Simulated Mesoscale Convective System Research Articles

Ensemble Spread Grows More Rapidly in Higher-Resolution Simulations of Deep Convection

Idealized ensemble simulations of mesoscale convective systems (MCSs) with horizontal grid spacings of 1, 1.4, and 2 km are used to analyze the influence of numerical resolution on the rate of growth of ensemble spread in convection-resolving numerical models. The ensembles are initialized with random phases of 91-km-wavelength moisture perturbations that are captured with essentially identical accuracy at all resolutions. The rate of growth of ensemble variance is shown to systematically increase at higher resolution. The largest horizontal wavelength at which the perturbation kinetic energy (KE′) grows to at least 50% of the background kinetic energy spectrum is also shown to grow more rapidly at higher resolution. The mechanism by which the presence of smaller scales accelerates the upscale growth of KE′ is clear-cut in the smooth-saturation Lorenz–Rotunno–Snyder (ssLRS) model of homogeneous surface quasigeostrophic turbulence. Comparing the growth of KE′ from the MCS ensemble simulations to that in the ssLRS model suggests interactions between perturbations at small scales, where KE′ is not yet completely saturated, and somewhat larger scales, where KE′ is clearly unsaturated, are responsible for the faster growth rate of ensemble variance at finer resolution. These results provide some empirical justification for the use of deep-convection-related stochastic parameterization schemes to reduce the problem of underdispersion in coarser-resolution ensemble prediction systems.

Convective-Permitting Hindcast Simulations during the North American Monsoon GPS Transect Experiment 2013: Establishing Baseline Model Performance without Data Assimilation

AbstractDuring the North American monsoon global positioning system (GPS) Transect Experiment 2013, daily convective-permitting WRF simulations are performed in northwestern Mexico and the southern Arizona border region using the operational Global Forecast System (GFS) and North American Mesoscale Forecast System (NAM) models as lateral boundary forcing and initial conditions. Compared to GPS precipitable water vapor (PWV), the WRF simulations display a consistent moist bias in the initial specification of PWV leading to convection beginning 3–6 h early. Given appreciable observed rainfall, days are classified as strongly and weakly forced based only on the presence of an inverted trough (IV); gulf surges did not noticeably impact the development of mesoscale convective systems (MCSs) and related convection in northwestern Mexico. Strongly forced days display higher modeled precipitation forecast skill than weakly forced days in the slopes of the northern Sierra Madre Occidental (SMO) away from the crest, especially toward the west where MCSs account for the greatest proportion of all monsoon-related precipitation. A case study spanning 8–10 July 2013 illustrates two consecutive days when nearly identical MCSs evolved over northern Sonora. Although a salient MCS is simulated on the strongly forced day (9–10 July 2013) when an IV is approaching the core monsoon region, a simulated MCS is basically nonexistent on the weakly forced day (8–9 July 2013) when the IV is farther away. The greater sensitivity to the initial specification of PWV in the weakly forced day suggests that assimilation of GPS-derived PWV for these types of days may be of greatest value in improving model precipitation forecasts.

Structure and Evolution of Mesoscale Convective Systems: Sensitivity to Cloud Microphysics in Convection‐Permitting Simulations Over the United States

