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- Author or Editor: Pavlos Kollias x
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Abstract
Fair-weather cumuli are fundamental in regulating the vertical structure of water vapor and entropy in the lowest 2–3 km of the earth’s atmosphere over vast areas of the oceans. In this study, a long record of profiling cloud radar observations at the Atmospheric Radiation Measurement Program (ARM) Climate Research Facility (ACRF) at Nauru Island is used to investigate cloud vertical air motion statistics over an 8-yr observing period. Appropriate processing of the observed low radar reflectivities provides radar volume samples that contain only small cloud droplets; thus, the Doppler velocities are used as air motion tracers. The technique is applied to shallow boundary layer clouds (less than 1000 m thick) during the 1999–2007 period when radar data are available. Using the boundary layer winds from the soundings obtained at the Nauru ACRF, the fair-weather cumuli fields are classified in easterly and westerly boundary layer wind regimes. This distinction is necessary to separate marine-forced (westerlies) from land-forced (easterlies) shallow clouds because of a well-studied island effect at the Nauru ACRF. The two regimes exhibit large diurnal differences in cloud fraction and cloud dynamics as manifested by the analysis of the hourly averaged vertical air motion statistics. The fair-weather cumuli fields associated with easterlies exhibit a strong diurnal cycle in cloud fraction and updraft strength and fraction, indicating a strong influence of land-forced clouds. In contrast over the fair-weather cumuli with oceanic origin, land-forced clouds are characterized by uniform diurnal cloudiness and persistent updrafts at the cloud-base level. This study provides a unique observational dataset appropriate for testing fair-weather cumulus mass flux and turbulence parameterizations in numerical models.
Abstract
Fair-weather cumuli are fundamental in regulating the vertical structure of water vapor and entropy in the lowest 2–3 km of the earth’s atmosphere over vast areas of the oceans. In this study, a long record of profiling cloud radar observations at the Atmospheric Radiation Measurement Program (ARM) Climate Research Facility (ACRF) at Nauru Island is used to investigate cloud vertical air motion statistics over an 8-yr observing period. Appropriate processing of the observed low radar reflectivities provides radar volume samples that contain only small cloud droplets; thus, the Doppler velocities are used as air motion tracers. The technique is applied to shallow boundary layer clouds (less than 1000 m thick) during the 1999–2007 period when radar data are available. Using the boundary layer winds from the soundings obtained at the Nauru ACRF, the fair-weather cumuli fields are classified in easterly and westerly boundary layer wind regimes. This distinction is necessary to separate marine-forced (westerlies) from land-forced (easterlies) shallow clouds because of a well-studied island effect at the Nauru ACRF. The two regimes exhibit large diurnal differences in cloud fraction and cloud dynamics as manifested by the analysis of the hourly averaged vertical air motion statistics. The fair-weather cumuli fields associated with easterlies exhibit a strong diurnal cycle in cloud fraction and updraft strength and fraction, indicating a strong influence of land-forced clouds. In contrast over the fair-weather cumuli with oceanic origin, land-forced clouds are characterized by uniform diurnal cloudiness and persistent updrafts at the cloud-base level. This study provides a unique observational dataset appropriate for testing fair-weather cumulus mass flux and turbulence parameterizations in numerical models.
