Explore the vast range of titles available.

Although tornadoes produced by quasi-linear convective systems (QLCSs) generally are weak and short lived, they have high societal impact due to their proclivity to develop over short time scales, within the cool season, and during nighttime hours. Precisely why they are weak and short lived is not well understood, although recent work suggests that QLCS updraft width may act as a limitation to tornado intensity. Herein, idealized simulations of tornadic QLCSs are performed with variations in hodograph shape and length as well as initiation mechanism to determine the controls of tornado intensity. Generally, the addition of hodograph curvature in these experiments results in stronger, longer-lived tornadic-like vortices (TLVs). A strong correlation between low-level mesocyclone width and TLV intensity is identified ( R 2 = 0.61), with a weaker correlation in the low-level updraft intensity ( R 2 = 0.41). The tilt and depth of the updraft are found to have little correlation to tornado intensity. Comparing QLCS and isolated supercell updrafts within these simulations, the QLCS updrafts are less persistent, with the standard deviations of low-level vertical velocity and updraft helicity approximately 48% and 117% greater, respectively. A forcing decomposition reveals that the QLCS cold pool plays a direct role in the development of the low-level updraft, providing the benefit of additional forcing for ascent while also having potentially deleterious effects on both the low-level updraft and near-surface rotation. The negative impact of the cold pool ultimately serves to limit the persistence of rotating updraft cores within the QLCS.

Organized systems of deep convective clouds are often associated with high-impact weather and changes in such systems may have implications for climate sensitivity. This has motivated the derivation of many organization indices that attempt to measure the level of deep convective aggregation in models and observations. Here we conduct a comprehensive review of existing methodologies and highlight some of their drawbacks, such as only measuring organization in a relative sense, being biased toward particular spatial scales, or being very sensitive to the details of the calculation algorithm. One widely used metric, I org , uses statistics of nearest-neighbor distances between convective storms to address the first of these concerns, but we show here that it is insensitive to organization beyond the meso- β scale and very contingent on the details of the implementation. We thus introduce a new and complementary metric, L org , based on all-pair convective storm distances, which is also an absolute metric that can discern regular, random, and clustered cloud scenes. It is linearly sensitive to spatial scale in most applications and robust to the implementation methodology. We also derive a discrete form suited to gridded data and provide corrections to account for cyclic boundary conditions and finite, open boundary domains of nonequal aspect ratios. We demonstrate the use of the metric with idealized synthetic configurations, as well as model output and satellite rainfall retrievals in the tropics. We claim that this new metric usefully supplements the existing family of indices that can help to understand convective organization across spatial scales.

Mean synoptic-scale conditions accompanying convective storms that produce hazardous weather phenomena in southern Brazil (SB) and neighboring areas are investigated. Emphasis is placed on discriminating between conditions conducive to tornadoes (TORN) and those to heavy rainfall (RAIN) and non-tornadic wind gusts (GUST). For this purpose, an analysis of the meteorological conditions associated with 40 events from each severe weather category is conducted using data from CFSR/CFSv2 reanalysis. Data are sampled for times closest to the severe weather event in a 30 ∘ × 30 ∘ adaptive latitude-longitude domain centered on each event location. Average charts are obtained for the synoptic fields and atmospheric parameters, and mean tropospheric profiles are compared among the distinct hazards. Overall, the role played by a surface low pressure system that extends to SB is highlighted, conditioning the environment to convective storms. This system favors low-level northwesterly moist flow and surface convergence over the center of the domain. Subtle differences are found between the TORN and GUST composites, with the former exhibiting weaker baroclinic forcing but stronger vertical wind shear in the lower troposphere. Distinctions between TORN and RAIN are more pronounced, with TORN exhibiting more intense horizontal pressure gradients, surface-based CAPE, and vertical wind shear. The average wind profile for TORN exhibited the most elongated and curved hodograph at low levels. Convective parameters showed poor discrimination between TORN and GUST, while performing better in discriminating TORN from RAIN, especially the shear parameters computed along the effective inflow layer of the storms.

