scholarly journals Melting Layer Detection and Observation with the NCAR Airborne W-Band Radar

2021 ◽  
Vol 13 (9) ◽  
pp. 1660
Author(s):  
Ulrike Romatschke
Keyword(s):  
Radar Data ◽  
Detection Algorithm ◽  
Melting Layer ◽  
Cloud Data ◽  
W Band ◽  
Shallow Clouds ◽  
Linear Depolarization Ratio ◽  
The Tropics ◽  
Level Analysis ◽  
Model Temperature

A melting layer detection algorithm is developed for the NCAR 94 GHz airborne cloud radar (HIAPER CloudRadar, HCR). The detection method is based on maxima in the linear depolarization ratio and a discontinuity in the radial velocity field. A melting layer field is added to the radar data, which provides detected, interpolated, and estimated altitudes of the melting layer and the altitude of the 0 °C isotherm detected in model temperature data. The icing level is defined as the lowest melting layer, and the cloud data are flagged as either above (cold) or below (warm) the icing level. Analysis of the detected melting layer shows that the offset between the 0 °C isotherm and the actual melting layer varies with cloud type: in heavy convection sampled in the tropics, the melting layer is found up to 500 m below the 0 °C isotherm, while in shallow clouds, the offset is much smaller or sometimes vanishes completely. A relationship between the offset and the particle fall speed both above and below the melting layer is established. Special phenomena, such as a lowering of the melting layer towards the center of storms or split melting layers, were observed.

scholarly journals Automatic Designation of the Melting Layer with a Polarimetric Prototype of the WSR-88D Radar

2008 ◽  
Vol 47 (5) ◽  
pp. 1354-1364 ◽  
Author(s):  
Scott E. Giangrande ◽  
John M. Krause ◽  
Alexander V. Ryzhkov
Keyword(s):  
Numerical Model ◽  
Root Mean Square Error ◽  
Mean Square Error ◽  
Detection Algorithm ◽  
Model Output ◽  
Mean Square ◽  
Temperature Analysis ◽  
Melting Layer ◽  
Model Temperature ◽  
Melting Level

Abstract A new polarimetric melting layer detection algorithm (MLDA) is utilized to estimate the top (melting level) and bottom boundaries of the melting layer and is tailored for operational deployment. Melting layer designations from a polarimetric prototype of the Weather Surveillance Radar-1988 Doppler (WSR-88D) in central Oklahoma are validated using radiosonde and model temperature analysis. It is demonstrated that the MLDA estimates the top of the melting layer with a root-mean-square error of about 200 m within 60 km of the radar. There is evidence that the polarimetric radar might yield better spatial and temporal designation of the melting layer within the storm than that obtained from existing numerical model output and soundings.

scholarly journals A Set of Single YOLO Modalities to Detect Occluded Entities via Viewpoint Conversion

2021 ◽  
Vol 11 (13) ◽  
pp. 6016
Author(s):  
Jinsoo Kim ◽  
Jeongho Cho
Keyword(s):  
Object Detection ◽  
Autonomous Vehicles ◽  
Autonomous Driving ◽  
Detection Algorithm ◽  
Detection Accuracy ◽  
Cloud Data ◽  
Detection Techniques ◽  
Bounding Boxes ◽  
Partially Occluded ◽  
Rgb Image

For autonomous vehicles, it is critical to be aware of the driving environment to avoid collisions and drive safely. The recent evolution of convolutional neural networks has contributed significantly to accelerating the development of object detection techniques that enable autonomous vehicles to handle rapid changes in various driving environments. However, collisions in an autonomous driving environment can still occur due to undetected obstacles and various perception problems, particularly occlusion. Thus, we propose a robust object detection algorithm for environments in which objects are truncated or occluded by employing RGB image and light detection and ranging (LiDAR) bird’s eye view (BEV) representations. This structure combines independent detection results obtained in parallel through “you only look once” networks using an RGB image and a height map converted from the BEV representations of LiDAR’s point cloud data (PCD). The region proposal of an object is determined via non-maximum suppression, which suppresses the bounding boxes of adjacent regions. A performance evaluation of the proposed scheme was performed using the KITTI vision benchmark suite dataset. The results demonstrate the detection accuracy in the case of integration of PCD BEV representations is superior to when only an RGB camera is used. In addition, robustness is improved by significantly enhancing detection accuracy even when the target objects are partially occluded when viewed from the front, which demonstrates that the proposed algorithm outperforms the conventional RGB-based model.

