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Abstract
The conversion of radar reflections into rain intensities is dependent upon assumptions regarding the drop size distribution. The gamma drop size distribution contains three unknown parameters; the number of parameters that can be obtained depends on the number of radar observables. When only the reflectivity is measured, one parameter is derived, combining it with the differential reflectivity results in the retrieval of two parameters, and when Doppler measurements are done as well, a third parameter is obtained. The Doppler spectrum may be distorted by turbulence; a correction procedure is developed. The combination of copolar and cross-polar radar measurements is used to estimate the canting-angle distribution. Analysis of data of the Delft atmospheric research radar during a moderate event shows that the three parameters of the gamma drop size distribution are statistically related. Combining these relationships results in an event-specific Z-R relationship.
Abstract
The conversion of radar reflections into rain intensities is dependent upon assumptions regarding the drop size distribution. The gamma drop size distribution contains three unknown parameters; the number of parameters that can be obtained depends on the number of radar observables. When only the reflectivity is measured, one parameter is derived, combining it with the differential reflectivity results in the retrieval of two parameters, and when Doppler measurements are done as well, a third parameter is obtained. The Doppler spectrum may be distorted by turbulence; a correction procedure is developed. The combination of copolar and cross-polar radar measurements is used to estimate the canting-angle distribution. Analysis of data of the Delft atmospheric research radar during a moderate event shows that the three parameters of the gamma drop size distribution are statistically related. Combining these relationships results in an event-specific Z-R relationship.
Abstract
A model for the radar reflectivity of boundary layer water clouds is constructed using cloud droplet spectra fitted to a truncated gamma distribution. The spectra were derived from several recent field experiments. Realistic space-based radar returns are simulated that take into account the pulse shape, digitization interval, averaging volume, and variations in droplet concentration, cloud depth, and cloud-top height. The results show that the long pulse length of the proposed radar is responsible for smearing out the real reflectivity spatially so that the space-based detected clouds occupy a volume far exceeding that of the “observed” cloud. However, the effect of smearing is reduced by the limited receiver sensitivity. Cloud volume of boundary layer clouds is overestimated by between 30% and 100% using proposed radar parameters. Even if clouds are detected, the radar reflectivity convoluted by the pulse shape is sufficiently different from the originally observed reflectivity to seriously impede the retrieval of accurate cloud liquid water content.
Abstract
A model for the radar reflectivity of boundary layer water clouds is constructed using cloud droplet spectra fitted to a truncated gamma distribution. The spectra were derived from several recent field experiments. Realistic space-based radar returns are simulated that take into account the pulse shape, digitization interval, averaging volume, and variations in droplet concentration, cloud depth, and cloud-top height. The results show that the long pulse length of the proposed radar is responsible for smearing out the real reflectivity spatially so that the space-based detected clouds occupy a volume far exceeding that of the “observed” cloud. However, the effect of smearing is reduced by the limited receiver sensitivity. Cloud volume of boundary layer clouds is overestimated by between 30% and 100% using proposed radar parameters. Even if clouds are detected, the radar reflectivity convoluted by the pulse shape is sufficiently different from the originally observed reflectivity to seriously impede the retrieval of accurate cloud liquid water content.
Abstract
A new method for retrieving air velocity fluctuations in the cloud-capped boundary layer (BL) using radar reflectivity and the Doppler velocity fields is proposed. The method was developed on the basis of data obtained by the Transportable Atmospheric Radar (TARA) located in Cabauw, Netherlands, at 0500–0812 UTC 8 May 2004, and tested using a detailed trajectory ensemble model of the cloud-capped BL. During the observations, the BL depth was 1200 m, and the cloud base (measured by a lidar) was at 500–550 m. No preliminary assumptions concerning the shapes of drop size distributions were made. On the basis of the TARA radar data, vertical profiles of the vertical air velocity standard deviation, of turbulent dissipation rate, etc. were estimated. The correlation functions indicate the existence of large eddies in the BL with a characteristic horizontal scale of about 600 m. Analysis of the slope (the scaling parameter) of the structure functions indicates that turbulence above 400 m can be considered to be isotropic. Below this level, the turbulence becomes anisotropic. The rate of anisotropy increases with the decrease of the height above the surface. The averaged values of the dissipation rate were evaluated as 1–2 cm2 s−3. The importance of using the cloud-capped BL model as a link between different types of observed data (radar, lidar, aircraft, etc.) is discussed. More data should be analyzed to understand the changes in the turbulent structure of the BL during its growth, as well as during cloud and drizzle formation.
