Cold Pool Strength Research Articles

The Impact on Simulated Bow Echoes of Changing Grid Spacing from 3 km to 1 km in the WRF Model

Abstract Ten bow echo events were simulated using the Weather Research and Forecasting (WRF) Model with 3- and 1-km horizontal grid spacing with both the Morrison and Thompson microphysics schemes to determine the impact of refined grid spacing on this often poorly simulated mode of convection. Simulated and observed composite reflectivities were used to classify convective mode. Skill scores were computed to quantify model performance at predicting all modes, and a new bow echo score was created to evaluate specifically the accuracy of bow echo forecasts. The full morphology score for runs using the Thompson scheme was noticeably improved by refined grid spacing, while the skill of Morrison runs did not change appreciably. However, bow echo scores for runs using both schemes improved when grid spacing was refined, with Thompson runs improving most significantly. Additionally, near storm environments were analyzed to understand why the simulated bow echoes changed as grid spacing was changed. A relationship existed between bow echo production and cold pool strength, as well as with the magnitude of microphysical cooling rates. More numerous updrafts were present in 1-km runs, leading to longer intense lines of convection which were more likely to evolve into longer-lived bow echoes in more cases. Large-scale features, such as a low-level jet orientation more perpendicular to the convective line and surface boundaries, often had to be present for bow echoes to occur in the 3-km runs.

Machine Learning Investigation of Downburst-Prone Environments in Canada

Abstract Thunderstorms are recognized as one of the most disastrous weather threats in Canada because of their power to cause substantial damage to human-made structures and even result in fatalities. It is therefore essential for operational forecasting to diagnose thunderstorms that generate damaging downdrafts of negatively buoyant air, known as downbursts. This study develops several machine learning models to identify environments supportive of downbursts in Canada. The models are trained and evaluated using 38 convective parameters calculated based on ERA5 reanalysis vertical profiles prior to thunderstorms with (306 cases) and without (19 132 cases) downbursts across Canada. Various resampling techniques are implemented to adjust data imbalance. An increase in the performance of the random forest (RF) model is observed when the support vector machine synthetic minority oversampling technique is utilized. The RF model outperforms other tested models, as indicated by model performance metrics and calibration. Several model interpretability methods highlight that the RF model has learned physical trends and patterns from the input variables. Moreover, the thermodynamic parameters are deemed to have higher impacts on the model outcomes compared to parcel, kinematic, and composite variables. For example, a considerable rise in the downburst probability is detected with an increase in cold pool strength. This study serves as one of the earliest attempts toward the fledgling field of machine learning applications in weather forecasting systems in Canada. The findings suggest that the developed model has the potential to enhance the effectiveness of issuing severe thunderstorm warnings in Canada, although further assessment with operational meteorologists is needed to validate its practical application. Significance Statement Severe thunderstorms demand particular attention in forecasting as their outflow can pose a serious threat to both structures and human life. This study uses machine learning techniques to predict whether or not a thunderstorm generates a damaging outflow in Canada. Atmospheric conditions that could trigger a severe thunderstorm are identified and discussed. Results show that the models have the potential to assist forecasters in better analyzing and predicting thunderstorms that generate destructive winds. Consequently, taking advantage of promising machine learning tools can yield more reliable forecasts of damaging thunderstorms, thereby mitigating the economic and societal burdens of these storms on Canadian communities.

An Evaluation of Non-Gaussian Data Assimilation Methods in Moist Convective Regimes

