Retrieval of Reflectivity in a Networked Radar Environment

Lim, Sanghun; Chandrasekar, V.; McLaughlin, D.J.

doi:10.1175/2008jtecha1008.1

Cited by 45 publications

(34 citation statements)

References 11 publications

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“…For further improvement, the next step will be the implementation of attenuation correction algorithms that use the advantage of a network (e.g. Chandrasekar and Lim, 2008;Srivastava and Tian, 1996;Testud and Amayenc, 1989). Better estimation of attenuation can lead to better precipitation estimates, because the relation between attenuation and precipitation is more stable than the relation between reflectivity and precipitation.…”

Section: Discussionmentioning

confidence: 99%

“…These methods allow for estimation of attenuation and correction of observed reflectivities simultaneously, if at least two radars observe a common volume (Testud and Amayenc, 1989;Kabeche and Testud, 1995;Srivastava and Tian, 1996;Tian and Srivastava, 1997;Chandrasekar and Lim, 2008;Lim et al, 2011). In the last few years, several networks consisting of different types of X-band radars have been installed to fill gaps in nationwide networks of C-or S-band radars, e.g.…”

Section: Introductionmentioning

confidence: 99%

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Performance of high-resolution X-band weather radar networks – the PATTERN example

Lengfeld¹,

Clemens²,

Münster

et al. 2014

Atmos. Meas. Tech.

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Abstract. This publication intends to prove that a network of low-cost local area weather radars (LAWR) is a reliable and scientifically valuable complement to nationwide radar networks. A network of four LAWRs has been installed in northern Germany within the framework of the Precipitation and Attenuation Estimates from a High-Resolution Weather Radar Network (PATTERN) project observing precipitation with a temporal resolution of 30 s, a range resolution of 60 m and a sampling resolution of 1 • in the azimuthal direction. The network covers an area of 60 km × 80 km. In this paper, algorithms used to obtain undisturbed precipitation fields from raw reflectivity data are described, and their performance is analysed. In order to correct operationally for background noise in reflectivity measurements, noise level estimates from the measured reflectivity field are combined with noise levels from the last 10 time steps. For detection of non-meteorological echoes, two different kinds of clutter algorithms are applied: single-radar algorithms and networkbased algorithms. Besides well-established algorithms based on the texture of the logarithmic reflectivity field (TDBZ) or sign changes in the reflectivity gradient (SPIN), the advantage of the unique features of the high temporal and spatial resolution of the network is used for clutter detection. Overall, the network-based clutter algorithm works best with a detection rate of up to 70 %, followed by the classic TDBZ filter using the texture of the logarithmic reflectivity field.A comparison of a reflectivity field from the PATTERN network with the product from a C-band radar operated by the German Meteorological Service indicates high spatial accordance of both systems in the geographical position of the rain event as well as reflectivity maxima. Long-term statistics from May to September 2013 prove very good accordance of the X-band radar of the network with C-band radar, but, especially at the border of precipitation events, higher-resolved X-band radar measurements provide more detailed information on precipitation structure because the 1 km range gate of C-band radars is only partially covered with rain. The standard deviation within a range gate of the C-band radar with a range resolution of 1 km is up to 3 dBZ at the borders of rain events. The probability of detection is at least 90 %, the false alarm ratio less than 10 % for both systems. Therefore, a network of high-resolution low-cost LAWRs can give valuable information on the small-scale structure of rain events in areas of special interest, e.g. urban regions, in addition to the nationwide radar networks.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Performance of high-resolution X-band weather radar networks – the PATTERN example

Lengfeld¹,

Clemens²,

Münster

et al. 2014

Atmos. Meas. Tech.

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“…Attenuation is a known issue for precipitation estimation using X-band radars (Seo et al 2010;Berne and Krajewski 2013). The CASA system uses the network reflectivity retrieval technique (Chandrasekar and Lim 2008) and the network based attenuation correction technique (Lim et al 2011) to mitigate the effects of attenuation. Lim et al (2011) showed that the technique works robustly in real time in retrieving attenuation corrected reflectivity.…”

Section: Figure 1 the Hl-rdhm Domain Encompassing Fortmentioning

confidence: 99%

High Resolution Flash Flood Forecasting for the Dallas-Fort Worth Metroplex

Habibi

Nasab

Norouzi

et al. 2016

JWMM

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Urban flash flooding is a serious problem in large highly populated areas such as the Dallas-Fort Worth metroplex (DFW). Being able to monitor and predict flash flooding at a high spatiotemporal resolution is critical to mitigating its threats and for cost effective emergency management. In this work, the prototype high resolution flash flood warning system under de velopment for DFW is described and a case study

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“…Due to the reduced cost of S-or C-band weather radars attention was moved from X-band to these systems during the 1970s and 1980s. However, with the launch of the TRMM satellite (Simpson et al, 1988) in 1997 and the CASA project, where a complementary X-band radar network is being proposed (Chandrasekar and Lim, 2008), better attenuation correction schemes have become of major interest and new research into X-band radar has begun. Where Hitschfeld and Bordan (1954) proposed a simple forward scheme to correct for attenuation, more sophisticated backward methods, which use a Path Integrated Attenuation constraint, have been developed since (e.g., Marzoug and Amayenc, 1994;Delrieu et al, 1997).…”

Section: Z Van De Beek Et Al: High-resolution X-band Radar For Rmentioning

confidence: 99%

Performance of high-resolution X-band radar for rainfall measurement in The Netherlands

Beek

Leijnse

Stricker

et al. 2010

Hydrol. Earth Syst. Sci.

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Abstract. This study presents an analysis of 195 rainfall events gathered with the X-band weather radar SOLIDAR and a tipping bucket rain gauge network near Delft, The Netherlands, between May 1993 and April 1994. The aim of this paper is to present a thorough analysis of a climatological dataset using a high spatial (120 m) and temporal (16 s) resolution X-band radar. This makes it a study of the potential for high-resolution rainfall measurements with nonpolarimetric X-band radar over flat terrain. An appropriate radar reflectivity -rain rate relation is derived from measurements of raindrop size distributions and compared with radar -rain gauge data. The radar calibration is assessed using a long-term comparison of rain gauge measurements with corresponding radar reflectivities as well as by analyzing the evolution of the stability of ground clutter areas over time. Three different methods for ground clutter correction as well as the effectiveness of forward and backward attenuation correction algorithms have been studied. Five individual rainfall events are discussed in detail to illustrate the strengths and weaknesses of high-resolution X-band radar and the effectiveness of the presented correction methods. X-band radar is found to be able to measure the space-time variation of rainfall at high resolution, far greater than what can be achieved by rain gauge networks or a typical operational C-band weather radar. On the other hand, SOLIDAR can suffer from receiver saturation, wet radome attenuation as well as signal loss along the path. During very strong convective situations the signal can even be lost completely. In combination with several rain gauges for quality control, high resolution X-band radar is considered to be suitable for Correspondence to: C. Z. van de Beek (remco.vandebeek@wur.nl) rainfall monitoring over relatively small (urban) catchments. These results offer great prospects for the new high resolution polarimetric doppler X-band radar IDRA.

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Retrieval of Reflectivity in a Networked Radar Environment

Cited by 45 publications

References 11 publications

Performance of high-resolution X-band weather radar networks – the PATTERN example

Performance of high-resolution X-band weather radar networks – the PATTERN example

High Resolution Flash Flood Forecasting for the Dallas-Fort Worth Metroplex

Performance of high-resolution X-band radar for rainfall measurement in The Netherlands

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