Abstract
A new method for retrieving air velocity fluctuations in the cloud-capped boundary layer (BL) using radar reflectivity and the Doppler velocity fields is proposed. The method was developed on the basis of data obtained by the Transportable Atmospheric Radar (TARA) located in Cabauw, Netherlands, at 0500–0812 UTC 8 May 2004, and tested using a detailed trajectory ensemble model of the cloud-capped BL. During the observations, the BL depth was 1200 m, and the cloud base (measured by a lidar) was at 500–550 m. No preliminary assumptions concerning the shapes of drop size distributions were made. On the basis of the TARA radar data, vertical profiles of the vertical air velocity standard deviation, of turbulent dissipation rate, etc. were estimated. The correlation functions indicate the existence of large eddies in the BL with a characteristic horizontal scale of about 600 m. Analysis of the slope (the scaling parameter) of the structure functions indicates that turbulence above 400 m can be considered to be isotropic. Below this level, the turbulence becomes anisotropic. The rate of anisotropy increases with the decrease of the height above the surface. The averaged values of the dissipation rate were evaluated as 1–2 cm2 s−3. The importance of using the cloud-capped BL model as a link between different types of observed data (radar, lidar, aircraft, etc.) is discussed. More data should be analyzed to understand the changes in the turbulent structure of the BL during its growth, as well as during cloud and drizzle formation.
Abstract
This paper describes advances in ground-based thermodynamic profiling of the lower troposphere through sensor synergy. The well-documented integrated profiling technique (IPT), which uses a microwave profiler, a cloud radar, and a ceilometer to simultaneously retrieve vertical profiles of temperature, humidity, and liquid water content (LWC) of nonprecipitating clouds, is further developed toward an enhanced performance in the boundary layer and lower troposphere. For a more accurate temperature profile, this is accomplished by including an elevation scanning measurement modus of the microwave profiler. Height-dependent RMS accuracies of temperature (humidity) ranging from ∼0.3 to 0.9 K (0.5–0.8 g m−3) in the boundary layer are derived from retrieval simulations and confirmed experimentally with measurements at distinct heights taken during the 2005 International Lindenberg Campaign for Assessment of Humidity and Cloud Profiling Systems and its Impact on High-Resolution Modeling (LAUNCH) of the German Weather Service. Temperature inversions, especially of the lower boundary layer, are captured in a very satisfactory way by using the elevation scanning mode. To improve the quality of liquid water content measurements in clouds the authors incorporate a sophisticated target classification scheme developed within the European cloud observing network CloudNet. It allows the detailed discrimination between different types of backscatterers detected by cloud radar and ceilometer. Finally, to allow IPT application also to drizzling cases, an LWC profiling method is integrated. This technique classifies the detected hydrometeors into three different size classes using certain thresholds determined by radar reflectivity and/or ceilometer extinction profiles. By inclusion into IPT, the retrieved profiles are made consistent with the measurements of the microwave profiler and an LWC a priori profile. Results of IPT application to 13 days of the LAUNCH campaign are analyzed, and the importance of integrated profiling for model evaluation is underlined.
Abstract
This paper describes advances in ground-based thermodynamic profiling of the lower troposphere through sensor synergy. The well-documented integrated profiling technique (IPT), which uses a microwave profiler, a cloud radar, and a ceilometer to simultaneously retrieve vertical profiles of temperature, humidity, and liquid water content (LWC) of nonprecipitating clouds, is further developed toward an enhanced performance in the boundary layer and lower troposphere. For a more accurate temperature profile, this is accomplished by including an elevation scanning measurement modus of the microwave profiler. Height-dependent RMS accuracies of temperature (humidity) ranging from ∼0.3 to 0.9 K (0.5–0.8 g m−3) in the boundary layer are derived from retrieval simulations and confirmed experimentally with measurements at distinct heights taken during the 2005 International Lindenberg Campaign for Assessment of Humidity and Cloud Profiling Systems and its Impact on High-Resolution Modeling (LAUNCH) of the German Weather Service. Temperature inversions, especially of the lower boundary layer, are captured in a very satisfactory way by using the elevation scanning mode. To improve the quality of liquid water content measurements in clouds the authors incorporate a sophisticated target classification scheme developed within the European cloud observing network CloudNet. It allows the detailed discrimination between different types of backscatterers detected by cloud radar and ceilometer. Finally, to allow IPT application also to drizzling cases, an LWC profiling method is integrated. This technique classifies the detected hydrometeors into three different size classes using certain thresholds determined by radar reflectivity and/or ceilometer extinction profiles. By inclusion into IPT, the retrieved profiles are made consistent with the measurements of the microwave profiler and an LWC a priori profile. Results of IPT application to 13 days of the LAUNCH campaign are analyzed, and the importance of integrated profiling for model evaluation is underlined.
