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Abstract
A topic of current practical interest is the accurate characterization of the synoptic-scale atmospheric state from wind profiler and radiosonde network observations. The authors have examined several related and commonly applied objective analysis techniques for performing this characterization and considered their associated level of uncertainty both from a theoretical and a practical standpoint. A case study is presented where two wind profiler triangles with nearly identical centroids and no common vertices produced strikingly different results during a 43-h period. It is concluded that the uncertainty in objectively analyzed quantities can easily be as large as the expected synoptic-scale signal. In order to quantify the statistical precision of the algorithms, the authors conducted a realistic observing system simulation experiment using output from a mesoscale model. A simple parameterization for estimating the uncertainty in horizontal gradient quantities in terms of known errors in the objectively analyzed wind components and temperature is developed from these results.
Abstract
A topic of current practical interest is the accurate characterization of the synoptic-scale atmospheric state from wind profiler and radiosonde network observations. The authors have examined several related and commonly applied objective analysis techniques for performing this characterization and considered their associated level of uncertainty both from a theoretical and a practical standpoint. A case study is presented where two wind profiler triangles with nearly identical centroids and no common vertices produced strikingly different results during a 43-h period. It is concluded that the uncertainty in objectively analyzed quantities can easily be as large as the expected synoptic-scale signal. In order to quantify the statistical precision of the algorithms, the authors conducted a realistic observing system simulation experiment using output from a mesoscale model. A simple parameterization for estimating the uncertainty in horizontal gradient quantities in terms of known errors in the objectively analyzed wind components and temperature is developed from these results.
Abstract
Collocated active and passive remote sensing measurements collected at U.S. Department of Energy Atmospheric Radiation Measurement Program sites enable simultaneous retrieval of cloud and precipitation properties and air motion. Previous studies indicate the parameters of a bimodal cloud particle size distribution can be effectively constrained using a combination of passive microwave radiometer and radar observations; however, aspects of the particle size distribution and particle shape are typically assumed to be known. In addition, many retrievals assume the observation and retrieval error statistics have Gaussian distributions and use least squares minimization techniques to find a solution. In truth, the retrieval error characteristics are largely unknown. Markov chain Monte Carlo (MCMC) methods can be used to produce a robust estimate of the probability distribution of a retrieved quantity that is nonlinearly related to the measurements and that has non-Gaussian error statistics. In this work, an MCMC algorithm is used to explore the error characteristics of cloud property retrievals from surface-based W-band radar and low-frequency microwave radiometer observations for a case of orographic snowfall. In this particular case, it is found that a combination of passive microwave radiometer measurements with radar reflectivity and Doppler velocity is sufficient to constrain the liquid and ice particle size distributions, but only if the width parameter of the assumed gamma particle size distribution and mass–dimensional relationships are specified. If the width parameter and mass–dimensional relationships are allowed to vary realistically, a unique retrieval of the liquid and ice particle size distribution for this orographic snowfall case is rendered far more problematic.
Abstract
Collocated active and passive remote sensing measurements collected at U.S. Department of Energy Atmospheric Radiation Measurement Program sites enable simultaneous retrieval of cloud and precipitation properties and air motion. Previous studies indicate the parameters of a bimodal cloud particle size distribution can be effectively constrained using a combination of passive microwave radiometer and radar observations; however, aspects of the particle size distribution and particle shape are typically assumed to be known. In addition, many retrievals assume the observation and retrieval error statistics have Gaussian distributions and use least squares minimization techniques to find a solution. In truth, the retrieval error characteristics are largely unknown. Markov chain Monte Carlo (MCMC) methods can be used to produce a robust estimate of the probability distribution of a retrieved quantity that is nonlinearly related to the measurements and that has non-Gaussian error statistics. In this work, an MCMC algorithm is used to explore the error characteristics of cloud property retrievals from surface-based W-band radar and low-frequency microwave radiometer observations for a case of orographic snowfall. In this particular case, it is found that a combination of passive microwave radiometer measurements with radar reflectivity and Doppler velocity is sufficient to constrain the liquid and ice particle size distributions, but only if the width parameter of the assumed gamma particle size distribution and mass–dimensional relationships are specified. If the width parameter and mass–dimensional relationships are allowed to vary realistically, a unique retrieval of the liquid and ice particle size distribution for this orographic snowfall case is rendered far more problematic.
