skip to main content

Title: Diagnosing Convective Dependencies on Near-Storm Environments Using Ensemble Sensitivity Analyses

Convection intensity and longevity is highly dependent on the surrounding environment. Ensemble sensitivity analysis (ESA), which quantitatively and qualitatively interprets impacts of initial conditions on forecasts, is applied to very short-term (1–2 h) convective-scale forecasts for three cases during the Mesoscale Predictability Experiment (MPEX) in 2013. The ESA technique reveals several dependencies of individual convective storm evolution on their nearby environments. The three MPEX cases are simulated using a previously verified 36-member convection-allowing model (Δ x = 3 km) ensemble created via the Weather Research and Forecasting (WRF) Model. Radar and other conventional observations are assimilated using an ensemble adjustment Kalman filter. The three cases include a mesoscale convective system (MCS) and both nontornadic and tornadic supercells. Of the many ESAs applied in this study, one of the most notable is the positive sensitivity of supercell updraft helicity to increases in both storm inflow region deep and shallow vertical wind shear. This result suggests that larger values of vertical wind shear within the storm inflow yield higher values of storm updraft helicity. Results further show that the supercell storms quickly enhance the environmental vertical wind shear within the storm inflow region. Application of ESA shows that these storm-induced perturbations then affect further storm evolution, suggesting the presence of storm–environment feedback cycles where perturbations affect future mesocyclone strength. Overall, ESA can provide insight into convection dependencies on the near-storm environment.

more » « less
Author(s) / Creator(s):
 ;  ;  
Publisher / Repository:
American Meteorological Society
Date Published:
Journal Name:
Monthly Weather Review
Page Range / eLocation ID:
p. 495-517
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Abstract Observational data collection is extremely hazardous in supercell storm environments, which makes for a scarcity of data used for evaluating the storm-scale guidance from convection allowing models (CAMs) like the National Oceanic and Atmospheric Administration (NOAA) Warn-on-Forecast System (WoFS). The Targeted Observations with UAS and Radar of Supercells (TORUS) 2019 field mission provided a rare opportunity to not only collect these observations, but to do so with advanced technology: vertically pointing Doppler lidar. One standing question for WoFS is how the system forecasts the feedback between supercells and their near-storm environment. The lidar can observe vertical profiles of wind over time, creating unique datasets to compare to WoFS kinematic predictions in rapidly evolving severe weather environments. Mobile radiosonde data are also presented to provide a thermodynamic comparison. The five lidar deployments (three of which observed tornadic supercells) analyzed show WoFS accurately predicted general kinematic trends in the inflow environment; however, the predicted feedback between the supercell and its environment, which resulted in enhanced inflow and larger storm-relative helicity (SRH), were muted relative to observations. The radiosonde observations reveal an overprediction of CAPE in WoFS forecasts, both in the near and far field, with an inverse relationship between the CAPE errors and distance from the storm. Significance Statement It is difficult to evaluate the accuracy of weather prediction model forecasts of severe thunderstorms because observations are rarely available near the storms. However, the TORUS 2019 field experiment collected multiple specialized observations in the near-storm environment of supercells, which are compared to the same near-storm environments predicted by the National Oceanic and Atmospheric Administration (NOAA) Warn-on-Forecast System (WoFS) to gauge its performance. Unique to this study is the use of mobile Doppler lidar observations in the evaluation; lidar can retrieve the horizontal winds in the few kilometers above ground on time scales of a few minutes. Using lidar and radiosonde observations in the near-storm environment of three tornadic supercells, we find that WoFS generally predicts the expected trends in the evolution of the near-storm wind profile, but the response is muted compared to observations. We also find an inverse relationship of errors in instability to distance from the storm. These results can aid model developers in refining model physics to better predict severe storms. 
    more » « less
  2. Abstract

    This study synthesizes the results of 13 high-resolution simulations of deep convective updrafts forming over idealized terrain using environments observed during the RELAMPAGO and CACTI field projects. Using composite soundings from multiple observed cases, and variations upon them, we explore the sensitivity of updraft properties (e.g., size, buoyancy, and vertical pressure gradient forces) to influences of environmental relative humidity, wind shear, and mesoscale orographic forcing that support or suppress deep convection initiation (CI). Emphasis is placed on differentiating physical processes affecting the development of updrafts (e.g., entrainment-driven dilution of updrafts) in environments typifying observed successful and null (i.e., no CI despite affirmative operational forecasts) CI events. Thermally induced mesoscale orographic lift favors the production of deep updrafts originating from ∼1- to 2-km-wide boundary layer thermals. Simulations without terrain forcing required much larger (∼5-km-wide) thermals to yield precipitating convection. CI outcome was quite sensitive to environmental relative humidity; updrafts with increased buoyancy, depth, and intensity thrived in otherwise inhospitable environments by simply increasing the free-tropospheric relative humidity. This implicates the entrainment of free-tropospheric air into updrafts as a prominent governor of CI, consistent with previous studies. Sensitivity of CI to the environmental wind is manifested by 1) low-level flow affecting the strength and depth of mesoscale convergence along the terrain, and 2) clouds encountering updraft-suppressing pressure gradient forces while interacting with vertical wind shear in the free troposphere. Among the ensemble of thermals occurring in each simulation, the widest deep updrafts in each simulation were the most sensitive to environmental influences.

