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- Author or Editor: Vickal V. Kumar x
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Abstract
C-band polarimetric radar measurements spanning two wet seasons are used to study the effects of the large-scale environment on the statistical properties of stratiform and convective rainfall around Darwin, Australia. The rainfall physical properties presented herein are the reflectivity fields, daily rainfall accumulations and raining area, rain rates, and drop size distribution (DSD) parameters (median volume diameter and “normalized” intercept parameter). Each of these properties is then analyzed according to five different atmospheric regimes and further separated into stratiform or convective rain categories following a DSD-based approach. The regimes, objectively identified by radiosonde thermodynamic and wind measurements, represent typical wet-season atmospheric conditions: the active monsoon regime, the “break” periods, the “buildup” regime, the trade wind regime, and a mixture of inactive/break periods. The large-scale context is found to strongly modulate rainfall and cloud microphysical properties. For example, during the active monsoon regime, the daily rain accumulation is higher than in the other regimes, while this regime is associated with the lowest rain rates. Precipitation in this active monsoon regime is found to be widespread and mainly composed of small particles in high concentration compared to the other regimes. Vertical profiles of reflectivity and DSD parameters suggest that warm rain processes are dominant during this regime. In contrast, rainfall properties in the drier regimes (trade wind/buildup regimes) are mostly of continental origin, with rain rates higher than in the moister regimes. In these drier regimes, precipitation is mainly formed of large raindrops in relatively low concentration due to a larger contribution of the ice microphysical processes on the rainfall formation.
Abstract
C-band polarimetric radar measurements spanning two wet seasons are used to study the effects of the large-scale environment on the statistical properties of stratiform and convective rainfall around Darwin, Australia. The rainfall physical properties presented herein are the reflectivity fields, daily rainfall accumulations and raining area, rain rates, and drop size distribution (DSD) parameters (median volume diameter and “normalized” intercept parameter). Each of these properties is then analyzed according to five different atmospheric regimes and further separated into stratiform or convective rain categories following a DSD-based approach. The regimes, objectively identified by radiosonde thermodynamic and wind measurements, represent typical wet-season atmospheric conditions: the active monsoon regime, the “break” periods, the “buildup” regime, the trade wind regime, and a mixture of inactive/break periods. The large-scale context is found to strongly modulate rainfall and cloud microphysical properties. For example, during the active monsoon regime, the daily rain accumulation is higher than in the other regimes, while this regime is associated with the lowest rain rates. Precipitation in this active monsoon regime is found to be widespread and mainly composed of small particles in high concentration compared to the other regimes. Vertical profiles of reflectivity and DSD parameters suggest that warm rain processes are dominant during this regime. In contrast, rainfall properties in the drier regimes (trade wind/buildup regimes) are mostly of continental origin, with rain rates higher than in the moister regimes. In these drier regimes, precipitation is mainly formed of large raindrops in relatively low concentration due to a larger contribution of the ice microphysical processes on the rainfall formation.
Abstract
Some cumulus clouds with tops between 3 and 7 km (Cu3km–7km) remain in this height region throughout their lifetime (congestus) while others develop into deeper clouds (cumulonimbus). This study describes two techniques to identify the congestus and cumulonimbus cloud types using data from scanning weather radar and identifies the atmospheric conditions that regulate these two modes. A two-wet-season cumulus cloud database of the Darwin C-band polarimetric radar is analyzed and the two modes are identified by examining the 0-dBZ cloud-top height (CTH) of the Cu3km–7km cells over a sequence of radar scans. It is found that ~26% of the classified Cu3km–7km population grow into cumulonimbus clouds. The cumulonimbus cells exhibit reflectivities, rain rates, and drop sizes larger than the congestus cells. The occurrence frequency of cumulonimbus cells peak in the afternoon at ~1500 local time—a few hours after the peak in congestus cells. The analysis of Darwin International Airport radiosonde profiles associated with the two types of cells shows no noticeable difference in the thermal stability rates, but a significant difference in midtropospheric (5–10 km) relative humidity. Moister conditions are found in the hours preceding the cumulonimbus cells when compared with the congestus cells. Using a moisture budget dataset derived for the Darwin region, it is shown that the existence of cumulonimbus cells, and hence deep convection, is mainly determined by the presence of the midtroposphere large-scale upward motion and not merely by the presence of congestus clouds prior to deep convection. This contradicts the thermodynamic viewpoint that the midtroposphere moistening prior to deep convection is solely due to the preceding cumulus congestus cells.