Abstract
Ice cloud properties are influenced by cloud-scale vertical air motion. Dynamical properties of ice clouds can be determined via Doppler measurements from ground-based, profiling cloud radars. Here, the decomposition of the Doppler velocities into reflectivity-weighted particle velocity Vt and vertical air motion w is described. The methodology is applied to high clouds observations from 35-GHz profiling millimeter wavelength radars at the Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) climate research facility in Oklahoma (January 1997–December 2010) and the ARM Tropical Western Pacific (TWP) site in Manus (July 1999–December 2010). The Doppler velocity measurements are used to detect gravity waves (GW), whose correlation with high cloud macrophysical properties is investigated. Cloud turbulence is studied in the absence and presence of GW. High clouds are less turbulent when GW are observed. Probability density functions of Vt , w, and high cloud macrophysical properties for the two cloud subsets (with and without GW) are presented. Air-density-corrected Vt for high clouds for which GW (no GW) were detected amounted to hourly means and standard deviations of 0.89 ± 0.52 m s−1 (0.8 ± 0.48 m s−1) and 1.03 ± 0.41 m s−1 (0.86 ± 0.49 m s−1) at SGP and Manus, respectively. The error of w at one standard deviation was estimated as 0.15 m s−1. Hourly means of w averaged around 0 m s−1 with standard deviations of ±0.27 (SGP) and ±0.29 m s−1 (Manus) for high clouds without GW and ±0.22 m s−1 (both sites) for high clouds with GW. The midlatitude site showed stronger seasonality in detected high cloud properties.
Abstract
Ice cloud properties are influenced by cloud-scale vertical air motion. Dynamical properties of ice clouds can be determined via Doppler measurements from ground-based, profiling cloud radars. Here, the decomposition of the Doppler velocities into reflectivity-weighted particle velocity Vt and vertical air motion w is described. The methodology is applied to high clouds observations from 35-GHz profiling millimeter wavelength radars at the Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) climate research facility in Oklahoma (January 1997–December 2010) and the ARM Tropical Western Pacific (TWP) site in Manus (July 1999–December 2010). The Doppler velocity measurements are used to detect gravity waves (GW), whose correlation with high cloud macrophysical properties is investigated. Cloud turbulence is studied in the absence and presence of GW. High clouds are less turbulent when GW are observed. Probability density functions of Vt , w, and high cloud macrophysical properties for the two cloud subsets (with and without GW) are presented. Air-density-corrected Vt for high clouds for which GW (no GW) were detected amounted to hourly means and standard deviations of 0.89 ± 0.52 m s−1 (0.8 ± 0.48 m s−1) and 1.03 ± 0.41 m s−1 (0.86 ± 0.49 m s−1) at SGP and Manus, respectively. The error of w at one standard deviation was estimated as 0.15 m s−1. Hourly means of w averaged around 0 m s−1 with standard deviations of ±0.27 (SGP) and ±0.29 m s−1 (Manus) for high clouds without GW and ±0.22 m s−1 (both sites) for high clouds with GW. The midlatitude site showed stronger seasonality in detected high cloud properties.
Abstract
The recent deployment of the Atmospheric Radiation Measurement Program (ARM) Mobile Facility at Graciosa Island, Azores, in the context of the Clouds, Aerosol and Precipitation in the Marine Boundary Layer (CAP-MBL) field campaign added the most extensive (19 months) and comprehensive dataset of marine boundary layer (MBL) clouds to date. Cloud occurrence is high (60%–80%), with a summertime minimum. Liquid precipitation is frequently present (30%–40%), mainly in the form of virga. Boundary layer clouds are the most frequently observed cloud type (40%–50%) with a maximum of occurrence during the summer and fall months under the presence of anticyclonic conditions. Cumulus clouds are the most frequently occurring MBL cloud type (20%) with cumulus under stratocumulus layers (10%–30%) and single-layer stratocumulus (0%–10%) following in frequency of occurrence. A stable transition layer in the subcloud layer is commonly observed (92% of the soundings). Cumulus cloud bases and stratocumulus cloud tops correlate very well with the top of the transition layer and the inversion base, respectively. Drizzling stratocumulus layers are thicker (350–400 m) and have higher liquid water path (75–150 g m−2) than their nondrizzling counterparts (100–250 m and 30–75 g m−2, respectively). The variance of the vertical air motion is maximum near the cloud base and is higher at night. The updraft mass flux is around 0.17 kg m−2 s−1 with 40%–60% explained by coherent updraft structures. Despite a high frequency of stratocumulus clouds in the Azores, the MBL is almost never well mixed and is often cumulus coupled.
