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The application of three-dimensional time-dependent models to weather modification experiments along with the ways in which mesoscale simulations may be used as an aid in clarifying and formulating the physical basis of a weather modification hypothesis is discussed. It is furthermore pointed out that such models can be an aid in the design of field experiments, in the evaluation of field experiments, and in decision making during the daily operations of the experiment. Not only does the challenge of weather modification require considerable advancement in our understanding of the complex physics and dynamics of mesoscale processes, but it is also essential that we develop parameterizations of these processes in order for a mesoscale model to be of value in the post hoc analyses of weather modification experiments and as a decision aid.
The application of three-dimensional time-dependent models to weather modification experiments along with the ways in which mesoscale simulations may be used as an aid in clarifying and formulating the physical basis of a weather modification hypothesis is discussed. It is furthermore pointed out that such models can be an aid in the design of field experiments, in the evaluation of field experiments, and in decision making during the daily operations of the experiment. Not only does the challenge of weather modification require considerable advancement in our understanding of the complex physics and dynamics of mesoscale processes, but it is also essential that we develop parameterizations of these processes in order for a mesoscale model to be of value in the post hoc analyses of weather modification experiments and as a decision aid.
Abstract
We examine the potential role of aerosol pollution on the rainfall and intensity of Hurricane Harvey. For this study, we use the global model, Ocean–Land–Atmosphere Model (OLAM), with aerosol estimates from the global atmospheric chemistry model GEOS-Chem. Two sets of simulations of Hurricane Harvey were performed. Simulations in the first set cover the intensification phase of Harvey until initial landfall in Texas and focus on the sensitivity of storm track and intensity, while simulations in the second set examine the sensitivity of storm track and precipitation during the period after initial landfall when record flooding occurred near Houston. During each period, simulations were performed with no anthropogenic sources of aerosol, with both natural and anthropogenic aerosol sources, and with both sources enhanced 10 times. During the rapid intensification phase, the results indicate that aerosol amounts had very little impact on storm motion. Moreover, very little difference was found on the intensity of the simulated storm to aerosol amounts for the no-anthropogenic versus the GEOS-Chem estimated amounts with anthropogenic sources. However, when both natural and anthropogenic aerosol amounts were enhanced 10 times, the simulated storm intensity was enhanced appreciably in terms of minimum sea level pressure. During the second period of the simulation, through which Harvey remained a tropical storm, the main result was that very little sensitivity was found in precipitation or any other tropical cyclone (TC) characteristic to aerosol concentrations. We cannot definitively state why the individual convective cells did not respond to high aerosol concentrations during this phase of the storm. However, the abundant precipitation in all three simulations scavenged the vast majority of aerosols as it flowed radially inward, and we speculate that this modulated the potential impact of aerosols on the inner TC and eyewall. Overall, the simulated response of Hurricane Harvey to aerosols was far less spectacular than what has been simulated in the past. We conclude that this is because Hurricane Harvey was a strongly dynamically driven storm system that as a result was relatively impervious to the effects of aerosols.
Abstract
We examine the potential role of aerosol pollution on the rainfall and intensity of Hurricane Harvey. For this study, we use the global model, Ocean–Land–Atmosphere Model (OLAM), with aerosol estimates from the global atmospheric chemistry model GEOS-Chem. Two sets of simulations of Hurricane Harvey were performed. Simulations in the first set cover the intensification phase of Harvey until initial landfall in Texas and focus on the sensitivity of storm track and intensity, while simulations in the second set examine the sensitivity of storm track and precipitation during the period after initial landfall when record flooding occurred near Houston. During each period, simulations were performed with no anthropogenic sources of aerosol, with both natural and anthropogenic aerosol sources, and with both sources enhanced 10 times. During the rapid intensification phase, the results indicate that aerosol amounts had very little impact on storm motion. Moreover, very little difference was found on the intensity of the simulated storm to aerosol amounts for the no-anthropogenic versus the GEOS-Chem estimated amounts with anthropogenic sources. However, when both natural and anthropogenic aerosol amounts were enhanced 10 times, the simulated storm intensity was enhanced appreciably in terms of minimum sea level pressure. During the second period of the simulation, through which Harvey remained a tropical storm, the main result was that very little sensitivity was found in precipitation or any other tropical cyclone (TC) characteristic to aerosol concentrations. We cannot definitively state why the individual convective cells did not respond to high aerosol concentrations during this phase of the storm. However, the abundant precipitation in all three simulations scavenged the vast majority of aerosols as it flowed radially inward, and we speculate that this modulated the potential impact of aerosols on the inner TC and eyewall. Overall, the simulated response of Hurricane Harvey to aerosols was far less spectacular than what has been simulated in the past. We conclude that this is because Hurricane Harvey was a strongly dynamically driven storm system that as a result was relatively impervious to the effects of aerosols.
