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- Author or Editor: Pavlos Kollias x
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A New Criterion to Improve Operational Drizzle Detection with Ground-Based Remote SensingAbstract
Light shallow precipitation in the form of drizzle is one of the mechanisms for liquid water removal, affecting cloud lifetime and boundary layer dynamics and thermodynamics. The early formation of drizzle drops is of particular interest for quantifying aerosol–cloud–precipitation interactions. In models, drizzle initiation is represented by the autoconversion, that is, the conversion of liquid water from a cloud liquid water category (where particle sedimentation is ignored) into a precipitating liquid water category. Various autoconversion parameterizations have been proposed in recent years, but their evaluation is challenging due to the lack of proper observations of drizzle development in the cloud. This work presents a new algorithm for Classification of Drizzle Stages (CLADS). CLADS is based on the skewness of the Ka-band radar Doppler spectrum. Skewness is sensitive to the drizzle growth in the cloud: the observed Gaussian Doppler spectrum has skewness zero when only cloud droplets are present without any significant fall velocity. Defining downward velocities positive, skewness turns positive when embryonic drizzle forms and becomes negative when drizzle starts to dominate the spectrum. CLADS identifies spatially coherent structures of positive, zero, and negative skewness in space and time corresponding to drizzle seeding, drizzle growth/nondrizzle, and drizzle mature, respectively. We test CLADS on case studies from the Jülich Observatory for Cloud Evolution Core Facility (JOYCE-CF) and the Barbados Cloud Observatory (BCO) to quantitatively estimate the benefits of CLADS compared to the standard Cloudnet target categorization algorithm. We suggest that CLADS can provide additional observational constraints for understanding the processes related to drizzle formation better.
Abstract
Light shallow precipitation in the form of drizzle is one of the mechanisms for liquid water removal, affecting cloud lifetime and boundary layer dynamics and thermodynamics. The early formation of drizzle drops is of particular interest for quantifying aerosol–cloud–precipitation interactions. In models, drizzle initiation is represented by the autoconversion, that is, the conversion of liquid water from a cloud liquid water category (where particle sedimentation is ignored) into a precipitating liquid water category. Various autoconversion parameterizations have been proposed in recent years, but their evaluation is challenging due to the lack of proper observations of drizzle development in the cloud. This work presents a new algorithm for Classification of Drizzle Stages (CLADS). CLADS is based on the skewness of the Ka-band radar Doppler spectrum. Skewness is sensitive to the drizzle growth in the cloud: the observed Gaussian Doppler spectrum has skewness zero when only cloud droplets are present without any significant fall velocity. Defining downward velocities positive, skewness turns positive when embryonic drizzle forms and becomes negative when drizzle starts to dominate the spectrum. CLADS identifies spatially coherent structures of positive, zero, and negative skewness in space and time corresponding to drizzle seeding, drizzle growth/nondrizzle, and drizzle mature, respectively. We test CLADS on case studies from the Jülich Observatory for Cloud Evolution Core Facility (JOYCE-CF) and the Barbados Cloud Observatory (BCO) to quantitatively estimate the benefits of CLADS compared to the standard Cloudnet target categorization algorithm. We suggest that CLADS can provide additional observational constraints for understanding the processes related to drizzle formation better.
Abstract
The joint European Space Agency–Japan Aerospace Exploration Agency (ESA–JAXA) Earth Clouds, Aerosols and Radiation Explorer (EarthCARE) mission is scheduled for launch in 2016 and features the first atmospheric Cloud Profiling Radar (CPR) with Doppler capability in space. Here, the uncertainty of the CPR Doppler velocity measurements in cirrus clouds and large-scale precipitation areas is discussed. These regimes are characterized by weak vertical motion and relatively horizontally homogeneous conditions and thus represent optimum conditions for acquiring high-quality CPR Doppler measurements. A large dataset of radar reflectivity observations from ground-based radars is used to examine the homogeneity of the cloud fields at the horizontal scales of interest. In addition, a CPR instrument model that uses as input ground-based radar observations and outputs simulations of CPR Doppler measurements is described. The simulator accurately accounts for the beam geometry, nonuniform beam-filling, and signal integration effects, and it is applied to representative cases of cirrus cloud and stratiform precipitation. The simulated CPR Doppler velocities are compared against those derived from the ground-based radars. The unfolding of the CPR Doppler velocity is achieved using simple conditional rules and a smoothness requirement for the CPR Doppler measurements. The application of nonuniform beam-filling Doppler velocity bias-correction algorithms is found necessary even under these optimum conditions to reduce the CPR Doppler biases. Finally, the analysis indicates that a minimum along-track integration of 5000 m is needed to reduce the uncertainty in the CPR Doppler measurements to below 0.5 m s−1 and thus enable the detection of the melting layer and the characterization of the rain- and ice-layer Doppler velocities.
