to detect because it does not have a permanent dipole moment and can only be detected via its IR absorption transitions against a strong background source (2). On page 202 of this issue, McGuire et al. (3) report the detection of benzonitrile (c-C6H5CN) with radio telescopes. Benzonitrile likely forms in the reaction of CN with benzene; from its observation, it is therefore possible to estimate the abundance of benzene itself.

Cloud point extraction and determination of trace trichlorfon by high performance liquid chromatography with ultraviolet-detection based on its catalytic effect on benzidine oxidizing.

PubMed

Zhu, Hai-Zhen; Liu, Wei; Mao, Jian-Wei; Yang, Ming-Min

2008-04-28

4-Amino-4'-nitrobiphenyl, which is formed by catalytic effect of trichlorfon on sodium perborate oxidizing benzidine, is extracted with a cloud point extraction method and then detected using a high performance liquid chromatography with ultraviolet detection (HPLC-UV). Under the optimum experimental conditions, there was a linear relationship between trichlorfon in the concentration range of 0.01-0.2 mgL(-1) and the peak areas of 4-amino-4'-nitrobiphenyl (r=0.996). Limit of detection was 2.0 microgL(-1), recoveries of spiked water and cabbage samples ranged between 95.4-103 and 85.2-91.2%, respectively. It was proved that the cloud point extraction (CPE) method was simple, cheap, and environment friendly than extraction with organic solvents and had more effective extraction yield.

Cloud-Free Satellite Image Mosaics with Regression Trees and Histogram Matching.

Treesearch

E.H. Helmer; B. Ruefenacht

2005-01-01

Cloud-free optical satellite imagery simplifies remote sensing, but land-cover phenology limits existing solutions to persistent cloudiness to compositing temporally resolute, spatially coarser imagery. Here, a new strategy for developing cloud-free imagery at finer resolution permits simple automatic change detection. The strategy uses regression trees to predict...

Detection Thresholds of Falling Snow From Satellite-Borne Active and Passive Sensors

NASA Technical Reports Server (NTRS)

Skofronick-Jackson, Gail M.; Johnson, Benjamin T.; Munchak, S. Joseph

2013-01-01

There is an increased interest in detecting and estimating the amount of falling snow reaching the Earths surface in order to fully capture the global atmospheric water cycle. An initial step toward global spaceborne falling snow algorithms for current and future missions includes determining the thresholds of detection for various active and passive sensor channel configurations and falling snow events over land surfaces and lakes. In this paper, cloud resolving model simulations of lake effect and synoptic snow events were used to determine the minimum amount of snow (threshold) that could be detected by the following instruments: the W-band radar of CloudSat, Global Precipitation Measurement (GPM) Dual-Frequency Precipitation Radar (DPR)Ku- and Ka-bands, and the GPM Microwave Imager. Eleven different nonspherical snowflake shapes were used in the analysis. Notable results include the following: 1) The W-band radar has detection thresholds more than an order of magnitude lower than the future GPM radars; 2) the cloud structure macrophysics influences the thresholds of detection for passive channels (e.g., snow events with larger ice water paths and thicker clouds are easier to detect); 3) the snowflake microphysics (mainly shape and density)plays a large role in the detection threshold for active and passive instruments; 4) with reasonable assumptions, the passive 166-GHz channel has detection threshold values comparable to those of the GPM DPR Ku- and Ka-band radars with approximately 0.05 g *m(exp -3) detected at the surface, or an approximately 0.5-1.0-mm * h(exp -1) melted snow rate. This paper provides information on the light snowfall events missed by the sensors and not captured in global estimates.

Water Ice Clouds as Seen from the Mars Exploration Rovers

NASA Astrophysics Data System (ADS)

Wolff, M. J.; Clancy, R. T.; Banfield, D.; Cuozzo, K.

2005-12-01

Water ice clouds that bear a striking resemblance to terrestrial cirrus (e.g., "Mare's tails") have been observed by the Panoramic Camera (Pancam), the Navigation Camera (Navcam), the Hazard Camera (Hazcam), and the Minature Thermal Emission Spectrometer (Mini-TES) on board the Mars Exploration Rovers (MER). Such phenomena represent an opportunity to characterize local and regional scale meteorology as well as our understanding of the processes involved. However, a necessary first-step is to adequately describe some basic properties of the detected clouds: 1) when are the clouds present (i.e., local time, season, etc.)? 2) where are the clouds present? That is to say, what is the relative frequency between the two rover sites as well as the connection to detections from orbiting spacecraft. 3) what are the observed morphologies? 4) what are the projected velocities (i.e., wind speeds and directions) associated with the clouds? 5) what is the abundance of water ice nuclei (i.e., optical depth)? Our talk will summarize our progress in answering the above questions, as well as provide initial results in connecting the observations to more global behavior in the Martian climate.

Detecting Abnormal Machine Characteristics in Cloud Infrastructures

NASA Technical Reports Server (NTRS)

Bhaduri, Kanishka; Das, Kamalika; Matthews, Bryan L.

2011-01-01

In the cloud computing environment resources are accessed as services rather than as a product. Monitoring this system for performance is crucial because of typical pay-peruse packages bought by the users for their jobs. With the huge number of machines currently in the cloud system, it is often extremely difficult for system administrators to keep track of all machines using distributed monitoring programs such as Ganglia1 which lacks system health assessment and summarization capabilities. To overcome this problem, we propose a technique for automated anomaly detection using machine performance data in the cloud. Our algorithm is entirely distributed and runs locally on each computing machine on the cloud in order to rank the machines in order of their anomalous behavior for given jobs. There is no need to centralize any of the performance data for the analysis and at the end of the analysis, our algorithm generates error reports, thereby allowing the system administrators to take corrective actions. Experiments performed on real data sets collected for different jobs validate the fact that our algorithm has a low overhead for tracking anomalous machines in a cloud infrastructure.

One-step production of multilayered microparticles by tri-axial electro-flow focusing

NASA Astrophysics Data System (ADS)

Si, Ting; Feng, Hanxin; Li, Yang; Luo, Xisheng; Xu, Ronald

2014-03-01

Microencapsulation of drugs and imaging agents in the same carrier is of great significance for simultaneous detection and treatment of diseases. In this work, we have developed a tri-axial electro-flow focusing (TEFF) device using three needles with a novel concentric arrangement to one-step form multilayered microparticles. The TEFF process can be characterized as a multi-fluidic compound cone-jet configuration in the core of a high-speed coflowing gas stream under an axial electric field. The tri-axial liquid jet eventually breaks up into multilayered droplets. To validate the method, the effect of main process parameters on characteristics of the cone and the jet has been studied experimentally. The applied electric field can dramatically promote the stability of the compound cone and enhance the atomization of compound liquid jets. Microparticles with both three-layer, double-layer and single-layer structures have been obtained. The results show that the TEFF technique has great benefits in fabricating multilayered microparticles at smaller scales. This method will be able to one-step encapsulate multiple therapeutic and imaging agents for biomedical applications such as multi-modal imaging, drug delivery and biomedicine.

Determination of Cloud Base Height, Wind Velocity, and Short-Range Cloud Structure Using Multiple Sky Imagers Field Campaign Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, Dong; Schwartz, Stephen E.; Yu, Dantong

Clouds are a central focus of the U.S. Department of Energy (DOE)’s Atmospheric System Research (ASR) program and Atmospheric Radiation Measurement (ARM) Climate Research Facility, and more broadly are the subject of much investigation because of their important effects on atmospheric radiation and, through feedbacks, on climate sensitivity. Significant progress has been made by moving from a vertically pointing (“soda-straw”) to a three-dimensional (3D) view of clouds by investing in scanning cloud radars through the American Recovery and Reinvestment Act of 2009. Yet, because of the physical nature of radars, there are key gaps in ARM's cloud observational capabilities. Formore » example, cloud radars often fail to detect small shallow cumulus and thin cirrus clouds that are nonetheless radiatively important. Furthermore, it takes five to twenty minutes for a cloud radar to complete a 3D volume scan and clouds can evolve substantially during this period. Ground-based stereo-imaging is a promising technique to complement existing ARM cloud observation capabilities. It enables the estimation of cloud coverage, height, horizontal motion, morphology, and spatial arrangement over an extended area of up to 30 by 30 km at refresh rates greater than 1 Hz (Peng et al. 2015). With fine spatial and temporal resolution of modern sky cameras, the stereo-imaging technique allows for the tracking of a small cumulus cloud or a thin cirrus cloud that cannot be detected by a cloud radar. With support from the DOE SunShot Initiative, the Principal Investigator (PI)’s team at Brookhaven National Laboratory (BNL) has developed some initial capability for cloud tracking using multiple distinctly located hemispheric cameras (Peng et al. 2015). To validate the ground-based cloud stereo-imaging technique, the cloud stereo-imaging field campaign was conducted at the ARM Facility’s Southern Great Plains (SGP) site in Oklahoma from July 15 to December 24. As shown in Figure 1, the cloud stereo-imaging system consisted of two inexpensive high-definition (HD) hemispheric cameras (each cost less than $1,500) and ARM’s Total Sky Imager (TSI). Together with other co-located ARM instrumentation, the campaign provides a promising opportunity to validate stereo-imaging-based cloud base height and, more importantly, to examine the feasibility of cloud thickness retrieval for low-view-angle clouds.« less

A high-resolution oxygen A-band spectrometer (HABS) and its radiation closure

NASA Astrophysics Data System (ADS)

Min, Q.; Yin, B.; Li, S.; Berndt, J.; Harrison, L.; Joseph, E.; Duan, M.; Kiedron, P.

2014-02-01

The pressure dependence of oxygen A-band absorption enables the retrieval of the vertical profiles of aerosol and cloud properties from oxygen A-band spectrometry. To improve the understanding of oxygen A-band inversions and utility, we developed a high-resolution oxygen A-band spectrometer (HABS), and deployed it at Howard University Beltsville site during the NASA Discover Air-Quality Field Campaign in July 2011. The HABS has the ability to measure solar direct-beam and zenith diffuse radiation through a telescope automatically. It exhibits excellent performance: stable spectral response ratio, high signal-to-noise ratio (SNR), high spectrum resolution (0.16 nm), and high Out-of-Band Rejection (10-5). To evaluate the spectra performance of HABS, a HABS simulator has been developed by combing the discrete ordinates radiative transfer (DISORT) code with the High Resolution Transmission (HTRAN) database HITRAN2008. The simulator uses double-k approach to reduce the computational cost. The HABS measured spectra are consistent with the related simulated spectra. For direct-beam spectra, the confidence intervals (95%) of relative difference between measurements and simulation are (-0.06, 0.05) and (-0.08, 0.09) for solar zenith angles of 27° and 72°, respectively. The main differences between them occur at or near the strong oxygen absorption line centers. They are mainly caused by the noise/spikes of HABS measured spectra, as a result of combined effects of weak signal, low SNR, and errors in wavelength registration and absorption line parameters. The high-resolution oxygen A-band measurements from HABS can constrain the active radar retrievals for more accurate cloud optical properties, particularly for multi-layer clouds and for mixed-phase clouds.

Recent observations of organic molecules in nearby cold, dark interstellar clouds

NASA Technical Reports Server (NTRS)

Suzuki, H.; Ohishi, M.; Morimoto, M.; Kaifu, N.; Friberg, P.

1985-01-01

Recent investigations of the organic chemistry of relatively nearby cold, dark interstellar clouds are reported. Specifically, the presence of interstellar tricarbon monoxide (C3O) in Taurus Molecular Cloud 1 (TMC-1) is confirmed. The first detection in such regions of acetaldehyde (CH3CHO), the most complex oxygen-containing organic molecule yet found in dark clouds is reported, as well as the first astronomical detection of several molecular rotational transitions, including the J = 18-17 and 14-13 transitions of cyanodiacetylene (HC5N), the 1(01)-0(00) transition of acetaldehyde, and the J = 5-4 transition of C3O. A significant upper limit is set on the abundance of cyanocarbene (HCCN) as a result of the first reported interstellar search for this molecule.

First stars of the ρ Ophiuchi dark cloud. XMM-Newton view of ρ Oph and its neighbors

NASA Astrophysics Data System (ADS)

Pillitteri, I.; Wolk, S. J.; Chen, H. H.; Goodman, A.

2016-08-01

Star formation in molecular clouds can be triggered by the dynamical action of winds from massive stars. Furthermore, X-ray and UV fluxes from massive stars can influence the life time of surrounding circumstellar disks. We present the results of a 53 ks XMM-Newton observation centered on the ρ Ophiuchi A+B binary system. ρ Ophiuchi lies in the center of a ring of dust, likely formed by the action of its winds. This region is different from the dense core of the cloud (L1688 Core F) where star formation is at work. X-rays are detected from ρ Ophiuchi as well as a group of surrounding X-ray sources. We detected 89 X-ray sources, 47 of them have at least one counterpart in 2MASS+All-WISE catalogs. Based on IR and X-ray properties, we can distinguish between young stellar objects (YSOs) belonging to the cloud and background objects. Among the cloud members, we detect three debris-disk objects and 22 disk-less - Class III young stars.We show that these stars have ages in 5-10 Myr, and are significantly older than the YSOs in L1688. We speculate that they are the result of an early burst of star formation in the cloud. An X-ray energy of ≥5 × 1044 erg has been injected into the surrounding mediumover the past 5 Myr, we discuss the effects of such energy budget in relation to the cloud properties and dynamics.

