Mesoscale Convective Organization Research Articles

Intensification of daily tropical precipitation extremes from more organized convection.

Tropical precipitation extremes and their changes with surface warming are investigated using global storm resolving simulations and high-resolution observations. The simulations demonstrate that the mesoscale organization of convection, a process that cannot be physically represented by conventional global climate models, is important for the variations of tropical daily accumulated precipitation extremes. In both the simulations and observations, daily precipitation extremes increase in a more organized state, in association with larger, but less frequent, storms. Repeating the simulations for a warmer climate results in a robust increase in monthly-mean daily precipitation extremes. Higher precipitation percentiles have a greater sensitivity to convective organization, which is predicted to increase with warming. Without changes in organization, the strongest daily precipitation extremes over the tropical oceans increase at a rate close to Clausius-Clapeyron (CC) scaling. Thus, in a future warmer state with increased organization, the strongest daily precipitation extremes over oceans increase at a faster rate than CC scaling.

Objectively Assessing Characteristics of Mesoscale Convective Organization in an Operational Convection-Permitting Model

Abstract The realism of convective organization in operational convection-permitting model simulations is objectively assessed, with a particular focus on the mesoscale aspects, such as convective mode. A tracking and classification algorithm is applied to observed radar reflectivity and simulated radar reflectivity from the operational ACCESS-C convection-permitting forecast domain over northern Australia between October 2020 and May 2022, and the characteristics of real and simulated convective organization are compared. Mesoscale convective systems from the operational forecast model are approximately twice as likely to be oriented parallel to the ambient wind and ambient wind shear than those observed by radar, indicating a bias toward the “training line” systems typically associated with more extreme rainfall. During highly humid active monsoon conditions, simulated convective systems have larger ground-relative speeds than systems observed in radar. Although there is less than 5% difference between the ratios of simulated and observed trailing, leading and parallel stratiform system observations, significant differences exist in other wind shear–based classifications. For instance, in absolute terms, simulated systems are 10%–35% less likely to be upshear tilted, and 15%–30% less likely to be downshear propagating than observed systems, suggesting errors in simulated cold pool characteristics. Significance Statement Remarkable progress has been made simulating thunderstorms in operational weather forecasting computer models. While some details of individual storm clouds may be unrealistic, how these storm clouds self-organize, i.e., cluster and regenerate, can be explicitly simulated, with this organization often appearing realistic. However, assessing the realism of this organization in an objective, systematic way has proven challenging. Here we assess organized convection in Australia’s current high-resolution weather prediction model. In some respects, simulated storm clouds organize realistically. High-altitude icy cloud mostly trails behind groups of storm clouds in both simulations and reality. In other respects, organization is unrealistic. Simulated storm clouds are twice as likely to orient along the mean wind direction than in reality, likely contributing to extreme rainfall biases.

Momentum fluxes from airborne wind measurements in three cumulus cases over land

Abstract. Measurements of wind and momentum fluxes are not typically at the centre of field studies on (shallow) cumulus convection, but the mesoscale organization of convection is likely closely tied to patterns in wind. This study combines in situ high-frequency turbulence measurements from a gust probe onboard a Cessna aircraft with downward profiling Doppler wind lidar (DWL) measurements onboard a Falcon aircraft to study variability in the wind profile and momentum fluxes in regions of convection. The dual-aircraft measurements were made during three prototype flights in shallow convective regimes over German agricultural areas (two of which had hilly topography, one flat) in late spring 2019, including forced cumulus humilis under weak winds and “popcorn” cumuli during stronger wind and wind shear after front passages. All flights show pronounced meso-gamma (2–20 km) scale variability in the wind, with the largest wind variance (on the order of 2–4 m2 s−2) towards cloud base and in the cloud layer on flights with large vertical wind shear. The wind and wind variance profiles measured in situ and by lidar compare very well, despite the DWL's coarse (∼ 8 km) horizontal footprint. This highlights the presence of wind fluctuations on scales larger than a few kilometres and that wind lidars can be used more deliberately in field studies to map (mesoscale) flows. Cloudy transects are associated with more than twice the momentum flux compared with cloud-free transects. The contribution of the updraft to the total momentum flux, typically one-third to two-thirds, is far less than the typical contribution of the updraft to buoyancy flux. Even on the same flight day, momentum flux profiles can differ per track, with one case of counter-gradient momentum transport when the updraft does carry substantial momentum flux. Scales beyond 1 km contribute significantly to the momentum flux and there is clear evidence for compensating flux contributions across scales. The results demonstrate that momentum flux profiles and their variability require understanding of motions across a range of scales, with non-negligible contributions of the clear-sky fluxes and of mesoscales that are likely coupled to the convection.