AbstractRegional climate simulations over the continental United States were conducted for the 2011 warm season using the Weather Research and Forecasting model at convection‐permitting resolution (4 km) with two commonly used microphysics parameterizations (Thompson and Morrison). Sensitivities of the simulated mesoscale convective system (MCS) properties and feedbacks to large‐scale environments are systematically examined against high‐resolution geostationary satellite and 3‐D mosaic radar observations. MCS precipitation including precipitation amount, diurnal cycle, and distribution of hourly precipitation intensity are reasonably captured by the two simulations despite significant differences in their simulated MCS properties. In general, the Thompson simulation produces better agreement with observations for MCS upper level cloud shield and precipitation area, convective feature horizontal and vertical extents, and partitioning between convective and stratiform precipitation. More importantly, Thompson simulates more stratiform rainfall, which agrees better with observations and results in top‐heavier heating profiles from robust MCSs compared to Morrison. A stronger dynamical feedback to the large‐scale environment is therefore seen in Thompson, wherein an enhanced mesoscale vortex behind the MCS strengthens the synoptic‐scale trough and promotes advection of cool and dry air into the rear of the MCS region. The latter prolongs the MCS lifetimes in the Thompson relative to the Morrison simulations. Hence, different treatment of cloud microphysics not only alters MCS convective‐scale dynamics but also has significant impacts on their macrophysical properties such as lifetime and precipitation. As long‐lived MCSs produced 2–3 times the amount of rainfall compared to short‐lived ones, cloud microphysics parameterizations have profound impact in simulating extreme precipitation and the hydrologic cycle.

Evaluation of mineral dust aerosol optical depth and related components from the CHIMERE-DUST model using satellite remote sensing and ground-based observations

Dust aerosol optical depth (AOD) simulated by the CHIMERE-DUST model over North Africa during 2006–2008 was evaluated by the SeaWiFS Deep Blue satellite data and AERONET ground based remote sensing measurements. The simulations were conducted using two meteorological inputs, ECMWF and CFSR forecast data, downscaled by the WRF model. The two simulations generated similar AODs and PM10 surface concentrations, which are highly correlated to dust emissions. The comparison of the simulated daily value of AOD with the satellite data showed good correlations (0.6–0.8) between them. A slightly better correlation was achieved using WRF-CFSR data. The regression coefficients fluctuated around 1.0 in cold months and decreased in summer, with minimums in August. The biases had similar seasonal cycles. This is consistent with the comparison against AERONET hourly AOD data that the model underestimated AODs in warm months at most stations. The comparison of PM10 surface concentration and dry deposition also showed negative biases in warm months at stations in the Sahel. The significant underestimation of wet deposition was found in monsoon season due to the unrealistic simulation of mesoscale convective system. It indicates that the low dust emission in August is partly associated with cold pools generated by the convective precipitation. Frequent overestimations of AOD were found in the northwest mostly because of the high dust emission produced by the overestimated winds near the Atlas Mountains. The dust emissions resulted from the two simulations were similar in terms of intra annual variations but differed in terms of annul dust emission. The estimated annual emission using WRF-CFSR data could be about 200 Tg more than the estimation using WRF-ECMWF data.

Impact of Assimilation of Conventional and Satellite Radiance GTS Observations on Simulation of Mesoscale Convective System Over Southeast India Using WRF-3DVar

The primary goal of present study is to investigate the impact of assimilation of conventional and satellite radiance observations in simulating the mesoscale convective system (MCS) formed over south east India. An assimilation methodology based on Weather Research and Forecasting model three dimensional variational data assimilation is considered. Few numerical experiments are carried out to examine the individual and combined impact of conventional and non-conventional (satellite radiance) observations. After the successful inclusion of additional observations, strong analysis increments of temperature and moisture fields are noticed and contributed to significant improvement in model’s initial fields. The resulting model simulations are able to successfully reproduce the prominent synoptic features responsible for the initiation of MCS. Among all the experiments, the final experiment in which both conventional and satellite radiance observations assimilated has showed considerable impact on the prediction of MCS. The location, genesis, intensity, propagation and development of rain bands associated with the MCS are simulated reasonably well. The biases of simulated temperature, moisture and wind fields at surface and different pressure levels are reduced. Thermodynamic, dynamic and vertical structure of convective cells associated with the passage of MCS are well captured. Spatial distribution of rainfall is fairly reproduced and comparable to TRMM observations. It is demonstrated that incorporation of conventional and satellite radiance observations improved the local and synoptic representation of temperature, moisture fields from surface to different levels of atmosphere. This study highlights the importance of assimilation of conventional and satellite radiances in improving the models initial conditions and simulation of MCS.

