scholarly journals Differences between Severe and Nonsevere Warm-Season, Nocturnal Bow Echo Environments

2021 ◽  
Vol 36 (1) ◽  
pp. 53-74
Author(s):  
Ezio L. Mauri ◽  
William A. Gallus Jr.
Keyword(s):  
Convective Available Potential Energy ◽  
Warm Season ◽  
Wind Damage ◽  
Wind Component ◽  
Predictive Skill ◽  
Shear Component ◽  
Wind Potential ◽  
Bow Echo ◽  
Composite Parameter ◽  
Two Parameters

AbstractNocturnal bow echoes can produce wind damage, even in situations where elevated convection occurs. Accurate forecasts of wind potential tend to be more challenging for operational forecasters than for daytime bows because of incomplete understanding of how elevated convection interacts with the stable boundary layer. The present study compares the differences in warm-season, nocturnal bow echo environments in which high intensity [>70 kt (1 kt ≈ 0.51 m s−1)] severe winds (HS), low intensity (50–55 kt) severe winds (LS), and nonsevere winds (NS) occurred. Using a sample of 132 events from 2010 to 2018, 43 forecast parameters from the SPC mesoanalysis system were examined over a 120 km × 120 km region centered on the strongest storm report or most pronounced bowing convective segment. Severe composite parameters are found to be among the best discriminators between all severity types, especially derecho composite parameter (DCP) and significant tornado parameter (STP). Shear parameters are significant discriminators only between severe and nonsevere cases, while convective available potential energy (CAPE) parameters are significant discriminators only between HS and LS/NS bow echoes. Convective inhibition (CIN) is among the worst discriminators for all severity types. The parameters providing the most predictive skill for HS bow echoes are STP and most unstable CAPE, and for LS bow echoes these are the V wind component at best CAPE (VMXP) level, STP, and the supercell composite parameter. Combinations of two parameters are shown to improve forecasting skill further, with the combination of surface-based CAPE and 0–6-km U shear component, and DCP and VMXP, providing the most skillful HS and LS forecasts, respectively.

scholarly journals The 2015 Plains Elevated Convection at Night Field Project

2017 ◽  
Vol 98 (4) ◽  
pp. 767-786 ◽  
Author(s):  
Bart Geerts ◽  
David Parsons ◽  
Conrad L. Ziegler ◽  
Tammy M. Weckwerth ◽  
Michael I. Biggerstaff ◽  
...  
Keyword(s):  
Great Plains ◽  
Climate Models ◽  
Convective Available Potential Energy ◽  
Warm Season ◽  
Lower Troposphere ◽  
Convective Systems ◽  
Predictive Skill ◽  
Mesoscale Convective ◽  
The Rich ◽  
Convection Initiation

Abstract The central Great Plains region in North America has a nocturnal maximum in warm-season precipitation. Much of this precipitation comes from organized mesoscale convective systems (MCSs). This nocturnal maximum is counterintuitive in the sense that convective activity over the Great Plains is out of phase with the local generation of CAPE by solar heating of the surface. The lower troposphere in this nocturnal environment is typically characterized by a low-level jet (LLJ) just above a stable boundary layer (SBL), and convective available potential energy (CAPE) values that peak above the SBL, resulting in convection that may be elevated, with source air decoupled from the surface. Nocturnal MCS-induced cold pools often trigger undular bores and solitary waves within the SBL. A full understanding of the nocturnal precipitation maximum remains elusive, although it appears that bore-induced lifting and the LLJ may be instrumental to convection initiation and the maintenance of MCSs at night. To gain insight into nocturnal MCSs, their essential ingredients, and paths toward improving the relatively poor predictive skill of nocturnal convection in weather and climate models, a large, multiagency field campaign called Plains Elevated Convection At Night (PECAN) was conducted in 2015. PECAN employed three research aircraft, an unprecedented coordinated array of nine mobile scanning radars, a fixed S-band radar, a unique mesoscale network of lower-tropospheric profiling systems called the PECAN Integrated Sounding Array (PISA), and numerous mobile-mesonet surface weather stations. The rich PECAN dataset is expected to improve our understanding and prediction of continental nocturnal warm-season precipitation. This article provides a summary of the PECAN field experiment and preliminary findings.