Utilizing a Storm-Generating Hotspot to Study Convective Cloud Transitions: The CACTI Experiment

AbstractThe Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign was designed to improve understanding of orographic cloud life cycles in relation to surrounding atmospheric thermodynamic, flow, and aerosol conditions. The deployment to the Sierras de Córdoba range in north-central Argentina was chosen because of very frequent cumulus congestus, deep convection initiation, and mesoscale convective organization uniquely observable from a fixed site. The C-band Scanning Atmospheric Radiation Measurement (ARM) Precipitation Radar was deployed for the first time with over 50 ARM Mobile Facility atmospheric state, surface, aerosol, radiation, cloud, and precipitation instruments between October 2018 and April 2019. An intensive observing period (IOP) coincident with the RELAMPAGO field campaign was held between 1 November and 15 December during which 22 flights were performed by the ARM Gulfstream-1 aircraft. A multitude of atmospheric processes and cloud conditions were observed over the 7-month campaign, including numerous orographic cumulus and stratocumulus events; new particle formation and growth producing high aerosol concentrations; drizzle formation in fog and shallow liquid clouds; very low aerosol conditions following wet deposition in heavy rainfall; initiation of ice in congestus clouds across a range of temperatures; extreme deep convection reaching 21-km altitudes; and organization of intense, hail-containing supercells and mesoscale convective systems. These comprehensive datasets include many of the first ever collected in this region and provide new opportunities to study orographic cloud evolution and interactions with meteorological conditions, aerosols, surface conditions, and radiation in mountainous terrain.

Equatorial Waves Triggering Extreme Rainfall and Floods in Southwest Sulawesi, Indonesia

AbstractOn the basis of detailed analysis of a case study and long-term climatology, it is shown that equatorial waves and their interactions serve as precursors for extreme rain and flood events in the central Maritime Continent region of southwest Sulawesi, Indonesia. Meteorological conditions on 22 January 2019 leading to heavy rainfall and devastating flooding in this area are studied. It is shown that a convectively coupled Kelvin wave (CCKW) and a convectively coupled equatorial Rossby wave (CCERW) embedded within the larger-scale envelope of the Madden–Julian oscillation (MJO) enhanced convective phase, contributed to the onset of a mesoscale convective system that developed over the Java Sea. Low-level convergence from the CCKW forced mesoscale convective organization and orographic ascent of moist air over the slopes of southwest Sulawesi. Climatological analysis shows that 92% of December–February floods and 76% of extreme rain events in this region were immediately preceded by positive low-level westerly wind anomalies. It is estimated that both CCKWs and CCERWs propagating over Sulawesi double the chance of floods and extreme rain event development, while the probability of such hazardous events occurring during their combined activity is 8 times greater than on a random day. While the MJO is a key component shaping tropical atmospheric variability, it is shown that its usefulness as a single factor for extreme weather-driven hazard prediction is limited.

Ship- and island-based atmospheric soundings from the 2020 EUREC4A field campaign

Abstract. To advance the understanding of the interplay among clouds, convection, and circulation, and its role in climate change, the Elucidating the role of clouds–circulation coupling in climate campaign (EUREC4A) and Atlantic Tradewind Ocean–Atmosphere Mesoscale Interaction Campaign (ATOMIC) collected measurements in the western tropical Atlantic during January and February 2020. Upper-air radiosondes were launched regularly (usually 4-hourly) from a network consisting of the Barbados Cloud Observatory (BCO) and four ships within 6–16∘ N, 51–60∘ W. From 8 January to 19 February, a total of 811 radiosondes measured wind, temperature, and relative humidity. In addition to the ascent, the descent was recorded for 82 % of the soundings. The soundings sampled changes in atmospheric pressure, winds, lifting condensation level, boundary layer depth, and vertical distribution of moisture associated with different ocean surface conditions, synoptic variability, and mesoscale convective organization. Raw (Level 0), quality-controlled 1 s (Level 1), and vertically gridded (Level 2) data in NetCDF format (Stephan et al., 2020) are available to the public at AERIS (https://doi.org/10.25326/137). The methods of data collection and post-processing for the radiosonde data set are described here.