Abstract Obtaining a faithful probabilistic depiction of moist convection is complicated by unknown errors in subgrid-scale physical parameterization schemes, invalid assumptions made by data assimilation (DA) techniques, and high system dimensionality. As an initial step toward untangling sources of uncertainty in convective weather regimes, we evaluate a novel Bayesian data assimilation methodology based on particle filtering within a WRF ensemble analysis and forecasting system. Unlike most geophysical DA methods, the particle filter (PF) represents prior and posterior error distributions nonparametrically rather than assuming a Gaussian distribution and can accept any type of likelihood function. This approach is known to reduce bias introduced by Gaussian approximations in low-dimensional and idealized contexts. The form of PF used in this research adopts a dimension-reduction strategy, making it affordable for typical weather applications. The present study examines posterior ensemble members and forecasts for select severe weather events between 2019 and 2020, comparing results from the PF with those from an ensemble Kalman filter (EnKF). We find that assimilating with a PF produces posterior quantities for microphysical variables that are more consistent with model climatology than comparable quantities from an EnKF, which we attribute to a reduction in DA bias. These differences are significant enough to impact the dynamic evolution of convective systems via cold pool strength and propagation, with impacts to forecast verification scores depending on the particular microphysics scheme. Our findings have broad implications for future approaches to the selection of physical parameterization schemes and parameter estimation within preexisting data assimilation frameworks. Significance Statement The accurate prediction of severe storms using numerical weather models depends on effective parameterization schemes for small-scale processes and the assimilation of incomplete observational data in a manner that faithfully represents the probabilistic state of the atmosphere. Current generation methods for data assimilation typically assume a standard form for the error distributions of relevant quantities, which can introduce bias that not only hinders numerical prediction, but that can also confound the characterization of errors from the model itself. The current study performs data assimilation using a novel method that does not make such assumptions and explores characteristics of resulting model fields and forecasts that might make such a method useful for improving model parameterization schemes.

Simulations of Severe Convective Systems Using 1- versus 3-km Grid Spacing

Abstract Herein, 14 severe quasi-linear convective systems (QLCS) covering a wide range of geographical locations and environmental conditions are simulated for both 1- and 3-km horizontal grid resolutions, to further clarify their comparative capabilities in representing convective system features associated with severe weather production. Emphasis is placed on validating the simulated reflectivity structures, cold pool strength, mesoscale vortex characteristics, and surface wind strength. As to the overall reflectivity characteristics, the basic leading-line trailing stratiform structure was often better defined at 1 versus 3 km, but both resolutions were capable of producing bow echo and line echo wave pattern type features. Cold pool characteristics for both the 1- and 3-km simulations were also well replicated for the differing environments, with the 1-km cold pools slightly colder and often a bit larger. Both resolutions captured the larger mesoscale vortices, such as line-end or bookend vortices, but smaller, leading-line mesoscale updraft vortices, that often promote QLCS tornadogenesis, were largely absent in the 3-km simulations. Finally, while maximum surface winds were only marginally well predicted for both resolutions, the simulations were able to reasonably differentiate the relative contributions of the cold pool versus mesoscale vortices. The present results suggest that while many QLCS characteristics can be reasonably represented at a grid scale of 3 km, some of the more detailed structures, such as overall reflectivity characteristics and the smaller leading-line mesoscale vortices would likely benefit from the finer 1-km grid spacing. Significance Statement High-resolution model forecasts using 3-km grid spacing have proven to offer significant forecast guidance enhancements for severe convective weather. However, it is unclear whether additional enhancements can be obtained by decreasing grid spacings further to 1 km. Herein, we compare forecasts of severe quasi-linear convective systems (QLCS) simulated using 1- versus 3-km grids to document the potential value added of such increases in grid resolutions. It is shown that some significant improvements can be obtained in the representation of many QLCS features, especially as regards reflectivity structure and in the development of small, leading-line mesoscale vortices that can contribute to both severe surface wind and tornado production.

