Observed Variability in Convective Cell Characteristics and Near-Storm Environments across the Sea- and Bay-Breeze Fronts in Southeast Texas
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Abstract 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. Significance Statement 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.
Mesoscale convective systems are a class of storm linked to extensive flooding and other destructive hazards in many regions globally. In West Africa, soil moisture impacts provide a valuable source of predictability for mature storm hazards, but little is known about mature storm sensitivity to soil moisture in other climatic regions. Here we use a storm track dataset, satellite observations and reanalysis fields to investigate the response of mature storms to soil moisture in seven global storm hotspots—West Africa, India, South America, South Africa, Australia and the United States Great Plains. We demonstrate that mesoscale soil moisture gradients (~500 km) can enhance storms by driving increased vertical wind shear conditions, a crucial ingredient for storm organization, through the strengthening of atmospheric temperature gradients. This is evidenced by a 10–30% increase in precipitation feature size and rainfall for the largest storms on days with favourable soil moisture gradients compared with unfavourable gradients. Global simulations confirm that soil moisture gradients influence wind shear. The results demonstrate the importance of soil moisture feedbacks for accurate forecasting of mesoscale convective systems and future projections of extreme events under climate change.
This presentation was given at the Photovoltaic Specialist Conference (PVSC) 54 in New Orleans, Louisiana. Photovoltaic (PV) systems are routinely exposed to extreme weather, including wind and hail storms. Historically, most systems have proven to be resilient to such events, but some storms have damaged PV systems, leading to physical and financial loss. Storm hardening measures and specific system attributes can reduce this risk. This work introduces a set of resilience metrics and a framework for quantifying, comparing, and predicting PV system resilience. The framework is divided into two parts: 1) predictive, attribute metrics based on site and component characteristics, and 2) impact metrics that assess post-storm performance. Metrics are weighted and aggregated, producing hazard-specific resilience scores. We derive damage functions from storm-impacted PV systems, establishing a baseline against which post-storm performance can be compared. This damage was widely variable across hail and wind intensities, and field hail damage was less than predicted by laboratory tests, suggesting that system features - in addition to storm conditions - influence damage likelihood. Finally, the metrics framework is demonstrated using three case studies of storm damaged PV systems. Although additional data are needed to create attribute specific damage functions and establish metric weights, this study presents a methodology for evaluating PV resilience and contributes new damage functions to the literature.
Here, we investigate the relationship between convective available potential energy (CAPE), precipitation, the number and size of storms and overshooting tops, and lightning stroke density ($\mathcal{f}$) over the Central America region. While $\mathcal{f}$ increases almost linearly with CAPE 1/2 over land, $\mathcal{f}$ is nearly muted over the ocean when CAPE is small. In the high-CAPE regime, on the contrary, oceanic storms produce as many lightning flashes as land storms. We show that individual oceanic storms are smaller and contain fewer overshooting tops compared to land storms, although the difference exists across low- and high-CAPE regimes. While $\mathcal{f}$ increases as individual storm size increases, the storm size required to produce lightning appears to be disproportionately high in the low-CAPE regime, likely due to the stronger entrainment effect. The entrainment effect on $\mathcal{f}$ in the low-CAPE regime appears to be much weaker over land. Applying the CAPE threshold for lightning over the ocean to the CAPE-based lightning parameterization scheme of Romps et al. (2014), https://doi.org/10.1126/science.1259100 improves its performance, in particular, at representing the land-sea contrast in $\mathcal{f}$.
Abstract While extreme precipitation is expected to increase in a warming climate, its scaling with temperature at weather timescales often produces puzzling results. Here, we focus on the summer months over the central U.S. to investigate the scaling of extreme precipitation intensity (EPI) with local temperature and determine the contribution of mesoscale convective systems (MCSs) to the EPI scaling. Using an observational data set that differentiates precipitation associated with MCS and non‐MCS storms, we find that MCS storms contribute to 70% of EPI samples at temperatures lower than 298 K where EPI increases with temperature. However, at temperatures of 298–305 K, MCSs' contribution to EPI decreases as the predominant storm type shifts from MCS to non‐MCS storms, causing EPI to decrease with temperature due to the weaker rainfall intensity associated with non‐MCS storms compared with MCS storms. Our findings underscore the important role of different storm types in affecting the EPI scaling relationships.
