scholarly journals Joint Monitoring and Analysis of Sea Fog Using Dual Visibility Lidar in Ningbo, China

2021 ◽  
Vol 2112 (1) ◽  
pp. 012014
Author(s):  
Lijun Hu ◽  
Hao Yang ◽  
Hao Wang ◽  
Xinyue Ren
Keyword(s):  
Liquid Water Content ◽  
Lidar Data ◽  
Equivalent Diameter ◽  
Large Area ◽  
Forward Scatter ◽  
Detection Range ◽  
Sea Fog ◽  
Low Visibility ◽  
Joint Monitoring ◽  
532 Nm

Abstract Visibility lidar has obvious monitoring advantages over forward scatter visibility sensors or fog droplet spectrometers; it can measure visibility information over a large area. In 2021, two visibility lidar instruments (1064 or 532 nm wavelengths) were installed in Beilun, Ningbo Zhoushan Port, to monitor sea fog. Comparing their monitoring data to those of forward scatter visibility sensors and a fog droplet spectrometer revealed that the visibility lidar instruments could obtain energy progress information section-by-section in the monitoring path, and could directly reflect sea fog changes. The 1064 nm lidar outperformed the 532 nm lidar regarding sea fog detection. The effective detection range decreased significantly with decreasing visibility; the reliability decreased in low-visibility, uneven atmospheres. In a low-visibility but uniform atmosphere, however, lidar data corresponded well with forward dispersion data. The 532 nm and 1064 nm lidar data sometimes differed at the same monitoring position owing to differing heights and particle reflection angles. During a sea fog event on May 9, 2021, the maximum droplet concentration was 14 cm−3, the maximum liquid water content was 0.21 g·m−3, and the maximum equivalent diameter was 49 μm. The formation of this sea fog was dominated by large particles.

scholarly journals Evaluating the integrity of forested riparian buffers over a large area using LiDAR data and Google Earth Engine

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Hamdi A. Zurqani ◽  
Christopher J. Post ◽  
Elena A. Mikhailova ◽  
Michael P. Cope ◽  
Jeffery S. Allen ◽  
...  
Keyword(s):  
Google Earth ◽  
Riparian Buffers ◽  
Lidar Data ◽  
Large Area ◽  
Google Earth Engine

scholarly journals Aerosol–Cloud Interaction in Deep Convective Clouds over the Indian Peninsula Using Spectral (Bin) Microphysics

2017 ◽  
Vol 74 (10) ◽  
pp. 3145-3166 ◽  
Author(s):  
K. Gayatri ◽  
S. Patade ◽  
T. V. Prabha
Keyword(s):  
Size Distribution ◽  
Cloud Condensation Nuclei ◽  
Wrf Model ◽  
Cloud Droplet ◽  
Liquid Water Content ◽  
Cloud Microphysics ◽  
Large Area ◽  
Surface Precipitation ◽  
Aerosol Cloud ◽  
Bin Microphysics

Abstract The Weather Research and Forecasting (WRF) Model coupled with a spectral bin microphysics (SBM) scheme is used to investigate aerosol effects on cloud microphysics and precipitation over the Indian peninsular region. The main emphasis of the study is in comparing simulated cloud microphysical structure with in situ aircraft observations from the Cloud Aerosol Interaction and Precipitation Enhancement Experiment (CAIPEEX). Aerosol–cloud interaction over the rain-shadow region is investigated with observed and simulated size distribution spectra of cloud droplets and ice particles in monsoon clouds. It is shown that size distributions as well as other microphysical characteristics obtained from simulations such as liquid water content, cloud droplet effective radius, cloud droplet number concentration, and thermodynamic parameters are in good agreement with the observations. It is seen that in clouds with high cloud condensation nuclei (CCN) concentrations, snow and graupel size distribution spectra were broader compared to clouds with low concentrations of CCN, mainly because of enhanced riming in the presence of a large number of droplets with a diameter of 10–30 μm. The Hallett–Mossop ice multiplication process is illustrated to have an impact on snow and graupel mass. The changes in CCN concentrations have a strong effect on cloud properties over the domain, amounts of cloud water, and the glaciation of the clouds, but the effects on surface precipitation are small when averaged over a large area. Overall enhancement of cold-phase cloud processes in the high-CCN case contributed to slight enhancement (5%) in domain-averaged surface precipitation.

