Content uploaded by Roger M. Wakimoto
Author content
All content in this area was uploaded by Roger M. Wakimoto on Feb 13, 2017
Content may be subject to copyright.
A preview of the PDF is not available
Convectively Driven High Wind Events
Abstract and Figures
On a day when the potential instability is sufficient, it is possible to initiate storms from rising air parcels. One estimate of the intensity of these buoyant plumes (also an indicator of the severity of the storm) is based on parcel theory (Bluestein et al. 1988, 1989; Holton 1992). These rising parcels of air rapidly cool until saturation occurs. Further lifting results in condensation and, in a short period of time, precipitation develops. It is often at this stage that another fundamental element of a storm commonly forms: the convective downdraft.
Figures - uploaded by Roger M. Wakimoto
Author content
All figure content in this area was uploaded by Roger M. Wakimoto
Content may be subject to copyright.
... The basic forcing mechanisms for downdrafts are given by the vertical momentum equation; the significance of the individual terms is summarized in the literature review by Wakimoto (2001). He notes that the vertical gradient of perturbation pressure and the perturbation pressure buoyancy term were, in most cases, less important than the precipitation induced changes in buoyancy. ...
... Srivastava (1985) notes that in the extreme case of an environmental lapse rate close to a dry adiabatic lapse rate, even light precipitation can lead to significant downdrafts. The dependence on ambient environmental humidity is less clear (see also Wakimoto, 2001). While a moister environment increases the virtual temperature difference between downdraft and environment, thus strengthening the downdraft, this effect can be reversed when the effect of entrainment of environmental air is considered. ...
One important component of precipitating convection is the formation of convective downdrafts. They can terminate the initial updraft, affect the mean properties of the boundary layer, and cause strong winds at the surface. While the basic forcing mechanisms for downdrafts are well understood, it is difficult to formulate general relationships between updrafts, environmental conditions, and downdrafts. To better understand what controls different downdraft properties, we analyze downdrafts over tropical oceans in a global storm resolving simulation. Using a global model allows us to examine a large number of downdrafts under naturally varying environmental conditions. We analyze the various factors affecting downdrafts using three alternative methods. First, hierarchical clustering is used to examine the correlation between different downdraft, updraft, and environmental variables. Then, either random forests or multiple linear regression are used to estimate the relationships between downdraft properties and the updraft and environmental predictors. We find that these approaches yield similar results. Around 75% of the variability in downdraft mass flux and 37% of the variability in downdraft velocity are predictable. Analyzing the relative importance of our various predictors, we find that downdrafts are coupled to updrafts via the precipitation generation argument. In particular, updraft properties determine rain amount and rate, which then largely control the downdraft mass flux and, albeit to a lesser extent, the downdraft velocity. Among the environmental variables considered, only lapse rate is a valuable predictor: a more unstable environment favors a higher downdraft mass flux and a higher downdraft velocity.
... Several recent works have brought forward methods to track cold pools, in particular their gust fronts, in numerical simulations (Drager & van den Heever, 2017;Fournier & Haerter, 2019;Henneberg et al., 2020;Hirt et al., 2020;Rochetin et al., 2021;Schlemmer & Hohenegger, 2016). Yet, the detection of cold pools in numerical simulations is far from trivial: (a) the area affected by rainfall, where the CP is fed by rain evaporation, is often not cleanly delimited and subject to setting a threshold value, for example, on the precipitation rate; (b) the CP density current, as a highly dynamic object, experiences turbulent mixing and heat exchange with the surface and ambient environment, and is subject to spontaneous symmetry breaking, such as under the formation of "lobe-and-cleft" instabilities-again feeding back on the dynamics (Härtel et al., 2000;Markowski & Richardson, 2010;Simpson, 1972;Wakimoto, 2001); (c) the larger-scale pattern of cold pools and the rain cells produced by their collisions, is highly complex, with families formed by CP-rain cell networks making for a challenging tracking problem. ...
Recent observations and modeling increasingly reveal the key role of cold pools in organizing the convective cloud field. Several methods for detecting cold pools in simulations exist, but are usually based on buoyancy fields and fall short of reliably identifying the active gust front. The current cold pool (CP) detection and tracking algorithm (CoolDeTA), aims to identify cold pools and follow them in time, thereby distinguishing their active gust fronts and the “offspring” rain cells generated nearby. To accomplish these tasks, CoolDeTA utilizes a combination of thermodynamic and dynamical variables and examines the spatial and temporal relationships between cold pools and rain events. We demonstrate that CoolDeTA can reconstruct CP family trees. Using CoolDeTA we can contrast radiative convective equilibrium (RCE) and diurnal cycle CP dynamics, as well as cases with vertical wind shear and without. We show that the results obtained are consistent with a conceptual model where CP triggering of children rain cells follows a simple birth rate, proportional to a CP's gust front length. The proportionality factor depends on the ambient atmospheric stability and is lower for RCE, in line with marginal stability as traditionally ascribed to the moist adiabat. In the diurnal case, where ambient stability is lower, the birth rate thus becomes substantially higher, in line with periodic insolation forcing—resulting in essentially run‐away mesoscale excitations generated by a single parent rain cell and its CP.
