Abstract

Vertically pointing Ka-band radar measurements are used to derive fall velocity–reflectivity factor ( $V_t=a{Z}_e^b$ ) relations for frozen hydrometeor populations of different habits during snowfall events observed at Oliktok Point, Alaska, and at the Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC). Case study events range from snowfall with highly rimed particles observed during periods with large amounts of supercooled liquid water path (LWP > 320 g m⁻²) to unrimed snowflakes including instances when pristine planar crystals were the dominant frozen hydrometeor habit. The prefactor a and the exponent b in the observed V_t –Z_e relations scaled to the sea level vary in the approximate ranges 0.5–1.4 and 0.03–0.13, respectively (reflectivities are in mm⁶ m⁻³ and velocities are in m s⁻¹). The coefficient a values are the smallest for planar crystals (a ∼ 0.5) and the largest (a > 1.2) for particles under severe riming conditions with high LWP. There is no clear distinction between b values for high and low LWP conditions. The range of the observed V_t –Z_e relation coefficients is in general agreement with results of modeling using fall velocity–size (υ_t = αD^β ) relations for individual particles found in literature for hydrometeors of different habits, though there is significant variability in α and β coefficients from different studies even for a same particle habit. Correspondences among coefficients in the V_t –Z_e relations for particle populations and in the individual particle υ_t –D relations are analyzed. These correspondences and the observed V_t –Z_e relations can be used for evaluating different frozen hydrometeor fall velocity parameterizations in models.

Abstract

An approach is described to retrieve the total amount of ice in a vertical atmospheric column in precipitating clouds observed by the operational Weather Surveillance Radar-1988 Doppler (WSR-88D) systems. This amount expressed as ice water path (IWP) is retrieved using measurements obtained during standard WSR-88D scanning procedures performed when observing precipitation. WSR-88D-based IWP estimates are evaluated using dedicated cloud microphysical retrievals available from the CloudSat and auxiliary spaceborne measurements. The evaluation is performed using measurements obtained in extensive predominantly stratiform precipitation systems containing both ice hydrometeors aloft and rain near the ground. The analysis is based on retrievals of IWP from satellite and the ground-based KWGX and KSHV WSR-88D that are closely collocated in time and space. The comparison results indicate a relatively high correlation between satellite and WSR-88D IWP retrievals, with corresponding correlation coefficients of around 0.7. The mean relative differences between spaceborne and ground-based estimates are around 50%–60%, which is on the order of IWP retrieval uncertainties and is comparable to the differences among various operational CloudSat IWP products. The analysis performed in this study suggests that the quantitative information on ice content of precipitation systems can generally be obtained from operational WSR-88D measurements, when they perform routine scans to observe precipitation. The limitations of WSR-88D IWP estimates due to radar beam tilt restrictions and the overshooting effects due to Earth’s sphericity are discussed.

Abstract

Instantaneous liquid-equivalent snowfall rates S retrieved from CloudSat W-band cloud radar reflectivity Z _e measurements are compared to estimates of S from operational Weather Surveillance Radar-1988 Doppler (WSR-88D) systems when the CloudSat satellite overflew the ground-based radar sites during spatially extensive nimbostratus snowfall events. For these comparisons, the ground-based radar measurements are interpolated to closely match in space and time spaceborne radar resolution volumes above ground clutter, thus avoiding uncertainties in deriving near-surface snowfall rates from measurements aloft by both radar types. Although typical uncertainties of both ground-based and spaceborne snowfall-rate retrieval approaches are quite high, the results from the standard optimal estimation CloudSat 2C-SNOW-PROFILE algorithm are on average in good agreement with the WSR-88D default snowfall algorithm results with correlation coefficients being around 0.8–0.85. The CloudSat standard optimal estimation snowfall-rate products are also shown to be in satisfactory agreement with retrievals from several simple W-band Z _e –S relations suggested earlier. The snowfall rate and snow/ice water content (IWC) parameters from the CloudSat 2C-SNOW-PROFILE algorithm are highly interdependent. A tight relation between S and IWC is apparently introduced through the ice particle fall velocity assumption that is made in the reflectivity-based snowfall retrieval algorithm. This suggests that ice sedimentation rate estimates can also be deduced from applications of numerous empirical IWC–reflectivity relations derived previously for different cloud conditions when appropriate assumptions about fall velocities are made. Intercomparisons between different CloudSat snow/ice water content products indicated significant discrepancies in IWC values from different standard CloudSat retrieval algorithms.