Abstract
Some cumulus clouds with tops between 3 and 7 km (Cu3km–7km) remain in this height region throughout their lifetime (congestus) while others develop into deeper clouds (cumulonimbus). This study describes two techniques to identify the congestus and cumulonimbus cloud types using data from scanning weather radar and identifies the atmospheric conditions that regulate these two modes. A two-wet-season cumulus cloud database of the Darwin C-band polarimetric radar is analyzed and the two modes are identified by examining the 0-dBZ cloud-top height (CTH) of the Cu3km–7km cells over a sequence of radar scans. It is found that ~26% of the classified Cu3km–7km population grow into cumulonimbus clouds. The cumulonimbus cells exhibit reflectivities, rain rates, and drop sizes larger than the congestus cells. The occurrence frequency of cumulonimbus cells peak in the afternoon at ~1500 local time—a few hours after the peak in congestus cells. The analysis of Darwin International Airport radiosonde profiles associated with the two types of cells shows no noticeable difference in the thermal stability rates, but a significant difference in midtropospheric (5–10 km) relative humidity. Moister conditions are found in the hours preceding the cumulonimbus cells when compared with the congestus cells. Using a moisture budget dataset derived for the Darwin region, it is shown that the existence of cumulonimbus cells, and hence deep convection, is mainly determined by the presence of the midtroposphere large-scale upward motion and not merely by the presence of congestus clouds prior to deep convection. This contradicts the thermodynamic viewpoint that the midtroposphere moistening prior to deep convection is solely due to the preceding cumulus congestus cells.
Abstract
C-band polarimetric radar measurements spanning two wet seasons are used to perform a critical evaluation of two algorithms for the classification of stratiform and convective precipitation. The first approach is based on the horizontal texture of the radar reflectivity field (two classes: stratiform, convective), and the second approach is based on the properties of the drop size distribution (DSD) parameters as derived from a set of polarimetric variables (three classes: stratiform, mixed, convective). To investigate how well those two methods compare quantitatively, probability density functions of reflectivity, rain rate, 5-dBZ echo top height, and DSD parameters (namely, the median volume diameter and the “generalized” intercept parameter) are built. The study found that while the two methods agree well on the identification of stratiform precipitation, large differences are obtained for convective rainfall. The texture-based approach seems to classify too many points as being of convective nature compared to the DSD-based method. Among the points that are classified as convective by the texture-based approach, 25% correspond to low concentration of relatively small particles associated with rain rates below 10 mm h−1. This large proportion of unrealistically low convective rain rates is not produced by the DSD-based approach, which only classifies 4% of the convective points with rain rates below 10 mm h−1. These points were found to be mainly isolated points embedded within stratiform precipitation and associated with low cloud-top height, suggesting a misclassification of the texture-based approach. Thus, to improve the statistics of the convective class, three modified equations of the peakedness criterion used in the radar-based algorithm are proposed to decrease the number of misclassified points.
Abstract
C-band polarimetric radar measurements spanning two wet seasons are used to perform a critical evaluation of two algorithms for the classification of stratiform and convective precipitation. The first approach is based on the horizontal texture of the radar reflectivity field (two classes: stratiform, convective), and the second approach is based on the properties of the drop size distribution (DSD) parameters as derived from a set of polarimetric variables (three classes: stratiform, mixed, convective). To investigate how well those two methods compare quantitatively, probability density functions of reflectivity, rain rate, 5-dBZ echo top height, and DSD parameters (namely, the median volume diameter and the “generalized” intercept parameter) are built. The study found that while the two methods agree well on the identification of stratiform precipitation, large differences are obtained for convective rainfall. The texture-based approach seems to classify too many points as being of convective nature compared to the DSD-based method. Among the points that are classified as convective by the texture-based approach, 25% correspond to low concentration of relatively small particles associated with rain rates below 10 mm h−1. This large proportion of unrealistically low convective rain rates is not produced by the DSD-based approach, which only classifies 4% of the convective points with rain rates below 10 mm h−1. These points were found to be mainly isolated points embedded within stratiform precipitation and associated with low cloud-top height, suggesting a misclassification of the texture-based approach. Thus, to improve the statistics of the convective class, three modified equations of the peakedness criterion used in the radar-based algorithm are proposed to decrease the number of misclassified points.