    more » « less
  3. null (Ed.)
    Abstract A detailed microphysical model of hail growth is developed and applied to idealized numerical simulations of deep convective storms. Hailstone embryos of various sizes and densities may be initialized in and around the simulated convective storm updraft, and then are tracked as they are advected and grow through various microphysical processes. Application to an idealized squall line and supercell storm results in a plausibly realistic distribution of maximum hailstone sizes for each. Simulated hail growth trajectories through idealized supercell storms exhibit many consistencies with previous hail trajectory work that used observed storms. Systematic tests of uncertain model parameters and parameterizations are performed, with results highlighting the sensitivity of hail size distributions to these changes. A set of idealized simulations is performed for supercells in environments with varying vertical wind shear to extend and clarify our prior work. The trajectory calculations reveal that, with increased zonal deep-layer shear, broader updrafts lead to increased residence time and thus larger maximum hail sizes. For cases with increased meridional low-level shear, updraft width is also increased, but hailstone sizes are smaller. This is a result of decreased residence time in the updraft, owing to faster northward flow within the updraft that advects hailstones through the growth region more rapidly. The results suggest that environments leading to weakened horizontal flow within supercell updrafts may lead to larger maximum hailstone sizes. 
    more » « less
  4. Abstract

    Lasting updrafts are necessary to produce severe hail; conventional wisdom suggests that extremely large hailstones require updrafts of commensurate strength. Because updraft strength is largely controlled by convective available potential energy (CAPE), one would expect environments with larger CAPE to be conducive to storms producing larger hail. By systematically varying CAPE in a horizontally homogeneous initial environment, we simulate hail production in high-shear, high-instability supercell storms using Cloud Model 1 and a detailed 3D hail growth trajectory model. Our results suggest that CAPE modulates the updraft’s strength, width, and horizontal wind field, as well as the liquid water content along hailstones’ trajectories, all of which have a significant impact on final hail sizes. In particular, hail sizes are maximized for intermediate CAPE values in the range we examined. Results show a non-monotonic relationship between the hailstones’ residence time and CAPE due to changes to the updraft wind field. The ratio of updraft area to southerly wind speed within the updraft serves as a proxy for residence time. Storms in environments with large CAPE may produce smaller hail because the in-updraft horizontal wind speeds become too great, and hailstones are prematurely ejected out of the optimal growth region. Liquid water content (LWC) along favorable hailstone pathways also exhibits peak values for intermediate CAPE values, owing to the horizontal displacement across the midlevel updraft of moist inflow air from differing source levels. In other words, larger CAPE does not equal larger hail, and storm-structural nuances must be examined.

    more » « less
  5. Abstract

    Supercell thunderstorms develop low-level rotation via tilting of environmental horizontal vorticity (ωh) by the updraft. This rotation induces dynamic lifting that can stretch near-surface vertical vorticity into a tornado. Low-level updraft rotation is generally thought to scale with 0–500 m storm-relative helicity (SRH): the combination of storm-relative flow, |SRF|, |ωh|, and cosϕ(whereϕis the angle betweenSRFandωh). It is unclear how much influence each component of SRH has in intensifying the low-level mesocyclone. This study surveys these three components using self-organizing maps (SOMs) to distill 15 906 proximity soundings for observed right-moving supercells. Statistical analyses reveal the component most highly correlated to SRH and to streamwise vorticity (ωs) in the observed profiles is |ωh|. Furthermore, |ωh| and |SRF| are themselves highly correlated due to their shared dependence on the hodograph length. The representative profiles produced by the SOMs were combined with a common thermodynamic profile to initialize quasi-realistic supercells in a cloud model. The simulations reveal that, across a range of real-world profiles, intense low-level mesocyclones are most closely linked toωhandSRF, while the angle between them appears to be mostly inconsequential.

    Significance Statement

    About three-fourths of all tornadoes are produced by rotating thunderstorms (supercells). When the part of the storm near cloud base (approximately 1 km above the ground) rotates more strongly, the chance of a tornado dramatically increases. The goal of this study is to identify the simplest characteristic(s) of the environmental wind profile that can be used to forecast the likelihood of strong cloud-base rotation. This study concludes that the most important ingredients for storm rotation are the magnitudes of the horizontal vertical wind shear between the surface and 500 m and the storm inflow wind, irrespective of their relative directions. This finding may lead to improved operational identification of environments favoring tornado formation.

    more » « less