331 research outputs found
Analysis of the microphysical properties of snowfall using scanning polarimetric and vertically pointing multi-frequency Doppler radars
No full textRadar dual-wavelength ratio (DWR) measurements from the Stony Brook Radar Observatory Ka-band scanning polarimetric radar (KASPR, 35 GHz), a W-band profiling radar (94 GHz), and a next-generation K-band (24 GHz) micro rain radar (MRRPro) were exploited for ice particle identification using triple-frequency approaches. The results indicated that two of the radar frequencies (K and Ka band) are not sufficiently separated; thus, the triple-frequency radar approaches had limited success. On the other hand, a joint analysis of DWR, mean Doppler velocity (MDV), and polarimetric radar variables indicated potential in identifying ice particle types and distinguishing among different ice growth processes and even in revealing additional microphysical details.
We investigated all DWR pairs in conjunction with MDV from the KASPR profiling measurements and differential reflectivity (ZDR) and specific differential phase (KDP) from the KASPR quasi-vertical profiles. The DWR-versus-MDV diagrams coupled with the polarimetric observables exhibited distinct separations of particle populations attributed to different rime degrees and particle growth processes. In fallstreaks, the 35–94 GHz DWR pair increased with the magnitude of MDV corresponding to the scattering calculations for aggregates with lower degrees of riming. The DWR values further increased at lower altitudes while ZDR slightly decreased, indicating further aggregation. Particle populations with higher rime degrees had a similar increase in DWR but a 1–1.5 m s−1 larger magnitude of MDV and rapid decreases in KDP and ZDR. The analysis also depicted the early stage of riming where ZDR increased with the MDV magnitude collocated with small increases in DWR. This approach will improve quantitative estimations of snow amount and microphysical quantities such as rime mass fraction. The study suggests that triple-frequency measurements are not always necessary for in-depth ice microphysical studies and that dual-frequency polarimetric and Doppler measurements can successfully be used to gain insights into ice hydrometeor microphysics
Influence of multiple scattering on CloudSat measurements in snow: A model study
No full textThe effects of multiple scattering on larger precipitating hydrometers have an influence on measurements of the spaceborne W-band (94 GHz) CloudSat radar. This study presents initial quantitative estimates of these effects in "dry" snow using radiative transfer calculations for appropriate snowfall models. It is shown that these effects become significant (i.e., greater than approximately 1 dB) when snowfall radar reflectivity factors are greater than about 10-15 dBZ. Reflectivity enhancement due to multiple scattering can reach 4-5 dB in heavier stratiform snowfalls. Multiple scattering effects counteract signal attenuation, so the observed CloudSat reflectivity factors in snowfall could be relatively close to the values that would be observed in the case of single scattering and the absence of attenuation. Copyright 2009 by the American Geophysical Union
Influence of multiple scattering on CloudSat measurements in snow: A model
No full text[1] The effects of multiple scattering on larger precipitating hydrometers have an influence on measurements of the spaceborne W-band (94 GHz) CloudSat radar. This study presents initial quantitative estimates of these effects in ''dry'' snow using radiative transfer calculations for appropriate snowfall models. It is shown that these effects become significant (i.e., greater than approximately 1 dB) when snowfall radar reflectivity factors are greater than about 10 -15 dBZ. Reflectivity enhancement due to multiple scattering can reach 4 -5 dB in heavier stratiform snowfalls. Multiple scattering effects counteract signal attenuation, so the observed CloudSat reflectivity factors in snowfall could be relatively close to the values that would be observed in the case of single scattering and the absence of attenuation. Citation: Matrosov, S. Y., and A. Battaglia (2009), Influence of multiple scattering on CloudSat measurements in snow: A model study, Geophys. Res. Lett., 36, L12806
Statistical Relations among Solid Precipitation, Atmospheric Moisture and Cloud Parameters in the Arctic
