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Observations of Convective Thermals with Weather Radar) and Wilson et al. (1994) discussed Bragg scatter and insects as sources of radar echoes from the convergence lines and came to a conclusion that insects are the main source of radar echoes, although Bragg scatter was not excluded. All the abovementioned observations used nonpolarimetric radar data in which distinguishing Bragg from insect echoes in not possible. Turbulent eddies with sizes of about 5-cm scatter S-band radiation (e.g., Doviak and Zrnić 2006 , section 11.6) and produce
) and Wilson et al. (1994) discussed Bragg scatter and insects as sources of radar echoes from the convergence lines and came to a conclusion that insects are the main source of radar echoes, although Bragg scatter was not excluded. All the abovementioned observations used nonpolarimetric radar data in which distinguishing Bragg from insect echoes in not possible. Turbulent eddies with sizes of about 5-cm scatter S-band radiation (e.g., Doviak and Zrnić 2006 , section 11.6) and produce
1. Introduction The current generation of Weather Surveillance Radar-1988 Doppler (WSR-88D) weather radars in the United States is more than 20 years of age ( Yussouf and Stensrud 2008 ). Despite recent major improvements to the network (such as dual-polarization capabilities; Doviak et al. 2000 ), there are a number of potential enhancements that are currently being explored as researchers look toward the future of weather radar observations. Of key importance to National Weather Service
1. Introduction The current generation of Weather Surveillance Radar-1988 Doppler (WSR-88D) weather radars in the United States is more than 20 years of age ( Yussouf and Stensrud 2008 ). Despite recent major improvements to the network (such as dual-polarization capabilities; Doviak et al. 2000 ), there are a number of potential enhancements that are currently being explored as researchers look toward the future of weather radar observations. Of key importance to National Weather Service
given here. Table 1. Precipitation type identifiers from NOAA’s NEXRAD reanalysis. 1) ROQPE Radar-only precipitation rates are obtained by applying Z – R relationships to the mosaicked hybrid scan reflectivity field pixel by pixel. Zhang et al. (2011) provide the overview of precipitation rate generation. 2) GCQPE Bias correction of radar-only QPEs is based on an additive radar rainfall error model. The details can be found in Zhang et al. (2011 , 2014) . Rain gauge observations used in this
given here. Table 1. Precipitation type identifiers from NOAA’s NEXRAD reanalysis. 1) ROQPE Radar-only precipitation rates are obtained by applying Z – R relationships to the mosaicked hybrid scan reflectivity field pixel by pixel. Zhang et al. (2011) provide the overview of precipitation rate generation. 2) GCQPE Bias correction of radar-only QPEs is based on an additive radar rainfall error model. The details can be found in Zhang et al. (2011 , 2014) . Rain gauge observations used in this
where this variability occurs. This paper presents one possible method using radars. Radars measure the reflectivity factor Z derived from observations of backscattered intensities I in sample volumes. For stationary antennas, the signal fluctuations are determined by random coherent summations of the electromagnetic waves reflected by the individual particles as described by Rayleigh statistics. The variance then is equal to the mean squared (i.e., the relative dispersion of the intensity σ I
where this variability occurs. This paper presents one possible method using radars. Radars measure the reflectivity factor Z derived from observations of backscattered intensities I in sample volumes. For stationary antennas, the signal fluctuations are determined by random coherent summations of the electromagnetic waves reflected by the individual particles as described by Rayleigh statistics. The variance then is equal to the mean squared (i.e., the relative dispersion of the intensity σ I
paper is on the radar observations of the El Reno Storm from its initial development through when it produced giant hail up to 16 cm in diameter. Data and methods are discussed in section 2 , with section 3 detailing the observations of the storm from the PAR. Section 4 presents DP data from KOUN and RaxPol around the time periods of giant hail. Discussion and conclusions follow in sections 5 and 6 . 2. Data and methods a. Giant hailstone observations Observations of giant hail mostly were
paper is on the radar observations of the El Reno Storm from its initial development through when it produced giant hail up to 16 cm in diameter. Data and methods are discussed in section 2 , with section 3 detailing the observations of the storm from the PAR. Section 4 presents DP data from KOUN and RaxPol around the time periods of giant hail. Discussion and conclusions follow in sections 5 and 6 . 2. Data and methods a. Giant hailstone observations Observations of giant hail mostly were
