Search Results
You are looking at 1 - 10 of 22 items for
- Author or Editor: Kenneth C. Young x
- Refine by Access: All Content x
Abstract
The effects of simplifications in the derivation of the Köhler equation describing the equilibrium saturation ratio for solution drops as a function of size on the activation of a population of CCN in an updraft are examined. Simulations based on the conventional form of the Köhler equation underestimate the numbers of droplets nucleated in a 2 m s−1 updraft by roughly 10%. The most simplified form of the Köhler equation using the van't Hoff factor for dilute solutions estimated the number of droplets nucleated to within 1%.
Abstract
The effects of simplifications in the derivation of the Köhler equation describing the equilibrium saturation ratio for solution drops as a function of size on the activation of a population of CCN in an updraft are examined. Simulations based on the conventional form of the Köhler equation underestimate the numbers of droplets nucleated in a 2 m s−1 updraft by roughly 10%. The most simplified form of the Köhler equation using the van't Hoff factor for dilute solutions estimated the number of droplets nucleated to within 1%.
Abstract
Mixing processes within the hall growth zone are examined as they pertain to competition within a population of growing hailstones. Mixing is demonstrated to produce broader particle spectra than predicted by the deterministic type of model. Mixing is also noted to promote unequal competition through spectral broadening and cannot be assumed to assure equal competition in the sense implied by Sulakvelidze et al. (1974) in regard to hall suppression by beneficial competition.
Treatment of particles in ensemble fashion likewise assumes equal competition. If the number of particles contained within an ensemble is very large, the resulting particle spectra may be narrower than if the particles were partitioned among several ensembles. This type of nonphysical competition is termed “numerical competition” and may lead to serious errors in model predictions of hail growth and fallout.
Abstract
Mixing processes within the hall growth zone are examined as they pertain to competition within a population of growing hailstones. Mixing is demonstrated to produce broader particle spectra than predicted by the deterministic type of model. Mixing is also noted to promote unequal competition through spectral broadening and cannot be assumed to assure equal competition in the sense implied by Sulakvelidze et al. (1974) in regard to hall suppression by beneficial competition.
Treatment of particles in ensemble fashion likewise assumes equal competition. If the number of particles contained within an ensemble is very large, the resulting particle spectra may be narrower than if the particles were partitioned among several ensembles. This type of nonphysical competition is termed “numerical competition” and may lead to serious errors in model predictions of hail growth and fallout.
Abstract
A numerical model of warm rain processes incorporating activation of cloud condensation nuclei, drop growth by condensation and stochastic coalescence, and drop breakup is described. A collisional breakup model is compared to a spontaneous disintegration model and found not only to dominate over the spontaneous disintegration model but to produce an exponential spectrum in fair agreement with average observed drop spectra. The steady-state spectrum was found to be quite insensitive to the number of satellite drops farmed by collision or their size distribution.
The effect of the finite-difference solution to the collection and breakup equations is analysed. A properly stochastic formulation for finite time steps is presented but found to differ only slightly from the simpler, “discrete” formulation. Time stops of 5 s and 45 size categories are found adequate to describe the essential quantitative features of more intensive treatments.
The model results were found to be somewhat sensitive to values used for the collection efficiency.
Abstract
A numerical model of warm rain processes incorporating activation of cloud condensation nuclei, drop growth by condensation and stochastic coalescence, and drop breakup is described. A collisional breakup model is compared to a spontaneous disintegration model and found not only to dominate over the spontaneous disintegration model but to produce an exponential spectrum in fair agreement with average observed drop spectra. The steady-state spectrum was found to be quite insensitive to the number of satellite drops farmed by collision or their size distribution.
The effect of the finite-difference solution to the collection and breakup equations is analysed. A properly stochastic formulation for finite time steps is presented but found to differ only slightly from the simpler, “discrete” formulation. Time stops of 5 s and 45 size categories are found adequate to describe the essential quantitative features of more intensive treatments.
The model results were found to be somewhat sensitive to values used for the collection efficiency.
Abstract
Ice particle multiplication mechanisms are summarized and considered to be incapable of producing the excess of ice crystals over ice nuclei (factors of 102–104) observed in several types of clouds. Contact freezing, sorption and immersion freezing nucleation are re-examined with regard to their temperature and mode of activation.
