Simulation of X-Band Rainfall Observations from S-Band Radar Data

Chandrasekar, V.; Lim, Sanghun; Gorgucci, E.

doi:10.1175/jtech1909.1

Cited by 44 publications

(28 citation statements)

References 22 publications

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“…The intrinsic reflectivity at X-band is not equal to the reflectivity at S-band. Chandrasekar et al [32] proposed three different methodologies for simulating X-band radar observations from the S-band radar data and the empirical conversion method is used in the paper. Figure 4 shows a plot of the intrinsic reflectivity at X and S bands for a monodispersed drop size distribution using the shape mode proposed by Beard and Chuang [33].…”

Section: Resultsmentioning

confidence: 99%

Rain Attenuation Correction of Reflectivity for X-Band Dual-Polarization Radar

et al. 2016

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Abstract:In order to improve the performance of X-band dual-polarization radars, it is necessary to conduct attenuation correction before using the X-band radar data. This study analyzes a variety of attenuation correction methods for the X-band radar reflectivity, and proposes a high-resolution slide self-consistency correction (SSCC) method, which is an improvement of Kim et al.'s method based on Bringi et al.'s original method. The new method is comprehensively evaluated with the observational data of convective cloud, stratiform cloud, and the stratiform cloud with embedded convection. Comparing with the intrinsic reflectivity at X-band calculated from the reflectivity at S-band, it is found that the new method can effectively reduce the correction errors when calculating differential propagation shift increments using the conventional self-consistency attenuation correction method. This method can efficiently correct the X-band dual-polarization radar reflectivity, in particular, for the echoes with reflectivity greater than 35 dBZ.

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Section: Resultsmentioning

confidence: 99%

Rain Attenuation Correction of Reflectivity for X-Band Dual-Polarization Radar

et al. 2016

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“…A further step would be to simulate range profiles maps, or volumes of radar measurements from existing high quality dataset of radar measurements. Chandrasekar et al [2006] proposed different methods to simulate realistic profiles starting from S-band dual polarization measurements to generate realistic range profiles of radar variables at attenuating frequencies using fundamental microphysical properties of rain, namely, size and shape distribution information of frequency mapping method. Conditioning the simulation from S band measurements maintains the natural distribution of rainfall microphysical parameters.…”

Section: Methodsmentioning

confidence: 99%

Microwave radar signatures of precipitation from S band to K_a band: application to GPM mission

Baldini

Chandrasekar

Moisseev

2012

European Journal of Remote Sensing

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Radars at different frequencies have been used over five decades for observing precipitation. S and C bands have been employed for long range coverage observations. Dual-polarization X-band radars have been shown to be useful for networked applications. Space borne precipitation radars have been at K u band, or higher frequencies such as K a , as in the GPM mission. This paper presents a comprehensive and unified view of radar precipitation observations at these bands, highlighting the advantages, limitations and the specific applications associated to them. Moreover, relationships between radar measurements at different bands in rain are illustrated. Examples of their use to predict attenuation margin and to simulate observations of the dual polarization, dual frequency K u and K a scanning radar D3R to be used in the ground validation program of the GPM mission are shown.

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“…Rain rates R calculated from the gamma distribution were used to limit the retrieval to 2.5 , R , 300 mm h 21 (Chandrasekar et al 2006). …”

Section: ) Rainmentioning

confidence: 99%

“…The HID algorithms were then applied to mosaicked gridded data. The IP1 reflectivity data were corrected for attenuation using the network-based attenuation correction algorithm described in Chandrasekar and Lim (2008) and a self-consistent differential phase-based attenuation correction (Park et al 2005) was applied to Z dr values. During the IP1 2007 project, IP1 Z dr values were uncalibrated.…”

Section: B Application Of Algorithmmentioning

confidence: 99%

“…The results of the simulations will be used to develop membership beta functions as part of an X-band fuzzy-logic hydrometeor identification scheme. The HID will be applied to data from the Collaborative Adaptive Sensing of the Atmosphere (CASA) Integrated Project 1 (IP1) network of X-band radars located in Oklahoma (Chandrasekar et al 2008). Section 2 describes the theoretical simulations and results.…”

Section: Introductionmentioning

confidence: 99%

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A Theory-Based Hydrometeor Identification Algorithm for X-Band Polarimetric Radars

Dolan

Rutledge

2009

Journal of Atmospheric and Oceanic Technology

160

127

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Although much work has been done at S band to automatically identify hydrometeors by using polarimetric radar, several challenges are presented when adapting such algorithms to X band. At X band, attenuation and non-Rayleigh scattering can pose significant problems. This study seeks to develop a hydrometeor identification (HID) algorithm for X band based on theoretical simulations using the T-matrix scattering model of seven different hydrometeor types: rain, drizzle, aggregates, pristine ice crystals, low-density graupel, highdensity graupel, and vertical ice. Hail and mixed-phase hydrometeors are excluded for the purposes of this study. Non-Rayleigh scattering effects are explored by comparison with S-band simulations. Variable ranges based on the theoretical simulations are used to create one-dimensional fuzzy-logic membership beta functions that form the basis of the new X-band HID. The theory-based X-band HID is applied to a case from the Collaborative Adaptive Sensing of the Atmosphere (CASA) Integrated Project 1 (IP1) network of X-band radars, and comparisons are made with similar S-band hydrometeor identification algorithms applied to data from the S-band polarimetric Next Generation Weather Radar (NEXRAD) prototype radar, KOUN. The Xband HID shows promise for illustrating bulk hydrometeor types and qualitatively agrees with analysis from KOUN. A simple reflectivity-and temperature-only HID is also applied to both KOUN and CASA IP1 data to reveal benefits of the polarimetric-based HID algorithms, especially in the classification of ice hydrometeors and oriented ice crystals.

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Simulation of X-Band Rainfall Observations from S-Band Radar Data

Cited by 44 publications

References 22 publications

Rain Attenuation Correction of Reflectivity for X-Band Dual-Polarization Radar

Rain Attenuation Correction of Reflectivity for X-Band Dual-Polarization Radar

Microwave radar signatures of precipitation from S band to K_a band: application to GPM mission

A Theory-Based Hydrometeor Identification Algorithm for X-Band Polarimetric Radars

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Simulation of X-Band Rainfall Observations from S-Band Radar Data

Cited by 44 publications

References 22 publications

Rain Attenuation Correction of Reflectivity for X-Band Dual-Polarization Radar

Rain Attenuation Correction of Reflectivity for X-Band Dual-Polarization Radar

Microwave radar signatures of precipitation from S band to Ka band: application to GPM mission

A Theory-Based Hydrometeor Identification Algorithm for X-Band Polarimetric Radars

Contact Info

Product

Resources

About

Microwave radar signatures of precipitation from S band to K_a band: application to GPM mission