Abstract
The joint European Space Agency–Japan Aerospace Exploration Agency (ESA–JAXA) Earth Clouds, Aerosols and Radiation Explorer (EarthCARE) mission is scheduled for launch in 2016 and features the first atmospheric Cloud Profiling Radar (CPR) with Doppler capability in space. Here, the uncertainty of the CPR Doppler velocity measurements in cirrus clouds and large-scale precipitation areas is discussed. These regimes are characterized by weak vertical motion and relatively horizontally homogeneous conditions and thus represent optimum conditions for acquiring high-quality CPR Doppler measurements. A large dataset of radar reflectivity observations from ground-based radars is used to examine the homogeneity of the cloud fields at the horizontal scales of interest. In addition, a CPR instrument model that uses as input ground-based radar observations and outputs simulations of CPR Doppler measurements is described. The simulator accurately accounts for the beam geometry, nonuniform beam-filling, and signal integration effects, and it is applied to representative cases of cirrus cloud and stratiform precipitation. The simulated CPR Doppler velocities are compared against those derived from the ground-based radars. The unfolding of the CPR Doppler velocity is achieved using simple conditional rules and a smoothness requirement for the CPR Doppler measurements. The application of nonuniform beam-filling Doppler velocity bias-correction algorithms is found necessary even under these optimum conditions to reduce the CPR Doppler biases. Finally, the analysis indicates that a minimum along-track integration of 5000 m is needed to reduce the uncertainty in the CPR Doppler measurements to below 0.5 m s−1 and thus enable the detection of the melting layer and the characterization of the rain- and ice-layer Doppler velocities.
Abstract
Two-dimensional water vapor fields were retrieved by simulated measurements from multiple ground-based microwave radiometers using a tomographic approach. The goal of this paper was to investigate how the various aspects of the instrument setup (number and spacing of elevation angles and of instruments, number of frequencies, etc.) affected the quality of the retrieved field. This was done for two simulated atmospheric water vapor fields: 1) an exaggerated turbulent boundary layer and 2) a simplified water vapor front. An optimal estimation algorithm was used to obtain the tomographic field from the microwave radiometers and to evaluate the fidelity and information content of this retrieved field.
While the retrieval of the simplified front was reasonably successful, the retrieval could not reproduce the details of the turbulent boundary layer field even using up to nine instruments and 25 elevation angles. In addition, the vertical profile of the variability of the water vapor field could not be captured. An additional set of tests was performed using simulated data from a Raman lidar. Even with the detailed lidar measurements, the retrieval did not succeed except when the lidar data were used to define the a priori covariance matrix. This suggests that the main limitation to obtaining fine structures in a retrieved field using tomographic retrievals is the definition of the a priori covariance matrix.
Abstract
Two-dimensional water vapor fields were retrieved by simulated measurements from multiple ground-based microwave radiometers using a tomographic approach. The goal of this paper was to investigate how the various aspects of the instrument setup (number and spacing of elevation angles and of instruments, number of frequencies, etc.) affected the quality of the retrieved field. This was done for two simulated atmospheric water vapor fields: 1) an exaggerated turbulent boundary layer and 2) a simplified water vapor front. An optimal estimation algorithm was used to obtain the tomographic field from the microwave radiometers and to evaluate the fidelity and information content of this retrieved field.
While the retrieval of the simplified front was reasonably successful, the retrieval could not reproduce the details of the turbulent boundary layer field even using up to nine instruments and 25 elevation angles. In addition, the vertical profile of the variability of the water vapor field could not be captured. An additional set of tests was performed using simulated data from a Raman lidar. Even with the detailed lidar measurements, the retrieval did not succeed except when the lidar data were used to define the a priori covariance matrix. This suggests that the main limitation to obtaining fine structures in a retrieved field using tomographic retrievals is the definition of the a priori covariance matrix.