Forecasting the Maintenance of Quasi-Linear Mesoscale Convective Systems

2007 ◽  
Vol 22 (3) ◽  
pp. 556-570 ◽  
Author(s):  
Michael C. Coniglio ◽  
Harold E. Brooks ◽  
Steven J. Weiss ◽  
Stephen F. Corfidi
Keyword(s):  
Convective Available Potential Energy ◽  
Warm Season ◽  
Value Added ◽  
Convective Cloud ◽  
Mesoscale Convective Systems ◽  
Linear Discriminant ◽  
Convective Systems ◽  
Shear Component ◽  
Mesoscale Convective ◽  
Deep Layers

Abstract The problem of forecasting the maintenance of mesoscale convective systems (MCSs) is investigated through an examination of observed proximity soundings. Furthermore, environmental variables that are statistically different between mature and weakening MCSs are input into a logistic regression procedure to develop probabilistic guidance on MCS maintenance, focusing on warm-season quasi-linear systems that persist for several hours. Between the mature and weakening MCSs, shear vector magnitudes over very deep layers are the best discriminators among hundreds of kinematic and thermodynamic variables. An analysis of the shear profiles reveals that the shear component perpendicular to MCS motion (usually parallel to the leading line) accounts for much of this difference in low levels and the shear component parallel to MCS motion accounts for much of this difference in mid- to upper levels. The lapse rates over a significant portion of the convective cloud layer, the convective available potential energy, and the deep-layer mean wind speed are also very good discriminators and collectively provide a high level of discrimination between the mature and dissipation soundings as revealed by linear discriminant analysis. Probabilistic equations developed from these variables used with short-term numerical model output show utility in forecasting the transition of an MCS with a solid line of 50+ dBZ echoes to a more disorganized system with unsteady changes in structure and propagation. This study shows that empirical forecast tools based on environmental relationships still have the potential to provide forecasters with improved information on the qualitative characteristics of MCS structure and longevity. This is especially important since the current and near-term value added by explicit numerical forecasts of convection is still uncertain.

scholarly journals Severe Convective Windstorms in Europe: Climatology, Preconvective Environments, and Convective Mode

2020 ◽  
pp. 1-45
Author(s):  
George P. Pacey ◽  
David M. Schultz ◽  
Luis Garcia-Carreras
Keyword(s):  
Convective Available Potential Energy ◽  
Warm Season ◽  
Cold Season ◽  
Lower Percentage ◽  
Convective Storms ◽  
Bow Echo ◽  
Strong Winds ◽  
Convective Mode

Abstract The frequency of European convective windstorms, environments in which they form, and their convective organizational modes remain largely unknown. A climatology is produced using 10 233 severe convective-wind reports from the European Severe Weather Database between 2009–2018. Severe convective-wind days have increased from 50 days yr–1 in 2009 to 117 days yr–1 in 2018, largely because of an increase in reporting. The highest frequency of reports occurred across central Europe, particularly Poland. Reporting was most frequent in summer, when a severe convective windstorm occurred every other day on average. The preconvective environment was assessed using 361 proximity soundings from 45 stations between 2006–2018, and a clustering technique was used to distinguish different environments from nine variables. Two environments for severe convective storms occurred: Type 1, generally low-shear–high-CAPE (mostly in the warm season) and Type 2, generally high-shear–low-CAPE (convective available potential energy; mostly in the cold season). Because convective mode often relates to the type of weather hazard, convective organizational mode was studied from 185 windstorms that occurred between 2013–2018. In Type-1 environments, the most frequent convective mode was cells, accounting for 58.5% of events, followed by linear modes (29%) and the nonlinear noncellular mode (12.5%). In Type-2 environments, the most frequent convective mode was linear modes (55%), followed by cells (36%) and the nonlinear noncellular mode (9%). Only 10% of windstorms were associated with bow echoes, a much lower percentage than other studies, suggesting that forecasters should not necessarily wait to see a bow echo before issuing a warning for strong winds.

