Polarization Radar Estimates of Raindrop Size Spectra and Rainfall Rates

Illingworth, Anthony J.; Caylor, I. J.

doi:10.1175/1520-0426(1989)006<0939:preors>2.0.co;2

Cited by 14 publications

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“…6 and the symbols correspond to the drop size ranges shown in the legend. Note the ZDR-Z regression relation in legend and close correspondence to the purple curve based upon theory and radar observations of Illingworth and Caylor (1989). The black curve is that of Zhang et al (2003). riod is marked by a sharp limit at Z ϭ 53 dBZ, 1.5 Ͻ D 0 Ͻ 3 mm, and 2 Ͻ ZDR Ͻ 4 dB.…”

Section: Reflectivitysupporting

confidence: 59%

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Microphysics of Raindrop Size Spectra: Tropical Continental and Maritime Storms

Ulbrich

Atlas

2007

Journal of Applied Meteorology and Climatology

140

108

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This work uses raindrop size spectra measured at the surface in tropical continental storms to determine the associated parameters of the best-fit gamma distributions. The physical processes responsible for those parameters and their relations to the measurable radar reflectivity Z and differential reflectivity ZDR are then explored. So too are their relations to quantitative measurements of rain. Comparison is then made with corresponding features previously reported in tropical maritime regimes. The storms observed in Brazil and Arecibo, Puerto Rico, have been divided into convective (C), transition (T), and stratiform (S) segments. The raindrop size distribution (DSD) parameters are clearly defined on a gamma parameter diagram (GPD) that shows 1) how median volume drop size D 0 increases from S to T to C segments of the rain while 2) the range of the spectrum breadth parameter increases, and the range of the slope parameter ⌳ decreases in the same sequence of S to C. Drop growth occurs predominantly below the 0°C level by collision, coalescence, and breakup in the C rains. The median volume diameter D 0 grows as more of the water is concentrated near that size and so the DSD narrows; that is, both and ⌳ increase. In both maritime and continental storms the DSD in the convective portion of the storm approaches equilibrium. The coefficient A in the Z ϭ AR b relation increases with D 0 while the exponent b approaches unity. The D 0 and A pair increase with, and appear to be determined largely by, the updraft strength, thus providing a possible means of determining the appropriate algorithms for rainfall measurement. Although the small drop number samples measured by the surface disdrometer relative to the large volumes sampled by a radar tend to truncate the DSD at both small and large drop sizes, narrow distributions with ϭ 5 to 12 cannot be attributed to such an effect. Such narrow DSDs accord with common experience of monodispersed large drops at the beginning of a convective storm. There is also remarkable agreement of the surface-based observations of ZDR-Z-D 0 with the time-space variations from C to T to S rain types observed by radar in England and elsewhere. Because the C region of a storm often accounts for a major share of the rain accumulation despite its shorter duration, it is particularly important to measure that region more accurately. There are distinctive clusters of the generalized number parameter N W versus D 0 between maritime and continental storms. Methods for remote sensing and parameterization must partition the rainstorms into convective, transition, and stratiform segments.

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Section: Reflectivitysupporting

confidence: 59%

“…The storm Bringi and Chandrasekar 2001). The solid curve is that of Illingworth and Caylor (1989). See text for details.…”

Section: ) the Environmentmentioning

confidence: 99%

Microphysics of Raindrop Size Spectra: Tropical Continental and Maritime Storms

Ulbrich

Atlas

2007

Journal of Applied Meteorology and Climatology

140

108

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“…To verify these estimated calibration numbers, a scatterplot of Z dr versus Z is made for data with f dp , 308 (to minimize possible bias caused FIG. For comparison, the curve found by Illingworth and Caylor (1989) is plotted in Fig. SHV mode Z dr (solid line) and FHV mode LDR h (dashed line) from the model.…”

Section: Koun Data Example Of Antenna Polarization Errorsmentioning

confidence: 99%

Modeling, Error Analysis, and Evaluation of Dual-Polarization Variables Obtained from Simultaneous Horizontal and Vertical Polarization Transmit Radar. Part II: Experimental Data

Hubbert

Ellis

Dixon

et al. 2010

Journal of Atmospheric and Oceanic Technology

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In this second article in a two-part work, the biases of weather radar polarimetric variables from simultaneous horizontally and vertically transmit (SHV) data are investigated. The biases are caused by cross coupling of the simultaneously transmitted vertical (V) and horizontal (H) electric fields. There are two primary causes of cross coupling: 1) the nonzero mean canting angle of the propagation medium (e.g., canted ice crystals) and 2) antenna polarization errors. Given herein are experimental data illustrating both bias sources. In Part I, a model is developed and used to quantify cross coupling and its impact on polarization measurements.

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“…The use of polarized radar to determine the raindrop size spectrum has been proposed to reduce this source of error (Ulbrich, 1986;Illingworth and Caylor, 1989;Jameson, 1989;Messaoud and Pointin, 1990). The ratio of the vertical to the horizontal polarization reflectivities contains information on the ratio of the minor to major axes of the reflectivity-weighted mean drop size.…”

Section: Estimation Of Precipitation With Radarmentioning

confidence: 99%

Precipitation

1996

Hydrology Handbook

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Polarization Radar Estimates of Raindrop Size Spectra and Rainfall Rates

Cited by 14 publications

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Microphysics of Raindrop Size Spectra: Tropical Continental and Maritime Storms

Microphysics of Raindrop Size Spectra: Tropical Continental and Maritime Storms

Modeling, Error Analysis, and Evaluation of Dual-Polarization Variables Obtained from Simultaneous Horizontal and Vertical Polarization Transmit Radar. Part II: Experimental Data

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