The response of a simulated mesoscale convective system to increased aerosol pollution: Part I: Precipitation intensity, distribution, and efficiency

Mesoscale Convective Systems (MCSs) are important contributors to rainfall in the High Plains of the United States and elsewhere in the world. It is therefore of interest to understand how different aerosols serving as cloud condensation nuclei (CCN) may impact the total amount, rates and spatial distribution of precipitation produced by MCSs. In this study, different aerosol concentrations and their effects on precipitation produced by an MCS are examined by simulating the 8 May 2009 “Super-Derecho” MCS using the Regional Atmospheric Modeling System (RAMS), a cloud-resolving model (CRM) with sophisticated aerosol and microphysical parameterizations. Three simulations were conducted that differed only in the initial concentration, spatial distribution, and chemical composition of aerosols. Aerosol fields were derived from the output of GEOS-Chem, a 3D chemical transport numerical model. Results from the RAMS simulations show that the total domain precipitation was not significantly affected by variations in aerosol concentrations, however, the pollution aerosols altered the precipitation characteristics. The more polluted simulations exhibited higher precipitation rates, higher bulk precipitation efficiency, a larger area with heavier precipitation, and a smaller area with lighter precipitation. These differences arose as a result of aerosols enhancing precipitation in the convective region of the MCS while suppressing precipitation from the MCS's stratiform-anvil. In the convective region, several processes likely contributed to an increase of precipitation. First, owing to the very humid environment of this storm, the enhanced amount of cloud water available to be collected overwhelmed the reduction in precipitation efficiency associated with the aerosol-induced production of smaller droplets which led to a net increase in the conversion of cloud droplets to precipitation. Second, higher aerosol concentrations led to invigoration of convective updrafts which enhanced precipitation in accordance to the convective invigoration hypothesis. The reduction in stratiform precipitation in the more polluted simulations was found to be attributed to the presence of greater aerosol number concentrations that reduced both collision-coalescence and riming. Analysis of back trajeocty flow showed that the air feeding the stratiform-anvil originated within the free troposphere, by mesoscale ascent. Therefore, increased aerosol pollution at higher elevations impacted the stratiform precipitation formation within the simulated MCS. As a consequence, the more polluted simulations produced the smallest precipitation from the MCS stratiform-anvil region. In Part II the impact of aerosols on the severe winds produced by this storm is examined.

On the Dependence of Squall-Line Characteristics on Surface Conditions

Abstract The influence of surface conditions in the form of changing surface temperatures on fully developed mesoscale convective systems (MCSs) is investigated using a cloud-system-resolving setup of the Icosahedral Nonhydrostatic (ICON) model (1-km grid spacing). The simulated MCSs take the form of squall lines with trailing stratiform precipitation. After the squall lines have reached a quasi-steady state, secondary convection is triggered ahead of the squall line, resulting in an increase of squall-line propagation speed, also known as discrete propagation. The higher propagation speed is then maintained for the remainder of the simulations because secondary convection ahead of the squall line acts to reduce the environmental wind shear over the depth of the squall line’s cold pool. The surface conditions have only a marginal effect on the squall lines themselves. This is so because the surface fluxes cannot significantly affect the cold pool, which is continuously replenished by midtropospheric air. The midtroposphere remains similar given the use of identical initial profiles. The only effect of the surface fluxes consists in an earlier acceleration of the squall line due to earlier initiation of secondary convection with higher surface temperature. Finally, a conceptual model to estimate the change in surface temperature needed to achieve a change in onset time of prefrontal secondary convection and the associated discrete propagation events given the environmental conditions is presented.