NAM Model Forecasts of Warm-Season Quasi-Stationary Frontal Environments in the Central United States

2010 ◽  
Vol 25 (4) ◽  
pp. 1281-1292 ◽  
Author(s):  
Shih-Yu Wang ◽  
Adam J. Clark
Keyword(s):  
United States ◽  
Mesoscale Model ◽  
Convective Available Potential Energy ◽  
Warm Season ◽  
Correlation Coefficients ◽  
Precipitable Water ◽  
Wind Fields ◽  
Vapor Flux ◽  
Convective Systems ◽  
Central United States

Abstract Using a composite procedure, North American Mesoscale Model (NAM) forecast and observed environments associated with zonally oriented, quasi-stationary surface fronts for 64 cases during July–August 2006–08 were examined for a large region encompassing the central United States. NAM adequately simulated the general synoptic features associated with the frontal environments (e.g., patterns in the low-level wind fields) as well as the positions of the fronts. However, kinematic fields important to frontogenesis such as horizontal deformation and convergence were overpredicted. Surface-based convective available potential energy (CAPE) and precipitable water were also overpredicted, which was likely related to the overprediction of the kinematic fields through convergence of water vapor flux. In addition, a spurious coherence between forecast deformation and precipitation was found using spatial correlation coefficients. Composite precipitation forecasts featured a broad area of rainfall stretched parallel to the composite front, whereas the composite observed precipitation covered a smaller area and had a WNW–ESE orientation relative to the front, consistent with mesoscale convective systems (MCSs) propagating at a slight right angle relative to the thermal gradient. Thus, deficiencies in the NAM precipitation forecasts may at least partially result from the inability to depict MCSs properly. It was observed that errors in the precipitation forecasts appeared to lag those of the kinematic fields, and so it seems likely that deficiencies in the precipitation forecasts are related to the overprediction of the kinematic fields such as deformation. However, no attempts were made to establish whether the overpredicted kinematic fields actually contributed to the errors in the precipitation forecasts or whether the overpredicted kinematic fields were simply an artifact of the precipitation errors. Regardless of the relationship between such errors, recognition of typical warm-season environments associated with these errors should be useful to operational forecasters.

scholarly journals North American Supercell Environments in Atmospheric Reanalyses and RUC-2

2019 ◽  
Vol 58 (1) ◽  
pp. 71-92 ◽  
Author(s):  
Austin T. King ◽  
Aaron D. Kennedy
Keyword(s):  
North American ◽  
Grid Point ◽  
Convective Available Potential Energy ◽  
Kinematic Parameters ◽  
The North ◽  
Composite Parameter ◽  
Analysis Package ◽  
North American Regional Reanalysis ◽  
Regional Reanalysis ◽  
Effective Layer

AbstractA suite of modern atmospheric reanalyses is analyzed to determine how they represent North American supercell environments. This analysis is performed by comparing a database of Rapid Update Cycle (RUC-2) proximity soundings with profiles derived from the nearest grid point in each reanalysis. Parameters are calculated using the Sounding and Hodograph Analysis and Research Program in Python (SHARPpy), an open-source Python sounding-analysis package. Representation of supercell environments varies across the reanalyses, and the results have ramifications for climatological studies that use these datasets. In particular, thermodynamic parameters such as the convective available potential energy (CAPE) show the widest range in biases, with reanalyses falling into two camps. The North American Regional Reanalysis (NARR) and the Japanese 55-year Reanalysis (JRA-55) are similar to RUC-2, but other reanalyses have a substantial negative bias. The reasons for these biases vary and range from thermodynamic biases at the surface to evidence of convective contamination. Overall, it is found that thermodynamic biases feed back to other convective parameters that incorporate CAPE directly or indirectly via the effective layer. As a result, significant negative biases are found for indices such as the supercell composite parameter. These biases are smallest for NARR and JRA-55. Kinematic parameters are more consistent across the reanalyses. Given the issues with thermodynamic properties, better segregation of soundings by storm type is found for fixed-layer parameters than for effective-layer shear parameters. Although no reanalysis can exactly reproduce the results of earlier RUC-2 studies, many of the reanalyses can broadly distinguish between environments that are significantly tornadic versus nontornadic.