Lagrangian Analysis of Tropical Cyclone Genesis Simulated by General Circulation Models Compared with Observations

AbstractAs a contribution to understanding the genesis of tropical cyclones (TCs), we compared TC genesis processes simulated by the Seoul National University Atmosphere Model version 0 with a Unified Convection Scheme (SAM0) and the Community Atmosphere Model version 5 (CAM5) with those from the ERA-Interim reanalysis (ERA-Interim, hereafter ERAI) and best track observations. In contrast to previous studies that estimated the TC genesis potential using the Eulerian mean environmental conditions, we calculated the probability of a pre-existing weak cyclonic embryo vortex (EV) developing into a TC by analyzing changes in the environmental conditions along the EV trajectories. Our analysis indicates that the spatial distribution and annual cycles of TCs obtained from the SAM0 and ERAI are similar to those obtained from the best track observation data. With the exception of the mesoscale convective organization and associated variables, most environmental variables along the trajectories of DEVs (EVs developing into TCs) showed monotonic variations. When EVs were born, environmental conditions of DEVs were significantly different from those of nondeveloping EVs, allowing for the prediction of TC genesis. In general, TC genesis probability increased as the environment became more cyclonic, moist, unstable, and with a weaker wind shear. Rapidly strengthening EVs were more likely to develop into TCs. SAM0 and ERAI have the same combination of environmental variables with the best prediction skill for TC genesis—absolute vorticity at 850 hPa, column saturation deficit, sea surface temperature, vertical shear of horizontal winds between 200 and 850 hPa, and latitude—with similar sensitivities to individual environmental variables, indicating that SAM0 well simulates the observed TC genesis processes.

Mechanisms of Convective Clustering During a 2‐Day Rain Event in AMIE/DYNAMO

AbstractPhysical mechanisms that are key to observed convective clustering in 2‐day rain events are examined. Previous analysis of the 2‐day rain events during the Atmospheric Radiation Measurement Madden‐Julian Oscillation Investigation Experiment (AMIE)/Dynamics of the Madden‐Julian Oscillation (DYNAMO) field campaign data revealed two distinct phases of convective clustering. Using a cloud‐system‐resolving model, we perform a series of intervention experiments to investigate the underlying mechanisms for convective clustering in each phase. In the developing phase, in addition to previously emphasized processes such as the cold pool‐updraft interaction and moisture‐convection feedbacks, our results show that the vertical wind shear in the lower free troposphere is a critical factor for convective clustering. Stronger lower free‐tropospheric wind shear increases the entrainment of environmental air into updrafts and prevents convective clouds from being omnipresent. This result suggests that stronger vertical wind shear in the lower free troposphere can help spatially organize the convection, even for non–squall‐line‐type convective systems. In the decaying phase, the cold pool‐updraft interaction becomes less effective in aggregating convective clouds because the boundary layer is widely cooled by stratiform precipitation. Instead, the mesoscale downdraft driven by the stratiform precipitation becomes the dominant factor to maintain the relatively aggregated convection. Additionally, removing horizontal variations in radiative heating has no impact on convective clustering on this 2‐day time scale, even in the decaying phase when stratiform clouds are widespread. The implication of these results for improving the representation of mesoscale convective organization in convection schemes is discussed.

Response of precipitation extremes to warming: what have we learned from theory and idealized cloud-resolving simulations, and what remains to be learned?

This paper reviews recent important advances in our understanding of the response of precipitation extremes to warming from theory and from idealized cloud-resolving simulations. A theoretical scaling for precipitation extremes has been proposed and refined in the past decades, allowing to address separately the contributions from the thermodynamics, the dynamics and the microphysics. Theoretical constraints, as well as remaining uncertainties, associated with each of these three contributions to precipitation extremes, are discussed. Notably, although to leading order precipitation extremes seem to follow the thermodynamic theoretical expectation in idealized simulations, considerable uncertainty remains regarding the response of the dynamics and of the microphysics to warming, and considerable departure from this theoretical expectation is found in observations and in more realistic simulations. We also emphasize key outstanding questions, in particular the response of mesoscale convective organization to warming. Observations suggest that extreme rainfall often comes from an organized system in very moist environments. Improved understanding of the physical processes behind convective organization is needed in order to achieve accurate extreme rainfall prediction in our current, and in a warming climate.

