On the Use of Ground Return Targets for Radar Reflectivity Factor Calibration Checks

1978 ◽  
Vol 17 (9) ◽  
pp. 1342-1350 ◽  
Author(s):  
R. E. Rinehart
Keyword(s):  
Radar Reflectivity ◽  
Reflectivity Factor

Fuzzy Logic Classification of S-Band Polarimetric Radar Echoes to Identify Three-Body Scattering and Improve Data Quality

2014 ◽  
Vol 53 (8) ◽  
pp. 2017-2033 ◽  
Author(s):  
Vivek N. Mahale ◽  
Guifu Zhang ◽  
Ming Xue
Keyword(s):  
Fuzzy Logic ◽  
Standard Deviation ◽  
Radar Data ◽  
Classification Algorithm ◽  
Radar Reflectivity ◽  
Membership Functions ◽  
Polarimetric Radar ◽  
Radar Echo ◽  
Three Body ◽  
Reflectivity Factor

AbstractThe three-body scatter signature (TBSS) is a radar artifact that appears downrange from a high-radar-reflectivity core in a thunderstorm as a result of the presence of hailstones. It is useful to identify the TBSS artifact for quality control of radar data used in numerical weather prediction and quantitative precipitation estimation. Therefore, it is advantageous to develop a method to automatically identify TBSS in radar data for the above applications and to help identify hailstones within thunderstorms. In this study, a fuzzy logic classification algorithm for TBSS identification is developed. Polarimetric radar data collected by the experimental S-band Weather Surveillance Radar-1988 Doppler (WSR-88D) in Norman, Oklahoma (KOUN), are used to develop trapezoidal membership functions for the TBSS class of radar echo within a hydrometeor classification algorithm (HCA). Nearly 3000 radar gates are removed from 50 TBSSs to develop the membership functions from the data statistics. Five variables are investigated for the discrimination of the radar echo: 1) horizontal radar reflectivity factor ZH, 2) differential reflectivity ZDR, 3) copolar cross-correlation coefficient ρhv, 4) along-beam standard deviation of horizontal radar reflectivity factor SD(ZH), and 5) along-beam standard deviation of differential phase SD(ΦDP). These membership functions are added to an HCA to identify TBSSs. Testing is conducted on radar data collected by dual-polarization-upgraded operational WSR-88Ds from multiple severe-weather events, and results show that automatic identification of the TBSS through the enhanced HCA is feasible for operational use.

scholarly journals Geographical Distribution of Variance of Intraseasonal Variations in Western Indochina as Revealed from Radar Reflectivity Data

2008 ◽  
Vol 21 (19) ◽  
pp. 5154-5161 ◽  
Author(s):  
Satoru Yokoi ◽  
Takehiko Satomura
Keyword(s):  
Geographical Distribution ◽  
Coastal Region ◽  
Radar Reflectivity ◽  
Windward Side ◽  
Synoptic Scale ◽  
Wind Anomaly ◽  
Orographic Rainfall ◽  
Intraseasonal Variations ◽  
Reflectivity Data ◽  
Reflectivity Factor

Abstract This study reveals remarkable differences in the geographical distribution of variance between two types of intraseasonal variations in daily-mean radar reflectivity data in the western part of the Indochina Peninsula. In this region, the Downa Range lies parallel to the coast and separates the inland region from the coastal region. The 30–60-day variation of reflectivity factor dominates most of the coastal region, while its variance in the inland region is less than that of background red noise with the same frequency band. Horizontal gradients in the variance are largest over the range, implying that the mountain range plays a significant role in the geographical contrast. Correlation analysis with reanalysis data shows that the variation only in the coastal region is associated with a synoptic-scale zonal wind anomaly with the same time scale, suggesting the importance of an orographic rainfall process that brings a large amount of precipitation only to the windward side of the Downa Range. In contrast, while the 10–20-day variation of reflectivity factor has larger variance in the inland region than in the coastal region, the variation in both of the regions is correlated with synoptic-scale cyclonic circulation anomaly. A possible reason for the differences between the two types is also discussed in terms of the relationship between synoptic-scale wind anomaly field and the orientation of the Downa Range.

scholarly journals Turbulent enhancement of radar reflectivity factor for polydisperse cloud droplets

2019 ◽  
Vol 19 (3) ◽  
pp. 1785-1799 ◽  
Author(s):  
Keigo Matsuda ◽  
Ryo Onishi
Keyword(s):  
Isotropic Turbulence ◽  
Density Fluctuations ◽  
Radar Reflectivity ◽  
Wave Number ◽  
Critical Wave Number ◽  
Cross Spectrum ◽  
Proposed Model ◽  
Droplet Sizes ◽  
The Cross ◽  
Reflectivity Factor

