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- Author or Editor: Paul R. Field x
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Abstract
Observations from a Lagrangian spiral descent within altostratus cloud associated with a cold front were used to study the evolution of ice particle spectra by following populations of ice crystals as they fell through the cloud. The flight track was corrected for wind effects and was divided into distinct regions for spatial comparison of ice particle spectra. Analysis of size spectra for particles larger than 800 μm revealed heterogeneity on horizontal scales of 5 km in average particle diameter and concentration. In the temperature range −40° to −20°C the ice crystal evolution was dominated by diffusional growth, although observations of the evolution of the bimodal size spectra suggested that aggregation was occurring. Between −20° and −10°C aggregation dominated evolution.
Abstract
Observations from a Lagrangian spiral descent within altostratus cloud associated with a cold front were used to study the evolution of ice particle spectra by following populations of ice crystals as they fell through the cloud. The flight track was corrected for wind effects and was divided into distinct regions for spatial comparison of ice particle spectra. Analysis of size spectra for particles larger than 800 μm revealed heterogeneity on horizontal scales of 5 km in average particle diameter and concentration. In the temperature range −40° to −20°C the ice crystal evolution was dominated by diffusional growth, although observations of the evolution of the bimodal size spectra suggested that aggregation was occurring. Between −20° and −10°C aggregation dominated evolution.
Abstract
Cloud horizontal size distributions from near-global satellite data, from aircraft, and from a global high-resolution numerical weather prediction model, are presented for the scale range 0.1–8000 km and are shown to be well-represented using a single power-law relationship with an exponent of β = 1.66 ±0.04 from 0.1 to 1500 km or more. At scales longer than 1500 km, there is a statistically significant scale break with fewer very large clouds than expected from the power law. The size distribution is integrated to determine the contribution to cloud cover and visible reflectance from clouds larger than a given size. Globally, clouds with a horizontal dimension of 200 km or more constitute approximately 50% of the cloud cover and 60% of the reflectance, and this result is not sensitive to the minimum size threshold assumed in the integral assuming that the power law can be extrapolated below 100-m scale. The result is also not sensitive to whether the size distribution is determined using cloud segment length or cloud area. This emphasizes the great role played by large cloud sheets in determining the earth’s albedo. On the other hand, some 15% of global cloud cover comes from clouds smaller than 10 km, thus emphasizing the broad range of cloud sizes that contribute significantly to the earth’s radiation budget. Both of these results stem from the fact that β is slightly less than 2. The data are further divided and geographical and seasonal variations in the cloud size L 50 for which clouds larger than L 50 constitute 50% of the cloud cover are determined. The largest clouds (L 50 > 300 km) are found over the midlatitude oceans, particularly in summer, and over the tropical convective regions of the west Pacific and Indian Oceans and the monsoon-influenced landmasses. The smallest clouds (L 50 < 100 km) are found over the trade wind regions of the tropics/subtropics and over arid land areas. Small variations in the exponent β contribute significantly to the variations in L50. Finally, it is shown that a bounded cascade model can faithfully simulate the observed cloud size distributions and use this to examine the effects of limiting sensor resolution (pixel size) and domain size (number of pixels across image). Sensor resolution is not found to strongly impact the cloud size distribution provided the ratio of the domain to pixel size remains greater than ~1000. Thus, previous studies with small domain–pixel size ratios may provide biased information about the true cloud size distribution, and should be interpreted with caution.