A model of ice phase nucleation based on contact nucleation is advanced. The collection of contact nuclei by drops is considered to result from Brownian motion and phoretic forces. Based on estimated sizes for natural contact nuclei of 0.3–0.5 μm, contact nueleation is predicted to be suppressed in updrafts and enhanced in downdrafts or mixing zones. This correlation is in excellent agreement with observations of first ice in cumuli. Blanchard's drop freezing data are used to deduce concentrations of natural contact nuclei active at −4C of 100–1000 liter−1. These concentrations are noted to be consistent with Hobbs’ observations of 1–10 ice particles liter−1 at −4C in an orographic cap cloud.
Abstract
Ice particle multiplication mechanisms are summarized and considered to be incapable of producing the excess of ice crystals over ice nuclei (factors of 102–104) observed in several types of clouds. Contact freezing, sorption and immersion freezing nucleation are re-examined with regard to their temperature and mode of activation.
A model of ice phase nucleation based on contact nucleation is advanced. The collection of contact nuclei by drops is considered to result from Brownian motion and phoretic forces. Based on estimated sizes for natural contact nuclei of 0.3–0.5 μm, contact nueleation is predicted to be suppressed in updrafts and enhanced in downdrafts or mixing zones. This correlation is in excellent agreement with observations of first ice in cumuli. Blanchard's drop freezing data are used to deduce concentrations of natural contact nuclei active at −4C of 100–1000 liter−1. These concentrations are noted to be consistent with Hobbs’ observations of 1–10 ice particles liter−1 at −4C in an orographic cap cloud.
Abstract
A numerical model which extends treatment of microphysical cloud processes to more than one level through use of the continuous bin technique is described. A general solution to the diffusion growth equation including latent heat release due to accretion is presented. Collection processes of coalescence, accretion and aggregation, activation of CCN, and ice phase nucleation through sorption and contact freezing nucleation are combined with a diffusion treatment which allows for calculation of the supersaturation in a multi-level framework and with sedimentation of particles between levels.
Abstract
A numerical model which extends treatment of microphysical cloud processes to more than one level through use of the continuous bin technique is described. A general solution to the diffusion growth equation including latent heat release due to accretion is presented. Collection processes of coalescence, accretion and aggregation, activation of CCN, and ice phase nucleation through sorption and contact freezing nucleation are combined with a diffusion treatment which allows for calculation of the supersaturation in a multi-level framework and with sedimentation of particles between levels.
Abstract
The multi-level, microphysical cloud model described in the accompanying article is applied in an orographic situation to simulate the development of precipitation under both natural and seeded conditions. In the case studied, a 1600 m thick cloud deck (base and top temperature of 0 and −10C) extends well west of a barrier ridge (top 3100 m MSL). Streamlines for flow over the barrier were taken as input to the model.
The model predicts a natural precipitation rate of 0.06 gm sec−1 for a 1 cm path width over the barrier. This can be increased 500-fold through cloud-top seeding with AgI at 40 km upwind of the ridge crest and represents a precipitation efficiency of 19.5%. The proper distance upwind for cloud-top seeding may be determined from the streamlines using a fall velocity of 1.2—1.4 m sec−1 starting 5 min after seeding.
These findings support previous observations that seeding orographic clouds to increase precipitation is likely to be more successful when the cloud-top temperatures are too warm for significant ice phase nucleation to occur naturally. Cloud-top seeding is suggested to be more efficient than ground-based seeding in targeting the resultant precipitation on the ridge crest, thereby reducing subcloud evaporation losses.
Abstract
The multi-level, microphysical cloud model described in the accompanying article is applied in an orographic situation to simulate the development of precipitation under both natural and seeded conditions. In the case studied, a 1600 m thick cloud deck (base and top temperature of 0 and −10C) extends well west of a barrier ridge (top 3100 m MSL). Streamlines for flow over the barrier were taken as input to the model.
The model predicts a natural precipitation rate of 0.06 gm sec−1 for a 1 cm path width over the barrier. This can be increased 500-fold through cloud-top seeding with AgI at 40 km upwind of the ridge crest and represents a precipitation efficiency of 19.5%. The proper distance upwind for cloud-top seeding may be determined from the streamlines using a fall velocity of 1.2—1.4 m sec−1 starting 5 min after seeding.