No full textObservations collected during cold-season precipitation periods at Utquagvik, Alaska and at the multidisciplinary drifting observatory for the study of Arctic climate (MOSAiC) are used to statistically analyze the relations among the atmospheric water cycle parameters including the columnar supercooled liquid and ice amounts (expressed as liquid-water and ice-water paths, i.e., LWP and IWP), the integrated water vapor (IWV) and the near-surface snowfall rate. Data come from radar and radiometer-based retrievals and from optical precipitation sensors. While the correlation between snowfall rate and LWP is rather weak, correlation coefficients between radar-derived snowfall rate and IWP are high (~0.8), which is explained, in part, by the generally low LWP/IWP ratios during significant precipitation. Correlation coefficients between snowfall rate and IWV are moderate (~0.45). Correlations are generally weaker if snowfall is estimated by optical sensors, which is, in part, due to blowing snow. Correlation coefficients between near-surface temperature and snowfall rates are low (r < 0.3). The results from the Alaska and MOSAiC sites are generally similar. These results are not very sensitive to the amount of time averaging (e.g., 15 min averaging versus daily averages). Observationally based relations among the water cycle parameters are informative about atmospheric moisture conversion processes and can be used for model evaluations
Ice Hydrometeor Shape Estimations Using Polarimetric Operational and Research Radar Measurements
No full textA polarimetric radar method to estimate mean shapes of ice hydrometeors was applied to several snowfall and ice cloud events observed by operational and research weather radars. The hydrometeor shape information is described in terms of their aspect ratios, r, which represent the ratio of particle minor and major dimensions. The method is based on the relations between depolarization ratio (DR) estimates and aspect ratios. DR values, which are a proxy for circular depolarization ratio, were reconstructed from radar variables of reflectivity factor, Ze, differential reflectivity, ZDR, and copolar correlation coefficient ρhv, which are available from radar systems operating in either simultaneous or alternate transmutation of horizontally and vertically polarized signals. DR-r relations were developed for retrieving aspect ratios and their sensitivity to different assumptions and model uncertainties were discussed. To account for changing particle bulk density, which is a major contributor to the retrieval uncertainty, an approach is suggested to tune the DR-r relations using reflectivity-based estimates of characteristic hydrometeor size. The analyzed events include moderate snowfall observed by an operational S-band weather radar and a precipitating ice cloud observed by a scanning Ka-band cloud radar at an Arctic location. Uncertainties of the retrievals are discussed
Distinguishing between Warm and Stratiform Rain Using Polarimetric Radar Measurements
No full textModeled statistical differential reflectivity–reflectivity (i.e., ZDR–Ze) correspondences for no bright-band warm rain and stratiform bright-band rain are evaluated using measurements from an operational polarimetric weather radar and independent information about rain types from a vertically pointing profiler. It is shown that these relations generally fit observational data satisfactorily. Due to a relative abundance of smaller drops, ZDR values for warm rain are, on average, smaller than those for stratiform rain of the same reflectivity by a factor of about two (in the logarithmic scale). A ZDR–Ze relation, representing a mean of such relations for warm and stratiform rains, can be utilized to distinguish between warm and stratiform rain types using polarimetric radar measurements. When a mean offset of observational ZDR data is accounted for and reflectivities are greater than 16 dBZ, about 70% of stratiform rains and approximately similar amounts of warm rains are classified correctly using the mean ZDR–Ze relation when applied to averaged data. Since rain rate estimators for warm rain are quite different from other common rain types, identifying and treating warm rain as a separate precipitation category can lead to better quantitative precipitation estimations
Microphysical properties of the November 26 cirrus cloud retrieved by Doppler radar/IR radiometer technique
No full textGaining information about cirrus cloud microphysics requires development of remote sensing techniques. In an earlier paper. Matrosov et al. (1992) proposed a method to estimate ice water path (IWP) (i.e., vertically integrated ice mass content IMC) and characteristic particle size averaged through the cloud from combined groundbased measurements of radar reflectivities and IR brightness temperatures of the downwelling thermal radiation in the transparency region of 10-12 mu m. For some applications, the vertically averaged characteristic particle sizes and IWP could be the appropriate information to use. However, vertical profiles of cloud microphysical parameters can provide a better understanding of cloud structure and development. Here we describe a further development of the previous method by Matrosov et al. (1992) for retrieving vertical profiles of cirrus particle sizes and IMC rather than their vertically averaged values. In addition to measurements of radar reflectivities, the measurements of Doppler velocities are used in the new method. This provides us with two vertical profiles of measurements to infer two vertical profiles of unknowns, i.e., particle characteristic sizes and IMC. Simultaneous measurements of the IR brightness temperatures are still needed to resolve an ambiguity in particle size-fall velocity relationships