Change Analysis in Structural Laser Scanning Point Clouds: The Baseline Method

PubMed Central

Shen, Yueqian; Lindenbergh, Roderik; Wang, Jinhu

2016-01-01

A method is introduced for detecting changes from point clouds that avoids registration. For many applications, changes are detected between two scans of the same scene obtained at different times. Traditionally, these scans are aligned to a common coordinate system having the disadvantage that this registration step introduces additional errors. In addition, registration requires stable targets or features. To avoid these issues, we propose a change detection method based on so-called baselines. Baselines connect feature points within one scan. To analyze changes, baselines connecting corresponding points in two scans are compared. As feature points either targets or virtual points corresponding to some reconstructable feature in the scene are used. The new method is implemented on two scans sampling a masonry laboratory building before and after seismic testing, that resulted in damages in the order of several centimeters. The centres of the bricks of the laboratory building are automatically extracted to serve as virtual points. Baselines connecting virtual points and/or target points are extracted and compared with respect to a suitable structural coordinate system. Changes detected from the baseline analysis are compared to a traditional cloud to cloud change analysis demonstrating the potential of the new method for structural analysis. PMID:28029121

Surface-induced brightness temperature variations and their effects on detecting thin cirrus clouds using IR emission channels in the 8-12 micrometer region

NASA Technical Reports Server (NTRS)

Gao, Bo-Cai; Wiscombe, W. J.

1993-01-01

A method for detecting cirrus clouds in terms of brightness temperature differences between narrow bands at 8, 11, and 12 mu m has been proposed by Ackerman et al. (1990). In this method, the variation of emissivity with wavelength for different surface targets was not taken into consideration. Based on state-of-the-art laboratory measurements of reflectance spectra of terrestrial materials by Salisbury and D'Aria (1992), we have found that the brightness temperature differences between the 8 and 11 mu m bands for soils, rocks and minerals, and dry vegetation can vary between approximately -8 K and +8 K due solely to surface emissivity variations. We conclude that although the method of Ackerman et al. is useful for detecting cirrus clouds over areas covered by green vegetation, water, and ice, it is less effective for detecting cirrus clouds over areas covered by bare soils, rocks and minerals, and dry vegetation. In addition, we recommend that in future the variation of surface emissivity with wavelength should be taken into account in algorithms for retrieving surface temperatures and low-level atmospheric temperature and water vapor profiles.

Change Analysis in Structural Laser Scanning Point Clouds: The Baseline Method.

PubMed

Shen, Yueqian; Lindenbergh, Roderik; Wang, Jinhu

2016-12-24

A method is introduced for detecting changes from point clouds that avoids registration. For many applications, changes are detected between two scans of the same scene obtained at different times. Traditionally, these scans are aligned to a common coordinate system having the disadvantage that this registration step introduces additional errors. In addition, registration requires stable targets or features. To avoid these issues, we propose a change detection method based on so-called baselines. Baselines connect feature points within one scan. To analyze changes, baselines connecting corresponding points in two scans are compared. As feature points either targets or virtual points corresponding to some reconstructable feature in the scene are used. The new method is implemented on two scans sampling a masonry laboratory building before and after seismic testing, that resulted in damages in the order of several centimeters. The centres of the bricks of the laboratory building are automatically extracted to serve as virtual points. Baselines connecting virtual points and/or target points are extracted and compared with respect to a suitable structural coordinate system. Changes detected from the baseline analysis are compared to a traditional cloud to cloud change analysis demonstrating the potential of the new method for structural analysis.

Daytime sea fog retrieval based on GOCI data: a case study over the Yellow Sea.

PubMed

Yuan, Yibo; Qiu, Zhongfeng; Sun, Deyong; Wang, Shengqiang; Yue, Xiaoyuan

2016-01-25

In this paper, a new daytime sea fog detection algorithm has been developed by using Geostationary Ocean Color Imager (GOCI) data. Based on spectral analysis, differences in spectral characteristics were found over different underlying surfaces, which include land, sea, middle/high level clouds, stratus clouds and sea fog. Statistical analysis showed that the Rrc (412 nm) (Rayleigh Corrected Reflectance) of sea fog pixels is approximately 0.1-0.6. Similarly, various band combinations could be used to separate different surfaces. Therefore, three indices (SLDI, MCDI and BSI) were set to discern land/sea, middle/high level clouds and fog/stratus clouds, respectively, from which it was generally easy to extract fog pixels. The remote sensing algorithm was verified using coastal sounding data, which demonstrated that the algorithm had the ability to detect sea fog. The algorithm was then used to monitor an 8-hour sea fog event and the results were consistent with observational data from buoys data deployed near the Sheyang coast (121°E, 34°N). The goal of this study was to establish a daytime sea fog detection algorithm based on GOCI data, which shows promise for detecting fog separately from stratus.

Search for molecular absorptions with the Fourier Transform Spectrometer

NASA Technical Reports Server (NTRS)

Knacke, Roger F.

1995-01-01

The objective of this research was a search for water molecules in the gas phase in molecular clouds. Water should be among the most abundant gases in the clouds and is of fundamental importance in gas chemistry, cloud cooling, shock wave chemistry, and gas-grain interactions of interstellar dust. Detection of water in Comet Halley in the 2.7 micron v(3) band in 1986 had shown that airborne H2O observations are feasible (ground-based observations of H2O are impossible because of the massive water content of the atmosphere). We planned to observe the v(3) band in interstellar clouds where a number of lines of this band should be in absorption. The search for H2O commenced in 1988 with a two flight program on the KAO. this resulted in a detection of interstellar H2O with S/N of 2-4 in the v(3) 1(01)-2(02) line at 3801.42/cm. A subsequent flight series of two flights in 1989 resulted in confirmation to the 3801.42/cm line detection and the detection of altogether four strong lines in the 000-001 v(3) vibration-rotation band of H2O.

Highly Tunable Aptasensing Microarrays with Graphene Oxide Multilayers

NASA Astrophysics Data System (ADS)

Jung, Yun Kyung; Lee, Taemin; Shin, Eeseul; Kim, Byeong-Su

2013-11-01

A highly tunable layer-by-layer (LbL)-assembled graphene oxide (GO) array has been devised for high-throughput multiplex protein sensing. In this array, the fluorescence of different target-bound aptamers labeled with dye is efficiently quenched by GO through fluorescence resonance energy transfer (FRET), and simultaneous multiplex target detection is performed by recovering the quenched fluorescence caused by specific binding between an aptamer and a protein. Thin GO films consisting of 10 bilayers displayed a high quenching ability, yielding over 85% fluorescence quenching with the addition of a 2 μM dye-labeled aptamer. The limit for human thrombin detection in the 6- and 10-bilayered GO array is estimated to be 0.1 and 0.001 nM, respectively, indicating highly tunable nature of LbL assembled GO multilayers in controlling the sensitivity of graphene-based FRET aptasensor. Furthermore, the GO chip could be reused up to four times simply by cleaning it with distilled water.

Simultaneous determination of dopamine and uric acid using layer-by-layer graphene and chitosan assembled multilayer films.

PubMed

Weng, Xuexiang; Cao, Qingxue; Liang, Lixin; Chen, Jianrong; You, Chunping; Ruan, Yongmin; Lin, Hongjun; Wu, Lanju

2013-12-15

Multilayer films containing graphene (Gr) and chitosan (CS) were prepared on glassy carbon electrodes with layer-by-layer (LBL) assembly technique. After being characterized with cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS) and scanning electron microscopy (SEM), the electrochemical sensor based on the resulted films was developed to simultaneously determine dopamine (DA) and uric acid (UA). The LBL assembled electrode showed excellent electrocatalytic activity towards the oxidation of DA and UA. In addition, the self-assembly electrode possessed an excellent sensing performance for detection of DA and UA with a linear range from 0.1 μM to 140 µM and from 1.0 µM to 125 µM with the detection limit as low as 0.05 µM and 0.1 µM based on S/N=3, respectively. © 2013 Elsevier B.V. All rights reserved.

Fast and accurate metrology of multi-layered ceramic materials by an automated boundary detection algorithm developed for optical coherence tomography data

PubMed Central

Ekberg, Peter; Su, Rong; Chang, Ernest W.; Yun, Seok Hyun; Mattsson, Lars

2014-01-01

Optical coherence tomography (OCT) is useful for materials defect analysis and inspection with the additional possibility of quantitative dimensional metrology. Here, we present an automated image-processing algorithm for OCT analysis of roll-to-roll multilayers in 3D manufacturing of advanced ceramics. It has the advantage of avoiding filtering and preset modeling, and will, thus, introduce a simplification. The algorithm is validated for its capability of measuring the thickness of ceramic layers, extracting the boundaries of embedded features with irregular shapes, and detecting the geometric deformations. The accuracy of the algorithm is very high, and the reliability is better than 1 µm when evaluating with the OCT images using the same gauge block step height reference. The method may be suitable for industrial applications to the rapid inspection of manufactured samples with high accuracy and robustness. PMID:24562018

Engaging observers to look at clouds from both sides: connecting NASA mission science with authentic STEM experiences

NASA Astrophysics Data System (ADS)

Chambers, L. H.; Taylor, J.; Ellis, T. D.; McCrea, S.; Rogerson, T. M.; Falcon, P.

2016-12-01

In 1997, NASA's Clouds and the Earth's Radiant Energy System (CERES) team began engaging K-12 schools as ground truth observers of clouds. CERES seeks to understand cloud effects on Earth's energy budget; thus accurate detection and characterization of clouds is key. While satellite remote sensing provides global information about clouds, it is limited in time and resolution. Ground observers, on the other hand, can observe clouds at any time of day (and sometimes night), and can see small and thin clouds that are challenging to detect from space. In 2006, two active sensing satellites, CloudSat and CALIPSO, were launched into the A-Train, which already contained 2 CERES instruments on the Aqua spacecraft. The CloudSat team also engaged K-12 schools to observe clouds, through The GLOBE Program, with a specialized observation protocol customized for the narrow radar swath. While providing valuable data for satellite assessment, these activities also engage participants in accessible, authentic science that gets people outdoors, helps them develop observation skills, and is friendly to all ages. The effort has evolved substantially since 1997, adopting new technology to provide a more compelling experience to citizen observers. Those who report within 15 minutes of the passage of a wide range of satellites (Terra, Aqua, CloudSat, CALIPSO, NPP, as well as a number of geostationary satellites) are sent a satellite image centered on their location and are invited to extend the experience beyond simple observation to include analysis of the two different viewpoints. Over the years these projects have collected large amounts of cloud observations from every continent and ocean basin on Earth. A number of studies have been conducted comparing the ground observations to the satellite results. This presentation will provide an overview of those results and also describe plans for a coordinated, thematic cloud observation and data analysis activity going forward.

Marine stratocumulus cloud characteristics from multichannel satellite measurements

NASA Technical Reports Server (NTRS)

Durkee, Philip A.; Mineart, Gary M.

1990-01-01

Understanding the effects of aerosols on the microphysical characteristics of marine stratocumulus clouds, and the resulting influence on cloud radiative properties, is a primary goal of FIRE. The potential for observing variations of cloud characteristics that might be related to variations of available aerosols is studied. Some results from theoretical estimates of cloud reflectance are presented. Also presented are the results of comparisons between aircraft measured microphysical characteristics and satellite detected radiative properties of marine stratocumulus clouds. These results are extracted from Mineart where the analysis procedures and a full discussion of the observations are presented. Only a brief description of the procedures and the composite results are presented.

The Q Continuum: Encounter with the Cloud Mask

NASA Astrophysics Data System (ADS)

Ackerman, S. A.; Frey, R.; Holz, R.; Philips, C.; Dutcher, S.

2017-12-01

We are developing a common cloud mask for MODIS and VIIRS observations, referred to as the MODIS VIIRS Continuity Mask (MVCM). Our focus is on extending the MODIS-heritage cloud detection approach in order to generate appropriate climate data records for clouds and climate studies. The MVCM is based on heritage from the MODIS cloud mask (MOD35 and MYD35) and employs a series of tests on MODIS reflectances and brightness temperatures. Cloud detection is based on contrasts (i.e., cloud versus background surface) at pixel resolution. The MVCM follows the same approach. These cloud masks use multiple cloud detection tests to indicate the confidence level that the observation is of a clear-sky scene. The outcome of a test ranges from 0 (cloudy) to 1 (clear-sky scene). Because of overlap in the sensitivities of the various spectral tests to the type of cloud, each test is considered in one of several groups. The final cloud mask is determined from the product of the minimum confidence of each group and is referred to as the Q value as defined in Ackerman et al (1998). In MOD35 and MYD35 processing, the Q value is not output, rather predetermined Q values determine the result: If Q ≥ .99 the scene is clear; .95 ≤ Q < .99 the pixel is probably a clear scene, .66 ≤ Q < .95 is probably cloudy and Q < .66 is cloudy. Thus representing Q discretely and not as a continuum. For the MVCM, the numerical value of the Q is output along with the classification of clear, probably clear, probably cloudy, and cloudy. Through comparisons with collocated CALIOP and MODIS observations, we will assess the categorization of the Q values as a function of scene type ). While validation studies have indicated the utility and statistical correctness of the cloud mask approach, the algorithm does not possess immeasurable power and perfection. This comparison will assess the time and space dependence of Q and assure that the laws of physics are followed, at least according to normal human notions. Using CALIOP as representing truth, a receiver operating characteristic curve (ROC) will be analyzed to determine the optimum Q for various scenes and seasons, thus providing a continuum of discriminating thresholds.

Magnetoresistive flux focusing eddy current flaw detection

NASA Technical Reports Server (NTRS)

Wincheski, Russell A. (Inventor); Simpson, John W. (Inventor); Namkung, Min (Inventor)

2005-01-01

A giant magnetoresistive flux focusing eddy current device effectively detects deep flaws in thick multilayer conductive materials. The probe uses an excitation coil to induce eddy currents in conducting material perpendicularly oriented to the coil's longitudinal axis. A giant magnetoresistive (GMR) sensor, surrounded by the excitation coil, is used to detect generated fields. Between the excitation coil and GMR sensor is a highly permeable flux focusing lens which magnetically separates the GMR sensor and excitation coil and produces high flux density at the outer edge of the GMR sensor. The use of feedback inside the flux focusing lens enables complete cancellation of the leakage fields at the GMR sensor location and biasing of the GMR sensor to a location of high magnetic field sensitivity. In an alternate embodiment, a permanent magnet is positioned adjacent to the GMR sensor to accomplish the biasing. Experimental results have demonstrated identification of flaws up to 1 cm deep in aluminum alloy structures. To detect deep flaws about circular fasteners or inhomogeneities in thick multilayer conductive materials, the device is mounted in a hand-held rotating probe assembly that is connected to a computer for system control, data acquisition, processing and storage.

