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- Author or Editor: Margaret A. LeMone x
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Abstract
Previously published profiles of vertical velocity (w) skewness observed in the convective atmospheric boundary layer show deficits in the upper part of the layer, relative to large eddy simulations designed to apply to highly convective cloudless planetary boundary layers. Thus, we examine w-skewness profiles from data collected in other experiments. We find that skewness profiles in the three highly convective cases with the fewest and smallest clouds agree better with the large eddy simulation results than other profiles presented here and previously; however the deficit at the top of the boundary layer—though smaller—remains.
We hypothesize that the remaining deficit for these three cases results from the presence of ∼10-km wavelength quasi two-dimensional sinusoidal structures, which have near-zero skewness. The small domain and periodic boundary conditions of a large eddy simulation may not allow such structures to develop fully. Removal of the effects of these structures by counting only flight legs nearly parallel to their axes, for two of the cases, improves agreement between the simulation and observations. We speculate that these structures result from gravity waves interacting with the boundary layer.
Abstract
Previously published profiles of vertical velocity (w) skewness observed in the convective atmospheric boundary layer show deficits in the upper part of the layer, relative to large eddy simulations designed to apply to highly convective cloudless planetary boundary layers. Thus, we examine w-skewness profiles from data collected in other experiments. We find that skewness profiles in the three highly convective cases with the fewest and smallest clouds agree better with the large eddy simulation results than other profiles presented here and previously; however the deficit at the top of the boundary layer—though smaller—remains.
We hypothesize that the remaining deficit for these three cases results from the presence of ∼10-km wavelength quasi two-dimensional sinusoidal structures, which have near-zero skewness. The small domain and periodic boundary conditions of a large eddy simulation may not allow such structures to develop fully. Removal of the effects of these structures by counting only flight legs nearly parallel to their axes, for two of the cases, improves agreement between the simulation and observations. We speculate that these structures result from gravity waves interacting with the boundary layer.
A survey of the Journal of the Atmospheric Sciences, the Journal of Applied Meteorology, and the Monthly Weather Review shows that the number of publications per year resulting from GATE (GARP Atlantic Tropical Experiment) peaked in 1980, six years after the experiment's field phase.
A survey of the Journal of the Atmospheric Sciences, the Journal of Applied Meteorology, and the Monthly Weather Review shows that the number of publications per year resulting from GATE (GARP Atlantic Tropical Experiment) peaked in 1980, six years after the experiment's field phase.
Abstract
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Abstract
No abstract available.
Abstract
Based on personal experience and input from colleagues, the natural history of a field program is discussed, from conception through data analysis and synthesis of results. For convenience, the life cycle of a field program is divided into three phases: the prefield phase, the field phase, and the aftermath. As described here, the prefield phase involves conceiving the idea, developing the scientific objectives, naming the program, obtaining support, and arranging the logistics. The field phase discussion highlights the decision making process, balancing input from data and numerical models, and human interactions. The data are merged, analyzed, and synthesized into knowledge mainly after the field effort.
Three major conclusions are drawn. First, it is the people most of all who make a field program successful, and cooperation and collegial consensus building are vital during all phases; good health and a sense of humor both help make this possible. Second, although numerical models are now playing a central role in all phases of a field program, not paying adequate attention to the observations can lead to problems. And finally, it cannot be overemphasized that both funding agencies and participants must recognize that it takes several years to fully exploit the datasets collected, with the corollary that high-quality datasets should be available long term.
Abstract
Based on personal experience and input from colleagues, the natural history of a field program is discussed, from conception through data analysis and synthesis of results. For convenience, the life cycle of a field program is divided into three phases: the prefield phase, the field phase, and the aftermath. As described here, the prefield phase involves conceiving the idea, developing the scientific objectives, naming the program, obtaining support, and arranging the logistics. The field phase discussion highlights the decision making process, balancing input from data and numerical models, and human interactions. The data are merged, analyzed, and synthesized into knowledge mainly after the field effort.