Abstract. The radar reflectivity factor is important for estimating cloud microphysical properties; thus, in this study, we determine the quantitative influence of microscale turbulent clustering of polydisperse droplets on the radar reflectivity factor. The theoretical solution for particulate Bragg scattering is obtained without assuming monodisperse droplet sizes. The scattering intensity is given by an integral function including the cross spectrum of number density fluctuations for two different droplet sizes. We calculate the cross spectrum based on turbulent clustering data, which are obtained by the direct numerical simulation (DNS) of particle-laden homogeneous isotropic turbulence. The results show that the coherence of the cross spectrum is close to unity for small wave numbers and decreases almost exponentially with increasing wave number. This decreasing trend is dependent on the combination of Stokes numbers. A critical wave number is introduced to characterize the exponential decrease of the coherence and parameterized using the Stokes number difference. Comparison with DNS results confirms that the proposed model can reproduce the rp3-weighted power spectrum, which is proportional to the clustering influence on the radar reflectivity factor to a sufficiently high accuracy. Furthermore, the proposed model is extended to incorporate the gravitational settling influence by modifying the critical wave number based on the analytical equation derived for the bidisperse radial distribution function. The estimate of the modified model also shows good agreement with the DNS results for the case with gravitational droplet settling. The model is then applied to high-resolution cloud-simulation data obtained from a spectral-bin cloud simulation. The result shows that the influence of turbulent clustering can be significant inside turbulent clouds. The large influence is observed at the near-top of the clouds, where the liquid water content and the energy dissipation rate are sufficiently large.

scholarly journals Reduction of Nonuniform Beamfilling Effects by Multiple Constraints: A Simulation Study

2015 ◽  
Vol 32 (11) ◽  
pp. 2114-2124 ◽  
Author(s):  
David A. Short ◽  
Robert Meneghini ◽  
Amber E. Emory ◽  
Mathew R. Schwaller
Keyword(s):  
Attenuation Correction ◽  
Vertical Structure ◽  
Radar Data ◽  
Radar Reflectivity ◽  
Radar Signal ◽  
Precipitation Radar ◽  
Sensor Field ◽  
Spaceborne Radar ◽  
Ku Band ◽  
Reflectivity Factor

AbstractA spaceborne precipitation radar samples the vertical structure of precipitating hydrometeors from the top down. The viewing geometry and operating frequency result in certain limitations and opportunities. Among the limitations is attenuation of the radar signal that can cause the measured radar reflectivity factor to be substantially less than the desired quantity, the true radar reflectivity factor. Another error source is the spatial variability in precipitation rates that occurs at scales smaller than the sensor field of view (FOV), giving rise to the nonuniform beamfilling (NUBF) effect. The opportunities arise when the radar return from the surface can be used to obtain constraints on the path-integrated attenuation (PIA) for use in hybrid attenuation correction algorithms. The surface return can also provide some information on the degree of NUBF at off-nadir viewing angles. In this paper ground-based radar data are used to simulate spaceborne radar data at nadir and off-nadir viewing angles at Ku band and Ka band and to test attenuation correction algorithms in the presence of nonuniform beamfilling. The cross-FOV gradient in PIA is found to be an important characteristic for describing the performance of attenuation correction algorithms.

scholarly journals The Unit Symbol for the Logarithmic Scale of Radar Reflectivity Factors

2010 ◽  
Vol 27 (3) ◽  
pp. 615-616 ◽  
Author(s):  
Paul L. Smith
Keyword(s):  
Radar Reflectivity ◽  
Engineering Practice ◽  
Logarithmic Scale ◽  
International Standard ◽  
Logarithmic Unit ◽  
Reflectivity Factor

Abstract This note argues that the proper symbol for the logarithmic unit of radar reflectivity factor is dBz. The basis for this contention lies in both customary engineering practice and the international standard for unit symbols.

Smaller land-sea contrast on probability of precipitation (POP) of warm clouds over globe

2021 ◽  
Author(s):  
Jihu Liu ◽  
Minghuai Wang ◽  
Daniel Rosenfeld ◽  
Yannian Zhu
Keyword(s):  
Satellite Observations ◽  
Radar Reflectivity ◽  
Formation Processes ◽  
Dynamic Feedback ◽  
Aerosol Cloud ◽  
Warm Rain ◽  
Warm Cloud ◽  
Probability Of Precipitation ◽  
Reflectivity Factor

<p>Proper observation of global warm rain and understanding of its formation processes can significantly advance our understanding on aerosol-cloud-precipitation interactions. Previous study shows that due to smaller cloud effective radii (Re), rain from liquid clouds over land is sharply reduced compared to oceans (Mülmenstädt, 2015). However, in our study, we use A-Train satellite observations to show that there should be smaller land-sea difference on probability of precipitation (POP) of warm clouds between land and oceans. The discrepancy is probably because the algorithm bias in CloudSat precipitation flag products over land, which may mistakenly treat drizzle as no rain. We also find that if Re is smaller than 14 mm, no matter how thick the warm cloud is it can hardly produce significant precipitation (here defined as radar reflectivity factor lager than 0dBZ), which can generate dynamic feedback on the development of clouds.</p>

Sign in / Sign up

Export Citation Format

Share Document