Mesoscale marine tropical precipitation varies independently from the spatial arrangement of its convective cells

AbstractThe relationship between mesoscale convective organization, quantified by the spatial arrangement of convection, and oceanic precipitation in the tropical belt is examined using the output of a global storm‐resolving simulation. The analysis uses a 2D watershed segmentation algorithm based on local precipitation maxima to isolate individual precipitation cells and derive their properties. 10° by 10° scenes are analyzed using a phase‐space representation made of the number of cells per scene and the mean area of the cells per scene to understand the controls on the spatial arrangement of convection and its precipitation. The presence of few and large cells in a scene indicates the presence of a more clustered distribution of cells, whereas many small cells in a scene tend to be randomly distributed. In general, the degree of clustering of a scene (Iorg) is positively correlated to the mean area of the cells and negatively correlated to the number of cells. Strikingly, the degree of clustering, whether the cells are randomly distributed or closely spaced, to a first order does not matter for the precipitation amounts produced. Scenes of similar precipitation amounts appear as hyperbolae in our phase‐space representation, hyperbolae that follow the contours of the precipitating area fraction. Finally, including the scene‐averaged water vapour path (WVP) in our phase‐space analysis reveals that scenes with larger WVP contain more cells than drier scenes, whereas the mean area of the cells only weakly varies with WVP. Dry scenes can contain both small and large cells, but they can contain only few cells of each category.

Toward a Dynamical Foundation for Organized Convection Parameterization in GCMs

AbstractA dynamically based parameterization of organized moist convection in the form of multiscale coherent structures and slantwise layer overturning principles provides upscale heat and counter‐gradient momentum transports distinct from diffusive down‐gradient mixing by unorganized cumulus. Implementation of a minimalist version of this new parameterization in a state‐of‐the‐art global climate model (GCM) improves the Madden‐Julian Oscillation and convectively coupled waves and generates large‐scale patterns of tropical precipitation consistent with Tropical Rainfall Measuring Mission satellite measurements. A question on the need to parameterize mesoscale convective organization to mitigate mean state biases is addressed.

Influence of deepening and mesoscale organization of shallow convection on stratiform cloudiness in the downstream trades

AbstractIn this study we use large‐eddy simulation to explore the factors controlling stratiform cloudiness in the downstream trades. We perform sensitivity experiments with different large‐scale forcings, radiation specifications and domain sizes, which isolate the influence of convective deepening, moisture–radiation interactions and mesoscale organization, respectively. Across the simulations with different large‐scale forcings, we find that the deepening of the cloud layer and the associated increase in precipitation strongly correlate with decreasing inversion strength and stratiform cloudiness. The relationship between cloud‐layer depth and cloud amount is largely independent of the way a specific change in the large‐scale forcing induces the deepening. The interaction of radiation with the domain‐averaged humidity and cloud profile is necessary for stratiform cloudiness to form. Strong radiative cooling experienced by updraughts overshooting a strong inversion induces the formation of detrained stratiform layers, and strong long‐wave cooling associated with the stratiform layers stabilizes the inversion. Interactive radiation is also important for exposing differences in shallow convection under different free‐tropospheric humidities. A drier initial free troposphere leads to both increased cloud‐layer and free‐tropospheric radiative cooling and increased surface evaporation, which forces deeper convection and more precipitation compared to a moister initial free troposphere. The simulations with a drier initial free troposphere thus have weaker inversions and less stratiform cloud. The organization of convection into larger clusters in large‐domain simulations increases precipitation and weakens the inversion compared to a simulation on a 16‐fold smaller domain, which does not support convective organization. Organized updraught clusters carry more moisture and liquid to the inversion, so that the same amount of stratiform cloudiness forms, despite the inversion being weaker. The simulations presented here suggest that the deepening and organization of shallow convection plays an important role in regulating stratiform cloudiness and thus total cloud cover in the downstream trades.

Do We Need to Parameterize Mesoscale Convective Organization to Mitigate the MJO‐Mean State Trade‐Off?

AbstractModifications in cumulus parameterizations that improve Madden‐Julian oscillation (MJO) simulation tend to degrade the mean state—known as the MJO‐mean state trade‐off. The impacts of parameterizing mesoscale convective organization on the relationship between the MJO and the mean state simulation fidelity are examined. A series of experiments are made with a general circulation model that parameterizes the mesoscale convective organization and simulates well both the MJO and the mean state. In the control simulation, a prognostic nondimensional variable (Ω) represents the degree of convective organization. In order to examine the effect of the parameterized convective organization, fixed Ω values are imposed in a series of constrained experiments. The fixed‐Ω simulations show a negative relationship between the MJO and the mean state simulation fidelity. The control simulation is deviated from the negative relationship, suggesting the parameterized mesoscale convective organization helps general circulation models to mitigate the MJO‐mean state trade‐off.