Abstract
Cloud horizontal size distributions from near-global satellite data, from aircraft, and from a global high-resolution numerical weather prediction model, are presented for the scale range 0.1–8000 km and are shown to be well-represented using a single power-law relationship with an exponent of β = 1.66 ±0.04 from 0.1 to 1500 km or more. At scales longer than 1500 km, there is a statistically significant scale break with fewer very large clouds than expected from the power law. The size distribution is integrated to determine the contribution to cloud cover and visible reflectance from clouds larger than a given size. Globally, clouds with a horizontal dimension of 200 km or more constitute approximately 50% of the cloud cover and 60% of the reflectance, and this result is not sensitive to the minimum size threshold assumed in the integral assuming that the power law can be extrapolated below 100-m scale. The result is also not sensitive to whether the size distribution is determined using cloud segment length or cloud area. This emphasizes the great role played by large cloud sheets in determining the earth’s albedo. On the other hand, some 15% of global cloud cover comes from clouds smaller than 10 km, thus emphasizing the broad range of cloud sizes that contribute significantly to the earth’s radiation budget. Both of these results stem from the fact that β is slightly less than 2. The data are further divided and geographical and seasonal variations in the cloud size L 50 for which clouds larger than L 50 constitute 50% of the cloud cover are determined. The largest clouds (L 50 > 300 km) are found over the midlatitude oceans, particularly in summer, and over the tropical convective regions of the west Pacific and Indian Oceans and the monsoon-influenced landmasses. The smallest clouds (L 50 < 100 km) are found over the trade wind regions of the tropics/subtropics and over arid land areas. Small variations in the exponent β contribute significantly to the variations in L50. Finally, it is shown that a bounded cascade model can faithfully simulate the observed cloud size distributions and use this to examine the effects of limiting sensor resolution (pixel size) and domain size (number of pixels across image). Sensor resolution is not found to strongly impact the cloud size distribution provided the ratio of the domain to pixel size remains greater than ~1000. Thus, previous studies with small domain–pixel size ratios may provide biased information about the true cloud size distribution, and should be interpreted with caution.
Abstract
A theoretical framework has been developed describing nonequilibrium formation and maintenance of mixed-phase clouds. The necessary and sufficient conditions required to activate liquid water within a preexisting ice cloud, and thus convert it to mixed phase, are considered for three scenarios: (i) uniform ascent, (ii) harmonic vertical oscillations, and (iii) turbulent fluctuations. The general conditions are the following:
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First necessary condition: The vertical velocity of an ice cloud parcel must exceed a threshold velocity to activate liquid water.
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Second necessary condition: The activation of liquid water within an ice cloud parcel, below water saturation, requires a vertical ascent above some threshold altitude to bring the vapor pressure of the parcel to water saturation.
Only when the first and second conditions are true do these conditions become sufficient for the activation of liquid water in ice clouds. These required conditions for the generation of mixed-phase cloud are supported by parcel modeling results and analogous conditions for a harmonic oscillation concerning the amplitude and tangential velocity of the parcel motion are proposed. The authors do not assume steady-state conditions, but demonstrate that nonequilibrium evolution of cloud parcels can lead to long-term steady existence of mixed-phase cloud.
Abstract
A theoretical framework has been developed describing nonequilibrium formation and maintenance of mixed-phase clouds. The necessary and sufficient conditions required to activate liquid water within a preexisting ice cloud, and thus convert it to mixed phase, are considered for three scenarios: (i) uniform ascent, (ii) harmonic vertical oscillations, and (iii) turbulent fluctuations. The general conditions are the following:
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First necessary condition: The vertical velocity of an ice cloud parcel must exceed a threshold velocity to activate liquid water.
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Second necessary condition: The activation of liquid water within an ice cloud parcel, below water saturation, requires a vertical ascent above some threshold altitude to bring the vapor pressure of the parcel to water saturation.
Only when the first and second conditions are true do these conditions become sufficient for the activation of liquid water in ice clouds. These required conditions for the generation of mixed-phase cloud are supported by parcel modeling results and analogous conditions for a harmonic oscillation concerning the amplitude and tangential velocity of the parcel motion are proposed. The authors do not assume steady-state conditions, but demonstrate that nonequilibrium evolution of cloud parcels can lead to long-term steady existence of mixed-phase cloud.
Abstract
Composite mean fields and probability distribution functions (PDFs) of rain rate, cloud type and cover, cloud-top temperature, surface wind velocity, and water vapor path (WVP) are constructed using satellite observations of midlatitude cyclones from four oceanic regions (i.e., the North Pacific, South Pacific, North Atlantic, and South Atlantic). Reanalysis surface pressure fields are used to ascertain the locations of the cyclone centers, onto which the satellite fields are interpolated to give a database of ∼1500 cyclones from a two-year period (2003–04). Cyclones are categorized by their strength, defined here using surface wind speed, and by their WVP, and it is found that these two measures can explain a considerable amount of the intercyclone variability of other key variables. Composite cyclones from each of the four ocean basins exhibit similar spatial structure for a given strength and WVP. A set of nine composites is constructed from the database using three strength and three WVP ranges and is used to demonstrate that the mean column relative humidity of these systems varies only slightly (0.58–0.62) for a doubling in WVP (or equivalently a 7-K rise in sea surface temperature) and a 50% increase in cyclone strength. However, cyclone-mean rain rate increases markedly with both cyclone strength and WVP, behavior that is explained with a simple warm conveyor belt model. Systemwide high cloud fraction (tops above 440 hPa) increases from 0.23 to 0.31 as cyclone strength increases by 50%, but does not vary systematically with WVP. It is suggested that the composite fields constitute useful diagnostics for evaluating the behavior of large-scale numerical models, and may provide insight into how precipitation and clouds in midlatitude cyclones respond under a changed climate.