Convective environments leading to microburst, macroburst and downburst events across the United States

Downbursts are strong downdrafts of negatively buoyant air associated with convective storms and are capable of producing severe near-surface winds. Microbursts and macrobursts are subcategories of downbursts with the horizontal extent of damaging winds smaller or larger than 4 km, respectively. From January 2000 to June 2020, the Severe Weather Event Reports provided by the National Centers for Environmental Information (hereafter: Storm Events Database) contained 927 downburst, 914 microburst, and only 27 macroburst entries. We found a spatial variability of reported downbursts that is unlikely to be a result of natural processes, but rather artificially caused by the population density. An example of this bias is the abrupt decline in the number of reported events between southern and northern Arizona. Combining the Storm Events Database, ERA5 reanalysis and lightning data from the National Lightning Detection Network, we showed that cold pool strength, low-level lapse rates, WINDEX, lifted condensation level, DCAPE, WMAXSHEAR, derecho composite parameter, 2-m temperature, delta theta-e and mean low-level relative humidity demonstrate some value in downburst prediction. By combining the best predictor (cold pool strength) with the least correlated WMAXSHEAR, we created a downburst environment index (DEI) and used it to model climatological frequency of favorable downburst environments. Our analysis has shown that favorable downburst environments conditioned on lightning are the most frequent during summer over Southwest and Southeast with the most extreme environments across Great Plains. The vertical profiles of theta-e for the downburst events from reanalysis are further compared against nonsevere thunderstorms and rawinsonde data from four downburst field measurement campaigns. The results show that changes in theta-e over the lowest 200 hPa are the most important for downburst formation.

Evaluation and Modification of Microphysics Schemes on the Cold Pool Evolution for a Simulated Bow Echo in Southeast China

AbstractA merger‐formation bow echo (MFBE) in southeast China during the pre‐summer rainy season (PSRS) was simulated using three microphysics schemes including Thompson (THOM), Morrison (MORR), and Weather Research and Forecasting Double‐Moment 6‐Class (WDM6) schemes to compare against polarimetric observations and Variational Doppler Radar Analysis System (VDRAS) analyses. The three schemes captured the basic kinematic structures for this MFBE event after assimilating radar radial velocities, but all underpredicted the cold pool strength by ∼25%. Particularly, THOM produced the best raindrop size distributions (DSDs) and precipitation pattern compared with observed retrievals; further analyses indicated the larger raindrop size bias and the weak cold pool strength in THOM were owing to the relatively low rain breakup efficiency and inefficient rain evaporation, respectively. By decreasing the cutoff diameter of rain breakup parameterization from the default 1.6–1.2 mm (i.e., increasing breakup efficiency) and increasing evaporation efficiency by threefold in THOM, the simulated DSDs and precipitation were greatly improved, and the cold pool strength was significantly increased from 77% to 99% compared to that in VDRAS analyses. This study illustrated a plausible approach of combining polarimetric radar retrievals and VDRAS analyses as bases to adjust THOM default settings in simulating a MFBE event in southeast China with physical characteristics more consistent with observations. Since microphysical processes vary from convective organizations and climate regions, it is recognized more cases studies are needed in the future to examine the validity and approach in this study to improve simulations and predictions of MFBEs in southeast China.

Convective Cold Pools in Long-Term Boundary Layer Mast Observations

AbstractCold pools are mesoscale features that are key for understanding the organization of convection, but are insufficiently captured in conventional observations. This study conducts a statistical characterization of cold-pool passages observed at a 280-m-high boundary layer mast in Hamburg (Germany) and discusses factors controlling their signal strength. During 14 summer seasons 489 cold-pool events are identified from rapid temperature drops below −2 K associated with rainfall. The cold-pool activity exhibits distinct annual and diurnal cycles peaking in July and midafternoon, respectively. The median temperature perturbation is −3.3 K at 2-m height and weakens above. Also the increase in hydrostatic air pressure and specific humidity is largest near the surface. Extrapolation of the vertically weakening pressure signal suggests a characteristic cold-pool depth of about 750 m. Disturbances in the horizontal and vertical wind speed components document a lifting-induced circulation of air masses prior to the approaching cold-pool front. According to a correlation analysis, the near-surface temperature perturbation is more strongly controlled by the pre-event saturation deficit (r = −0.71) than by the event-accumulated rainfall amount (r = −0.35). Simulating the observed temperature drops as idealized wet-bulb processes suggests that evaporative cooling alone explains 64% of the variability in cold-pool strength. This number increases to 92% for cases that are not affected by advection of midtropospheric low-Θe air masses under convective downdrafts.