Magnetoresistive Flux Focusing Eddy Current Flaw Detection

NASA Technical Reports Server (NTRS)

Wincheski, Russell A. (Inventor); Namkung, Min (Inventor); Simpson, John W. (Inventor)

2005-01-01

A giant magnetoresistive flux focusing eddy current device effectively detects deep flaws in thick multilayer conductive materials. The probe uses an excitation coil to induce eddy currents in conducting material perpendicularly oriented to the coil s longitudinal axis. A giant magnetoresistive (GMR) sensor, surrounded by the excitation coil, is used to detect generated fields. Between the excitation coil and GMR sensor is a highly permeable flux focusing lens which magnetically separates the GMR sensor and excitation coil and produces high flux density at the outer edge of the GMR sensor. The use of feedback inside the flux focusing lens enables complete cancellation of the leakage fields at the GMR sensor location and biasing of the GMR sensor to a location of high magnetic field sensitivity. In an alternate embodiment, a permanent magnet is positioned adjacent to the GMR sensor to accomplish the biasing. Experimental results have demonstrated identification of flaws up to 1 cm deep in aluminum alloy structures. To detect deep flaws about circular fasteners or inhomogeneities in thick multi-layer conductive materials, the device is mounted in a hand-held rotating probe assembly that is connected to a computer for system control, data acquisition, processing and storage.

Cold Water Vapor in the Barnard 5 Molecular Cloud

NASA Technical Reports Server (NTRS)

Wirstrom, E. S.; Charnley, S. B.; Persson, C. M.; Buckle, J. V.; Cordiner, M. A.; Takakuwa, S.

2014-01-01

After more than 30 yr of investigations, the nature of gas-grain interactions at low temperatures remains an unresolved issue in astrochemistry. Water ice is the dominant ice found in cold molecular clouds; however, there is only one region where cold ((is) approximately 10 K) water vapor has been detected-L1544. This study aims to shed light on ice desorption mechanisms under cold cloud conditions by expanding the sample. The clumpy distribution of methanol in dark clouds testifies to transient desorption processes at work-likely to also disrupt water ice mantles. Therefore, the Herschel HIFI instrument was used to search for cold water in a small sample of prominent methanol emission peaks. We report detections of the ground-state transition of o-H2O (J = 110-101) at 556.9360 GHz toward two positions in the cold molecular cloud, Barnard 5. The relative abundances of methanol and water gas support a desorption mechanism which disrupts the outer ice mantle layers, rather than causing complete mantle removal.

Cloud cover determination in polar regions from satellite imagery

NASA Technical Reports Server (NTRS)

Barry, R. G.; Key, J.

1989-01-01

The objectives are to develop a suitable validation data set for evaluating the effectiveness of the International Satellite Cloud Climatology Project (ISCCP) algorithm for cloud retrieval in polar regions, to identify limitations of current procedures and to explore potential means to remedy them using textural classifiers, and to compare synoptic cloud data from model runs with observations. Toward the first goal, a polar data set consisting of visible, thermal, and passive microwave data was developed. The AVHRR and SMMR data were digitally merged to a polar stereographic projection with an effective pixel size of 5 sq km. With this data set, two unconventional methods of classifying the imagery for the analysis of polar clouds and surfaces were examined: one based on fuzzy sets theory and another based on a trained neural network. An algorithm for cloud detection was developed from an early test version of the ISCCP algorithm. This algorithm includes the identification of surface types with passive microwave, then temporal tests at each pixel location in the cloud detection phase. Cloud maps and clear sky radiance composites for 5 day periods are produced. Algorithm testing and validation was done with both actural AVHRR/SMMR data, and simulated imagery. From this point in the algorithm, groups of cloud pixels are examined for their spectral and textural characteristics, and a procedure is developed for the analysis of cloud patterns utilizing albedo, IR temperature, and texture. In a completion of earlier work, empirical analyses of arctic cloud cover were explored through manual interpretations of DMSP imagery and compared to U.S. Air Force 3D-nephanalysis. Comparisons of observed cloudiness from existing climatologies to patterns computed by the GISS climate model were also made.

Reconciling Ground-Based and Space-Based Estimates of the Frequency of Occurrence and Radiative Effect of Clouds around Darwin, Australia

DOE Office of Scientific and Technical Information (OSTI.GOV)

Protat, Alain; Young, Stuart; McFarlane, Sally A.

2014-02-01

The objective of this paper is to investigate whether estimates of the cloud frequency of occurrence and associated cloud radiative forcing as derived from ground-based and satellite active remote sensing and radiative transfer calculations can be reconciled over a well instrumented active remote sensing site located in Darwin, Australia, despite the very different viewing geometry and instrument characteristics. It is found that the ground-based radar-lidar combination at Darwin does not detect most of the cirrus clouds above 10 km (due to limited lidar detection capability and signal obscuration by low-level clouds) and that the CloudSat radar - Cloud-Aerosol Lidar withmore » Orthogonal Polarization (CALIOP) combination underreports the hydrometeor frequency of occurrence below 2 km height, due to instrument limitations at these heights. The radiative impact associated with these differences in cloud frequency of occurrence is large on the surface downwelling shortwave fluxes (ground and satellite) and the top-of atmosphere upwelling shortwave and longwave fluxes (ground). Good agreement is found for other radiative fluxes. Large differences in radiative heating rate as derived from ground and satellite radar-lidar instruments and RT calculations are also found above 10 km (up to 0.35 Kday-1 for the shortwave and 0.8 Kday-1 for the longwave). Given that the ground-based and satellite estimates of cloud frequency of occurrence and radiative impact cannot be fully reconciled over Darwin, caution should be exercised when evaluating the representation of clouds and cloud-radiation interactions in large-scale models and limitations of each set of instrumentation should be considered when interpreting model-observations differences.« less

Macrophysical Properties of Tropical Cirrus Clouds from the CALIPSO Satellite and from Ground-based Micropulse and Raman Lidars

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thorsen, Tyler J.; Fu, Qiang; Comstock, Jennifer M.

2013-08-27

Lidar observations of cirrus cloud macrophysical properties over the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) program Darwin, Australia site are compared from the Cloud-Aerosol Lidar and In- frared Pathfinder Satellite Observation (CALIPSO) satellite, the ground-based ARM micropulse lidar (MPL), and the ARM Raman lidar (RL). Comparisons are made using the subset of profiles where the lidar beam is not fully attenuated. Daytime measurements using the RL are shown to be relatively unaffected by the solar background and are therefore suited for checking the validity of diurnal cycles. RL and CALIPSO cloud fraction profiles show good agreement while themore » MPL detects significantly less cirrus, particularly during the daytime. Both MPL and CALIPSO observations show that cirrus clouds occur less frequently during the day than at night at all altitudes. In contrast, the RL diurnal cy- cle is significantly different than zero only below about 11 km; where it is the opposite sign (i.e. more clouds during the daytime). For cirrus geomet- rical thickness, the MPL and CALIPSO observations agree well and both datasets have signficantly thinner clouds during the daytime than the RL. From the examination of hourly MPL and RL cirrus cloud thickness and through the application of daytime detection limits to all CALIPSO data we find that the decreased MPL and CALIPSO cloud thickness during the daytime is very likely a result of increased daytime noise. This study highlights the vast im- provement the RL provides (compared to the MPL) in the ARM program's ability to observe tropical cirrus clouds as well as a valuable ground-based lidar dataset for the validation of CALIPSO observations and to help im- prove our understanding of tropical cirrus clouds.« less

Magnetic seismology of interstellar gas clouds: Unveiling a hidden dimension

NASA Astrophysics Data System (ADS)

Tritsis, Aris; Tassis, Konstantinos

2018-05-01

Stars and planets are formed inside dense interstellar molecular clouds by processes imprinted on the three-dimensional (3D) morphology of the clouds. Determining the 3D structure of interstellar clouds remains challenging because of projection effects and difficulties measuring the extent of the clouds along the line of sight. We report the detection of normal vibrational modes in the isolated interstellar cloud Musca, allowing determination of the 3D physical dimensions of the cloud. We found that Musca is vibrating globally, with the characteristic modes of a sheet viewed edge on, not the characteristics of a filament as previously supposed. We reconstructed the physical properties of Musca through 3D magnetohydrodynamic simulations, reproducing the observed normal modes and confirming a sheetlike morphology.

FDTD-based quantitative analysis of terahertz wave detection for multilayered structures.

PubMed

Tu, Wanli; Zhong, Shuncong; Shen, Yaochun; Zhou, Qing; Yao, Ligang

2014-10-01

Experimental investigations have shown that terahertz pulsed imaging (TPI) is able to quantitatively characterize a range of multilayered media (e.g., biological issues, pharmaceutical tablet coatings, layered polymer composites, etc.). Advanced modeling of the interaction of terahertz radiation with a multilayered medium is required to enable the wide application of terahertz technology in a number of emerging fields, including nondestructive testing. Indeed, there have already been many theoretical analyses performed on the propagation of terahertz radiation in various multilayered media. However, to date, most of these studies used 1D or 2D models, and the dispersive nature of the dielectric layers was not considered or was simplified. In the present work, the theoretical framework of using terahertz waves for the quantitative characterization of multilayered media was established. A 3D model based on the finite difference time domain (FDTD) method is proposed. A batch of pharmaceutical tablets with a single coating layer of different coating thicknesses and different refractive indices was modeled. The reflected terahertz wave from such a sample was computed using the FDTD method, assuming that the incident terahertz wave is broadband, covering a frequency range up to 3.5 THz. The simulated results for all of the pharmaceutical-coated tablets considered were found to be in good agreement with the experimental results obtained using a commercial TPI system. In addition, we studied a three-layered medium to mimic the occurrence of defects in the sample.

Adolescent Interstellar Cloud Poised to Make Star-forming Debut

NASA Astrophysics Data System (ADS)

2001-06-01

Astronomers using the National Science Foundation's (NSF) 140-foot radio telescope at the National Radio Astronomy Observatory (NRAO) in Green Bank, W.Va., have discovered a highly unusual, massive interstellar cloud that appears poised to begin a burst of star formation. The cloud may be the first ever to be detected in the transition between atomic and molecular states. NRAO scientists Felix J. Lockman and Anthony H. Minter presented their findings at the American Astronomical Society meeting in Pasadena, Calif. Radio Image of G28.17+0.05 The scientists discovered the cloud, identified as G28.17+0.05, lying along the inner plane of the Milky Way Galaxy, approximately 16,300 light-years from Earth. Observations of the cloud indicate that it is near one of the Galaxy's sweeping spiral arms, which are outlined by young stars and the massive clouds that form them. Lockman and Minter speculate that as the interstellar cloud slams into the Galactic arm, the resulting shock wave may be precipitating the conversion of the neutral hydrogen atoms into heavier molecules, which could herald the onset of star formation. "These may be the first observations of a cloud that is in the transition between the neutral atomic hydrogen and molecular phases," said Lockman. "This provides astronomers a unique opportunity to study the chemistry of very young interstellar clouds, which could give us significant insights into the early stages of star formation and the structure of the Galaxy." Interstellar clouds that contain neutral atomic hydrogen, called HI (H-one) clouds, are thought of as giant, cold blobs of gas. Researchers study these objects because they offer intriguing glimpses of the composition of our Galaxy and the cosmos, and reveal much about how stars and planets are born. Hydrogen atoms in these clouds give off natural signals (at the 21-cm wavelength), which can be detected only by radio telescopes. The scientists discovered that this HI cloud was unusual in many respects. First, it was uncharacteristically massive, about 500 light- years across and containing nearly 100,000 times the mass of the sun in atomic hydrogen. The gas in clouds this large and massive has typically undergone the transition to the molecular phase, and has begun making stars. The size and mass of this cloud indicate that it is gravitationally bound, which means that it should be collapsing and forming new stars. "When you find a cloud that is as massive as the one we detected, and one that is gravitationally bound as this structure indicates, then you would expect to see areas of star formation," said Lockman. The scientists were able to identify a few indicators of star formation, but not at the rate that one would expect. "We think we have caught something in a special state." Lockman said, "It could be one of the missing links in the cycle of star formation." The core of the cloud also gives off radio signals at 1720 MHz from the molecule OH in an unusual state of excitation. Since other astronomers have detected similar signals throughout the Galactic plane, the researchers believe that these emissions may be an indication that this previously undetected type of cloud may turn out to be fairly common. "We suspect that this cloud may be the first example of an object that may be fairly common in the inner Galactic plane," said Lockman, "but has not been recognized. That is, a cloud that is observed while entering a spiral shock and is in the transition between atomic to molecular hydrogen." The NRAO 140-Foot Telescope The scientists caution, however, that additional research is needed to confirm their speculations. "The presence of anomalous OH through the Galactic plane does suggest that other clouds of this nature can be detected," said Lockman, "and it would be particularly valuable if a similar cloud could be detected entering the 'spiral shock' on the opposite side of the Galactic center." The patterns of velocities of atomic and molecular gas should be reversed there, due to the difference in galactic rotation. Such a discovery could help to validate the possible interaction among the spiral shock, atomic hydrogen, and star formation. The NSF's 140-foot radio telescope now is decommissioned after a long and highly productive career. Research will continue on the newly commissioned Robert C. Byrd Green Bank Telescope, which is the world's largest fully steerable radio telescope. "Though the 140-foot telescope enabled us to make remarkable observations," commented Minter, "we anticipate that the new Green Bank Telescope, with its increased sensitivity and better resolution, will enable us to see more clearly the nature of this peculiar object." In addition to Minter and Lockman, other astronomers involved in this research include Glen I. Langston, NRAO; and Jennifer A. Lockman who was a student from the College of Charleston, S.C., at the time the research was conducted. The National Radio Astronomy Observatory is a facility of the National Science Foundation, operated under cooperative agreement by Associated Universities, Inc.

