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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
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
The utility of X-band polarimetric radar to provide rainfall estimations with high spatial and temporal resolution in heavy convective precipitation in the presence of hail is explored. A case study involving observations of strong convective cells with a transportable polarimetric X-band radar near Boulder, Colorado, is presented. These cells produced rain–hail mixtures with a significant liquid fraction, causing local flash floods and debris flow in an environmentally sensitive burn area that had been previously affected by wildfire. It is demonstrated that the specific differential phase shift (K DP)–based rainfall estimator provided liquid accumulations that were in relatively good agreement with a network of high-density rain gauges and experimental disdrometers. This estimator was also able to capture the significant variability of accumulated rainfall in a relatively small area of interest, and the corresponding results were not significantly affected by hail. Hail presence, however, was a likely reason for significant overestimation of rainfall retrievals for X-band radar approaches that are based on radar-reflectivity Ze measurements that have been corrected for attenuation in rain. Even greater overestimations were observed with the S-band radar of the weather-service network. In part because of larger range distances, these radar data could not correctly reproduce the spatial variability of rainfall in the burn area.
Abstract
The utility of X-band polarimetric radar to provide rainfall estimations with high spatial and temporal resolution in heavy convective precipitation in the presence of hail is explored. A case study involving observations of strong convective cells with a transportable polarimetric X-band radar near Boulder, Colorado, is presented. These cells produced rain–hail mixtures with a significant liquid fraction, causing local flash floods and debris flow in an environmentally sensitive burn area that had been previously affected by wildfire. It is demonstrated that the specific differential phase shift (K DP)–based rainfall estimator provided liquid accumulations that were in relatively good agreement with a network of high-density rain gauges and experimental disdrometers. This estimator was also able to capture the significant variability of accumulated rainfall in a relatively small area of interest, and the corresponding results were not significantly affected by hail. Hail presence, however, was a likely reason for significant overestimation of rainfall retrievals for X-band radar approaches that are based on radar-reflectivity Ze measurements that have been corrected for attenuation in rain. Even greater overestimations were observed with the S-band radar of the weather-service network. In part because of larger range distances, these radar data could not correctly reproduce the spatial variability of rainfall in the burn area.
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
The influence of ice hydrometeor shape on the dual-wavelength ratio (DWR) of radar reflectivities at millimeter-wavelength frequencies is studied theoretically and on the basis of observations. Data from dual-frequency (Ka–W bands) radar show that, for vertically pointing measurements, DWR increasing trends with reflectivity Z e are very pronounced when Ka-band Z e is greater than about 0 dBZ and that DWR and Z e values are usually well correlated. This correlation is explained by strong relations between hydrometeor characteristic size and both of these radar variables. The observed DWR variability for a given level of reflectivity is as large as 8 dB, which is in part due to changes in mean hydrometeor shape as expressed in terms of the particle aspect ratio. Hydrometeors with a higher degree of nonsphericity exhibit lower DWR values when compared with quasi-spherical particles because of near-zenith reflectivity enhancements for particles outside the Rayleigh-scattering regime. When particle mass–size relations do not change significantly (e.g., for low-rime conditions), DWR can be used to differentiate between quasi-spherical and highly nonspherical hydrometeors because (for a given reflectivity value) DWR tends to increase as particles become more spherical. Another approach for differentiating among different degrees of nonsphericity for larger scatterers is based on analyzing DWR changes as a function of radar elevation angle. These changes are more pronounced for highly nonspherical particles and can exceed 10 dB. Measurements of snowfall spatiotemporally collocated with spaceborne CloudSat W-band radar and ground-based S-band operational weather radars also indicate that DWR values are generally smaller for ice hydrometeors with higher degrees of nonsphericity, which, for the same level of S-band reflectivity, exhibit greater differential reflectivity values.
