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Dive into the research topics where Ariel E. Cohen is active.

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Featured researches published by Ariel E. Cohen.


Weather and Forecasting | 2007

Discrimination of Mesoscale Convective System Environments Using Sounding Observations

Ariel E. Cohen; Michael C. Coniglio; Stephen F. Corfidi; Sarah J. Corfidi

Abstract The prediction of the strength of mesoscale convective systems (MCSs) is a major concern to operational meteorologists and the public. To address this forecast problem, this study examines meteorological variables derived from sounding observations taken in the environment of quasi-linear MCSs. A set of 186 soundings that sampled the beginning and mature stages of the MCSs are categorized by their production of severe surface winds into weak, severe, and derecho-producing MCSs. Differences in the variables among these three MCS categories are identified and discussed. Mean low- to upper-level wind speeds and deep-layer vertical wind shear, especially the component perpendicular to the convective line, are excellent discriminators among all three categories. Low-level inflow relative to the system is found to be an excellent discriminator, largely because of the strong relationship of system severity to system speed. Examination of the mean wind and shear vectors relative to MCS motion suggests th...


Weather and Forecasting | 2015

A Review of Planetary Boundary Layer Parameterization Schemes and Their Sensitivity in Simulating Southeastern U.S. Cold Season Severe Weather Environments

Ariel E. Cohen; Steven M. Cavallo; Michael C. Coniglio; Harold E. Brooks

AbstractThe representation of turbulent mixing within the lower troposphere is needed to accurately portray the vertical thermodynamic and kinematic profiles of the atmosphere in mesoscale model forecasts. For mesoscale models, turbulence is mostly a subgrid-scale process, but its presence in the planetary boundary layer (PBL) can directly modulate a simulation’s depiction of mass fields relevant for forecast problems. The primary goal of this work is to review the various parameterization schemes that the Weather Research and Forecasting Model employs in its depiction of turbulent mixing (PBL schemes) in general, and is followed by an application to a severe weather environment. Each scheme represents mixing on a local and/or nonlocal basis. Local schemes only consider immediately adjacent vertical levels in the model, whereas nonlocal schemes can consider a deeper layer covering multiple levels in representing the effects of vertical mixing through the PBL. As an application, a pair of cold season sever...


Bulletin of the American Meteorological Society | 2016

A Proposed Revision to the Definition of “Derecho”

Stephen F. Corfidi; Michael C. Coniglio; Ariel E. Cohen; Corey M. Mead

AbstractThe word “derecho” was first used by Gustavus Hinrichs in 1888 to distinguish the widespread damaging windstorms that occurred on occasion over the mid–Mississippi Valley region of the United States from damaging winds associated with tornadoes. The term soon fell into disuse, however, and did not appear in the literature until Robert Johns and William Hirt resurrected it in the mid-1980s.While the present definition of derecho served well during the early years of the term’s reintroduction to the meteorological community, it has several shortcomings. These have become more apparent in recent years as various studies shed light on the physical processes responsible for the production of widespread damaging winds. In particular, the current definition’s emphasis on the coverage of storm reports at the expense of identifying the convective structures and physical processes deemed responsible for the reports has led to the term being applied to wind events beyond those for which it originally was int...


Weather and Forecasting | 2014

Environments of Northeast U.S. Severe Thunderstorm Events from 1999 to 2009

Melissa M. Hurlbut; Ariel E. Cohen

AbstractAn investigation of the environments and climatology of severe thunderstorms from 1999 through 2009 across the northeastern United States is presented. A total of 742 severe weather events producing over 12 000 reports were examined. Given the challenges that severe weather forecasting can present in the Northeast, this study is an effort to distinguish between the more prolific severe-weather-producing events and those that produce only isolated severe weather. The meteorological summer months (June–August) are found to coincide with the peak severe season. During this time, 850–500- and 700–500-hPa lapse rates, mixed layer convective inhibition (MLCIN), and downdraft convective available potential energy (DCAPE) are found to be statistically significant in discriminating events with a large number of reports from those producing fewer reports, based on observed soundings. Composite synoptic pattern analyses are also presented to spatially characterize the distribution of key meteorological varia...


Weather and Forecasting | 2017

Structure and Motion of Severe-Wind-Producing Mesoscale Convective Systems and Derechos in Relation to the Mean Wind

Matthew A. Campbell; Ariel E. Cohen; Michael C. Coniglio; Andrew R. Dean; Stephen F. Corfidi; Sarah J. Corfidi; Corey M. Mead

AbstractThe goal of this study is to document differences in the convective structure and motion of long-track, severe-wind-producing MCSs from short-track severe-wind-producing MCSs in relation to the mean wind. An ancillary goal is to determine if these differences are large enough that some criterion for MCS motion relative to the mean wind could be used in future definitions of “derechos.” Results confirm past investigations that well-organized MCSs, including those that produce derechos, tend to move faster than the mean wind, exhibiting a significantly larger degree of propagation (component of MCS motion in addition to the component contributed by the mean flow). Furthermore, well-organized systems that produce shorter-track swaths of damaging winds likewise tend to move faster than the mean wind with a significant propagation component along the mean wind. Therefore, propagation in the direction of the mean wind is not necessarily a characteristic that can be used to distinguish derechos from nond...