Abstract
Cumulus parameterizations in weather and climate models frequently apply mass-flux schemes in their description of tropical convection. Mass flux constitutes the product of the fractional area covered by convection in a model grid box and the vertical velocity in cumulus clouds. However, vertical velocities are difficult to observe on GCM scales, making the evaluation of mass-flux schemes difficult. Here, the authors combine high-temporal-resolution observations of in-cloud vertical velocities derived from a pair of wind profilers over two wet seasons at Darwin with physical properties of precipitating clouds [cloud-top heights (CTH), convective–stratiform classification] derived from the Darwin C-band polarimetric radar to provide estimates of cumulus mass flux and its constituents. The length of this dataset allows for investigations of the contributions from different cumulus cloud types—namely, congestus, deep, and overshooting convection—to the overall mass flux and of the influence of large-scale conditions on mass flux. The authors found that mass flux was dominated by updrafts and, in particular, the updraft area fraction, with updraft vertical velocity playing a secondary role. The updraft vertical velocities peaked above 10 km where both the updraft area fractions and air densities were small, resulting in a marginal effect on mass-flux values. Downdraft area fractions are much smaller and velocities are much weaker than those in updrafts. The area fraction responded strongly to changes in midlevel large-scale vertical motion and convective inhibition (CIN). In contrast, changes in the lower-tropospheric relative humidity and convective available potential energy (CAPE) strongly modulate in-cloud vertical velocities but have moderate impacts on area fractions. Although average mass flux is found to increase with increasing CTH, it is the environmental conditions that seem to dictate the magnitude of mass flux produced by convection through a combination of effects on area fraction and velocity.
Abstract
Cumulus parameterizations in weather and climate models frequently apply mass-flux schemes in their description of tropical convection. Mass flux constitutes the product of the fractional area covered by convection in a model grid box and the vertical velocity in cumulus clouds. However, vertical velocities are difficult to observe on GCM scales, making the evaluation of mass-flux schemes difficult. Here, the authors combine high-temporal-resolution observations of in-cloud vertical velocities derived from a pair of wind profilers over two wet seasons at Darwin with physical properties of precipitating clouds [cloud-top heights (CTH), convective–stratiform classification] derived from the Darwin C-band polarimetric radar to provide estimates of cumulus mass flux and its constituents. The length of this dataset allows for investigations of the contributions from different cumulus cloud types—namely, congestus, deep, and overshooting convection—to the overall mass flux and of the influence of large-scale conditions on mass flux. The authors found that mass flux was dominated by updrafts and, in particular, the updraft area fraction, with updraft vertical velocity playing a secondary role. The updraft vertical velocities peaked above 10 km where both the updraft area fractions and air densities were small, resulting in a marginal effect on mass-flux values. Downdraft area fractions are much smaller and velocities are much weaker than those in updrafts. The area fraction responded strongly to changes in midlevel large-scale vertical motion and convective inhibition (CIN). In contrast, changes in the lower-tropospheric relative humidity and convective available potential energy (CAPE) strongly modulate in-cloud vertical velocities but have moderate impacts on area fractions. Although average mass flux is found to increase with increasing CTH, it is the environmental conditions that seem to dictate the magnitude of mass flux produced by convection through a combination of effects on area fraction and velocity.
Abstract
Two seasons of Darwin, Australia, C-band polarimetric (CPOL) research radar, radiosoundings, and lightning data are examined to study the relative influence of the large-scale atmospheric regimes and the underlying surface types on tropical convective cloud properties and their diurnal evolution. The authors find that in the “deep westerly” regime, which corresponds to the monsoon period, the convective cloud occurrence rate is highest, consistent with its highest relative humidity. However, these convective clouds have relatively low cloud-top heights, smaller-than-average cell volumes, and are electrically least active. In this regime, the cloud cell volume does not vary significantly across different underlying surfaces and afternoon convective activity is suppressed. Thus, the picture emerging is that the convective cloud activity in the deep westerly regime is primarily regulated by the large-scale conditions. The remaining regimes (“easterly,” “shallow westerly,” and “moist easterly”) also demonstrate strong dependence on the large-scale forcing and a secondary dependence on the underlying surface type. The easterly regime has a small convective cloud occurrence rate and low cloud heights but higher lightning counts per convective cloud. The other two regimes have moderate convective cloud occurrence rates and larger cloud sizes. The easterly, shallow westerly, and moist easterly regimes exhibit a strong, clearly defined semidiurnal convective cloud occurrence pattern, with peaks in the early morning and afternoon periods. The cell onset times in these three regimes depend on the combination of local time and the underlying surface.