Three major conclusions are drawn. First, it is the people most of all who make a field program successful, and cooperation and collegial consensus building are vital during all phases; good health and a sense of humor both help make this possible. Second, although numerical models are now playing a central role in all phases of a field program, not paying adequate attention to the observations can lead to problems. And finally, it cannot be overemphasized that both funding agencies and participants must recognize that it takes several years to fully exploit the datasets collected, with the corollary that high-quality datasets should be available long term.
Abstract
The cloud-base diameters of 40 cumulus clouds traversed by aircraft on 14 days of the Cooperative Convective Precipitation Experiment (CCOPE) are shown to increase with the vertical shear of the horizontal wind through cloud base. The relationship is stronger when only the largest clouds sampled in each of the 16 populations are considered. The relationship is strongest when the cloud diameter is normalized by the maximum achievable cloud height, as estimated by the parcel equilibrium height. Assuming a cloud diameter—height ratio of around 1, this implies that larger shear enables clouds to reach a larger fraction of their maximum possible size given the thermodynamic conditions. Alternatively, larger shear may lead to clouds with larger diameter-height ratios. The correct interpretation is probably a combination of the two.
The physical mechanisms for the growth of these largest clouds seem to involve interaction among clouds and the interaction of the clouds with cloud—and boundary layer—induced tropospheric gravity waves, as discussed by Clerk et al. (1986), since these interactions are stronger with stronger vertical shear of the horizontal wind through cloud base. Once produced, the larger clouds that produce outflows have a greater chance to enlarge or to produce new clouds in situations with stronger shear, enhancing the chance of sampling larger clouds.
Abstract
The cloud-base diameters of 40 cumulus clouds traversed by aircraft on 14 days of the Cooperative Convective Precipitation Experiment (CCOPE) are shown to increase with the vertical shear of the horizontal wind through cloud base. The relationship is stronger when only the largest clouds sampled in each of the 16 populations are considered. The relationship is strongest when the cloud diameter is normalized by the maximum achievable cloud height, as estimated by the parcel equilibrium height. Assuming a cloud diameter—height ratio of around 1, this implies that larger shear enables clouds to reach a larger fraction of their maximum possible size given the thermodynamic conditions. Alternatively, larger shear may lead to clouds with larger diameter-height ratios. The correct interpretation is probably a combination of the two.
The physical mechanisms for the growth of these largest clouds seem to involve interaction among clouds and the interaction of the clouds with cloud—and boundary layer—induced tropospheric gravity waves, as discussed by Clerk et al. (1986), since these interactions are stronger with stronger vertical shear of the horizontal wind through cloud base. Once produced, the larger clouds that produce outflows have a greater chance to enlarge or to produce new clouds in situations with stronger shear, enhancing the chance of sampling larger clouds.
Abstract
The vertical transport of horizontal momentum normal to a line of cumulonimbus observed during GATE on 14 September 1974 is against the vertical momentum gradient, contrary to the predictions of mixing-length theory. Data from repeated aircraft passes normal to the line's axis at heights from 0.15 to 5.5 km are used to document the flux and determine its source. The flux is concentrated in roughly a 25 km wide “active zone” just behind the leading edge of the line, in kilometer-scale convective updrafts accelerated upward by buoyancy and toward the rear of the line by mesoscale pressure forces. The fall in mesoscale pressure from the leading edge to the rear of the active zone is mainly hydrostatic, resulting from relatively high virtual temperatures and the 60 degree tilt of the leading edge from the vertical, with the clouds at the surface well ahead of those aloft.
Evaluation of the terms in the momentum-flux generation equation confirms that the above process, reflected by the velocity-buoyancy correlation term, is responsible for generating momentum flux of the observed sign. The component of momentum flux parallel to the axis of the convective band is generated much like “down-gradient” momentum flux within the fair-weather subcloud layer.