Predicting and validating the motion of an ash cloud during the 2006 eruption of Mount Augustine volcano

USGS Publications Warehouse

Collins, Richard L.; Fochesatto, Javier; Sassen, Kenneth; Webley, Peter W.; Atkinson, David E.; Dean, Kenneson G.; Cahill, Catherine F.; Mizutani, Kohei

2007-01-01

On 11 January 2006, Mount Augustine volcano in southern Alaska began erupting after 20- year repose. The Anchorage Forecast Office of the National Weather Service (NWS) issued an advisory on 28 January for Kodiak City. On 31 January, Alaska Airlines cancelled all flights to and from Anchorage after multiple advisories from the NWS for Anchorage and the surrounding region. The Alaska Volcano Observatory (AVO) had reported the onset of the continuous eruption. AVO monitors the approximately 100 active volcanoes in the Northern Pacific. Ash clouds from these volcanoes can cause serious damage to an aircraft and pose a serious threat to the local communities, and to transcontinental air traffic throughout the Arctic and sub-Arctic region. Within AVO, a dispersion model has been developed to track the dispersion of volcanic ash clouds. The model, Puff, was used operational by AVO during the Augustine eruptive period. Here, we examine the dispersion of a volcanic ash (or aerosol) cloud from Mount Augustine across Alaska from 29 January through the 2 February 2006. We present the synoptic meteorology, the Puff predictions, and measurements from aerosol samplers, laser radar (or lidar) systems, and satellites. Aerosol samplers revealed the presence of volcanic aerosols at the surface at sites where Puff predicted the ash clouds movement. Remote sensing satellite data showed the development of the ash cloud in close proximity to the volcano consistent with the Puff predictions. Two lidars showed the presence of volcanic aerosol with consistent characteristics aloft over Alaska and were capable of detecting the aerosol, even in the presence of scattered clouds and where the ash cloud is too thin/disperse to be detected by remote sensing satellite data. The lidar measurements revealed the different trajectories of ash consistent with the Puff predictions. Dispersion models provide a forecast of volcanic ash cloud movement that might be undetectable by any other means but are still a significant hazard. Validation is the key to assessing the accuracy of any predictions. The study highlights the use of multiple and complementary observations used in detecting the trajectory ash cloud, both at the surface and aloft in the atmosphere.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Webley, Peter W.; Atkinson, D.; Collins, Richard L.

On 11 January 2006, Mount Augustine volcano in southern Alaska began erupting after 20-year repose. The Anchorage Forecast Office of the National Weather Service (NWS) issued an advisory on 28 January for Kodiak City. On 31 January, Alaska Airlines cancelled all flights to and from Anchorage after multiple advisories from the NWS for Anchorage and the surrounding region. The Alaska Volcano Observatory (AVO) had reported the onset of the continuous eruption. AVO monitors the approximately 100 active volcanoes in the Northern Pacific. Ash clouds from these volcanoes can cause serious damage to an aircraft and pose a serious threat tomore » the local communities, and to transcontinental air traffic throughout the Arctic and sub-Arctic region. Within AVO, a dispersion model has been developed to track the dispersion of volcanic ash clouds. The model, Puff, was used operational by AVO during the Augustine eruptive period. Here, we examine the dispersion of a volcanic ash cloud from Mount Augustine across Alaska from 29 January through the 2 February 2006. We present the synoptic meteorology, the Puff predictions, and measurements from aerosol samplers, laser radar (or lidar) systems, and satellites. UAF aerosol samplers revealed the presence of volcanic aerosols at the surface at sites where Puff predicted the ash clouds movement. Remote sensing satellite data showed the development of the ash cloud in close proximity to the volcano and a sulfur-dioxide cloud further from the volcano consistent with the Puff predictions. Lidars showed the presence of volcanic aerosol with consistent characteristics aloft over Alaska and were capable of detecting the aerosol, even in the presence of scattered clouds and where the cloud is too thin/disperse to be detected by remote sensing satellite data. The lidar measurements revealed the different trajectories of ash consistent with the Puff predictions. Dispersion models provide a forecast of volcanic ash cloud movement that might be undetectable by any other means but are still a significant hazard. Validation is the key to assessing the accuracy of any future predictions. The study highlights the use of multiple and complementary observations used in detecting the trajectory ash cloud, both at the surface and aloft within the atmosphere.« less

Diffusion algorithms and data reduction routine for onsite real-time launch predictions for the transport of Delta-Thor exhaust effluents

NASA Technical Reports Server (NTRS)

Stephens, J. B.

1976-01-01

The National Aeronautics and Space Administration/Marshall Space Flight Center multilayer diffusion algorithms have been specialized for the prediction of the surface impact for the dispersive transport of the exhaust effluents from the launch of a Delta-Thor vehicle. This specialization permits these transport predictions to be made at the launch range in real time so that the effluent monitoring teams can optimize their monitoring grids. Basically, the data reduction routine requires only the meteorology profiles for the thermodynamics and kinematics of the atmosphere as an input. These profiles are graphed along with the resulting exhaust cloud rise history, the centerline concentrations and dosages, and the hydrogen chloride isopleths.

Wavelength dependence of coherent and incoherent satellite-based lidar measurements of wind velocity and aerosol backscatter

NASA Technical Reports Server (NTRS)

Kavaya, M. J.; Huffaker, R. M.

1986-01-01

The results are presented of a capability study of Earth orbiting lidar systems, at various wavelengths from 1.06 to 10.6 microns, for the measurement of wind velocity and aerosol backscatter, and for the detection of clouds. Both coherent and incoherent lidar systems were modeled and compared for the aerosol backscatter and cloud detection applications.

Comparison of CERES-MODIS stratus cloud properties with ground-based measurements at the DOE ARM Southern Great Plains site

NASA Astrophysics Data System (ADS)

Dong, Xiquan; Minnis, Patrick; Xi, Baike; Sun-Mack, Sunny; Chen, Yan

2008-02-01

Overcast stratus cloud properties derived for the Clouds and the Earth's Radiant Energy System (CERES) project using Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) data are compared with observations taken at the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Southern Great Plains site from March 2000 through December 2004. Retrievals from ARM surface-based data were averaged over a 1-h interval centered at the time of each satellite overpass, and the CERES-MODIS cloud properties were averaged within a 30 km × 30 km box centered on the ARM SGP site. Two data sets were analyzed: all of the data (ALL), which include multilayered, single-layered, and slightly broken stratus decks and a subset, single-layered unbroken decks (SL). The CERES-MODIS effective cloud heights were determined from effective cloud temperature using a lapse rate method with the surface temperature specified as the 24-h mean surface air temperature. For SL stratus, they are, on average, within the ARM radar-lidar estimated cloud boundaries and are 0.534 ± 0.542 km and 0.108 ± 0.480 km lower than the cloud physical tops and centers, respectively, and are comparable for day and night observations. The mean differences and standard deviations are slightly larger for ALL data, but not statistically different to those of SL data. The MODIS-derived effective cloud temperatures are 2.7 ± 2.4 K less than the surface-observed SL cloud center temperatures with very high correlations (0.86-0.97). Variations in the height differences are mainly caused by uncertainties in the surface air temperatures, lapse rates, and cloud top height variability. The biases are mainly the result of the differences between effective and physical cloud top, which are governed by cloud liquid water content and viewing zenith angle, and the selected lapse rate, -7.1 K km-1. On the basis of a total of 43 samples, the means and standard deviations of the differences between the daytime Terra and surface retrievals of effective radius re, optical depth, and liquid water path for SL stratus are 0.1 ± 1.9 μm (1.2 ± 23.5%), -1.3 ± 9.5 (-3.6 ± 26.2%), and 0.6 ± 49.9 gm-2 (0.3 ± 27%), respectively, while the corresponding correlation coefficients are 0.44, 0.87, and 0.89. For Aqua, they are 0.2 ± 1.9 μm (2.5 ± 23.4%), 2.5 ± 7.8 (7.8 ± 24.3%), and 28.1 ± 52.7 gm-2 (17.2 ± 32.2%), as well as 0.35, 0.96, and 0.93 from a total of 21 cases. The results for ALL cases are comparable. Although a bias in re was expected because the satellite retrieval of effective radius only represents the top of the cloud, the surface-based radar retrievals revealed that the vertical profile of re is highly variable with smaller droplets occurring at cloud top in some cases. The larger bias in optical depth and liquid water path for Aqua is due, at least partially, to differences in the Terra and Aqua MODIS visible channel calibrations. Methods for improving the cloud top height and microphysical property retrievals are suggested.

Comparison of CERES-MODIS Stratus Cloud Properties with Ground-Based Measurements at the DOE ARM Southern Great Plains Site

NASA Technical Reports Server (NTRS)

Dong, Xiquan; Minnis Patrick; Xi, Baike; Sun-Mack, Sunny; Chen, Yan

2008-01-01

Overcast stratus cloud properties derived for the Clouds and the Earth's Radiant Energy system (CERES) Project using Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) data are compared with observations taken at the Atmospheric Radiation Measurement (ARM) Southern Great Plains site from March 2000 through December 2004. Retrievals from ARM surface-based data were averaged over a 1-hour interval centered at the time of each satellite overpass, and the CERES-MODIS cloud properties were averaged within a 30-km x 30 km box centered on the ARM SGP site. Two datasets were analyzed: all of the data (ALL) which include multilayered, single-layered, and slightly broken stratus decks and a subset, single-layered unbroken decks (SL). The CERES-MODIS effective cloud heights were determined from effective cloud temperature using a lapse rate method with the surface temperature specified as the 24-h mean surface air temperature. For SL stratus, they are, on average, within the ARM radar-lidar estimated cloud boundaries and are 0.534 +/- 0.542 km and 0.108 +/- 0.480 km lower than the cloud physical tops and centers, respectively, and are comparable for day and night observations. The mean differences and standard deviations are slightly larger for ALL data, but not statistically different to those of SL data. The MODIS-derived effective cloud temperatures are 2.7 +/- 2.4 K less than the surface-observed SL cloud center temperatures with very high correlations (0.86-0.97). Variations in the height differences are mainly caused by uncertainties in the surface air temperatures, lapse rates, and cloud-top height variability. The biases are mainly the result of the differences between effective and physical cloud top, which are governed by cloud liquid water content and viewing zenith angle, and the selected lapse rate, -7.1 K km(exp -1). Based on a total of 43 samples, the means and standard deviations of the differences between the daytime Terra and surface retrievals of effective radius r(sub e), optical depth, and liquid water path for SL stratu are 0.1 +/- 1.9 micrometers (1.2 +/- 23.5%), -1.3 +/- 9.5 (-3.6 +/-26.2%), and 0.6 +/- 49.9 gm (exp -2) (0.3 +/- 27%), respectively, while the corresponding correlation coefficients are 0.44, 0.87, and 0.89. For Aqua, they are 0.2 +/- 1.9 micrometers (2.5 +/- 23.4%), 2.5 +/- 7.8 (7.8 +/- 24.3%), and 28.1 +/- 52.7 gm (exp -2) (17.2 +/- 32.2%), as well as 0.35, 0.96, and 0.93 from a total of 21 cases. The results for ALL cases are comparable. Although a bias in R(sub e) was expected because the satellite retrieval of effective radius only represents the top of the cloud, the surface-based radar retrievals revealed that the vertical profile of r(sub e) is highly variable with smaller droplets occurring at cloud top in some cases. The larger bias in optical depth and liquid water path for Aqua is due, at least partially, to differences in the Terra and Aqua MODIS visible channel calibrations. methods for improving the cloud-top height and microphysical property retrievals are suggested.

Identification of Program Signatures from Cloud Computing System Telemetry Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nichols, Nicole M.; Greaves, Mark T.; Smith, William P.

Malicious cloud computing activity can take many forms, including running unauthorized programs in a virtual environment. Detection of these malicious activities while preserving the privacy of the user is an important research challenge. Prior work has shown the potential viability of using cloud service billing metrics as a mechanism for proxy identification of malicious programs. Previously this novel detection method has been evaluated in a synthetic and isolated computational environment. In this paper we demonstrate the ability of billing metrics to identify programs, in an active cloud computing environment, including multiple virtual machines running on the same hypervisor. The openmore » source cloud computing platform OpenStack, is used for private cloud management at Pacific Northwest National Laboratory. OpenStack provides a billing tool (Ceilometer) to collect system telemetry measurements. We identify four different programs running on four virtual machines under the same cloud user account. Programs were identified with up to 95% accuracy. This accuracy is dependent on the distinctiveness of telemetry measurements for the specific programs we tested. Future work will examine the scalability of this approach for a larger selection of programs to better understand the uniqueness needed to identify a program. Additionally, future work should address the separation of signatures when multiple programs are running on the same virtual machine.« less

The potential of using Landsat time-series to extract tropical dry forest phenology

NASA Astrophysics Data System (ADS)

Zhu, X.; Helmer, E.

2016-12-01

Vegetation phenology is the timing of seasonal developmental stages in plant life cycles. Due to the persistent cloud cover in tropical regions, current studies often use satellite data with high frequency, such as AVHRR and MODIS, to detect vegetation phenology. However, the spatial resolution of these data is from 250 m to 1 km, which does not have enough spatial details and it is difficult to relate to field observations. To produce maps of phenology at a finer spatial resolution, this study explores the feasibility of using Landsat images to detect tropical forest phenology through reconstructing a high-quality, seasonal time-series of images, and tested it in Mona Island, Puerto Rico. First, an automatic method was applied to detect cloud and cloud shadow, and a spatial interpolator was use to retrieve pixels covered by clouds, shadows, and SLC-off gaps. Second, enhanced vegetation index time-series derived from the reconstructed Landsat images were used to detect 11 phenology variables. Detected phenology is consistent with field investigations, and its spatial pattern is consistent with the rainfall distribution on this island. In addition, we may expect that phenology should correlate with forest biophysical attributes, so 47 plots with field measurement of biophysical attributes were used to indirectly validate the phenology product. Results show that phenology variables can explain a lot of variations in biophysical attributes. This study suggests that Landsat time-series has great potential to detect phenology in tropical areas.