... Such patterns, which can be characterized as eddies forming along the azimuthal direction along the GF, have previously been referred to as lobe-and-cleft instabilities (Härtel, Carlsson & Thunblom, 2000;Markowski & Richardson, 2010;J. E. Simpson, 1972;Wakimoto, 2001). Based on numerical simulations it was suggested that the activation of these azimuthal features could affect the radial spreading of the CPs by causing a transition from a power law r(t) ∼ t α with α ≈ 0.6 at times before, but α ≈ 0.4 after the transition . ...
Plain Language Summary
Convective cold pools (CPs) are regions of cool air forming beneath precipitating clouds. As rain droplets evaporate during their fall, they cool down the surrounding air, thereby increasing its weight and causing it to sink down. As the cold sinking airflow hits the ground, it spreads outward in all directions, creating strong wind gusts which are important mediators of the weather system. Indeed, such gust fronts can suppress cloud formation in some locations, by cooling the near‐surface air, while simultaneously triggering cloud formation along their edges by wedging underneath and lifting the ambient air. Numerical weather models should ideally account for these effects. Unfortunately, the models' grid resolution is often too coarse to represent the thin CPs, and it is not yet known what resolution should be used. In this study, high‐resolution simulations of idealized CPs are carried out at different mesh resolutions, allowing a systematic exploration of CPs' sensitivity to grid resolution. Our simulation results may help reveal configuration requirements for high‐resolution simulations and guide climate model development.
Previous research has suggested that the frequency and intensity of surface hazards associated with thunderstorms and convection, such as severe convective winds (SCWs), could potentially change in a future climate due to global warming. However, because of the small spatial scales associated with SCWs, they are unresolved in global climate models, and future climate projections are uncertain. Here, we evaluate the representation of SCW events in a convection-permitting climate model (Bureau of Meteorology Regional Projections for Australia, BARPAC-M), run over southeastern Australia for December–February months. We also assess changes in SCW event frequency in a projected future climate for the year 2050, and compare this with an approach based on identifying large-scale environments favourable for SCWs from a regional parent model (BARPA-R). This is done for three different types of SCW events that have been identified in this region, based on clustering of the large-scale environment. Results show that BARPAC-M representation of the extreme daily maximum wind gust distribution is improved relative to the gust distribution simulated by the regional parent model. This is due to the high spatial resolution of BARPAC-M output, as well as partly resolving strong and short-lived gusts associated with convection. However, BARPAC-M significant overestimates the frequency of simulated SCW events, particularly in environments having steep low-level temperature lapse rates. A future decrease in SCW frequency under steep lapse rate conditions is projected by BARPAC-M, along with less frequently favourable large-scale environments. In contrast, an increase in SCW frequency is projected under high surface moisture conditions, with more frequently favourable large-scale environments. Therefore, overall changes in SCWs for this region remain uncertain, due to different responses between event types, combined with historical model biases.
Wind storms impact human lives in their built as well as natural habitats. During the past century, society’s vulnerability to wind storms has been reduced by enhanced knowledge of their impact and by controlling exposure through better design. However, only two wind systems have so far been considered in the design of buildings and structures: synoptic winds resulting from macroscale weather systems spanning thousands of kilometers (e.g., extratropical storms) and mesoscale tropical storms spanning hundreds of kilometers and traveling fast (e.g., hurricanes, typhoons, cyclones). During the past two decades, enough evidence has surfaced to support that a third type of very localized wind storms, the non-synoptic winds, are the most damaging in some regions of the world. Thus far there are no design provisions established for the codification of these wind storms. Their characterization in terms of climatology, wind field and intensity, frequency, and occurrence, as well as their impact on the built environment, is slowly developing. This handbook presents state-of-the-art knowledge related to all these features including their risk, insurance issues, and economics. The research in this area is, on the one hand, more arduous given the reduced scale, three-dimensionality, and nonstationary aspects of these non-synoptic winds while, on the other hand, its understanding and modeling are being aided by the emergence of the novel modeling and simulation techniques addressed in this handbook. This handbook will serve as a guiding resource for those interested in learning about and contributing to the advancement of the field.
