An official website of the United States government
Abstract The intensity of deep convective storms is driven in part by the strength of their updrafts and cold pools. In spite of the importance of these storm features, they can be poorly represented within numerical models. This has been attributed to model parameterizations, grid resolution, and the lack of appropriate observations with which to evaluate such simulations. The overarching goal of the Colorado State University Convective CLoud Outflows and UpDrafts Experiment (C 3 LOUD-Ex) was to enhance our understanding of deep convective storm processes and their representation within numerical models. To address this goal, a field campaign was conducted during July 2016 and May–June 2017 over northeastern Colorado, southeastern Wyoming, and southwestern Nebraska. Pivotal to the experiment was a novel “Flying Curtain” strategy designed around simultaneously employing a fleet of uncrewed aerial systems (UAS; or drones), high-frequency radiosonde launches, and surface observations to obtain detailed measurements of the spatial and temporal heterogeneities of cold pools. Updraft velocities were observed using targeted radiosondes and radars. Extensive datasets were successfully collected for 16 cold pool–focused and seven updraft-focused case studies. The updraft characteristics for all seven supercell updraft cases are compared and provide a useful database for model evaluation. An overview of the 16 cold pools’ characteristics is presented, and an in-depth analysis of one of the cold pool cases suggests that spatial variations in cold pool properties occur on spatial scales from O (100) m through to O (1) km. Processes responsible for the cold pool observations are explored and support recent high-resolution modeling results.
more »
« less
Updraft Vertical Velocity Observations and Uncertainties in High Plains Supercells Using Radiosondes and Radars
Abstract Observations of the air vertical velocities ( w air ) in supercell updrafts are presented, including uncertainty estimates, from radiosonde GPS measurements in two supercells. These in situ observations were collected during the Colorado State University Convective Cloud Outflows and Updrafts Experiment (C 3 LOUD-Ex) in moderately unstable environments in Colorado and Wyoming. Based on the radiosonde accelerations, instances when the radiosonde balloon likely bursts within the updraft are determined, and adjustments are made to account for the subsequent reduction in radiosonde buoyancy. Before and after these adjustments, the maximum estimated w air values are 36.2 and 49.9 m s −1 , respectively. Radar data are used to contextualize the in situ observations and suggest that most of the radiosonde observations were located several kilometers away from the most intense vertical motions. Therefore, the radiosonde-based w air values presented likely underestimate the maximum values within these storms due to these sampling biases, as well as the impacts from hydrometeors, which are not accounted for. When possible, radiosonde-based w air values were compared to estimates from dual-Doppler methods and from parcel theory. When the radiosondes observed their highest w air values, dual-Doppler methods generally produced 15–20 m s −1 lower w air for the same location, which could be related to the differences in the observing systems’ resolutions. In situ observations within supercell updrafts, which have been limited in recent decades, can be used to improve our understanding and modeling of storm dynamics. This study provides new in situ observations, as well as methods and lessons that could be applied to future field campaigns.
more »
« less
- Award ID(s):
- 2019947
- PAR ID:
- 10302961
- Date Published:
- Journal Name:
- Monthly Weather Review
- Volume:
- 148
- Issue:
- 11
- ISSN:
- 0027-0644
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Abstract The quantification of storm updrafts remains unavailable for operational forecasting despite their inherent importance to convection and its associated severe weather hazards. Updraft proxies, like overshooting top area from satellite images, have been linked to severe weather hazards but only relate to a limited portion of the total storm updraft. This study investigates if a machine learning model, namely, U-Nets, can skillfully retrieve maximum vertical velocity and its areal extent from three-dimensional gridded radar reflectivity alone. The machine learning model is trained using simulated radar reflectivity and vertical velocity from the National Severe Storm Laboratory’s convection permitting Warn-on-Forecast System (WoFS). A parametric regression technique using the sinh–arcsinh–normal distribution is adapted to run with U-Nets, allowing for both deterministic and probabilistic predictions of maximum vertical velocity. The best models after hyperparameter search provided less than 50% root mean squared error, a coefficient of determination greater than 0.65, and an intersection over union (IoU) of more than 0.45 on the independent test set composed of WoFS data. Beyond the WoFS analysis, a case study was conducted using real radar data and corresponding dual-Doppler analyses of vertical velocity within a supercell. The U-Net consistently underestimates the dual-Doppler updraft speed estimates by 50%. Meanwhile, the area of the 5 and 10 m s−1updraft cores shows an IoU of 0.25. While the above statistics are not exceptional, the machine learning model enables quick distillation of 3D radar data that is related to the maximum vertical velocity, which could be useful in assessing a storm’s severe potential. Significance StatementAll convective storm hazards (tornadoes, hail, heavy rain, straight line winds) can be related to a storm’s updraft. Yet, there is no direct measurement of updraft speed or area available for forecasters to make their warning decisions from. This paper addresses the lack of observational data by providing a machine learning solution that skillfully estimates the maximum updraft speed within storms from only the radar reflectivity 3D structure. After further vetting the machine learning solutions on additional real-world examples, the estimated storm updrafts will hopefully provide forecasters with an added tool to help diagnose a storm’s hazard potential more accurately.more » « less