Abstract
The vertical transport of horizontal momentum normal to a line of cumulonimbus observed during GATE on 14 September 1974 is against the vertical momentum gradient, contrary to the predictions of mixing-length theory. Data from repeated aircraft passes normal to the line's axis at heights from 0.15 to 5.5 km are used to document the flux and determine its source. The flux is concentrated in roughly a 25 km wide “active zone” just behind the leading edge of the line, in kilometer-scale convective updrafts accelerated upward by buoyancy and toward the rear of the line by mesoscale pressure forces. The fall in mesoscale pressure from the leading edge to the rear of the active zone is mainly hydrostatic, resulting from relatively high virtual temperatures and the 60 degree tilt of the leading edge from the vertical, with the clouds at the surface well ahead of those aloft.
Evaluation of the terms in the momentum-flux generation equation confirms that the above process, reflected by the velocity-buoyancy correlation term, is responsible for generating momentum flux of the observed sign. The component of momentum flux parallel to the axis of the convective band is generated much like “down-gradient” momentum flux within the fair-weather subcloud layer.
Abstract
Horizontal roll vortices influence the distribution of turbulence, with turbulence variances and fluxes concentrated in regions of positive roll vertical velocity ωr. This “modulation” of turbulence can be explained simply in terms of the advection of turbulence-generating elements by rolls.
A budget equation is derived for the roll-modulated turbulence energy. Evaluations of various terms in the equation shows that the modulation of turbulence variance is accounted for primarily by a similar modulation in mechanical and buoyancy production near the surface and by vertical transport at higher levels (∼100 m). Energy exchange between rolls and turbulence is relatively unimportant. That is, the rolls modulate, turbulence energy mainly by redistributing turbulence and turbulence-producing elements, rather than by exchanging energy.
Similarly, it is shown that the exchange of energy between rolls and roll-modulated turbulence contributes considerably less to the energy equation of rolls than does the major term, buoyancy.
Abstract
Horizontal roll vortices influence the distribution of turbulence, with turbulence variances and fluxes concentrated in regions of positive roll vertical velocity ωr. This “modulation” of turbulence can be explained simply in terms of the advection of turbulence-generating elements by rolls.
A budget equation is derived for the roll-modulated turbulence energy. Evaluations of various terms in the equation shows that the modulation of turbulence variance is accounted for primarily by a similar modulation in mechanical and buoyancy production near the surface and by vertical transport at higher levels (∼100 m). Energy exchange between rolls and turbulence is relatively unimportant. That is, the rolls modulate, turbulence energy mainly by redistributing turbulence and turbulence-producing elements, rather than by exchanging energy.
Similarly, it is shown that the exchange of energy between rolls and roll-modulated turbulence contributes considerably less to the energy equation of rolls than does the major term, buoyancy.
Abstract
Results from a detailed three-dimensional model of the atmospheric boundary layer are compared with observational data in a case of nonprecipitating convection in a tropical boundary layer. The model is a slightly improved version of the one developed by Sommeria (1976) in collaboration with J.W. Deardorff. The experimental data come from the NCAR 1972 Puerto Rico experiment which provided a good set of aircraft turbulence measurements in the fair weather mixed layer over the tropical ocean. The comparison involves statistical properties of the turbulent field as well as some structural features in the presence of small clouds.
Abstract
Results from a detailed three-dimensional model of the atmospheric boundary layer are compared with observational data in a case of nonprecipitating convection in a tropical boundary layer. The model is a slightly improved version of the one developed by Sommeria (1976) in collaboration with J.W. Deardorff. The experimental data come from the NCAR 1972 Puerto Rico experiment which provided a good set of aircraft turbulence measurements in the fair weather mixed layer over the tropical ocean. The comparison involves statistical properties of the turbulent field as well as some structural features in the presence of small clouds.
Abstract
The structure of the convective atmospheric boundary layer and the characteristics of the associated turbulent mixing processes in undisturbed conditions over the tropical ocean are investigated using data collected during the GARP Atlantic Tropical Experiment (GATE). The data were obtained by a number of aircraft equipped with turbulence measuring instrumentation. The fluxes of momentum, sensible and latent heat throughout the subcloud layer are presented for four cases considered in detail. It is shown that the sensible and latent heat fluxes at the top of the mixed layer (and therefore the distribution of heating and moistening in the boundary layer) are strongly affected by the presence or absence of cumulus convection while the virtual heat flux remains unaffected. Features of this cloud-subcloud interaction are discussed in the light of Betts (1976) coupled cloud-subcloud layer model.