Abstract
The influence of ice hydrometeor shape on the dual-wavelength ratio (DWR) of radar reflectivities at millimeter-wavelength frequencies is studied theoretically and on the basis of observations. Data from dual-frequency (Ka–W bands) radar show that, for vertically pointing measurements, DWR increasing trends with reflectivity Z e are very pronounced when Ka-band Z e is greater than about 0 dBZ and that DWR and Z e values are usually well correlated. This correlation is explained by strong relations between hydrometeor characteristic size and both of these radar variables. The observed DWR variability for a given level of reflectivity is as large as 8 dB, which is in part due to changes in mean hydrometeor shape as expressed in terms of the particle aspect ratio. Hydrometeors with a higher degree of nonsphericity exhibit lower DWR values when compared with quasi-spherical particles because of near-zenith reflectivity enhancements for particles outside the Rayleigh-scattering regime. When particle mass–size relations do not change significantly (e.g., for low-rime conditions), DWR can be used to differentiate between quasi-spherical and highly nonspherical hydrometeors because (for a given reflectivity value) DWR tends to increase as particles become more spherical. Another approach for differentiating among different degrees of nonsphericity for larger scatterers is based on analyzing DWR changes as a function of radar elevation angle. These changes are more pronounced for highly nonspherical particles and can exceed 10 dB. Measurements of snowfall spatiotemporally collocated with spaceborne CloudSat W-band radar and ground-based S-band operational weather radars also indicate that DWR values are generally smaller for ice hydrometeors with higher degrees of nonsphericity, which, for the same level of S-band reflectivity, exhibit greater differential reflectivity values.
Abstract
One of the challenges that limit the amount of information that can be inferred from radar measurements of ice and mixed-phase precipitating clouds is the variability in ice mass within hydrometeors. The variable amount of ice mass within particles of a given size drives further variability in single-scattering properties that results in uncertainties of forward-modeled remote sensing quantities. Nonspherical ice-phase hydrometeors are often approximated as spheroids to simplify the calculation of single-scattering properties, yet offline calculations remain necessary to quantify these radiative properties as a function of size in discrete increments. In this paper, a simple scaling of the Clausius–Mossotti factor is used that allows for an approximation of the scattering and extinction cross sections for an arbitrary mass–dimensional power-law relationship of a nonspherical particle given a single T-matrix calculation. Using data collected by the University of Wyoming King Air in snow clouds over the Colorado Park Range, the uncertainty in forward-modeled radar reflectivity to assumptions regarding mass–dimensional relationships is examined. This is accomplished by taking advantage of independently measured condensed mass and particle size distributions to estimate the variability of the prefactor in the mass–dimensional power law. Then, calculating the partial derivative of the radar backscatter cross sections using the scaling relationships, an estimate is made of the statistical uncertainty in forward-modeled radar reflectivity. Uncertainties on the order of 4 dB are found in this term for the dataset considered.
Abstract
One of the challenges that limit the amount of information that can be inferred from radar measurements of ice and mixed-phase precipitating clouds is the variability in ice mass within hydrometeors. The variable amount of ice mass within particles of a given size drives further variability in single-scattering properties that results in uncertainties of forward-modeled remote sensing quantities. Nonspherical ice-phase hydrometeors are often approximated as spheroids to simplify the calculation of single-scattering properties, yet offline calculations remain necessary to quantify these radiative properties as a function of size in discrete increments. In this paper, a simple scaling of the Clausius–Mossotti factor is used that allows for an approximation of the scattering and extinction cross sections for an arbitrary mass–dimensional power-law relationship of a nonspherical particle given a single T-matrix calculation. Using data collected by the University of Wyoming King Air in snow clouds over the Colorado Park Range, the uncertainty in forward-modeled radar reflectivity to assumptions regarding mass–dimensional relationships is examined. This is accomplished by taking advantage of independently measured condensed mass and particle size distributions to estimate the variability of the prefactor in the mass–dimensional power law. Then, calculating the partial derivative of the radar backscatter cross sections using the scaling relationships, an estimate is made of the statistical uncertainty in forward-modeled radar reflectivity. Uncertainties on the order of 4 dB are found in this term for the dataset considered.