Potential deformation and its application to the diagnosis of heavy precipitation in mesoscale convective systems

Many observational studies have shown that deformation, like vertical vorticity and divergence, is closely related to the occurrence and distribution of strong precipitation. In this paper, to involve deformation in precipitation diagnosis, a new parameter called potential deformation (PD) is derived and then applied to precipitation detection within a simulated mesoscale convective system (MCS). It is shown that PD includes both stretching deformation and shearing deformation and shares similar characteristics with deformation insofar as it does not change with the rotating coordinate. Diagnosis of the simulated MCS reveals that PD performs well in tracing the MCS’ precipitation. In terms of their distributional pattern, the large-value areas of PD are similar to the precipitation in the different development stages of the MCS. A detailed analysis of the physical processes contained within the PD shows that it can reflect the three-dimensional moisture variation, vertical wind shear and wind deformation within the MCS. These structures are usually a comprehensive reflection of the characteristics of the surface cold pool, rear inflow jet, downward cold air flow and upward warm moist flow within the precipitating convective cells. For this reason, the PD shows much stronger anomalies in the precipitating atmosphere than the non-precipitating atmosphere, which implies considerable potential for its application in detecting heavy precipitation within MCSs.

The response of a simulated mesoscale convective system to increased aerosol pollution: Part II: Derecho characteristics and intensity in response to increased pollution

Mesoscale Convective Systems (MCS) are important contributors to rainfall as well as producers of severe weather such as hail, tornados, and straight-line wind events known as derechos. In this study, different aerosol concentrations and their effects on a derecho event are examined by simulating a case study, the 8 May 2009 “Super-Derecho”, using the Regional Atmospheric Modeling System (RAMS), a cloud-resolving model with sophisticated aerosol and cloud microphysics. Three simulations were conducted that differed in the initial aerosol concentrations, spatial distribution and chemical composition as derived from output of GEOS-Chem, a 3D chemical transport model. In order to understand the impact of changes in aerosol concentrations on the derecho characteristics, the dynamical processes that produced the strong surface wind were determined by performing back-trajectory analysis during two periods of the simulated storm: the development and the onset of dissipation. A time dependent and non-monotonic trend was found between the intensity of the derecho and the increased aerosol concentrations that served as cloud condensation nuclei. During the formation period of the MCS, the non-monotonic trend was attributed to the microphysical impact of aerosol loading on the intensity of the cold pool; that is, the impact of aerosols on both the melting and evaporation rates of hydrometeors. The subsequent intensity changes within the cold pool modified the balance between the horizontal vorticity generated by the cold pool and that of the environment, thereby impacting the orientation of the convective updraft at the leading line. This, in turn, altered the primary flow that contributed to the formation of the derecho-strength surface winds. The simulation with no anthropogenic aerosols exhibited the strongest cold pool and the primary flow was associated with a descending rear inflow jet that produced the derecho winds over a larger region. The simulation with the highest amount of anthropogenic aerosols featured a stronger mesovortex and the derecho winds were primarily due to stronger convective downbursts. As the simulated storm matured, the changes in the derecho winds were found to be associated with the strength of the mesovortex at the gust front. During the period when the simulated storm began to dissipate, the non-monotonic trend in derecho intensity was associated with a non-monotonic response in mesovortex strength to increased aerosol concentrations. A moderate increase in aerosol concentrations led to the formation of a weaker mesovortex while a greater increase in aerosol concentration led to the formation of a stronger mesovortex. The formation of a stronger mesovortex was found to increase the contribution of the derecho winds following a convective downburst associated with an “up-down” downdraft trajectory.

The impact of simulated mesoscale convective systems on global precipitation: A multiscale modeling study.