Abstract

A Ka-band (~35 GHz) and W-band (~94 GHz) radar approach to retrieve profiles of characteristic raindrop sizes, such as mean mass-weighted drop diameters D _m , from measurements of the difference in the mean vertical Doppler velocities (DDV) is analyzed. This retrieval approach is insensitive to radar calibration errors, vertical air motions, and attenuation effects. The D _m –DDV relations are derived using long-term measurements of drop size distributions (DSDs) from different observational sites and do not assume a functional DSD shape. Unambiguous retrievals using this approach are shown to be available in the D _m range of approximately 0.5–2 mm, with average uncertainties of around 21%. Potential retrieval ambiguities occurring when larger drop populations exist can be avoided by using a Ka-band vertical Doppler velocity threshold. The performance of the retrievals is illustrated using a long predominantly stratiform rain event observed at the Atmospheric Radiation Measurement (ARM) Southern Great Plains site. An intercomparison of DDV-based estimates of characteristic raindrop sizes with independent estimates available from ground-based disdrometer measurements reveal good agreement, with a correlation coefficient of 0.88, and mean differences between radar and disdrometer-based D _m of approximately 14% for the entire range of unambiguous retrievals. The Ka–W-band DDV method to retrieve mean mass-weighted drop sizes is applicable to measurements from new dual-wavelength ARM cloud radars that are being deployed at a variety of observational facilities. An illustration for the retrievals at the Oliktok Point ARM facility is also given.

Abstract

Information on ice cloud particle nonsphericity is important for many practical applications ranging from modeling the cloud radiation impact to remote sensing of hydrometeor microphysical properties. Scanning cloud radars, which often measure depolarization ratio as a sole polarization variable, can provide a means for retrieving this information. The applicability of a spheroidal particle model (i.e., a regular ellipsoid that has two principal axes of the same length) is evaluated for describing depolarization properties of ice particles. It is shown that this simple model, which uses an aspect ratio as a single parameter characterizing particle nonsphericity, explains reasonably well the scatter of slant 45° linear depolarization ratio (SLDR) measurements versus direct estimates of the zenith direction backscatter enhancement observed during the Storm Peak Laboratory Cloud Property Validation Experiment (StormVEx) with the scanning W-band cloud radar (SWACR). Observed SLDR elevation angle patterns are also approximated reasonably well by this shape model. It is suggested that an SLDR difference between slant and zenith radar pointing can be used for prospective remote sensing methods of inferring particle aspect ratio from cloud radar depolarization measurements. Depending on mass–size relations, the value of this difference corresponding to median zenith reflectivity enhancement observed during StormVEx relates to aspect ratios of about 0.5 ± 0.2, which generally agrees with typical aspect ratios of ice particles. Expected aspect ratio retrieval uncertainties within the spheroidal shape model and the use of different types of radar depolarization ratio measurements are discussed. A correction for estimated zenith direction reflectivity enhancements due to particle nonsphericity is suggested.

Abstract

A dual-wavelength radar method to estimate snowfall rate has been developed. The method suggests taking simultaneous and collocated reflectivity measurements at two radar wavelengths. Snowfall backscattering at one of these wavelengths should be in the Rayleigh regime or sufficiently close to this regime, while backscattering at the other wavelength should be substantially outside this regime for typical snowflake sizes. Combinations of K_a-band (for a shorter wavelength) and X-, C-, or S-band (for a longer wavelength) radar measurements satisfy this requirement. The logarithmic difference between reflectivities at these two wavelengths provides an independent estimate of snowflake median size D _m , which exhibits a very low sensitivity to snowflake density and details of the size distribution. The estimates of D _m and radar reflectivities Z _e at the longer wavelength are then used to obtain snowfall rate R from the Z _e –R–D _m relationships, which have a snowflake effective density ρ _e as a “tuning” parameter. The independent information about snowflake characteristic size accounts for much of the improvement of the dual-wavelength method over traditional, single-parameter Z _e –R relationships.

The paper also presents experimental data collected during January–March 1996, near Boulder, Colorado, with the National Oceanic and Atmospheric Administration’s K_a- and X-band radars. The radar data were supplemented by simultaneous ground measurements of snow accumulation. Comparisons of the ground and dual-wavelength radar measurements indicate that a tuning value ρ _e of about 0.03–0.04 g cm⁻³ provides a good match with surface-observed snow accumulations. Differences in dual-wavelength radar estimates of accumulation for ρ _e between 0.03 and 0.04 g cm⁻³ are usually within 25%, while existing X-band, single-parameter Z _e –R relationships yield accumulations that differ by as much as a factor of 4.