Abstract
Idealized large-eddy simulations (LESs) are performed of deep convective clouds over south Florida to examine the relative role of aerosol-induced condensational versus mixed-phase invigoration to convective intensity and rainfall. Aerosol concentrations and chemistry are represented by using output from the GEOS-Chem global atmospheric chemistry model run with and without anthropogenic aerosol sources. The results clearly show that higher aerosol concentrations result in enhanced precipitation, larger amounts of cloud liquid water content, enhanced updraft velocities during the latter part of the simulation, and a modest enhancement of the latent heating of condensation. Overall, our results are consistent with the concept that convective cloud invigoration is mainly due to condensational invigoration and not primarily to mixed-phase invigoration. Furthermore, our results suggest that condensational invigoration can result in appreciable precipitation enhancement of ordinary warm-based convective clouds such as are common in locations like south Florida.
Abstract
Idealized large-eddy simulations (LESs) are performed of deep convective clouds over south Florida to examine the relative role of aerosol-induced condensational versus mixed-phase invigoration to convective intensity and rainfall. Aerosol concentrations and chemistry are represented by using output from the GEOS-Chem global atmospheric chemistry model run with and without anthropogenic aerosol sources. The results clearly show that higher aerosol concentrations result in enhanced precipitation, larger amounts of cloud liquid water content, enhanced updraft velocities during the latter part of the simulation, and a modest enhancement of the latent heating of condensation. Overall, our results are consistent with the concept that convective cloud invigoration is mainly due to condensational invigoration and not primarily to mixed-phase invigoration. Furthermore, our results suggest that condensational invigoration can result in appreciable precipitation enhancement of ordinary warm-based convective clouds such as are common in locations like south Florida.
Abstract
The North American monsoon system is known to produce significant summertime precipitation on the west coast of Mexico and the southwestern United States, with some areas receiving greater than 50% of their yearly rainfall between the months of July and September. The onset of the monsoon is attributed to a shift in the large-scale upper-level anticyclonic flow over the central United States, and the associated increases in moisture flux and resulting precipitation are tied to the low-level jets from the Gulf of California and the Gulf of Mexico. Individual monsoon surge events vary in intensity, as does the magnitude of the diurnal cycle of the low-level jets and precipitation. Numerical modeling and forecasting of these interacting large-and mesoscale monsoon features is often difficult in terms of accurately recreating the varying flow regimes aloft and near the surface and over both the flat and steep terrain that are encompassed within the monsoon region of influence.
The Regional Atmospheric Modeling System (RAMS) at Colorado State University has been utilized to investigate seasonal monsoon simulations for the 1988 (United States drought), 1993 (Midwest flood), and 1997 (El Niño year) monsoon seasons. In Part I of this paper the credibility of RAMS, as far as its ability to reproduce observed features of the North American monsoon system, is evaluated. Part II provides interseasonal comparisons of model-simulated monsoon features from the three simulated extreme seasons and results of sensitivity studies to SSTs and soil moisture variability. Part III presents the development of potential vorticity anomalies associated with convection over Mexico and their downstream influence over the central United States.
Abstract
The North American monsoon system is known to produce significant summertime precipitation on the west coast of Mexico and the southwestern United States, with some areas receiving greater than 50% of their yearly rainfall between the months of July and September. The onset of the monsoon is attributed to a shift in the large-scale upper-level anticyclonic flow over the central United States, and the associated increases in moisture flux and resulting precipitation are tied to the low-level jets from the Gulf of California and the Gulf of Mexico. Individual monsoon surge events vary in intensity, as does the magnitude of the diurnal cycle of the low-level jets and precipitation. Numerical modeling and forecasting of these interacting large-and mesoscale monsoon features is often difficult in terms of accurately recreating the varying flow regimes aloft and near the surface and over both the flat and steep terrain that are encompassed within the monsoon region of influence.
The Regional Atmospheric Modeling System (RAMS) at Colorado State University has been utilized to investigate seasonal monsoon simulations for the 1988 (United States drought), 1993 (Midwest flood), and 1997 (El Niño year) monsoon seasons. In Part I of this paper the credibility of RAMS, as far as its ability to reproduce observed features of the North American monsoon system, is evaluated. Part II provides interseasonal comparisons of model-simulated monsoon features from the three simulated extreme seasons and results of sensitivity studies to SSTs and soil moisture variability. Part III presents the development of potential vorticity anomalies associated with convection over Mexico and their downstream influence over the central United States.
