**4. Advances with polarimetric radar**

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**3. The development of polarimetric weather radar**

extreme precipitation events such as hail and snow storms.

wind effects that can cause considerable errors in radar rainfall measurements. For instance, interception of the radar beam with melting snow precipitation particles can cause overestimation of precipitation up to a factor of 5. Typical errors in radar rainfall include radar calibration, radar signal attenuation due to rain, radar measurements contaminated with nonmeteorological echoes (e.g., echoes due to ground or sea, buildings, ships, airplanes, birds, insects, wind farms, etc.), variation in the reflectivity-rainfall (*Z-R*) equation, variations of the vertical profile of reflectivity, extrapolation of reflectivity measured aloft to the ground, wind drift effects, radar beam overshooting the shallow precipitation, radar beam blockage and occultation, etc. Substantial work has been carried out to correct these errors in radar rainfall measurements and the literature is too large to summarize here. Perhaps the most significant progress has been the development of dual-polarization radar (or polarimetric radar), which has demonstrated significant improvements in terms of both data quality and accuracy of rainfall estimation [14] and this is why many countries have upgraded (or replaced) their operational weather radar networks with polarimetric capability.

Operational weather radars can be largely classified into single-polarization (SP) and dual-polarization (DP) weather radars. SP radars measure the reflectivity (Z) only and if the radar has Doppler capability, they also measure the radial velocities (*V*) of precipitation particles. DP radars, on the other hand, simultaneously (or alternately) transmit vertically and horizontally polarized electromagnetic waves and receive polarized backscattered signals. DP radars can measure additional variables such as the reflectivities at horizontal and vertical polarizations (*Zh* and *Zv*, respectively), the differential reflectivity (*Zdr*), the linear depolarization ratio (LDR), the correlation coefficient (ρ*hv*), and the differential phase (Φdp) (or its derivative, the specific differential phase *K*dp) that provide more information about the nature of the precipitation event. DP radars are sensitive to size, shape, orientation, and thermodynamic phase of the precipitation particles. This allows them to distinguish rain, snow, hail, melting snow, ice particles, etc., that can help to improve not only the precipitation measurement but also the identification of

DP weather radar can contribute not only to improve precipitation estimation, but also to improve our understanding of the microphysics of precipitation. DP

(*Zh* and *Zv*, respectively), which can be used to compute the differential reflectivity (*Zdr*) which is a measure of the size of the raindrops. In fact, *Zdr* was originally proposed to improve the estimation of precipitation because large raindrops falling to the ground are distorted into oblate spheroids due to aerodynamic forces being in average their maximal dimensions horizontally oriented [15]. From this, the backscattering cross section for large raindrops is larger for a horizontal polarized wave than for a vertical polarized wave (i.e., *Zh* > *Zv*). The differential reflectivity *Zdr* measures this difference, and typical small raindrops have *Zdr* values of about 0 dB, whereas large raindrops can have values of 3–4 dB depending on the radar frequency. Seliga and Bringi [16] showed that the mean volumetric diameter of raindrops can be related to the value *Zdr*, and therefore, *Zdr* is a measure of the mean particle shape, where large raindrops are associated with large values of *Zdr*. LDR provides a measure of depolarization of the precipitation particles. When nonspherical particles fall with their major axis at an angle to the axis of polarization, a small percentage of the transmitted energy is depolarized and yields a cross-polar return [17]. Depolarization is also a measure of the canting angle of the raindrops.

radars measure the reflectivities at horizontal and vertical polarizations

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#### **4.1 Identification of nonmeteorological echoes**

A weather radar usually scans at low-elevation angles to obtain rainfall measurements closer to the ground for hydrological purposes, but echoes from high ground or buildings can be misinterpreted as heavy precipitation. Although these echoes can be easily identified by using ground clutter maps, occasionally the radar beam is bent towards the earth surface due to changes in the vertical temperature and humidity distributions producing ground echoes due to anomalous propagation (AP), where their location is unpredictable. DP radar has enabled accurate classifications of clutter and AP echoes through the use of fuzzy logic or Bayes classifiers (see **Figure 2**) [18]. In fact, the fluctuating characteristics of the radar echoes such as the spatial variability (e.g., texture or the standard deviation) of *Zdr* and Φdp are good indicators of ground clutter and AP echoes. These features have been exploited to identify nonmeteorological echoes in radar observations, and recently, the same principle has been applied to identify echoes due to wind farms [19].

#### **4.2 Improvements in attenuation correction**

Attenuation (*A*) is the loss of signal power due to absorption and scattering of electromagnetic waves along the propagation path. Attenuation is considered negligible at S-band (3 GHz) frequencies, but not at C-band (5 GHz) or X-band (10 GHz) frequencies. Attenuation can cause significant underestimation of precipitation if no correction is performed. DP radar has enabled the development of robust algorithms for attenuation correction in the reflectivity through the use of differential phase measurements (Φdp and *K*dp), which are immune to rain attenuation. **Figure 3** shows an example of rain attenuation caused by an extreme

**Figure 2.** *Identification of nonmeteorological echoes in radar rainfall measurements [18].*

**Figure 3.** *Reflectivity and differential phase measured by a C-band radar during an extreme rain event [20].*

storm, which caused a large attenuation of reflectivity (see circled region on the left figure) that can be observed by the large phase shifts in Φdp (see circled region on the right figure). The figure shows a circled region where the reflectivity values decreased (in some areas by more than 20dBZ) due to the signal attenuation produced by the large heavy rainfall cell shown in red.
