scholarly journals Significance of the Coupled Term in the Doppler Weather Radar Spectrum Width Equation

2011 ◽  
Vol 28 (4) ◽  
pp. 539-547 ◽  
Author(s):  
Ming Fang ◽  
Richard J. Doviak ◽  
Bruce A. Albrecht
Keyword(s):  
Wind Shear ◽  
Doppler Radar ◽  
Weather Radar ◽  
Random Variable ◽  
Doppler Weather Radar ◽  
Significant Contributor ◽  
Spectrum Width

Abstract There is an additional zero mean random variable term that couples mean wind shear and turbulence in the Doppler radar spectrum width equation. This random variable, labeled the “coupled term,” has been neglected heretofore in the literature. Herein, the variance of the squared spectrum width ascribed to this coupled term is determined from data collected with a Weather Surveillance Radar-1988 Doppler (WSR-88D) in two snowstorms; it can exceed 1 m4 s−4. Thus, this coupled term can be a significant contributor to the variance of the spectrum width and must be considered when using spectrum width to deduce turbulence.

scholarly journals Turbulence and Wind Shear in Layers of Large Doppler Spectrum Width in Stratiform Precipitation

2009 ◽  
Vol 26 (3) ◽  
pp. 430-443 ◽  
Author(s):  
Valery M. Melnikov ◽  
Richard J. Doviak
Keyword(s):  
Wind Shear ◽  
Weather Radar ◽  
Velocity Fields ◽  
The Other ◽  
Doppler Spectrum ◽  
Weak Turbulence ◽  
Radar Observations ◽  
Spectrum Width ◽  
Stratiform Precipitation ◽  
Radar Resolution

Abstract Weather radar observations of stratiform precipitation often reveal regions having very large measured Doppler spectrum widths, exceeding 7, and sometimes 10, m s−1. These widths are larger than those typically found in thunderstorms; widths larger than 4 m s−1 are associated with moderate or severe turbulence in thunderstorms. In this work, stratiform precipitation has been found to have layers of widths larger than 4 m s−1 in more than 80% of cases studied, wherein the shear of the wind on scales that are large compared to the dimensions of the radar resolution volume is the dominant contributor to spectrum width. Analyzed data show that if width ≤7 m s−1, and if the layers are not wavy or patchy, these layers have weak turbulence. On the other hand, regions having widths >4 m s−1 in patches or in wavelike structures are likely to have moderate to severe turbulence with the potential to be a hazard to safe flight. To separate the contributions to spectrum width from wind shear and turbulence and to evaluate the errors in turbulence estimates, data have been collected with elevation increments much less than a beamwidth. Despite beamwidth limitations, the small elevation increments reveal impressive structures in the fields. For example, the “cat’s eye” structure associated with Kelvin–Helmholtz waves is clearly exhibited in the fields of spectrum width observed at low-elevation angles, but not in the reflectivity or velocity fields. Reflectivity fields in stratiform precipitation are featureless compared to spectrum width fields.

scholarly journals Early Operational Successes of the University of Louisiana Monroe’s Polarimetric S-band Doppler Radar

2019 ◽  
pp. 105-116
Author(s):  
Todd A. Murphy ◽  
Cynthia Palmer ◽  
Chad Entremont ◽  
James D. Lamb
Keyword(s):  
Real Time ◽  
Doppler Radar ◽  
Weather Radar ◽  
Weather Forecast ◽  
Radar Data ◽  
Doppler Weather Radar ◽  
Low Level ◽  
Coverage Gap ◽  
University Of Louisiana ◽  
The University

In October 2016, the University of Louisiana Monroe (ULM) began operating a polarimetric S-band Doppler weather radar to help close the low-level radar coverage gap across northern Louisiana by increasing the quantity of data sampled below 3.0 km AGL. Data are delivered in near-real time to local National Weather Service (NWS) Weather Forecast Offices to help meteorologists accomplish their mission of protecting life and property. The inclusion of ULM radar data into NWS operations has led to improved detection of severe and hazardous weather across northern Louisiana. This paper details how the ULM radar has been incorporated into NWS operations, the improvement in operational radar coverage, and the challenges of using a non-NWS radar in the NWS operational setting.

scholarly journals Development of nowcasting technique and evaluation of convective indices for thunderstorm prediction in Gangetic West Bengal (India) using Doppler Weather Radar and upper air data

MAUSAM ◽  
2021 ◽  
Vol 63 (2) ◽  
pp. 299-318
Author(s):  
DEVENDRA PRADHAN ◽  
U.K. DE ◽  
U.V. SINGH
Keyword(s):  
Lead Time ◽  
West Bengal ◽  
Doppler Radar ◽  
Monsoon Season ◽  
Weather Radar ◽  
Doppler Weather Radar ◽  
Monsoon Period ◽  
Cumulonimbus Cloud ◽  
Very High ◽  
Fair Degree

Thunderstorm and hailstorm are well known short term severe weather phenomena which sometimes turn in to natural hazard especially in Gangetic West Bengal region of India. Large vertical extent of the cumulonimbus cloud, very high reflectivity, squally wind speed sometimes exceeding 100 km/h and heavy rainfall are the main features of these thunderstorms during pre-monsoon period in this region. A study of 70 thunderstorms has been carried out during the pre-monsoon season (March-May) of the year 2005 around Kolkata (22.5° N, 88.5° E) using Doppler Weather Radar and Upper air data. Standard convective indices like CAPE, CINE, LI, BRN and VGP have been evaluated and analyzed statistically. As no definite thresholds of the convective indices are available for thunderstorm prediction in this region, an attempt has been made to find threshold of these indices for possible occurrences of thunderstorms in Gangetic West Bengal region after the analysis of the thunderstorms during year 2005. The validity of these convective indices has been checked with 34 occurrences of thunderstorms during 2006-2007 recorded by Doppler Weather Radar Kolkata. The study reveals that nowcasting of thunderstorms may be done at least 2-3 hrs in advance witha fair degree of accuracy using Doppler radar products only. However, the lead time of nowcasting may be further improved if the convective indices are also analyzed and used in addition to the DWR data. A simple technique has been suggested by the authors for better prediction of thunderstorms at least three to four hours in advance.

scholarly journals Technical a Gaussian Mixture Model to Separate Birds and Insects in Single-Polarization Weather Radar Data

2021 ◽  
Vol 13 (10) ◽  
pp. 1989
Author(s):  
Raphaël Nussbaumer ◽  
Baptiste Schmid ◽  
Silke Bauer ◽  
Felix Liechti
Keyword(s):  
Gaussian Mixture Model ◽  
Mixture Model ◽  
Doppler Radar ◽  
Animal Movement ◽  
Weather Radar ◽  
Gaussian Mixture ◽  
Radar Data ◽  
Volume Data ◽  
Simple Method ◽  
Single Polarization

Recent and archived data from weather radar networks are extensively used for the quantification of continent-wide bird migration patterns. While the process of discriminating birds from weather signals is well established, insect contamination is still a problem. We present a simple method combining two Doppler radar products within a Gaussian mixture model to estimate the proportions of birds and insects within a single measurement volume, as well as the density and speed of birds and insects. This method can be applied to any existing archives of vertical bird profiles, such as the European Network for the Radar surveillance of Animal Movement repository, with no need to recalculate the huge amount of original polar volume data, which often are not available.

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