Yinghui Lu

X-Band Polarimetric and Ka-Band Doppler Spectral Radar Observations of a Graupel-Producing Arctic Mixed-Phase Cloud

AbstractCharacteristics of graupel in an Arctic deep mixed-phase cloud on 7 December 2013 were identified with observations from an X-band scanning polarimetric radar and a Ka-band zenith-pointing radar in conjunction with scattering calculations. The cloud system produced generating cells and strongly sheared precipitation fall streaks. The X-band radar hemispheric RHI observables revealed spatial sorting of polarimetric signatures: decreasing (with increasing range) differential propagation phase shift φDP, negative specific differential phase KDP collocated with negative differential reflectivity ZDR in the upper half of the fall streak, and increasing or near-constant φDP with positive ZDR at the bottom edge of the fall streak. The negative KDP and ZDR, indicating prolate particles with vertically oriented maximum dimensions, were consistent with small, slow-falling conical graupel coexisting with low concentrations of more isometric graupel. The observed negative KDP values were best matched by scatt...

Polarimetric Radar Signatures of Dendritic Growth Zones within Colorado Winter Storms

AbstractX-band polarimetric radar observations of winter storms in northeastern Colorado on 20–21 February, 9 March, and 9 April 2013 are examined. These observations were taken by the Colorado State University–University of Chicago–Illinois State Water Survey (CSU-CHILL) radar during the Front Range Orographic Storms (FROST) project. The polarimetric radar moments of reflectivity factor at horizontal polarization ZH, differential reflectivity ZDR, and specific differential phase KDP exhibited a range of signatures at different times near the −15°C temperature level favored for dendritic ice crystal growth. In general, KDP was enhanced in these regions with ZDR decreasing and ZH increasing toward the ground, suggestive of aggregation (or riming). The largest ZDR values (~3.5–5.5 dB) were observed during periods of significant low-level upslope flow. Convective features observed when the upslope flow was weaker had the highest KDP (>1.5° km−1) and ZH (>20 dBZ) values. Electromagnetic scattering calculation...

Linear Depolarization Ratios of Columnar Ice Crystals in a Deep Precipitating System over the Arctic Observed by Zenith-Pointing Ka-Band Doppler Radar

AbstractThis study demonstrates that linear depolarization ratio (LDR) values obtained from zenith-pointing Ka-band radar Doppler velocity spectra are sufficient for detecting columnar ice crystals. During a deep precipitating system over the Arctic on 7 December 2013, the radar recorded LDR values up to −15 dB at temperatures corresponding to the columnar ice crystal growth regime. These LDR values were also consistent with scattering calculations for columnar ice crystals. Enhancements in LDR were suppressed within precipitation fallstreaks because the enhanced LDR values of columnar ice crystals were masked by the returns from the particles within the fallstreaks. However, Doppler velocity spectra of LDR within the fallstreak distinguished populations of slower-falling particles with high LDR (>−15 dB) and faster-falling particles with much lower LDR, suggesting that columnar ice crystals with high LDR coexisted with larger isometric particles that produced low LDR while dominating the total copolar re...

Use of X-Band Differential Reflectivity Measurements to Study Shallow Arctic Mixed-Phase Clouds

AbstractMicrophysical processes in shallow Arctic precipitation clouds are illustrated using measurements of differential reflectivity ZDR from the U.S. Department of Energy Atmospheric Radiation Measurement Program polarimetric X-band radar deployed in Barrow, Alaska. X-band hemispheric range height indicator scans used in conjunction with Ka-band radar and lidar measurements revealed prolonged periods dominated by vapor depositional, riming, and/or aggregation growth. In each case, ice precipitation fell through at least one liquid-cloud layer in a seeder–feeder situation before reaching the surface. A long period of sustained low radar reflectivity ZH (<0–5 dBZ) and high ZDR (6–7.5 dB) throughout the depth of the cloud and subcloud layer, coinciding with observations of large pristine dendrites at the surface, suggests vapor depositional growth of large dendrites at low number concentrations. In contrast, ZDR values decreased to 2–3 dB in the mean profile when surface precipitation was dominated by agg...

Estimating ice particle scattering properties using a modified Rayleigh-Gans approximation

A modification to the Rayleigh-Gans approximation is made that includes self-interactions between different parts of an ice crystal, which both improves the accuracy of the Rayleigh-Gans approximation and extends its applicability to polarization-dependent parameters. This modified Rayleigh-Gans approximation is both efficient and reasonably accurate for particles with at least one dimension much smaller than the wavelength (e.g., dendrites at millimeter or longer wavelengths) or particles with sparse structures (e.g., low-density aggregates). Relative to the Generalized Multiparticle Mie method, backscattering reflectivities at horizontal transmit and receive polarization (HH) (ZHH) computed with this modified Rayleigh-Gans approach are about 3 dB more accurate than with the traditional Rayleigh-Gans approximation. For realistic particle size distributions and pristine ice crystals the modified Rayleigh-Gans approach agrees with the Generalized Multiparticle Mie method to within 0.5 dB for ZHH whereas for the polarimetric radar observables differential reflectivity (ZDR) and specific differential phase (KDP) agreement is generally within 0.7 dB and 13%, respectively. Compared to the A-DDA code, the modified Rayleigh-Gans approximation is several to tens of times faster if scattering properties for different incident angles and particle orientations are calculated. These accuracies and computational efficiencies are sufficient to make this modified Rayleigh-Gans approach a viable alternative to the Rayleigh-Gans approximation in some applications such as millimeter to centimeter wavelength radars and to other methods that assume simpler, less accurate shapes for ice crystals. This method should not be used on materials with dielectric properties much different from ice and on compact particles much larger than the wavelength.

