An Integrated Display and Analysis Methodology for Multivariable Radar Data

2007 ◽  
Vol 46 (8) ◽  
pp. 1196-1213 ◽  
Author(s):  
Brenda A. Dolan ◽  
Steven A. Rutledge
Keyword(s):  
Quality Control ◽  
Real Time ◽  
Cross Sections ◽  
Three Dimensional ◽  
Radar Data ◽  
Control Measures ◽  
Integrated Analysis ◽  
Colorado State University ◽  
Depth Analysis ◽  
Rain Rates

Abstract Polarimetric Doppler radars provide valuable information about the kinematic and microphysical structure of storms. However, in-depth analysis using radar products, such as Doppler-derived wind vectors and hydrometeor identification, has been difficult to achieve in (near) real time, mainly because of the large volumes of data generated by these radars, lack of quick access to these data, and the challenge of applying quality-control measures in real time. This study focuses on modifying and automating several radar-analysis and quality-control algorithms currently used in postprocessing and merging the resulting data from several radars into an integrated analysis and display in (near) real time. Although the method was developed for a specific network of four Doppler radars: two Weather Surveillance Radar-1988 Doppler (WSR-88D) radars (KFTG and KCYS) and two Colorado State University (CSU) research radars [Pawnee and CSU–University of Chicago–Illinois State Water Survey (CSU–CHILL)], the software is easily adaptable to any radar platform or network of radars. The software includes code to synthesize radial velocities to obtain three-dimensional wind vectors and includes algorithms for automatic quality control of the raw polarimetric data, hydrometeor identification, and rainfall rate. The software was successfully tested during the summers of 2004 and 2005 at the CSU–CHILL radar facility, ingesting data from the four-radar network. The display software allows users the ability to view mosaics of reflectivity, wind vectors, and rain rates, to zoom in and out of radar features easily, to create vertical cross sections, to contour data, and to archive data in real time. Despite the lag time of approximately 10 min, the software proved invaluable for diagnosing areas of intense rainfall, hail, strong updrafts, and other features such as mesocyclones and convergence lines. A case study is presented to demonstrate the utility of the software.

The Three-Dimensional Structure and Kinematics of Drizzling Stratocumulus

2007 ◽  
Vol 135 (11) ◽  
pp. 3767-3784 ◽  
Author(s):  
Kimberly K. Comstock ◽  
Sandra E. Yuter ◽  
Robert Wood ◽  
Christopher S. Bretherton
Keyword(s):  
Cross Sections ◽  
Doppler Radar ◽  
Cell Structure ◽  
Three Dimensional ◽  
Radar Data ◽  
Dimensional Structure ◽  
Cloud Base ◽  
Marine Stratocumulus ◽  
Cloud Structure ◽  
Rain Rates

Abstract Drizzling marine stratocumulus are examined using observations from the 2001 East Pacific Investigation of Climate Stratocumulus (EPIC Sc) field experiment. This study uses a unique combination of satellite and shipborne Doppler radar data including both horizontal and vertical cross sections through drizzle cells. Stratocumulus cloud structure was classified as closed cellular, open cellular, or unclassifiable using infrared satellite images. Distributions of drizzle cell structure, size, and intensity are similar among the cloud-structure categories, though the open-cellular distributions are shifted toward higher values. Stronger and larger drizzle cells preferentially occur when the cloud field is broken (open-cellular and unclassifiable categories). Satellite observations of cloud structure may be useful to indicate the most likely distribution of rain rates associated with a set of scenes, but infrared data alone are not sufficient to develop routine precipitation retrievals for marine stratocumulus. Individual drizzle cells about 2–20 km across usually showed precipitation growth within the cloud layer and evaporation below, divergence near echo top, and convergence below cloud base. Diverging flow near the surface was also observed beneath heavily precipitating drizzle cells. As the cloud field transitioned from a closed to an open-cellular cloud structure, shipborne radar revealed prolific development of small drizzle cells (<10 km2) that exceeded by over 5 times the number of total cells in either the preceding closed-cellular or following open-cellular periods. Peak area-average rain rates lagged by a few hours the peak in total number of drizzle cells. Based on observations from EPIC Sc, the highest stratocumulus rain rates are more likely to occur near the boundary between closed and open-cellular cloud structures.

