scholarly journals Single ice crystal measurements during nucleation experiments with the depolarization detector IODE

2010 ◽  
Vol 10 (2) ◽  
pp. 313-325 ◽  
Author(s):  
M. Nicolet ◽  
O. Stetzer ◽  
F. Lüönd ◽  
O. Möhler ◽  
U. Lohmann
Keyword(s):  
Theoretical Calculations ◽  
Scattered Light ◽  
Detection Algorithm ◽  
Ice Nucleation ◽  
Ice Crystals ◽  
Time Signal ◽  
Depolarization Ratio ◽  
Particle Detection ◽  
Mean Values ◽  
High Particle

Abstract. In order to determine the efficiency of different aerosol particles to nucleate ice, an Ice Optical DEpolarization detector (IODE) was developed to distinguish between water droplets and ice crystals in ice nucleation chambers. A laser beam polarized linearly (power: 50 mW, wavelength: 407 nm) is directed through the chamber. The scattered light intensity from particles is measured at a scattering angle of Θ=175° in both polarization components (parallel and perpendicular). The ratio between the perpendicular intensity over the total one yields the depolarization ratio δ. Single particle detection is possible, using a peak detection algorithm. For high particle concentrations, a real-time signal averaging method can also be run simultaneously. The IODE detector was used in connection with the Zurich ice nucleation chamber during the ICIS 2007 workshop where ice nucleation experiments were performed with several aerosol types. In presence of ice crystals, a depolarization ratio could be measured on a particle-by-particle basis. Mean values of δ ranged from 0.24 to 0.37 and agree well with theoretical calculations.

scholarly journals Single ice crystal measurements during nucleation experiments with the depolarization detector IODE

2008 ◽  
Vol 8 (6) ◽  
pp. 20965-21000 ◽  
Author(s):  
M. Nicolet ◽  
O. Stetzer ◽  
U. Lohmann ◽  
O. Möhler
Keyword(s):  
Scattered Light ◽  
Detection Algorithm ◽  
Ice Nucleation ◽  
Ice Crystals ◽  
Time Signal ◽  
Particle Detection ◽  
Mean Values ◽  
High Particle ◽  
Peak Detection Algorithm ◽  
Single Particle Detection

Abstract. In order to determine the efficiency of aerosol particles of several types to nucleate ice, an Ice Optical DEpolarization detector (IODE) was developed to distinguish between water droplets and ice crystals in ice nucleation chambers. A laser beam polarized linearly (power: 50 mW, wavelength: 407 nm) is directed through the chamber. The scattered light intensity from particles is measured at a scattering angle of Θ=175° in both polarization components (parallel and perpendicular). The ratio between the perpendicular intensity over the total one gives the depolarization ratio δ. Single particle detection is possible, using a peak detection algorithm. For high particle concentrations, a real-time signal averaging method can also be run simultaneously. The IODE detector was used in connection with the Zurich ice nucleation chamber during the ICIS 2007 workshop where ice nucleation experiments were performed with several aerosol types. In presence of ice crystals, peaks were detected in both channels, generating depolarization signals. Mean values of δ ranged from 0.24 to 0.37.

Optical and Microphysical Properties of Upper Clouds Measured with the Raman Lidar and Hydrometeor Videosonde: A Case Study on 29 March 2004 over Tsukuba, Japan

2006 ◽  
Vol 63 (8) ◽  
pp. 2156-2166 ◽  
Author(s):  
Tetsu Sakai ◽  
Narihiro Orikasa ◽  
Tomohiro Nagai ◽  
Masataka Murakami ◽  
Kenichi Kusunoki ◽  
...  
Keyword(s):  
Extinction Coefficient ◽  
Theoretical Calculations ◽  
Ice Crystals ◽  
Lidar Measurement ◽  
Depolarization Ratio ◽  
Raman Lidar ◽  
Microphysical Properties ◽  
Vertical Distributions ◽  
Lidar Ratio ◽  
Cloud Particles