Objective Quantification of Convective Clustering Observed During the AMIE/DYNAMO Two‐Day Rain Episodes

AbstractOne critical bottleneck in developing and evaluating ways to represent the mesoscale organization of convection in cumulus parameterization schemes is that there is no single accepted method of objectively quantifying the degree of convective organization or clustering from observations. This study addresses this need using high‐quality S‐PolKa radar data from the Atmospheric Radiation Measurement Madden‐Julian Oscillation Investigation Experiment/Dynamics of the Madden‐Julian Oscillation (AMIE/DYNAMO) field campaign. We first identify convective elements (contiguous convective echoes [CCEs]) from radar reflectivity observations using the rain type classification algorithm of Powell et al. (2016, https://doi.org/10.1175/JTECH‐D‐15‐0135.1). Then we apply scalar clustering metrics, including the organization index (Iorg) of Tompkins and Semie, to the radar CCEs to test their ability of quantifying convective clustering during the observed two‐day rain episodes. Our results show two distinct phases of convective clustering during the two‐day rain episodes, with each phase covering about 10 hr before (Phase 1) and after (Phase 2) the time of peak rain rate. In Phase 1 clustering, the number of CCEs increases and convective cells cluster as new cells form preferentially near existing convective entities. The number of CCEs decreases as the environment stabilizes in Phase 2 clustering, during which already clustered cells with associated stratiform clouds are preferred over the isolated ones. Iorg is capable of capturing convective clustering in both phases. The possible mechanisms for convective clustering are discussed, including cold pool‐updraft feedback, moisture‐convection interaction, and mesoscale circulations. Our results suggest that parameterizations of convective organization should represent the feedback processes that are responsible for the convective clustering during both phases.

Estimating Bulk Entrainment With Unaggregated and Aggregated Convection

AbstractTo investigate how entrainment is influenced by convective organization, we use the ICON (ICOsahedral Nonhydrostatic) model in a radiative‐convective equilibrium framework, with a 1 km spatial grid mesh covering a 600 by 520 km2 domain. We analyze two simulations, with unaggregated and aggregated convection, and find that, in the lower free troposphere, the bulk entrainment rate increases when convection aggregates. The increase of entrainment rate with aggregation is caused by a strong increase of turbulence in the close environment of updrafts, masking other effects like the increase of updraft size and of static stability with aggregation. Even though entrainment rate increases with aggregation, updraft buoyancy reduction through entrainment decreases because aggregated updrafts are protected by a moist shell. Parameterizations that wish to represent mesoscale convective organization would need to model this moist shell.

The impacts of heterogeneous land surface fluxes on the diurnal cycle precipitation: A framework for improving the GCM representation of land‐atmosphere interactions

AbstractThe present study aims to investigate the modulation of the diurnal cycle precipitation by heterogeneous land surface fluxes. By combining the National Center for Atmospheric Research Community Land Model (CLM) and vector vorticity equation cloud‐resolving model (VVM), experiments are designed to understand the responses of diurnal convection to heterogeneous land surface forcings of various spatial scales and intensities. To delineate the land‐atmosphere interactions, a two‐step off‐line approach is adopted. First, the CLM is driven by observational atmospheric forcing with different characteristic length scales and magnitudes. While the surface fluxes from the CLM show no significant difference in the domain‐averaged values, their spatial distribution responds significantly to the precipitation heterogeneity. In the second step, the derived CLM surface fluxes are used to drive the VVM. Results show that the timing of precipitation accelerates with increasing magnitude of surface flux perturbation, while the mean and diurnal ranges of precipitation roughly remain the same. The larger perturbation magnitude enhances the boundary layer vertical kinetic energy, which advances the development of the boundary layer. On the other hand, the mean and diurnal ranges of precipitation increase significantly, and the timing of initial precipitation delays with increasing perturbation length scale. The inland breeze induced by the large patches of surface fluxes tends to enhance the mesoscale organization of deep convection, hence the stronger precipitation. The present results highlight the importance of taking heterogeneous land surface fluxes into consideration in future development of general circulation model convection parameterizations associated with land and atmosphere interactions.