Abstract
In situ measurements indicate the complexity and nonunique character of radar reflectivity–liquid water content (Z–LWC) relationships in stratocumulus and cumulus clouds. Parameters of empirical (statistical) Z–LWC dependences vary within a wide range. Respectively, the accuracy of retrieval algorithms remains low. This situation is partially related to the fact that empirical algorithms and parameters are often derived without a corresponding understanding of physical mechanisms responsible for the formation of the Z–LWC diagrams. In this study, the authors investigate the processes of formation of the Z–LWC relationships using a new trajectory ensemble model of the cloud-topped boundary layer (BL). In the model, the entire volume of the BL is covered by Lagrangian parcels advected by a turbulent-like velocity field. The time-dependent velocity field is generated by a turbulent model and obeys the correlation turbulent laws. Each Lagrangian parcel represents the “cloud parcel model” with an accurate description of processes of diffusion growth–evaporation of aerosols and droplets and droplet collisions. The fact that parcels are adjacent to each other allows one to calculate sedimentation of droplets and precipitation (drizzle) formation. The characteristic parcel size is 50 m; the number of parcels is 1840. The model calculates droplet size distributions (DSDs), as well as their moments (e.g., aerosol and drop concentration, mass content, radar reflectivity) in each parcel. In the course of the model integration, Z–LWC relationships are calculated for each parcel, as well as the scattering diagram including all parcels. The model reproduces in situ observed types of the Z–LWC relationships. It is shown that different regimes represent different stages of cloud evolution: diffusion growth, beginning of drizzle formation, and stage of heavy drizzle, respectively. The large scattering of the Z–LWC relationships is found to be an inherent property of any drizzling cloud. Different zones on the Z–LWC diagram are related to cloud volumes located at different levels within a cloud and having different DSD. This finding allows for improvement of retrieval algorithms.
Abstract
In situ measurements indicate the complexity and nonunique character of radar reflectivity–liquid water content (Z–LWC) relationships in stratocumulus and cumulus clouds. Parameters of empirical (statistical) Z–LWC dependences vary within a wide range. Respectively, the accuracy of retrieval algorithms remains low. This situation is partially related to the fact that empirical algorithms and parameters are often derived without a corresponding understanding of physical mechanisms responsible for the formation of the Z–LWC diagrams. In this study, the authors investigate the processes of formation of the Z–LWC relationships using a new trajectory ensemble model of the cloud-topped boundary layer (BL). In the model, the entire volume of the BL is covered by Lagrangian parcels advected by a turbulent-like velocity field. The time-dependent velocity field is generated by a turbulent model and obeys the correlation turbulent laws. Each Lagrangian parcel represents the “cloud parcel model” with an accurate description of processes of diffusion growth–evaporation of aerosols and droplets and droplet collisions. The fact that parcels are adjacent to each other allows one to calculate sedimentation of droplets and precipitation (drizzle) formation. The characteristic parcel size is 50 m; the number of parcels is 1840. The model calculates droplet size distributions (DSDs), as well as their moments (e.g., aerosol and drop concentration, mass content, radar reflectivity) in each parcel. In the course of the model integration, Z–LWC relationships are calculated for each parcel, as well as the scattering diagram including all parcels. The model reproduces in situ observed types of the Z–LWC relationships. It is shown that different regimes represent different stages of cloud evolution: diffusion growth, beginning of drizzle formation, and stage of heavy drizzle, respectively. The large scattering of the Z–LWC relationships is found to be an inherent property of any drizzling cloud. Different zones on the Z–LWC diagram are related to cloud volumes located at different levels within a cloud and having different DSD. This finding allows for improvement of retrieval algorithms.
