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1. Tornadoes in Southeast South America: Mesoscale to Planetary-Scale Environments

   https://doi.org/10.1175/MWR-D-22-0248.1  

   Veloso-Aguila, Daniel ; Rasmussen, Kristen L. ; Maloney, Eric D. ( January 2024 , Monthly Weather Review)

   A multiscale analysis of the environment supporting tornadoes in southeast South America (SESA) was conducted based on a self-constructed database of 74 reports. Composites of environmental and convective parameters from ERA5 were generated relative to tornado events. The distribution of the reported tornadoes maximizes over the Argentine plains, while events are rare close to the Andes and south of Sierras de Córdoba. Events are relatively common in all seasons except in winter. Proximity environment evolution shows enhanced instability, deep-layer vertical wind shear, storm-relative helicity, reduced convective inhibition, and a lowered lifting condensation level before or during the development of tornadic storms in SESA. No consistent signal in low-level wind shear is seen during tornado occurrence. However, a curved hodograph with counterclockwise rotation is present. The Significant Tornado Parameter (STP) is also maximized prior to tornadogenesis, most strongly associated with enhanced CAPE. Differences in the convective environment between tornadoes in SESA and the U.S. Great Plains are discussed. On the synoptic scale, tornado events are associated with a strong anomalous trough crossing the southern Andes that triggers lee cyclogenesis, subsequently enhancing the South American low-level jet (SALLJ) that increases moisture advection to support deep convection. This synoptic trough also enhances vertical shear that, along with enhanced instability, sustains organized convection capable of producing tornadic storms. At planetary scales, the tornadic environment is modulated by Rossby wave trains that appear to be forced by convection near northern Australia. Madden–Julian oscillation phase 3 preferentially occurs 1–2 weeks ahead of tornado occurrence.

   The main goal of this study is to describe what atmospheric conditions (from local to global scales) are present prior to and during tornadic storms impacting southeast South America (SESA). Increasing potential for deep convection, wind shear, and potential for rotating updrafts, as well as reducing convective inhibition and cloud-base height, are predominant a few hours before and during the events in connection to low-level northerly winds enhancing moisture transport to the region. Remote convective activity near northern Australia appears to influence large-scale atmospheric circulation that subsequently triggers convective storms supporting tornadogenesis 1–2 weeks later in SESA. Our findings highlight the importance of accounting for atmospheric processes occurring at different scales to understand and predict tornado occurrences.

    

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2. Relation between Baroclinity, Horizontal Vorticity, and Mesocyclone Evolution in the 6–7 April 2018 Monroe, Louisiana, Tornadic Supercell during VORTEX-SE

   https://doi.org/10.1175/MWR-D-22-0313.1  

   Hosek, Michael J. ; Ziegler, Conrad L. ; Biggerstaff, Michael I. ; Murphy, Todd A. ; Wang, Zhien ( November 2023 , Monthly Weather Review)

   This case study analyzes a tornadic supercell observed in northeast Louisiana as part of the Verification of the Origins of Rotation in Tornadoes Experiment Southeast (VORTEX-SE) on 6–7 April 2018. One mobile research radar (SR1-P), one WSR-88D equivalent (KULM), and two airborne radars (TAFT and TFOR) have sampled the storm at close proximity for ∼70 min through its mature phase, tornadogenesis at 2340 UTC, and dissipation and subsequent ingestion into a developing MCS segment. The 4D wind field and reflectivity from up to four Doppler analyses, combined with 4D diabatic Lagrangian analysis (DLA) retrievals, has enabled kinematic and thermodynamic analysis of storm-scale boundaries leading up to, during, and after the dissipation of the NWS-surveyed EF0 tornado. The kinematic and thermodynamic analyses reveal a transient current of low-level streamwise vorticity leading into the low-level supercell updraft, appearing similar to the streamwise vorticity current (SVC) that has been identified in supercell simulations and previously observed only kinematically. Vorticity dynamical calculations demonstrate that both baroclinity and horizontal stretching play significant roles in the generation and amplification of streamwise vorticity associated with this SVC. While the SVC does not directly feed streamwise vorticity to the tornado–cyclone, its development coincides with tornadogenesis and an intensification of the supercell’s main low-level updraft, although a causal relationship is unclear. Although the mesoscale environment is not high-shear/low-CAPE (HSLC), the updraft of the analyzed supercell shares some similarities to past observations and simulations of HSLC storms in the Southeast United States, most notably a pulse-like updraft that is maximized in the low- to midlevels of the storm.

   The purpose of this study is to analyze the airflow and thermodynamics of a highly observed tornado-producing supercell. While computer simulations can provide us with highly detailed looks at the complicated evolution of supercells, it is rare, due to the difficulty of data collection, to collect enough data to perform a highly detailed analysis on a particular supercell, especially in the Southeast United States. We identified a “current” of vorticity—rotating wind—that develops at the intersection of the supercell’s rain-cooled outflow and warm inflow, similar to previous simulations. This vorticity current develops and feeds the storm’s updraft as its tornado develops and the storm intensifies, although it does not directly enter the tornado.