Abstract
Empirical knowledge of how cirrus cloud properties are coupled with the large-scale meteorological environment is a prerequisite for understanding the role of microphysical processes in the life cycle of cirrus cloud systems. Using active and passive remote sensing data from the A-Train, relationships between cirrus cloud properties and the large-scale dynamics are examined. Mesoscale cirrus events from along the A-Train track from 1 yr of data are sorted on the basis of vertical distributions of radar reflectivity and on large-scale meteorological parameters derived from the NCEP–NCAR reanalysis using a K-means cluster-analysis algorithm. With these defined regimes, the authors examine two questions: Given a cirrus cloud type defined by cloud properties, what are the large-scale dynamics? Vice versa, what cirrus cloud properties tend to emerge from large-scale dynamics regimes that tend to form cirrus? From the answers to these questions, the links between the large-scale dynamics regimes and the genre of cirrus that evolve within these regimes are identified. It is found that, to a considerable extent, the large-scale environment determines the bulk cirrus properties and that, within the dynamics regimes, cirrus cloud systems tend to evolve through life cycles, the details of which are not necessarily explained by the large-scale motions alone. These results suggest that, while simple relationships may be used to parameterize the gross properties of cirrus, more sophisticated parameterizations are required for representing the detailed structure and radiative feedbacks of these clouds.
Abstract
Empirical knowledge of how cirrus cloud properties are coupled with the large-scale meteorological environment is a prerequisite for understanding the role of microphysical processes in the life cycle of cirrus cloud systems. Using active and passive remote sensing data from the A-Train, relationships between cirrus cloud properties and the large-scale dynamics are examined. Mesoscale cirrus events from along the A-Train track from 1 yr of data are sorted on the basis of vertical distributions of radar reflectivity and on large-scale meteorological parameters derived from the NCEP–NCAR reanalysis using a K-means cluster-analysis algorithm. With these defined regimes, the authors examine two questions: Given a cirrus cloud type defined by cloud properties, what are the large-scale dynamics? Vice versa, what cirrus cloud properties tend to emerge from large-scale dynamics regimes that tend to form cirrus? From the answers to these questions, the links between the large-scale dynamics regimes and the genre of cirrus that evolve within these regimes are identified. It is found that, to a considerable extent, the large-scale environment determines the bulk cirrus properties and that, within the dynamics regimes, cirrus cloud systems tend to evolve through life cycles, the details of which are not necessarily explained by the large-scale motions alone. These results suggest that, while simple relationships may be used to parameterize the gross properties of cirrus, more sophisticated parameterizations are required for representing the detailed structure and radiative feedbacks of these clouds.