Abstract Optical and microphysical properties of the upper clouds at an altitude range of 5–11 km were measured over Tsukuba, Japan, on 29–30 March 2004 using a ground-based Raman lidar and a balloon-borne hydrometeor videosonde (HYVIS). The Raman lidar measured the vertical distributions of the particle extinction coefficient, backscattering coefficients, depolarization ratio, and extinction-to-backscatter ratio (lidar ratio) at 532 nm; further, it measured the water vapor mixing ratio. The HYVIS measured the vertical distributions of the particle size, shape, cross-sectional area, and number concentration of the cloud particles by taking microscopic images. The HYVIS measurement showed that the cloud particles were ice crystals whose shapes were columnar, bulletlike, platelike, and irregular, and 7–400 μm in size. The Raman lidar measurement showed that the depolarization ratio ranged from 0% to 35% and the lidar ranged from 0.3 to 30 sr for the clouds in ice-saturated air. The comparison between the measured data and theoretical calculations of the cloud optical properties suggests that the observed variations in the depolarization ratio and lidar ratio were primarily due to the variation in the proportion of the horizontally oriented ice crystals in the clouds. The optical thickness of the cloud obtained from the lidar was about 2 times lower than that calculated from the HYVIS data, and the maximum extinction coefficient was about 5 times lower than the HYVIS data. The most probable reason for the differences is the horizontal inhomogeneities of the cloud properties between the measurements sites for the two instruments.

scholarly journals Detection of Fire Smoke Plumes Based on Aerosol Scattering Using VIIRS Data over Global Fire-Prone Regions

2021 ◽  
Vol 13 (2) ◽  
pp. 196
Author(s):  
Xiaoman Lu ◽  
Xiaoyang Zhang ◽  
Fangjun Li ◽  
Mark A. Cochrane ◽  
Pubu Ciren
Keyword(s):  
Infrared Imaging ◽  
Scattered Light ◽  
Detection Algorithm ◽  
Mie Scattering ◽  
Spectral Contrast ◽  
Aerosol Scattering ◽  
Smoke Plumes ◽  
Fire Smoke ◽  
Weather And Human Health ◽  
Aerosol Index

Smoke from fires significantly influences climate, weather, and human health. Fire smoke is traditionally detected using an aerosol index calculated from spectral contrast changes. However, such methods usually miss thin smoke plumes. It also remains challenging to accurately separate smoke plumes from dust, clouds, and bright surfaces. To improve smoke plume detections, this paper presents a new scattering-based smoke detection algorithm (SSDA) depending mainly on visible and infrared imaging radiometer suite (VIIRS) blue and green bands. The SSDA is established based on the theory of Mie scattering that occurs when the diameter of an atmospheric particulate is similar to the wavelength of the scattered light. Thus, smoke commonly causes Mie scattering in VIIRS blue and green bands because of the close correspondence between smoke particulate diameters and the blue/green band wavelengths. For developing the SSDA, training samples were selected from global fire-prone regions in North America, South America, Africa, Indonesia, Siberia, and Australia. The SSDA performance was evaluated against the VIIRS aerosol detection product and smoke detections from the ultraviolet aerosol index using manually labeled fire smoke plumes as a benchmark. Results show that the SSDA smoke detections are superior to existing products due chiefly to the improved ability of the algorithm to detect thin smoke and separate fire smoke from other surface types. Moreover, the SSDA smoke distribution pattern exhibits a high spatial correlation with the global fire density map, suggesting that SSDA is capable of detecting smoke plumes of fires in near real-time across the globe.

