A Robust C-Band Hydrometeor Identification Algorithm and Application to a Long-Term Polarimetric Radar Dataset

Abstract

A new 10-category, polarimetric-based hydrometeor identification algorithm (HID) for C band is developed from theoretical scattering simulations including wet snow, hail, and big drops/melting hail. The HID is applied to data from seven wet seasons in Darwin, Australia, using the polarimetric C-band (C-POL) radar, to investigate microphysical differences between monsoon and break periods. Scattering simulations reveal significant Mie effects with large hail (diameter . 1.5 cm), with reduced reflectivity and enhanced differential reflectivity Z dr and specific differential phase K dp relative to those associated with S band. Wet snow is found to be associated with greatly depreciated correlation coefficient r hv and moderate values of Z dr . It is noted that large oblate liquid drops can produce the same electromagnetic signatures at C band as melting hail falling quasi stably, resulting in some ambiguity in the HID retrievals. Application of the new HID to seven seasons of C-POL data reveals that hail and big drops/melting hail occur much more frequently during break periods than during monsoon periods. Break periods have a high frequency of vertically aligned ice above 12 km, suggesting the presence of strong electric fields. Reflectivity and mean drop diameter D 0 statistics demonstrate that convective areas in both monsoon and break periods may have robust coalescence or melting precipitation ice processes, leading to enhanced reflectivity and broader distributions of D 0 . Conversely, for stratiform regions in both regimes, mean reflectivity decreases below the melting level, indicative of evaporative processes. Break periods also have larger ice water path fractions, indicating substantial mixedphase precipitation generation as compared with monsoonal periods. In monsoon periods, a larger percentage of precipitation is produced through warm-rain processes.

The Green Ocean: Precipitation Insights from the GoAmazon2014/5 Experiment

“…Since BR was developed using a Darwin monsoonal dataset, we anticipate that study included modest convective diversity into congestus clouds, maritime continental and deeper convective 25 properties (those supporting additional graupel growth). Darwin may exhibit even more intense 'Break' (e.g., more continental characteristics) convective cell periods and associated DSD changes interspersed with maritime tropical 'Active' monsoonal conditions than observed from Amazon convection (e.g., May and Ballinger, 2007;Dolan et al, 2013;Schumacher et al, 2015;Giangrande et al, 2014aGiangrande et al, , 2016b. However, it appears use of BR would minimize the contributions from congestus or shallower organized convective precipitation found under Amazon conditions.…”

Multi-sensor analysis of convective activity in central Italy during the HyMeX SOP 1.1

“…Tmatrix simulations were performed for temperatures between −15 and 0 • C, liquid water fractions between 5 and 55 %, and particle densities between 0.2 and 0.9 g cm −3 (Pruppacher and Klett, 1978;Dolan and Rutledge, 2009;Dolan et al, 2013). The microphysical parameters used for simulations are summarized in Table 1.…”

“…The wide ranges from which microphysical parameters are randomly chosen take into account mechanisms that involved graupel formation and accretion during cloud development and are consistent with graupel microphysics described in literature cited above. Some classification algorithms do not distinguish graupel from small and dense ice hydrometeors, such as small hail (Straka et al, 2000), while others categorize it as either low-density or high-density graupel (Dolan et al, 2013). A wide, single set of graupel microphysics to take into account the different types of graupel including low-density graupel to small hail was used.…”

“…1 have been used to tune the membership functions for graupel. Those of Z dr and K dp were set to account for both spheroidal and conical shaped graupel by allowing Z dr to vary between −1 and 2 dB and K dp to vary between −2 and 10 •−1 similarly to Dolan et al (2013) and Evaristo et al (2013). Table 2 lists the parameters of the membership functions for the planes Z h − Z dr and Z h − K dp in comparison with those used in Baldini et al (2005).…”

Anvil microphysical signatures associated with lightning-produced NO<sub><i>x</i></sub>

“…As discussed in Stith et al (2014), for the 6 June 2012 Colorado case, data from the CSU-CHILL S-band dualpolarization Doppler radar in Greeley, CO were employed (Junyent et al, 2013). The dual-polarization capabilities of the CHILL radar facilitated the identification of the dominant hydrometeor types in the 6 June case using a fuzzy-logic hydrometeor identification developed by Dolan et al (2013). The 15 June 2012 case was out of range of the CHILL radar, so data from the National Weather Service (NWS) Weather Surveillance Radar 1998 Doppler (WSR-88D or NEXRAD) radar located near Denver, CO (KFTG) were used.…”