Abstract
Composite mean fields and probability distribution functions (PDFs) of rain rate, cloud type and cover, cloud-top temperature, surface wind velocity, and water vapor path (WVP) are constructed using satellite observations of midlatitude cyclones from four oceanic regions (i.e., the North Pacific, South Pacific, North Atlantic, and South Atlantic). Reanalysis surface pressure fields are used to ascertain the locations of the cyclone centers, onto which the satellite fields are interpolated to give a database of ∼1500 cyclones from a two-year period (2003–04). Cyclones are categorized by their strength, defined here using surface wind speed, and by their WVP, and it is found that these two measures can explain a considerable amount of the intercyclone variability of other key variables. Composite cyclones from each of the four ocean basins exhibit similar spatial structure for a given strength and WVP. A set of nine composites is constructed from the database using three strength and three WVP ranges and is used to demonstrate that the mean column relative humidity of these systems varies only slightly (0.58–0.62) for a doubling in WVP (or equivalently a 7-K rise in sea surface temperature) and a 50% increase in cyclone strength. However, cyclone-mean rain rate increases markedly with both cyclone strength and WVP, behavior that is explained with a simple warm conveyor belt model. Systemwide high cloud fraction (tops above 440 hPa) increases from 0.23 to 0.31 as cyclone strength increases by 50%, but does not vary systematically with WVP. It is suggested that the composite fields constitute useful diagnostics for evaluating the behavior of large-scale numerical models, and may provide insight into how precipitation and clouds in midlatitude cyclones respond under a changed climate.
How Biased Is Aircraft Cloud Sampling?Abstract
Aircraft are the dominant method for in situ sampling of cloud properties. Resource limitations mean that aircraft tend to follow a sampling strategy when there is more than one cloud from which to choose. This can result in biased cloud statistics that are used for parameterization development and model testing. In this study, order statistics are used to estimate the potential magnitude of this bias when a strategy based on choosing the larger cloud is employed. It is found for cloud properties following gamma distributions that a typical bias of a factor of 1.5 can result when the larger of two clouds is repeatedly chosen for sampling.
Abstract
Aircraft are the dominant method for in situ sampling of cloud properties. Resource limitations mean that aircraft tend to follow a sampling strategy when there is more than one cloud from which to choose. This can result in biased cloud statistics that are used for parameterization development and model testing. In this study, order statistics are used to estimate the potential magnitude of this bias when a strategy based on choosing the larger cloud is employed. It is found for cloud properties following gamma distributions that a typical bias of a factor of 1.5 can result when the larger of two clouds is repeatedly chosen for sampling.
Abstract
Relationships among total water, condensed water, and cloud fraction in boundary layer and cold tropospheric stratiform clouds are investigated using a large observational dataset collected by the U.K. Met. Office C-130 aircraft. Values of the above parameters are estimated using horizontal aircraft runs ranging from 40 to 80 km in length. Boundary layer (warm cloud) data were taken from the Atlantic Stratocumulus Transition Experiment (ASTEX) and First International Satellite Cloud Climatology Project (ISCCP) Research Experiment (FIRE). Free tropospheric (cold cloud) data were taken from the European Cloud and Radiation Experiment (EUCREX). In both warm and cold cloud a single reasonably well-defined relationship exists between the cloud fraction and the total water content (vapor + condensate) when normalized with the saturation specific humidity. A relationship exists between the condensed water content and the cloud fraction when appropriately scaled with the saturation specific humidity. Functional forms fitted to the data are used as comparators to test three existing diagnostic cloud fraction parameterization schemes.