An effective detection range calculation model for shipboard infrared system under sea fog conditions

2019 ◽  
Vol 48 (5) ◽  
pp. 504002
Author(s):  
李 伟 Li Wei ◽  
卲利民 Shao Limin ◽  
唐 君 Tang Jun ◽  
郑崇伟 Zheng Chongwei
Keyword(s):  
Calculation Model ◽  
Detection Range ◽  
Sea Fog ◽  
Range Calculation

scholarly journals The Microphysical Properties of a Sea-Fog Event along the West Coast of the Yellow Sea in Spring

Atmosphere ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 413
Author(s):  
Shengkai Wang ◽  
Li Yi ◽  
Suping Zhang ◽  
Xiaomeng Shi ◽  
Xianyao Chen
Keyword(s):  
Distribution Function ◽  
Yellow Sea ◽  
Droplet Size Distribution ◽  
Liquid Water Content ◽  
Mean Value ◽  
The Yellow Sea ◽  
Sea Fog ◽  
Microphysical Properties ◽  
The Mean ◽  
Microphysical Parameterization

The microphysics and visibility of a sea-fog event were measured at the Qingdao Meteorological Station (QDMS) (120°19′ E, 36°04′ N) from 5 April to 8 April 2017. The two foggy periods with low visibility (<200 m) lasted 31 h together. The mean value of the average liquid water content (LWC) was 0.057 g m−3, and the mean value of the number concentration (NUM) was 64.4 cm−3. We found that although large droplets only constituted a small portion of the total number of the concentration; they contributed the majority of the LWC and therefore determined ~76% of total extinction of the visibility. The observed droplet-size distribution (DSD) exhibited a new bimodal Gaussian (G-exponential) distribution function, rather than the well-accepted Gamma distribution. This work suggests a new distribution function to describe fog DSD, which may help to improve the microphysical parameterization for the Yellow Sea fog numerical forecasting.

scholarly journals EXTRACTION OF ELEMENT AT RISK FOR LANDSLIDES USING REMOTE SENSING METHOD

2018 ◽  
Vol XLII-4/W9 ◽  
pp. 181-188
Author(s):  
R. C. Hasan ◽  
Q. A. Rosle ◽  
M. A. Asmadi ◽  
N. A. Mohd Kamal
Keyword(s):  
At Risk ◽  
Extraction Process ◽  
Automatic Process ◽  
Landslide Risk ◽  
Lidar Data ◽  
Large Area ◽  
Building Footprint ◽  
Element At Risk ◽  
Hazard And Risk ◽  
Study Sites

<p><strong>Abstract.</strong> One of the most critical steps towards landslide risk analysis is the determination of element at risk. Element at risk describes any object that could potentially fail or exposed to hazards during disaster. Without quantification of element at risk information, it is difficult to estimate risk. This paper aims at developing a methodology to extract and quantity element at risk from airborne Light Detection and Ranging (LiDAR) data. The element at risk map produced was then used to construct exposure map which describes the amount of hazard for each element at risk involved. This study presented two study sites at Kundasang and Kota Kinabalu in Sabah with both areas have experienced major earthquake in June 2015. The results show that not all the features can be automatically extracted from the LiDAR data. For example, automatic extraction process could be done for building footprint and building heights, but for others such as roads and vegetation areas, a manual digitization is still needed because of the difficulties to differentiate between these features. In addition to this, there were also difficulties in identifying attribute for each feature, for example to separate between federal roads with state and unpaved roads. Therefore, for large area hazard and risk mapping, the authors suggested that an automatic process should be investigated in the future to reduce time and cost to extract important features from LiDAR data.</p>

scholarly journals Land/Water Discrimination And Land Cover Classification Using Multispectral Airborne Lidar Data

2021 ◽  
Author(s):  
Salem Wagih Salem Morsy
Keyword(s):  
Land Cover ◽  
Urban Areas ◽  
Region Growing ◽  
Point Clouds ◽  
Land Cover Classification ◽  
Lidar Data ◽  
Coastal Zones ◽  
532 Nm ◽  
Land Water