Abstract
A record of single-layer and overcast low-level Arctic stratus cloud properties has been generated using data collected from May to September 2000 at the Atmospheric Radiation Measurement (ARM) North Slope of Alaska (NSA) (71.3°N, 156.6°W) site near Barrow, Alaska. The record includes liquid-phase and liquid dominant mixed-phase Arctic stratus macrophysical, microphysical, and radiative properties, as well as surface radiation budget and cloud radiative forcing. The macrophysical properties consist of cloud fractions, cloud-base/top heights and temperatures, and cloud thickness derived from a ground-based radar and lidar pair, and rawinsonde sounding. The microphysical properties include cloud liquid water path and content, and cloud-droplet effective radius and number concentration obtained from microwave radiometer brightness temperature measurements, and the new cloud parameterization. The radiative properties contain cloud optical depth, effective solar transmission, and surface/cloud/top-of-atmosphere albedos derived from the new cloud parameterization and standard Epply precision spectral pyranometers. The shortwave, longwave, and net cloud radiative forcings at the surface are inferred from measurements by standard Epply precision spectral pyranometers and pyrgeometers. There are approximately 300 h and more than 3600 samples (5-min resolution) of single-layer and overcast low-level stratus during the study period. The 10-day averaged total and low-level cloud (Z top < 3 km) fractions are 0.87 and 0.55, and low-level cloud-base and -top heights are around 0.4 and 0.8 km. The cloud-droplet effective radii and number concentrations in the spring are similar to midlatitude continental stratus cloud microphysical properties, and in the summer they are similar to midlatitude marine stratus clouds. The total cloud fractions in this study show good agreement with the satellite and surface results compiled from data collected during the First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment (FIRE) Arctic Cloud Experiment (ACE) and the Surface Heat Budget of the Arctic Ocean (SHEBA) (∼77°N, 165°W) field experiments in 1998. The cloud microphysics derived from this study are similar, in general, to those collected in past field programs, although these comparisons are based on data collected at different locations and years. At the ARM NSA site, the summer cooling period is much longer (2–3 months vs 1–2 weeks), and the summer cooling magnitude is much larger (−100 W m−2 vs −5 W m−2) than at the SHEBA ship under the conditions of all skies at the SHEBA and overcast low-level stratus clouds at the NSA site.
Abstract
A record of single-layer and overcast low-level Arctic stratus cloud properties has been generated using data collected from May to September 2000 at the Atmospheric Radiation Measurement (ARM) North Slope of Alaska (NSA) (71.3°N, 156.6°W) site near Barrow, Alaska. The record includes liquid-phase and liquid dominant mixed-phase Arctic stratus macrophysical, microphysical, and radiative properties, as well as surface radiation budget and cloud radiative forcing. The macrophysical properties consist of cloud fractions, cloud-base/top heights and temperatures, and cloud thickness derived from a ground-based radar and lidar pair, and rawinsonde sounding. The microphysical properties include cloud liquid water path and content, and cloud-droplet effective radius and number concentration obtained from microwave radiometer brightness temperature measurements, and the new cloud parameterization. The radiative properties contain cloud optical depth, effective solar transmission, and surface/cloud/top-of-atmosphere albedos derived from the new cloud parameterization and standard Epply precision spectral pyranometers. The shortwave, longwave, and net cloud radiative forcings at the surface are inferred from measurements by standard Epply precision spectral pyranometers and pyrgeometers. There are approximately 300 h and more than 3600 samples (5-min resolution) of single-layer and overcast low-level stratus during the study period. The 10-day averaged total and low-level cloud (Z top < 3 km) fractions are 0.87 and 0.55, and low-level cloud-base and -top heights are around 0.4 and 0.8 km. The cloud-droplet effective radii and number concentrations in the spring are similar to midlatitude continental stratus cloud microphysical properties, and in the summer they are similar to midlatitude marine stratus clouds. The total cloud fractions in this study show good agreement with the satellite and surface results compiled from data collected during the First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment (FIRE) Arctic Cloud Experiment (ACE) and the Surface Heat Budget of the Arctic Ocean (SHEBA) (∼77°N, 165°W) field experiments in 1998. The cloud microphysics derived from this study are similar, in general, to those collected in past field programs, although these comparisons are based on data collected at different locations and years. At the ARM NSA site, the summer cooling period is much longer (2–3 months vs 1–2 weeks), and the summer cooling magnitude is much larger (−100 W m−2 vs −5 W m−2) than at the SHEBA ship under the conditions of all skies at the SHEBA and overcast low-level stratus clouds at the NSA site.
