Precipitation and Turbulence Intensity Classification Based on the Polarimetric Doppler Radar Data Analysis

2006 ◽  
Vol 65 (12) ◽  
pp. 1077-1085 ◽  
Author(s):  
F. J. Yanovsky ◽  
Ya. P. Ostrovsky
Keyword(s):  
Data Analysis ◽  
Turbulence Intensity ◽  
Doppler Radar ◽  
Radar Data ◽  
Doppler Radar Data ◽  
Intensity Classification

Airborne Doppler Radar Data Analysis Workshop

2003 ◽  
Vol 84 (8) ◽  
pp. 1063-1075 ◽  
Author(s):  
Wen-Chau Lee ◽  
Frank D. Marks ◽  
Craig Walther
Keyword(s):  
Data Analysis ◽  
Doppler Radar ◽  
Radar Data ◽  
Doppler Radar Data ◽  
Airborne Doppler Radar

A Variational Method for Filling in Missing Data in Doppler Velocity Fields

2021 ◽  
Author(s):  
VINCENT T. WOOD ◽  
ROBERT P. DAVIES-JONES ◽  
ALAN SHAPIRO
Keyword(s):  
Missing Data ◽  
Doppler Radar ◽  
Signal To Noise Ratio ◽  
Original Data ◽  
Radar Data ◽  
Velocity Fields ◽  
Doppler Velocity ◽  
Doppler Radar Data ◽  
Ground Clutter ◽  
Tornado Warnings

AbstractSingle-Doppler radar data are often missing in important regions of a severe storm due to low return power, low signal-to-noise ratio, ground clutter associated with normal and anomalous propagation, and missing radials associated with partial or total beam blockage. Missing data impact the ability of WSR-88D algorithms to detect severe weather. To aid the algorithms, we develop a variational technique that fills in Doppler velocity data voids smoothly by minimizing Doppler velocity gradients while not modifying good data. This method provides estimates of the analysed variable in data voids without creating extrema.Actual single-Doppler radar data of four tornadoes are used to demonstrate the variational algorithm. In two cases, data are missing in the original data, and in the other two, data are voided artificially. The filled-in data match the voided data well in smoothly varying Doppler velocity fields. Near singularities such as tornadic vortex signatures, the match is poor as anticipated. The algorithm does not create any velocity peaks in the former data voids, thus preventing false triggering of tornado warnings. Doppler circulation is used herein as a far-field tornado detection and advance-warning parameter. In almost all cases, the measured circulation is quite insensitive to the data that have been voided and then filled. The tornado threat is still apparent.

scholarly journals Retrieval of three-dimensional wind fields from Doppler radar data using an efficient two-step approach

2010 ◽  
Vol 3 (5) ◽  
pp. 4459-4495 ◽  
Author(s):  
C. López Carrillo ◽  
D. J. Raymond
Keyword(s):  
Variational Approach ◽  
Continuity Equation ◽  
Doppler Radar ◽  
Three Dimensional ◽  
Relevant Information ◽  
Radar Data ◽  
Wind Fields ◽  
Wind Retrieval ◽  
Complex Sampling ◽  
Doppler Radar Data

Abstract. In this work, we describe an efficient approach for wind retrieval from dual Doppler radar data. The approach produces a gridded field that not only satisfies the observations, but also satisfies the anelastic mass continuity equation. The method is based on the so-called three-dimensional variational approach to the retrieval of wind fields from radar data. The novelty consists in separating the task into steps that reduce the amount of data processed by the global minimization algorithm, while keeping the most relevant information from the radar observations. The method is flexible enough to incorporate observations from several radars, accommodate complex sampling geometries, and readily include dropsonde or sounding observations in the analysis. We demonstrate the usefulness of our method by analyzing a real case with data collected during the TPARC/TCS-08 field campaign.

Mapping of Airborne Doppler Radar Data

1994 ◽  
Vol 11 (2) ◽  
pp. 572-578 ◽  
Author(s):  
Wen-Chau Lee ◽  
Peter Dodge ◽  
Frank D. Marks ◽  
Peter H. Hildebrand
Keyword(s):  
Doppler Radar ◽  
Radar Data ◽  
Doppler Radar Data ◽  
Airborne Doppler Radar

Retrieved Thermodynamic Structure of Hurricane Rita (2005) from Airborne Multi-Doppler Radar Data

2021 ◽  
Author(s):  
Annette M. Boehm ◽  
Michael M. Bell
Keyword(s):  
Wind Shear ◽  
Doppler Radar ◽  
Three Dimensional ◽  
Vertical Wind Shear ◽  
Vertical Motion ◽  
Radar Data ◽  
Vertical Wind ◽  
Vertical Acceleration ◽  
Hurricane Rita ◽  
Doppler Radar Data

AbstractThe newly developed SAMURAI-TR is used to estimate three-dimensional temperature and pressure perturbations in Hurricane Rita on 23 September 2005 from multi-Doppler radar data during the RAINEX field campaign. These are believed to be the first fully three-dimensional gridded thermodynamic observations from a TC. Rita was a major hurricane at this time and was affected by 13 m s−1 deep-layer vertical wind shear. Analysis of the contributions of the kinematic and retrieved thermodynamic fields to different azimuthal wavenumbers suggests the interpretation of eyewall convective forcing within a three-level framework of balanced, quasi-balanced, and unbalanced motions. The axisymmetric, wavenumber-0 structure was approximately in thermal-wind balance, resulting in a large pressure drop and temperature increase toward the center. The wavenumber-1 structure was determined by the interaction of the storm with environmental vertical wind shear resulting in a quasi-balance between shear and shear-induced kinematic and thermo-dynamic perturbations. The observed wavenumber-1 thermodynamic asymmetries corroborate results of previous studies on the response of a vortex tilted by shear, and add new evidence that the vertical motion is nearly hydrostatic on the wavenumber-1 scale. Higher-order wavenumbers were associated with unbalanced motions and convective cells within the eyewall. The unbalanced vertical acceleration was positively correlated with buoyant forcing from thermal perturbations and negatively correlated with perturbation pressure gradients relative to the balanced vortex.

scholarly journals An Algorithm for Automated Identification of Gust Fronts from Doppler Radar Data

2018 ◽  
Vol 32 (3) ◽  
pp. 444-455 ◽  
Author(s):  
Yue Yuan ◽  
Ping Wang ◽  
Di Wang ◽  
Huizhen Jia
Keyword(s):  
Doppler Radar ◽  
Radar Data ◽  
Automated Identification ◽  
Doppler Radar Data ◽  
Gust Fronts
Sign in / Sign up

Export Citation Format

Share Document