These findings support previous observations that seeding orographic clouds to increase precipitation is likely to be more successful when the cloud-top temperatures are too warm for significant ice phase nucleation to occur naturally. Cloud-top seeding is suggested to be more efficient than ground-based seeding in targeting the resultant precipitation on the ridge crest, thereby reducing subcloud evaporation losses.
Early progress in weather modification is attributed to a healthy interaction between theory and experiment. During the 1970s, a divergence of approaches took place. A “theoretical/experimental” approach, exemplified by the Cascade Project, focused on testing scientific hypotheses; an “observational/experimental” approach, exemplified by the Colorado River Basin Pilot Project, sought to enhance understanding of the seeding process through more detailed observations.
The theoretical/experimental school soon came to focus almost exclusively on natural cloud processes, leaving the field of weather modification nearly devoid of a theoretical component. It is suggested that this theoretical component is necessary to revitalize the field of weather modification.
Key questions are addressed. These include 1) identification of clouds that are amenable to seeding; 2) glaciogenic versus hygroscopic seeding; 3) optimizing critical seeding variables, such as seed particle concentration for glaciogenic seeding and seed particle size for hygroscopic seeding; and 4) seeding for hail suppression.
Early progress in weather modification is attributed to a healthy interaction between theory and experiment. During the 1970s, a divergence of approaches took place. A “theoretical/experimental” approach, exemplified by the Cascade Project, focused on testing scientific hypotheses; an “observational/experimental” approach, exemplified by the Colorado River Basin Pilot Project, sought to enhance understanding of the seeding process through more detailed observations.
The theoretical/experimental school soon came to focus almost exclusively on natural cloud processes, leaving the field of weather modification nearly devoid of a theoretical component. It is suggested that this theoretical component is necessary to revitalize the field of weather modification.
Key questions are addressed. These include 1) identification of clouds that are amenable to seeding; 2) glaciogenic versus hygroscopic seeding; 3) optimizing critical seeding variables, such as seed particle concentration for glaciogenic seeding and seed particle size for hygroscopic seeding; and 4) seeding for hail suppression.
Abstract
A method is described for simultaneously simulating maximum and minimum temperatures and daily precipitation amounts in a physically consistent manner. The method “chains” actual days from a historical dataset by defining a “discriminant space” using multiple discriminant analysis. A set of analogous days is selected from discriminant space using a nearest-neighbor search. The next day in the chain is the day subsequent to a randomly selected day from the set of analogous days. The method was tested on data for Tucson and Safford, Arizona.
A high degree of similarity between the simulated and observed data was found. A slight tendency to underestimate the variance of monthly average temperatures was noted. The distribution of monthly temperature extremes was quite well reproduced with the exception of a tendency to be conservative in predicting the warmest minimum temperatures and the coolest maximum temperatures. Very little difference between the simulated and observed distributions of diurnal temperature range was found.
The median and 90th percentile of monthly precipitation totals were well reproduced. A tendency to underestimate the frequency of dry months was noted. The frequency of runs of wet and dry days of different lengths was found to be not significantly different for the simulated and observed data. Reproduction of wet-day run frequency for the first-order multivariate chain model was comparable to that using a two-state, first-order Markov chain.
Abstract
A method is described for simultaneously simulating maximum and minimum temperatures and daily precipitation amounts in a physically consistent manner. The method “chains” actual days from a historical dataset by defining a “discriminant space” using multiple discriminant analysis. A set of analogous days is selected from discriminant space using a nearest-neighbor search. The next day in the chain is the day subsequent to a randomly selected day from the set of analogous days. The method was tested on data for Tucson and Safford, Arizona.
A high degree of similarity between the simulated and observed data was found. A slight tendency to underestimate the variance of monthly average temperatures was noted. The distribution of monthly temperature extremes was quite well reproduced with the exception of a tendency to be conservative in predicting the warmest minimum temperatures and the coolest maximum temperatures. Very little difference between the simulated and observed distributions of diurnal temperature range was found.
The median and 90th percentile of monthly precipitation totals were well reproduced. A tendency to underestimate the frequency of dry months was noted. The frequency of runs of wet and dry days of different lengths was found to be not significantly different for the simulated and observed data. Reproduction of wet-day run frequency for the first-order multivariate chain model was comparable to that using a two-state, first-order Markov chain.