Abstract
Two seasons of Darwin, Australia, C-band polarimetric (CPOL) research radar, radiosoundings, and lightning data are examined to study the relative influence of the large-scale atmospheric regimes and the underlying surface types on tropical convective cloud properties and their diurnal evolution. The authors find that in the “deep westerly” regime, which corresponds to the monsoon period, the convective cloud occurrence rate is highest, consistent with its highest relative humidity. However, these convective clouds have relatively low cloud-top heights, smaller-than-average cell volumes, and are electrically least active. In this regime, the cloud cell volume does not vary significantly across different underlying surfaces and afternoon convective activity is suppressed. Thus, the picture emerging is that the convective cloud activity in the deep westerly regime is primarily regulated by the large-scale conditions. The remaining regimes (“easterly,” “shallow westerly,” and “moist easterly”) also demonstrate strong dependence on the large-scale forcing and a secondary dependence on the underlying surface type. The easterly regime has a small convective cloud occurrence rate and low cloud heights but higher lightning counts per convective cloud. The other two regimes have moderate convective cloud occurrence rates and larger cloud sizes. The easterly, shallow westerly, and moist easterly regimes exhibit a strong, clearly defined semidiurnal convective cloud occurrence pattern, with peaks in the early morning and afternoon periods. The cell onset times in these three regimes depend on the combination of local time and the underlying surface.
Abstract
In this study, methods of convective/stratiform precipitation classification and surface rain-rate estimation based on the Atmospheric Radiation Measurement Program (ARM) cloud radar measurements were developed and evaluated. Simultaneous and collocated observations of the Ka-band ARM zenith radar (KAZR), two scanning precipitation radars [NCAR S-band/Ka-band Dual Polarization, Dual Wavelength Doppler Radar (S-PolKa) and Texas A&M University Shared Mobile Atmospheric Research and Teaching Radar (SMART-R)], and surface precipitation during the Dynamics of the Madden–Julian Oscillation/ARM MJO Investigation Experiment (DYNAMO/AMIE) field campaign were used. The motivation of this study is to apply the unique long-term ARM cloud radar observations without accompanying precipitation radars to the study of cloud life cycle and precipitation features under different weather and climate regimes. The resulting convective/stratiform classification from KAZR was evaluated against precipitation radars. Precipitation occurrence and classified convective/stratiform rain fractions from KAZR compared favorably to the collocated SMART-R and S-PolKa observations. Both KAZR and S-PolKa radars observed about 5% precipitation occurrence. The convective (stratiform) precipitation fraction is about 18% (82%). Collocated disdrometer observations of two days showed an increased number concentration of small and large raindrops in convective rain relative to dominant small raindrops in stratiform rain. The composite distributions of KAZR reflectivity and Doppler velocity also showed distinct structures for convective and stratiform rain. These evidences indicate that the method produces physically consistent results for the two types of rain. A new KAZR-based, two-parameter [the gradient of accumulative radar reflectivity Z e (GAZ) below 1 km and near-surface Z e ] rain-rate estimation procedure was developed for both convective and stratiform rain. This estimate was compared with the exponential Z–R (reflectivity–rain rate) relation. The relative difference between the estimated and surface-measured rainfall rates showed that the two-parameter relation can improve rainfall estimation relative to the Z–R relation.