Abstract
Assumptions regarding the vertical overlap characteristics of horizontal cloudy layers have been shown to be important to both the radiation transfer and the cloud microphysics that are predicted in general circulation models. Certain reasonable assumptions regarding cloud-layer overlap have been applied in models up to now where vertically continuous cloudy layers were assumed to overlap maximally leading to a minimum in cloud cover, and layers separated by noncloudy layers were assumed to overlap randomly. However, these assumptions have not been systematically evaluated with a comprehensive dataset that can resolve simultaneously occurring cloud layers. Presented here is an analysis of cloud-layer overlap characteristics derived from 103 months of cloud radar data collected by continuously operating millimeter-wavelength instruments deployed at the Atmospheric Radiation Measurement (ARM) sites in the Tropics, middle latitudes, and the Arctic. Using an approach recently proposed by Hogan and Illingworth, it is shown that an assumption of random overlap for layers separated by noncloudy layers is supported by observations. However, that the overlap characteristics of vertically continuous layers cannot be considered maximal is also shown. Indeed, vertically continuous cloudy layers do not appear to lend themselves to a simple overlap assumption. Therefore, to avoid significant biases in diagnosed cloud cover, the overlap properties of these layers in models will need to be parameterized. It is shown that the cloud-layer overlap characteristics in the middle latitudes do appear to be a strong function of season, suggesting that an overlap parameterization in terms of cloud system type may be possible.
Abstract
Assumptions regarding the vertical overlap characteristics of horizontal cloudy layers have been shown to be important to both the radiation transfer and the cloud microphysics that are predicted in general circulation models. Certain reasonable assumptions regarding cloud-layer overlap have been applied in models up to now where vertically continuous cloudy layers were assumed to overlap maximally leading to a minimum in cloud cover, and layers separated by noncloudy layers were assumed to overlap randomly. However, these assumptions have not been systematically evaluated with a comprehensive dataset that can resolve simultaneously occurring cloud layers. Presented here is an analysis of cloud-layer overlap characteristics derived from 103 months of cloud radar data collected by continuously operating millimeter-wavelength instruments deployed at the Atmospheric Radiation Measurement (ARM) sites in the Tropics, middle latitudes, and the Arctic. Using an approach recently proposed by Hogan and Illingworth, it is shown that an assumption of random overlap for layers separated by noncloudy layers is supported by observations. However, that the overlap characteristics of vertically continuous layers cannot be considered maximal is also shown. Indeed, vertically continuous cloudy layers do not appear to lend themselves to a simple overlap assumption. Therefore, to avoid significant biases in diagnosed cloud cover, the overlap properties of these layers in models will need to be parameterized. It is shown that the cloud-layer overlap characteristics in the middle latitudes do appear to be a strong function of season, suggesting that an overlap parameterization in terms of cloud system type may be possible.
Abstract
Data collected at the Atmospheric Radiation Measurement (ARM) Program ground sites allow for the description of the atmospheric thermodynamic state, cloud occurrence, and cloud properties. This information allows for the derivation of estimates of the effects of clouds on the radiation budget of the surface and atmosphere. Herein 8 yr of continuous data collected at the ARM Southern Great Plains (SGP) Climate Research Facility (ACRF) are analyzed, and the influence of clouds on the radiative flux divergence of solar and infrared energy on annual, seasonal, and monthly time scales is documented. Given the uncertainties in derived cloud microphysical properties that result in calculated radiant flux errors, it is demonstrated that the ability to quantitatively resolve all but the largest heating and cooling influences by clouds is marginal for averaging periods less than 1 month. Concentrating on seasonal and monthly averages, it is found that the net column-integrated radiative effect of clouds on the atmosphere is nearly neutral at this middle-latitude location. However, a net heating of the upper troposphere by upper-tropospheric clouds and a cooling of the lower troposphere by boundary layer clouds is documented. The balance evolves over the course of an annual cycle as the troposphere deepens in summer and boundary layer clouds become less frequent relative to upper-tropospheric clouds. Although the top-of-atmosphere IR radiative effect is nearly invariant through the annual cycle, the seasonally varying heating profile is determined largely by the convergence of IR flux because solar heating is offset by IR cooling within the column.