Abstract
The recent ship-based Marine ARM GCSS Pacific Cross-Section Intercomparison (GPCI) Investigation of Clouds (MAGIC) field campaign with the marine-capable Second ARM Mobile Facility (AMF2) deployed on the Horizon Lines cargo container M/V Spirit provided nearly 200 days of intraseasonal high-resolution observations of clouds, precipitation, and marine boundary layer (MBL) structure on multiple legs between Los Angeles, California, and Honolulu, Hawaii. During the deployment, MBL clouds exhibited a much higher frequency of occurrence than other cloud types and occurred more often in the warm season than in the cold season. MBL clouds demonstrated a propensity to produce precipitation, which often evaporated before reaching the ocean surface. The formation of stratocumulus is strongly correlated to a shallow MBL with a strong inversion and a weak transition, while cumulus formation is associated with a much weaker inversion and stronger transition. The estimated inversion strength is shown to depend seasonally on the potential temperature at 700 hPa. The location of the commencement of systematic MBL decoupling always occurred eastward of the locations of cloud breakup, and the systematic decoupling showed a strong moisture stratification. The entrainment of the dry warm air above the inversion appears to be the dominant factor triggering the systematic decoupling, while surface latent heat flux, precipitation, and diurnal circulation did not play major roles. MBL clouds broke up over a short spatial region due to the changes in the synoptic conditions, implying that in real atmospheric conditions the MBL clouds do not have enough time to evolve as in the idealized models.
Abstract
The recent ship-based Marine ARM GCSS Pacific Cross-Section Intercomparison (GPCI) Investigation of Clouds (MAGIC) field campaign with the marine-capable Second ARM Mobile Facility (AMF2) deployed on the Horizon Lines cargo container M/V Spirit provided nearly 200 days of intraseasonal high-resolution observations of clouds, precipitation, and marine boundary layer (MBL) structure on multiple legs between Los Angeles, California, and Honolulu, Hawaii. During the deployment, MBL clouds exhibited a much higher frequency of occurrence than other cloud types and occurred more often in the warm season than in the cold season. MBL clouds demonstrated a propensity to produce precipitation, which often evaporated before reaching the ocean surface. The formation of stratocumulus is strongly correlated to a shallow MBL with a strong inversion and a weak transition, while cumulus formation is associated with a much weaker inversion and stronger transition. The estimated inversion strength is shown to depend seasonally on the potential temperature at 700 hPa. The location of the commencement of systematic MBL decoupling always occurred eastward of the locations of cloud breakup, and the systematic decoupling showed a strong moisture stratification. The entrainment of the dry warm air above the inversion appears to be the dominant factor triggering the systematic decoupling, while surface latent heat flux, precipitation, and diurnal circulation did not play major roles. MBL clouds broke up over a short spatial region due to the changes in the synoptic conditions, implying that in real atmospheric conditions the MBL clouds do not have enough time to evolve as in the idealized models.
Why Mie?
Accurate Observations of Vertical Air Velocities and Raindrops Using a Cloud Radar
This article demonstrates an innovative method for the observation of vertical air motion and raindrop size distribution in precipitation using a 94-GHz Doppler radar. The method is particularly appealing since it is based on fundamental physics—the scattering of microwave radiation by large particles (Mie scattering). The technique was originally proposed in 1988 by Dr. Roger Lhermitte, who ironically pioneered the development of 94-GHz Doppler radars for the study of nonprecipitating clouds. Since then, no real effort for the evaluation and demonstration of the technique was undertaken. In this article, observations from stratiform rain are presented to illustrate the potential and accuracy of the method. The retrievals from this technique provide vertical air motion to an accuracy of 5–10 cm s−1. Despite attenuation, the Doppler velocity measurements remain unbiased and the data revealed high-resolution kinematical and microphysical structures within the stratiform precipitation for the first time. This article will hopefully expose the potential of this technique to the meteorological community and will serve as another example of the visionary contributions that Dr. Lhermitte has made to radar meteorology.
This article demonstrates an innovative method for the observation of vertical air motion and raindrop size distribution in precipitation using a 94-GHz Doppler radar. The method is particularly appealing since it is based on fundamental physics—the scattering of microwave radiation by large particles (Mie scattering). The technique was originally proposed in 1988 by Dr. Roger Lhermitte, who ironically pioneered the development of 94-GHz Doppler radars for the study of nonprecipitating clouds. Since then, no real effort for the evaluation and demonstration of the technique was undertaken. In this article, observations from stratiform rain are presented to illustrate the potential and accuracy of the method. The retrievals from this technique provide vertical air motion to an accuracy of 5–10 cm s−1. Despite attenuation, the Doppler velocity measurements remain unbiased and the data revealed high-resolution kinematical and microphysical structures within the stratiform precipitation for the first time. This article will hopefully expose the potential of this technique to the meteorological community and will serve as another example of the visionary contributions that Dr. Lhermitte has made to radar meteorology.