Polarimetric Radar–Based Estimates of Spatial Variability in Characteristic Sizes of Raindrops in Stratiform Rainfall
No full textAbstractPolarimetric X-band radar measurements of differential reflectivity ZDR in stratiform rainfall were used for retrieving mean mass-weighted raindrop diameters Dm and estimating their spatial variability δDm at different scales. The ZDR data were calibrated and corrected for differential attenuation. The results revealed greater variability in Dm for larger spatial scales. Mean values of δDm were respectively around 0.32–0.34, 0.28–0.30, and 0.24–0.26 mm at scales of 20, 10, and 4.5 km, which are representative of footprints of various spaceborne sensors. For a given spatial scale, δDm decreases when the mean value of Dm increases. At the 20-km scale the decreasing trend exhibits a factor-of-1.7 decrease of δDm when the average Dm changes from 1 to 2 mm. Estimation data suggest that this trend diminishes as the spatial scale decreases. Measurement noise and other uncertainties preclude accurate estimations of Dm variability at smaller spatial scales because for many data points estimated variability values are equal to or less than the expected retrieval errors. Even though they are important for retrievals of absolute values of Dm, the details of the drop shape–size relation did not significantly affect estimates of size spatial variability. The polarization cross coupling in simultaneous transmission–simultaneous receiving measurement mode presents another limiting factor for accurate estimations of Dm. This factor, however, was not too severe in estimations of the size variability. There are indications that tuning the differential attenuation correction scheme might balance off some possible cross-coupling ZDR bias if differential phase accumulation is less than approximately 40°.</jats:p
CloudSat Studies of Stratiform Precipitation Systems Observed in the Vicinity of the Southern Great Plains Atmospheric Radiation Measurement Site
No full textAbstract
The spaceborne W-band (94 GHz) radar on board the CloudSat polar-orbiting satellite offers new opportunities for retrieving parameters of precipitating cloud systems. CloudSat measurements can resolve the vertical cross sections of such systems. The radar brightband features, which are commonly present when observing stratiform precipitating systems, allow the vertical separation of the ice, mixed, and liquid precipitating hydrometeor layers. In this study, the CloudSat data are used to simultaneously retrieve ice water path (IWP) values for ice layers of precipitating systems using absolute radar reflectivity measurements and mean rainfall rates Rm in the liquid hydrometeor layers using the attenuation-based reflectivity gradient method. The retrievals were performed for precipitating events observed in the vicinity of the Southern Great Plains (SGP) Atmospheric Radiation Measurement Program (ARM) Climate Research Facility. The retrieval results indicated that IWP values in stratiform precipitating systems vary from a few hundreds up to about 10 thousands of grams per meter squared, and the mean rain rates were in a general range between 0.5 and about 12 mm h−1. On average, mean rainfall increases with an increase in ice mass observed above the melting layer; the corresponding mean correlation coefficient is about 0.35, although events with higher correlation as well as those with no appreciable correlation were observed. Horizontal advection, wind shear, and vertical air motions might be some of the reasons for decorrelation between IWP and Rm retrieved for the same vertical atmospheric column. A mean statistical relation between IWP and Rm derived from CloudSat retrievals is in good agreement with the data obtained from multiwavelength ground-based cloud radar measurements at the SGP site.</jats:p
Observations of Wintertime U.S. West Coast Precipitating Systems with W-Band Satellite Radar and Other Spaceborne Instruments
No full textAbstract
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.</jats:p
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