The Role of Cold Pools in Tropical Oceanic Convective Systems

Abstract The processes governing organized tropical convective systems are not completely understood despite their important influences on the tropical atmosphere and global circulation. In particular, cold pools are known to influence the structure and maintenance of midlatitude systems via Rotunno–Klemp–Weisman (RKW) theory, but cold pools may interact differently with tropical convection because of differences in cold pool strength and environmental shear. In this study, the role of cold pools in organized oceanic tropical convective systems is investigated, including their influence on system intensity, mesoscale structure, and propagation. To accomplish this goal, high-resolution idealized simulations are performed for two different systems that are embedded within a weakly sheared cloud population approaching radiative–convective equilibrium. The cold pools are altered by changing evaporation rates below cloud base in a series of sensitivity tests. The simulations demonstrate surprising findings: when cold pools are weakened, the convective systems become more intense. However, their propagation speeds and mesoscale structure are largely unaffected by the cold pool changes. Passive tracers introduced into the cold pools indicate that the convection intensifies when cold pools are weakened because cold pool air is entrained into updrafts, thereby reducing updraft intensity via the cold pools’ initial negative buoyancy. Gravity waves, rather than cold pools, appear to be the important modulators of system propagation and mesoscale structure. These results reconfirm that RKW theory does not fully explain the behavior of tropical oceanic convective systems, even those that otherwise appear consistent with RKW thinking.

Radiative effect of black carbon aerosol on a squall line case in North China

The radiative effect of black carbon aerosol (BC) on a squall line case in north China is studied with the Weather Research and Forecasting model. Before the initiation of the squall line, the surface-emitted BC is mixed only in the boundary layer (BL). BC is then transported from the BL into the free troposphere by the updrafts in the squall line system. Once distributed in the atmosphere, BC absorbs solar radiation and heats the surrounding air. The maximum increase of temperature is 0.05K for the moderately polluted case bc2 and 0.37K for the heavily polluted case bc20. In case bc2, where the BC concentration is not very high, the solar flux reaching the surface, the sensible heat flux, and the latent heat flux are not significantly affected by BC. In case bc20, the solar flux reaching the surface, the sensible heat flux, and the latent heat flux are reduced by up to 80, 30, and 21Wm−2, respectively. The reduced surface evaporation leads to a reduced vapor amount at the early stage. After some time, the heating effect causes a large-scale convergence and brings slightly more vapor into the domain. The effect of BC on the cold pool strength and low-level wind shear is small and hence does not significantly affect the triggering of new convections. In addition, our results show that the effect of BC is negligible on the strength and rain rate of the squall line case.

Impact of Variations in Upper-Level Shear on Simulated Supercells

It has previously been suggested, based on limited observations, that vertical wind shear in the upper troposphere is a key control on supercell morphology, with the low-precipitation, high-precipitation, and classic archetypes favored under strong, weak, and moderate shear, respectively. The idea is that, with increasing upper-level shear (ULS), hydrometeors are transported farther from the updraft by stronger storm-relative anvil-level winds, limiting their growth and thereby reducing precipitation intensity. The present study represents the first attempt to test this hypothesis, using idealized simulations of supercells performed across a range of 6–12-km shear profiles. Contrary to expectations, there is a significant increase in surface precipitation and an associated strengthening of outflow winds as ULS magnitude is increased from 0 to 20 m s−1. These changes result from an increase in storm motion, which drives stronger low-level inflow, a wider updraft, and enhanced condensation. A further increase in ULS magnitude to 30 m s−1 promotes a slight reduction in storm intensity associated with surging rear-flank outflow. However, this transition in behavior is found to be sensitive to other factors that influence cold-pool strength, such as mixed-layer depth and model microphysics. Variations in the vertical distribution and direction of ULS are also considered, but are found to have a much smaller impact on storm intensity than variations in ULS magnitude. Suggestions for the disparity between the current results and the aforementioned observations are offered and the need for further research on supercell morphology—in particular, simulations in drier environments—is emphasized.

