Mariko Oue

Two types of precipitation particle distribution in convective cells accompanying a Baiu frontal rainband around Okinawa Island, Japan

[1] Polarimetric radar variables and ground-based raindrop size distributions (DSDs) of two convective cells in a Baiu frontal rainband over the Okinawa region were analyzed to clarify the precipitation particle distributions in convective cells with low echo top heights. One cell existed in the stratiform rain zone, and the other was in the convective rain zone of the rainband. Both cells had echo top (30 dBZ) heights of approximately 5.5 km above sea level, with large radar reflectivity (Z h ) greater than 50 dBZ in each core. For the cell in the stratiform rain zone, polarimetric variables indicated that small raindrops predominated; differential reflectivity (Z DR ) was smaller than 1.5 dB, and the correlation coefficient (ρ hv ) was greater than 0.98 with large Z h (>40 dBZ). The DSD showed high number densities of small raindrops with diameters of 1-2 mm. For the other cell, polarimetric variables indicated the presence of large raindrops; Z DR greater than 1.5 dB and ρ hv smaller than 0.98 predominated in large Z h (>40 dBZ). The DSD for this cell showed lower number densities of raindrops with diameters of 1-2 mm and higher number densities of raindrops exceeding 3 mm. The significance of these distributions was confirmed by the Z DR and ρ hv for 25 cells in the stratiform rain zone and for 28 cells in the convective rain zone. It is notable that different precipitation particle distributions in convective cells were found in the stratiform and convective rain zones of a Baiu frontal rainband with common characteristics of low echo top heights and large Z h .

Estimation of cloud fraction profile in shallow convection using a scanning cloud radar

Large spatial heterogeneities in shallow convection result in uncertainties in estimations of domain-averaged cloud fraction profiles (CFP). This issue is addressed using large eddy simulations of shallow convection over land coupled with a radar simulator. Results indicate that zenith profiling observations are inadequate to provide reliable CFP estimates. Use of Scanning Cloud Radar (SCR), performing a sequence of cross-wind horizon-to-horizon scans, is not straightforward due to the strong dependence of radar sensitivity to target distance. An objective method for estimating domain-averaged CFP is proposed that uses observed statistics of SCR hydrometeor detection with height to estimate optimum sampling regions. This method shows good agreement with the model CFP. Results indicate that CFP estimates require more than 35 min of SCR scans to converge on the model domain average. Lastly, the proposed technique is expected to improve our ability to compare model output with cloud radar observations in shallow cumulus cloud conditions.

A Hydrometeor Classification Method for X-Band Polarimetric Radar: Construction and Validation Focusing on Solid Hydrometeors under Moist Environments

AbstractA fuzzy-logic-based hydrometeor classification (HC) method for X-band polarimetric radar (X-pol), which is suitable for observation of solid hydrometeors under moist environments producing little or no hail, is constructed and validated. This HC method identifies the most likely hydrometeor at each radar sampling volume from eight categories: 1) drizzle, 2) rain, 3) wet snow aggregates, 4) dry snow aggregates, 5) ice crystals, 6) dry graupel, 7) wet graupel, and 8) rain–hail mixture. Membership functions are defined on the basis of previous studies. The HC method uses radar reflectivity Zh, differential reflectivity Zdr, specific differential phase Kdp, and correlation coefficient ρhv as its main inputs, and temperature with some consideration of relative humidity as supplemental information. The method is validated against ground and in situ observations of solid hydrometeors (dry graupel, dry snow aggregates, and ice crystals) under a moist environment. Observational data from a ground-based ima...

Toward Exploring the Synergy Between Cloud Radar Polarimetry and Doppler Spectral Analysis in Deep Cold Precipitating Systems in the Arctic

The study of Arctic ice and mixed-phase clouds, which are characterized by a variety of ice particle types in the same cloudy volume, is challenging research. This study illustrates a new approach to qualitative and quantitative analysis of the complexity of ice and mixed-phase microphysical processes in Arctic deep precipitating systems using the combination of Ka-band zenith-pointing radar Doppler spectra and quasi-vertical profiles of polarimetric radar variables measured by a Ka/W-band scanning radar. The results illustrate the frequent occurrence of multimodal Doppler spectra in the dendritic/planar growth layer, where locally generated, slower-falling particle populations are well separated from faster-falling populations in terms of Doppler velocity. The slower-falling particle populations contribute to an increase of differential reflectivity (ZDR), while an enhanced specific differential phase (KDP) in this dendritic growth temperature range is caused by both the slower and faster-falling particle populations. Another area with frequent occurrence of multimodal Doppler spectra is in mixed-phase layers, where both populations produce ZDR and KDP values close to 0, suggesting the occurrence of a riming process. Joint analysis of the Doppler spectra and the polarimetric radar variables provides important insight into the microphysics of snow formation and allows the separation of the contributions of ice of different habits to the values of reflectivity and ZDR.