The importance of precipitating mesoscale convective systems (MCSs) has been quantified from TRMM precipitation radar and microwave imager retrievals. MCSs generate more than 50% of the rainfall in most tropical regions. MCSs usually have horizontal scales of a few hundred kilometers (km); therefore, a large domain with several hundred km is required for realistic simulations of MCSs in cloud-resolving models (CRMs). Almost all traditional global and climate models do not have adequate parameterizations to represent MCSs. Typical multiscale modeling frameworks (MMFs) may also lack the resolution (4 km grid spacing) and domain size (128 km) to realistically simulate MCSs. The impact of MCSs on precipitation is examined by conducting model simulations using the Goddard Cumulus Ensemble (GCE, a CRM) model and Goddard MMF that uses the GCEs as its embedded CRMs. Both models can realistically simulate MCSs with more grid points (i.e., 128 and 256) and higher resolutions (1 or 2 km) compared to those simulations with fewer grid points (i.e., 32 and 64) and low resolution (4 km). The modeling results also show the strengths of the Hadley circulations, mean zonal and regional vertical velocities, surface evaporation, and amount of surface rainfall are weaker or reduced in the Goddard MMF when using more CRM grid points and higher CRM resolution. In addition, the results indicate that large-scale surface evaporation and wind feedback are key processes for determining the surface rainfall amount in the GMMF. A sensitivity test with reduced sea surface temperatures shows both reduced surface rainfall and evaporation.

Idealized numerical simulations of Mesoscale Convective Systems and their implications for forecast error

Deep convective mass transfer in a rotating, stratified fluid is capable of generating characteristic potential vorticity features and, if of sufficient spatial scale, these may affect baroclinic wave development and hence weather predictability. In current global numerical prediction models, it is still necessary to include convection parametrization even though these algorithms are ill‐suited to representing singular, mesoscale convective events. Some stochastic representations of the non‐equilibrium convective process in ensemble prediction systems perturb the vertical component of vorticity in order to crudely represent the upscale impact of deep convection (i.e. kinetic energy backscatter schemes). These use ad hoc assumptions about the structure of random wind errors associated with convection. The idealized, explicit convection simulations described here form the basis of a study of these convectively generated vorticity perturbations, and their implications for stochastic convective forcing in ensemble prediction systems is considered. Cases with no initial flow and constant shear are examined with emphasis on the impact on vertical vorticity within the mesoscale cloud shield. The results are interpreted in the wider context of operational forecast error in the simulated infrared radiance for cases of intense convective activity over the North American Great Plains. A Met Office Unified Model forecast made with 2.2 km horizontal resolution during the Hazardous Weather Testbed project provides additional support for the idealized model findings. The Stochastic Convective Backscatter scheme proposed by the author is integrated forward in time using the simulated convective mass transport as a driver for the random forcing term. In its ensemble forecast model implementation, this term uses parametrized convective mass fluxes. The results suggest a retuning of the scheme's filter scales in order to obtain a representation of model wind error more consistent with the simulations.

Impact of different parameterization schemes on simulation of mesoscale convective system over south-east India

Main objective of the present paper is to examine the role of various parameterization schemes in simulating the evolution of mesoscale convective system (MCS) occurred over south-east India. Using the Weather Research and Forecasting (WRF) model, numerical experiments are conducted by considering various planetary boundary layer, microphysics, and cumulus parameterization schemes. Performances of different schemes are evaluated by examining boundary layer, reflectivity, and precipitation features of MCS using ground-based and satellite observations. Among various physical parameterization schemes, Mellor–Yamada–Janjic (MYJ) boundary layer scheme is able to produce deep boundary layer height by simulating warm temperatures necessary for storm initiation; Thompson (THM) microphysics scheme is capable to simulate the reflectivity by reasonable distribution of different hydrometeors during various stages of system; Betts–Miller–Janjic (BMJ) cumulus scheme is able to capture the precipitation by proper representation of convective instability associated with MCS. Present analysis suggests that MYJ, a local turbulent kinetic energy boundary layer scheme, which accounts strong vertical mixing; THM, a six-class hybrid moment microphysics scheme, which considers number concentration along with mixing ratio of rain hydrometeors; and BMJ, a closure cumulus scheme, which adjusts thermodynamic profiles based on climatological profiles might have contributed for better performance of respective model simulations. Numerical simulation carried out using the above combination of schemes is able to capture storm initiation, propagation, surface variations, thermodynamic structure, and precipitation features reasonably well. This study clearly demonstrates that the simulation of MCS characteristics is highly sensitive to the choice of parameterization schemes.