Convectively Induced Stabilizations and Subsequent Recovery with Supercell Thunderstorms during the Mesoscale Predictability Experiment (MPEX)

Abstract The adiabatic and diabatic processes inherent to midlatitude deep convective storms are well known to modify the atmospheric temperature, moisture, and winds especially within horizontal scales equivalent to a Rossby radius of deformation. Such modifications, or “feedbacks,” induced by supercell thunderstorms were a particular focus of the Mesoscale Predictability Experiment (MPEX), owing to the unique supercell dynamics and associated supercell intensity and longevity. During the MPEX field phase, which was conducted 15 May–15 June 2013 within the Great Plains region of the United States, radiosonde observations collected in immediate supercell wakes exhibited temperature lapse rates that were qualitatively and quantitatively similar to preconvective lapse rates above the boundary layer. Complementary idealized model simulations were used to confirm that there was little residual effect of the supercell in the wake of the moving storm except within the area occupied by the surface cold pool, and where stabilizations were induced adiabatically by transient gravity wave disturbances. The persistency of the (i) cold pool, and its inhibition to surface-based convection, depended on the evolving cold pool strength and environmental winds; and (ii) gravity wave effects depended on the Doppler-shifted phase speed relative to the moving storm. Otherwise, recovery of the wake environment to its preconvective state occurred approximately over a time scale defined by the updraft length scale and horizontal advective velocity scale.

Effects of Urban Plume Aerosols on a Mesoscale Convective System

Abstract This study examines the effects of urban aerosols on a mesoscale convective system (MCS) in the central Great Plains with the Weather Research and Forecasting Model coupled with chemistry (WRF-Chem). Urban emissions from Kansas City, Missouri, were scaled by factors of 0.5, 1.0, and 2.0 to investigate the impact of urban aerosol load on MCS propagation and strength. The first half of the storm development is characterized by a stationary front to the north of Kansas City (phase I; 1800 UTC 26 May–0600 UTC 27 May), which develops into a squall line south of the urban area (phase II; 0600–1800 UTC 27 May). During phase I, doubling urban emissions shifts the precipitation accumulation, with enhancement downwind of the storm propagation and suppression upwind. During phase II, a squall line develops in the baseline and doubled emissions scenarios but not when emissions are halved. These changes in MCS propagation and strength are a function of cold pool strength, which is determined by microphysical processes and directly influenced by aerosol load. Overall, changes in urban emissions drive changes in cloud microphysics, which trigger large-scale changes in storm morphology and precipitation patterns. These results show that urban emissions can play an important role in mesoscale weather systems.

The relationship between latent heating, vertical velocity, and precipitation processes: The impact of aerosols on precipitation in organized deep convective systems.

A high-resolution, two-dimensional cloud-resolving model with spectral-bin microphysics is used to study the impact of aerosols on precipitation processes in both a tropical oceanic and a midlatitude continental squall line with regard to three processes: latent heating (LH), cold pool dynamics and ice microphysics. Evaporative cooling in the lower troposphere is found to enhance rainfall in low cloud condensation nuclei (CCN) concentration scenarios in the developing stages of a midlatitude convective precipitation system. In contrast, the tropical case produced more rainfall under high CCN concentrations. Both cold pools and low-level convergence are stronger for those configurations having enhanced rainfall. Nevertheless, latent heat release is stronger (especially after initial precipitation) in the scenarios having more rainfall in both the tropical and midlatitude environment. Sensitivity tests are performed to examine the impact of ice and evaporative cooling on the relationship between aerosols, LH and precipitation processes. The results show that evaporative cooling is important for cold pool strength and rain enhancement in both cases. However, ice microphysics play a larger role in the midlatitude case compared to the tropical. Detailed analysis of the vertical velocity governing equation shows that temperature buoyancy can enhance updrafts/downdrafts in the middle/lower troposphere in the convective core region; however, the vertical pressure gradient force (PGF) is the same order and acts in the opposite direction. Water loading is small but on the same order as the net PGF-temperature buoyancy forcing. The balance among these terms determines the intensity of convection.