Abstract
The recent deployment of the Atmospheric Radiation Measurement Program (ARM) Mobile Facility at Graciosa Island, Azores, in the context of the Clouds, Aerosol and Precipitation in the Marine Boundary Layer (CAP-MBL) field campaign added the most extensive (19 months) and comprehensive dataset of marine boundary layer (MBL) clouds to date. Cloud occurrence is high (60%–80%), with a summertime minimum. Liquid precipitation is frequently present (30%–40%), mainly in the form of virga. Boundary layer clouds are the most frequently observed cloud type (40%–50%) with a maximum of occurrence during the summer and fall months under the presence of anticyclonic conditions. Cumulus clouds are the most frequently occurring MBL cloud type (20%) with cumulus under stratocumulus layers (10%–30%) and single-layer stratocumulus (0%–10%) following in frequency of occurrence. A stable transition layer in the subcloud layer is commonly observed (92% of the soundings). Cumulus cloud bases and stratocumulus cloud tops correlate very well with the top of the transition layer and the inversion base, respectively. Drizzling stratocumulus layers are thicker (350–400 m) and have higher liquid water path (75–150 g m−2) than their nondrizzling counterparts (100–250 m and 30–75 g m−2, respectively). The variance of the vertical air motion is maximum near the cloud base and is higher at night. The updraft mass flux is around 0.17 kg m−2 s−1 with 40%–60% explained by coherent updraft structures. Despite a high frequency of stratocumulus clouds in the Azores, the MBL is almost never well mixed and is often cumulus coupled.
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.
Abstract
A long data record (14 yr) of ground-based observations at the Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) site is analyzed to document the macroscopic and dynamical properties of daytime fair-weather cumulus clouds during summer months. First, a fuzzy logic–based algorithm is developed to eliminate insect radar echoes in the boundary layer that hinder the ability to develop representative cloud statistics. The refined dataset is used to document the daytime composites of fair-weather cumulus clouds properties. Doppler velocities are processed for lower reflectivity thresholds that contain small cloud droplets having insignificant terminal velocities; thus, Doppler velocities are used as tracers of air motion. The algorithm is implemented to process the entire 14-yr dataset of cloud radar vertical velocity data. Composite diurnal variations of the cloud vertical velocity statistics, surface parameters, and profiles of updraft and downdraft fractions, bulk velocity of updrafts and downdrafts, and updraft and downdraft mass flux are calculated. Statistics on the cloud geometrical properties such as cloud thickness, cloud chord length, cloud spacing, and aspect ratios are calculated on the cloud scale. The present dataset provides a unique insight into the daytime evolution and statistical description of the turbulent structure inside fair-weather cumuli over land.
Abstract
A long data record (14 yr) of ground-based observations at the Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) site is analyzed to document the macroscopic and dynamical properties of daytime fair-weather cumulus clouds during summer months. First, a fuzzy logic–based algorithm is developed to eliminate insect radar echoes in the boundary layer that hinder the ability to develop representative cloud statistics. The refined dataset is used to document the daytime composites of fair-weather cumulus clouds properties. Doppler velocities are processed for lower reflectivity thresholds that contain small cloud droplets having insignificant terminal velocities; thus, Doppler velocities are used as tracers of air motion. The algorithm is implemented to process the entire 14-yr dataset of cloud radar vertical velocity data. Composite diurnal variations of the cloud vertical velocity statistics, surface parameters, and profiles of updraft and downdraft fractions, bulk velocity of updrafts and downdrafts, and updraft and downdraft mass flux are calculated. Statistics on the cloud geometrical properties such as cloud thickness, cloud chord length, cloud spacing, and aspect ratios are calculated on the cloud scale. The present dataset provides a unique insight into the daytime evolution and statistical description of the turbulent structure inside fair-weather cumuli over land.