The microphysical contributions to and evolution of latent heating profiles in two MC3E MCSs

AbstractThe shapes and magnitudes of latent heating profiles have been shown to be different within the convective and stratiform regions of mesoscale convective systems (MCSs). Properly representing these distinctions has significant implications for the atmospheric responses to latent heating on various scales. This study details (1) the microphysical process contributions to latent heating profiles within MCS convective, stratiform, and anvil regions and (2) the time evolution of these profiles throughout the MCS lifetime, using cloud‐resolving model simulations. Simulations of two MCS events that occurred during the Midlatitude Continental Convective Clouds Experiment (MC3E) are conducted. Several features of the simulated MCSs are compared to a suite of observations obtained during the MC3E field campaign, and it is concluded that the simulations reasonably reproduce the MCS events. The simulations show that condensation and deposition are the primary contributors to MCS latent warming, as compared to riming and nucleation processes. In terms of MCS latent cooling, sublimation, melting, and evaporation all play significant roles. It is evident that throughout the MCS lifecycle, convective regions demonstrate an approximately linear decrease in the magnitudes of latent heating rates, while latent heating within stratiform regions is associated with transitions between MCS flow regimes. Such information regarding the temporal evolution of latent heating within convective and stratiform MCS regions could be useful in developing parameterizations representing convective organization.

Dynamics Governing a Simulated Mesoscale Convective System with a Training Convective Line

Abstract This research investigates the dynamics of a simulated training line/adjoining stratiform (TL/AS) mesoscale convective system (MCS), with composite atmospheric fields used as initial and lateral boundary conditions for the simulation. An initial forward-propagating MCS developed within a region of elevated convective instability and low-level lifting associated with warm-air advection along the terminus of the low-level jet. The environmental conditions external to the MCS continued to provide lift, moisture, and instability to the western side of the forward-propagating MCS, and these conditions were initially responsible for backbuilding on the system’s western side. Most parcels that encountered the southwestern outflow boundary were lifted insufficiently far to reach their levels of free convection (LFCs), and their LFC heights were increased by latent heating above them. These parcels continued northeastward beyond the surface outflow boundary (OFB), were gradually lifted, and initiated convection 80–100 km beyond encountering the OFB. Eventually the surface cold pool became sufficiently deep so that gradual ascent of parcels with moisture and instability over the OFB began initiating new convection close to the OFB—this drove backbuilding during the later portion of the MCS lifetime. These results disentangle the relative contributions of large-scale environmental factors and storm-scale processes on the quasi-stationary behavior of the MCS and show that both contributed to upstream backbulding at different times during the MCS life cycle.

Sensitivity of summer ensembles of fledgling superparameterized U.S. mesoscale convective systems to cloud resolving model microphysics and grid configuration

AbstractThe sensitivities of simulated mesoscale convective systems (MCSs) in the central U.S. to microphysics and grid configuration are evaluated here in a global climate model (GCM) that also permits global‐scale feedbacks and variability. Since conventional GCMs do not simulate MCSs, studying their sensitivities in a global framework useful for climate change simulations has not previously been possible. To date, MCS sensitivity experiments have relied on controlled cloud resolving model (CRM) studies with limited domains, which avoid internal variability and neglect feedbacks between local convection and larger‐scale dynamics. However, recent work with superparameterized (SP) GCMs has shown that eastward propagating MCS‐like events are captured when embedded CRMs replace convective parameterizations. This study uses a SP version of the Community Atmosphere Model version 5 (SP‐CAM5) to evaluate MCS sensitivities, applying an objective empirical orthogonal function algorithm to identify MCS‐like events, and harmonizing composite storms to account for seasonal and spatial heterogeneity. A five‐summer control simulation is used to assess the magnitude of internal and interannual variability relative to 10 sensitivity experiments with varied CRM parameters, including ice fall speed, one‐moment and two‐moment microphysics, and grid spacing. MCS sensitivities were found to be subtle with respect to internal variability, and indicate that ensembles of over 100 storms may be necessary to detect robust differences in SP‐GCMs. These results emphasize that the properties of MCSs can vary widely across individual events, and improving their representation in global simulations with significant internal variability may require comparison to long (multidecadal) time series of observed events rather than single season field campaigns.