Abstract
Extended, high-resolution measurements of vertical air motion and median volume drop diameter D0 in widespread precipitation from three diverse Atmospheric Radiation Measurement Program (ARM) locations [Lamont, Oklahoma, Southern Great Plains site (SGP); Niamey, Niger; and Black Forest, Germany] are presented. The analysis indicates a weak (0–10 cm−1) downward air motion beneath the melting layer for all three regions, a magnitude that is to within the typical uncertainty of the retrieval methods. On average, the hourly estimated standard deviation of the vertical air motion is 0.25 m s−1 with no pronounced vertical structure. Profiles of D0 vary according to region and rainfall rate. The standard deviation of 1-min-averaged D0 profiles for isolated rainfall rate intervals is 0.3–0.4 mm. Additional insights into the form of the raindrop size distribution are provided using available dual-frequency Doppler velocity observations at SGP. The analysis suggests that gamma functions better explain paired velocity observations and radar retrievals for the Oklahoma dataset. This study will be useful in assessing uncertainties introduced in the measurement of precipitation parameters from ground-based and spaceborne remote sensors that are due to small-scale variability.
Abstract
Extended, high-resolution measurements of vertical air motion and median volume drop diameter D0 in widespread precipitation from three diverse Atmospheric Radiation Measurement Program (ARM) locations [Lamont, Oklahoma, Southern Great Plains site (SGP); Niamey, Niger; and Black Forest, Germany] are presented. The analysis indicates a weak (0–10 cm−1) downward air motion beneath the melting layer for all three regions, a magnitude that is to within the typical uncertainty of the retrieval methods. On average, the hourly estimated standard deviation of the vertical air motion is 0.25 m s−1 with no pronounced vertical structure. Profiles of D0 vary according to region and rainfall rate. The standard deviation of 1-min-averaged D0 profiles for isolated rainfall rate intervals is 0.3–0.4 mm. Additional insights into the form of the raindrop size distribution are provided using available dual-frequency Doppler velocity observations at SGP. The analysis suggests that gamma functions better explain paired velocity observations and radar retrievals for the Oklahoma dataset. This study will be useful in assessing uncertainties introduced in the measurement of precipitation parameters from ground-based and spaceborne remote sensors that are due to small-scale variability.
Abstract
Observations from the Atmospheric Radiation Measurement Program (ARM) site at Manus Island in the western Pacific and (re)analysis products are used to investigate moistening by shallow cumulus clouds and by the circulation in large-scale convective events. Large-scale convective events are defined as rainfall anomalies larger than one standard deviation for a minimum of three consecutive days over a 10° × 10° domain centered at Manus. These events are categorized into two groups: Madden–Julian oscillation (MJO) events, with eastward propagation, and non-MJO events, without propagation. Shallow cumulus clouds are identified as continuous time–height echoes from 1-min cloud radar observations with their tops below the freezing level and their bases within the boundary layer. Daily moistening tendencies of shallow clouds, estimated from differences between their mean liquid water content and precipitation over their presumed life spans, and those of physical processes and advection from (re)analysis products are compared with local moistening tendencies from soundings. Increases in low-level moisture before rainfall peaks of MJO and non-MJO events are evident in both observations and reanalyses. Before and after the rainfall peaks of these events, precipitating and nonprecipitating shallow clouds exist all the time, but their occurrence fluctuates randomly. Their contributions to moisture tendencies through evaporation of condensed water are evident. These clouds provide perpetual background moistening to the lower troposphere but do not cause the observed increase in low-level moisture leading to rainfall peaks. Such moisture increase is mainly caused by anomalous nonlinear zonal advection.