An automatic seismic signal detection algorithm based on the Walsh transform

1981 ◽  
Vol 71 (4) ◽  
pp. 1351-1360
Author(s):  
Tom Goforth ◽  
Eugene Herrin
Keyword(s):  
Signal Detection ◽  
Real Time ◽  
Seismic Signal ◽  
Detection Algorithm ◽  
Machine Language ◽  
Walsh Transform ◽  
Time Signal ◽  
Data Systems ◽  
Detection Capability ◽  
Short Period

abstract An automatic seismic signal detection algorithm based on the Walsh transform has been developed for short-period data sampled at 20 samples/sec. Since the amplitude of Walsh function is either +1 or −1, the Walsh transform can be accomplished in a computer with a series of shifts and fixed-point additions. The savings in computation time makes it possible to compute the Walsh transform and to perform prewhitening and band-pass filtering in the Walsh domain with a microcomputer for use in real-time signal detection. The algorithm was initially programmed in FORTRAN on a Raytheon Data Systems 500 minicomputer. Tests utilizing seismic data recorded in Dallas, Albuquerque, and Norway indicate that the algorithm has a detection capability comparable to a human analyst. Programming of the detection algorithm in machine language on a Z80 microprocessor-based computer has been accomplished; run time on the microcomputer is approximately 110 real time. The detection capability of the Z80 version of the algorithm is not degraded relative to the FORTRAN version.

Monitoring and Defect Detection of an All-Composite Road Bridge

2000 ◽  
Author(s):  
Roger M. Crane ◽  
John W. Gillespie ◽  
Dirk Heider ◽  
Douglas A. Eckel ◽  
Colin P. Ratcliffe
Keyword(s):  
Structural Integrity ◽  
Theoretical Calculations ◽  
Detection Algorithm ◽  
Mode Shapes ◽  
Manufacturing Defects ◽  
Vibration Data ◽  
Composite Bridges ◽  
Longitudinal Joint ◽  
Composite Bridge ◽  
Sandwich Core

Abstract This paper presents the results of an ongoing investigation into the use of broadband vibration data to monitor the structural integrity and health of an all-composite road bridge. Bridge 1-351 on Business Route 896 in Glasgow, Delaware, was replaced with one of the first state-owned all-composite bridges in the nation in the fall of 1998. The bridge consists of two E-Glass/vinyl ester sandwich core sections (13-ft × 32 ft) joined by a longitudinal joint in the traffic direction. Each sandwich core section consists of a 28-inch deep core and 0.4-0.7-inch thick facesheets. Vibration data were obtained from the upper and lower surfaces of the bridge using a mesh of 1050 test points. From the modal information and the visualization of the data, several aspects of the structural behavior of the bridge were obtained. These characteristics include the interactions between the bridge and abutments; the effectiveness of the longitudinal joint to couple the deck sections; the effectiveness of the core to couple the face sheets; and the structural integrity and dynamic consistency of the entire structure. Mode shapes and natural frequencies were determined and are correlated with theoretical calculations and vibration analyses conducted for this bridge. A novel algorithm using the vibration data is being developed that enables local perturbations sensitive to the state of the material (e.g. manufacturing defects, material degradation or service damage) to be detected and spatially located in the bridge. This technique has been successfully validated for locating damage in 1-D beam structures and is being extended to the 3-D sandwich configuration of the bridge. By coupling this damage detection algorithm with the more conventional modal technique, the quality assurance/quality control and health monitoring of large composite bridge can be obtained.

scholarly journals Simulating the influence of primary biological aerosol particles on clouds by heterogeneous ice nucleation

2018 ◽  
Vol 18 (20) ◽  
pp. 15437-15450 ◽  
Author(s):  
Matthias Hummel ◽  
Corinna Hoose ◽  
Bernhard Pummer ◽  
Caroline Schaupp ◽  
Janine Fröhlich-Nowoisky ◽  
...  
Keyword(s):  
Pseudomonas Syringae ◽  
Aerosol Particles ◽  
Fungal Spores ◽  
Ice Nucleation ◽  
Ice Crystals ◽  
Atmospheric Measurements ◽  
Cloud Ice ◽  
Biological Aerosol Particles ◽  
Ice Phase ◽  
Heterogeneous Ice Nucleation

