Radar estimates of rainfall rates at the ground in bright band and non‐bright band events

Abstract

The major error in estimating precipitation rates at the ground from radar arises from the change in radar reflectivity (Z) with height. In stratiform precipitation Z rises in the 'bright band', where the snow is melting, and then falls steeply in the dry ice above. In regions of vigorous convection containing graupel, the bright band is absent and the fall in Z with height is less marked. If accurate estimates of surface precipitation are to be made, based upon radar observations taken within or above the bright band, it is important to use a correction scheme which uses a different vertical profile of reflectivity (VPR) for the two precipitation types. Using a large radar data set, this work addresses the issue of VPR variability by constructing average vertical profiles and sorting them into snow and graupel categories using the value of the Linear Depolarization Ratio at the melting layer. These observations show that convection is often embedded within stratiform precipitation, and some convective showers containing snow have bright bands. As a result, the use of an average profile over the whole region scanned by radar leads to only marginal improvement in rain estimates. Instead, this work proposes that a bright band correction should always be applied unless the value of Z at 1.5 km above the bright band exceeds 30 dBZ, in which case a 'convective' vertical profile of -2 dBZ km-' should be used. This Z threshold indicates that graupel only forms when the ice water content exceeds 0.35 gm-' which has implications for ice parametrization schemes in mesoscale models.

Brightband Identification Based on Vertical Profiles of Reflectivity from the WSR-88D

“…To obtain an accurate estimate of the brightband layer, the observed precipitation is segregated into convective and stratiform areas based on vertical reflectivity structure. A radar bin column is identified as convective if one of the following conditions is met: a) a reflectivity at any height in the column is greater than 50 dBZ (adaptable parameter) or b) a reflectivity is greater than 30 dBZ at Ϫ10°C height or above (Smyth and Illingworth 1998). Temperature soundings are obtained from hourly analyses of the Rapid Update Cycle (RUC; Benjamin et al 2004) model.…”

“…Further, the threshold is an adaptive parameter and can be easily adjusted. The second criterion is similar to that proposed by Smyth and Illingworth (1998). The current scheme directly applies to each pixel column and does not require searching and repetitive computations in a moving window surrounding each pixel for the "peakness" criteria in Steiner et al (1995), and it is therefore more computationally efficient.…”

“…The phenomenon has been recognized since the very early ages of radar meteorology (e.g., Ryde 1946;Austin and Bemis 1950;Wexler and Atlas 1956;Lhermitte and Atlas 1963). The locally high reflectivity causes significant overestimation in radar precipitation estimates if an appropriate correction is not applied (e.g., Koistinen 1991;Joss and Lee 1995;Andrieu and Creutin 1995;Kitchen et al 1994;Smyth and Illingworth 1998;Westrick et al 1999;Vignal et al 1999Vignal et al , 2000Seo et al 2000;Vignal and Krajewski 2001;Germann and Joss 2002;Bellon et al 2005; and references therein). Thus it is important to identify those areas of radar observations that are af-fected by the brightband layer.…”

A Real-Time Algorithm for the Correction of Brightband Effects in Radar-Derived QPE

“…The BB layer was clearly defined and its bottom was well above the ground (Fig. To mitigate radar precipitation errors associated with bright band and also with the ice region above BB, both of which are due to nonuniform vertical profiles of reflectivity (VPRs), many methods have been proposed (e.g., Koistinen 1991;Joss and Lee 1995;Andrieu and Creutin 1995;Kitchen et al 1994;Smyth and Illingworth 1998;Westrick et al 1999;Vignal et al 1999Vignal et al , 2000Seo et al 2000;Vignal and Krajewski 2001;Germann and Joss 2002;Bellon et al 2005; and references therein). The second was a springtime squall-line system that occurred on 27 May 2008 in the southern plains (Figs.…”

“…Andrieu and Creutin (1995) proposed a sophisticated inversion scheme to filter radar sampling effects (i.e., beam broadening as a function of range) and retrieved a mean VPR over the radar domain from two elevation angles. Smyth and Illingworth (1998) applied similar parameterized VPR correction to radar-derived QPE, but only to stratiform precipitation, which was segregated from convective regions. Both evaluations showed that the local VPR approach provided more improvements in radar-derived QPE than the mean volume scan VPRs.…”