Abstract
A method is presented to obtain droplet concentration for water clouds from ground-based remote sensing observations. It relies on observations of cloud thickness, liquid water path, and optical extinction near the cloud base. The method was tested for two case studies (19 April 1996 and 4 September 1996) during the Clouds And Radiation experiment (CLARA). The CLARA experiment was designed to observe clouds using a variety of remote sensing instruments near the city of Delft in the western part of the Netherlands. The measurement of cloud thickness is dependent on the detection of cloud base by lidar and cloud top by radar. It is shown that during CLARA it was possible to detect cloud base with an uncertainty of less than 30 m using current lidar techniques. The agreement between in situ and remote sensing observations of droplet concentration was reasonable. An error analysis indicates that this method is most sensitive to uncertainties in liquid water path and the unknown effects of multiple scattering on lidar signal returns. When the liquid water path is very small the relative error of the liquid water path increases to unacceptable levels, so that the retrieval of droplet concentration becomes very difficult. The estimated uncertainty in the strength of multiple scattering can explain differences between observations and retrievals of droplet concentration on one day, but not the other.
Abstract
A method is presented to obtain droplet concentration for water clouds from ground-based remote sensing observations. It relies on observations of cloud thickness, liquid water path, and optical extinction near the cloud base. The method was tested for two case studies (19 April 1996 and 4 September 1996) during the Clouds And Radiation experiment (CLARA). The CLARA experiment was designed to observe clouds using a variety of remote sensing instruments near the city of Delft in the western part of the Netherlands. The measurement of cloud thickness is dependent on the detection of cloud base by lidar and cloud top by radar. It is shown that during CLARA it was possible to detect cloud base with an uncertainty of less than 30 m using current lidar techniques. The agreement between in situ and remote sensing observations of droplet concentration was reasonable. An error analysis indicates that this method is most sensitive to uncertainties in liquid water path and the unknown effects of multiple scattering on lidar signal returns. When the liquid water path is very small the relative error of the liquid water path increases to unacceptable levels, so that the retrieval of droplet concentration becomes very difficult. The estimated uncertainty in the strength of multiple scattering can explain differences between observations and retrievals of droplet concentration on one day, but not the other.
Retrieving Fall Streaks within Cloud Systems Using Doppler RadarAbstract
The interaction of ice crystals with supercooled liquid droplets in mixed-phase clouds leads to an enhanced growth of ice particles. However, such processes are still not clearly understood although they are important processes for precipitation formation in midlatitudes. To better understand how ice particles grow within such clouds, changes in the microphysical parameters of a particle population falling through the cloud have to be analyzed. The Transportable Atmospheric Radar (TARA) can retrieve the full 3D Doppler velocity vector based on a unique three-beam configuration. Using the derived wind information, a new fall streak retrieval technique is proposed so that microphysical changes along those streaks can be studied. The method is based on Doppler measurements only. The shown examples measured during the Analysis of the Composition of Clouds with Extended Polarization Techniques (ACCEPT) campaign demonstrate that the retrieval is able to capture the fall streaks within different cloud systems. These fall streaks can be used to study changes in a single particle population from its generation (at cloud top) until its disintegration. In this study fall streaks are analyzed using radar moments or Doppler spectra. Synergetic measurements with other instruments during ACCEPT allow the detection of liquid layers within the clouds. The estimated microphysical information is used here to get a better understanding of the influence of supercooled liquid layers on ice crystal growth. This technique offers a new perspective for cloud microphysical studies.
Abstract
The interaction of ice crystals with supercooled liquid droplets in mixed-phase clouds leads to an enhanced growth of ice particles. However, such processes are still not clearly understood although they are important processes for precipitation formation in midlatitudes. To better understand how ice particles grow within such clouds, changes in the microphysical parameters of a particle population falling through the cloud have to be analyzed. The Transportable Atmospheric Radar (TARA) can retrieve the full 3D Doppler velocity vector based on a unique three-beam configuration. Using the derived wind information, a new fall streak retrieval technique is proposed so that microphysical changes along those streaks can be studied. The method is based on Doppler measurements only. The shown examples measured during the Analysis of the Composition of Clouds with Extended Polarization Techniques (ACCEPT) campaign demonstrate that the retrieval is able to capture the fall streaks within different cloud systems. These fall streaks can be used to study changes in a single particle population from its generation (at cloud top) until its disintegration. In this study fall streaks are analyzed using radar moments or Doppler spectra. Synergetic measurements with other instruments during ACCEPT allow the detection of liquid layers within the clouds. The estimated microphysical information is used here to get a better understanding of the influence of supercooled liquid layers on ice crystal growth. This technique offers a new perspective for cloud microphysical studies.