Multispectral airborne Light Detection And Ranging (LiDAR) systems are currently available. Optech Titan is an example of these systems, which acquires LiDAR point clouds at three independent wavelengths (1550, 1064 and 532 nm) from Earth’s surface. This dissertation aims to use the radiometric information (i.e., intensity) of the Optech Titan LiDAR data along with the geometric information (e.g., height) for land/water discrimination in coastal zones and land cover classification of urban areas. A set of point features based on elevation, intensity, and geometry was extracted and evaluated for land/water discrimination in coastal zones. In addition, an automated land/water discrimination approach based on seeded region growing algorithm was presented. Two data subsets were tested at Lake Ontario and Tobermory Harbour in Ontario, Canada. The elevation and geometry-based features achieved average overall accuracies of 72.8% - 83.3% and 69.9% -74.4%, respectively, while the intensity-based features achieved an average overall accuracy of 59.0% - 63.4%. The region growing method achieved an average overall accuracy of more than 99%, and the automation of this method is restricted by having double returns from water bodies at the 532 nm wavelength. A hierarchal point-based classification approach was presented for land cover classification of urban areas. The collected point clouds at the three wavelengths were first merged and three intensity values were estimated for each LiDAR point, followed by three-level classification approach. First, a ground filtering method was applied to separate non-ground from ground points. Second, three normalized difference vegetation indices (NDVIs) were computed, followed by NDVIs’ histograms construction. A multivariate Gaussian decomposition (MVGD) was then used to divide those histograms into buildings or trees from non-ground and roads or grass from ground points. Third, classes such as power lines, swimming pools and different types of trees were labeled based on their spectral characteristics. Three data subsets were tested representing different complexity of urban areas in Oshawa, Ontario, Canada. It is shown that the presented approach has achieved an overall accuracy up to 93.0%, which increased to more than 99% by considering the spatial coherence of the LiDAR point clouds.

scholarly journals Comparison of Wind Lidar Data and Numerical Simulations of the Low-Level Jet at a Grassland Site

Energies ◽  
2020 ◽  
Vol 13 (23) ◽  
pp. 6264
Author(s):  
Astrid Ziemann ◽  
André Galvez Arboleda ◽  
Astrid Lampert
Keyword(s):  
Wind Speed ◽  
Numerical Simulations ◽  
Lidar Data ◽  
Large Area ◽  
Data Set ◽  
Low Level ◽  
The North ◽  
Wind Lidar ◽  
Low Level Jet ◽  
Grassland Site

For the increasing importance of the wind energy branch, exact wind climatologies at the operation altitudes are essential. As wind turbines of increasing hub height are erected, the rotors are located at an altitude interval influenced by the phenomenon of low-level jet (LLJ). The main objective of the study is to assess if and how numerical simulations can represent the development especially of nocturnal LLJs in comparison to measurements. In this article, the microscale numerical model HIRVAC2D is used for a range of parameters. The simulated results for properties of the LLJ are compared to lidar data at an altitude range of 40 m to 500 m at the study site Braunschweig in the North German Plain, a grassland location that may be representative for a large area. Similarities and differences of the occurrence, height and maximum wind speed of the nocturnal LLJ are discussed using two different criteria to define a LLJ. The analysis of the lidar data set for the grassland site revealed for the first time increasing height of the LLJ with increasing wind speed during the summer months June to August 2013. The comparison of measurements and simulation data shows that boundary (and inital) conditions have to be adapted in model simulations to provide realistic LLJ properties. It was found that land use and vegetation parameters are important for practical LLJ prognosis, both for wind climatologies and nowcasting.

Experimentally Determined Optical Properties of a Polydisperse Carbon Black Cloud for a Solar Particle Receiver

2004 ◽  
Vol 126 (3) ◽  
pp. 833-841 ◽  
Author(s):  
Rudi Bertocchi ◽  
Abraham Kribus ◽  
Jacob Karni
Keyword(s):  
Optical Properties ◽  
Carbon Black ◽  
Extinction Coefficient ◽  
Mie Theory ◽  
Carbon Black Particle ◽  
Equivalent Diameter ◽  
Particle Cloud ◽  
Solar Particle ◽  
Black Particle ◽  
532 Nm

Measured physical and optical properties of a stable polydisperse carbon black particle cloud at 532 nm and 1064 nm are reported. The particle cloud consisted of 99.7% spheroid primary particles (45–570 nm diameter) and 0.3% large irregularly shaped agglomerates (1.2–7.25 μm equivalent diameter). Although the numerical fraction of the agglomerates was only 0.2%, they contributed 60% to the cloud’s scattering cross section. The extinction coefficient, scattering coefficient and the scattering phase function were measured for both parallel and perpendicular polarized radiation at linear extinction coefficients ranging from 0.6 to 4.1 m−1. The cloud exhibited strong forward scattering, with 62% of all scattered energy in a forward lobe of 15° at 532 nm and 48% at 1064 nm. The scattering albedo was measured to 35% at 532 nm and 47% at 1064 nm. The dimensionless extinction coefficient was measured to 8.25 at 532 nm. The experimental data was compared to standard Mie theory by integrating the weighed contribution based on particle size, including agglomerates, according to the detailed measured population distribution. Neglecting the contribution of the agglomerates to the cloud’s optical properties was shown to introduce discrepancies between Mie theory and measured results. The results indicate that the-Mie theory can be used for estimating the optical properties of a partially agglomerated carbon black particle cloud for simulation of a solar particle receiver.

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