Abstract
Relationships among total water, condensed water, and cloud fraction in boundary layer and cold tropospheric stratiform clouds are investigated using a large observational dataset collected by the U.K. Met. Office C-130 aircraft. Values of the above parameters are estimated using horizontal aircraft runs ranging from 40 to 80 km in length. Boundary layer (warm cloud) data were taken from the Atlantic Stratocumulus Transition Experiment (ASTEX) and First International Satellite Cloud Climatology Project (ISCCP) Research Experiment (FIRE). Free tropospheric (cold cloud) data were taken from the European Cloud and Radiation Experiment (EUCREX). In both warm and cold cloud a single reasonably well-defined relationship exists between the cloud fraction and the total water content (vapor + condensate) when normalized with the saturation specific humidity. A relationship exists between the condensed water content and the cloud fraction when appropriately scaled with the saturation specific humidity. Functional forms fitted to the data are used as comparators to test three existing diagnostic cloud fraction parameterization schemes.
Abstract
Ice particle size distributions (PSDs) can be scaled onto a single exponential distribution for a wide range of observed conditions as demonstrated using data from Atmospheric Research Measurement (ARM) cirrus uncinus, Tropical Rainfall Measurement Mission (TRMM) tropical anvils, and First International Satellite Cloud Climatalogy Project (ISCCP) Regional Experiment (FIRE1) midlatitude cirrus field programs. The successful scaling of the PSDs is the result of the dominance of the aggregation process. The PSD is found to be a function of mean particle size and precipitation rate only. A correlation between precipitation rate and particle mass and fall speed relations is demonstrated and made use of in a semiempirical model of ice cloud that predicts the evolution of PSDs.
Abstract
Ice particle size distributions (PSDs) can be scaled onto a single exponential distribution for a wide range of observed conditions as demonstrated using data from Atmospheric Research Measurement (ARM) cirrus uncinus, Tropical Rainfall Measurement Mission (TRMM) tropical anvils, and First International Satellite Cloud Climatalogy Project (ISCCP) Regional Experiment (FIRE1) midlatitude cirrus field programs. The successful scaling of the PSDs is the result of the dominance of the aggregation process. The PSD is found to be a function of mean particle size and precipitation rate only. A correlation between precipitation rate and particle mass and fall speed relations is demonstrated and made use of in a semiempirical model of ice cloud that predicts the evolution of PSDs.
Abstract
Many microphysical process rates involving snow are proportional to moments of the snow particle size distribution (PSD), and in this study a moment estimation parameterization applicable to both midlatitude and tropical ice clouds is proposed. To this end aircraft snow PSD data were analyzed from tropical anvils [Tropical Rainfall Measuring Mission/Kwajelein Experiment (TRMM/KWAJEX), Cirrus Regional Study of Tropical Anvils and Cirrus Layers-Florida Area Cirrus Experiment (CRYSTAL-FACE)] and midlatitude stratiform cloud [First International Satellite Cloud Climatology Project Research Experiment (FIRE), Atmospheric Radiation Measurement Program (ARM)]. For half of the dataset, moments of the PSDs are computed and a parameterization is generated for estimating other PSD moments when the second moment (proportional to the ice water content when particle mass is proportional to size squared) and temperature are known. Subsequently the parameterization was tested with the other half of the dataset to facilitate an independent comparison. The parameterization for estimating moments can be applied to midlatitude or tropical clouds without requiring prior knowledge of the regime of interest. Rescaling of the tropical and midlatitude size distributions is presented along with fits to allow the user to recreate realistic PSDs given estimates of ice water content and temperature. The effects of using different time averaging were investigated and were found not to be adverse. Finally, the merits of a single-moment snow microphysics versus multimoment representations are discussed, and speculation on the physical differences between the rescaled size distributions from the Tropics and midlatitudes is presented.