The Mesoscale Heavy Rainfall Observing System (MHROS) over the middle region of the Yangtze River in China

AbstractThe Mesoscale Heavy Rainfall Observing System (MHROS), supported by the Institute of Heavy Rain (IHR), Chinese Meteorology Administration, is one of the major systems to observe mesoscale convective systems (MCSs) over the middle region of the Yangtze River in China. The IHR MHROS consists of mobile C‐POL and X‐POL precipitation radars, millimeter wavelength cloud radar, fixed S‐band precipitation radars, GPS network, microwave radiometers, radio soundings, wind profiler radars, and disdrometers. The atmospheric variables observed or retrieved by these instruments include the profiles of atmospheric temperature, moisture, wind speed and direction, vertical structures of MCS clouds and precipitation, atmospheric water vapor, and cloud liquid water. These quality‐controlled observations and retrievals have been used in mesoscale numerical weather prediction to improve the accuracy of weather forecasting and MCS research since 2007. These long‐term observations have provided the most comprehensive data sets for researchers to investigate the formation‐dissipation processes of MCSs and for modelers to improve their simulations of MCSs. As the first paper of a series, we briefly introduce the IHR MHROS and describe the specifications of its major instruments. Then, we provide an integrative analysis of the IHR MHROS observations for a heavy rain case on 3–5 July 2014 as well as the application of IHR MHROS observations in improving the model simulations. In a series of papers, we will tentatively answer several key scientific questions related to the MCS and Meiyu frontal systems over the middle region of the Yangtze River using the IHR MHROS observations.

Properties of a Mesoscale Convective System in the Context of an Isentropic Analysis

Abstract Application of an isentropic analysis of convective motions to a simulated mesoscale convective system is presented. The approach discriminates the vertical mass transport in terms of equivalent potential temperature. The scheme separates rising air at high entropy from subsiding air at low entropy. This also filters out oscillatory motions associated with gravity waves and isolates the overturning motions associated with convection and mesoscale circulation. The mesoscale convective system is additionally partitioned into stratiform and convective regions based on the radar reflectivity field. For each of the subregions, the mass transport derived in terms of height and an isentropic invariant of the flow is analyzed. The difference between the Eulerian mass flux and the isentropic counterpart is a significant and symmetric contribution of the buoyant oscillations to the upward and downward mass fluxes. Filtering out these oscillations results in substantial reduction of the diagnosed downward-to-upward convective mass flux ratio. The analysis is also applied to graupel and snow mixing ratios and number concentrations, illustrating the relationship of the particle formation process to the updrafts.

The Simulated Structure and Evolution of a Quasi-Idealized Warm-Season Convective System with a Training Convective Line