Comparison of using distribution‐specific versus effective radius methods for hydrometeor single‐scattering properties for all‐sky microwave satellite radiance simulations with different microphysics parameterization schemes

The Community Radiative Transfer Model (CRTM) presently uses one lookup table (LUT) of cloud and precipitation single-scattering properties at microwave frequencies, with which any particle size distribution may interface via effective radius. This may produce scattering properties insufficiently representative of the model output if the microphysics parameterization scheme particle size distribution mismatches that assumed in constructing the LUT, such as one being exponential and the other monodisperse, or assuming different particle bulk densities. The CRTM also assigns a 5-μm effective radius to all non-precipitating clouds, an additional inconsistency. Brightness temperatures are calculated from 3-hour convection-permitting simulations of Hurricane Karl (2010) by the Weather Research and Forecasting model; each simulation uses one of three different microphysics schemes. For each microphysics scheme, a consistent cloud scattering LUT is constructed; the use of these LUTs produces differences in brightness temperature fields that would be better for analyzing and constraining microphysics schemes than using the CRTM LUT as-released. Other LUTs are constructed which contain one of the known microphysics-inconsistencies with the CRTM LUT as-released, such as the bulk density of graupel, but are otherwise microphysics-consistent; differences in brightness temperature to using an entirely microphysics-consistent LUT further indicate the significance of that inconsistency. The CRTM LUT as-released produces higher brightness temperature than using microphysics-consistent LUTs. None of the LUTs can produce brightness temperatures that can match well to observations at all frequencies, which is likely due in part to the use of spherical particle scattering.

What Can We Conclude about the Real Aspect Ratios of Ice Particle Aggregates from Two-Dimensional Images?

AbstractA simple numerical experiment was performed to investigate the result published in many papers that measurements indicate that aggregates may be well represented as oblate spheroids with mean aspect ratio (semiminor axis to semimajor axis length) of 0.6. The aspect ratio measurements are derived from two-dimensional projections of complex three-dimensional aggregates. Here, aggregates were modeled as ellipsoids with semiprincipal axes of length a, b, and c, which include oblate spheroids (a = b) as a class, and the projected aspect ratios of large numbers of two-dimensional projections of them were sampled. When sampling oblate spheroids with aspect ratio 0.6 over random orientations, the mean projected aspect ratio is 0.746. A mean projected aspect ratio of 0.6 is obtained for an oblate spheroid with aspect ratio of 0.33. When sampling randomly oriented ellipsoids with semiminor axes (b, c) varying from 0.10 to 1.00 in steps of 0.01, representing many complex shapes, the mean projected aspect rat...

Multiple-kernel learning-based unmixing algorithm for estimation of cloud fractions with MODIS and CloudSat data

Detection of clouds in satellite-generated radiance images, including those from MODIS, is an important first step in many applications of these data. In this paper we apply spectral unmixing to this problem with the aim of estimating subpixel cloud fractions, as opposed to identification only of whether or not a pixel radiance contains cloud contributions. We formulate the spectral unmixing approach in terms of multiple-kernel learning (MKL). To this end we propose a MKL-based unmixing algorithm that drives a multiple-kernel description of cloud, enabling estimation of sub-pixel cloud fractions. This approach is based on supervised learning. We generate training and testing samples by using CloudSat and CALIPSO data to compute cloud fractions within individual MODIS pixels. Results of our study on limited data (1875 training and testing MODIS pixels along with their CloudSat and CALIPSO based sub-pixel cloud fractions) show that the proposed algorithm can effectively estimate sub-pixel MODIS cloud fraction and outperforms support vector machine (SVM) in terms of estimation performance.

Retrieving Cloud Ice Water Content Using Millimeter- and Centimeter-Wavelength Radar Polarimetric Observables

AbstractScattering properties of a large collection of pristine ice crystals at millimeter and centimeter wavelengths are calculated using the generalized multiparticle Mie method. Millimeter- and centimeter-wavelength radar observables are also calculated by employing particle size distributions (PSDs) that ensure the bulk properties (e.g., ice water content and total number concentration) fall within physically realistic ranges. The relationships between radar reflectivity Z and ice water content (IWC) are shown to be sensitive (from one to two orders of magnitude in variability) to the PSDs used and are thus not recommended for IWC retrievals. The relationships between IWC and specific differential phase KDP are less dependent on PSDs. Simple relationships between IWC and KDP at different radar elevation angles and wavelengths are given. If only the general crystal type is known (i.e., planar vs columnar), IWC retrieval errors based on KDP mostly fall within 30%. If more detailed ice crystal type is kn...