Abstract
The performance of radar reflectivity (Z e )–based relations for retrievals of marine stratiform cloud liquid water content (LWC) is evaluated by comparing liquid water path (LWP) estimates from microwave radiometers with vertically integrated LWC values retrieved from radar measurements. Based on a measurement dataset from a research vessel in the tropical eastern Pacific Ocean, it is shown that reflectivity thresholding allows minimizing of the influence of drizzle drops present in marine stratiform clouds to the extent that LWP estimates from a ground-/shipborne radar can have uncertainties that might be acceptable for different applications. The accuracies of Z e -based retrievals depend on the thresholding level Z et, and they are generally better than a factor of 2 for Z et ≲ −15 dBZ. These accuracies typically improve when Z et is lowered; however, the amount of cloud profiles that pass thresholding diminishes as Z et is decreased from about 50% for a −15-dbZ threshold to only about 10% for a −25-dBZ threshold. Different thresholding strategies are considered. Ancillary information on cloud-base heights can improve LWP estimates from reflectivities. The ship-based dataset was used to simulate measurements from prospective 94-GHz spaceborne cloud radar (CloudSat). CloudSat measurements would, on average, detect about 75% of warm marine stratiform clouds, though many clouds with negligible presence of drizzle will be missed. Because of sensitivity and resolution issues for the spaceborne radar, reflectivity-based estimates of LWP are generally biased toward high values and have higher uncertainties when compared with the ground-based radar, for the same Z et.
Abstract
The performance of radar reflectivity (Z e )–based relations for retrievals of marine stratiform cloud liquid water content (LWC) is evaluated by comparing liquid water path (LWP) estimates from microwave radiometers with vertically integrated LWC values retrieved from radar measurements. Based on a measurement dataset from a research vessel in the tropical eastern Pacific Ocean, it is shown that reflectivity thresholding allows minimizing of the influence of drizzle drops present in marine stratiform clouds to the extent that LWP estimates from a ground-/shipborne radar can have uncertainties that might be acceptable for different applications. The accuracies of Z e -based retrievals depend on the thresholding level Z et, and they are generally better than a factor of 2 for Z et ≲ −15 dBZ. These accuracies typically improve when Z et is lowered; however, the amount of cloud profiles that pass thresholding diminishes as Z et is decreased from about 50% for a −15-dbZ threshold to only about 10% for a −25-dBZ threshold. Different thresholding strategies are considered. Ancillary information on cloud-base heights can improve LWP estimates from reflectivities. The ship-based dataset was used to simulate measurements from prospective 94-GHz spaceborne cloud radar (CloudSat). CloudSat measurements would, on average, detect about 75% of warm marine stratiform clouds, though many clouds with negligible presence of drizzle will be missed. Because of sensitivity and resolution issues for the spaceborne radar, reflectivity-based estimates of LWP are generally biased toward high values and have higher uncertainties when compared with the ground-based radar, for the same Z et.
Abstract
Single pristine planar ice crystals exhibit some flutter around their preferential horizontal orientation as they fall. This study presents estimates of flutter and analyzes predominant fall attitudes of pristine dendritic crystals observed with a polarization agile Ka-band cloud radar. The observations were made in weakly precipitating winter clouds on slopes of Mt. Washington, New Hampshire. The radar is capable of measuring the linear depolarization ratios in the standard horizontal–vertical polarization basis (HLDR) and the slant 45°–135° polarization basis (SLDR). Both HLDR and SLDR depend on crystal shape. HLDR also exhibits a strong dependence on crystal orientation, while SLDR depends only weakly on orientation. The different sensitivities of SLDR and HLDR to the shape and orientation effects are interpreted to estimate the angular flutter of crystals. A simple analytical expression is derived for the standard deviation of angular flutter as a function of the HLDR to SLDR ratio assuming perfect radar system characteristics. The flutter is also assessed by matching theoretical and observed depolarization patterns as a function of the elevation of the radar’s beam. The matching procedure is generally more robust since it accounts for the actual polarization states and imperfections in the radar hardware. The depolarization approach was used to estimate flutter of falling pristine dendrites that were characterized by Reynolds numbers in a range of approximately 40–100. Using the matching approach, this flutter was found to be about 9° ± 3°, as expressed by the standard deviation of the crystal minor axes from the vertical direction. The analytical expression provides a value of flutter of about 12°, which is at the high end of the estimate obtained by the matching procedure. The difference is explained by the imperfections in the polarization states and radar hardware, so the analytical result serves as an upper bound to the more robust result from matching. The values of flutter estimated from the experimental example are comparable to estimates for planar crystals obtained in laboratory models and by individual crystal sampling.