Selective enrichment of volatiles confirmed

NASA Astrophysics Data System (ADS)

de Pater, Imke

2018-04-01

Hydrogen sulfide gas is detected above Uranus's main cloud deck, confirming the prevalence of H2S ice particles as the main cloud component and a strongly unbalanced nitrogen/sulfur ratio in the planet's deep atmosphere.

Selective enrichment of volatiles confirmed

NASA Astrophysics Data System (ADS)

de Pater, Imke

2018-05-01

Hydrogen sulfide gas is detected above Uranus's main cloud deck, confirming the prevalence of H2S ice particles as the main cloud component and a strongly unbalanced nitrogen/sulfur ratio in the planet's deep atmosphere.

Correlation dynamics and enhanced signals for the identification of serial biomolecules and DNA bases.

PubMed

Ahmed, Towfiq; Haraldsen, Jason T; Rehr, John J; Di Ventra, Massimiliano; Schuller, Ivan; Balatsky, Alexander V

2014-03-28

Nanopore-based sequencing has demonstrated a significant potential for the development of fast, accurate, and cost-efficient fingerprinting techniques for next generation molecular detection and sequencing. We propose a specific multilayered graphene-based nanopore device architecture for the recognition of single biomolecules. Molecular detection and analysis can be accomplished through the detection of transverse currents as the molecule or DNA base translocates through the nanopore. To increase the overall signal-to-noise ratio and the accuracy, we implement a new 'multi-point cross-correlation' technique for identification of DNA bases or other molecules on the single molecular level. We demonstrate that the cross-correlations between each nanopore will greatly enhance the transverse current signal for each molecule. We implement first-principles transport calculations for DNA bases surveyed across a multilayered graphene nanopore system to illustrate the advantages of the proposed geometry. A time-series analysis of the cross-correlation functions illustrates the potential of this method for enhancing the signal-to-noise ratio. This work constitutes a significant step forward in facilitating fingerprinting of single biomolecules using solid state technology.

An energy-efficient failure detector for vehicular cloud computing.

PubMed

Liu, Jiaxi; Wu, Zhibo; Dong, Jian; Wu, Jin; Wen, Dongxin

2018-01-01

Failure detectors are one of the fundamental components for maintaining the high availability of vehicular cloud computing. In vehicular cloud computing, lots of RSUs are deployed along the road to improve the connectivity. Many of them are equipped with solar battery due to the unavailability or excess expense of wired electrical power. So it is important to reduce the battery consumption of RSU. However, the existing failure detection algorithms are not designed to save battery consumption RSU. To solve this problem, a new energy-efficient failure detector 2E-FD has been proposed specifically for vehicular cloud computing. 2E-FD does not only provide acceptable failure detection service, but also saves the battery consumption of RSU. Through the comparative experiments, the results show that our failure detector has better performance in terms of speed, accuracy and battery consumption.

An energy-efficient failure detector for vehicular cloud computing

PubMed Central

Liu, Jiaxi; Wu, Zhibo; Wu, Jin; Wen, Dongxin

2018-01-01

Failure detectors are one of the fundamental components for maintaining the high availability of vehicular cloud computing. In vehicular cloud computing, lots of RSUs are deployed along the road to improve the connectivity. Many of them are equipped with solar battery due to the unavailability or excess expense of wired electrical power. So it is important to reduce the battery consumption of RSU. However, the existing failure detection algorithms are not designed to save battery consumption RSU. To solve this problem, a new energy-efficient failure detector 2E-FD has been proposed specifically for vehicular cloud computing. 2E-FD does not only provide acceptable failure detection service, but also saves the battery consumption of RSU. Through the comparative experiments, the results show that our failure detector has better performance in terms of speed, accuracy and battery consumption. PMID:29352282

Night Sky Weather Monitoring System Using Fish-Eye CCD

NASA Astrophysics Data System (ADS)

Tomida, Takayuki; Saito, Yasunori; Nakamura, Ryo; Yamazaki, Katsuya

Telescope Array (TA) is international joint experiment observing ultra-high energy cosmic rays. TA employs fluorescence detection technique to observe cosmic rays. In this technique, tho existence of cloud significantly affects quality of data. Therefore, cloud monitoring provides important information. We are developing two new methods for evaluating night sky weather with pictures taken by charge-coupled device (CCD) camera. One is evaluating the amount of cloud with pixels brightness. The other is counting the number of stars with contour detection technique. The results of these methods show clear correlation, and we concluded both the analyses are reasonable methods for weather monitoring. We discuss reliability of the star counting method.

Biogenic, urban, and wildfire influences on the molecular composition of dissolved organic compounds in cloud water

DOE PAGES

Cook, Ryan D.; Lin, Ying-Hsuan; Peng, Zhuoyu; ...

2017-12-21

Organic aerosol formation and transformation occurs within aqueous aerosol and cloud droplets, yet little is known about the composition of high molecular weight organic compounds in cloud water. Cloud water samples collected at Whiteface Mountain, New York, during August-September 2014 were analyzed by ultra-high-resolution mass spectrometry to investigate the molecular composition of dissolved organic carbon, with a focus on sulfur- and nitrogen-containing compounds. Organic molecular composition was evaluated in the context of cloud water inorganic ion concentrations, pH, and total organic carbon concentrations to gain insights into the sources and aqueous-phase processes of the observed high molecular weight organic compounds.more » Cloud water acidity was positively correlated with the average oxygen : carbon ratio of the organic constituents, suggesting the possibility for aqueous acid-catalyzed (prior to cloud droplet activation or during/after cloud droplet evaporation) and/or radical (within cloud droplets) oxidation processes. Many tracer compounds recently identified in laboratory studies of bulk aqueous-phase reactions were identified in the cloud water. Organosulfate compounds, with both biogenic and anthropogenic volatile organic compound precursors, were detected for cloud water samples influenced by air masses that had traveled over forested and populated areas. Oxidation products of long-chain (C 10-12) alkane precursors were detected during urban influence. Influence of Canadian wildfires resulted in increased numbers of identified sulfur-containing compounds and oligomeric species, including those formed through aqueous-phase reactions involving methylglyoxal. Light-absorbing aqueous-phase products of syringol and guaiacol oxidation were observed in the wildfire-influenced samples, and dinitroaromatic compounds were observed in all cloud water samples (wildfire, biogenic, and urban-influenced). Overall, the cloud water molecular composition depended on air mass source influence and reflected aqueous-phase reactions involving biogenic, urban, and biomass burning precursors.« less

Biogenic, urban, and wildfire influences on the molecular composition of dissolved organic compounds in cloud water

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cook, Ryan D.; Lin, Ying-Hsuan; Peng, Zhuoyu

Organic aerosol formation and transformation occurs within aqueous aerosol and cloud droplets, yet little is known about the composition of high molecular weight organic compounds in cloud water. Cloud water samples collected at Whiteface Mountain, New York, during August-September 2014 were analyzed by ultra-high-resolution mass spectrometry to investigate the molecular composition of dissolved organic carbon, with a focus on sulfur- and nitrogen-containing compounds. Organic molecular composition was evaluated in the context of cloud water inorganic ion concentrations, pH, and total organic carbon concentrations to gain insights into the sources and aqueous-phase processes of the observed high molecular weight organic compounds.more » Cloud water acidity was positively correlated with the average oxygen : carbon ratio of the organic constituents, suggesting the possibility for aqueous acid-catalyzed (prior to cloud droplet activation or during/after cloud droplet evaporation) and/or radical (within cloud droplets) oxidation processes. Many tracer compounds recently identified in laboratory studies of bulk aqueous-phase reactions were identified in the cloud water. Organosulfate compounds, with both biogenic and anthropogenic volatile organic compound precursors, were detected for cloud water samples influenced by air masses that had traveled over forested and populated areas. Oxidation products of long-chain (C 10-12) alkane precursors were detected during urban influence. Influence of Canadian wildfires resulted in increased numbers of identified sulfur-containing compounds and oligomeric species, including those formed through aqueous-phase reactions involving methylglyoxal. Light-absorbing aqueous-phase products of syringol and guaiacol oxidation were observed in the wildfire-influenced samples, and dinitroaromatic compounds were observed in all cloud water samples (wildfire, biogenic, and urban-influenced). Overall, the cloud water molecular composition depended on air mass source influence and reflected aqueous-phase reactions involving biogenic, urban, and biomass burning precursors.« less

Retrieval of volcanic ash height from satellite-based infrared measurements

NASA Astrophysics Data System (ADS)

Zhu, Lin; Li, Jun; Zhao, Yingying; Gong, He; Li, Wenjie

2017-05-01

A new algorithm for retrieving volcanic ash cloud height from satellite-based measurements is presented. This algorithm, which was developed in preparation for China's next-generation meteorological satellite (FY-4), is based on volcanic ash microphysical property simulation and statistical optimal estimation theory. The MSG satellite's main payload, a 12-channel Spinning Enhanced Visible and Infrared Imager, was used as proxy data to test this new algorithm. A series of eruptions of Iceland's Eyjafjallajökull volcano during April to May 2010 and the Puyehue-Cordón Caulle volcanic complex eruption in the Chilean Andes on 16 June 2011 were selected as two typical cases for evaluating the algorithm under various meteorological backgrounds. Independent volcanic ash simulation training samples and satellite-based Cloud-Aerosol Lidar with Orthogonal Polarization data were used as validation data. It is demonstrated that the statistically based volcanic ash height algorithm is able to rapidly retrieve volcanic ash heights, globally. The retrieved ash heights show comparable accuracy with both independent training data and the lidar measurements, which is consistent with previous studies. However, under complicated background, with multilayers in vertical scale, underlying stratus clouds tend to have detrimental effects on the final retrieval accuracy. This is an unresolved problem, like many other previously published methods using passive satellite sensors. Compared with previous studies, the FY-4 ash height algorithm is independent of simultaneous atmospheric profiles, providing a flexible way to estimate volcanic ash height using passive satellite infrared measurements.

Accurate mobile malware detection and classification in the cloud.

PubMed

Wang, Xiaolei; Yang, Yuexiang; Zeng, Yingzhi

2015-01-01

As the dominator of the Smartphone operating system market, consequently android has attracted the attention of s malware authors and researcher alike. The number of types of android malware is increasing rapidly regardless of the considerable number of proposed malware analysis systems. In this paper, by taking advantages of low false-positive rate of misuse detection and the ability of anomaly detection to detect zero-day malware, we propose a novel hybrid detection system based on a new open-source framework CuckooDroid, which enables the use of Cuckoo Sandbox's features to analyze Android malware through dynamic and static analysis. Our proposed system mainly consists of two parts: anomaly detection engine performing abnormal apps detection through dynamic analysis; signature detection engine performing known malware detection and classification with the combination of static and dynamic analysis. We evaluate our system using 5560 malware samples and 6000 benign samples. Experiments show that our anomaly detection engine with dynamic analysis is capable of detecting zero-day malware with a low false negative rate (1.16 %) and acceptable false positive rate (1.30 %); it is worth noting that our signature detection engine with hybrid analysis can accurately classify malware samples with an average positive rate 98.94 %. Considering the intensive computing resources required by the static and dynamic analysis, our proposed detection system should be deployed off-device, such as in the Cloud. The app store markets and the ordinary users can access our detection system for malware detection through cloud service.

Road Signs Detection and Recognition Utilizing Images and 3d Point Cloud Acquired by Mobile Mapping System

NASA Astrophysics Data System (ADS)

Li, Y. H.; Shinohara, T.; Satoh, T.; Tachibana, K.

2016-06-01

High-definition and highly accurate road maps are necessary for the realization of automated driving, and road signs are among the most important element in the road map. Therefore, a technique is necessary which can acquire information about all kinds of road signs automatically and efficiently. Due to the continuous technical advancement of Mobile Mapping System (MMS), it has become possible to acquire large number of images and 3d point cloud efficiently with highly precise position information. In this paper, we present an automatic road sign detection and recognition approach utilizing both images and 3D point cloud acquired by MMS. The proposed approach consists of three stages: 1) detection of road signs from images based on their color and shape features using object based image analysis method, 2) filtering out of over detected candidates utilizing size and position information estimated from 3D point cloud, region of candidates and camera information, and 3) road sign recognition using template matching method after shape normalization. The effectiveness of proposed approach was evaluated by testing dataset, acquired from more than 180 km of different types of roads in Japan. The results show a very high success in detection and recognition of road signs, even under the challenging conditions such as discoloration, deformation and in spite of partial occlusions.

Automated Point Cloud Correspondence Detection for Underwater Mapping Using AUVs

NASA Technical Reports Server (NTRS)

Hammond, Marcus; Clark, Ashley; Mahajan, Aditya; Sharma, Sumant; Rock, Stephen

2015-01-01

An algorithm for automating correspondence detection between point clouds composed of multibeam sonar data is presented. This allows accurate initialization for point cloud alignment techniques even in cases where accurate inertial navigation is not available, such as iceberg profiling or vehicles with low-grade inertial navigation systems. Techniques from computer vision literature are used to extract, label, and match keypoints between "pseudo-images" generated from these point clouds. Image matches are refined using RANSAC and information about the vehicle trajectory. The resulting correspondences can be used to initialize an iterative closest point (ICP) registration algorithm to estimate accumulated navigation error and aid in the creation of accurate, self-consistent maps. The results presented use multibeam sonar data obtained from multiple overlapping passes of an underwater canyon in Monterey Bay, California. Using strict matching criteria, the method detects 23 between-swath correspondence events in a set of 155 pseudo-images with zero false positives. Using less conservative matching criteria doubles the number of matches but introduces several false positive matches as well. Heuristics based on known vehicle trajectory information are used to eliminate these.

