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- Author or Editor: Sergey Y. Matrosov x
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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
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 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 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 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 e –R relationships yield accumulations that differ by as much as a factor of 4.
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 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 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 e –R relationships yield accumulations that differ by as much as a factor of 4.
Abstract
A method to retrieve total vertical amounts of cloud liquid and ice in stratiform precipitating systems is described. The retrievals use measurements from the vertically pointing Ka- and W-band cloud radars operated by the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Program and auxiliary measurements from a scanning National Weather Service radar and a ground-based disdrometer. Separation between the cloud liquid and rain is based on estimations of the total attenuation of millimeter-wavelength radar signals in the liquid hydrometeor layer. Disdrometer measurements are used for the retrieval constraints. Because the liquid phase hydrometeor retrievals use only differential measurements, they are immune to the absolute radar calibration uncertainties. Estimates of the ice cloud phase are performed using empirical relations between absolute radar reflectivity and ice water content. Data from the nearby scanning weather-service radar, which operates at a lower frequency, are used to correct cloud radar measurements observed above the freezing level for attenuation caused by the layers of liquid and melting hydrometeors and also by wet radomes of cloud radars. Polarimetric and vertical Doppler measurements from ARM cloud radars provide a distinct separation between regions of liquid and ice phases, and therefore the corresponding retrievals are performed in each region separately. The applicability of the suggested method is illustrated for a stratiform precipitation event observed at the ARM Southern Great Plains facility. Expected uncertainties for retrievals of cloud liquid water path are estimated at about 200–250 g m−2 for typical rainfall rates observed in stratiform systems (∼3–4 mm h−1). These uncertainties increase as rainfall rate increases. The ice water path retrieval uncertainties can be as high as a factor of 2.
Abstract
A method to retrieve total vertical amounts of cloud liquid and ice in stratiform precipitating systems is described. The retrievals use measurements from the vertically pointing Ka- and W-band cloud radars operated by the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) Program and auxiliary measurements from a scanning National Weather Service radar and a ground-based disdrometer. Separation between the cloud liquid and rain is based on estimations of the total attenuation of millimeter-wavelength radar signals in the liquid hydrometeor layer. Disdrometer measurements are used for the retrieval constraints. Because the liquid phase hydrometeor retrievals use only differential measurements, they are immune to the absolute radar calibration uncertainties. Estimates of the ice cloud phase are performed using empirical relations between absolute radar reflectivity and ice water content. Data from the nearby scanning weather-service radar, which operates at a lower frequency, are used to correct cloud radar measurements observed above the freezing level for attenuation caused by the layers of liquid and melting hydrometeors and also by wet radomes of cloud radars. Polarimetric and vertical Doppler measurements from ARM cloud radars provide a distinct separation between regions of liquid and ice phases, and therefore the corresponding retrievals are performed in each region separately. The applicability of the suggested method is illustrated for a stratiform precipitation event observed at the ARM Southern Great Plains facility. Expected uncertainties for retrievals of cloud liquid water path are estimated at about 200–250 g m−2 for typical rainfall rates observed in stratiform systems (∼3–4 mm h−1). These uncertainties increase as rainfall rate increases. The ice water path retrieval uncertainties can be as high as a factor of 2.
Abstract
Dual-frequency millimeter-wavelength radar observations in snowfall are analyzed in order to evaluate differences in conventional polarimetric radar variables such as differential reflectivity (Z DR) specific differential phase shift (K DP) and linear depolarization ratio (LDR) at traditional cloud radar frequencies at Ka and W bands (~35 and ~94 GHz, correspondingly). Low radar beam elevation (~5°) measurements were performed at Oliktok Point, Alaska, with a scanning fully polarimetric radar operating in the horizontal–vertical polarization basis. This radar has the same gate spacing and very close beam widths at both frequencies, which largely alleviates uncertainties associated with spatial and temporal data matching. It is shown that observed Ka- and W-band Z DR differences are, on average, less than about 0.5 dB and do not have a pronounced trend as a function of snowfall reflectivity. The observed Z DR differences agree well with modeling results obtained using integration over nonspherical ice particle size distributions. For higher signal-to-noise ratios, K DP data derived from differential phase measurements are approximately scaled as reciprocals of corresponding radar frequencies indicating that the influence of non-Rayleigh scattering effects on this variable is rather limited. This result is also in satisfactory agreement with data obtained by modeling using realistic particle size distributions. Observed Ka- and W-band LDR differences are strongly affected by the radar hardware system polarization “leak” and are generally less than 4 dB. Smaller differences are observed for higher depolarizations, where the polarization “leak” is less pronounced. Realistic assumptions about particle canting and the system polarization isolation lead to modeling results that satisfactorily agree with observational dual-frequency LDR data.