Abstract. Primary ice formation, which is an important process for mixed-phase clouds with an impact on their lifetime, radiative balance, and hence the climate, strongly depends on the availability of ice-nucleating particles (INPs). Supercooled droplets within these clouds remain liquid until an INP immersed in or colliding with the droplet reaches its activation temperature. Only a few aerosol particles are acting as INPs and the freezing efficiency varies among them. Thus, the fraction of supercooled water in the cloud depends on the specific properties and concentrations of the INPs. Primary biological aerosol particles (PBAPs) have been identified as very efficient INPs at high subzero temperatures, but their very low atmospheric concentrations make it difficult to quantify their impact on clouds. Here we use the regional atmospheric model COSMO–ART to simulate the heterogeneous ice nucleation by PBAPs during a 1-week case study on a domain covering Europe. We focus on three highly ice-nucleation-active PBAP species, Pseudomonas syringae bacteria cells and spores from the fungi Cladosporium sp. and Mortierella alpina. PBAP emissions are parameterized in order to represent the entirety of bacteria and fungal spores in the atmosphere. Thus, only parts of the simulated PBAPs are assumed to act as INPs. The ice nucleation parameterizations are specific for the three selected species and are based on a deterministic approach. The PBAP concentrations simulated in this study are within the range of previously reported results from other modeling studies and atmospheric measurements. Two regimes of PBAP INP concentrations are identified: a temperature-limited and a PBAP-limited regime, which occur at temperatures above and below a maximal concentration at around −10 ∘C, respectively. In an ensemble of control and disturbed simulations, the change in the average ice crystal concentration by biological INPs is not statistically significant, suggesting that PBAPs have no significant influence on the average state of the cloud ice phase. However, if the cloud top temperature is below −15 ∘C, PBAP can influence the cloud ice phase and produce ice crystals in the absence of other INPs. Nevertheless, the number of produced ice crystals is very low and it has no influence on the modeled number of cloud droplets and hence the cloud structure.

scholarly journals Airborne pollen observations using a multi-wavelength Raman polarization lidar in Finland: characterization of pure pollen types

2020 ◽  
Author(s):  
Xiaoxia Shang ◽  
Elina Giannakaki ◽  
Stephanie Bohlmann ◽  
Maria Filioglou ◽  
Annika Saarto ◽  
...  
Keyword(s):  
Optical Properties ◽  
Airborne Pollen ◽  
Pollen Grains ◽  
Wavelength Dependence ◽  
Depolarization Ratio ◽  
Mean Values ◽  
Pollen Types ◽  
Pine Pollen ◽  
Significant Wavelength ◽  
532 Nm

Abstract. We present a novel algorithm for characterizing the optical properties of pure pollen particles, based on the depolarization values obtained in lidar measurements. The algorithm was first tested and validated through a simulator, and then applied to the lidar observations during a four-month pollen campaign from May to August 2016 at the European Aerosol Research Lidar Network (EARLINET) station in Kuopio (62°44′ N, 27°33′ E), in Eastern Finland. Twenty types of pollen were observed and identified from concurrent measurements with Burkard sampler; Birch (Betula), pine (Pinus), spruce (Picea) and nettle (Urtica) pollen were most abundant, contributing more than 90 % of total pollen load, regarding number concentrations. Mean values of lidar-derived optical properties in the pollen layer were retrieved for four intense pollination periods (IPPs). Lidar ratios at both 355 and 532 nm ranged from 55 to 70 sr for all pollen types, without significant wavelength-dependence. Enhanced depolarization ratio was found when there were pollen grains in the atmosphere, and even higher depolarization ratio (with mean values of 25 % or 14 %) was observed with presence of the more non-spherical spruce or pine pollen. The depolarization ratio at 532 nm of pure pollen particles was assessed, resulting to 24 ± 3 % and 36 ± 5 % for birch and pine pollen, respectively. Pollen optical properties at 1064 nm and 355 nm were also estimated. The backscatter-related Ångström exponent between 532 and 1064 nm was assessed as ~ 0.8 (~ 0.5) for pure birch (pine) pollen, thus the longer wavelength would be better choice to trace pollen in the air. The pollen depolarization ratio at 355 nm of 17 % and 30 % were found for birch and pine pollen, respectively. The depolarization values show a wavelength dependence for pollen. This can be the key parameter for pollen detection and characterization.