Bow Echo Sensitivity to Ambient Moisture and Cold Pool Strength

2006 ◽  
Vol 134 (3) ◽  
pp. 950-964 ◽  
Author(s):  
Richard P. James ◽  
Paul M. Markowski ◽  
J. Michael Fritsch
Keyword(s):  
Convective Available Potential Energy ◽  
Three Dimensional ◽  
Cold Pool ◽  
Convective System ◽  
Cold Air ◽  
Convective Systems ◽  
Cold Pools ◽  
Bow Echo ◽  
Dry Conditions ◽  
Water Vapor Mixing Ratio

Abstract Bow echo development within quasi-linear convective systems is investigated using a storm-scale numerical model. A strong sensitivity to the ambient water vapor mixing ratio is demonstrated. Relatively dry conditions at low and midlevels favor intense cold-air production and strong cold pool development, leading to upshear-tilted, “slab-like” convection for various magnitudes of convective available potential energy (CAPE) and low-level shear. High relative humidity in the environment tends to reduce the rate of production of cold air, leading to weak cold pools and downshear-tilted convective systems, with primarily cell-scale three-dimensionality in the convective region. At intermediate moisture contents, long-lived, coherent bowing segments are generated within the convective line. In general, the scale of the coherent three-dimensional structures increases with increasing cold pool strength. The bowing lines are characterized in their developing and mature stages by segments of the convective line measuring 15–40 km in length over which the cold pool is much stronger than at other locations along the line. The growth of bow echo structures within a linear convective system appears to depend critically on the local strengthening of the cold pool to the extent that the convection becomes locally upshear tilted. A positive feedback process is thereby initiated, allowing the intensification of the bow echo. If the environment favors an excessively strong cold pool, however, the entire line becomes uniformly upshear tilted relatively quickly, and the along-line heterogeneity of the bowing line is lost.

scholarly journals Bivariate Gaussian models for wind vectors in a distributional regression framework

2019 ◽  
Vol 5 (2) ◽  
pp. 115-132 ◽  
Author(s):  
Moritz N. Lang ◽  
Georg J. Mayr ◽  
Reto Stauffer ◽  
Achim Zeileis
Keyword(s):  
Wind Direction ◽  
Wind Component ◽  
Smooth Functions ◽  
Ensemble Forecasts ◽  
Alpine Valley ◽  
Explanatory Variables ◽  
Predictive Skill ◽  
Regression Framework ◽  
Distribution Parameters ◽  
Distributional Regression

Abstract. A new probabilistic post-processing method for wind vectors is presented in a distributional regression framework employing the bivariate Gaussian distribution. In contrast to previous studies, all parameters of the distribution are simultaneously modeled, namely the location and scale parameters for both wind components and also the correlation coefficient between them employing flexible regression splines. To capture a possible mismatch between the predicted and observed wind direction, ensemble forecasts of both wind components are included using flexible two-dimensional smooth functions. This encompasses a smooth rotation of the wind direction conditional on the season and the forecasted ensemble wind direction. The performance of the new method is tested for stations located in plains, in mountain foreland, and within an alpine valley, employing ECMWF ensemble forecasts as explanatory variables for all distribution parameters. The rotation-allowing model shows distinct improvements in terms of predictive skill for all sites compared to a baseline model that post-processes each wind component separately. Moreover, different correlation specifications are tested, and small improvements compared to the model setup with no estimated correlation could be found for stations located in alpine valleys.

scholarly journals The College Park, Maryland Tornado of 24 September 2001

2019 ◽  
Author(s):  
Kenneth Pryor ◽  
Tyler Wawrzyniak ◽  
Da-Lin Zhang
Keyword(s):  
Convective Available Potential Energy ◽  
Vertical Shear ◽  
Operational Environment ◽  
South Central ◽  
Bow Echo ◽  
Close Range ◽  
Upper Level ◽  
College Park ◽  
Forcing Mechanisms ◽  
Cloud Tops

The 24 September 2001 College Park, Maryland, tornado was a long track and strong tornado that passed within a close range of two Doppler radars. It was the third in a series of three tornadoes associated with a supercell storm that developed in Stafford County, Virginia, and initiated 3 - 4 km southwest of College Park and dissipated near Columbia, Howard County. The supercell tracked approximately 120 km and lasted for about 126 minutes. This study presents a synoptic and mesoscale overview of favorable conditions and forcing mechanisms that resulted in the severe convective outbreak associated with the College Park tornado. Results show many critical elements of the tornadic event, including a negative-tilted upper-level trough over the Ohio Valley, a jet stream with moderate vertical shear, a warm, moist tongue of the air associated with strong southerly flow over south-central Maryland and Virginia, and significantly increased convective available potential energy during the late afternoon hours. Satellite imagery reveals banded convective morphology with high cloud tops associated with the supercell that produced the College Park tornado. Operational WSR-88D data exhibits a high reflectivity “debris ball” or tornadic debris signature (TDS) within the hook echo, the evolution of the parent storm from a supercell structure to a bow echo, and a tornado cyclone signature (TCS). Many of the mesoscale environmental features could be captured by contemporary numerical model analyses. This study concludes with a discussion of the effectiveness of the coordinated use of satellite and radar observations in the operational environment of nowcasting severe convection.