Abstract
At Colorado State University the Regional Atmospheric Modeling System (RAMS) has been used to produce real-time forecasts of precipitation for the Colorado mountain region since 1991. Originally a so-called dump-bucket scheme was used to generate precipitation, but starting in the fall of 1995 real-time forecasts used the bulk microphysics scheme available with RAMS.
For the month of April 1995, a series of 24-h accumulated precipitation forecasts for the month were generated with both the dump-bucket and microphysics versions of the forecast model. Both sets of output were compared to a set of 167 community-based station reports and another set of 32 snow telemetry (SNOTEL) automatic pillow-sensor stations.
The addition of microphysics improved the forecasting of the areal extent and maximum amount of precipitation, especially when compared to the SNOTEL observational set, which is found at locations more representative of the model topography. Climatological station precipitation forecasts were improved on the average by correcting for the difference between a station’s actual elevation and the cell-averaged topography used by the model. The model had more problems with the precise timing and geographical location of the precipitation features, probably due in part to the influence of other model physics, the failure of the model to resolve adequately wintertime convection events, and inadequate initializations.
Abstract
At Colorado State University the Regional Atmospheric Modeling System (RAMS) has been used to produce real-time forecasts of precipitation for the Colorado mountain region since 1991. Originally a so-called dump-bucket scheme was used to generate precipitation, but starting in the fall of 1995 real-time forecasts used the bulk microphysics scheme available with RAMS.
For the month of April 1995, a series of 24-h accumulated precipitation forecasts for the month were generated with both the dump-bucket and microphysics versions of the forecast model. Both sets of output were compared to a set of 167 community-based station reports and another set of 32 snow telemetry (SNOTEL) automatic pillow-sensor stations.
The addition of microphysics improved the forecasting of the areal extent and maximum amount of precipitation, especially when compared to the SNOTEL observational set, which is found at locations more representative of the model topography. Climatological station precipitation forecasts were improved on the average by correcting for the difference between a station’s actual elevation and the cell-averaged topography used by the model. The model had more problems with the precise timing and geographical location of the precipitation features, probably due in part to the influence of other model physics, the failure of the model to resolve adequately wintertime convection events, and inadequate initializations.
Abstract
Mesoscale convective systems (MCSs) have a large influence on the weather over the central United States during the warm season by generating essential rainfall and severe weather. To gain insight into the predictability of these systems, the precursor environments of several hundred MCSs across the United States were reviewed during the warm seasons of 1996–98. Surface analyses were used to identify initiating mechanisms for each system, and North American Regional Reanalysis (NARR) data were used to examine the environment prior to MCS development. Similarly, environments unable to support organized convective systems were also investigated for comparison with MCS precursor environments. Significant differences were found between environments that support MCS development and those that do not support convective organization. MCSs were most commonly initiated by frontal boundaries; however, features that enhance convective initiation are often not sufficient for MCS development, as the environment needs also to be supportive for the development and organization of long-lived convective systems. Low-level warm air advection, low-level vertical wind shear, and convective instability were found to be the most important parameters in determining whether concentrated convection would undergo upscale growth into an MCS. Based on these results, an index was developed for use in forecasting MCSs. The MCS index assigns a likelihood of MCS development based on three terms: 700-hPa temperature advection, 0–3-km vertical wind shear, and the lifted index. An evaluation of the MCS index revealed that it exhibits features consistent with common MCS characteristics and is reasonably accurate in forecasting MCSs, especially given that convective initiation has occurred, offering the possibility of usefulness in operational forecasting.
Abstract
Mesoscale convective systems (MCSs) have a large influence on the weather over the central United States during the warm season by generating essential rainfall and severe weather. To gain insight into the predictability of these systems, the precursor environments of several hundred MCSs across the United States were reviewed during the warm seasons of 1996–98. Surface analyses were used to identify initiating mechanisms for each system, and North American Regional Reanalysis (NARR) data were used to examine the environment prior to MCS development. Similarly, environments unable to support organized convective systems were also investigated for comparison with MCS precursor environments. Significant differences were found between environments that support MCS development and those that do not support convective organization. MCSs were most commonly initiated by frontal boundaries; however, features that enhance convective initiation are often not sufficient for MCS development, as the environment needs also to be supportive for the development and organization of long-lived convective systems. Low-level warm air advection, low-level vertical wind shear, and convective instability were found to be the most important parameters in determining whether concentrated convection would undergo upscale growth into an MCS. Based on these results, an index was developed for use in forecasting MCSs. The MCS index assigns a likelihood of MCS development based on three terms: 700-hPa temperature advection, 0–3-km vertical wind shear, and the lifted index. An evaluation of the MCS index revealed that it exhibits features consistent with common MCS characteristics and is reasonably accurate in forecasting MCSs, especially given that convective initiation has occurred, offering the possibility of usefulness in operational forecasting.