This dataset provides long-duration large-eddy simulations (LES) of Hurricane Laura (2020), capturing the turbulent boundary-layer wind field during the storm's passage at horizontal grid spacings of 55.55 m and 10 m. Hurricane Laura made landfall as a Category 4 storm in southwestern Louisiana at 06:00 UTC on 27 August 2020, producing widespread damage to coastal infrastructure. The simulations characterize the spatial and temporal variability of the turbulent wind at heights spanning the lowest 300 m of the boundary layer, throughout the approach and passage of the storm's eyewall over a fixed location. To resolve the spatial heterogeneity of wind and turbulence conditions across the storm, seven independent refined LES runs are performed at radial locations spanning the storm relative to its direction of motion. The refinement positions are defined on a normalized radial coordinate r ̂=r/R, where R≈21 km is Laura's radius of maximum wind, and lie between r ̂=-1.5 and r ̂=+1.5 in ∆r ̂=0.5 increments along a line perpendicular to the storm's track at the midpoint of the simulation. Negative r ̂ corresponds to locations south-southwest of the storm center and positive r ̂ to locations north-northeast. The dataset is segmented into seven radial refinement groups.
We compare ESA PROBA-V observations of electron flux at LEO with those from the NASA Van Allen Probes mostly at MEO for October 2013. Dropouts are visible at all energy during four storms from both satellites. Equatorially trapped electron fluxes are higher than at LEO by 10 2 (<1 MeV) to 10 5 (>2.5 MeV). We observe a quite isotropic structure of the outer belt during quiet times, contrary to the inner belt, and pitch angle dependence of high energy injection. We find a very good overlap of the outer belt at MEO and LEO at ~0.5 MeV. We use test-particle simulations of the energetic electrons trapped in the terrestrial magnetic field to study the outer radiation belt electron flux changes during geomagnetic storms. We show that the Dst (Disturbance storm time) effect during the main phase of a geomagnetic storm results in a betatron mechanism causing outward radial drift and a deceleration of the electrons. This outward drift motion is energy independent, pitch angle-dependent, and represents a significant distance (~1 L-shell at L = 5 for moderate storms). At fixed L-shell, this causes a decay of the LEO precipitating flux (adiabatic outward motion), followed by a return to the normal state (adiabatic inward motion) during main and recovery phases. Dst effect, associated with magnetopause shadowing and radial diffusion can explain the main characteristics of outer radiation belt electron dropouts in October 2013. We also use Fokker-Planck simulations with event-driven diffusion coefficients at high temporal resolution, to distinguish instantaneous loss from the gradual scattering that depopulates the slot region and the outer belt after storms. Simulations reproduce the slot formation and the gradual loss in the outer belt. The typical energy dependence of these losses leads to the absence of scattering for relativistic and ultra-relativistic electrons in the outer belt, oppositely to dropouts.
Where rivers meet the sea, tides can exert a physical and chemical influence on the lower reaches of a river. How tidal dynamics in these tidal river reaches interact with upstream hydrological drivers such as storm rainfall, which ultimately determines the quantity and composition of material transferred from watersheds to estuaries, is currently unknown. We monitored a small freshwater tidal river in the Pacific Northwest, USA in high resolution over one year to evaluate the relative importance of tides versus upstream hydrological flows (i.e., base flow and precipitation events) on basic physico-chemical parameters (pH, dissolved oxygen, turbidity, specific conductivity, and temperature), and how these interactions relate to the downstream estuary. Tidal variability and diurnal cycles (i.e. solar radiation) dominated water physico-chemical variability in the summer, but the influence of these drivers was overshadowed by storm-driven sharp pulses in river physico-chemistry during the remainder of the year. Within such events, we found incidences of counterclockwise hysteresis of pH, counterclockwise hysteresis of dissolved oxygen, and clockwise hysteresis of turbidity, although systematic trends were not observed across events. The dominance of storm rainfall in the river’s physico-chemistry dynamics, and similar pulses of decreased pH observed in adjacent estuarine waters, suggest that the linkage between tidal streams and the broader system is variable throughout the year. High-frequency monitoring of tidal river biogeochemistry is therefore crucial to enable the assessment of how the relative strength of these drivers may change with future sea level rise and altered precipitation patterns to modulate biogeochemical dynamics across the land-ocean-atmosphere continuum.