scholarly journals The College Park, Maryland Tornado of 24 September 2001

2019 ◽  
Author(s):  
Kenneth Pryor ◽  
Tyler Wawrzyniak ◽  
Da-Lin Zhang
Keyword(s):  
Convective Available Potential Energy ◽  
Vertical Shear ◽  
Washington Dc ◽  
Operational Environment ◽  
South Central ◽  
Bow Echo ◽  
Upper Level ◽  
College Park ◽  
Forcing Mechanisms ◽  
Cloud Tops

The 24 September 2001 College Park, Maryland, tornado was a long-track and strong tornado that passed within a close range of two Doppler radars. It was the third in a series of three tornadoes associated with a supercell storm that developed in Stafford County, Virginia, and initiated 3 - 4 km southwest of College Park and dissipated near Columbia, Howard County. The supercell tracked approximately 120 km and lasted for about 126 minutes. This study presents a synoptic and mesoscale overview of favorable conditions and forcing mechanisms that resulted in the severe convective outbreak associated with the College Park tornado. Results show many critical elements of the tornadic event, including a negative-tilted upper-level trough over the Ohio Valley, a jet stream with moderate vertical shear, a low-level warm, moist tongue of the air associated with strong southerly flow over south-central Maryland and Virginia, and significantly increased convective available potential energy (CAPE) during the late afternoon hours. A possible role of the urban heat island effects from Washington, DC in increasing CAPE for the development of the supercell is discussed. Satellite imagery reveals banded convective morphology with high cloud tops associated with the supercell that produced the College Park tornado. Operational WSR-88D data exhibits a high reflectivity “debris ball” or tornadic debris signature (TDS) within the hook echo, the evolution of the parent storm from a supercell structure to a bow echo, and a tornado cyclone signature (TCS). Many of the mesoscale features could be captured by contemporary numerical model analyses. This study concludes with a discussion of the effectiveness of the coordinated use of satellite and radar observations in the operational environment of nowcasting severe convection.

scholarly journals Entraining CAPE for Better Assessment of Tornado Outbreak Potential in the Warm Sector of Extratropical Cyclones

2019 ◽  
Vol 147 (3) ◽  
pp. 913-930 ◽  
Author(s):  
Eigo Tochimoto ◽  
Kenta Sueki ◽  
Hiroshi Niino
Keyword(s):  
Convective Available Potential Energy ◽  
The United States ◽  
Extratropical Cyclones ◽  
Strongly Correlated ◽  
Composite Analysis ◽  
Synoptic Scale ◽  
Warm Sector ◽  
Composite Parameter ◽  
Environmental Air ◽  
Tornado Outbreaks

Abstract Convective available potential energy (CAPE) is known to lack skill in discussing the environments of tornadic and nontornadic storms, or those of tornado outbreaks and nonoutbreaks. In this paper, a composite analysis of extratropical cyclones that caused 15 or more tornadoes [outbreak cyclones (OCs)] and 5 or fewer tornadoes [nonoutbreak cyclones (NOCs)] in the United States in April and May between 1995 and 2012 shows that entraining-CAPE (E-CAPE), which considers the effects of the entrainment of environmental air, is useful in the analysis of the environments of OCs and NOCs. E-CAPE in the warm sector of OCs is larger than that in the warm sector of NOCs (statistically significant at the 95%–99% level). Moreover, the regions with large E-CAPE for both OCs and NOCs are more closely correlated with the locations of tornadoes than those with large CAPE. The larger E-CAPE near the center in the warm sector of OCs is due to greater moisture at low and midlevels that results from advection by strong southerly winds and synoptic-scale ascent, respectively. The composite analysis also shows that E-EHI, E-SCP, and E-STP, for which traditional CAPE used in the energy helicity index (EHI), supercell composite parameter (SCP), and significant tornado parameter (STP) is substituted by E-CAPE, are more strongly correlated with tornado locations than are the original EHI, SCP, and STP, respectively.

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