Abstract
This study examines the sensitivity of varying the horizontal heterogeneities of the soil moisture initialization (SMI) in the cloud-resolving grid of a real-data simulation of a midlatitude mesoscale convective system (MCS) during its genesis phase. The quasi-stationary MCS of this study formed in the Texas/Oklahoma panhandle with a lifetime of 9 h (2200 UTC 26 July to 0700 UTC 27 July 1998). Soil moisture for the finest nested grid (the cloud-resolving grid) was derived from the antecedent precipitation index (API) using 4-km-grid-spacing precipitation data for a 3-month period. In order to vary the heterogeneities of the SMI in the cloud-resolving grid, (i) Barnes objective analysis was used to alter the resolution of the soil moisture initialization, (ii) the amplitudes of the soil moisture anomalies were reduced, (iii) the position of a soil moisture anomaly was altered, and (iv) two experiments with homogeneous SMI (31% and 50% saturation) were performed. Because of the severe drought in the Texas/Oklahoma panhandle area, the saturation API value was lowered in order to introduce heterogeneities in the soil moisture for the sensitivity experiments.
All of the experiments with heterogeneous SMI (in addition to an experiment with a homogeneous SMI at 31% saturation) produced an MCS with a quasi-circular cloud shield, similar to the observed timing, size, and location. The authors' findings suggest that a soil moisture dataset with approximately 40-km grid spacing may be adequate to initialize a cloud-resolving model for simulating MCSs. For the simulations in this study, the soil moisture distribution determined where convection was likely to occur. Wetter soil tended to suppress convection for this case, and convection preferentially occurred around the peripheries of wet soil moisture anomalies.
Abstract
This study examines the sensitivity of varying the horizontal heterogeneities of the soil moisture initialization (SMI) in the cloud-resolving grid of a real-data simulation of a midlatitude mesoscale convective system (MCS) during its genesis phase. The quasi-stationary MCS of this study formed in the Texas/Oklahoma panhandle with a lifetime of 9 h (2200 UTC 26 July to 0700 UTC 27 July 1998). Soil moisture for the finest nested grid (the cloud-resolving grid) was derived from the antecedent precipitation index (API) using 4-km-grid-spacing precipitation data for a 3-month period. In order to vary the heterogeneities of the SMI in the cloud-resolving grid, (i) Barnes objective analysis was used to alter the resolution of the soil moisture initialization, (ii) the amplitudes of the soil moisture anomalies were reduced, (iii) the position of a soil moisture anomaly was altered, and (iv) two experiments with homogeneous SMI (31% and 50% saturation) were performed. Because of the severe drought in the Texas/Oklahoma panhandle area, the saturation API value was lowered in order to introduce heterogeneities in the soil moisture for the sensitivity experiments.
All of the experiments with heterogeneous SMI (in addition to an experiment with a homogeneous SMI at 31% saturation) produced an MCS with a quasi-circular cloud shield, similar to the observed timing, size, and location. The authors' findings suggest that a soil moisture dataset with approximately 40-km grid spacing may be adequate to initialize a cloud-resolving model for simulating MCSs. For the simulations in this study, the soil moisture distribution determined where convection was likely to occur. Wetter soil tended to suppress convection for this case, and convection preferentially occurred around the peripheries of wet soil moisture anomalies.
Abstract
The impacts of urban-enhanced aerosol concentrations on convective storm development and precipitation over and downwind of St. Louis, Missouri, are investigated. This is achieved through the use of a cloud-resolving mesoscale model, in which sophisticated land use processes and aerosol microphysics are both incorporated. The results indicate that urban-forced convergence downwind of the city, rather than the presence of greater aerosol concentrations, determines whether storms actually develop in the downwind region. Once convection is initiated, urban-enhanced aerosols can exert a significant effect on the dynamics, microphysics, and precipitation produced by these storms. The model results indicate, however, that the response to urban-enhanced aerosol depends on the background concentrations of aerosols; a weaker response occurs with increasing background aerosol concentrations. The effects of aerosols influence the rate and amount of liquid water and ice produced within these storms, the accumulated surface precipitation, the strength and timing of the updrafts and downdrafts, the longevity of the updrafts, and the strength and influence of the cold pool. Complex, nonlinear relationships and feedbacks between the microphysics and storm dynamics exist, making it difficult to make definitive statements about the effects of urban-enhanced aerosols on downwind precipitation and convection. Because the impacts of urban aerosol on downwind storms decrease with increasing background aerosol concentrations, generalization of these results depends on the unique character of background aerosol for each urban area. For urban centers in coastal areas where background aerosol concentrations may be very low, it is speculated that urban aerosol can have very large influences on convective storm dynamics, microphysics, and precipitation.