1. Introduction During the last couple of decades several studies in the literature have focused on observations of ice particles with polarimetric radars. These studies often included the analysis of in situ aircraft measurements and mainly considered the radar observations of differential reflectivity ( Bader et al. 1987 ; Wolde and Vali 2001a , b ; Hogan et al. 2002 ) and linear depolarization ratio ( Matrosov et al. 1996 , 2001 ; Wolde and Vali 2001a , b ). Several papers considered
1. Introduction During the last couple of decades several studies in the literature have focused on observations of ice particles with polarimetric radars. These studies often included the analysis of in situ aircraft measurements and mainly considered the radar observations of differential reflectivity ( Bader et al. 1987 ; Wolde and Vali 2001a , b ; Hogan et al. 2002 ) and linear depolarization ratio ( Matrosov et al. 1996 , 2001 ; Wolde and Vali 2001a , b ). Several papers considered
will yield that are, in general, equal to or larger than those found using ρ 12 . Regardless of which is larger, however, it is clear that precipitation Bragg scatter (pBs) is seen by radars looking tangentially to the ground. In the limited number of observations thus far, the average in rain and snow are 34% and 72%, respectively. An obvious question, then, is: Can pBs also occur when a radar looks vertically? In this brief paper, it is shown that the answer is yes. I then also discuss some
will yield that are, in general, equal to or larger than those found using ρ 12 . Regardless of which is larger, however, it is clear that precipitation Bragg scatter (pBs) is seen by radars looking tangentially to the ground. In the limited number of observations thus far, the average in rain and snow are 34% and 72%, respectively. An obvious question, then, is: Can pBs also occur when a radar looks vertically? In this brief paper, it is shown that the answer is yes. I then also discuss some
-minute-averaged DSD samples are available for analysis in this study. Synthetic radar variables are calculated from 2DVD observations using the T matrix scattering approach for nonspherical particles ( Zhang et al. 2001 ). The axis ratio of raindrops in calculating backscattering amplitudes used in this study is based on Brandes et al. (2002) . Since the effects of temperature on synthetic radar variables are negligibly small ( Aydin and Giridhar 1992 ), the raindrop temperature is assumed to be 10°C and the
-minute-averaged DSD samples are available for analysis in this study. Synthetic radar variables are calculated from 2DVD observations using the T matrix scattering approach for nonspherical particles ( Zhang et al. 2001 ). The axis ratio of raindrops in calculating backscattering amplitudes used in this study is based on Brandes et al. (2002) . Since the effects of temperature on synthetic radar variables are negligibly small ( Aydin and Giridhar 1992 ), the raindrop temperature is assumed to be 10°C and the
obtained from social media postings in the aftermath of the 27 April 2011 tornado outbreak. However, Knox et al. (2013) also found that the debris that were transported the farthest actually traveled to the right of tornado motion, perhaps due to being lofted to higher altitudes and experiencing more westerly winds. Van Den Broeke (2015) provided polarimetric radar observations of debris fallout both downstream of the storm-relative flow and on the northwest periphery of supercells. Fallout of
obtained from social media postings in the aftermath of the 27 April 2011 tornado outbreak. However, Knox et al. (2013) also found that the debris that were transported the farthest actually traveled to the right of tornado motion, perhaps due to being lofted to higher altitudes and experiencing more westerly winds. Van Den Broeke (2015) provided polarimetric radar observations of debris fallout both downstream of the storm-relative flow and on the northwest periphery of supercells. Fallout of
1. Introduction Close proximity to quickly evolving severe weather phenomena for high-resolution data collection is difficult to achieve with traditional fixed-site radars. Thus, mobile weather radar systems are used to increase the likelihood of near-storm observations. Mobile radars are a common sight in midwestern regions when the potential for high-impact weather events is significant. One of the original mobile systems was the Center for Severe Weather Research (CSWR) Doppler on Wheels
1. Introduction Close proximity to quickly evolving severe weather phenomena for high-resolution data collection is difficult to achieve with traditional fixed-site radars. Thus, mobile weather radar systems are used to increase the likelihood of near-storm observations. Mobile radars are a common sight in midwestern regions when the potential for high-impact weather events is significant. One of the original mobile systems was the Center for Severe Weather Research (CSWR) Doppler on Wheels