Abstract
Data collected at the Atmospheric Radiation Measurement (ARM) Program ground sites allow for the description of the atmospheric thermodynamic state, cloud occurrence, and cloud properties. This information allows for the derivation of estimates of the effects of clouds on the radiation budget of the surface and atmosphere. Herein 8 yr of continuous data collected at the ARM Southern Great Plains (SGP) Climate Research Facility (ACRF) are analyzed, and the influence of clouds on the radiative flux divergence of solar and infrared energy on annual, seasonal, and monthly time scales is documented. Given the uncertainties in derived cloud microphysical properties that result in calculated radiant flux errors, it is demonstrated that the ability to quantitatively resolve all but the largest heating and cooling influences by clouds is marginal for averaging periods less than 1 month. Concentrating on seasonal and monthly averages, it is found that the net column-integrated radiative effect of clouds on the atmosphere is nearly neutral at this middle-latitude location. However, a net heating of the upper troposphere by upper-tropospheric clouds and a cooling of the lower troposphere by boundary layer clouds is documented. The balance evolves over the course of an annual cycle as the troposphere deepens in summer and boundary layer clouds become less frequent relative to upper-tropospheric clouds. Although the top-of-atmosphere IR radiative effect is nearly invariant through the annual cycle, the seasonally varying heating profile is determined largely by the convergence of IR flux because solar heating is offset by IR cooling within the column.
Abstract
The International Satellite Cloud Climatology Project (ISCCP) provides a multidecadal and global description of cloud properties that are often grouped into joint histograms of column visible optical depth τ and effective cloud-top pressure P top. It has not been possible until recently to know the actual distributions of hydrometeor layers within the ISCCP P top–τ bins. Distributions of hydrometeor layers within the ISCCP P top–τ conditional probability space using measurements from the CloudSat Cloud Profiling Radar and the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) lidar within two 40° × 40° regions in the eastern and western equatorial Pacific over a 2-yr period are examined. With the exception of thin cirrus and stratocumulus, the authors show that of the P top–τ types that are commonly analyzed, none of the types contain unique distributions of geometrically defined layer types but tend to be populated by diverse sets of hydrometeor layers whose bulk profile properties conspire to render specific radiative signatures when interpreted by two-channel visible and IR sensors from space. In comparing the geometric distribution of cloud layers for common P top–τ types, it is found that the ISCCP Cirrostratus, Deep Convection, and Stratocumulus types appear to have been drawn from a common geometric distribution of hydrometeor layers. The other six common ISCCP P top–τ types do not share this feature. The authors can confidently reject an assumption that even though they have common top-of-atmosphere radiative signatures, they do not appear to share a common distribution of cloud layers and therefore are likely to have significantly different radiative heating profiles and different surface radiative forcing even though their top-of-atmosphere radiative signatures are similar.
Abstract
The International Satellite Cloud Climatology Project (ISCCP) provides a multidecadal and global description of cloud properties that are often grouped into joint histograms of column visible optical depth τ and effective cloud-top pressure P top. It has not been possible until recently to know the actual distributions of hydrometeor layers within the ISCCP P top–τ bins. Distributions of hydrometeor layers within the ISCCP P top–τ conditional probability space using measurements from the CloudSat Cloud Profiling Radar and the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) lidar within two 40° × 40° regions in the eastern and western equatorial Pacific over a 2-yr period are examined. With the exception of thin cirrus and stratocumulus, the authors show that of the P top–τ types that are commonly analyzed, none of the types contain unique distributions of geometrically defined layer types but tend to be populated by diverse sets of hydrometeor layers whose bulk profile properties conspire to render specific radiative signatures when interpreted by two-channel visible and IR sensors from space. In comparing the geometric distribution of cloud layers for common P top–τ types, it is found that the ISCCP Cirrostratus, Deep Convection, and Stratocumulus types appear to have been drawn from a common geometric distribution of hydrometeor layers. The other six common ISCCP P top–τ types do not share this feature. The authors can confidently reject an assumption that even though they have common top-of-atmosphere radiative signatures, they do not appear to share a common distribution of cloud layers and therefore are likely to have significantly different radiative heating profiles and different surface radiative forcing even though their top-of-atmosphere radiative signatures are similar.