Abstract
Single pristine planar ice crystals exhibit some flutter around their preferential horizontal orientation as they fall. This study presents estimates of flutter and analyzes predominant fall attitudes of pristine dendritic crystals observed with a polarization agile Ka-band cloud radar. The observations were made in weakly precipitating winter clouds on slopes of Mt. Washington, New Hampshire. The radar is capable of measuring the linear depolarization ratios in the standard horizontal–vertical polarization basis (HLDR) and the slant 45°–135° polarization basis (SLDR). Both HLDR and SLDR depend on crystal shape. HLDR also exhibits a strong dependence on crystal orientation, while SLDR depends only weakly on orientation. The different sensitivities of SLDR and HLDR to the shape and orientation effects are interpreted to estimate the angular flutter of crystals. A simple analytical expression is derived for the standard deviation of angular flutter as a function of the HLDR to SLDR ratio assuming perfect radar system characteristics. The flutter is also assessed by matching theoretical and observed depolarization patterns as a function of the elevation of the radar’s beam. The matching procedure is generally more robust since it accounts for the actual polarization states and imperfections in the radar hardware. The depolarization approach was used to estimate flutter of falling pristine dendrites that were characterized by Reynolds numbers in a range of approximately 40–100. Using the matching approach, this flutter was found to be about 9° ± 3°, as expressed by the standard deviation of the crystal minor axes from the vertical direction. The analytical expression provides a value of flutter of about 12°, which is at the high end of the estimate obtained by the matching procedure. The difference is explained by the imperfections in the polarization states and radar hardware, so the analytical result serves as an upper bound to the more robust result from matching. The values of flutter estimated from the experimental example are comparable to estimates for planar crystals obtained in laboratory models and by individual crystal sampling.
Abstract
Arctic mixed-phase cloud macro- and microphysical properties are derived from a year of radar, lidar, microwave radiometer, and radiosonde observations made as part of the Surface Heat Budget of the Arctic Ocean (SHEBA) Program in the Beaufort Sea in 1997–98. Mixed-phase clouds occurred 41% of the time and were most frequent in the spring and fall transition seasons. These clouds often consisted of a shallow, cloud-top liquid layer from which ice particles formed and fell, although deep, multilayered mixed-phase cloud scenes were also observed. On average, individual cloud layers persisted for 12 h, while some mixed-phase cloud systems lasted for many days. Ninety percent of the observed mixed-phase clouds were 0.5–3 km thick, had a cloud base of 0–2 km, and resided at a temperature of −25° to −5°C. Under the assumption that the relatively large ice crystals dominate the radar signal, ice properties were retrieved from these clouds using radar reflectivity measurements. The annual average ice particle mean diameter, ice water content, and ice water path were 93 μm, 0.027 g m−3, and 42 g m−2, respectively. These values are all larger than those found in single-phase ice clouds at SHEBA. Vertically resolved cloud liquid properties were not retrieved; however, the annual average, microwave radiometer–derived liquid water path (LWP) in mixed-phase clouds was 61 g m−2. This value is larger than the average LWP observed in single-phase liquid clouds because the liquid water layers in the mixed-phase clouds tended to be thicker than those in all-liquid clouds. Although mixed-phase clouds were observed down to temperatures of about −40°C, the liquid fraction (ratio of LWP to total condensed water path) increased on average from zero at −24°C to one at −14°C. The observations show a range of ∼25°C at any given liquid fraction and a phase transition relationship that may change moderately with season.