A Real-Time, Three-Dimensional, Rapidly Updating, Heterogeneous Radar Merger Technique for Reflectivity, Velocity, and Derived Products

2006 ◽  
Vol 21 (5) ◽  
pp. 802-823 ◽  
Author(s):  
Valliappa Lakshmanan ◽  
Travis Smith ◽  
Kurt Hondl ◽  
Gregory J. Stumpf ◽  
Arthur Witt
Keyword(s):  
Real Time ◽  
Time Synchronization ◽  
Three Dimensional ◽  
Radar Data ◽  
Streaming Data ◽  
Weather Radars ◽  
Beam Geometry ◽  
Time Stamps ◽  
Scalar Products ◽  
Radar Calibration

Abstract With the advent of real-time streaming data from various radar networks, including most Weather Surveillance Radars-1988 Doppler and several Terminal Doppler Weather Radars, it is now possible to combine data in real time to form 3D multiple-radar grids. Herein, a technique for taking the base radar data (reflectivity and radial velocity) and derived products from multiple radars and combining them in real time into a rapidly updating 3D merged grid is described. An estimate of that radar product combined from all the different radars can be extracted from the 3D grid at any time. This is accomplished through a formulation that accounts for the varying radar beam geometry with range, vertical gaps between radar scans, the lack of time synchronization between radars, storm movement, varying beam resolutions between different types of radars, beam blockage due to terrain, differing radar calibration, and inaccurate time stamps on radar data. Techniques for merging scalar products like reflectivity, and innovative, real-time techniques for combining velocity and velocity-derived products are demonstrated. Precomputation techniques that can be utilized to perform the merger in real time and derived products that can be computed from these three-dimensional merger grids are described.

scholarly journals Real-Time Detection and Filtering of Chaff Clutter from Single-Polarization Doppler Radar Data

2013 ◽  
Vol 30 (5) ◽  
pp. 873-895 ◽  
Author(s):  
Yong Hyun Kim ◽  
Sungshin Kim ◽  
Hye-Young Han ◽  
Bok-Haeng Heo ◽  
Cheol-Hwan You
Keyword(s):  
Real Time ◽  
Doppler Radar ◽  
Meteorological Data ◽  
Three Dimensional ◽  
Weather Radar ◽  
Cost Effective ◽  
Radar Data ◽  
Control Procedure ◽  
South Korean ◽  
Single Polarization

Abstract In countries with frequent aerial military exercises, chaff particles that are routinely spread by military aircraft represent significant noise sources for ground-based weather radar observation. In this study, a cost-effective procedure is proposed for identifying and removing chaff echoes from single-polarization Doppler radar readings in order to enhance the reliability of observed meteorological data. The proposed quality control procedure is based on three steps: 1) spatial and temporal clustering of decomposed radar image elements, 2) extraction of the clusters’ static and time-evolution characteristics, and 3) real-time identification and removal (or censoring) of target echoes from radar data. Simulation experiments based on this procedure were conducted on site-specific ground-echo-removed weather radar data provided by the Korea Meteorological Administration (KMA), from which three-dimensional (3D) reflectivity echoes covering hundreds of thousands of square kilometers of South Korean territory within an altitude range of 0.25–10 km were retrieved. The algorithm identified and removed chaff clutter from the South Korean data with a novel decision support system at an 81% accuracy level under typical cases in which chaff and weather clusters were isolated from one another with no overlapping areas.

scholarly journals COMPREHENSIVE RADAR DATA FOR THE CONTIGUOUS UNITED STATES: MULTI-YEAR REANALYSIS OF REMOTELY SENSED STORMS

2021 ◽  
Keyword(s):  
United States ◽  
Quality Control ◽  
Initial Period ◽  
Three Dimensional ◽  
Radar Data ◽  
Remotely Sensed ◽  
Model Verification ◽  
Doppler Velocity ◽  
Data Set ◽  
Quality Control Process