The environmental characteristics and formation process of a tornado spawned by a quasi-linear convective system (QLCS) over Kanto Plain, Japan, are examined using observations, a reanalysis dataset, and a high-resolution numerical simulation with a horizontal grid spacing of 50 m. The QLCS environment responsible for tornadogenesis was characterized by small convective available potential energy and large storm-relative environmental helicity due to strong vertical shear associated with a low-level jet. The strong low-level jet was associated with a large zonal pressure gradient between two meridionally aligned extratropical cyclones and a synoptic-scale high pressure system to the east. The numerical simulation reproduced the tornado in the central part of the QLCS. Before the tornadogenesis, three mesovortices developed that were meridionally aligned at 500-m height, and a rear inflow jet (RIJ) associated with relatively cold air originated from aloft and developed on the west side of the QLCS, while descending from rear to front. Tornadogenesis occurred in the southernmost mesovortex at the northern tip of the RIJ. This mesovortex induces strong low-level updrafts through vertical pressure gradient force. A circulation analysis and vorticity budget analysis for the mesovortex show that environmental crosswise vorticity in the forward inflow region east of the QLCS played a significant role in the formation of the mesovortex. The circulation analysis for the tornado shows that frictional effects contribute to the increase of circulation associated with the tornado. Moreover, environmental shear associated with horizontal and vertical shear of the horizontal wind also contribute to the circulation of the tornado.

The sensitivity of low-frequency gravity waves generated during the development and mature stages of an MCS to variations in the characteristics of the rimed ice parameterization were tested through idealized numerical simulations over a range of environment shears and instabilities. Latent cooling in the simulations with less dense, graupel-like rimed ice was more concentrated aloft near the melting level, while cooling in simulations with denser, hail-like rimed ice extended from the melting level to the surface. However, the cooling profiles still had significant internal variability across different environments and over each simulation’s duration. Initial wave production during the MCS developing stage was fairly similar in the hail and graupel simulations. During the mature stages, graupel simulations showed stronger perturbations in CAPE due to the cooling and associated wave vertical motion being farther aloft; hail simulations showed stronger perturbations in LFC due to cooling and wave vertical motion being concentrated at lower levels. The differences in the cooling profiles were not uniform enough to produce consistently different higher-order wave modes. However, the initiation of discrete cells ahead of the convective line was found to be highly sensitive to the nature of the prior destabilizing wave. Individual events of discrete propagation were suppressed in some of the graupel simulations due to the higher location of both peak cooling and vertical wave motion. Such results underscore the need to fully characterize MCS microphysical heating profiles and their low-frequency gravity waves to understand their structure and development.

The Geostationary Operational Environmental Satellite-14 ( GOES-14 ) Imager operated in 1-min Super Rapid Scan Operations for GOES-R (SRSOR) mode during summer and fall of 2012 to emulate the high temporal resolution sampling of the GOES-R Advanced Baseline Imager (ABI). The current GOES operational scan interval is 15–30 min, which is too coarse to capture details important for severe convective storm forecasting including 1) when indicators of a severe storm such as rapid cloud-top cooling, overshooting tops, and above-anvil cirrus plumes first appear; 2) how satellite-observed cloud tops truly evolve over time; and 3) how satellite cloud-top observations compare with radar and lightning observations at high temporal resolution. In this paper, SRSOR data, radar, and lightning observations are used to analyze five convective storms, four of which were severe, to address these uncertainties. GOES cloud-top cooling, increased lightning flash rates, and peak precipitation echo tops often preceded severe weather, signaling rapid intensification of the storm updraft. Near the time of several severe hail or damaging wind events, GOES cloud-top temperatures and radar echo tops were warming rapidly, which indicated variability in the storm updraft that could have allowed the hail and wind gusts to reach the surface. Above-anvil cirrus plumes were another prominent indicator of impending severe weather. Detailed analysis of storms throughout the 2012 SRSOR period indicates that 57% of the plume-producing storms were severe and 85% of plumes from severe storms appeared before a severe weather report with an average lead time of 18 min, 9 min earlier than what would be observed by GOES operational scanning.

This study examined a typical case of deep convective storm that formed over southwest India on October 12, 2011, using ground-based X-band radar measurements and Weather Research and Forecasting (WRF) model simulations. The radar observation showed isolated pockets of convective storm, which merged later to form a convective cluster. The observed storms were tall, extending well into the mixed-phase region. Few storms even extended up to the tropopause height. Three different WRF cloud microphysics schemes (WRF Double-Moment 6-Class, Morrison Double-Moment, and Milbrandt–Yau Double-Moment) were used to simulate the observed deep convective storm to examine the vertical structure of hydrometeors. All the cloud microphysics schemes were able to reproduce the convective storm event with a lag time of almost two and a half hours. The WRF Double-Moment 6-Class scheme better simulates the vertical structure of storm compared to the other two microphysics schemes. The WRF model reasonably simulated the observed patterns of convective storm when the WRF cloud microphysics scheme better simulate the graupel and snow. The differences in simulated storm structure obtained by different microphysics schemes compared to observation highlight the deficiency involved in the simulations in capturing the microphysics that is guiding the intensity of convective storms. The present study thus underscores the importance of microphysics in different parameterization schemes of WRF simulation over southwest India, which has an implication in the forecasting of convective storms.