Abstract This study details the development and use of an idealized modeling framework to simulate a quasi-stationary heavy-rain-producing mesoscale convective system (MCS). A 36-h composite progression of atmospheric fields computed from 26 observed warm-season heavy-rain-producing training line/adjoining stratiform (TL/AS) MCSs was used as initial and lateral boundary conditions for a numerical simulation of this MCS archetype. A realistic TL/AS MCS initiated and evolved within a simulated mesoscale environment that featured a low-level jet terminus, maximized low-level warm-air advection, and an elevated maximum in convective available potential energy. The first stage of MCS evolution featured an eastward-moving trailing-stratiform-type MCS that generated a surface cold pool. The initial system was followed by rearward off-boundary development, where a new line of convective cells simultaneously redeveloped north of the surface cold pool boundary. Backbuilding persisted on the western end of the new line, with individual convective cells training over a fixed geographic region. The final stage was characterized by a deepening and southward surge of the cold pool, accompanied by the weakening and slow southward movement of the training line. The low-level vertical wind shear profile favored kinematic lifting along the southeastern cold pool flank over the southwestern flank, potentially explaining why convection propagated with (did not propagate with) the former (latter) outflow boundaries. The morphological features of the simulated MCS are common among observed cases and may, therefore, be generalizable. These results suggest that they are emergent from fundamental features of the large-scale environment, such as persistent regional low-level lifting, and with the vertical environmental wind profile characteristic to TL/AS systems.

Use of the Parcel Buoyancy Minimum (Bmin) to Diagnose Simulated Thermodynamic Destabilization. Part II: Composite Analysis of Mature MCS Environments

Abstract Herein, the parcel buoyancy minimum (Bmin) defined in Part I of this two-part paper is used to examine physical processes influencing thermodynamic destabilization in environments of mature simulated mesoscale convective systems (MCSs). These convection-permitting simulations consist of twelve 24-h forecasts during two 6-day periods characterized by two different commonly occurring warm-season weather regimes that support MCSs over the central United States. A composite analysis of 22 MCS environments is performed where cases are stratified into surface-based (SB), elevated squall (ES), and elevated nonsquall (ENS) categories. A gradual reduction of lower-tropospheric Bmin to values indicative of small convection inhibition, occurring over horizontal scales >100 km from the MCS leading edge, is a common aspect of each category. These negative buoyancy decreases are most pronounced for the ES and ENS environments, in which convective available potential energy (CAPE) is greatest for air parcels originating above the surface. The implication is that the vertical structure of the mesoscale environment plays a key role in the evolution and sustenance of convection long after convection initiation and internal MCS circulations develop, particularly in elevated systems. Budgets of Bmin forcing are computed for the nocturnally maturing ES and ENS composites. Though warm advection occurs through the entire 1.5-km-deep layer comprising the vertical intersection of the largest environmental CAPE and smallest environmental Bmin magnitude, the net effect of terms involving vertical motion dominate the destabilization in both composites. These effects include humidity increases in air parcels due to vertical moisture advection and the adiabatic cooling of the environment above.

The Role of Cloud Microphysics Parameterization in the Simulation of Mesoscale Convective System Clouds and Precipitation in the Tropical Western Pacific

Abstract This paper presents a detailed analysis of convection-permitting cloud simulations, aimed at increasing the understanding of the role of parameterized cloud microphysics in the simulation of mesoscale convective systems (MCSs) in the tropical western Pacific (TWP). Simulations with three commonly used bulk microphysics parameterizations with varying complexity have been compared against satellite-retrieved cloud properties. An MCS identification and tracking algorithm was applied to the observations and the simulations to evaluate the number, spatial extent, and microphysical properties of individual cloud systems. Different from many previous studies, these individual cloud systems could be tracked over larger distances because of the large TWP domain studied. The analysis demonstrates that the simulation of MCSs is very sensitive to the parameterization of microphysical processes. The most crucial element was found to be the fall velocity of frozen condensate. Differences in this fall velocity between the experiments were more related to differences in particle number concentrations than to fall speed parameterization. Microphysics schemes that exhibit slow sedimentation rates for ice aloft experience a larger buildup of condensate in the upper troposphere. This leads to more numerous and/or larger MCSs with larger anvils. Mean surface precipitation was found to be overestimated and insensitive to the microphysical schemes employed in this study. In terms of the investigated properties, the performances of complex two-moment schemes were not superior to the simpler one-moment schemes, since explicit prediction of number concentration does not necessarily improve processes such as ice nucleation, the aggregation of ice crystals into snowflakes, and their sedimentation characteristics.