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- Author or Editor: Sergey Y. Matrosov x
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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
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 R–K 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 eh–R relation, 17%–22% for the K DP-based estimators (depending on the drop shape model), and about 20%–32% for different Z eh–Z 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.
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 R–K 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 eh–R relation, 17%–22% for the K DP-based estimators (depending on the drop shape model), and about 20%–32% for different Z eh–Z 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.
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.
Comparative Evaluation of Snowfall Retrievals from the CloudSat W-band Radar Using Ground-Based Weather RadarsAbstract
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.
Characteristic Raindrop Size Retrievals from Measurements of Differences in Vertical Doppler Velocities at Ka- and W-Band Radar FrequenciesAbstract
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
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.
Retrieving Mean Temperature of Atmospheric Liquid Water Layers Using Microwave Radiometer MeasurementsAbstract
A remote sensing method to retrieve the mean temperature of cloud liquid using ground-based microwave radiometer measurements is evaluated and tested by comparisons with direct cloud temperature information inferred from ceilometer cloud-base measurements and temperature profiles from radiosonde soundings. The method is based on the dependence of the ratio of cloud optical thicknesses at W-band (~90 GHz) and Ka-band (~30 GHz) frequencies on cloud liquid temperature. This ratio is obtained from total optical thicknesses inferred from radiometer measurements of brightness temperatures after accounting for the contributions from oxygen and water vapor. This accounting is done based on the radiometer-based retrievals of integrated water vapor amount and temperature and pressure measurements at the surface. The W–Ka-band ratio method is applied to the measurements from a three-channel (90, 31.4, and 23.8 GHz) microwave radiometer at the U.S. Department of Energy Atmospheric Radiation Measurement Mobile Facility at Oliktok Point, Alaska. The analyzed events span conditions from warm stratus clouds with temperatures above freezing to mixed-phase clouds with supercooled liquid water layers. Intercomparisons of radiometer-based cloud liquid temperature retrievals with estimates from collocated ceilometer and radiosonde measurements indicated on average a standard deviation of about 3.5°C between the two retrieval types in a wide range of cloud temperatures, from warm liquid clouds to mixed-phase clouds with supercooled liquid and liquid water paths greater than 50 g m−2. The three-channel microwave radiometer–based method has a broad applicability, since it requires neither the use of active sensors to locate the boundaries of liquid cloud layers nor information on the vertical profile of temperature.
Abstract
A remote sensing method to retrieve the mean temperature of cloud liquid using ground-based microwave radiometer measurements is evaluated and tested by comparisons with direct cloud temperature information inferred from ceilometer cloud-base measurements and temperature profiles from radiosonde soundings. The method is based on the dependence of the ratio of cloud optical thicknesses at W-band (~90 GHz) and Ka-band (~30 GHz) frequencies on cloud liquid temperature. This ratio is obtained from total optical thicknesses inferred from radiometer measurements of brightness temperatures after accounting for the contributions from oxygen and water vapor. This accounting is done based on the radiometer-based retrievals of integrated water vapor amount and temperature and pressure measurements at the surface. The W–Ka-band ratio method is applied to the measurements from a three-channel (90, 31.4, and 23.8 GHz) microwave radiometer at the U.S. Department of Energy Atmospheric Radiation Measurement Mobile Facility at Oliktok Point, Alaska. The analyzed events span conditions from warm stratus clouds with temperatures above freezing to mixed-phase clouds with supercooled liquid water layers. Intercomparisons of radiometer-based cloud liquid temperature retrievals with estimates from collocated ceilometer and radiosonde measurements indicated on average a standard deviation of about 3.5°C between the two retrieval types in a wide range of cloud temperatures, from warm liquid clouds to mixed-phase clouds with supercooled liquid and liquid water paths greater than 50 g m−2. The three-channel microwave radiometer–based method has a broad applicability, since it requires neither the use of active sensors to locate the boundaries of liquid cloud layers nor information on the vertical profile of temperature.
Abstract
An attenuation-based method to retrieve vertical profiles of rainfall rates from height derivatives/gradients of CloudSat nadir-pointing W-band reflectivity measurements is discussed. This method takes advantage of the high attenuation of W-band frequency signals in rain and the low variability of nonattenuated reflectivity due to strong non-Rayleigh scattering from rain drops. The retrieval uncertainties could reach 40%–50%. The suggested method is generally applicable to rainfall rates (R) in an approximate range from about 2–3 to about 20–25 mm h−1. Multiple scattering noticeably affects the gradients of CloudSat measurements for R values greater than about 5 mm h−1. To avoid a retrieval bias caused by multiple-scattering effects, a special correction for retrievals is introduced. For rainfall rates greater than about 25 mm h−1, the influence of multiple scattering gets overwhelming, and the retrievals become problematic, especially for rainfalls with higher freezing-level altitudes. The attenuation-based retrieval method was applied to experimental data from CloudSat covering the range of rainfall rates. CloudSat retrievals were compared to the rainfall estimates available from a National Weather Service ground-based scanning precipitation radar operating at S band. Comparisons between spaceborne and conventional radar rainfall retrievals were generally in good agreement and indicated the mutual consistency of both quantitative precipitation estimate types. The suggested CloudSat rainfall retrieval method is immune to the absolute calibration of the radar and to attenuation caused by the melting layer and snow regions. Since it does not require surface returns, it is applicable to measurements above both land and water surfaces.