Abstract
Many radar measurements of the atmosphere can be explained in terms of two scattering mechanisms: incoherent scattering from particles, and coherent scattering from variations in the refractive index of the air, commonly called clear-air or Bragg scattering. Spatial variations in the liquid water content of clouds may also give a coherent contribution to the radar return, but it is commonly believed that this coherent scattering from the droplets is insignificant because variations in humidity have a much larger influence on the refractive index than equal variations in liquid water content. It is argued that the fluctuations in water vapor mixing ratio in clouds can be much smaller than those in liquid water mixing ratio.
In this article an expression for the strength of the coherent scattering from particles will be derived for fluctuations caused by turbulent mixing with clean (i.e., particle-free) air, where it will be assumed that the particles follow the flow, that is, their inertia is neglected. It will be shown that the coherent contribution adds to the incoherent contribution, the latter always being present. The coherent particle scattering can be stronger than the incoherent scattering, especially at longer wavelengths and high particle concentrations.
Recently published dual-frequency measurements of developing cumulus clouds and smoke show a correlation for which no explanation has been found in terms of incoherent particle scattering and coherent air scattering. Scatterplots of the reflectivity factors at both frequencies show a clustering of points in between the values that correspond to pure clear-air and pure incoherent scattering. Those differences in the radar reflectivity factors could be due to a mixture of Bragg scattering and incoherent particle scattering, but then no correlation is expected, because the origin of the scattering mechanism that dominates at each wavelength is different.
However, coherent scattering from the particles can cause the radar reflectivities of dual-wavelength radar measurements to become correlated with each other. It may explain the slopes and the differences seen in the scatterplots of the radar reflectivities of cloud and smoke measurements, with reasonable values of the parameters involved. However, the correlation between the radar reflectivities is very tight near the cloud top and seems to be present in adiabatic cores as well. This is an indication that, apart from mixing with environmental air, the inertia of the droplets could also be important for the creation of small-scale fluctuations in droplet concentration.
Abstract
Many radar measurements of the atmosphere can be explained in terms of two scattering mechanisms: incoherent scattering from particles, and coherent scattering from variations in the refractive index of the air, commonly called clear-air or Bragg scattering. Spatial variations in the liquid water content of clouds may also give a coherent contribution to the radar return, but it is commonly believed that this coherent scattering from the droplets is insignificant because variations in humidity have a much larger influence on the refractive index than equal variations in liquid water content. It is argued that the fluctuations in water vapor mixing ratio in clouds can be much smaller than those in liquid water mixing ratio.
In this article an expression for the strength of the coherent scattering from particles will be derived for fluctuations caused by turbulent mixing with clean (i.e., particle-free) air, where it will be assumed that the particles follow the flow, that is, their inertia is neglected. It will be shown that the coherent contribution adds to the incoherent contribution, the latter always being present. The coherent particle scattering can be stronger than the incoherent scattering, especially at longer wavelengths and high particle concentrations.
Recently published dual-frequency measurements of developing cumulus clouds and smoke show a correlation for which no explanation has been found in terms of incoherent particle scattering and coherent air scattering. Scatterplots of the reflectivity factors at both frequencies show a clustering of points in between the values that correspond to pure clear-air and pure incoherent scattering. Those differences in the radar reflectivity factors could be due to a mixture of Bragg scattering and incoherent particle scattering, but then no correlation is expected, because the origin of the scattering mechanism that dominates at each wavelength is different.
However, coherent scattering from the particles can cause the radar reflectivities of dual-wavelength radar measurements to become correlated with each other. It may explain the slopes and the differences seen in the scatterplots of the radar reflectivities of cloud and smoke measurements, with reasonable values of the parameters involved. However, the correlation between the radar reflectivities is very tight near the cloud top and seems to be present in adiabatic cores as well. This is an indication that, apart from mixing with environmental air, the inertia of the droplets could also be important for the creation of small-scale fluctuations in droplet concentration.
