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- Author or Editor: Lawrence Cheng x
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Abstract
Procedures have been developed from relationships between parameters of hailstone size distributions and storm thermodynamics to normalize the effects of storm thermodynamics of integral hail parameters observed at the ground. Hail parameters considered in this study are the number concentration, water content and kinetic energy. Results from statistical tests on these integral hail parameters obtained from various not-seeded storms showed that significant differences exist among these storms. The differences appear to be due to variations in storm intensity. However, once the normalization of the storm thermodynamic variability is applied to the data, no significant differences are found. The technique seems to reduce, if not eliminate, the variations due to the effects of storm thermodynamics on the integral hail parameters.
Statistical analyses of the normalized surface integral hail parameters, obtained from two operationally seeded storms, are carried out to test the procedure for the evaluation of silver iodide seeding effects. A storm-by-storm approach is used to illustrate the anthropogenic variability such as differences in the execution of the seeding operation. Integral hail parameters obtained from a storm that is not seeded at the appropriate location as prescribed by the seeding hypothesis do not differ from those of the control storms. For the other storms seeded at the right location, a nominally significant difference is found in the hail total number concentration but not in the integral hail water content and kinetic energy. However, no conclusion as to the cause of the isolated significant difference can be drawn because the storms analyzed did not constitute a randomized experiment.
Abstract
Procedures have been developed from relationships between parameters of hailstone size distributions and storm thermodynamics to normalize the effects of storm thermodynamics of integral hail parameters observed at the ground. Hail parameters considered in this study are the number concentration, water content and kinetic energy. Results from statistical tests on these integral hail parameters obtained from various not-seeded storms showed that significant differences exist among these storms. The differences appear to be due to variations in storm intensity. However, once the normalization of the storm thermodynamic variability is applied to the data, no significant differences are found. The technique seems to reduce, if not eliminate, the variations due to the effects of storm thermodynamics on the integral hail parameters.
Statistical analyses of the normalized surface integral hail parameters, obtained from two operationally seeded storms, are carried out to test the procedure for the evaluation of silver iodide seeding effects. A storm-by-storm approach is used to illustrate the anthropogenic variability such as differences in the execution of the seeding operation. Integral hail parameters obtained from a storm that is not seeded at the appropriate location as prescribed by the seeding hypothesis do not differ from those of the control storms. For the other storms seeded at the right location, a nominally significant difference is found in the hail total number concentration but not in the integral hail water content and kinetic energy. However, no conclusion as to the cause of the isolated significant difference can be drawn because the storms analyzed did not constitute a randomized experiment.
Abstract
Hailstone size distributions have been determined from 41 time-resolved hailstone samples collected at the ground from seven storms that occurred in Alberta in the summer of 1980. Most size distributions were found to quite closely fit an exponential function of the form n(D) = n 0 e −λD . In studying variations in n 0 and λ, it was found that a relationship exists between the two. In particular, correlation coefficients of ∼−0.9 were found when least-square linear regressions were fitted to the values of logn 0 versus logλ. For Alberta storms, therefore, n 0 can be expressed in terms of λ as n 0 = 115λ3.63, and hail size distributions can be expressed in terms of the single parameter λ as n(D) = 115λ3.63 e −λD . From an examination of hail size distributions from one storm that occurred in Switzerland, it appears likely that similar relationships can be determined for hailstorms from other regions.
Abstract
Hailstone size distributions have been determined from 41 time-resolved hailstone samples collected at the ground from seven storms that occurred in Alberta in the summer of 1980. Most size distributions were found to quite closely fit an exponential function of the form n(D) = n 0 e −λD . In studying variations in n 0 and λ, it was found that a relationship exists between the two. In particular, correlation coefficients of ∼−0.9 were found when least-square linear regressions were fitted to the values of logn 0 versus logλ. For Alberta storms, therefore, n 0 can be expressed in terms of λ as n 0 = 115λ3.63, and hail size distributions can be expressed in terms of the single parameter λ as n(D) = 115λ3.63 e −λD . From an examination of hail size distributions from one storm that occurred in Switzerland, it appears likely that similar relationships can be determined for hailstorms from other regions.
Abstract
Dynamic processes of cumulus clouds which may produce significant horizontal eddy transport of vertical vorticity in the tropical atmosphere are discussed. It is shown in this paper that horizontal eddy transport of vorticity by cumulus convection, if it exists, must be due entirely to the irrotational component of the horizontal wind produced by clouds. The ability of clouds to produce this eddy transport depends critically on the presence of cyclonic-anticyclonic vortex couplets in the cloud circulations. The generation processes of these vortex couplets are also discussed.
