Microphysical and Polarimetric Radar Modeling of Hydrometeor Refreezing

A unique polarimetric radar signature indicative of hydrometeor refreezing during ice pellet events has been documented in several recent studies, yet the underlying microphysical causes remain unknown. The signature is characterized by enhancements in differential reflectivity (ZDR), specific differential phase (KDP), and linear depolarization ratio (LDR), and a reduction in co-polar correlation coefficient (ρhv) within a layer of decreasing radar reflectivity factor at horizontal polarization (ZH). In previous studies, the leading hypothesis for the observed radar signature is the preferential refreezing of small drops. Here, a simplified, one-dimensional, explicit bin microphysics model is developed to simulate the refreezing of fully melted hydrometeors, and coupled with a polarimetric radar forward operator to quantify the impact of preferential refreezing on simulated radar signatures. The modeling results demonstrate that preferential refreezing is insufficient by itself to produce the observed signatures. In contrast, simulations considering an ice shell growing asymmetrically around a freezing particle (i.e., emulating a thicker ice shell on the bottom of a falling particle) produce realistic ZDR enhancements, and also closely replicate observed features in ZH, KDP, LDR, and ρhv. Simulations that assume no increase in particle wobbling with freezing produce an even greater ZDR enhancement, but this comes at the expense of reducing the LDR enhancement. It is suggested that the polarimetric refreezing signature is instead strongly related to both the distribution of the unfrozen liquid portion within a freezing particle, and the orientation of this liquid with respect to the horizontal.

Radar Remote Sensing of Precipitation in High Mountains: Detection and Characterization of Melting Layer in the Grenoble Valley, French Alps

The RadAlp experiment aims at developing advanced methods for rain and snow estimation using weather radar remote sensing techniques in high mountain regions for improved water resource assessment and hydrological risk mitigation. A unique observation system has been deployed in the French Alps, Grenoble region. It is composed of a Météo-France operated X-band MOUC radar (volumetric, Doppler and polarimetric) on top of the Mt Moucherotte (1920 m ASL), the X-band XPORT research radar (volumetric, Doppler, polarimetric), a K-band micro rain radar (MRR, Doppler, vertically pointing) and in situ sensors (rain gauges, disdrometers), latter three operated on the Grenoble campus (220 m ASL). Based on the observation that the precipitation phase changes at/below the elevation of mountain-top MOUC radar for more than 60% of the significant events, an algorithm for ML identification has been developed using valley-based radar systems: it uses the quasi vertical profiles of XPORT polarimetric measurements (horizontal and vertical reflectivity, differential reflectivity, cross-polar correlation coefficient) and the MRR vertical profiles of apparent falling velocity spectra. The algorithm produces time series of the altitudes and values of peaks and inflection points of the different radar observables. A literature review allows us to link the micro-physical processes at play during the melting process with the available polarimetric and Doppler signatures, e.g., (i) regarding the altitude differences between the peaks of reflectivity, cross-polar correlation coefficient and differential reflectivity, as well as (ii) regarding the co-variation of the profiles of Doppler velocity spectra and cross-polar correlation coefficient. A statistical analysis of the ML based on 42 rain events (98 h of XPORT data) is then proposed. Among other results, this study indicates that (i) the mean value of the ML width in Grenoble is 610 m with a standard deviation of 160 m; (ii) the mean altitude difference between the horizontal reflectivity and the ρ H V peaks is 90 m and the mean altitude difference between the ρ H V and Zdr peaks is 30 m; (iii) even for the limited rainrate range in the dataset (0–8.5 mm h − 1 ), the “intensity effect” is clear on the reflectivity profile and the ML width, as well as on polarimetric variables such as ρ H V peak value and the Zdr enhancement in the upper part of the profile. On the contrary, the study of both the “density effect” and the influence of the 0 ° C isotherm altitude did not yield significant results with the considered dataset; (iv) a principal component analysis on one hand shows the richness of the dataset since the first 2 PCs explain only 50% of the total variance and on the other hand the added-value of the polarimetric variables since they rank high in a ranking of the total variance explained by individual variables.

Phased array transformation methods to estimate non-compact jet noise source characteristics

This paper reviews the basis of the beamformer and polar correlation phased array methods and shows that these provide different information about axially distributed, non-compact noise sources, which nevertheless satisfy a simple integral relationship. The conventional beamformer method provides an image of the source power or auto spectral density, whereas the polar correlation method yields a ‘source strength’ which is an image of the axial wavenumber transform of the source cross-spectral density. However, the beamformer method can be generalised to provide an image of the source cross-spectral density. At first sight, the generalised beamformer method is therefore more useful for diagnostic purposes but the results presented here suggest that the combined effects of resolution and source convection place serious limitations on the source cross-spectral density image information. For the same reasons, although the source power or auto spectral density axial shape can be obtained with the conventional beamformer method, it cannot yield its absolute level for this type of source. The polar correlation method yields a source strength axial distribution at each ‘reference’ microphone, which when integrated over the source length, yields the far-field power or auto spectral density at that reference microphone. Therefore, the polar correlation source strength is arguably the more relevant quantity to measure when determining what proportion of the sound at a particular microphone position comes from each region of the jet axis, as a function of radiation angle.

Rain microstructure retrievals using 2-D video disdrometer and C-band polarimetric radar

Measurements using the 2-D video disdrometer (2DVD) taken during a heavy rainfall event in Huntsville, Alabama, are analysed. The 2DVD images were processed to derive the rain microstructure parameters for each individual drop, which in turn were used as input to the T-matrix method to compute the forward and back scatter amplitudes of each drop at C-band. The polarimetric radar variables were then calculated from the individual drop contribution over a finite time period, e.g., 1 min. The calculated co-polar reflectivity, differential reflectivity, specific differential propagation phase and the co-polar correlation coefficient were compared with measurements from a C-band polarimetric radar located 15 km away. An attenuation-correction method based on the specific differential propagation phase was applied to the co-polar and differential reflectivity data from the C-band radar, after ensuring accurate radar calibration. Time series comparisons of the parameters derived from the 2DVD and C-band radar data show very good agreement for all four quantities, the agreement being sometimes better than the computations using the 1-min drop size distribution and bulk assumptions on rain microstructure (such as mean shapes and model-based assumptions for drop orientation). The agreement is particularly improved in the case of co-polar correlation coefficient since this parameter is very sensitive to variation of shapes as well as orientation angles. The calculations mark the first attempt at utilizing experimentally derived "drop- by-drop" rain microstructure information to compute the radar polarimetric parameters and to demonstrate the value of utilizing the 2-D video disdrometer for studying rain microstructure under various precipitation conditions. Histograms of drop orientation angles as well as the most probable drop shapes and the corresponding variations were also derived and compared with prior results from the 80 m fall "artificial rain" experiment.