Convective wind gusts (CGs) are usually related to thunderstorms, and they may cause great structural damage and serious hazards, such as train derailment, service interruption, and building collapse. Due to the small-scale and nonstationary nature of CGs, reliable CG nowcasting with high spatial and temporal resolutions has remained unattainable. In this study, a novel nowcasting model based on deep learning-namely, CGsNet-is developed for 0-2 h lead times of quantitative CG nowcasting, achieving minute-kilometer-level forecasts. CGsNet is a physics-constrained model established by training on large corpora of average surface wind speed (ASWS) and radar observations; it can produce realistic and spatiotemporally consistent ASWS predictions in CG events. By combining the gust factor (1.77, the ratio of the observed peak wind gust speed (PWGS) to the ASWS) with the ASWS predictions, the PWGS forecasts are estimated with a spatial resolution of 0.01 • × 0.01 • and a 6 min temporal resolution. CGsNet is shown to be effective, and it has an essential advantage in learning the spatiotem-poral features of CGs. In addition, quantitative evaluation experiments indicate that CGsNet exhibits higher generalization performance for CGs than the traditional nowcasting method based on numerical weather prediction models. CG-nowcasting technology can be applied to provide real-time quantitative CG forecasts.
Many studies have aimed to identify novel storm characteristics that are indicative of current or future severe weather potential using a combination of ground-based radar observations and severe reports. However, this is often done on a small scale using limited case studies on the order of tens to hundreds of storms due to how time-intensive this process is. Herein, we introduce the GridRad-Severe dataset, a database including ∼100 severe weather days per year and upwards of 1.3 million objectively tracked storms from 2010-2019. Composite radar volumes spanning objectively determined, report-centered domains are created for each selected day using the GridRad compositing technique, with dates objectively determined using report thresholds defined to capture the highest-end severe weather days from each year, evenly distributed across all severe report types (tornadoes, severe hail, and severe wind). Spatiotemporal domain bounds for each event are objectively determined to encompass both the majority of reports as well as the time of convection initiation. Severe weather reports are matched to storms that are objectively tracked using the radar data, so the evolution of the storm cells and their severe weather production can be evaluated. Herein, we apply storm mode (single cell, multicell, or mesoscale convective system) and right-moving supercell classification techniques to the dataset, and revisit various questions about severe storms and their bulk characteristics posed and evaluated in past work. Additional applications of this dataset are reviewed for possible future studies.
The initiation of thunderstorms in environments characterized by strong wind shear presents a forecast challenge because of the complexities of the interactions between growing cumulus clouds and wind shear. Thunderstorms that develop in such environments are often capable of producing high-impact hazards, highlighting the importance of convection initiation in sheared environments. Although recent research has greatly improved understanding of the structure and evolution of rising thermals in unsheared environments, there remains uncertainty in how wind shear influences the convection initiation process. Two large-eddy simulations (75-m horizontal grid spacing) were performed to study this problem. Convection initiation attempts are forced in the simulations through prescribed surface heat fluxes (the initial boundary layers are statistically horizontally homogeneous and quasi–steady state but contain turbulent eddies as a result of random initial temperature perturbations). The only difference between the two simulations is the presence or absence of wind shear above 2 km. Important differences in the entrainment patterns are present between sheared and unsheared growing cumulus clouds. As found in previous research, the overturning circulation associated with rising thermals drives dynamic entrainment in the unsheared clouds. However, in sheared clouds, wake entrainment resulting from the tilting of environmental vorticity is an important dynamic entrainment pathway. This result has implications for both the structure of sheared growing cumulus clouds and for convection initiation in sheared environments.
Significance Statement
Forecasts of thunderstorm hazards such as tornadoes, hail, and strong winds, require the accurate prediction of when and where thunderstorms form. Unfortunately, predicting thunderstorm formation is not easy, as there are a lot of different factors to consider. One such factor is environmental vertical wind shear, which describes how winds change speed and direction with height. The purpose of this study is to better understand how wind shear impacts developing clouds. Our results demonstrate a specific mechanism, called “wake entrainment,” through which wind shear can weaken developing clouds and potentially prevent them from becoming strong thunderstorms entirely. Understanding this mechanism may be useful for thunderstorm prediction in environments characterized by wind shear.