Cold Pool and Precipitation Responses to Aerosol Loading: Modulation by Dry Layers

Abstract The relative sensitivity of midlatitude deep convective precipitation to aerosols and midlevel dry layers has been investigated in this study using high-resolution cloud-resolving model simulations. Nine simulations, including combinations of three moisture profiles and three aerosol number concentration profiles, were performed. Because of the veering wind profile of the initial sounding, the convection splits into a left-moving storm that is multicellular in nature and a right-moving storm, a supercell, which are analyzed separately. The results demonstrate that while changes to the moisture profile always induce larger changes in precipitation than do variations in aerosol concentrations, multicells are sensitive to aerosol perturbations whereas supercells are less so. The multicellular precipitation sensitivity arises through aerosol impacts on the cold pool forcing. It is shown that the altitude of the dry layer influences whether cold pools are stronger or weaker and hence whether precipitation increases or decreases with increasing aerosol concentrations. When the dry-layer altitude is located near cloud base, cloud droplet evaporation rates and hence latent cooling rates are greater with higher aerosol loading, which results in stronger low-level downdrafts and cold pools. However, when the dry-layer altitude is located higher above cloud base, the low-level downdrafts and cold pools are weaker with higher aerosol loading because of reduced raindrop evaporation rates. The changes to the cold pool strength initiate positive feedbacks that further modify the cold pool strength and subsequent precipitation totals. Aerosol impacts on deep convection are therefore found to be modulated by the altitude of the dry layer and to vary inversely with the storm organization.

A Study of the Role of Daytime Land–Atmosphere Interactions on Nocturnal Convective Activity in the Southern Great Plains during CLASIC

Abstract This study examines whether and how land–atmosphere interactions can have an impact on nocturnal convection over the southern Great Plains (SGP) through numerical simulations of an intense nocturnal mesoscale convective system (MCS) on 19–20 June 2007 with the Weather Research and Forecasting (WRF) Model. High-resolution nested simulations were conducted using realistic and idealized land surfaces and two planetary boundary layer (PBL) parameterizations (PBLp): Yonsei University (YSU) and Mellor–Yamada–Janjić (MYJ). Differences in timing and amount of MCS precipitation among observations and model results were examined in the light of daytime land–atmosphere interactions, nocturnal prestorm environment, and cold pool strength. At the meso-γ scale, land cover and soil type have as much of an effect on the simulated prestorm environment as the choice of PBLp: MYJ simulations exhibit strong sensitivity to changes in the land surface in contrast to negligible impact in the case of YSU. At the end of the afternoon, as the boundary layer collapses, a more homogeneous and deeper PBL (and stronger low-level shear) is evident for YSU as compared to MYJ when initial conditions and land surface properties are the same. At the meso-β scale, propagation speed is faster and organization (bow echo morphology) and cold pool strength are enhanced when nocturnal PBL heights are higher, and there is stronger low-level shear in the prestorm environment independent of the boundary layer parameterization for different land surface conditions. A comparison of one- and two-way nested MYJ results demonstrates how daytime land–atmosphere interactions modify the prestorm environment remotely through advection of low-level thermodynamic features. This remote feedback strongly impacts the MCS development phase as well as its spatial organization and propagation velocity and, consequently, nocturnal rainfall. These results indicate that synoptic- and meso-α-scale dynamics can play an important role in determining the spatial and temporal scales over which precipitation feedbacks of land–atmosphere interactions emerge regionally. Finally, this study demonstrates the high degree of uncertainty in defining the spatial and temporal scales of land–atmosphere interactions where and when organized convection is dominant.