An examination of the spectra (and cospectra) of subcloud-layer variables shows that with the exception of vertical velocity, the spectra are generally dominated by low-frequency fluctuations. This behavior is attributed to the effects of entrainment which may produce relatively large, long-lived excursions from the mixed-layer average in the weakly mixed GATE boundary layer and to the existence of mesoscale (∼10 km) variability.
Wherever possible comparisons are drawn with previous measurements and corresponding situations over land, where mixing processes are usually much more energetic. Aircraft measurements of the sensible and latent heat fluxes are compared with those derived from tethered balloon probes and budget calculations which were employed concurrently during GATE. Aircraft and tethered balloon fluxes showed good agreement; however, the budget results differ, probably due to a different sampling strategy.
Abstract
The structure of the convective atmospheric boundary layer and the characteristics of the associated turbulent mixing processes in undisturbed conditions over the tropical ocean are investigated using data collected during the GARP Atlantic Tropical Experiment (GATE). The data were obtained by a number of aircraft equipped with turbulence measuring instrumentation. The fluxes of momentum, sensible and latent heat throughout the subcloud layer are presented for four cases considered in detail. It is shown that the sensible and latent heat fluxes at the top of the mixed layer (and therefore the distribution of heating and moistening in the boundary layer) are strongly affected by the presence or absence of cumulus convection while the virtual heat flux remains unaffected. Features of this cloud-subcloud interaction are discussed in the light of Betts (1976) coupled cloud-subcloud layer model.
An examination of the spectra (and cospectra) of subcloud-layer variables shows that with the exception of vertical velocity, the spectra are generally dominated by low-frequency fluctuations. This behavior is attributed to the effects of entrainment which may produce relatively large, long-lived excursions from the mixed-layer average in the weakly mixed GATE boundary layer and to the existence of mesoscale (∼10 km) variability.
Wherever possible comparisons are drawn with previous measurements and corresponding situations over land, where mixing processes are usually much more energetic. Aircraft measurements of the sensible and latent heat fluxes are compared with those derived from tethered balloon probes and budget calculations which were employed concurrently during GATE. Aircraft and tethered balloon fluxes showed good agreement; however, the budget results differ, probably due to a different sampling strategy.
Abstract
The relationship of satellite-derived cloud motions to actual convective systems within a convectively active phase of the intraseasonal oscillation is examined by using both cloud-scale properties produced by a cloud-resolving model and field observations to clarify what is going on at shorter time- and space scales. Each convective system has a life cycle of up to 1–2 days. Described in terms of active convection, the system consists of successive precipitation cells generated ahead of the gust front. Described in terms of its cloud shield, the system is more continuous. When easterly winds prevail above 2 km, both precipitating clouds and upper-tropospheric anvil clouds move westward with about the same phase speed (∼10 m s−1). However, during the westerly wind period, precipitating clouds move eastward with a phase speed of ∼10 m s−1, which is better represented by the radar observations and surface precipitation. The westward movement of cloud patterns viewed from the satellite images is mostly due to the horizontal advection of the anvil by the mean flow and the creation of new convective cells to the west of the old convective clouds.
Abstract
The relationship of satellite-derived cloud motions to actual convective systems within a convectively active phase of the intraseasonal oscillation is examined by using both cloud-scale properties produced by a cloud-resolving model and field observations to clarify what is going on at shorter time- and space scales. Each convective system has a life cycle of up to 1–2 days. Described in terms of active convection, the system consists of successive precipitation cells generated ahead of the gust front. Described in terms of its cloud shield, the system is more continuous. When easterly winds prevail above 2 km, both precipitating clouds and upper-tropospheric anvil clouds move westward with about the same phase speed (∼10 m s−1). However, during the westerly wind period, precipitating clouds move eastward with a phase speed of ∼10 m s−1, which is better represented by the radar observations and surface precipitation. The westward movement of cloud patterns viewed from the satellite images is mostly due to the horizontal advection of the anvil by the mean flow and the creation of new convective cells to the west of the old convective clouds.