Convective wind gusts (CGs) are usually related to thunderstorms, and they may cause great structural damage and serious hazards, such as train derailment, service interruption, and building collapse. Due to the small-scale and nonstationary nature of CGs, reliable CGs nowcasting with high spatial and temporal resolutions has remained unattainable. In this study, a novel nowcasting model based on deep learning – namely, CGsNet – is developed for 0–2 h of quantitative CGs nowcasting, first achieving minute-kilometer-level forecasts. CGsNet is a physics-constrained model established by training on large corpora of average surface wind speed (ASWS) and radar observations, it can produce realistic and spatiotemporally consistent ASWS predictions in CGs events. By combining the gust factor (1.77, the ratio of the observed peak wind gust speed (PWGS) to the ASWS) with the ASWS predictions, the PWGS forecasts are estimated with a spatial resolution of 0.01° × 0.01° and a 6-minute temporal resolution. CGsNet is shown to be effective, and it has an essential advantage in learning the spatiotemporal features of CGs. In addition, quantitative evaluation experiments indicate that CGsNet exhibits higher generalization performance for CGs than the traditional nowcasting method based on numerical weather prediction models. CGs nowcasting technology can be applied to provide real-time quantitative CGs forecasts and alerts the damaging wind events in meteorological services.
Radar-scope patterns at the time of known tornado occurrences were examined. There seems to be a good correlation between tornadoes and an echo pattern called a LEWP (Line Echo Wave Pattern). Many of these LEWP's were observed without reports of tornadoes or large hail. In about 75 per cent of the confirmed cases of tornadoes, their occurrence could be associated with a line of echoes. Individual echo trajectory convergence predominated in the remainer of cases.
The objectives of the American Meteorological Society are "the development and dissemination of knowledge of meteorology in all its phases and applications, and the advancement of its professional ideals." The organization of the Society took place in affiliation with the American Association for the Advancement of Science at Saint Louis, Missouri, December 29, 1919, and its incorporation, at Washington, D. C., January 21, 1920. The work of the Society is carried on by the Bulletin, the Journal, and Meteorological Monographs, by papers and discussions at meetings of the Society, through the offices of the Secretary and the Executive Secretary, and by correspondence. All of the Americas are represented in the membership of the Society as well as many foreign countries.
This book is a collection of selected lectures presented at the ‘Intensive Course on Mesoscale Meteorology and Forecasting’ in Boulder, USA, in 1984. It includes mesoscale classifications, observing techniques and systems, internally generated circulations, mesoscale convective systems, externally forced circulations, modeling and short-range forecasting techniques. This is a highly illustrated book and comprehensive work, including extensive bibliographic references. It is aimed at graduates in meteorology and for professionals working in the field.
Author sees geostationary satellite data as the key to nowcasting because of the high temporal resolution available, and gives some case studies of the use of the imagery for mesoscale analysis in the S. USA. Concludes with a brief discussion on combining satellite and radar data. -R.Harris
Detailed analyses of radar echoes, betanetwork data and upper-air soundings recorded on 3 April 1964 are made to investigate possible mechanisms of the movement of severe thunderstorms. One of the storms investigated moved significantly to the left of the mean wind while others moved in the direction of or moderately to the right of the mean wind. The left-moving storm was found to generally display a mirror image of the radar echo intensity structure, growth, and circulation character of right-moving storms. A similar relationship is found in the surface pressure and wind fields. Analyses of a diverging storm pair revealed that the left-moving storm echo indicated the presence of continuous echo growth and development along the left flank of a quasi-steady supercell. An area of low surface pressure, and converging surface wind occurred along the left-front quadrant beneath a low-level inflowing current. The right-moving storms were found to contain similar pressure and wind features along the right-rear flank. The analytical results give reasonable evidence that continuous propagation was occurring on opposing flanks of the storm pair. The continuous propagation mechanism, incorporated in a simple, qualitative model taking into account low-level momentum conservation, drag, and lift is demonstrated to be important in order to explain the observed movement of these storms.
In discussing the value of weather radar in meteorological research, Lidga (1951) recognized a scale too gross to be observed from a single station in the usual manner, yet too small to appear even on a sectional synoptic chart. He stated that “phenomena of this size might well be designated as mesometeorological.” Until a few years later, when Swingle and Rosenberg (1953) used this term in their research on cold fronts, a large number of studies dealing with these phenomena were reported as either micrometeorological or detailed synoptic. Regarding the expanded scope of mesometeorological research integrating radar and special network data, Tepper (1959) has emphasized the importance of research dealing, in detail, with the definition of the characteristic dimensions of the mesoscale.
A general characteristic of the atmosphere is its streakiness. It manifests itself in many phenomena such as the “cloudstreets” of polar outbreaks and tradewinds, the radar bands of hurricanes and certain precipitation patterns, the squall lines and the jet stream cirrus. The banded structure can be traced back to convection in heated air flows with a curved velocity profile of rather uniform direction. The typical vertical curvature was found to be 10 −7 (cm −1 sec −1 ). A preliminary note deals with some theoretical considerations. Synoptic cloud analysis by weather satellites will greatly profit from the wide spread existence of cloud bands. DOI: 10.1111/j.2153-3490.1959.tb00033.x