scholarly journals Emergency Landing Spot Detection Algorithm for Unmanned Aerial Vehicles

2021 ◽  
Vol 13 (10) ◽  
pp. 1930
Author(s):  
Gabriel Loureiro ◽  
André Dias ◽  
Alfredo Martins ◽  
José Almeida
Keyword(s):  
Point Cloud ◽  
Principal Component ◽  
Detection Algorithm ◽  
Cloud Data ◽  
Safety Issues ◽  
Spot Detection ◽  
Cloud Clusters ◽  
Aerial Vehicle ◽  
Incoming Light ◽  
Landing Spot

The use and research of Unmanned Aerial Vehicle (UAV) have been increasing over the years due to the applicability in several operations such as search and rescue, delivery, surveillance, and others. Considering the increased presence of these vehicles in the airspace, it becomes necessary to reflect on the safety issues or failures that the UAVs may have and the appropriate action. Moreover, in many missions, the vehicle will not return to its original location. If it fails to arrive at the landing spot, it needs to have the onboard capability to estimate the best area to safely land. This paper addresses the scenario of detecting a safe landing spot during operation. The algorithm classifies the incoming Light Detection and Ranging (LiDAR) data and store the location of suitable areas. The developed method analyses geometric features on point cloud data and detects potential right spots. The algorithm uses the Principal Component Analysis (PCA) to find planes in point cloud clusters. The areas that have a slope less than a threshold are considered potential landing spots. These spots are evaluated regarding ground and vehicle conditions such as the distance to the UAV, the presence of obstacles, the area’s roughness, and the spot’s slope. Finally, the output of the algorithm is the optimum spot to land and can vary during operation. The proposed approach evaluates the algorithm in simulated scenarios and an experimental dataset presenting suitability to be applied in real-time operations.

scholarly journals Polarimetric radar observations during an orographic rain event and the performance of a hydrometeor classification scheme

2014 ◽  
Vol 11 (7) ◽  
pp. 8845-8877
Author(s):  
M. Frech ◽  
J. Steinert
Keyword(s):  
Classification Scheme ◽  
Ground Level ◽  
Radar Data ◽  
Precipitation Event ◽  
Orographic Precipitation ◽  
Rain Event ◽  
Melting Layer ◽  
Surface Observation ◽  
Meteorological Observatory ◽  
Radar Sensing

Abstract. An intense orographic precipitation event is analysed using two polarimetric C-Band radars situated north of the Alps on 5 January 2013. One radar is operated at DWD's meteorological observatory Hohenpeißenberg (MHP, 1006 m a.s.l. – above sea level) and the Memmingen (MEM, 65 km west of MHP, 600 m a.s.l.) radar is part of DWD's operational radar network. The event lasted about 1.5 days and in total 44 mm precipitation was measured at Hohenpeißenberg. Detailed high resolution observation on the vertical structure of this event is obtained through a birdbath scan at 90° elevation which is part of the operational scanning. This scan is acquired every 5 min and provides meteorological profiles at high spatial resolution. In the course of this event, the melting layer (ML) descends until the transition from rain into snow is observed at ground level. This transition from rain into snow is well documented by local weather observers and a present-weather sensor. The orographic precipitation event reveals mesoscale variability above the melting layer which is unexpected from a meteorological point of view. It corresponds to a substantial increase in rain rate at the surface. The performance of the newly developed hydrometeor classification scheme "Hymec" using Memmingen radar data over Hohenpeißenberg is analyzed. The detection in location and timing of the ML agrees well with the Hohenpeißenberg radar data. Considering the size of the Memmingen radar sensing volume, the detected hydrometeor (HM) types are consistent for measurements at or in a ML, even though surface observation indicate for example rain whereas the predominant HM is classified as wet snow. To better link the HM classification with the surface observation, either better thermodynamic input is needed for Hymec or a statistical correction of the HM classification similar to a model output statistics (MOS) approach may be needed.