Abstract The Multi-Year Reanalysis of Remotely Sensed Storms (MYRORSS) data set blends radar data from the WSR-88D network and Near-Storm Environmental (NSE) model analyses using the Multi-Radar Multi-Sensor (MRMS) framework. The MYRORSS data set uses the WSR-88D archive starting in 1998 through 2011, processing all valid single-radar volumes to produce a seamless three-dimensional reflectivity volume over the entire contiguous United States with an approximate 5-min update frequency. The three-dimensional grid has an approximate 1-km by 1-km horizontal dimension and is on a stretched vertical grid that extends to 20 km MSL with a maximal vertical spacing of 1 km. Several reflectivity-derived, severe storm related products are also produced, which leverage the ability to merge the MRMS and NSE data. Two Doppler velocity-derived azimuthal shear layer maximum products are produced at a higher horizontal resolution of approximately 0.5-km by 0.5-km. The initial period of record for the data set is 1998-2011. The data set underwent intensive manual quality control to ensure that all available and valid data were included while excluding highly problematic radar volumes that were a negligible percentage of the overall data set, but which caused large data errors in some cases. This data set has applications towards radar-based climatologies, post-event analysis, machine learning applications, model verification, and warning improvements. Details of the manual quality control process are included and examples of some of these applications are presented.

scholarly journals rt-me-fMRI: a task and resting state dataset for real-time, multi-echo fMRI methods development and validation

F1000Research ◽  
2021 ◽  
Vol 10 ◽  
pp. 70
Author(s):  
Stephan Heunis ◽  
Marcel Breeuwer ◽  
César Caballero-Gaudes ◽  
Lydia Hellrung ◽  
Willem Huijbers ◽  
...  
Keyword(s):  
Quality Control ◽  
Real Time ◽  
Resting State ◽  
Shape Matching ◽  
Control Measures ◽  
Finger Tapping ◽  
Link Type ◽  
Full Dataset ◽  
Methods Development ◽  
Fmri Analysis

A multi-echo fMRI dataset (N=28 healthy participants) with four task-based and two resting state runs was collected, curated and made available to the community. Its main purpose is to advance the development of methods for real-time multi-echo functional magnetic resonance imaging (rt-me-fMRI) analysis with applications in neurofeedback, real-time quality control, and adaptive paradigms, although the variety of experimental task paradigms supports a multitude of use cases. Tasks include finger tapping, emotional face and shape matching, imagined finger tapping and imagined emotion processing. This work provides a detailed description of the full dataset; methods to collect, prepare, standardize and preprocess it; quality control measures; and data validation measures. A web-based application is provided as a supplementary tool with which to interactively explore, visualize and understand the data and its derivative measures: https://rt-me-fmri.herokuapp.com/. The dataset itself can be accessed via a data use agreement on DataverseNL at https://dataverse.nl/dataverse/rt-me-fmri. Supporting information and code for reproducibility can be accessed at https://github.com/jsheunis/rt-me-fMRI.

scholarly journals Virtual CSU-CHILL Radar: The VCHILL

2005 ◽  
Vol 22 (7) ◽  
pp. 979-987 ◽  
Author(s):  
V. Chandrasekar ◽  
Yoong-Goog Cho ◽  
D. Brunkow ◽  
A. Jayasumana
Keyword(s):  
Real Time ◽  
Radar Data ◽  
Graphic User Interface ◽  
Research Experience ◽  
Time Data ◽  
System Architectures ◽  
Colorado State University ◽  
Radar Images ◽  
Atmospheric Remote Sensing ◽  
High Bandwidth