Abstract
The algorithm described in Part I has been applied to the millimeter cloud radar observations from January 1999 to December 2005 at the Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) and Tropical Western Pacific (including Manus and Nauru) sites. Approximately 10 000 cirrus hours from each of these sites were analyzed. Retrieved cloud properties including condensed mass, particle size, optical depth, and in-cloud vertical air motions were analyzed in terms of their geographical, seasonal, and diurnal variations. The analysis shows that tropical ice clouds observed by millimeter radar are very different from ice clouds at SGP, with the tropical clouds having slightly larger particle sizes and greater ice masses and being more likely to be associated with ascending air motions, in addition to being colder and higher in altitude. A positive residual of derived in-cloud air motion found in the tropical data likely provides evidence for lofting of air into the tropopause transition layer as a result of radiative heating. The midlatitude cirrus demonstrate strong seasonal variations with more frequent, thicker clouds occurring during the summer than during the winter. Very subtle seasonal variations are found for tropical ice clouds, and evidence is presented that cirrus properties vary interannually and are correlated with El Niño oscillations. In addition, it is found that tropical cirrus demonstrate a stronger diurnal cycle than cirrus of the midlatitudes, with the in-cloud updrafts peaking in the early afternoon.
Abstract
The algorithm described in Part I has been applied to the millimeter cloud radar observations from January 1999 to December 2005 at the Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) and Tropical Western Pacific (including Manus and Nauru) sites. Approximately 10 000 cirrus hours from each of these sites were analyzed. Retrieved cloud properties including condensed mass, particle size, optical depth, and in-cloud vertical air motions were analyzed in terms of their geographical, seasonal, and diurnal variations. The analysis shows that tropical ice clouds observed by millimeter radar are very different from ice clouds at SGP, with the tropical clouds having slightly larger particle sizes and greater ice masses and being more likely to be associated with ascending air motions, in addition to being colder and higher in altitude. A positive residual of derived in-cloud air motion found in the tropical data likely provides evidence for lofting of air into the tropopause transition layer as a result of radiative heating. The midlatitude cirrus demonstrate strong seasonal variations with more frequent, thicker clouds occurring during the summer than during the winter. Very subtle seasonal variations are found for tropical ice clouds, and evidence is presented that cirrus properties vary interannually and are correlated with El Niño oscillations. In addition, it is found that tropical cirrus demonstrate a stronger diurnal cycle than cirrus of the midlatitudes, with the in-cloud updrafts peaking in the early afternoon.
Abstract
The properties of clouds derived using a suite of remote sensors on board the Australian research vessel (R/V) Investigator during the 5-week Clouds, Aerosols, Precipitation, Radiation, and Atmospheric Composition over the Southern Ocean (CAPRICORN) voyage south of Australia during March and April 2016 are examined and compared to similar measurements collected by CloudSat and CALIPSO (CC) and from data collected at Graciosa Island, Azores (GRW). In addition, we use depolarization lidar data to examine the thermodynamic phase partitioning as a function of temperature and compare those statistics to similar information reported from the CALIPSO lidar in low-Earth orbit. We find that cloud cover during CAPRICORN was 76%, dominated by clouds based in the marine boundary layer. This was lower than comparable measurements collected by CC during these months, although the CC dataset observed significantly more high clouds. In the surface-based data, approximately 2/3 (1/2) of all low-level layers observed had a reflectivity below −20 dBZ in the CAPRICORN data (GRW) with 30% (20%) of the layers observed only by the lidar. The phase partitioning in layers based in the lower 4 km of the atmosphere was similar in the two surface-based datasets, indicating a greater occurrence of the ice phase in subfreezing low clouds than what is reported from analysis of CALIPSO data.