Reliable development of the power grid is an evolving concern for humanity due to extreme weather that frequently threatens power sector infrastructure. The state of Texas is a uniquely structured testbed for grid planners to study when looking for solutions to development, innovation, and overcoming such challenges. Because of its size and islanded structure, Texas is small enough to model, but big enough to matter. Texas is a global leader in energy production, energy consumption, and maintains an unusually diverse fuel mix. In addition, the state has experienced winter freezes, heat waves, wind storms, droughts and floods that have threatened power sector infrastructure or caused recent blackouts and calls for demand side conservation. One of the most devastating of these events was the North American winter storm, dubbed “Winter Storm Uri” by the Weather Channel, that froze the region in February 2021 and led to an extended power outage event that put the majority of Texan residents in darkness for days. While preparing to avoid such outage events in the future, various tools have been proposed to improve grid reliability, including energy efficiency, demand response, and distributed energy resources. An additional option would be to develop interregional transmission that connects the Texas grid to other national grids. To assess the merits of this idea, we developed a novel, universally-applicable and internationally-relevant framework to study how the Texas grid would evolve alongside access to various interregional ties. This method allows us to stress the synthetic grid structure and analyze how it would respond to the shock of a simulated winter storm event. Our method leverages open-source modeling tools, such as PowerGenome, pyGRETA, and GenX to synthesize unique zonal grid data, construct a consolidated network of model regions, and simulate different developmental pathways of capacity expansion and operational dispatch. We demonstrate our method with an analysis connecting the Electric Reliability Council of Texas (ERCOT), the grid that serves most of Texas, the Western Electricity Coordinating Council (WECC), the grid that serves the western half of the contiguous U.S., and the Eastern Interconnect, the grid that serves the eastern half of the contiguous U.S. Our results indicate that the cost-optimal capacity of interregional transmission connecting the ERCOT grid to other grids lies between 9–13 GW assuming baseline conditions. Building this amount of connecting capacity in one or multiple directions lowers the costs and emissions of development and operation by up to $16 billion and 257 million metric tonnes (MMT) respectively. Additionally, our results show that the interregional connections between ERCOT and other national grids reduce the amount of total load shed required through mild winter storm events. However, our results also show that there is a threshold of very extreme winter storm conditions, spanning multiple service areas, above which the connections exacerbate resource adequacy problems. Therefore, the results indicate that the connections need to be carefully planned alongside the rest of the grid infrastructure to avoid over-reliance on specific resources or technology options.
In this study we explored the environmental conditions hypothesized to induce a dominant charge structure in thunderstorms in the province of Cordoba, Argentina, during the RELAMPAGO-CACTI (Remote sensing of Electrification, Lightning, And Mesoscale/microscale Processes with Adaptive Ground Observations-Clouds, Aerosols, Complex Terrain Interactions) field campaigns. Hypothesized environmental conditions are thought to be related to small warm cloud residence time and warm rain growth suppression, which lead to high cloud liquid water contents in the mixed-phase zone, contributing to positive charging of graupel and anomalous charge structure storms. Data from radiosondes, a cloud condensation nuclei (CCN) ground-based instrument and reanalysis were used to characterize the proximity inflow air of storms with anomalous and normal charge structures. Consistent with the initial hypothesis, anomalous storms had small warm cloud depth caused by dry low-level humidity and low 0°C height. Anomalous storms were associated with lower CCN concentrations than normal storms, an opposite result to the initial expectation. High CAPE is not an important condition for the development of anomalous storms in Argentina, as no clear pattern could be found among the different parameters calculated for updraft proxy that would be consistent with the initial hypothesis.
Abstract Stormwater is a vital resource and dynamic driver of terrestrial ecosystem processes. However, processes controlling interactions during and shortly after storms are often poorly seen and poorly sensed when direct observations are substituted with technological ones. We discuss how human observations complement technological ones and the benefits of scientists spending more time in the storm. Human observation can reveal ephemeral storm-related phenomena such as biogeochemical hot moments, organismal responses, and sedimentary processes that can then be explored in greater resolution using sensors and virtual experiments. Storm-related phenomena trigger lasting, oversized impacts on hydrologic and biogeochemical processes, organismal traits or functions, and ecosystem services at all scales. We provide examples of phenomena in forests, across disciplines and scales, that have been overlooked in past research to inspire mindful, holistic observation of ecosystems during storms. We conclude that technological observations alone are insufficient to trace the process complexity and unpredictability of fleeting biogeochemical or ecological events without the shower thoughts produced by scientists’ human sensory and cognitive systems during storms.