Abstract
Arctic mixed-phase cloud macro- and microphysical properties are derived from a year of radar, lidar, microwave radiometer, and radiosonde observations made as part of the Surface Heat Budget of the Arctic Ocean (SHEBA) Program in the Beaufort Sea in 1997–98. Mixed-phase clouds occurred 41% of the time and were most frequent in the spring and fall transition seasons. These clouds often consisted of a shallow, cloud-top liquid layer from which ice particles formed and fell, although deep, multilayered mixed-phase cloud scenes were also observed. On average, individual cloud layers persisted for 12 h, while some mixed-phase cloud systems lasted for many days. Ninety percent of the observed mixed-phase clouds were 0.5–3 km thick, had a cloud base of 0–2 km, and resided at a temperature of −25° to −5°C. Under the assumption that the relatively large ice crystals dominate the radar signal, ice properties were retrieved from these clouds using radar reflectivity measurements. The annual average ice particle mean diameter, ice water content, and ice water path were 93 μm, 0.027 g m−3, and 42 g m−2, respectively. These values are all larger than those found in single-phase ice clouds at SHEBA. Vertically resolved cloud liquid properties were not retrieved; however, the annual average, microwave radiometer–derived liquid water path (LWP) in mixed-phase clouds was 61 g m−2. This value is larger than the average LWP observed in single-phase liquid clouds because the liquid water layers in the mixed-phase clouds tended to be thicker than those in all-liquid clouds. Although mixed-phase clouds were observed down to temperatures of about −40°C, the liquid fraction (ratio of LWP to total condensed water path) increased on average from zero at −24°C to one at −14°C. The observations show a range of ∼25°C at any given liquid fraction and a phase transition relationship that may change moderately with season.
Abstract
A polarimetric radar–based method for retrieving atmospheric ice particle shapes is applied to snowfall measurements by a scanning Ka-band radar deployed at Oliktok Point, Alaska (70.495°N, 149.883°W). The mean aspect ratio, which is defined by the hydrometeor minor-to-major dimension ratio for a spheroidal particle model, is retrieved as a particle shape parameter. The radar variables used for aspect ratio profile retrievals include reflectivity, differential reflectivity, and the copolar correlation coefficient. The retrievals indicate that hydrometeors with mean aspect ratios below 0.2–0.3 are usually present in regions with air temperatures warmer than approximately from −17° to −15°C, corresponding to a regime that has been shown to be favorable for growth of pristine ice crystals of planar habits. Radar reflectivities corresponding to the lowest mean aspect ratios are generally between −10 and 10 dBZ. For colder temperatures, mean aspect ratios are typically in a range between 0.3 and 0.8. There is a tendency for hydrometeor aspect ratios to increase as particles transition from altitudes in the temperature range from −17° to −15°C toward the ground. This increase is believed to result from aggregation and riming processes that cause particles to become more spherical and is associated with areas demonstrating differential reflectivity decreases with increasing reflectivity. Aspect ratio retrievals at the lowest altitudes are consistent with in situ measurements obtained using a surface-based multiangle snowflake camera. Pronounced gradients in particle aspect ratio profiles are observed at altitudes at which there is a change in the dominant hydrometeor species, as inferred by spectral measurements from a vertically pointing Doppler radar.