A Squall-Line-Like Principal Rainband in Typhoon Hagupit (2008) Observed by Airborne Doppler Radar

Abstract This study examines the structure and dynamics of Typhoon Hagupit’s (2008) principal rainband using airborne radar and dropsonde observations. The convection in Hagupit’s principal rainband was organized into a well-defined line with trailing stratiform precipitation on the inner side. Individual convective cells had intense updrafts and downdrafts and were aligned in a wavelike pattern along the line. The line-averaged vertical cross section possessed a slightly inward-tilting convective core and two branches of low-level inflow feeding the convection. The result of a thermodynamic retrieval showed a pronounced cold pool behind the convective line. The horizontal and vertical structures of this principal rainband show characteristics that are different than the existing conceptual model and are more similar to squall lines and outer rainbands. The unique convective structure of Hagupit’s principal rainband was associated with veering low-level vertical wind shear and large convective instability in the environment. A quantitative assessment of the cold pool strength showed that it was quasi balanced with that of the low-level vertical wind shear. The balanced state and the structural characteristics of convection in Hagupit’s principal rainband were dynamically consistent with the theory of cold pool dynamics widely applied to strong and long-lived squall lines. The analyses suggest that cold pool dynamics played a role in determining the principal rainband structure in addition to storm-scale vortex dynamics.

Examination of CCN impacts on hail in a simulated supercell storm with triple-moment hail bulk microphysics

Aerosols that act as cloud condensation nuclei (CCN) play a crucial role in the formation of cloud particles and recent research suggests that CCN can influence ice processes within deep convection as well. In this study, a triple-moment bulk hail microphysics scheme is used to investigate the impact of changing CCN concentrations on hail for a well-observed supercell storm that occurred over northwest Kansas on 29 June 2000 during the Severe Thunderstorm and Electrification and Precipitation Study (STEPS). For the simulated supercells in the particular environment examined, an increase in potential CCN concentrations from 100 to 3000cm−3 leads to increasing numbers and decreasing sizes of cloud droplets, as expected, yet the overall storm dynamics and evolution are largely unaffected. Increases in potential CCN concentrations lead to non-monotonic responses in the bulk characteristics of nearly all hydrometeor fields, surface precipitation, and cold-pool strength. However, higher concentrations of CCN also result in larger hail sizes and greater amounts of large diameter (≥2cm) hail. The results suggest that a combination of increased sizes and localized reductions in numbers of hail embryos near favorable growth regions with increasing potential CCN concentrations tend to promote conditions that lead to increased hail sizes and amounts of large hail.

Are simulated aerosol-induced effects on deep convective clouds strongly dependent on saturation adjustment?

Abstract. Three configurations of a bulk microphysics scheme in conjunction with a detailed bin scheme are implemented in the Weather Research and Forecasting (WRF) model to specifically address the role of the saturation adjustment assumption (i.e., condensing/evaporating the surplus/deficit water vapor relative to saturation in one time step) on aerosol-induced invigoration of deep convective clouds. The bulk model configurations are designed to treat cloud droplet condensation/evaporation using either saturation adjustment, as employed in most bulk models, or an explicit representation of supersaturation over a time step, as used in bin models. Results demonstrate that the use of saturation adjustment artificially enhances condensation and latent heating at low levels and limits the potential for an increase in aerosol concentration to increase buoyancy at mid to upper levels. This leads to a small weakening of the time- and domain-averaged convective mass flux (~-3%) in polluted compared to clean conditions. In contrast, the bin model and bulk scheme with explicit prediction of supersaturation simulate an increase in latent heating aloft and the convective updraft mass flux is weakly invigorated (~5%). The bin model also produces a large increase in domain-mean cumulative surface precipitation in polluted conditions (~18%), while all of the bulk model configurations simulate little change in precipitation. Finally, it is shown that the cold pool weakens substantially with increased aerosol loading when saturation adjustment is applied, which acts to reduce the low-level convergence and weaken the convective dynamics. With an explicit treatment of supersaturation in the bulk and bin models there is little change in cold pool strength, so that the convective response to polluted conditions is influenced more by changes in latent heating aloft. It is concluded that the use of saturation adjustment can explain differences in the response of cold pool evolution and convective dynamics with aerosol loading simulated by the bulk and bin models, but cannot explain large differences in the response of surface precipitation between these models.