Abstract The Virtual CHILL (VCHILL) system makes it possible to transfer the educational and research experience of the Colorado State University dual polarization radar to remote locations over the Internet. The VCHILL operation includes remote control of radar and display of radar images, as well as the ability to locally process high-bandwidth radar data transferred over data networks. The low-bandwidth VCHILL operation allows the distant users to access the archived and real-time data estimated at the radar site and simultaneously display them on their local systems. A parallel receiver was developed exclusively for the high-bandwidth VCHILL. End-system architectures were designed to accommodate the demands of the high-bandwidth VCHILL operations in real time. A graphic user interface was also developed with the objective of easy installation and usage at various end-user institutions. The VCHILL not only expands the education experience provided by the radar system, but also stimulates the development of innovative research applications for atmospheric remote sensing. The VCHILL is being used by several universities for research and education.

scholarly journals A Real-Time and Offline Quality Control Methodology for SeaSonde High-Frequency Radar Currents

2012 ◽  
Vol 29 (9) ◽  
pp. 1313-1328 ◽  
Author(s):  
Simone Cosoli ◽  
Giorgio Bolzon ◽  
Andrea Mazzoldi
Keyword(s):  
Quality Control ◽  
Real Time ◽  
Signal To Noise Ratio ◽  
Radar Data ◽  
Control Procedure ◽  
Spectral Quality ◽  
Quality Factors ◽  
High Frequency Radar ◽  
Minimization Procedure ◽  
Control Methodology

Abstract A near-real-time and offline quality control methodology for SeaSonde systems is proposed. It is applied on radial current maps and is based on the determination of the signal-to-noise ratio (SNR) values of the Doppler lines that contribute to the hourly radial current at each range-bearing (R, θ) pair, under the assumption that SNR is a proxy for radar data quality. The retrieval of the sequence of Doppler lines is performed through a minimization procedure that takes advantage of the statistical descriptors output in the short-term radial maps. The separation of the contributing Doppler velocities into valid observations and anomalous velocities is based on their spectral quality factor and on a range-dependent noise threshold derived from statistics (average and standard deviation) of the signal amplitudes in the tails of the Doppler spectra. The final product of the quality control procedure is a radial current map, in which Doppler velocities are weighted by their SNR values and their spectral quality factors, and averaged to produce an output that is fully compatible with the proprietary software. This procedure is fast, despite the fact that a large number of combinations might be required during the retrieval of the Doppler lines, and effective, because it removes both evident spikes as well as Doppler velocities that are not clearly identified as anomalous velocities. In principle, this approach can be used to fill gaps in the radar coverage without the need for interpolation in time or space, proved that the Doppler velocities satisfy predetermined SNR constraints.

scholarly journals rt-me-fMRI: A task and resting state dataset for real-time, multi-echo fMRI methods development and validation

2020 ◽  
Author(s):  
Stephan Heunis ◽  
Marcel Breeuwer ◽  
César Caballero-Gaudes ◽  
Lydia Hellrung ◽  
Willem Huijbers ◽  
...  
Keyword(s):  
Quality Control ◽  
Real Time ◽  
Resting State ◽  
Shape Matching ◽  
Control Measures ◽  
Finger Tapping ◽  
Link Type ◽  
Full Dataset ◽  
Methods Development ◽  
Fmri Analysis

AbstractA multi-echo fMRI dataset (N=28 healthy participants) with four task-based and two resting state runs was collected, curated and made available to the community. Its main purpose is to advance the development of methods for real-time multi-echo functional magnetic resonance imaging (rt-me-fMRI) analysis with applications in neurofeedback, real-time quality control, and adaptive paradigms, although the variety of experimental task paradigms supports a multitude of use cases. Tasks include finger tapping, emotional face and shape matching, imagined finger tapping and imagined emotion processing. This work provides a detailed description of the full dataset; methods to collect, prepare, standardize and preprocess it; quality control measures; and data validation measures. A web-based application is provided as a supplementary tool with which to interactively explore, visualize and understand the data and its derivative measures: https://rt-me-fmri.herokuapp.com/. The dataset itself can be accessed via a data use agreement on DataverseNL at https://dataverse.nl/dataverse/rt-me-fmri. Supporting information and code for reproducibility can be accessed at https://github.com/jsheunis/rt-me-fMRI.

Sign in / Sign up

Export Citation Format

Share Document