Abstract
In this study, methods of convective/stratiform precipitation classification and surface rain-rate estimation based on the Atmospheric Radiation Measurement Program (ARM) cloud radar measurements were developed and evaluated. Simultaneous and collocated observations of the Ka-band ARM zenith radar (KAZR), two scanning precipitation radars [NCAR S-band/Ka-band Dual Polarization, Dual Wavelength Doppler Radar (S-PolKa) and Texas A&M University Shared Mobile Atmospheric Research and Teaching Radar (SMART-R)], and surface precipitation during the Dynamics of the Madden–Julian Oscillation/ARM MJO Investigation Experiment (DYNAMO/AMIE) field campaign were used. The motivation of this study is to apply the unique long-term ARM cloud radar observations without accompanying precipitation radars to the study of cloud life cycle and precipitation features under different weather and climate regimes. The resulting convective/stratiform classification from KAZR was evaluated against precipitation radars. Precipitation occurrence and classified convective/stratiform rain fractions from KAZR compared favorably to the collocated SMART-R and S-PolKa observations. Both KAZR and S-PolKa radars observed about 5% precipitation occurrence. The convective (stratiform) precipitation fraction is about 18% (82%). Collocated disdrometer observations of two days showed an increased number concentration of small and large raindrops in convective rain relative to dominant small raindrops in stratiform rain. The composite distributions of KAZR reflectivity and Doppler velocity also showed distinct structures for convective and stratiform rain. These evidences indicate that the method produces physically consistent results for the two types of rain. A new KAZR-based, two-parameter [the gradient of accumulative radar reflectivity Z e (GAZ) below 1 km and near-surface Z e ] rain-rate estimation procedure was developed for both convective and stratiform rain. This estimate was compared with the exponential Z–R (reflectivity–rain rate) relation. The relative difference between the estimated and surface-measured rainfall rates showed that the two-parameter relation can improve rainfall estimation relative to the Z–R relation.
Abstract
Cumulus parameterizations in general circulation models (GCMs) frequently apply mass-flux schemes in their description of tropical convection. Mass flux constitutes the product of the fractional area covered by cumulus clouds in a model grid box and the vertical velocity within the cumulus clouds. The cumulus area fraction profiles can be derived from precipitating radar reflectivity volumes. However, the vertical velocities are difficult to observe, making the evaluation of mass-flux schemes difficult. In this paper, the authors develop and evaluate a parameterization of vertical velocity in convective (cumulus) clouds using only radar reflectivities collected by a C-band polarimetric research radar (CPOL), operating at Darwin, Australia. The parameterization is trained using vertical velocity retrievals from a dual-frequency wind profiler pair located within the field of view of CPOL. The parametric model uses two inputs derived from CPOL reflectivities: the 0-dBZ echo-top height (0-dBZ ETH) and a height-weighted column reflectivity index (Z HWT). The 0-dBZ ETH determines the shape of the vertical velocity profile, while Z HWT determines its strength. The evaluation of these parameterized vertical velocities using (i) the training dataset, (ii) an independent wind-profiler-based dataset, and (iii) 1 month of dual-Doppler vertical velocity retrievals indicates that the statistical representation of vertical velocity is reasonably accurate up to the 75th percentile. However, the parametric model underestimates the extreme velocities. The method allows for the derivation of cumulus mass flux and its variability on current GCM scales based only on reflectivities from precipitating radar, which could be valuable to modelers.
Abstract
Cumulus parameterizations in general circulation models (GCMs) frequently apply mass-flux schemes in their description of tropical convection. Mass flux constitutes the product of the fractional area covered by cumulus clouds in a model grid box and the vertical velocity within the cumulus clouds. The cumulus area fraction profiles can be derived from precipitating radar reflectivity volumes. However, the vertical velocities are difficult to observe, making the evaluation of mass-flux schemes difficult. In this paper, the authors develop and evaluate a parameterization of vertical velocity in convective (cumulus) clouds using only radar reflectivities collected by a C-band polarimetric research radar (CPOL), operating at Darwin, Australia. The parameterization is trained using vertical velocity retrievals from a dual-frequency wind profiler pair located within the field of view of CPOL. The parametric model uses two inputs derived from CPOL reflectivities: the 0-dBZ echo-top height (0-dBZ ETH) and a height-weighted column reflectivity index (Z HWT). The 0-dBZ ETH determines the shape of the vertical velocity profile, while Z HWT determines its strength. The evaluation of these parameterized vertical velocities using (i) the training dataset, (ii) an independent wind-profiler-based dataset, and (iii) 1 month of dual-Doppler vertical velocity retrievals indicates that the statistical representation of vertical velocity is reasonably accurate up to the 75th percentile. However, the parametric model underestimates the extreme velocities. The method allows for the derivation of cumulus mass flux and its variability on current GCM scales based only on reflectivities from precipitating radar, which could be valuable to modelers.
