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- Author or Editor: Sergey Y. Matrosov x
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Abstract
Narrow elongated regions of moisture transport known as atmospheric rivers (ARs), which affect the West Coast of North America, were simultaneously observed over the eastern North Pacific Ocean by the polar-orbiting CloudSat and Aqua satellites. The presence, location, and extent of precipitation regions associated with ARs and their properties were retrieved from measurements taken at 265 satellite crossings of AR formations during the three consecutive cool seasons of the 2006–09 period. Novel independent retrievals of AR mean rain rate, precipitation regime types, and precipitation ice region properties from satellite measurements were performed. Relations between widths of precipitation bands and AR thicknesses (as defined by the integrated water vapor threshold of 20 mm) were quantified. Precipitation regime partitioning indicated that “cold” precipitation with a significant amount of melting precipitating ice and “warm” rainfall conditions with limited or no ice in the atmospheric column were observed, on average, with similar frequencies, though the cold rainfall fraction had an increasing trend as AR temperature decreased. Rain rates were generally higher for the cold precipitation regime. Precipitating ice cloud and rainfall retrievals indicated a significant correlation between the total ice amounts and the resultant rain rate. Observationally based statistical relations were derived between the boundaries of AR precipitation regions and integrated water vapor amounts and between the total content of precipitating ice and rain rate. No statistically significant differences of AR properties were found for three different cool seasons, which were characterized by differing phases of El Niño–Southern Oscillation.
Abstract
Narrow elongated regions of moisture transport known as atmospheric rivers (ARs), which affect the West Coast of North America, were simultaneously observed over the eastern North Pacific Ocean by the polar-orbiting CloudSat and Aqua satellites. The presence, location, and extent of precipitation regions associated with ARs and their properties were retrieved from measurements taken at 265 satellite crossings of AR formations during the three consecutive cool seasons of the 2006–09 period. Novel independent retrievals of AR mean rain rate, precipitation regime types, and precipitation ice region properties from satellite measurements were performed. Relations between widths of precipitation bands and AR thicknesses (as defined by the integrated water vapor threshold of 20 mm) were quantified. Precipitation regime partitioning indicated that “cold” precipitation with a significant amount of melting precipitating ice and “warm” rainfall conditions with limited or no ice in the atmospheric column were observed, on average, with similar frequencies, though the cold rainfall fraction had an increasing trend as AR temperature decreased. Rain rates were generally higher for the cold precipitation regime. Precipitating ice cloud and rainfall retrievals indicated a significant correlation between the total ice amounts and the resultant rain rate. Observationally based statistical relations were derived between the boundaries of AR precipitation regions and integrated water vapor amounts and between the total content of precipitating ice and rain rate. No statistically significant differences of AR properties were found for three different cool seasons, which were characterized by differing phases of El Niño–Southern Oscillation.
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.
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.
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
Ground-based vertically pointing and airborne/spaceborne nadir-pointing millimeter-wavelength radars are being increasingly used worldwide. Though such radars are primarily designed for cloud remote sensing, they can also be used for precipitation measurements including snowfall estimates. In this study, modeling of snowfall radar properties is performed for the common frequencies of millimeter-wavelength radars such as those used by the U.S. Department of Energy’s Atmospheric Radiation Measurement Program (Ka and W bands) and the CloudSat mission (W band). Realistic snowflake models including aggregates and single dendrite crystals were used. The model input included appropriate mass–size and terminal fall velocity–size relations and snowflake orientation and shape assumptions. It was shown that unlike in the Rayleigh scattering regime, which is often applicable for longer radar wavelengths, the spherical model does not generally satisfactorily describe scattering of larger snowflakes at millimeter wavelengths. This is especially true when, due to aerodynamic forcing, these snowflakes are oriented primarily with their major dimensions in the horizontal plane and the zenith/nadir radar pointing geometry is used. As a result of modeling using the experimental snowflake size distributions, radar reflectivity–liquid equivalent snowfall rates (Z e–S) relations are suggested for “dry” snowfalls that consist of mostly unrimed snowflakes containing negligible amounts of liquid water. Owing to uncertainties in the model assumptions, these relations, which are derived for the common Ka- and W-band radar frequencies, have significant variability in their coefficients that can exceed a factor of 2 or so. Modeling snowfall attenuation suggests that the attenuation effects in “dry” snowfall can be neglected at the Ka band for most practical cases, while at the W band attenuation may need to be accounted for in heavier snowfalls observed at longer ranges.