Hard X-ray mirrors for Nuclear Security

DOE Office of Scientific and Technical Information (OSTI.GOV)

Descalle, M. A.; Brejnholt, N.; Hill, R.

Research performed under this LDRD aimed to demonstrate the ability to detect and measure hard X-ray emissions using multilayer X-ray reflective optics above 400 keV, to enable the development of inexpensive and high-accuracy mirror substrates, and to investigate applications of hard X-ray mirrors of interest to the nuclear security community. Experiments conducted at the European Synchrotron Radiation Facility demonstrated hard X-ray mirror reflectivity up to 650 keV for the first time. Hard X-ray optics substrates must have surface roughness under 3 to 4 Angstrom rms, and three materials were evaluated as potential substrates: polycarbonates, thin Schott glass and a newmore » type of flexible glass called Willow Glass®. Chemical smoothing and thermal heating of the surface of polycarbonate samples, which are inexpensive but have poor intrinsic surface characteristics, did not yield acceptable surface roughness. D263 Schott glass was used for the focusing optics of the NASA NuSTAR telescope. The required specialized hardware and process were costly and motivated experiments with a modified non-contact slumping technique. The surface roughness of the glass was preserved and the process yielded cylindrical shells with good net shape pointing to the potential advantage of this technique. Finally, measured surface roughness of 200 and 130 μm thick Willow Glass sheets was between 2 and 2.5 A rms. Additional results of flexibility tests and multilayer deposition campaigns indicated it is a promising substrate for hard X-ray optics. The detection of U and Pu characteristics X-ray lines and gamma emission lines in a high background environment was identified as an area for which X-ray mirrors could have an impact and where focusing optics could help reduce signal to noise ratio by focusing signal onto a smaller detector. Hence the first one twelvetant of a Wolter I focusing optics for the 90 to 140 keV energy range based on aperiodic multilayer coating was designed. Finally, we conducted the first demonstration that reflective multilayer mirrors could be used as diagnostic for HED experiment with an order of magnitude improvement in signal-to-noise ratio for the multilayer optic compared a transmission crystal spectrometer.« less

Six Martian years of CO2 clouds survey by OMEGA/MEx.

NASA Astrophysics Data System (ADS)

Gondet, Brigitte; bibring, Jean-Pierre; Vincendon, Mathieu

2014-05-01

Mesospheric clouds have been detected first from Earth (Bell et al 1996 [1]), then from Mars orbit (MGS/TES and MOC, Clancy et al 1998 [2]). Their composition (CO2) was inferred from temperature. Similar detection and temperature-inferred composition was then performed by Spicam and PFS on board Mars Express (Monmessin et al [3], Formisano et al [4]., 2006). The first direct detection and characterization (altitude, composition, velocity) was performed by OMEGA/ Mars Express (then coupled to HRSC/ Mars Express, and confirmed by CRISM/MRO (Montmessin et al. [5], 2007, Maattanen et al [6]., Scholten et al. [7], 2010, Vincendon et al [8]., 2011). Omega is a very powerful tool for the study of CO2 clouds as it is able to unambiguously identify the CO2 composition of a cloud based on a near-IR spectral feature located at 4.26 μm [5],. Therefore since the beginning of the Mars Express mission (2004) OMEGA as done a systematic survey of these mesospheric clouds. Thanks to the orbit of Mars Express, we can observe this clouds from different altitudes (from apocenter to pericenter) and at different local times. We will present the result of 6 Martians years of observations and point out a correlation with the dust activity. We also observe that their time of appearance/disappearance varies slightly from year to year. We will mention also the existence of mesospheric H2O clouds. References [1] JF Bell. et al. JGR 1996; [2] RT Clancy et al., GRL 1998 [3] F. Montmessin et al. JGR 2006; [4] V. Formisano et al., Icarus 2006; [5] F. Montmessin et al JGR 2007 [6] A. Määttänen et al. Icarus 2010; [7] F. Scholten et al. PSS 2010; [8] M. Viencendon et al. JGR 2011

Mesospheric CO2 Clouds at Mars: Seven Martian Years Survey by OMEGA/MEX

NASA Astrophysics Data System (ADS)

Gondet, Brigitte; Bibring, Jean-Pierre

2016-04-01

Mesospheric clouds have been detected first from Earth (Bell et al 1996 [1]), then from Mars orbit (MGS/TES and MOC, Clancy et al 1998 [2]). Their composition (CO2) was inferred from temperature. Similar detection and temperature-inferred composition was then performed by Spicam and PFS on board Mars Express (Monmessin et al [3], Formisano et al [4]. 2006). The first direct detection and characterization (altitude, composition, velocity) was performed by OMEGA/ Mars Express (then coupled to HRSC/ Mars Express, and confirmed by CRISM/MRO (Montmessin et al. [5], 2007, Maattanen et al [6]. Scholten et al. [7], 2010, Vincendon et al [8], 2011). Omega is a very powerful tool for the study of CO2 clouds as it is able to unambiguously identify the CO2 composition of a cloud based on a near-IR spectral feature located at 4.26 μm [5] Therefore since the beginning of the Mars Express mission (2004) OMEGA as done a systematic survey of these mesospheric clouds. Thanks to the orbit of Mars Express, we can observe this clouds from different altitudes (from apocenter to pericenter) and at different local times. We will present the result of 7 Martians years of observations, point out a correlation with the dust activity and an irregular concentration of clouds from years to years. References [1] JF Bell. et al. JGR 1996; [2] RT Clancy et al., GRL 1998 [3] F. Montmessin et al. JGR 2006; [4] V. Formisano et al., Icarus 2006; [5] F. Montmessin et al JGR 2007 [6] A. Määttänen et al. Icarus 2010; [7] F. Scholten et al. PSS 2010; [8] M. Viencendon et al. JGR 2011

A Comparison of High Spectral Resolution Infrared Cloud-Top Pressure Altitude Algorithms Using S-HIS Measurements

NASA Technical Reports Server (NTRS)

Holz, Robert E.; Ackerman, Steve; Antonelli, Paolo; Nagle, Fred; McGill, Matthew; Hlavka, Dennis L.; Hart, William D.

2005-01-01

This paper presents a comparison of cloud-top altitude retrieval methods applied to S-HIS (Scanning High Resolution Interferometer Sounder) measurements. Included in this comparison is an improvement to the traditional CO2 Slicing method. The new method, CO2 Sorting, determines optimal channel pairs to apply the CO2 Slicing. Measurements from collocated samples of the Cloud Physics Lidar (CPL) and Modis Airborne Simulator (MAS) instruments assist in the comparison. For optically thick clouds good correlation between the S-HIS and lidar cloud-top retrievals are found. For tenuous ice clouds there can be large differences between lidar (CPL) and S-HIS retrieved cloud-tops. It is found that CO2 Sorting significantly reduces the cloud height biases for the optically thin cloud (total optical depths less then 1.0). For geometrically thick but optically thin cirrus clouds large differences between the S-HIS infrared cloud top retrievals and the CPL detected cloud top where found. For these cases the cloud height retrieved by the S-HIS cloud retrievals correlated closely with the level the CPL integrated cloud optical depth was approximately 1.0.

Exploring Richtmyer-Meshkov instability phenomena and ejecta cloud physics

NASA Astrophysics Data System (ADS)

Zellner, M. B.; Buttler, W. T.

2008-09-01

This effort investigates ejecta cloud expansion from a shocked Sn target propagating into vacuum. To assess the expansion, dynamic ejecta cloud density distributions were measured via piezoelectric pin diagnostics offset at three heights from the target free surface. The dynamic distributions were first converted into static distributions, similar to a radiograph, and then self compared. The cloud evolved self-similarly at the distances and times measured, inferring that the amount of mass imparted to the instability, detected as ejecta, either ceased or approached an asymptotic limit.

An Assessment Tool to Detect Unique Characteristics of Cognitive Deficiency

DTIC Science & Technology

2017-06-01

psychological impairment and cognitive deficiency that results from either physical trauma, emotional distress or a combination of both factors, which we...27 To fully remove the DDM, we will integrate our cloud support into the...DANA codebase. We will integrate cloud authentication into DANA to enable users to store their data on the cloud and access the data from the DANA

A Radiative Analysis of Angular Signatures and Oblique Radiance Retrievals over the Polar Regions from the Multi-Angle Imaging Spectroradiometer

ERIC Educational Resources Information Center

Wilson, Michael Jason

2009-01-01

This dissertation studies clouds over the polar regions using the Multi-angle Imaging SpectroRadiometer (MISR) on-board EOS-Terra. Historically, low thin clouds have been problematic for satellite detection, because these clouds have similar brightness and temperature properties to the surface they overlay. However, the oblique angles of MISR…

Analytic model for washout of HCl(g) from dispersing rocket exhaust clouds

NASA Technical Reports Server (NTRS)

Pellett, G. L.

1981-01-01

The potential is investigated that precipitation scavenging of HCl from large solid rocket exhaust clouds may result in unacceptably acidic rain in the Cape Canaveral, Florida, area before atmospheric dispersion reduces HCl concentrations to safe limits. Several analytic expressions for HCl(g) and HCl(g + aq) washout are derived; a geometric mean washout coefficient is recommended. A previous HCl washout model is refined and applied to a space shuttle case (70 t HCl exhausted up to 4 km) and eight Titan 3 (60 percent less exhaust) dispersion cases. The vertical column density (sigma) decays were deduced by application of a multilayer Gaussian diffusion model to seven standard meteorological regimes for overland advection. The Titan 3 decays of sigma and initial rain pH differed greatly among regimes; e.g., a range of 2 pH units was spanned at x 100 km downwind and t = 2 hr. Environmentally significant pH's .5 for infrequent exposures were shown possible at X = 50 km and t 5 hr for the two least dispersive Titan 3 cases. Representative examples of downwind rainwater pH and G(X) are analyzed. Factors affecting the validity of the results are discussed.

Evaluating NASA S-NPP continuity cloud products for climate research using CALIPSO, CATS and Level-3 analysis

NASA Astrophysics Data System (ADS)

Holz, R.; Platnick, S. E.; Meyer, K.; Frey, R.; Wind, G.; Ackerman, S. A.; Heidinger, A. K.; Botambekov, D.; Yorks, J. E.; McGill, M. J.

2016-12-01

The launch of VIIRS and CrIS on Suomi NPP in the fall of 2011 introduced the next generation of U.S. operational polar orbiting environmental observations. Similar to MODIS, VIIRS provides visible and IR observations at moderate spatial resolution and has a 1:30 pm equatorial crossing time consistent with the MODIS on Aqua platform. However unlike MODIS, VIIRS lacks water vapor and CO2 absorbing channels that are used by the MODIS cloud algorithms for both cloud detection and to retrieve cloud top height and cloud emissivity for ice clouds. Given the different spectral and spatial characteristics of VIIRS, we seek to understand the extent to which the 15-year MODIS climate record can be continued with VIIRS/CrIS observations while maintaining consistent sensitivities across the observational systems. This presentation will focus on the evaluation of the latest version of the NASA funded cloud retrieval algorithms being developed for climate research. We will present collocated inter-comparisons between the imagers (VIIRS and MODIS Aqua) with CALIPSO and Cloud Aerosol Transport System (CATS) lidar observations as well as long term statistics based on a new Level-3 (L3) product being developed as part the project. The CALIPSO inter-comparisons will focus on cloud detection (cloud mask) with a focus on the impact of recent modifications to the cloud mask and how these changes impact the global statistics. For the first time we will provide inter-comparisons between two different cloud lidar systems (CALIOP and CATS) and investigate how the different sensitivities of the lidars impact the cloud mask and cloud comparisons. Using CALIPSO and CATS as the reference, and applying the same algorithms to VIIRS and MODIS, we will discuss the consistency between products from both imagers. The L3 analysis will focus on the regional and seasonal consistency between the suite of MODIS and VIIRS continuity cloud products. Do systematic biases remains when using consistent algorithms but applied to different observations (MODIS or VIIRS)?

Nanosatellite Maneuver Planning for Point Cloud Generation With a Rangefinder

DTIC Science & Technology

2015-06-05

aided active vision systems [11], dense stereo [12], and TriDAR [13]. However, these systems are unsuitable for a nanosatellite system from power, size...command profiles as well as improving the fidelity of gap detection with better filtering methods for background objects . For example, attitude...application of a single beam laser rangefinder (LRF) to point cloud generation, shape detection , and shape reconstruction for a space-based space

Feature extraction and classification of clouds in high resolution panchromatic satellite imagery

NASA Astrophysics Data System (ADS)

Sharghi, Elan

The development of sophisticated remote sensing sensors is rapidly increasing, and the vast amount of satellite imagery collected is too much to be analyzed manually by a human image analyst. It has become necessary for a tool to be developed to automate the job of an image analyst. This tool would need to intelligently detect and classify objects of interest through computer vision algorithms. Existing software called the Rapid Image Exploitation Resource (RAPIER®) was designed by engineers at Space and Naval Warfare Systems Center Pacific (SSC PAC) to perform exactly this function. This software automatically searches for anomalies in the ocean and reports the detections as a possible ship object. However, if the image contains a high percentage of cloud coverage, a high number of false positives are triggered by the clouds. The focus of this thesis is to explore various feature extraction and classification methods to accurately distinguish clouds from ship objects. An examination of a texture analysis method, line detection using the Hough transform, and edge detection using wavelets are explored as possible feature extraction methods. The features are then supplied to a K-Nearest Neighbors (KNN) or Support Vector Machine (SVM) classifier. Parameter options for these classifiers are explored and the optimal parameters are determined.