Abstract
A heat budget model to predict heat stress in humans during exercise is developed. The model considers the transfer of heat by conduction/convection from the skin (C), the latent heat due to evaporation from the skin (E), the sensible and latent heat exchanges due to respiration (CR and ER ) and the heat gain due to solar radiation. Heat generated in the body core is conducted to the skin in accordance with a body conductance which is a function of the level of dehydration. The skin temperature is calculated assuming no heat storage, balancing C+E−R with the heat conducted from the body core to the skin. Heat that cannot be dissipated is assumed to elevate the core temperature. The model predicts the core and skin temperatures and moisture loss as a function of time.
The model is used to define the maximum recommended duration of exercise (MRDE) as a function of ambient conditions and the level of exercise. Comparisons between daytime and nighttime conditions and light- and dark-colored clothing are made. MRDE charts for six different levels of exercise are given. It is suggested that these be used as guides in limiting exercise when the possibility of heat exhaustion is indicated.
Abstract
A heat budget model to predict heat stress in humans during exercise is developed. The model considers the transfer of heat by conduction/convection from the skin (C), the latent heat due to evaporation from the skin (E), the sensible and latent heat exchanges due to respiration (CR and ER ) and the heat gain due to solar radiation. Heat generated in the body core is conducted to the skin in accordance with a body conductance which is a function of the level of dehydration. The skin temperature is calculated assuming no heat storage, balancing C+E−R with the heat conducted from the body core to the skin. Heat that cannot be dissipated is assumed to elevate the core temperature. The model predicts the core and skin temperatures and moisture loss as a function of time.
The model is used to define the maximum recommended duration of exercise (MRDE) as a function of ambient conditions and the level of exercise. Comparisons between daytime and nighttime conditions and light- and dark-colored clothing are made. MRDE charts for six different levels of exercise are given. It is suggested that these be used as guides in limiting exercise when the possibility of heat exhaustion is indicated.
Abstract
An adaptive, three-way interpolation model based on multiple discriminant analysis, multiple linear regression, and normal ratio methods was used to reconstruct streamflows for three gauges in central Arizona for the period from 1580, using available annual tree ring indices and monthly precipitation. The reduction in mean absolute error compared to the use of the long-term mean for the period reconstructed from tree ring data only (1580–1863) was roughly 30% for both annual and spring streamflow; the corresponding reduction in mean absolute error when monthly precipitation values were included was roughly 60%.
The reconstruction procedures were noted to produce a negative bias due to the positive skewness of the streamflow values. Procedures to correct for this bias and restore the variance of the streamflow time series are described. Reconstructed and adjusted annual and spring (February–May) streamflows are provided for the Verde and Salt Rivers and the Tonto Creek.
A harmonic analysis of the reconstructed and adjusted annual streamflow time series from 1848 through 1989 shows a 70-year cycle (P-value > 99.5% ) and a 5.2-year cycle (P-value > 99.9% ) for each of the three gauges. Correlation coefficients between the 70-year-cycle-projected streamflow and the reconstructed and adjusted streamflow for the period 1589–1847 were between 14.6% and 20.5% for the three gauges, all significant at P- value > 99% .
Abstract
An adaptive, three-way interpolation model based on multiple discriminant analysis, multiple linear regression, and normal ratio methods was used to reconstruct streamflows for three gauges in central Arizona for the period from 1580, using available annual tree ring indices and monthly precipitation. The reduction in mean absolute error compared to the use of the long-term mean for the period reconstructed from tree ring data only (1580–1863) was roughly 30% for both annual and spring streamflow; the corresponding reduction in mean absolute error when monthly precipitation values were included was roughly 60%.
The reconstruction procedures were noted to produce a negative bias due to the positive skewness of the streamflow values. Procedures to correct for this bias and restore the variance of the streamflow time series are described. Reconstructed and adjusted annual and spring (February–May) streamflows are provided for the Verde and Salt Rivers and the Tonto Creek.
A harmonic analysis of the reconstructed and adjusted annual streamflow time series from 1848 through 1989 shows a 70-year cycle (P-value > 99.5% ) and a 5.2-year cycle (P-value > 99.9% ) for each of the three gauges. Correlation coefficients between the 70-year-cycle-projected streamflow and the reconstructed and adjusted streamflow for the period 1589–1847 were between 14.6% and 20.5% for the three gauges, all significant at P- value > 99% .