scholarly journals Land–atmosphere interactions in the tropics

2019 ◽  
Author(s):  
Pierre Gentine ◽  
Adam Massmann ◽  
Benjamin R. Lintner ◽  
Sayed Hamed Alemohammad ◽  
Rong Fu ◽  
...  
Keyword(s):  
Land Surface ◽  
Deep Convection ◽  
Lower Troposphere ◽  
Surface Fluxes ◽  
Surface Radiation ◽  
Spatial And Temporal Scales ◽  
Wide Range ◽  
Shallow Clouds ◽  
The Tropics ◽  
The Impact

Abstract. The continental tropics play a leading role in the terrestrial water and carbon cycles. Land–atmosphere interactions are integral in the regulation of surface energy, water and carbon fluxes across multiple spatial and temporal scales over tropical continents. We review here some of the important characteristics of tropical continental climates and how land–atmosphere interactions regulate them. Along with a wide range of climates, the tropics manifest a diverse array of land–atmosphere interactions. Broadly speaking, in tropical rainforests, light and energy are typically more limiting than precipitation and water supply for photosynthesis and evapotranspiration; whereas in savanna and semi-arid regions water is the critical regulator of surface fluxes and land–atmosphere interactions. We discuss the impact of the land surface, how it affects shallow clouds and how these clouds can feedback to the surface by modulating surface radiation. Some results from recent research suggest that shallow clouds may be especially critical to land–atmosphere interactions as these regulate the energy budget and moisture transport to the lower troposphere, which in turn affects deep convection. On the other hand, the impact of land surface conditions on deep convection appear to occur over larger, non-local, scales and might be critically affected by transitional regions between the climatologically dry and wet tropics.

scholarly journals Modeling of the Melting Layer. Part IV: Brightband Bulk Parameterization

2008 ◽  
Vol 65 (6) ◽  
pp. 1991-2001 ◽  
Author(s):  
Catherine Heyraud ◽  
Wanda Szyrmer ◽  
Stéphane Laroche ◽  
Isztar Zawadzki
Keyword(s):  
Data Assimilation ◽  
Radar Data ◽  
Melting Layer ◽  
Observation Operator ◽  
Data Assimilation Scheme ◽  
Bulk Model ◽  
Assimilation Scheme ◽  
Bulk Parameterization ◽  
Good Agreement ◽  
Extract Information

Abstract In this paper a simplified UHF-band backscattering parameterization for individual melting snowflakes is proposed. This parameterization is a function of the density, shape, and melted fraction, and is used here in a brightband bulk modeling study. A 1D bulk model is developed where aggregation and breakup are neglected. Model results are in good agreement with detailed bin-model results and simulate the radar brightband observations well. It is shown the model can be seen as an observation operator that could be introduced into a data assimilation scheme to extract information contained in the radar data measurements.

scholarly journals A Multi-Feature Search Window Method for Road Boundary Detection Based on LIDAR Data

Sensors ◽  
2019 ◽  
Vol 19 (7) ◽  
pp. 1551 ◽  
Author(s):  
Kai Li ◽  
Jinju Shao ◽  
Dong Guo
Keyword(s):  
Boundary Detection ◽  
Detection Algorithm ◽  
Boundary Extraction ◽  
Cloud Data ◽  
The Road ◽  
Window Method ◽  
Single Feature ◽  
Distribution Features ◽  
Curve Model ◽  
Cluster Points

In order to improve the accuracy of structured road boundary detection and solve the problem of the poor robustness of single feature boundary extraction, this paper proposes a multi-feature road boundary detection algorithm based on HDL-32E LIDAR. According to the road environment and sensor information, the former scenic cloud data is extracted, and the primary and secondary search windows are set according to the road geometric features and the point cloud spatial distribution features. In the search process, we propose the concept of the largest and smallest cluster points set and a two-way search method. Finally, the quadratic curve model is used to fit the road boundary. In the actual road test in the campus road, the accuracy of the linear boundary detection is 97.54%, the accuracy of the curve boundary detection is 92.56%, and the average detection period is 41.8 ms. In addition, the algorithm is still robust in a typical complex road environment.

