![]() ![]() ![]() 2013) to segregate observed rainfall into either stratiform or convective type so that a corresponding Z e –R relation can be applied. Algorithms that are based on radar measurements were developed (e.g., Qi et al. (1993) for monsoon, convective maritime rain regimes, and continental squall lines. The Z e = 230 R 1.25 relation, which is based on observed tropical rainfall DSDs, was proposed for C-band (~5 GHz) frequencies by Rosenfeld et al. The convective WSR-88D relation represents the “Miami” relation from Woodley (1970). ![]() Snowflake melting is one of the dominant mechanisms for stratiform-rainfall formation, and this rainfall type typically exhibits the radar bright band caused by mixed-phase hydrometeors in the melting layer. The stratiform WSR-88D relation is often referred to as the Marshall–Palmer relation ( Marshall et al. 2011), including those for convective rain ( Z e = 300 R 1.4 Z e is in mm 6 m −3 and R is in millimeters per hour), stratiform rain ( Z e = 200 R 1.6), and warm “tropical” rain ( Z e = 230 R 1.25). The DSD variability results in changes in relations between rain rate R and the equivalent radar reflectivity factor on horizontal polarization Z eh (hereinafter, just reflectivity Z e), which are used in the traditional radar-based QPE methods and also in relations that additionally utilize polarimetric radar variables such as differential reflectivity Z DR and the specific differential phase shift K DP (e.g., Bringi and Chandrasekar 2001).įor the continental United States, the Multi-Radar Multi-Sensor (MRMS) system, which was built using components of the National Mosaic and Multi-Sensor QPE (NMQ) system and which utilizes National Weather Service ground-based scanning S-band (~3 GHz) Weather Surveillance Radar-1998 Doppler (WSR-88D) measurements, uses several default Z e –R relations (e.g., Zhang et al. Identifying areas of common NBB rain could be possible from Z e and Z DR measurements.Įrrors of radar-based quantitative precipitation estimation (QPE) at the ground are caused by a number of different factors, including radar calibration uncertainties, partial beamfilling and blockage, vertical changes in observed variables between radar resolution volumes and the ground, and variability in drop size distributions (DSDs) that modify mean relations between rainfall and radar variables. No significant differences among the estimators for the same rain type derived using DSDs from different observational sites were present despite significant separation and differing terrain. Underestimations in NBB rain-rate retrievals derived using other rain-type estimators (e.g., those for BB or convective rain or default operational radar estimators) for the same values of radar variables can be on average about 40%, although the differential phase-based estimators are somewhat less susceptible to DSD details. Differences among same-type estimators for mostly stratiform BB and deep-convective rain were relatively minor, but estimators derived for the common NBB rain type were distinct. Data from a year of combined DSD and rain-type observations were used to derive S-band-radar estimators of rain rate R, including those based on traditional reflectivity Z e and ones that also use differential reflectivity Z DR and specific differential phase K DP. Collocated with S-PROF, disdrometer measurements showed that drop size distributions (DSDs) of NBB rain have much larger relative fractions of smaller drops when compared with those of BB and convective rains. This common nonbrightband (NBB) rain contributes ~15%–20% of total accumulation and is not considered as a separate rain type by current precipitation-segregation operational radar-based schemes, which separate rain into stratiform, convective, and, sometimes, tropical types. Hydrometeorology Testbed sites indicated a frequent occurrence of rain that did not exhibit radar bright band (BB) and was observed outside the periods of deep-convective precipitation. S-band profiling (S-PROF) radar measurements from different southeastern U.S.
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