Abstract
The impacts of urban-enhanced aerosol concentrations on convective storm development and precipitation over and downwind of St. Louis, Missouri, are investigated. This is achieved through the use of a cloud-resolving mesoscale model, in which sophisticated land use processes and aerosol microphysics are both incorporated. The results indicate that urban-forced convergence downwind of the city, rather than the presence of greater aerosol concentrations, determines whether storms actually develop in the downwind region. Once convection is initiated, urban-enhanced aerosols can exert a significant effect on the dynamics, microphysics, and precipitation produced by these storms. The model results indicate, however, that the response to urban-enhanced aerosol depends on the background concentrations of aerosols; a weaker response occurs with increasing background aerosol concentrations. The effects of aerosols influence the rate and amount of liquid water and ice produced within these storms, the accumulated surface precipitation, the strength and timing of the updrafts and downdrafts, the longevity of the updrafts, and the strength and influence of the cold pool. Complex, nonlinear relationships and feedbacks between the microphysics and storm dynamics exist, making it difficult to make definitive statements about the effects of urban-enhanced aerosols on downwind precipitation and convection. Because the impacts of urban aerosol on downwind storms decrease with increasing background aerosol concentrations, generalization of these results depends on the unique character of background aerosol for each urban area. For urban centers in coastal areas where background aerosol concentrations may be very low, it is speculated that urban aerosol can have very large influences on convective storm dynamics, microphysics, and precipitation.
Abstract
Variations in storm microstructure due to updraft strength, liquid water content, and the presence of dry layers, wind shear, and cloud nucleating aerosol concentrations are likely to lead to changes in hail sizes within deep convective storms. The focus of this paper is to determine how the overall dynamics and microphysical structure of deep convective storms are affected if hail sizes are somehow altered in a storm environment that is otherwise the same. The sensitivity of simulated supercell storms to hail size distributions is investigated by systematically varying the mean hail diameter from 3 mm to 1 cm using the Regional Atmospheric Modeling System (RAMS) model. Increasing the mean hail diameter results in a hail size distribution in which the number concentration of smaller hailstones is decreased, while that of the larger hailstones is increased. This shift in the hail size distribution as a result of increasing the mean hail diameter leads to an increase in the mean terminal fall speed of the hail species and to reduced melting and evaporation rates. The sensitivity simulations demonstrate that the low-level downdrafts are stronger, the cold pools are deeper and more intense, the left-moving updraft is shorter-lived, the right-moving storm is stronger but not as steady, and the low-level vertical vorticity is greater in the cases with smaller hail stones. The maximum hail mixing ratios are greater in the larger hail simulations, but they are located higher in the storm and farther away from the updraft core in the smaller hail runs. Changes in the hail size distribution also appear to influence the type of supercell that develops.
Abstract
Variations in storm microstructure due to updraft strength, liquid water content, and the presence of dry layers, wind shear, and cloud nucleating aerosol concentrations are likely to lead to changes in hail sizes within deep convective storms. The focus of this paper is to determine how the overall dynamics and microphysical structure of deep convective storms are affected if hail sizes are somehow altered in a storm environment that is otherwise the same. The sensitivity of simulated supercell storms to hail size distributions is investigated by systematically varying the mean hail diameter from 3 mm to 1 cm using the Regional Atmospheric Modeling System (RAMS) model. Increasing the mean hail diameter results in a hail size distribution in which the number concentration of smaller hailstones is decreased, while that of the larger hailstones is increased. This shift in the hail size distribution as a result of increasing the mean hail diameter leads to an increase in the mean terminal fall speed of the hail species and to reduced melting and evaporation rates. The sensitivity simulations demonstrate that the low-level downdrafts are stronger, the cold pools are deeper and more intense, the left-moving updraft is shorter-lived, the right-moving storm is stronger but not as steady, and the low-level vertical vorticity is greater in the cases with smaller hail stones. The maximum hail mixing ratios are greater in the larger hail simulations, but they are located higher in the storm and farther away from the updraft core in the smaller hail runs. Changes in the hail size distribution also appear to influence the type of supercell that develops.