scholarly journals On the Introduction of Canny Operator in an Advanced Imaging Algorithm for Real-Time Detection of Hyperbolas in Ground-Penetrating Radar Data

Electronics ◽  
2020 ◽  
Vol 9 (3) ◽  
pp. 541 ◽  
Author(s):  
Željko Bugarinović ◽  
Lara Pajewski ◽  
Aleksandar Ristić ◽  
Milan Vrtunski ◽  
Miro Govedarica ◽  
...  
Keyword(s):  
Real Time ◽  
Ground Penetrating Radar ◽  
Urban Areas ◽  
Radar Data ◽  
Detection Algorithm ◽  
Advanced Imaging ◽  
Canny Operator ◽  
Imaging Algorithm ◽  
Canny Edge ◽  
Ground Penetrating

This paper focuses on the use of the Canny edge detector as the first step of an advanced imaging algorithm for automated detection of hyperbolic reflections in ground-penetrating radar (GPR) data. Since the imaging algorithm aims to work in real time; particular attention is paid to its computational efficiency. Various alternative criteria are designed and examined, to fasten the procedure by eliminating unnecessary edge pixels from Canny-processed data, before such data go through the subsequent steps of the detection algorithm. The effectiveness and reliability of the proposed methodology are tested on a wide set of synthetic and experimental radargrams with promising results. The finite-difference time-domain simulator gprMax is used to generate synthetic radargrams for the tests, while the real radargrams come from GPR surveys carried out by the authors in urban areas. The imaging algorithm is implemented in MATLAB.

Melting layer attenuation at 28.6 GHz from simultaneous comstar beacon and polarisation diversity radar data

1981 ◽  
Vol 17 (5) ◽  
pp. 190 ◽  
Author(s):  
A. Hendry ◽  
Y.M.M. Antar ◽  
J.J. Schlesak ◽  
R.L. Olsen
Keyword(s):  
Radar Data ◽  
Melting Layer

Understanding the Importance of Microphysics and Macrophysics for Warm Rain in Marine Low Clouds. Part I: Satellite Observations

2009 ◽  
Vol 66 (10) ◽  
pp. 2953-2972 ◽  
Author(s):  
Terence L. Kubar ◽  
Dennis L. Hartmann ◽  
Robert Wood
Keyword(s):  
Gulf Of Mexico ◽  
Radar Data ◽  
Droplet Radius ◽  
Liquid Water Path ◽  
Cloud Radar ◽  
Warm Rain ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Cloud Tops ◽  
The Tropics

Abstract The importance of macrophysical variables [cloud thickness, liquid water path (LWP)] and microphysical variables (effective radius re, effective droplet concentration Neff) on warm drizzle intensity and frequency across the tropics and subtropics is studied. In this first part of a two-part study, Moderate Resolution Imaging Spectroradiometer (MODIS) optical and CloudSat cloud radar data are used to understand warm rain in marine clouds. Part II uses simple heuristic models. Cloud-top height and LWP substantially increase as drizzle intensity increases. Droplet radius estimated from MODIS also increases with cloud radar reflectivity (dBZ) but levels off as dBZ > 0, except where the influence of continental pollution is present, in which case a monotonic increase of re with drizzle intensity occurs. Off the Asian coast and over the Gulf of Mexico, re values are smaller (by several μm) and Neff values are larger compared to more remote marine regions. For heavy drizzle intensity, both re and Neff values off the Asian coast and over the Gulf of Mexico approach re and Neff values in more remote marine regions. Drizzle frequency, defined as profiles in which maximum dBZ > −15, increases dramatically and nearly uniformly when cloud tops grow from 1 to 2 km. Drizzle frequencies exceed 90% in all regions when LWPs exceed 250 g m−2 and Neff values are below 50 cm−3, even in regions where drizzle occurs infrequently on the whole. The fact that the relationship among drizzle frequency, LWP, and Neff is essentially the same for all regions suggests a near universality among tropical and subtropical regions.

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