Abstract
Dual-frequency millimeter-wavelength radar observations in snowfall are analyzed in order to evaluate differences in conventional polarimetric radar variables such as differential reflectivity (Z DR) specific differential phase shift (K DP) and linear depolarization ratio (LDR) at traditional cloud radar frequencies at Ka and W bands (~35 and ~94 GHz, correspondingly). Low radar beam elevation (~5°) measurements were performed at Oliktok Point, Alaska, with a scanning fully polarimetric radar operating in the horizontal–vertical polarization basis. This radar has the same gate spacing and very close beam widths at both frequencies, which largely alleviates uncertainties associated with spatial and temporal data matching. It is shown that observed Ka- and W-band Z DR differences are, on average, less than about 0.5 dB and do not have a pronounced trend as a function of snowfall reflectivity. The observed Z DR differences agree well with modeling results obtained using integration over nonspherical ice particle size distributions. For higher signal-to-noise ratios, K DP data derived from differential phase measurements are approximately scaled as reciprocals of corresponding radar frequencies indicating that the influence of non-Rayleigh scattering effects on this variable is rather limited. This result is also in satisfactory agreement with data obtained by modeling using realistic particle size distributions. Observed Ka- and W-band LDR differences are strongly affected by the radar hardware system polarization “leak” and are generally less than 4 dB. Smaller differences are observed for higher depolarizations, where the polarization “leak” is less pronounced. Realistic assumptions about particle canting and the system polarization isolation lead to modeling results that satisfactorily agree with observational dual-frequency LDR data.
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
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
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
Circular depolarization ratio (CDR) is a polarimetric parameter, which, unlike linear depolarization ratio (LDR), does not exhibit significant dependence on hydrometeor orientation and can be used for particle type identification and shape estimation if propagation effects are small. The measurement scheme with simultaneous transmission and simultaneous reception (STSR) of horizontally and vertically polarized signals is widely used with research and operational radars. The STSR scheme does not provide direct measurements of depolarization. This study presents an estimator to obtain depolarization ratios from STSR complex voltages in radar receivers. This estimator provides true CDR if the phase shift on transmission, β, is equal to ±90° and the phase shift on reception, γ, equals −β. Even if these conditions are not satisfied, depolarization estimates are still possible if β + γ = 0° (though such estimates deviate slightly from true CDR varying between CDR and slant-45°LDR). The sum β + γ represents the initial differential phase shift offset and can be accounted for. The use of this depolarization estimator is illustrated with the data from the NOAA X-band radar. The measurements in ice clouds demonstrate the utility of near-CDR estimates to identify dendritic crystals and their gradual aggregation within the cloud. Illustrations are also given for near-CDR estimates in rain. An important advantage of depolarization estimates in the STSR mode is that these estimates are obtained from two “strong” channel returns. This greatly relaxes the radar sensitivity requirements compared to radar systems that utilize direct depolarization measurements as the power ratio of radar echoes measured in “strong” and “weak” receiving channels that represent two orthogonal polarizations.
Abstract
Circular depolarization ratio (CDR) is a polarimetric parameter, which, unlike linear depolarization ratio (LDR), does not exhibit significant dependence on hydrometeor orientation and can be used for particle type identification and shape estimation if propagation effects are small. The measurement scheme with simultaneous transmission and simultaneous reception (STSR) of horizontally and vertically polarized signals is widely used with research and operational radars. The STSR scheme does not provide direct measurements of depolarization. This study presents an estimator to obtain depolarization ratios from STSR complex voltages in radar receivers. This estimator provides true CDR if the phase shift on transmission, β, is equal to ±90° and the phase shift on reception, γ, equals −β. Even if these conditions are not satisfied, depolarization estimates are still possible if β + γ = 0° (though such estimates deviate slightly from true CDR varying between CDR and slant-45°LDR). The sum β + γ represents the initial differential phase shift offset and can be accounted for. The use of this depolarization estimator is illustrated with the data from the NOAA X-band radar. The measurements in ice clouds demonstrate the utility of near-CDR estimates to identify dendritic crystals and their gradual aggregation within the cloud. Illustrations are also given for near-CDR estimates in rain. An important advantage of depolarization estimates in the STSR mode is that these estimates are obtained from two “strong” channel returns. This greatly relaxes the radar sensitivity requirements compared to radar systems that utilize direct depolarization measurements as the power ratio of radar echoes measured in “strong” and “weak” receiving channels that represent two orthogonal polarizations.
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.
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.
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
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 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.
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 (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.