    

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3. The Development of Severe Vortices within Simulated High-Shear, Low-CAPE Convection

   https://doi.org/10.1175/MWR-D-18-0246.1  

   Sherburn, Keith D. ; Parker, Matthew D. ( June 2019 , Monthly Weather Review)

   Environments characterized by large values of vertical wind shear and modest convective available potential energy (CAPE) are colloquially referred to as high-shear, low-CAPE (HSLC) environments. Convection within these environments represents a considerable operational forecasting challenge. Generally, it has been determined that large low-level wind shear and steep low-level lapse rates—along with synoptic-scale forcing for ascent—are common ingredients supporting severe HSLC convection. This work studies the specific processes that lead to the development of strong surface vortices in HSLC convection, particularly associated with supercells embedded within a quasi-linear convective system (QLCS), and how these processes are affected by varying low-level shear vector magnitudes and lapse rates. Analysis of a control simulation, conducted with a base state similar to a typical HSLC severe environment, reveals that the key factors in the development of a strong surface vortex in HSLC embedded supercells are (i) a strong low- to midlevel mesocyclone, and (ii) a subsequent strong low-level updraft that results from the intense, upward-pointing dynamic perturbation pressure gradient acceleration. Through a matrix of high-resolution, idealized simulations, it is determined that sufficient low-level shear vector magnitudes are necessary for the development of low- to midlevel vertical vorticity [factor (i)], while steeper low-level lapse rates provide stronger initial low-level updrafts [factor (ii)]. This work shows why increased low-level lapse rates and low-level shear vector magnitudes are important to HSLC convection on the storm scale, while also revealing similarities between surface vortexgenesis in HSLC embedded supercells and higher-CAPE supercells.

    

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4. A Benchmark to Test Generalization Capabilities of Deep Learning Methods to Classify Severe Convective Storms in a Changing Climate

   https://doi.org/10.1029/2020EA001490  

   Molina, Maria J. ; Gagne, David John ; Prein, Andreas F. ( August 2021 , Earth and Space Science)

   This is a test case study assessing the ability of deep learning methods to generalize to a future climate (end of 21st century) when trained to classify thunderstorms in model output representative of the present‐day climate. A convolutional neural network (CNN) was trained to classify strongly rotating thunderstorms from a current climate created using the Weather Research and Forecasting model at high‐resolution, then evaluated against thunderstorms from a future climate and found to perform with skill and comparatively in both climates. Despite training with labels derived from a threshold value of a severe thunderstorm diagnostic (updraft helicity), which was not used as an input attribute, the CNN learned physical characteristics of organized convection and environments that are not captured by the diagnostic heuristic. Physical features were not prescribed but rather learned from the data, such as the importance of dry air at mid‐levels for intense thunderstorm development when low‐level moisture is present (i.e., convective available potential energy). Explanation techniques also revealed that thunderstorms classified as strongly rotating are associated with learned rotation signatures. Results show that the creation of synthetic data with ground truth is a viable alternative to human‐labeled data and that a CNN is able to generalize a target using learned features that would be difficult to encode due to spatial complexity. Most importantly, results from this study show that deep learning is capable of generalizing to future climate extremes and can exhibit out‐of‐sample robustness with hyperparameter tuning in certain applications.

    

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5. The Synoptically-Influenced Extreme Precipitation Systems over Asian-Austrailian Monsoon Region from TRMM PR Measurements

   Jian, Hong-Wen ; Chen, Wei-Ting ; Chen, Peng-Jen ; Wu, Chien-Ming ; Rasmussen, Kristen L. ( January 2021 , Journal of the Meteorological Society of Japan)

   null (Ed.)

   This study investigates the synoptic scale flows associated with extreme rainfall systems over the Asian-Australian monsoon region (90-160°E and 12°S-27°N). Based on statistics of the 17-year Precipitation Radar observations from Tropical Rainfall Measurement Mission, a total of 916 extreme systems with both the horizontal size and maximum rainfall intensity exceeding the 99.9th percentiles of the tropical rainfall systems are identified over this region. The synoptic wind pattern and rainfall distribution surrounding each system are classified into four major types: Vortex, Coastal, Coastal with Vortex, and None of above, with each accounting for 44 %, 29 %, 7 %, and 20 %, respectively. The vortex type occurs mainly over the off-equatorial areas in boreal summer. The coast-related types show significant seasonal variations in their occurrence, with high frequency in the Bay of Bengal in boreal summer and on the west side of Borneo and Sumatra in boreal winter. The None-of-the-above type occurs mostly over the open ocean, and in boreal winter these events are mainly associated with the cold surge events. The environment analysis shows that coast-related extremes in the warm season are found within the areas where high total water vapor and low-level vertical wind shear occur frequently. Despite the different synoptic environments, these extremes show a similar internal structure, with broad stratiform and wide convective core rain. Furthermore, the maximum rain rate locates mostly over convective area, near convective-stratiform boundary in the system. Our results highlight the critical role of the strength and direction of synoptic flows in the generation of extreme rainfall systems near coastal areas. With the enhancement of the low-level vertical wind shear and moisture by the synoptic flow, the coastal convection triggered diurnally has a higher chance to organize into mesoscale convective systems and hence a higher probability to produce extreme rainfall. 

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