A Complex Systems Approach to More Resilient Multi-Layered Security Systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brown, Nathanael J. K.; Jones, Katherine A.; Bandlow, Alisa

In July 2012, protestors cut through security fences and gained access to the Y-12 National Security Complex. This was believed to be a highly reliable, multi-layered security system. This report documents the results of a Laboratory Directed Research and Development (LDRD) project that created a consistent, robust mathematical framework using complex systems analysis algorithms and techniques to better understand the emergent behavior, vulnerabilities and resiliency of multi-layered security systems subject to budget constraints and competing security priorities. Because there are several dimensions to security system performance and a range of attacks that might occur, the framework is multi-objective for amore » performance frontier to be estimated. This research explicitly uses probability of intruder interruption given detection (P I) as the primary resilience metric. We demonstrate the utility of this framework with both notional as well as real-world examples of Physical Protection Systems (PPSs) and validate using a well-established force-on-force simulation tool, Umbra.« less

Ubiquity and impact of thin mid-level clouds in the tropics

PubMed Central

Bourgeois, Quentin; Ekman, Annica M. L.; Igel, Matthew R.; Krejci, Radovan

2016-01-01

Clouds are crucial for Earth's climate and radiation budget. Great attention has been paid to low, high and vertically thick tropospheric clouds such as stratus, cirrus and deep convective clouds. However, much less is known about tropospheric mid-level clouds as these clouds are challenging to observe in situ and difficult to detect by remote sensing techniques. Here we use Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) satellite observations to show that thin mid-level clouds (TMLCs) are ubiquitous in the tropics. Supported by high-resolution regional model simulations, we find that TMLCs are formed by detrainment from convective clouds near the zero-degree isotherm. Calculations using a radiative transfer model indicate that tropical TMLCs have a cooling effect on climate that could be as large in magnitude as the warming effect of cirrus. We conclude that more effort has to be made to understand TMLCs, as their influence on cloud feedbacks, heat and moisture transport, and climate sensitivity could be substantial. PMID:27530236

Ubiquity and impact of thin mid-level clouds in the tropics.

PubMed

Bourgeois, Quentin; Ekman, Annica M L; Igel, Matthew R; Krejci, Radovan

2016-08-17

Clouds are crucial for Earth's climate and radiation budget. Great attention has been paid to low, high and vertically thick tropospheric clouds such as stratus, cirrus and deep convective clouds. However, much less is known about tropospheric mid-level clouds as these clouds are challenging to observe in situ and difficult to detect by remote sensing techniques. Here we use Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) satellite observations to show that thin mid-level clouds (TMLCs) are ubiquitous in the tropics. Supported by high-resolution regional model simulations, we find that TMLCs are formed by detrainment from convective clouds near the zero-degree isotherm. Calculations using a radiative transfer model indicate that tropical TMLCs have a cooling effect on climate that could be as large in magnitude as the warming effect of cirrus. We conclude that more effort has to be made to understand TMLCs, as their influence on cloud feedbacks, heat and moisture transport, and climate sensitivity could be substantial.

Global Single and Multiple Cloud Classification with a Fuzzy Logic Expert System

NASA Technical Reports Server (NTRS)

Welch, Ronald M.; Tovinkere, Vasanth; Titlow, James; Baum, Bryan A.

1996-01-01

An unresolved problem in remote sensing concerns the analysis of satellite imagery containing both single and multiple cloud layers. While cloud parameterizations are very important both in global climate models and in studies of the Earth's radiation budget, most cloud retrieval schemes, such as the bispectral method used by the International Satellite Cloud Climatology Project (ISCCP), have no way of determining whether overlapping cloud layers exist in any group of satellite pixels. Coakley (1983) used a spatial coherence method to determine whether a region contained more than one cloud layer. Baum et al. (1995) developed a scheme for detection and analysis of daytime multiple cloud layers using merged AVHRR (Advanced Very High Resolution Radiometer) and HIRS (High-resolution Infrared Radiometer Sounder) data collected during the First ISCCP Regional Experiment (FIRE) Cirrus 2 field campaign. Baum et al. (1995) explored the use of a cloud classification technique based on AVHRR data. This study examines the feasibility of applying the cloud classifier to global satellite imagery.

NARROW Na AND K ABSORPTION LINES TOWARD T TAURI STARS: TRACING THE ATOMIC ENVELOPE OF MOLECULAR CLOUDS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pascucci, I.; Simon, M. N.; Edwards, S.

2015-11-20

We present a detailed analysis of narrow Na i and K i absorption resonance lines toward nearly 40 T Tauri stars in Taurus with the goal of clarifying their origin. The Na i λ5889.95 line is detected toward all but one source, while the weaker K i λ7698.96 line is detected in about two-thirds of the sample. The similarity in their peak centroids and the significant positive correlation between their equivalent widths demonstrate that these transitions trace the same atomic gas. The absorption lines are present toward both disk and diskless young stellar objects, which excludes cold gas within themore » circumstellar disk as the absorbing material. A comparison of Na i and CO detections and peak centroids demonstrates that the atomic gas and molecular gas are not co-located, the atomic gas being more extended than the molecular gas. The width of the atomic lines corroborates this finding and points to atomic gas about an order of magnitude warmer than the molecular gas. The distribution of Na i radial velocities shows a clear spatial gradient along the length of the Taurus molecular cloud filaments. This suggests that absorption is associated with the Taurus molecular cloud. Assuming that the gradient is due to cloud rotation, the rotation of the atomic gas is consistent with differential galactic rotation, whereas the rotation of the molecular gas, although with the same rotation axis, is retrograde. Our analysis shows that narrow Na i and K i absorption resonance lines are useful tracers of the atomic envelope of molecular clouds. In line with recent findings from giant molecular clouds, our results demonstrate that the velocity fields of the atomic and molecular gas are misaligned. The angular momentum of a molecular cloud is not simply inherited from the rotating Galactic disk from which it formed but may be redistributed by cloud–cloud interactions.« less

Volunteered Cloud Computing for Disaster Management

NASA Astrophysics Data System (ADS)

Evans, J. D.; Hao, W.; Chettri, S. R.

2014-12-01

Disaster management relies increasingly on interpreting earth observations and running numerical models; which require significant computing capacity - usually on short notice and at irregular intervals. Peak computing demand during event detection, hazard assessment, or incident response may exceed agency budgets; however some of it can be met through volunteered computing, which distributes subtasks to participating computers via the Internet. This approach has enabled large projects in mathematics, basic science, and climate research to harness the slack computing capacity of thousands of desktop computers. This capacity is likely to diminish as desktops give way to battery-powered mobile devices (laptops, smartphones, tablets) in the consumer market; but as cloud computing becomes commonplace, it may offer significant slack capacity -- if its users are given an easy, trustworthy mechanism for participating. Such a "volunteered cloud computing" mechanism would also offer several advantages over traditional volunteered computing: tasks distributed within a cloud have fewer bandwidth limitations; granular billing mechanisms allow small slices of "interstitial" computing at no marginal cost; and virtual storage volumes allow in-depth, reversible machine reconfiguration. Volunteered cloud computing is especially suitable for "embarrassingly parallel" tasks, including ones requiring large data volumes: examples in disaster management include near-real-time image interpretation, pattern / trend detection, or large model ensembles. In the context of a major disaster, we estimate that cloud users (if suitably informed) might volunteer hundreds to thousands of CPU cores across a large provider such as Amazon Web Services. To explore this potential, we are building a volunteered cloud computing platform and targeting it to a disaster management context. Using a lightweight, fault-tolerant network protocol, this platform helps cloud users join parallel computing projects; automates reconfiguration of their virtual machines; ensures accountability for donated computing; and optimizes the use of "interstitial" computing. Initial applications include fire detection from multispectral satellite imagery and flood risk mapping through hydrological simulations.

[CII] observations of H2 molecular layers in transition clouds

NASA Astrophysics Data System (ADS)

Velusamy, T.; Langer, W. D.; Pineda, J. L.; Goldsmith, P. F.; Li, D.; Yorke, H. W.

2010-10-01

We present the first results on the diffuse transition clouds observed in [CII] line emission at 158 μm (1.9 THz) towards Galactic longitudes near 340° (5 LOSs) & 20° (11 LOSs) as part of the HIFI tests and GOT C+ survey. Out of the total 146 [CII] velocity components detected by profile fitting we identify 53 as diffuse molecular clouds with associated 12CO emission but without 13CO emission and characterized by AV < 5 mag. We estimate the fraction of the [CII] emission in the diffuse HI layer in each cloud and then determine the [CII] emitted from the molecular layers in the cloud. We show that the excess [CII] intensities detected in a few clouds is indicative of a thick H2 layer around the CO core. The wide range of clouds in our sample with thin to thick H2 layers suggests that these are at various evolutionary states characterized by the formation of H2 and CO layers from HI and C+, respectively. In about 30% of the clouds the H2 column densities (“dark gas”) traced by the [CII] is 50% or more than that traced by 12CO emission. On the average ~25% of the total H2 in these clouds is in an H2 layer which is not traced by CO. We use the HI, [CII], and 12CO intensities in each cloud along with simple chemical models to obtain constraints on the FUV fields and cosmic ray ionization rates. Herschel is an ESA space observatory with science instruments provided by European-led Principal Investigator consortia and with important participation from NASA.

Method and Apparatus for Monitoring the Integrity of a Geomembrane Liner using time Domain Reflectometry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Morris, John L.

1998-11-09

Leaks are detected in a multi-layered geomembrane liner by a two-dimensional time domain reflectometry (TDR) technique. The TDR geomembrane liner is constructed with an electrically conductive detection layer positioned between two electrically non-conductive dielectric layers, which are each positioned between the detection layer and an electrically conductive reference layer. The integrity of the TDR geomembrane liner is determined by generating electrical pulses within the detection layer and measuring the time delay for any reflected electrical energy caused by absorption of moisture by a dielectric layer.

Method and apparatus for monitoring the integrity of a geomembrane liner using time domain reflectometry

DOEpatents

Morrison, John L [Idaho Falls, ID

2001-04-24

Leaks are detected in a multi-layered geomembrane liner by a two-dimensional time domain reflectometry (TDR) technique. The TDR geomembrane liner is constructed with an electrically conductive detection layer positioned between two electrically non-conductive dielectric layers, which are each positioned between the detection layer and an electrically conductive reference layer. The integrity of the TDR geomembrane liner is determined by generating electrical pulses within the detection layer and measuring the time delay for any reflected electrical energy caused by absorption of moisture by a dielectric layer.

An intelligent control system for failure detection and controller reconfiguration

NASA Technical Reports Server (NTRS)

Biswas, Saroj K.

1994-01-01

We present an architecture of an intelligent restructurable control system to automatically detect failure of system components, assess its impact on system performance and safety, and reconfigure the controller for performance recovery. Fault detection is based on neural network associative memories and pattern classifiers, and is implemented using a multilayer feedforward network. Details of the fault detection network along with simulation results on health monitoring of a dc motor have been presented. Conceptual developments for fault assessment using an expert system and controller reconfiguration using a neural network are outlined.

Classification of Clouds in Satellite Imagery Using Adaptive Fuzzy Sparse Representation.

PubMed

Jin, Wei; Gong, Fei; Zeng, Xingbin; Fu, Randi

2016-12-16

Automatic cloud detection and classification using satellite cloud imagery have various meteorological applications such as weather forecasting and climate monitoring. Cloud pattern analysis is one of the research hotspots recently. Since satellites sense the clouds remotely from space, and different cloud types often overlap and convert into each other, there must be some fuzziness and uncertainty in satellite cloud imagery. Satellite observation is susceptible to noises, while traditional cloud classification methods are sensitive to noises and outliers; it is hard for traditional cloud classification methods to achieve reliable results. To deal with these problems, a satellite cloud classification method using adaptive fuzzy sparse representation-based classification (AFSRC) is proposed. Firstly, by defining adaptive parameters related to attenuation rate and critical membership, an improved fuzzy membership is introduced to accommodate the fuzziness and uncertainty of satellite cloud imagery; secondly, by effective combination of the improved fuzzy membership function and sparse representation-based classification (SRC), atoms in training dictionary are optimized; finally, an adaptive fuzzy sparse representation classifier for cloud classification is proposed. Experiment results on FY-2G satellite cloud image show that, the proposed method not only improves the accuracy of cloud classification, but also has strong stability and adaptability with high computational efficiency.

HUBBLE SPOTS NORTHERN HEMISPHERIC CLOUDS ON URANUS

NASA Technical Reports Server (NTRS)

2002-01-01

Using visible light, astronomers for the first time this century have detected clouds in the northern hemisphere of Uranus. The newest images, taken July 31 and Aug. 1, 1997 with NASA Hubble Space Telescope's Wide Field and Planetary Camera 2, show banded structure and multiple clouds. Using these images, Dr. Heidi Hammel (Massachusetts Institute of Technology) and colleagues Wes Lockwood (Lowell Observatory) and Kathy Rages (NASA Ames Research Center) plan to measure the wind speeds in the northern hemisphere for the first time. Uranus is sometimes called the 'sideways' planet, because its rotation axis is tipped more than 90 degrees from the planet's orbit around the Sun. The 'year' on Uranus lasts 84 Earth years, which creates extremely long seasons - winter in the northern hemisphere has lasted for nearly 20 years. Uranus has also been called bland and boring, because no clouds have been detectable in ground-based images of the planet. Even to the cameras of the Voyager spacecraft in 1986, Uranus presented a nearly uniform blank disk, and discrete clouds were detectable only in the southern hemisphere. Voyager flew over the planet's cloud tops near the dead of northern winter (when the northern hemisphere was completely shrouded in darkness). Spring has finally come to the northern hemisphere of Uranus. The newest images, both the visible-wavelength ones described here and those taken a few days earlier with the Near Infrared and Multi-Object Spectrometer (NICMOS) by Erich Karkoschka (University of Arizona), show a planet with banded structure and detectable clouds. Two images are shown here. The 'aqua' image (on the left) is taken at 5,470 Angstroms, which is near the human eye's peak response to wavelength. Color has been added to the image to show what a person on a spacecraft near Uranus might see. Little structure is evident at this wavelength, though with image-processing techniques, a small cloud can be seen near the planet's northern limb (rightmost edge). The 'red' image (on the right) is taken at 6,190 Angstroms, and is sensitive to absorption by methane molecules in the planet's atmosphere. The banded structure of Uranus is evident, and the small cloud near the northern limb is now visible. Scientists are expecting that the discrete clouds and banded structure may become even more pronounced as Uranus continues in its slow pace around the Sun. 'Some parts of Uranus haven't seen the Sun in decades,' says Dr. Hammel, 'and historical records suggest that we may see the development of more banded structure and patchy clouds as the planet's year progresses.' Some scientists have speculated that the winds of Uranus are not symmetric around the planet's equator, but no clouds were visible to test those theories. The new data will provide the opportunity to measure the northern winds. Hammel and colleagues expect to have results soon. Credits: Heidi Hammel (Massachusetts Institute of Technology), and NASA.