Abstract
An attenuation-based method to retrieve vertical profiles of rainfall rates from height derivatives/gradients of CloudSat nadir-pointing W-band reflectivity measurements is discussed. This method takes advantage of the high attenuation of W-band frequency signals in rain and the low variability of nonattenuated reflectivity due to strong non-Rayleigh scattering from rain drops. The retrieval uncertainties could reach 40%–50%. The suggested method is generally applicable to rainfall rates (R) in an approximate range from about 2–3 to about 20–25 mm h−1. Multiple scattering noticeably affects the gradients of CloudSat measurements for R values greater than about 5 mm h−1. To avoid a retrieval bias caused by multiple-scattering effects, a special correction for retrievals is introduced. For rainfall rates greater than about 25 mm h−1, the influence of multiple scattering gets overwhelming, and the retrievals become problematic, especially for rainfalls with higher freezing-level altitudes. The attenuation-based retrieval method was applied to experimental data from CloudSat covering the range of rainfall rates. CloudSat retrievals were compared to the rainfall estimates available from a National Weather Service ground-based scanning precipitation radar operating at S band. Comparisons between spaceborne and conventional radar rainfall retrievals were generally in good agreement and indicated the mutual consistency of both quantitative precipitation estimate types. The suggested CloudSat rainfall retrieval method is immune to the absolute calibration of the radar and to attenuation caused by the melting layer and snow regions. Since it does not require surface returns, it is applicable to measurements above both land and water surfaces.
Abstract
Realistic aggregate snowflake models and experimental snowflake size distribution parameters are used to derive X-band power-law relations between the equivalent radar reflectivity factor Ze and the liquid equivalent snowfall precipitation rate S (Ze = ASB ). There is significant variability in coefficients of these relations caused by uncertainties in the snowflake bulk densities (as defined by the mass–size relationships), fall velocities, and particle size distribution parameters. The variability in snowflake parameters results in differing Ze –S relations that provide more than a factor of 2 difference in precipitation rate and liquid equivalent accumulation estimates for typical reflectivity values observed in snowfall (∼20–30 dBZ). Characteristic values of the exponent B in the derived for dry snowfall relations were generally in the range 1.3–1.55 (when Ze is in mm6 m−3 and S is in mm h−1). The coefficient A exhibited stronger variability and varied in the range from about 30 (for aircraft-based size distributions and smaller density particles) to about 140 (for surface-based size distributions). The non-Rayleigh scattering effects at X band result in diminishing of both A and B, as compared to the relations for longer wavelength radars. The snowflake shape and orientation also influences its backscatter properties, but to a lesser extent compared to the particle bulk density. The derived relations were primarily obtained for snowfall consisting of dry aggregate snowflakes. They were applied to the X-band radar measurements during observations of wintertime storms. For approximately collocated measurements, the in situ estimates of snowfall accumulations were generally within the range of radar-derived values when the coefficient A was around 100–120.
Abstract
Realistic aggregate snowflake models and experimental snowflake size distribution parameters are used to derive X-band power-law relations between the equivalent radar reflectivity factor Ze and the liquid equivalent snowfall precipitation rate S (Ze = ASB ). There is significant variability in coefficients of these relations caused by uncertainties in the snowflake bulk densities (as defined by the mass–size relationships), fall velocities, and particle size distribution parameters. The variability in snowflake parameters results in differing Ze –S relations that provide more than a factor of 2 difference in precipitation rate and liquid equivalent accumulation estimates for typical reflectivity values observed in snowfall (∼20–30 dBZ). Characteristic values of the exponent B in the derived for dry snowfall relations were generally in the range 1.3–1.55 (when Ze is in mm6 m−3 and S is in mm h−1). The coefficient A exhibited stronger variability and varied in the range from about 30 (for aircraft-based size distributions and smaller density particles) to about 140 (for surface-based size distributions). The non-Rayleigh scattering effects at X band result in diminishing of both A and B, as compared to the relations for longer wavelength radars. The snowflake shape and orientation also influences its backscatter properties, but to a lesser extent compared to the particle bulk density. The derived relations were primarily obtained for snowfall consisting of dry aggregate snowflakes. They were applied to the X-band radar measurements during observations of wintertime storms. For approximately collocated measurements, the in situ estimates of snowfall accumulations were generally within the range of radar-derived values when the coefficient A was around 100–120.