A formula is derived to parameterize this eddy transport process in the large-scale mean vorticity equation. The formulation is tested using. GATE data. GATE-A/B-scale mean vorticity budgets are analyzed for two 1-day periods during Phase III of the experiment. The agreements between the theoretically predicted and the observed apparent vorticity sources are found to be much improved by including the effects of cloud horizontal eddy transport of vertical vorticity.
Abstract
Dynamic processes of cumulus clouds which may produce significant horizontal eddy transport of vertical vorticity in the tropical atmosphere are discussed. It is shown in this paper that horizontal eddy transport of vorticity by cumulus convection, if it exists, must be due entirely to the irrotational component of the horizontal wind produced by clouds. The ability of clouds to produce this eddy transport depends critically on the presence of cyclonic-anticyclonic vortex couplets in the cloud circulations. The generation processes of these vortex couplets are also discussed.
A formula is derived to parameterize this eddy transport process in the large-scale mean vorticity equation. The formulation is tested using. GATE data. GATE-A/B-scale mean vorticity budgets are analyzed for two 1-day periods during Phase III of the experiment. The agreements between the theoretically predicted and the observed apparent vorticity sources are found to be much improved by including the effects of cloud horizontal eddy transport of vertical vorticity.
Abstract
Observational evidence from an Alberta hailstorm was examined in an attempt to demonstrate the link between feeder clouds and hailfalls. Radar data, time resolved surface collections of hail, and cloud photographs from a storm were analyzed. It was found that the streak events in the surface hailfall can he linked to small-scale radar reflectivity maxima in the new growth region of the storm. The results suggest that the hail growth process began with packets of hail embryos in distinct feeder clouds, and that the separation between feeder clouds was eventually manifested as distinct hail streak events at the surface. The feeder clouds formed approximately in a line parallel to the vertical ambient wind shear near the cloud base level. The spacings between feeder clouds were almost equal and estimated to he 3 km. Theoretical predictions indicate that convective spacing in a horizontally uniform atmosphere is determined by environmental wind shear, stability, and depth of the shear layer. The results of this and other observational studies lead to the speculation that the spacing between distinct hail streak events may be controlled by the same factors in the vicinity of the new growth zone of hailstorms.
Abstract
Observational evidence from an Alberta hailstorm was examined in an attempt to demonstrate the link between feeder clouds and hailfalls. Radar data, time resolved surface collections of hail, and cloud photographs from a storm were analyzed. It was found that the streak events in the surface hailfall can he linked to small-scale radar reflectivity maxima in the new growth region of the storm. The results suggest that the hail growth process began with packets of hail embryos in distinct feeder clouds, and that the separation between feeder clouds was eventually manifested as distinct hail streak events at the surface. The feeder clouds formed approximately in a line parallel to the vertical ambient wind shear near the cloud base level. The spacings between feeder clouds were almost equal and estimated to he 3 km. Theoretical predictions indicate that convective spacing in a horizontally uniform atmosphere is determined by environmental wind shear, stability, and depth of the shear layer. The results of this and other observational studies lead to the speculation that the spacing between distinct hail streak events may be controlled by the same factors in the vicinity of the new growth zone of hailstorms.
Abstract
A formulation is proposed to represent the effects of cumulus clouds in the large-scale vorticity equation. Cumulus clouds are found to modify the large-scale vorticity field through two processes: 1) the vertical advection of mean vorticity by the cumulus vertical cloud mass flux and 2) the twisting of horizontal vorticity into the vertical direction due to the inhomogeneous spatial distribution of the cloud population. Under the assumption that the divergence of mean horizontal eddy flux of vorticity can be neglected, the net effect of cumulus clouds can be completely specified in terms of the total cloud mass flux alone. No detailed knowledge of the dynamic fields of cumulus clouds is needed.
GATE A/B-scale heat, moisture and vorticity budgets have been analyzed for a 1-day period (0000–2400 GMT 9 September) during Phase III to verify the validity of the theoretical formulation. The agreement between the theoretically predicted and the observed cloud effects appears very encouraging.
Another important conclusion of this study is that the cloud vorticity when averaged over a cloud cross-sectional area is of the same order of magnitude as the large-scale mean vorticity, despite the smallness of the horizontal scale of cumulus clouds. This has some important implications on the analysis of mesoscale dynamic fields using observational data.
Abstract
A formulation is proposed to represent the effects of cumulus clouds in the large-scale vorticity equation. Cumulus clouds are found to modify the large-scale vorticity field through two processes: 1) the vertical advection of mean vorticity by the cumulus vertical cloud mass flux and 2) the twisting of horizontal vorticity into the vertical direction due to the inhomogeneous spatial distribution of the cloud population. Under the assumption that the divergence of mean horizontal eddy flux of vorticity can be neglected, the net effect of cumulus clouds can be completely specified in terms of the total cloud mass flux alone. No detailed knowledge of the dynamic fields of cumulus clouds is needed.