Weather and Forecasting | 2016

The Challenge of Forecasting Significant Tornadoes from June to October Using Convective Parameters

John A. Hart; Ariel E. Cohen

AbstractThis study is an application of the Statistical Severe Convective Risk Assessment Model (SSCRAM), which objectively assesses conditional severe thunderstorm probabilities based on archived hourly mesoscale data across the United States collected from 2006 to 2014. In the present study, SSCRAM is used to assess the utility of severe thunderstorm parameters commonly employed by forecasters in anticipating thunderstorms that produce significant tornadoes (i.e., causing F2/EF2 or greater damage) from June through October. The utility during June–October is compared to that during other months. Previous studies have identified some aspects of the summertime challenge in severe storm forecasting, and this study provides an in-depth quantification of the within-year variability of severe storms predictability. Conditional probabilities of significant tornadoes downstream of lightning occurrence using common parameter values, such as the effective-layer significant tornado parameter, convective available ...


Weather and Forecasting | 2017

Synoptic and Mesoscale Environment of Convection during the North American Monsoon across Central and Southern Arizona

Lee B. Carlaw; Ariel E. Cohen; Jaret W. Rogers

AbstractThis paper comprehensively analyzes the synoptic and mesoscale environment associated with North American monsoon–related thunderstorms affecting central and southern Arizona. Analyses of thunderstorm environments are presented using reanalysis data, severe thunderstorm reports, and cloud-to-ground lightning information from 2003 to 2013, which serves as a springboard for lightning-prediction models provided in a companion paper. Spatial and temporal analyses of lightning strikes indicate thunderstorm frequencies maximize between 2100 and 0000 UTC, when the greatest frequencies are concentrated over higher terrain. Severe thunderstorm reports typically occur later in the day (between 2300 and 0100 UTC), while reports are maximized in the Tucson and Phoenix metropolitan areas. Composite analyses of the synoptic-scale patterns associated with severe thunderstorm days and nonthunderstorm days during the summer using the North American Regional Reanalysis dataset are presented. Severe thunderstorm cas...


Weather and Forecasting | 2017

Convection during the North American Monsoon across Central and Southern Arizona: Applications to Operational Meteorology

Jaret W. Rogers; Ariel E. Cohen; Lee B. Carlaw

AbstractThis comprehensive analysis of convective environments associated with thunderstorms affecting portions of central and southern Arizona during the North American monsoon focuses on both observed soundings and mesoanalysis parameters relative to lightning flash counts and severe-thunderstorm reports. Analysis of observed sounding data from Phoenix and Tucson, Arizona, highlights several moisture and instability parameters exhibiting moderate correlations with 24-h, domain-total lightning and severe thunderstorm counts, with accompanying plots of the precipitable water, surface-based lifted index, and 0–3-km layer mixing ratio highlighting the relationship to the domain-total lightning count. Statistical techniques, including stepwise, multiple linear regression and logistic regression, are applied to sounding and gridded mesoanalysis data to predict the domain-total lightning count and individual gridbox 3-h-long lightning probability, respectively. Applications of these forecast models to an indep...


Weather and Forecasting | 2016

The Statistical Severe Convective Risk Assessment Model

John A. Hart; Ariel E. Cohen

AbstractThis study introduces a system that objectively assesses severe thunderstorm nowcast probabilities based on hourly mesoscale data across the contiguous United States during the period from 2006 to 2014. Previous studies have evaluated the diagnostic utility of parameters in characterizing severe thunderstorm environments. In contrast, the present study merges cloud-to-ground lightning flash data with both severe thunderstorm report and Storm Prediction Center Mesoscale Analysis system data to create lightning-conditioned prognostic probabilities for numerous parameters, thus incorporating null-severe cases. The resulting dataset and corresponding probabilities are called the Statistical Severe Convective Risk Assessment Model (SSCRAM), which incorporates a sample size of over 3.8 million 40-km grid boxes. A subset of five parameters of SSCRAM is investigated in the present study. This system shows that severe storm probabilities do not vary strongly across the range of values for buoyancy paramete...


Weather and Forecasting | 2018

Simulating Tornado Probability and Tornado Wind Speed Based on Statistical Models

Ariel E. Cohen; Joel B. Cohen; Richard L. Thompson; Bryan T. Smith

AbstractThis study presents the development and testing of two statistical models that simulate tornado potential and wind speed. This study reports on the first-ever development of two multiple re...

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Michael C. Coniglio

National Oceanic and Atmospheric Administration

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Stephen F. Corfidi

National Oceanic and Atmospheric Administration

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Bryan T. Smith

National Oceanic and Atmospheric Administration

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Jaret W. Rogers

National Oceanic and Atmospheric Administration

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Sarah J. Corfidi

National Oceanic and Atmospheric Administration

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Andrew R. Dean

National Oceanic and Atmospheric Administration

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Harold E. Brooks

National Oceanic and Atmospheric Administration

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John A. Hart

National Oceanic and Atmospheric Administration

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