Convective storms CS frequently occur in Kerala during the premonsoon period, particularly in the month of May, presenting numerous hazards such as intense rainfall, lightning, and wind gusts, which cause significant damage to life, property, infrastructure, livelihoods, and various societal sectors. The current study explored the triple-threat nature of convective storms in the month of May over Kerala. This study revealed that CS is accompanied by excessive rainfall in northern regions and exhibits greater intensity than in southern areas. The coastal areas are emerging as the most vulnerable to extreme rainfall hotspots, exhibiting increased intensity from Ernakulam to Kasargod. The topographical characteristics of these regions, encompassing the Kottayam-Idukki border and the eastern sections of Malapuram, also influence rainfall intensity. The districts of Kottayam, Ernakulam, Idukki, and Pathanamthitta are particularly vulnerable to lightning strikes. Over Kerala, CS clouds with brightness temperatures below 240 K and gust winds above 30 kt are particularly hazardous since they pose the triple threat of heavy rainfall, lightning, and strong winds. The study revealed that CS occurs more frequently in regions adjacent to western Ghats WG with northern Kerala exhibiting the highest intensity and southern Kerala displaying a greater frequency of CS.

Tornadoes are the most violent and destructive of all the severe weather phenomena that localized convective storms produce. There is a requirement in operational meteorology increasing nowadays that an indicator index which allows to reduce the uncertainty of severe convective storms and tornadoes in the scope of climate change adaptation strategies. The main intention is not to replace or substitute mesoscale modeling approaches, or composite indexes, but to warn operationally to draw attention to the Eastern Mediterranean and Türkiye in particular a few days in advance. The development of some indicators using atmospheric variables can undertake a crucial role by enabling such numerical models to be run only at certain time intervals, thus enduring lower computational costs. In this study, Eastern Mediterranean oscillation index (EMEDOi) has been developed in order to be able to detect the presence of ULLs (upper-level low) and frontogenesis approach is employed for selected tornadic storm events in Türkiye. EMEDOi has 7 different its variations (members) which these members have been developed to detect differences depending on the entry directions of cyclones and storms influencing Türkiye from the west of the country. In line with the GDAS data analysis, values of geopotential height are derived for the requirement of EMEDOi in a limited area. A few of the results from the study are as in the following: 86% of the trained tornado events revealed that the EMEDO-Oper index was in negative phase at the time a tornado was reported, regardless of whether the events featured a supercell mesoscale convective storm or a frontal movement. The hourly period until the local minimum is obtained can be described and characterized as the process by which the EMEDO-Oper index value decreases continuously. The time required to reach the local minimum varies based on the tornado occurrence. Based on the tornadic storm scenario in the test cluster in 2022 and the train cluster, this timeframe is predicted to be roughly 33.2 h on average. In western Türkiye, there is a 79% chance of a tornado occurring between six and forty-two hours after the EMEDO-Oper index reaches its local minimum. In particular, the projected chance for this period is 63% between 12 and 30 h after the local minimum is obtained. Besides, the majority of the tornado incidents with EMEDO-Oper values below − 0.75 were evaluated. After an EMEDO-Oper index value falls below that threshold, it is likely to forecast the risk period of a tornado in Türkiye with a probability of 79% and the local minimum point must be identified.

Severe convective storms that produce tornadoes and straight-line winds usually develop under particular environmental conditions and have specific signatures on the cloud tops associated with intense updrafts. In this study, we performed a comparative analysis of satellite-derived characteristics, with a focus on cloud-top properties, and ERA5-based environmental parameters of convective storms in forested regions of the western part of Northern Eurasia in 2006–2021. The analyzed sample includes 128 different convective storms that produced 138 tornadoes and 143 linear windstorms. We found most tornadoes and linear windstorms are generated by quasi-linear convective storms or supercells. Such supercells form under lower convective instability and precipitable water content compared to those for other types of storms. We found a significant negative correlation of minimum temperature on the storm cloud top with instability parameters. In turn, the longevity of convective storms significantly correlates with wind shear and storm-relative helicity. About half of the tornadoes and 2/3 of linear windstorms are associated with the presence of cloud-top signatures, such as overshooting tops, cold-ring or cold U/V features. The events associated with such signatures are formed under high values of instability parameters. Our results can be used for further analysis of peculiarities of tornado and linear windstorm formation and to enhance the predictability of such severe events, especially in regions with a lack of weather radar coverage.