Abstract
Many microphysical process rates involving snow are proportional to moments of the snow particle size distribution (PSD), and in this study a moment estimation parameterization applicable to both midlatitude and tropical ice clouds is proposed. To this end aircraft snow PSD data were analyzed from tropical anvils [Tropical Rainfall Measuring Mission/Kwajelein Experiment (TRMM/KWAJEX), Cirrus Regional Study of Tropical Anvils and Cirrus Layers-Florida Area Cirrus Experiment (CRYSTAL-FACE)] and midlatitude stratiform cloud [First International Satellite Cloud Climatology Project Research Experiment (FIRE), Atmospheric Radiation Measurement Program (ARM)]. For half of the dataset, moments of the PSDs are computed and a parameterization is generated for estimating other PSD moments when the second moment (proportional to the ice water content when particle mass is proportional to size squared) and temperature are known. Subsequently the parameterization was tested with the other half of the dataset to facilitate an independent comparison. The parameterization for estimating moments can be applied to midlatitude or tropical clouds without requiring prior knowledge of the regime of interest. Rescaling of the tropical and midlatitude size distributions is presented along with fits to allow the user to recreate realistic PSDs given estimates of ice water content and temperature. The effects of using different time averaging were investigated and were found not to be adverse. Finally, the merits of a single-moment snow microphysics versus multimoment representations are discussed, and speculation on the physical differences between the rescaled size distributions from the Tropics and midlatitudes is presented.
Abstract
The ventilation factor and capacitance used in numerical models to represent ice crystal aggregates directly affects the growth rate of the ice crystal aggregates, and consequently the sink of atmospheric water vapor. Currently, numerical models that prognose ice water content (IWC) and water vapor mixing ratio represent the capacitance and ventilation factor of precipitation-sized particles with simplified geometries, such as hexagonal plates. The geometries of actual precipitation-sized particles are often more complex, and a test of the values being employed is needed. Aircraft observations obtained during a Lagrangian spiral descent through the sublimation zone of a tropical anvil cloud have been used to determine an estimate of combined dimensionless capacitance and ventilation factor for the nonpristine geometries exhibited by ice crystal aggregates. By combining measurements of bulk ice water content, the particle size distribution, and environmental subsaturation, the change in ice water content was modeled throughout the spiral descent and compared with observations of the change in ice water content. Uncertainties resulting from potential systematic biases in the measurements and parameterizations used in the analysis were investigated with sensitivity tests. Most of the uncertainty was related to an assumed maximum potential bias in the measurement of IWC of ±45%. The resulting combined ventilation factor and dimensionless capacitance value was 1.3 (with a range of 0.6–1.9, defined by 68% of sensitivity test trials) for a particle size–weighted mean value of (Sc)1/3(Re)1/2 = 14.9 ± 1.7, where Sc is the Schmidt number and Re is the Reynolds number. Results from commonly adopted combinations of ventilation factor relations and capacitances are compared with the observations presented here, and, finally, surrogate dimensionless capacitances are suggested that when combined with commonly used ventilation factor relations are consistent with the results presented herein.
Abstract
The ventilation factor and capacitance used in numerical models to represent ice crystal aggregates directly affects the growth rate of the ice crystal aggregates, and consequently the sink of atmospheric water vapor. Currently, numerical models that prognose ice water content (IWC) and water vapor mixing ratio represent the capacitance and ventilation factor of precipitation-sized particles with simplified geometries, such as hexagonal plates. The geometries of actual precipitation-sized particles are often more complex, and a test of the values being employed is needed. Aircraft observations obtained during a Lagrangian spiral descent through the sublimation zone of a tropical anvil cloud have been used to determine an estimate of combined dimensionless capacitance and ventilation factor for the nonpristine geometries exhibited by ice crystal aggregates. By combining measurements of bulk ice water content, the particle size distribution, and environmental subsaturation, the change in ice water content was modeled throughout the spiral descent and compared with observations of the change in ice water content. Uncertainties resulting from potential systematic biases in the measurements and parameterizations used in the analysis were investigated with sensitivity tests. Most of the uncertainty was related to an assumed maximum potential bias in the measurement of IWC of ±45%. The resulting combined ventilation factor and dimensionless capacitance value was 1.3 (with a range of 0.6–1.9, defined by 68% of sensitivity test trials) for a particle size–weighted mean value of (Sc)1/3(Re)1/2 = 14.9 ± 1.7, where Sc is the Schmidt number and Re is the Reynolds number. Results from commonly adopted combinations of ventilation factor relations and capacitances are compared with the observations presented here, and, finally, surrogate dimensionless capacitances are suggested that when combined with commonly used ventilation factor relations are consistent with the results presented herein.