Abstract
Ground-based vertically pointing and airborne/spaceborne nadir-pointing millimeter-wavelength radars are being increasingly used worldwide. Though such radars are primarily designed for cloud remote sensing, they can also be used for precipitation measurements including snowfall estimates. In this study, modeling of snowfall radar properties is performed for the common frequencies of millimeter-wavelength radars such as those used by the U.S. Department of Energy’s Atmospheric Radiation Measurement Program (Ka and W bands) and the CloudSat mission (W band). Realistic snowflake models including aggregates and single dendrite crystals were used. The model input included appropriate mass–size and terminal fall velocity–size relations and snowflake orientation and shape assumptions. It was shown that unlike in the Rayleigh scattering regime, which is often applicable for longer radar wavelengths, the spherical model does not generally satisfactorily describe scattering of larger snowflakes at millimeter wavelengths. This is especially true when, due to aerodynamic forcing, these snowflakes are oriented primarily with their major dimensions in the horizontal plane and the zenith/nadir radar pointing geometry is used. As a result of modeling using the experimental snowflake size distributions, radar reflectivity–liquid equivalent snowfall rates (Z e–S) relations are suggested for “dry” snowfalls that consist of mostly unrimed snowflakes containing negligible amounts of liquid water. Owing to uncertainties in the model assumptions, these relations, which are derived for the common Ka- and W-band radar frequencies, have significant variability in their coefficients that can exceed a factor of 2 or so. Modeling snowfall attenuation suggests that the attenuation effects in “dry” snowfall can be neglected at the Ka band for most practical cases, while at the W band attenuation may need to be accounted for in heavier snowfalls observed at longer ranges.
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
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
An approach is described to retrieve the total amount of ice in a vertical atmospheric column in precipitating clouds observed by the operational Weather Surveillance Radar-1988 Doppler (WSR-88D) systems. This amount expressed as ice water path (IWP) is retrieved using measurements obtained during standard WSR-88D scanning procedures performed when observing precipitation. WSR-88D-based IWP estimates are evaluated using dedicated cloud microphysical retrievals available from the CloudSat and auxiliary spaceborne measurements. The evaluation is performed using measurements obtained in extensive predominantly stratiform precipitation systems containing both ice hydrometeors aloft and rain near the ground. The analysis is based on retrievals of IWP from satellite and the ground-based KWGX and KSHV WSR-88D that are closely collocated in time and space. The comparison results indicate a relatively high correlation between satellite and WSR-88D IWP retrievals, with corresponding correlation coefficients of around 0.7. The mean relative differences between spaceborne and ground-based estimates are around 50%–60%, which is on the order of IWP retrieval uncertainties and is comparable to the differences among various operational CloudSat IWP products. The analysis performed in this study suggests that the quantitative information on ice content of precipitation systems can generally be obtained from operational WSR-88D measurements, when they perform routine scans to observe precipitation. The limitations of WSR-88D IWP estimates due to radar beam tilt restrictions and the overshooting effects due to Earth’s sphericity are discussed.
Abstract
An approach is described to retrieve the total amount of ice in a vertical atmospheric column in precipitating clouds observed by the operational Weather Surveillance Radar-1988 Doppler (WSR-88D) systems. This amount expressed as ice water path (IWP) is retrieved using measurements obtained during standard WSR-88D scanning procedures performed when observing precipitation. WSR-88D-based IWP estimates are evaluated using dedicated cloud microphysical retrievals available from the CloudSat and auxiliary spaceborne measurements. The evaluation is performed using measurements obtained in extensive predominantly stratiform precipitation systems containing both ice hydrometeors aloft and rain near the ground. The analysis is based on retrievals of IWP from satellite and the ground-based KWGX and KSHV WSR-88D that are closely collocated in time and space. The comparison results indicate a relatively high correlation between satellite and WSR-88D IWP retrievals, with corresponding correlation coefficients of around 0.7. The mean relative differences between spaceborne and ground-based estimates are around 50%–60%, which is on the order of IWP retrieval uncertainties and is comparable to the differences among various operational CloudSat IWP products. The analysis performed in this study suggests that the quantitative information on ice content of precipitation systems can generally be obtained from operational WSR-88D measurements, when they perform routine scans to observe precipitation. The limitations of WSR-88D IWP estimates due to radar beam tilt restrictions and the overshooting effects due to Earth’s sphericity are discussed.
Abstract
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.
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.