Abstract
A polarimetric radar–based method for retrieving atmospheric ice particle shapes is applied to snowfall measurements by a scanning Ka-band radar deployed at Oliktok Point, Alaska (70.495°N, 149.883°W). The mean aspect ratio, which is defined by the hydrometeor minor-to-major dimension ratio for a spheroidal particle model, is retrieved as a particle shape parameter. The radar variables used for aspect ratio profile retrievals include reflectivity, differential reflectivity, and the copolar correlation coefficient. The retrievals indicate that hydrometeors with mean aspect ratios below 0.2–0.3 are usually present in regions with air temperatures warmer than approximately from −17° to −15°C, corresponding to a regime that has been shown to be favorable for growth of pristine ice crystals of planar habits. Radar reflectivities corresponding to the lowest mean aspect ratios are generally between −10 and 10 dBZ. For colder temperatures, mean aspect ratios are typically in a range between 0.3 and 0.8. There is a tendency for hydrometeor aspect ratios to increase as particles transition from altitudes in the temperature range from −17° to −15°C toward the ground. This increase is believed to result from aggregation and riming processes that cause particles to become more spherical and is associated with areas demonstrating differential reflectivity decreases with increasing reflectivity. Aspect ratio retrievals at the lowest altitudes are consistent with in situ measurements obtained using a surface-based multiangle snowflake camera. Pronounced gradients in particle aspect ratio profiles are observed at altitudes at which there is a change in the dominant hydrometeor species, as inferred by spectral measurements from a vertically pointing Doppler radar.
Abstract
It is demonstrated that millimeter-wavelength radars that are designed primarily for cloud studies can be also used effectively for snowfall retrievals. Radar reflectivity–liquid equivalent snowfall rate (Ze–S) relations specifically tuned for Ka- and W-band radar frequencies are applied to measurements taken by vertically pointing ground-based 8-mm cloud radars (MMCR) that are designed for the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) Program and by the nadir-pointing spaceborne 94-GHz CloudSat radar. Comparisons of the MMCR-based snowfall accumulations estimated during experimental events with no significant snowflake riming and controlled gauge measurements indicated an 87% standard deviation between radar and gauge data that is consistent with the uncertainties in the coefficients of the Ze–S relations resulting from variability in snowflake microphysical properties. Comparisons of CloudSat-based snowfall-rate retrievals in heavy snowfall were consistent with estimates from surface S-band precipitation surveillance radars made using algorithms that were specifically designed for use with these radars. A typical difference between the CloudSat and the S-band precipitation radar estimates of snowfall rate for approximately collocated resolution pixels was within a factor of 2, which is of the order of the uncertainty of each estimate. The results of this study suggest that the ground-based and satellite-borne radars operating at Ka and W bands can provide valuable retrieval information on vertical profiles of snowfall, which is an important component of the global water cycle. This information is particularly important in Arctic regions where precipitation information from other sources is scarce.
Abstract
It is demonstrated that millimeter-wavelength radars that are designed primarily for cloud studies can be also used effectively for snowfall retrievals. Radar reflectivity–liquid equivalent snowfall rate (Ze–S) relations specifically tuned for Ka- and W-band radar frequencies are applied to measurements taken by vertically pointing ground-based 8-mm cloud radars (MMCR) that are designed for the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) Program and by the nadir-pointing spaceborne 94-GHz CloudSat radar. Comparisons of the MMCR-based snowfall accumulations estimated during experimental events with no significant snowflake riming and controlled gauge measurements indicated an 87% standard deviation between radar and gauge data that is consistent with the uncertainties in the coefficients of the Ze–S relations resulting from variability in snowflake microphysical properties. Comparisons of CloudSat-based snowfall-rate retrievals in heavy snowfall were consistent with estimates from surface S-band precipitation surveillance radars made using algorithms that were specifically designed for use with these radars. A typical difference between the CloudSat and the S-band precipitation radar estimates of snowfall rate for approximately collocated resolution pixels was within a factor of 2, which is of the order of the uncertainty of each estimate. The results of this study suggest that the ground-based and satellite-borne radars operating at Ka and W bands can provide valuable retrieval information on vertical profiles of snowfall, which is an important component of the global water cycle. This information is particularly important in Arctic regions where precipitation information from other sources is scarce.