GATE A/B-scale heat, moisture and vorticity budgets have been analyzed for a 1-day period (0000–2400 GMT 9 September) during Phase III to verify the validity of the theoretical formulation. The agreement between the theoretically predicted and the observed cloud effects appears very encouraging.
Another important conclusion of this study is that the cloud vorticity when averaged over a cloud cross-sectional area is of the same order of magnitude as the large-scale mean vorticity, despite the smallness of the horizontal scale of cumulus clouds. This has some important implications on the analysis of mesoscale dynamic fields using observational data.
Abstract
The use of a shifted gamma size distribution for hailstone samples is proposed. This is shown to provide a better fit than the usual exponential form, using time-resolved Alberta data. It is also concluded that there is a dependence of the shape of hailstone size distributions on the duration of sampling time. Such shape variations are associated with the sampling efficiency of the smaller size categories. The importance of the smaller sizes to the common hail integral estimates is also investigated. The minimum sizes required for sampling accuracy of these integral estimates are also obtained.
Abstract
The use of a shifted gamma size distribution for hailstone samples is proposed. This is shown to provide a better fit than the usual exponential form, using time-resolved Alberta data. It is also concluded that there is a dependence of the shape of hailstone size distributions on the duration of sampling time. Such shape variations are associated with the sampling efficiency of the smaller size categories. The importance of the smaller sizes to the common hail integral estimates is also investigated. The minimum sizes required for sampling accuracy of these integral estimates are also obtained.
Abstract
The effects of cumulus clouds on the large-scale potential vorticity field are investigated using GATE data. Clouds are found to modify the mean potential vorticity field not only through vertical mixing but also through the generation of potential vorticity by the release of latent beat. Overall, the dynamic effect and the thermodynamic effect of clouds are found to contribute about equally to the large-scale potential vorticity budget.
A diagnostic method is also developed to determine mean cloud vertical vorticity profiles from observed large-scale potential vorticity sources. The method is applied to GATE AIB-scale potential vorticity budgets. The results show that 1) the mean cloud vorticity is of the same order of magnitude as the large-scale mean vorticity, despite the smallness of the horizontal scales of cumulus clouds, and 2) the mean cloud vorticity is smaller than the large-scale mean vorticity in the mean detrainment layer of the cloud population, and larger than the large-scale mean vorticity in the mean cloud entrainment layer. These properties are in agreement with the theoretical analysis presented in Choet al. (1979a).
Abstract
The effects of cumulus clouds on the large-scale potential vorticity field are investigated using GATE data. Clouds are found to modify the mean potential vorticity field not only through vertical mixing but also through the generation of potential vorticity by the release of latent beat. Overall, the dynamic effect and the thermodynamic effect of clouds are found to contribute about equally to the large-scale potential vorticity budget.
A diagnostic method is also developed to determine mean cloud vertical vorticity profiles from observed large-scale potential vorticity sources. The method is applied to GATE AIB-scale potential vorticity budgets. The results show that 1) the mean cloud vorticity is of the same order of magnitude as the large-scale mean vorticity, despite the smallness of the horizontal scales of cumulus clouds, and 2) the mean cloud vorticity is smaller than the large-scale mean vorticity in the mean detrainment layer of the cloud population, and larger than the large-scale mean vorticity in the mean cloud entrainment layer. These properties are in agreement with the theoretical analysis presented in Choet al. (1979a).
Abstract
Soil moisture memory is a key aspect of land–atmosphere interaction and has major implications for seasonal forecasting. Because of a severe lack of soil moisture observations on most continents, existing analyses of global-scale soil moisture memory have relied previously on atmospheric general circulation model (AGCM) experiments, with derived conclusions that are probably model dependent. The present study is the first survey examining and contrasting global-scale (near) monthly soil moisture memory characteristics across a broad range of AGCMs. The investigated simulations, performed with eight different AGCMs, were generated as part of the Global Land–Atmosphere Coupling Experiment.
Overall, the AGCMs present relatively similar global patterns of soil moisture memory. Outliers are generally characterized by anomalous water-holding capacity or biases in radiation forcing. Water-holding capacity is highly variable among the analyzed AGCMs and is the main factor responsible for intermodel differences in soil moisture memory. Therefore, further studies on this topic should focus on the accurate characterization of this parameter for present AGCMs. Despite the range in the AGCMs’ behavior, the average soil moisture memory characteristics of the models appear realistic when compared to available in situ soil moisture observations. An analysis of the processes controlling soil moisture memory in the AGCMs demonstrates that it is mostly controlled by two effects: evaporation’s sensitivity to soil moisture, which increases with decreasing soil moisture content, and runoff’s sensitivity to soil moisture, which increases with increasing soil moisture content. Soil moisture memory is highest in regions of medium soil moisture content, where both effects are small.