On the robustness of aerosol effects on an idealized supercell storm simulated with a cloud system-resolving model

Abstract. A cloud system-resolving model (the Weather Research and Forecasting model) with 1 km horizontal grid spacing is used to investigate the response of an idealized supercell storm to increased cloud droplet concentrations associated with polluted conditions. The primary focus is on exploring robustness of simulated aerosol effects in the face of complex process interactions and feedbacks between the cloud microphysics and dynamics. Simulations are run using sixteen different model configurations with various microphysical or thermodynamic processes modified or turned off. Robustness of the storm response to polluted conditions is also explored for each configuration by performing additional simulations with small perturbations to the initial conditions. Differences in the domain-mean accumulated surface precipitation and convective mass flux between polluted and pristine conditions are small for almost all model configurations, with relative differences in each quantity generally less than 15%. Configurations that produce a decrease (increase) in cold pool strength in polluted conditions also tend to simulate a decrease (increase) in surface precipitation and convective mass flux. Combined with an analysis of the dynamical and thermodynamic fields, these results indicate the importance of interactions between microphysics, cold pool evolution, and dynamics along outflow boundaries in explaining the system response. Several model configurations, including the baseline, produce an overall similar storm response (weakening) in polluted conditions despite having different microphysical or thermodynamic processes turned off. With hail initiation turned off or the hail fallspeed-size relation set to that of snow, the model produces an invigoration instead of weakening of the storm in polluted conditions. These results highlight the difficulty of foreseeing impacts of changes to model parameterizations and isolating process interactions that drive the system response to aerosols. Overall, these findings are robust, in a qualitative sense, to small perturbations in the initial conditions. However, there is sensitivity in the magnitude, and in some cases sign, of the storm response to polluted conditions with small perturbations in the temperature of the thermal used to initiate convection (less than ±0.5 K) or the vertical shear of the environmental wind (±5%). It is concluded that reducing uncertainty in simulations of aerosol effects on individual deep convective storms will likely require ensemble methods in addition to continued improvement of model parameterizations.

Sensitivity of a Simulated Midlatitude Squall Line to Parameterization of Raindrop Breakup

Abstract This paper describes idealized simulations of a squall line observed on 20 June 2007, in central Oklahoma. Results are compared with measurements from dual-polarization radar and surface disdrometer. The baseline model configuration qualitatively reproduces key storm features, but underpredicts precipitation rates and generally overpredicts median volume raindrop diameter. The sensitivity of model simulations to parameterization of raindrop breakup is tested under different low-level (0–2.5 km) environmental vertical wind shears. Storm characteristics exhibit considerable sensitivity to the parameterization of breakup, especially for moderate (0.0048 s−1) shear. Simulations with more efficient breakup tend to have higher domain-mean precipitation rates under both moderate and higher (0.0064 s−1) shear, despite the smaller mean drop size and hence lower mass-weighted fall speed and higher evaporation rate for a given rainwater content. In these runs, higher evaporation leads to stronger cold pools, faster propagation, larger storm size, greater updraft mass flux (but weaker convective updrafts at mid- and upper levels), and greater total condensation that compensates for the increased evaporation to give more surface precipitation. The impact of drop breakup on mass-weighted fall speed is also important and leads to a nonmonotonic response of storm characteristics (surface precipitation, cold pool strength, etc.) to changes in breakup efficiency under moderate wind shear. In contrast, the response is generally monotonic at higher wind shear. Interactions between drop breakup, convective dynamics, cold pool intensity, and low-level environmental wind shear are also described in the context of “Rotunno–Klemp–Weisman (RKW) theory,” which addresses how density currents evolve in sheared environments.