-
null (Ed.)Abstract Observation system simulation experiments are used to evaluate different dual-Doppler analysis (DDA) methods for retrieving vertical velocity w at grid spacings on the order of 100 m within a simulated tornadic supercell. Variational approaches with and without a vertical vorticity equation constraint are tested, along with a typical (traditional) method involving vertical integration of the mass conservation equation. The analyses employ emulated radar data from dual-Doppler placements 15, 30, and 45 km east of the mesocyclone, with volume scan intervals ranging from 10 to 150 s. The effect of near-surface data loss is examined by denying observations below 1 km in some of the analyses. At the longer radar ranges and when no data denial is imposed, the “traditional” method produces results similar to those of the variational method and is much less expensive to implement. However, at close range and/or with data denial, the variational method is much more accurate, confirming results from previous studies. The vorticity constraint shows the potential to improve the variational analysis substantially, reducing errors in the w retrieval by up to 30% for rapid-scan observations (≤30 s) at close range when the local vorticity tendency is estimated using spatially variable advection correction. However, the vorticity constraint also degrades the analysis for longer scan intervals, and the impact diminishes with increased range. Furthermore, analyses using 30-s data also frequently outperform analyses using 10-s data, suggesting a limit to the benefit of increasing the radar scan rate for variational DDA employing the vorticity constraint.more » « less
-
Abstract On 10 November 2018, during the RELAMPAGO field campaign in Argentina, South America, a thunderstorm with supercell characteristics was observed by an array of mobile observing instruments, including three Doppler on Wheels radars. In contrast to the archetypal supercell described in the Glossary of Meteorology, the updraft rotation in this storm was rather short lived (~25 min), causing some initial doubt as to whether this indeed was a supercell. However, retrieved 3D winds from dual-Doppler radar scans were used to document a high spatial correspondence between midlevel vertical velocity and vertical vorticity in this storm, thus providing evidence to support the supercell categorization. Additional data collected within the RELAMPAGO domain revealed other storms with this behavior, which appears to be attributable in part to effects of the local terrain. Specifically, the IOP4 supercell and other short-duration supercell cases presented had storm motions that were nearly perpendicular to the long axis of the Sierras de Córdoba Mountains; a long-duration supercell case, on the other hand, had a storm motion nearly parallel to these mountains. Sounding observations as well as model simulations indicate that a mountain-perpendicular storm motion results in a relatively short storm residence time within the narrow zone of terrain-enhanced vertical wind shear. Such a motion and short residence time would limit the upward tilting, by the left-moving supercell updraft, of the storm-relative, antistreamwise horizontal vorticity associated with anabatic flow near complex terrain.more » « less
-
Abstract Observed supercell updrafts consistently produce the fastest mid- to upper-tropospheric vertical velocities among all modes of convection. Two hypotheses for this feature are investigated. In the dynamic hypothesis, upward, largely rotationally driven pressure gradient accelerations enhance supercell updrafts relative to other forms of convection. In the thermodynamic hypothesis, supercell updrafts have more low-level inflow than ordinary updrafts because of the large vertical wind shear in supercell environments. This large inflow makes supercell updrafts wider than that of ordinary convection and less susceptible to the deleterious effects of entrainment-driven updraft core dilution on buoyancy. These hypotheses are tested using a large suite of idealized supercell simulations, wherein vertical shear, CAPE, and moisture are systematically varied. Consistent with the thermodynamic hypothesis, storms with the largest storm-relative flow have larger inflow, are wider, have larger buoyancy, and have faster updrafts. Analyses of the vertical momentum forcing along trajectories shows that maximum vertical velocities are often enhanced by dynamic pressure accelerations, but this enhancement is accompanied by larger downward buoyant pressure accelerations than in ordinary convection. Integrated buoyancy along parcel paths is therefore a strong constraint on maximum updraft speeds. Thus, through a combination of processes consistent with the dynamic and thermodynamic hypotheses, supercell updrafts are able to realize a larger percentage of CAPE than ordinary updrafts.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1175/MWR-D-20-0071.1
