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Sergey Y. Matrosov

Abstract

An approach is suggested to retrieve low-resolution rainfall rate profiles and layer-averaged rainfall rates, R a, from radar reflectivity measurements made by vertically pointing Ka-band radars. This approach is based on the effects of attenuation of radar signals in rain and takes advantage of the nearly linear relation between specific attenuation and rainfall rate at Ka-band frequencies. The variability of this relation due to temperature, details of raindrop size distributions, and the nature of rain (convective versus stratiform) is rather small (∼10%) and contributes little to errors in rainfall rate retrievals. The main contribution to the retrieval errors comes from the uncertainty of the difference in the nonattenuated radar reflectivities in the beginning and the end of the range resolution interval. For 2- and 1-dB uncertainties in this difference, the retrieval errors due to this main contribution are less than 34% and 17%, correspondingly, for rains with R a ≈ 10 mm h−1 at a 1-km resolution interval. The heavier rain rates are retrieved with a better accuracy since this retrieval error contribution is proportional to 1/R a. The retrieval accuracy can also be improved but at the expense of more coarse vertical resolutions of retrievals since the main retrieval error contribution is also proportional to the reciprocal of the resolution interval. The Mie scattering effects at Ka band results in less variability in nonattenuated reflectivities (cf. lower radar frequencies), which aids the suggested approach. Given that radar receivers are not saturated, the rainfall rates can be retrieved using cloud radars that were originally designed for measuring only nonprecipitating and weakly precipitating clouds. An important advantage of the attenuation-based retrievals of rainfall is that absolute radar calibration is not required. The inclusion of rainfall information will improve the characterization of the atmospheric column obtained with such radars used for climate research. The applications of the suggested approach are illustrated using the vertically pointing Ka-band radar measurements made during a field experiment in southern Florida. The retrieval results are in good agreement with surface estimates of rainfall rates.

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Sergey Y. Matrosov

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.

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Sergey Y. Matrosov

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 Ka-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 eR–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 eR relationships.

The paper also presents experimental data collected during January–March 1996, near Boulder, Colorado, with the National Oceanic and Atmospheric Administration’s Ka- 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 eR relationships yield accumulations that differ by as much as a factor of 4.

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Sergey Y. Matrosov

Abstract

Different relations between rainfall rate R and polarimetric X-band radar measurables were evaluated using the radar, disdrometer, and rain gauge measurements conducted during the 4-month-long field experiment. The specific differential phase shift K DP–based estimators generally show less scatter resulting from variability in raindrop size distributions than with the power-based relations. These estimators depend on model assumptions about the drop aspect ratios and are not applicable for lighter rainfalls. The polynomial approximation for the mean drop aspect ratio provides RK DP relations that result overall in good agreement between the radar retrievals of rainfall accumulations and estimates from surface rain gauges. The accumulation data obtained from power estimators that use reflectivity Z eh and differential reflectivity Z DR measurements generally exhibit greater standard deviations with respect to the gauge measurements. Unlike the phase-based estimators, the power-based estimators have an advantage of being “point” measurements, thus providing continuous quantitative precipitation estimation (QPE) for the whole area of radar coverage. The uncertainty in the drop shape model can result in errors in the attenuation and differential attenuation correction procedures. These errors might provide biases of radar-derived QPE for the estimators that use power measurements. Overall, for all considered estimators, the radar-based total rainfall accumulations showed biases less than 10% (relative to gauges). The standard deviations of radar retrievals were about 23% for the mean Z ehR relation, 17%–22% for the K DP-based estimators (depending on the drop shape model), and about 20%–32% for different Z ehZ DR-based estimators. Comparing Z DR-based retrievals of mean mass raindrop size Dm (for Dm > 1 mm) with disdrometer-derived values reveals an about 20%–25% relative standard deviation between these two types of estimates.

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Sergey Y. Matrosov

Abstract

Polarimetric X-band radar measurements of differential reflectivity Z DR in stratiform rainfall were used for retrieving mean mass-weighted raindrop diameters Dm and estimating their spatial variability δDm at different scales. The Z DR 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 Z DR bias if differential phase accumulation is less than approximately 40°.

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Sergey Y. Matrosov

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.

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Sergey Y. Matrosov

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.

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Sergey Y. Matrosov

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.

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Sergey Y. Matrosov

Abstract

Experimental retrievals of rain rates using the CloudSat spaceborne 94-GHz radar reflectivity gradient method over land were evaluated by comparing them with standard estimates from ground-based operational S-band radar measurements, which are widely used for quantitative precipitation estimations. The comparisons were performed for predominantly stratiform precipitation events that occurred in the vicinity of the Weather Surveillance Radar-1988 Doppler (WSR-88D) KGWX and KSHV radars during the CloudSat overpasses in the vicinity of these ground radar sites. The standard reflectivity-based WSR-88D rain-rate retrievals used in operational practice were utilized as a reference for the CloudSat retrieval evaluation. Spaceborne and ground-based radar rain-rate estimates that were closely collocated in space and time were generally well correlated. The correlation coefficients were approximately 0.65 on average, and the mean relative biases were usually within ±35% for the whole dataset and for individual events with typical rain rates exceeding ~2 mm h−1. For events with lighter rainfall, higher biases and lower correlations were often present. The normalized mean absolute differences between satellite- and ground-based radar retrievals were on average ~60%, with an increasing trend for lighter rainfall. Such mean differences are comparable to combined retrieval errors from both ground-based and satellite radar remote sensing approaches. Evaluation of potential effects of partial beam blockage on the ground-based radar measurements was performed, and the influence of the choice of relation between WSR-88D reflectivity and rain rate that was utilized in the ground-based rain-rate retrievals was assessed.

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Sergey Y. Matrosov

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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 (ZDR), 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.

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