Abstract
Observations from the Atmospheric Radiation Measurement Program (ARM) site at Manus Island in the western Pacific and (re)analysis products are used to investigate moistening by shallow cumulus clouds and by the circulation in large-scale convective events. Large-scale convective events are defined as rainfall anomalies larger than one standard deviation for a minimum of three consecutive days over a 10° × 10° domain centered at Manus. These events are categorized into two groups: Madden–Julian oscillation (MJO) events, with eastward propagation, and non-MJO events, without propagation. Shallow cumulus clouds are identified as continuous time–height echoes from 1-min cloud radar observations with their tops below the freezing level and their bases within the boundary layer. Daily moistening tendencies of shallow clouds, estimated from differences between their mean liquid water content and precipitation over their presumed life spans, and those of physical processes and advection from (re)analysis products are compared with local moistening tendencies from soundings. Increases in low-level moisture before rainfall peaks of MJO and non-MJO events are evident in both observations and reanalyses. Before and after the rainfall peaks of these events, precipitating and nonprecipitating shallow clouds exist all the time, but their occurrence fluctuates randomly. Their contributions to moisture tendencies through evaporation of condensed water are evident. These clouds provide perpetual background moistening to the lower troposphere but do not cause the observed increase in low-level moisture leading to rainfall peaks. Such moisture increase is mainly caused by anomalous nonlinear zonal advection.
Abstract
Turbulence and drizzle-rate measurements from a large dataset of marine and continental low stratiform clouds are presented. Turbulence peaks at cloud base over land and near cloud top over the ocean. For both regions, eddy dissipation rate values of 10−5–10−2 m2 s−3 are observed. Surface-based measurements of cloud condensation nuclei number concentration N CCN and liquid water path (LWP) are used to estimate the precipitation susceptibility S 0. Results show that positive S 0 values are found at low turbulence, consistent with the principle that aerosols suppress precipitation formation, whereas S 0 is smaller, and can be negative, in a more turbulent environment. Under similar macrophysical conditions, especially for medium to high LWP, high (low) turbulence is likely to lessen (promote) the suppression effect of high N CCN on precipitation. Overall, the turbulent effect on S 0 is stronger in continental than marine stratiform clouds. These observational findings are consistent with recent analytical prediction for a turbulence-broadening effect on cloud droplet size distribution.
Abstract
Turbulence and drizzle-rate measurements from a large dataset of marine and continental low stratiform clouds are presented. Turbulence peaks at cloud base over land and near cloud top over the ocean. For both regions, eddy dissipation rate values of 10−5–10−2 m2 s−3 are observed. Surface-based measurements of cloud condensation nuclei number concentration N CCN and liquid water path (LWP) are used to estimate the precipitation susceptibility S 0. Results show that positive S 0 values are found at low turbulence, consistent with the principle that aerosols suppress precipitation formation, whereas S 0 is smaller, and can be negative, in a more turbulent environment. Under similar macrophysical conditions, especially for medium to high LWP, high (low) turbulence is likely to lessen (promote) the suppression effect of high N CCN on precipitation. Overall, the turbulent effect on S 0 is stronger in continental than marine stratiform clouds. These observational findings are consistent with recent analytical prediction for a turbulence-broadening effect on cloud droplet size distribution.
Abstract
This study uses eddy-permitting simulations to investigate the mechanisms that promote mesoscale variability of moisture in drizzling stratocumulus-topped marine boundary layers. Simulations show that precipitation tends to increase horizontal scales. Analysis of terms in the prognostic equation for total water mixing ratio variance indicates that moisture stratification plays a leading role in setting horizontal scales. This result is supported by simulations in which horizontal mean thermodynamic profiles are strongly nudged to their initial well-mixed state, which limits cloud scales. It is found that the spatial variability of subcloud moist cold pools surprisingly tends to respond to, rather than determine, the mesoscale variability, which may distinguish them from dry cold pools associated with deeper convection. Simulations also indicate that moisture stratification increases cloud scales specifically by increasing latent heating within updrafts, which increases updraft buoyancy and favors greater horizontal scales.
Abstract
This study uses eddy-permitting simulations to investigate the mechanisms that promote mesoscale variability of moisture in drizzling stratocumulus-topped marine boundary layers. Simulations show that precipitation tends to increase horizontal scales. Analysis of terms in the prognostic equation for total water mixing ratio variance indicates that moisture stratification plays a leading role in setting horizontal scales. This result is supported by simulations in which horizontal mean thermodynamic profiles are strongly nudged to their initial well-mixed state, which limits cloud scales. It is found that the spatial variability of subcloud moist cold pools surprisingly tends to respond to, rather than determine, the mesoscale variability, which may distinguish them from dry cold pools associated with deeper convection. Simulations also indicate that moisture stratification increases cloud scales specifically by increasing latent heating within updrafts, which increases updraft buoyancy and favors greater horizontal scales.