On 8 February 2018, a supercell storm produced gargantuan (>15 cm or >6 inches in maximum dimension) hail as it moved over the heavily populated city of Villa Carlos Paz in Cordoba Province, Argentina, South America. Observations of gargantuan hail are quite rare, but the large population density here yielded numerous witnesses and social media pictures and videos from this event that document multiple large hailstones. The storm was also sampled by the newly installed operational polarimetric C-band radar in Cordoba. During the RELAMPAGO campaign, the authors interviewed local residents about their accounts of the storm, and uncovered additional social media video and photographs revealing extremely large hail at multiple locations in town. This article documents the case, including the meteorological conditions supporting the storm (with the aid of a high-resolution WRF simulation), the storm's observed radar signatures, and three noteworthy hailstones observed by residents. These hailstones include a freezer-preserved 4.48-inch (11.38-cm) maximum dimension stone that was scanned with a 3D infrared laser scanner, a 7.1-inch (18-cm) maximum dimension stone, and a hailstone photogrammetrically estimated to be between 7.4 and 9.3 inches (18.8-23.7-cm) in maximum dimension, which is close to or exceeds the world record for maximum dimension. Such a well-observed case is an important step forward in understanding environments and storms that produce gargantuan hail, and ultimately how to anticipate and detect such extreme events.
Abstract Vertical wind shear is known to affect supercell thunderstorms by displacing updraft hydrometeor mass downshear, thereby facilitating the storms’ longevity. Shear also impacts the size of supercell updrafts, with stronger shear leading to wider, less dilute, and stronger updrafts with likely greater hydrometeor production. To more clearly define the role of shear across different vertical layers on hydrometeor concentrations and displacements relative to supercell updrafts, a suite of idealized numerical model simulations of supercells was conducted. Shear magnitudes were systematically varied across the 0–1, 1–6, and 6–12 km AGL layers, while the thermodynamic environment was held fixed. Simulations show that as shear magnitude increases, especially from 1 to 6 km, updrafts become wider and less dilute with an increase in hydrometeor loading, along with an increase in the low-level precipitation area/rate and total precipitation accumulation. Even with greater updraft hydrometeor loading amid stronger shear, updrafts are more intense in stronger shear simulations due to larger thermal buoyancy owing to wider, less dilute updraft cores. Furthermore, downshear hydrometeor displacements are larger in environments with stronger 1–6-km shear. In contrast, there is relatively less sensitivity of hydrometeor concentrations and displacements to variations in either 0–1- or 6–12-km shear. Results are consistent across free tropospheric relative humidity sensitivity simulations, which show an increase in updraft size and hydrometeor mass with increasing free tropospheric relative humidity owing to a reduction in entrainment-driven dilution for wider updrafts in moister environments. Significance Statement Rotating thunderstorms, known as supercells, are able to persist for multiple hours. One common explanation is that large changes in wind speed and/or direction with height, or shear, transport rain/hail away from supercell updrafts, supporting their maintenance. The strong shear within supercell environments, however, may also lead to greater rail/hail amounts, thereby leading to weaker storms due to this extra mass of water/ice within updrafts. Furthermore, the impact of shear across different height layers on supercell rain/hail characteristics has not been thoroughly investigated. In this study, computer simulations of supercells were conducted to determine that shear occurring between 1 and 6 km above ground level has a large impact on rain/hail distribution in supercells and that stronger shear in this layer leads to wider/stronger supercells with greater rain/hail accumulations at the surface. Additionally, some of the extra mass of water/ice is transported farther away from updrafts due to the stronger environmental storm-relative winds.
The aim of this project is to improve the initial conditions of large eddy simulations (LES) of deep convective storms by assimilating scanning radar reflectivity and radial velocity data as well as local environmental observations. Accomplishing this goal often results in more accurate numerical forecasts of clouds and precipitation than if the background initial meteorological conditions are solely relied upon for convection initiation and intensification, as is typical of most operational and research models. Conducted in a storm-scale LES framework, these more accurate numerical analyses can serve as tool to better understand and parameterize land-atmosphere coupling, boundary layer turbulence, and cloud processes, each used for model parameterization development of convection. Our work examined the sensitivity of the numerical representation of cloud-scale wind and microphysical structures to: i) the assimilation of radiosonde observations characterizing the near-storm inflow, ii) the assimilation of radar data of varying resolution for model simulations with grid spacings of 1-km and 0.25-km, and iii) to the assimilation of three-dimensional plan-projection-indicator (PPI) and range-height indicator (RHI) radar volumes. Few studies have explored deep convective storm analyses and forecasts produced by assimilation of radar observations to cloud-scale LES. Furthermore, to our knowledge, no storm-scale DA study has explored the value of assimilating high-resolution sector RHI volumes to determine if they can improve the retrieval of the vertical kinematic and microphysical storm structure aloft over the use of traditionally utilized PPI scans.