Abstract
The southeast Pacific stratocumulus regime is an important component of the earth’s climate system because of its substantial impact on albedo. Observational studies of this cloud regime have been limited, but during the past 5 yr, a series of cruises with research vessels equipped with in situ and remote sensing systems have provided unprecedented observations of boundary layer cloud and drizzle structures. These cruises started with the East Pacific Investigation of Climate (EPIC) 2001 field experiment, followed by cruises in a similar area in 2003 and 2004 [Pan-American Climate Studies (PACS) Stratus cruises]. The sampling from these three cruises provides a sufficient dataset to study the variability occurring over this region. This study compares observations from the 2004 cruise with those obtained during the previous two cruises. Observations from the ship provide information about boundary layer structure, fractional cloudiness, cloud depth, and drizzle characteristics. This study indicates more strongly decoupled boundary layers during the 2004 cruise than the well-mixed conditions that dominated the cloud and boundary layer structures during the EPIC cruise, and the highly variable conditions—sharp transitions from a solid stratus deck to broken-cloud and clear-sky periods—encountered during PACS Stratus 2003. Diurnal forcing and synoptic conditions are considered to be factors affecting these variations. A statistical evaluation of the macrophysical boundary layer, cloud, and drizzle properties is performed using the 5–6-day periods for which the research vessels remained stationed at the location of 20°S, 85°W during each cruise.
Abstract
The southeast Pacific stratocumulus regime is an important component of the earth’s climate system because of its substantial impact on albedo. Observational studies of this cloud regime have been limited, but during the past 5 yr, a series of cruises with research vessels equipped with in situ and remote sensing systems have provided unprecedented observations of boundary layer cloud and drizzle structures. These cruises started with the East Pacific Investigation of Climate (EPIC) 2001 field experiment, followed by cruises in a similar area in 2003 and 2004 [Pan-American Climate Studies (PACS) Stratus cruises]. The sampling from these three cruises provides a sufficient dataset to study the variability occurring over this region. This study compares observations from the 2004 cruise with those obtained during the previous two cruises. Observations from the ship provide information about boundary layer structure, fractional cloudiness, cloud depth, and drizzle characteristics. This study indicates more strongly decoupled boundary layers during the 2004 cruise than the well-mixed conditions that dominated the cloud and boundary layer structures during the EPIC cruise, and the highly variable conditions—sharp transitions from a solid stratus deck to broken-cloud and clear-sky periods—encountered during PACS Stratus 2003. Diurnal forcing and synoptic conditions are considered to be factors affecting these variations. A statistical evaluation of the macrophysical boundary layer, cloud, and drizzle properties is performed using the 5–6-day periods for which the research vessels remained stationed at the location of 20°S, 85°W during each cruise.
Abstract
A long-term study of the turbulent structure of the convective boundary layer (CBL) at the U.S. Department of Energy Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) Climate Research Facility is presented. Doppler velocity measurements from insects occupying the lowest 2 km of the boundary layer during summer months are used to map the vertical velocity component in the CBL. The observations cover four summer periods (2004–08) and are classified into cloudy and clear boundary layer conditions. Profiles of vertical velocity variance, skewness, and mass flux are estimated to study the daytime evolution of the convective boundary layer during these conditions. A conditional sampling method is applied to the original Doppler velocity dataset to extract coherent vertical velocity structures and to examine plume dimension and contribution to the turbulent transport. Overall, the derived turbulent statistics are consistent with previous aircraft and lidar observations. The observations provide unique insight into the daytime evolution of the convective boundary layer and the role of increased cloudiness in the turbulent budget of the subcloud layer. Coherent structures (plumes–thermals) are found to be responsible for more than 80% of the total turbulent transport resolved by the cloud radar system. The extended dataset is suitable for evaluating boundary layer parameterizations and testing large-eddy simulations (LESs) for a variety of surface and cloud conditions.