First X-ray Statistical Tests for Clumpy-Torus Models: Constraints from RXTEmonitoring of Seyfert AGN

NASA Astrophysics Data System (ADS)

Markowitz, Alex; Krumpe, Mirko; Nikutta, R.

2016-06-01

In two papers (Markowitz, Krumpe, & Nikutta 2014, and Nikutta et al., in prep.), we derive the first X-ray statistical constraints for clumpy-torus models in Seyfert AGN by quantifying multi-timescale variability in line of-sight X-ray absorbing gas as a function of optical classification.We systematically search for discrete absorption events in the vast archive of RXTE monitoring of 55 nearby type Is and Compton-thin type IIs. We are sensitive to discrete absorption events due to clouds of full-covering, neutral/mildly ionized gas transiting the line of sight. Our results apply to both dusty and non-dusty clumpy media, and probe model parameter space complementary to that for eclipses observed with XMM-Newton, Suzaku, and Chandra.We detect twelve eclipse events in eight Seyferts, roughly tripling the number previously published from this archive. Event durations span hours to years. Most of our detected clouds are Compton-thin, and most clouds' distances from the black hole are inferred to be commensurate with the outer portions of the BLR or the inner regions of infrared-emitting dusty tori.We present the density profiles of the highest-quality eclipse events; the column density profile for an eclipsing cloud in NGC 3783 is doubly spiked, possibly indicating a cloud that is being tidallysheared. We discuss implications for cloud distributions in the context of clumpy-torus models. We calculate eclipse probabilities for orientation-dependent Type I/II unification schemes.We present constraints on cloud sizes, stability, and radial distribution. We infer that clouds' small angular sizes as seen from the SMBH imply 107 clouds required across the BLR + torus. Cloud size is roughly proportional to distance from the black hole, hinting at the formation processes (e.g., disk fragmentation). All observed clouds are sub-critical with respect to tidal disruption; self-gravity alone cannot contain them. External forces, such as magnetic fields or ambient pressure, are needed to contain them; otherwise, clouds must be short-lived.

Efficient surface formation route of interstellar hydroxylamine through NO hydrogenation. II. The multilayer regime in interstellar relevant ices

NASA Astrophysics Data System (ADS)

Fedoseev, G.; Ioppolo, S.; Lamberts, T.; Zhen, J. F.; Cuppen, H. M.; Linnartz, H.

2012-08-01

Hydroxylamine (NH2OH) is one of the potential precursors of complex pre-biotic species in space. Here, we present a detailed experimental study of hydroxylamine formation through nitric oxide (NO) surface hydrogenation for astronomically relevant conditions. The aim of this work is to investigate hydroxylamine formation efficiencies in polar (water-rich) and non-polar (carbon monoxide-rich) interstellar ice analogues. A complex reaction network involving both final (N2O, NH2OH) and intermediate (HNO, NH2O., etc.) products is discussed. The main conclusion is that hydroxyl-amine formation takes place via a fast and barrierless mechanism and it is found to be even more abundantly formed in a water-rich environment at lower temperatures. In parallel, we experimentally verify the non-formation of hydroxylamine upon UV photolysis of NO ice at cryogenic temperatures as well as the non-detection of NC- and NCO-bond bearing species after UV processing of NO in carbon monoxide-rich ices. Our results are implemented into an astrochemical reaction model, which shows that NH2OH is abundant in the solid phase under dark molecular cloud conditions. Once NH2OH desorbs from the ice grains, it becomes available to form more complex species (e.g., glycine and β-alanine) in gas phase reaction schemes.

Determining the Best Method for Estimating the Observed Level of Maximum Detrainment Based on Radar Reflectivity

DOE Office of Scientific and Technical Information (OSTI.GOV)

Carletta, Nicholas D.; Mullendore, Gretchen L.; Starzec, Mariusz

Convective mass transport is the transport of mass from near the surface up to the upper troposphere and lower stratosphere (UTLS) by a deep convective updraft. This transport can alter the chemical makeup and water vapor balance of the UTLS, which affects cloud formation and the radiative properties of the atmosphere. It is therefore important to understand the exact altitudes at which mass is detrained from convection. The purpose of this study was to improve upon previously published methodologies for estimating the level of maximum detrainment (LMD) within convection using data from a single ground-based radar. Four methods were usedmore » to identify the LMD and validated against dual-Doppler derived vertical mass divergence fields for six cases with a variety of storm types. The best method for locating the LMD was determined to be the method that used a reflectivity texture technique to determine convective cores and a multi-layer echo identification to determine anvil locations. Although an improvement over previously published methods, the new methodology still produced unreliable results in certain regimes. The methodology worked best when applied to mature updrafts, as the anvil needs time to grow to a detectable size. Thus, radar reflectivity is found to be valuable in estimating the LMD, but storm maturity must also be considered for best results.« less

The symmetry and coupling properties of solutions in general anisotropic multilayer waveguides.

PubMed

Hernando Quintanilla, F; Lowe, M J S; Craster, R V

2017-01-01

Multilayered plate and shell structures play an important role in many engineering settings where, for instance, coated pipes are commonplace such as in the petrochemical, aerospace, and power generation industries. There are numerous demands, and indeed requirements, on nondestructive evaluation (NDE) to detect defects or to measure material properties using guided waves; to choose the most suitable inspection approach, it is essential to know the properties of the guided wave solutions for any given multilayered system and this requires dispersion curves computed reliably, robustly, and accurately. Here, the circumstances are elucidated, and possible layer combinations, under which guided wave solutions, in multilayered systems composed of generally anisotropic layers in flat and cylindrical geometries, have specific properties of coupling and parity; the partial wave decomposition of the wave field is utilised to unravel the behaviour. A classification into five families is introduced and the authors claim that this is the fundamental way to approach generally anisotropic waveguides. This coupling and parity provides information to be used in the design of more efficient and robust dispersion curve tracing algorithms. A critical benefit is that the analysis enables the separation of solutions into categories for which dispersion curves do not cross; this allows the curves to be calculated simply and without ambiguity.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shah, S.; Ghosh, K.; Jejurikar, S.

Graphical abstract: - Highlights: • Investigation of ground state energy in single and multi-layered InAs/GaAs QD. • Strain reducing layer (InGaAs) prevents the formation of non-radiative. • Strain reducing layer (InGaAs) is responsible for high activation energy. • Significant deviation from the Varshni model, E(T) = E − αT{sup 2}/T + β. - Abstract: Vertically coupled, multilayered InAs/GaAs quantum dots (QDs) covered with thin InGaAs strain-reducing layers (SRLs) are in demand for various technological applications. We investigated low temperature photoluminescence of single and multilayered structures in which the SRL thickness was varied. The SRL layer was responsible for high activationmore » energies. Deviation of experimental data from the Varshni (1967) model, E(T) = E − ∞ T{sup 2}/T + β, suggests that the InAs-layered QDs have properties different from those in bulk material. Anomalous ground-state peak linewidths (FWHM), especially for annealed multilayer structures, were observed. A ground-state peak blue-shift with a broadened linewidth was also observed. Loss of intensity was detected in samples annealed at 800 °C. Presence of SRLs prevents formation of non-radiative centers under high temperature annealing. The results indicate the potential importance of such structures in optoelectronic applications.« less

Scientists Discover Sugar in Space

NASA Astrophysics Data System (ADS)

2000-06-01

The prospects for life in the Universe just got sweeter, with the first discovery of a simple sugar molecule in space. The discovery of the sugar molecule glycolaldehyde in a giant cloud of gas and dust near the center of our own Milky Way Galaxy was made by scientists using the National Science Foundation's 12 Meter Telescope, a radio telescope on Kitt Peak, Arizona. "The discovery of this sugar molecule in a cloud from which new stars are forming means it is increasingly likely that the chemical precursors to life are formed in such clouds long before planets develop around the stars," said Jan M. Hollis of the NASA Goddard Space Flight Center in Greenbelt, MD. Hollis worked with Frank J. Lovas of the University of Illinois and Philip R. Jewell of the National Radio Astronomy Observatory (NRAO) in Green Bank, WV, on the observations, made in May. The scientists have submitted their results to the Astrophysical Journal Letters. "This discovery may be an important key to understanding the formation of life on the early Earth," said Jewell. Conditions in interstellar clouds may, in some cases, mimic the conditions on the early Earth, so studying the chemistry of interstellar clouds may help scientists understand how bio-molecules formed early in our planet's history. In addition, some scientists have suggested that Earth could have been "seeded" with complex molecules by passing comets, made of material from the interstellar cloud that condensed to form the Solar System. Glycolaldehyde, an 8-atom molecule composed of carbon, oxygen and hydrogen, can combine with other molecules to form the more-complex sugars Ribose and Glucose. Ribose is a building block of nucleic acids such as RNA and DNA, which carry the genetic code of living organisms. Glucose is the sugar found in fruits. Glycolaldehyde contains exactly the same atoms, though in a different molecular structure, as methyl formate and acetic acid, both of which were detected previously in interstellar clouds. Glycolaldehyde is a simpler molecular cousin to table sugar, the scientists say. The sugar molecule was detected in a large cloud of gas and dust some 26,000 light-years away, near the center of our Galaxy. Such clouds, often many light-years across, are the material from which new stars are formed. Though very rarified by Earth standards, these interstellar clouds are the sites of complex chemical reactions that occur over hundreds of thousands or millions of years. So far, about 120 different molecules have been discovered in these clouds. Most of these molecules contain a small number of atoms, and only a few molecules with eight or more atoms have been found in interstellar clouds. The 12 Meter Telescope "Finding glycolaldehyde in one of these interstellar clouds means that such molecules can be formed even in very rarified conditions," said Hollis. "We don't yet understand how it could be formed there," he added. "A combination of more astronomical observations and theoretical chemistry work will be required to resolve the mystery of how this molecule is formed in space." "We hope this discovery inspires renewed efforts to find even more kinds of molecules, so that, with a better idea of the total picture, we may be able to deduce the details of the prebiotic chemistry taking place in interstellar clouds," Hollis said. The discovery was made by detecting faint radio emission from the sugar molecules in the interstellar cloud. Molecules rotate end-for-end, and as they change from one rotational energy state to another, they emit radio waves at precise frequencies. The "family" of radio frequencies emitted by a particular molecule forms a unique "fingerprint" that scientists can use to identify that molecule. The scientists identified glycolaldehyde by detecting six frequencies of radio emission in what is termed the millimeter-wavelength region of the electromagnetic spectrum -- a region between more-familiar microwaves and infrared radiation. The NRAO 12 Meter Telescope used to detect the sugar molecule has been a pioneer instrument in the detection of molecules in space. Built in 1967, it made the first detections of dozens of the molecules now known to exist in space, including the important first discovery of carbon monoxide, now widely used by astronomers as a signpost showing regions where stars are being formed. The 12 Meter Telescope is scheduled to be closed at the end of July, in preparation for the Atacama Large Millimeter Array, an advanced system of 64 radio-telescope antennas in northern Chile now being developed by an international partnership. The National Radio Astronomy Observatory is a facility of the National Science Foundation, operated under cooperative agreement by Associated Universities, Inc. Giant Molecular Cloud Near Milky Way's Center The giant molecular cloud, known as Sagittarius B2 (North), as seen by the NSF's Very Large Array (VLA) radio telescope in New Mexico. This is the cloud in which scientists using the 12 Meter Telescope detected the simple sugar molecule glycolaldehyde. This VLA image shows hydrogen gas in a region nearly 3 light-years across. In this image, red indicates stronger radio emission; blue weaker. The 12 Meter Telescope studied this region at much shorter wavelengths, which revealed the evidence of sugar molecules. CREDIT: R. Gaume, M. Claussen, C. De Pree, W.M. Goss, D. Mehringer, NRAO/AUI/NSF.

Bag-of-visual-phrases and hierarchical deep models for traffic sign detection and recognition in mobile laser scanning data

NASA Astrophysics Data System (ADS)

Yu, Yongtao; Li, Jonathan; Wen, Chenglu; Guan, Haiyan; Luo, Huan; Wang, Cheng

2016-03-01

This paper presents a novel algorithm for detection and recognition of traffic signs in mobile laser scanning (MLS) data for intelligent transportation-related applications. The traffic sign detection task is accomplished based on 3-D point clouds by using bag-of-visual-phrases representations; whereas the recognition task is achieved based on 2-D images by using a Gaussian-Bernoulli deep Boltzmann machine-based hierarchical classifier. To exploit high-order feature encodings of feature regions, a deep Boltzmann machine-based feature encoder is constructed. For detecting traffic signs in 3-D point clouds, the proposed algorithm achieves an average recall, precision, quality, and F-score of 0.956, 0.946, 0.907, and 0.951, respectively, on the four selected MLS datasets. For on-image traffic sign recognition, a recognition accuracy of 97.54% is achieved by using the proposed hierarchical classifier. Comparative studies with the existing traffic sign detection and recognition methods demonstrate that our algorithm obtains promising, reliable, and high performance in both detecting traffic signs in 3-D point clouds and recognizing traffic signs on 2-D images.