Theoretical Methods of Images Processing in Optoelectronic Systems

Biometrics ◽  
2017 ◽  
pp. 361-381
Author(s):  
Tatyana Strelkova ◽  
Vladimir Kartashov ◽  
Alexander P. Lytyuga ◽  
Alexander I. Strelkov
Keyword(s):  
Mathematical Model ◽  
Signal To Noise Ratio ◽  
Detection Algorithm ◽  
Optical Signal ◽  
Optoelectronic System ◽  
Output Plane ◽  
Mean Values ◽  
Optical Signals ◽  
Images Processing ◽  
Detection Characteristics

The chapter covers development of mathematical model of signals in output plane of optoelectronic system with registration of optical signals from objects. Analytical forms for mean values and dispersion of signal and interference components of photo receiver response are given. The mathematical model can be used as a base with detection algorithm development for optical signal from objects. An algorithm of signals' detection in output plane of optoelectronic system for the control is offered. The algorithm is synthesized taking into account corpuscular and statistical properties of optical signals. Analytical expressions for mean values and signal and noise components dispersion are cited. These expressions can be used for estimating efficiency of the offered algorithm by the criterion of detection probabilistic characteristics and criterion of signal/noise relation value. The possibility of signal detection characteristics improvement with low signal-to-noise ratio is shown.

scholarly journals Falling Mixed-Phase Ice Virga and their Liquid Parent Cloud Layers as Observed by Ground-Based Lidars

2020 ◽  
Vol 12 (13) ◽  
pp. 2094
Author(s):  
Chong Cheng ◽  
Fan Yi
Keyword(s):  
Local Maximum ◽  
Water Layer ◽  
Supercooled Liquid ◽  
Mixed Phase ◽  
Ice Crystals ◽  
Cloud Base ◽  
Depolarization Ratio ◽  
Ice Crystal ◽  
Liquid Drops ◽  
The Mean

Falling mixed-phase virga from a thin supercooled liquid layer cloud base were observed on 20 occasions at altitudes of 2.3–9.4 km with ground-based lidars at Wuhan (30.5 °N, 114.4 °E), China. Polarization lidar profile (3.75-m) analysis reveals some ubiquitous features of both falling mixed-phase virga and their liquid parent cloud layers. Each liquid parent cloud had a well-defined base height where the backscatter ratio R was ~7.0 and the R profile had a clear inflection point. At an altitude of ~34 m above the base height, the depolarization ratio reached its minimum value (~0.04), indicating a liquid-only level therein. The thin parent cloud layers tended to form on the top of a broad preexisting aerosol/liquid water layer. The falling virga below the base height showed firstly a significant depolarization ratio increase, suggesting that most supercooled liquid drops in the virga were rapidly frozen into ice crystals (via contact freezing). After reaching a local maximum value of the depolarization ratio, both the values of the backscatter ratio and depolarization ratio for the virga exhibited an overall decrease with decreasing height, indicating sublimated ice crystals. The diameters of the ice crystals in the virga were estimated based on an ice particle sublimation model along with the lidar and radiosonde observations. It was found that the ice crystal particles in these virga cases tended to have smaller mean diameters and narrower size distributions with increasing altitude. The mean diameter value is 350 ± 111 µm at altitudes of 4–8.5 km.

Sign in / Sign up

Export Citation Format

Share Document