Restricting 32–128 km horizontal scales hardly affects the MJO in the Superparameterized Community Atmosphere Model v.3.0 but the number of cloud‐resolving grid columns constrains vertical mixing

AbstractThe effects of artificially restricting the 32–128 km horizontal scale regime on MJO dynamics in the Superparameterized Community Atmosphere Model v.3.0 have been explored through reducing the extent of its embedded cloud resolving model (CRM) arrays. Two and four‐fold reductions in CRM extent (from 128 to 64 km and 32 km) produce statistical composite MJO signatures with spatial scale, zonal phase speed, and intrinsic wind‐convection anomaly structure that are all remarkably similar to the standard SPCAM's MJO. This suggests that the physics of mesoscale convective organization on 32–128 km scales are not critical to MJO dynamics in SPCAM and that reducing CRM extent may be a viable strategy for 400% more computationally efficient analysis of superparameterized MJO dynamics. However several unexpected basic state responses caution that extreme CRM domain reduction can lead to systematic mean state issues in superparameterized models. We hypothesize that an artificial limit on the efficiency of vertical updraft mixing is set by the number of grid columns available for compensating subsidence in the embedded CRM arrays. This can lead to reduced moisture ventilation supporting too much liquid cloud and thus an overly strong cloud shortwave radiative forcing, particularly in regions of deep convection.

The dominant synoptic‐scale modes of North American monsoon precipitation

ABSTRACTIn this study, we explore the mechanisms of synoptic rainfall variability using observations from the Tropical Rainfall Measuring Mission satellite. Although previously shown to have an important impact on North American monsoon rainfall, tropical cyclones are excluded from this analysis, in order to focus on more frequent synoptic disturbances within the region. A rotated empirical orthogonal function (EOF) analysis of North American monsoon rainfall during June to September 2002–2009 suggests that low‐level tropical disturbances contribute to the leading two modes of precipitation variability within this region. These disturbances result in gulf surges or low‐level surges of moisture up the Gulf of California, and provide a key moisture source to facilitate the development of organized convection. In the first mode, the low‐level trough brings precipitation to lower elevations along the western slopes of the Sierra Madre Occidental south of Hermosillo, Mexico and over the southern Baja Peninsula. In the second mode, the low‐level trough interacts with an upper‐level inverted trough enhancing precipitation into the southwestern United States and northwest Mexico. In particular, the upper‐level trough contributes to the easterly to northeasterly shear across the region, favouring mesoscale convective organization and enhanced deep convection over the Sierra Madre Occidental and higher elevations in southeast Arizona. The EOF methodology offers an objective approach for determining the dominant modes of precipitation for the monsoon region useful for identifying past and monitoring future low‐frequency impacts on these modes.

Meteorological Overview of the Devastating 27 April 2011 Tornado Outbreak

By many metrics, the tornado outbreak on 27 April 2011 was the most significant tornado outbreak since 1950, exceeding the super outbreak of 3–4 April 1974. The number of tornadoes over a 24-h period (midnight to midnight) was 199; the tornado fatalities and injuries were 316 and more than 2,700, respectively; and the insurable loss exceeded $4 billion (U.S. dollars). In this paper, we provide a meteorological overview of this outbreak and illustrate that the event was composed of three mesoscale events: a large early morning quasi-linear convective system (QLCS), a midday QLCS, and numerous afternoon supercell storms. The main data sources include NWS and research radars, profilers, surface measurements, and photos and videos of the tornadoes. The primary motivation for this preliminary research is to document the diverse characteristics (e.g., tornado characteristics and mesoscale organization of deep convection) of this outbreak and summarize preliminary analyses that are worthy of additional research ...

Modes of mesoscale convective system organization during Meiyu season over the Yangtze River basin

Mesoscale convective systems (MCSs) are classified and investigated through a statistical analysis of composite radar reflectivity data and station observations during June and July 2010–2012. The number of linear-mode MCSs is slightly larger than the number of nonlinear-mode MCSs. Eight types of linear-mode MCSs are identified: trailing stratiform MCSs (TS), leading stratiform MCSs (LS), training line/adjoining stratiform MCSs (TL/AS), back-building/quasi-stationary MCSs (BB), parallel stratiform MCSs (PS), broken line MCSs (BL), embedded line MCSs (EL), and long line MCSs (LL). Six of these types have been identified in previous studies, but EL and LL MCSs are described for the first time by this study. TS, LS, PS, and BL MCSs are all moving systems, while TL/AS, BB, EL, and LL MCSs are quasi-stationary. The average duration of linear-mode MCSs is more than 7 h. TL/AS and TS MCSs typically have the longest durations. Linear-mode MCSs often develop close to the Yangtze River, especially over low-lying areas and river valleys. The diurnal cycle of MCS initiation over the Yangtze River valley contains multiple peaks. The vertical distribution of environmental wind is decomposed into storm-relative perpendicular and parallel wind components. The environmental wind field is a key factor in determining the organizational mode of a linear-mode MCS.