Abstract
Polarization properties of radar waves that are scattered from atmospheric objects are of great interest in meteorological studies. However, polarimetric radar measurements are often not sufficiently accurate for retrieving physical properties of targets. To compensate for errors, radar polarimetric calibration is applied. Typical calibrations are performed based on measurements of point targets with known scattering matrices located in the boresight of the antenna. Such calibration takes into account the polarization state of the antenna pattern only at one point. Since radar measurements of atmospheric phenomena involve distributed targets that fill the full antenna beam, point target radar calibrations are inadequate for meteorological studies.
This paper explains in detail the effects of the complete antenna patterns on weather echoes. It is shown that the conventional polarimetric calibration can be significantly improved by incorporating light-rain (<20 dBZ) zenith-pointing measurements into the calibration procedure. As a result, the sensitivity of cross-polar measurements can be improved by 7 dB on average. Also it is shown that the bias in co-cross-polar correlation coefficient can be reduced.
Abstract
Polarization properties of radar waves that are scattered from atmospheric objects are of great interest in meteorological studies. However, polarimetric radar measurements are often not sufficiently accurate for retrieving physical properties of targets. To compensate for errors, radar polarimetric calibration is applied. Typical calibrations are performed based on measurements of point targets with known scattering matrices located in the boresight of the antenna. Such calibration takes into account the polarization state of the antenna pattern only at one point. Since radar measurements of atmospheric phenomena involve distributed targets that fill the full antenna beam, point target radar calibrations are inadequate for meteorological studies.
This paper explains in detail the effects of the complete antenna patterns on weather echoes. It is shown that the conventional polarimetric calibration can be significantly improved by incorporating light-rain (<20 dBZ) zenith-pointing measurements into the calibration procedure. As a result, the sensitivity of cross-polar measurements can be improved by 7 dB on average. Also it is shown that the bias in co-cross-polar correlation coefficient can be reduced.
Velocity-Based EDR Retrieval Techniques Applied to Doppler Radar Measurements from Rain: Two Case StudiesAbstract
In this article, five velocity-based energy dissipation rate (EDR) retrieval techniques are assessed. The EDR retrieval techniques are applied to Doppler measurements from Transportable Atmospheric Radar (TARA)—a precipitation profiling radar—operating in the vertically fixed-pointing mode. A generalized formula for the Kolmogorov constant is derived, which gives potential for the application of the EDR retrieval techniques to any radar line of sight (LOS). Two case studies are discussed that contain rain events of about 2 and 18 h, respectively. The EDR values retrieved from the radar are compared to in situ EDR values from collocated sonic anemometers. For the two case studies, a correlation coefficient of 0.79 was found for the wind speed variance (WSV) EDR retrieval technique, which uses 3D wind vectors as input and has a total sampling time of 10 min. From this comparison it is concluded that the radar is able to measure EDR with a reasonable accuracy. Almost no correlation was found for the vertical wind velocity variance (VWVV) EDR retrieval technique, as it was not possible to sufficiently separate the turbulence dynamics contribution to the radar Doppler mean velocities from the velocity contribution of falling raindrops. An important cause of the discrepancies between radar and in situ EDR values is thus due to insufficient accurate estimation of vertical air velocities.
Abstract
In this article, five velocity-based energy dissipation rate (EDR) retrieval techniques are assessed. The EDR retrieval techniques are applied to Doppler measurements from Transportable Atmospheric Radar (TARA)—a precipitation profiling radar—operating in the vertically fixed-pointing mode. A generalized formula for the Kolmogorov constant is derived, which gives potential for the application of the EDR retrieval techniques to any radar line of sight (LOS). Two case studies are discussed that contain rain events of about 2 and 18 h, respectively. The EDR values retrieved from the radar are compared to in situ EDR values from collocated sonic anemometers. For the two case studies, a correlation coefficient of 0.79 was found for the wind speed variance (WSV) EDR retrieval technique, which uses 3D wind vectors as input and has a total sampling time of 10 min. From this comparison it is concluded that the radar is able to measure EDR with a reasonable accuracy. Almost no correlation was found for the vertical wind velocity variance (VWVV) EDR retrieval technique, as it was not possible to sufficiently separate the turbulence dynamics contribution to the radar Doppler mean velocities from the velocity contribution of falling raindrops. An important cause of the discrepancies between radar and in situ EDR values is thus due to insufficient accurate estimation of vertical air velocities.