Abstract
Soil moisture memory is a key aspect of land–atmosphere interaction and has major implications for seasonal forecasting. Because of a severe lack of soil moisture observations on most continents, existing analyses of global-scale soil moisture memory have relied previously on atmospheric general circulation model (AGCM) experiments, with derived conclusions that are probably model dependent. The present study is the first survey examining and contrasting global-scale (near) monthly soil moisture memory characteristics across a broad range of AGCMs. The investigated simulations, performed with eight different AGCMs, were generated as part of the Global Land–Atmosphere Coupling Experiment.
Overall, the AGCMs present relatively similar global patterns of soil moisture memory. Outliers are generally characterized by anomalous water-holding capacity or biases in radiation forcing. Water-holding capacity is highly variable among the analyzed AGCMs and is the main factor responsible for intermodel differences in soil moisture memory. Therefore, further studies on this topic should focus on the accurate characterization of this parameter for present AGCMs. Despite the range in the AGCMs’ behavior, the average soil moisture memory characteristics of the models appear realistic when compared to available in situ soil moisture observations. An analysis of the processes controlling soil moisture memory in the AGCMs demonstrates that it is mostly controlled by two effects: evaporation’s sensitivity to soil moisture, which increases with decreasing soil moisture content, and runoff’s sensitivity to soil moisture, which increases with increasing soil moisture content. Soil moisture memory is highest in regions of medium soil moisture content, where both effects are small.
Abstract
The 12 weather and climate models participating in the Global Land–Atmosphere Coupling Experiment (GLACE) show both a wide variation in the strength of land–atmosphere coupling and some intriguing commonalities. In this paper, the causes of variations in coupling strength—both the geographic variations within a given model and the model-to-model differences—are addressed. The ability of soil moisture to affect precipitation is examined in two stages, namely, the ability of the soil moisture to affect evaporation, and the ability of evaporation to affect precipitation. Most of the differences between the models and within a given model are found to be associated with the first stage—an evaporation rate that varies strongly and consistently with soil moisture tends to lead to a higher coupling strength. The first-stage differences reflect identifiable differences in model parameterization and model climate. Intermodel differences in the evaporation–precipitation connection, however, also play a key role.
Abstract
The 12 weather and climate models participating in the Global Land–Atmosphere Coupling Experiment (GLACE) show both a wide variation in the strength of land–atmosphere coupling and some intriguing commonalities. In this paper, the causes of variations in coupling strength—both the geographic variations within a given model and the model-to-model differences—are addressed. The ability of soil moisture to affect precipitation is examined in two stages, namely, the ability of the soil moisture to affect evaporation, and the ability of evaporation to affect precipitation. Most of the differences between the models and within a given model are found to be associated with the first stage—an evaporation rate that varies strongly and consistently with soil moisture tends to lead to a higher coupling strength. The first-stage differences reflect identifiable differences in model parameterization and model climate. Intermodel differences in the evaporation–precipitation connection, however, also play a key role.
Abstract
The Global Land–Atmosphere Coupling Experiment (GLACE) is a model intercomparison study focusing on a typically neglected yet critical element of numerical weather and climate modeling: land–atmosphere coupling strength, or the degree to which anomalies in land surface state (e.g., soil moisture) can affect rainfall generation and other atmospheric processes. The 12 AGCM groups participating in GLACE performed a series of simple numerical experiments that allow the objective quantification of this element for boreal summer. The derived coupling strengths vary widely. Some similarity, however, is found in the spatial patterns generated by the models, with enough similarity to pinpoint multimodel “hot spots” of land–atmosphere coupling. For boreal summer, such hot spots for precipitation and temperature are found over large regions of Africa, central North America, and India; a hot spot for temperature is also found over eastern China. The design of the GLACE simulations are described in full detail so that any interested modeling group can repeat them easily and thereby place their model’s coupling strength within the broad range of those documented here.
Abstract
The Global Land–Atmosphere Coupling Experiment (GLACE) is a model intercomparison study focusing on a typically neglected yet critical element of numerical weather and climate modeling: land–atmosphere coupling strength, or the degree to which anomalies in land surface state (e.g., soil moisture) can affect rainfall generation and other atmospheric processes. The 12 AGCM groups participating in GLACE performed a series of simple numerical experiments that allow the objective quantification of this element for boreal summer. The derived coupling strengths vary widely. Some similarity, however, is found in the spatial patterns generated by the models, with enough similarity to pinpoint multimodel “hot spots” of land–atmosphere coupling. For boreal summer, such hot spots for precipitation and temperature are found over large regions of Africa, central North America, and India; a hot spot for temperature is also found over eastern China. The design of the GLACE simulations are described in full detail so that any interested modeling group can repeat them easily and thereby place their model’s coupling strength within the broad range of those documented here.