Abstract
A long-term study of the turbulent structure of the convective boundary layer (CBL) at the U.S. Department of Energy Atmospheric Radiation Measurement Program (ARM) Southern Great Plains (SGP) Climate Research Facility is presented. Doppler velocity measurements from insects occupying the lowest 2 km of the boundary layer during summer months are used to map the vertical velocity component in the CBL. The observations cover four summer periods (2004–08) and are classified into cloudy and clear boundary layer conditions. Profiles of vertical velocity variance, skewness, and mass flux are estimated to study the daytime evolution of the convective boundary layer during these conditions. A conditional sampling method is applied to the original Doppler velocity dataset to extract coherent vertical velocity structures and to examine plume dimension and contribution to the turbulent transport. Overall, the derived turbulent statistics are consistent with previous aircraft and lidar observations. The observations provide unique insight into the daytime evolution of the convective boundary layer and the role of increased cloudiness in the turbulent budget of the subcloud layer. Coherent structures (plumes–thermals) are found to be responsible for more than 80% of the total turbulent transport resolved by the cloud radar system. The extended dataset is suitable for evaluating boundary layer parameterizations and testing large-eddy simulations (LESs) for a variety of surface and cloud conditions.
Abstract
The observation and representation in general circulation models (GCMs) of cloud vertical overlap are the objects of active research due to their impacts on the earth’s radiative budget. Previous studies have found that vertically contiguous cloudy layers show a maximum overlap between layers up to several kilometers apart but tend toward a random overlap as separations increase. The decorrelation length scale that characterizes the progressive transition from maximum to random overlap changes from one location and season to another and thus may be influenced by large-scale vertical motion, wind shear, or convection. Observations from the U.S. Department of Energy Atmospheric Radiation Measurement program ground-based radars and lidars in midlatitude and tropical locations in combination with reanalysis meteorological fields are used to evaluate how dynamics and atmospheric state influence cloud overlap. For midlatitude winter months, strong synoptic-scale upward motion maintains conditions closer to maximum overlap at large separations. In the tropics, overlap becomes closer to maximum as convective stability decreases. In midlatitude subsidence and tropical convectively stable situations, where a smooth transition from maximum to random overlap is found on average, large wind shears sometimes favor minimum overlap. Precipitation periods are discarded from the analysis but, when included, maximum overlap occurs more often at large separations. The results suggest that a straightforward modification of the existing GCM mixed maximum–random overlap parameterization approach that accounts for environmental conditions can capture much of the important variability and is more realistic than approaches that are only based on an exponential decay transition from maximum to random overlap.
Abstract
The observation and representation in general circulation models (GCMs) of cloud vertical overlap are the objects of active research due to their impacts on the earth’s radiative budget. Previous studies have found that vertically contiguous cloudy layers show a maximum overlap between layers up to several kilometers apart but tend toward a random overlap as separations increase. The decorrelation length scale that characterizes the progressive transition from maximum to random overlap changes from one location and season to another and thus may be influenced by large-scale vertical motion, wind shear, or convection. Observations from the U.S. Department of Energy Atmospheric Radiation Measurement program ground-based radars and lidars in midlatitude and tropical locations in combination with reanalysis meteorological fields are used to evaluate how dynamics and atmospheric state influence cloud overlap. For midlatitude winter months, strong synoptic-scale upward motion maintains conditions closer to maximum overlap at large separations. In the tropics, overlap becomes closer to maximum as convective stability decreases. In midlatitude subsidence and tropical convectively stable situations, where a smooth transition from maximum to random overlap is found on average, large wind shears sometimes favor minimum overlap. Precipitation periods are discarded from the analysis but, when included, maximum overlap occurs more often at large separations. The results suggest that a straightforward modification of the existing GCM mixed maximum–random overlap parameterization approach that accounts for environmental conditions can capture much of the important variability and is more realistic than approaches that are only based on an exponential decay transition from maximum to random overlap.