Abstract

The remote sensing method for retrieving vertical profiles of microphysical parameters in ice clouds from ground-based measurements taken by the Doppler radar and IR radiometer was applied to several cloud cases observed during different field experiments including FIRE-II, ASTEX, and the Arizona Program. The measurements were performed with the NOAA Environmental Technology Laboratory instrumentation. The observed ice clouds were mostly cirrus clouds located in the upper troposphere above 5.6 km. Their geometrical thicknesses varied from a few hundred meters to 3 km. Characteristic cloud particle sizes expressed in median mass diameters of equal-volume spheres varied from about 25 μm to more than 400 μm. Typically, characteristic particle sizes were increasing toward the cloud base, with the exception of the lowest range gates where particles were quickly sublimating. Highest particle concentrations were usually observed near the cloud tops. The vertical variability of particle sizes inside an individual cloud could reach one order of magnitude. The standard deviation of the mean profile for a typical cloud is usually factor of 2 or 3 smaller than mean values of particle characteristic size. Typical values of retrieved cloud ice water content varied from 1 to 100 mg m⁻³; however, individual variations were as high as four orders of magnitude. There was no consistent pattern in the vertical distribution of ice water content except for the rapid decrease in the vicinity of the cloud base. The relationships between retrieved cloud parameters and measured radar reflectivities were considered. The uncertainty of estimating cloud parameters from the power-law regressions is discussed. The parameters of these regressions varied from cloud to cloud and were comparable to the parameters in corresponding regressions obtained from direct particle sampling in other experiments. Relationships between cloud microphysical parameters and reflectivity can vary even for the same observational case. The variability diminishes if stronger reflectivities are considered. A procedure of “tuning” cloud microphysics–reflectivity regressions for individual profiles is suggested. Such a procedure can simplify the radar–radiometer method and make it applicable for a broader range of clouds.

Abstract

A theoretical investigation of radar polarization parameters that characterize cloud ice backscattering is presented. The parameters considered were those commonly used in radar polarimetrics such as differential reflectivity (Z_DR), linear depolarization ratio (LDR), circular depolarization ratio (CDR), intrinsic degree of orientation (ORTT) as well as conventional reflectivities. Experimental data on the shapes of ice crystals and their orientations are taken into account. Results suggest that prolate-shaped scatterers can be distinguished from those having oblate shapes by analyzing the depolarization ratio dependence on the elevation angle. Calculations suggest that circular polarization parameters provide stronger signals in a cross-polar channel and also show a 1esser dependence on scatterer orientation in comparison with linear polarization parameters. Propagation effects do not significantly affect the polarization parameters for equivalent water contents and cloud thicknesses that are typical for cirrus clouds. Differential phase shift that might be observed in cirrus clouds is relatively small. Finally, equivalent reflectivity factors are analyzed for several ice particle types as a function of their major axis. Reflectivity dependence on particle shapes is demonstrated, and comments on the possibility of making approximate estimates of cloud particle sizes are given.

Abstract

The potential of CloudSat W-band radar for observing wintertime storms affecting the West Coast of North America is evaluated. Storms having high hydrological impact often result from landfalls of “atmospheric rivers” (“ARs”), which are the narrow elongated regions of water vapor transport from the tropics. CloudSat measurements are used for retrievals of rain rate R and cloud ice water path (IWP) along the satellite ground track over ocean and land. These retrievals present quasi-instantaneous vertical cross sections of precipitating systems with high-resolution information about hydrometeors. This information is valuable in coastal areas with complex terrain where observations with existing instrumentation, including ground-based radars, are limited. CloudSat reflectivity enhancements [i.e., bright band (BB)] present a way to estimate freezing levels, indicating transitions between rainfall and snowfall. CloudSat estimates of these levels were validated using data from radiosonde soundings and compared to model and microwave sounder data. Comparisons of CloudSat retrievals of rain rates with estimates from ground-based radars in the areas where measurements from these radars were available indicated an agreement within retrieval uncertainties, which were around 50%. The utility of CloudSat was illustrated for case studies of pronounced AR events at landfall and over ocean. Initial analysis of CloudSat crossings of ARs during the 2006/07 season were used for rainfall regime prevalence assessment. It indicated that stratiform rain, which often had BB features, warm rain, and mixed rain were observed with about 26%, 24%, and 50% frequency. Stratiform regions generally had higher rain rates. Significant correlation (~0.72) between mean values of IWP and rain rate was observed for stratiform rainfall.

Abstract

Empirical power-law relations between the equivalent radar reflectivity factor Z _e and the slope parameter of the gamma function Λ (i.e., Λ = c ; used to describe ice hydrometeor size distributions) are derived. The Λ parameter can also be considered as a size parameter since it is proportional to the inverse of the hydrometeor characteristic size, which is an important geophysical parameter describing the entire distribution. Two datasets from two-dimensional microphysical probes, collected during aircraft flights in subtropical and midlatitude regions, were used to obtain Λ by fitting measured size distributions. Reflectivity for different radar frequencies was calculated from microphysical probe data by using nonspherical-particle models. The derived relations have exponent d values that are approximately from −0.35 to −0.40, and the prefactors c are approximately between 30 and 55 (Λ: cm⁻¹; Z _e : mm⁶ m⁻³). There is a tendency for d and c to decrease when radar frequency increases from K_u band (~14 GHz) to W band (~94 GHz). Correlation coefficients between Z _e and Λ can be very high (~0.8), especially for lower frequencies. Such correlations are similar to those for empirical relations between reflectivity and ice water content (IWC), which are used in many modeling and remote sensing applications. Close correspondences of reflectivity to both Λ and IWC are due to a relatively high correlation between these two microphysical parameters. Expected uncertainties in estimating Λ from reflectivity could be as high as a factor of 2, although estimates at lower radar frequencies are more robust. Stratifying retrievals by temperature could result in relatively modest improvement of Λ estimates.