Abstract
The properties of clouds derived using a suite of remote sensors on board the Australian research vessel (R/V) Investigator during the 5-week Clouds, Aerosols, Precipitation, Radiation, and Atmospheric Composition over the Southern Ocean (CAPRICORN) voyage south of Australia during March and April 2016 are examined and compared to similar measurements collected by CloudSat and CALIPSO (CC) and from data collected at Graciosa Island, Azores (GRW). In addition, we use depolarization lidar data to examine the thermodynamic phase partitioning as a function of temperature and compare those statistics to similar information reported from the CALIPSO lidar in low-Earth orbit. We find that cloud cover during CAPRICORN was 76%, dominated by clouds based in the marine boundary layer. This was lower than comparable measurements collected by CC during these months, although the CC dataset observed significantly more high clouds. In the surface-based data, approximately 2/3 (1/2) of all low-level layers observed had a reflectivity below −20 dBZ in the CAPRICORN data (GRW) with 30% (20%) of the layers observed only by the lidar. The phase partitioning in layers based in the lower 4 km of the atmosphere was similar in the two surface-based datasets, indicating a greater occurrence of the ice phase in subfreezing low clouds than what is reported from analysis of CALIPSO data.
Abstract
The properties of clouds derived from measurements collected using a suite of remote sensors on board the Australian R/V Investigator during a 5-week voyage into the Southern Ocean during March and April 2016 are examined. Based on the findings presented in a companion paper (Part I), we focus our attention on a subset of marine boundary layer (MBL) clouds that form a substantial portion of the cloud-coverage fraction. We find that the MBL clouds that dominate the coverage fraction tend to occur in decoupled boundary layers near the base of marine inversions. The thermodynamic conditions under which these clouds are found are reminiscent of marine stratocumulus studied extensively in the subtropical eastern ocean basins except that here they are often supercooled with a rare presence of the ice phase, quite tenuous in terms of their physical properties, rarely drizzling, and tend to occur in migratory high pressure systems in cold-air advection. We develop a simple cloud property retrieval algorithm that uses as input the lidar-attenuated backscatter, the W-band radar reflectivity, and the 31-GHz brightness temperature. We find that the stratocumulus clouds examined have water paths in the 15–25 g m−2 range, effective radii near 8 μm, and number concentrations in the 20 cm−3 range in the Southern Ocean with optical depths in the range of 3–4. We speculate that addressing the high bias in absorbed shortwave radiation in climate models will require understanding the processes that form and maintain these marine stratocumulus clouds in southern mid- and high latitudes.
Abstract
The properties of clouds derived from measurements collected using a suite of remote sensors on board the Australian R/V Investigator during a 5-week voyage into the Southern Ocean during March and April 2016 are examined. Based on the findings presented in a companion paper (Part I), we focus our attention on a subset of marine boundary layer (MBL) clouds that form a substantial portion of the cloud-coverage fraction. We find that the MBL clouds that dominate the coverage fraction tend to occur in decoupled boundary layers near the base of marine inversions. The thermodynamic conditions under which these clouds are found are reminiscent of marine stratocumulus studied extensively in the subtropical eastern ocean basins except that here they are often supercooled with a rare presence of the ice phase, quite tenuous in terms of their physical properties, rarely drizzling, and tend to occur in migratory high pressure systems in cold-air advection. We develop a simple cloud property retrieval algorithm that uses as input the lidar-attenuated backscatter, the W-band radar reflectivity, and the 31-GHz brightness temperature. We find that the stratocumulus clouds examined have water paths in the 15–25 g m−2 range, effective radii near 8 μm, and number concentrations in the 20 cm−3 range in the Southern Ocean with optical depths in the range of 3–4. We speculate that addressing the high bias in absorbed shortwave radiation in climate models will require understanding the processes that form and maintain these marine stratocumulus clouds in southern mid- and high latitudes.
