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D. Muñoz‐Esparza, J. Sauer, R. Linn, B. Kosović (2016)
Limitations of One-Dimensional Mesoscale PBL Parameterizations in Reproducing Mountain-Wave FlowsJournal of the Atmospheric Sciences, 73
R. Sharman, J. Pearson (2017)
Prediction of Energy Dissipation Rates for Aviation Turbulence. Part I: Forecasting Nonconvective TurbulenceJournal of Applied Meteorology and Climatology, 56
Douglas Behne, Douglas Behne (2008)
NAM-WRF Verification of Subtropical Jet and Turbulence
S. Trier, R. Sharman (2016)
Mechanisms Influencing Cirrus Banding and Aviation Turbulence near a Convectively Enhanced Upper-Level Jet StreamMonthly Weather Review, 144
W. Skamarock, J. Klemp (2008)
A time-split nonhydrostatic atmospheric model for weather research and forecasting applicationsJ. Comput. Phys., 227
T. Lane, J. Knievel (2005)
Some Effects of Model Resolution on Simulated Gravity Waves Generated by Deep, Mesoscale Convection.Journal of the Atmospheric Sciences, 62
(2016)
2016: Mechanisms influencing
Katelyn Barber (2015)
Simulations of convectively-induced turbulence based on radar-based climatology of tropical storm types
T. Lane, R. Sharman (2014)
Intensity of thunderstorm‐generated turbulence revealed by large‐eddy simulationGeophysical Research Letters, 41
P. Lester (1993)
Turbulence: A New Perspective for Pilots
C. Stephan, M. Alexander (2014)
Summer Season Squall-Line Simulations: Sensitivity of Gravity Waves to Physics Parameterization and Implications for Their Parameterization in Global Climate ModelsJournal of the Atmospheric Sciences, 71
G. Ellrod, David Knapp (1992)
An Objective Clear-Air Turbulence Forecasting Technique: Verification and Operational UseWeather and Forecasting, 7
John Towns, T. Cockerill, M. Dahan, Ian Foster, K. Gaither, A. Grimshaw, Victor Hazlewood, Scott Lathrop, D. Lifka, G. Peterson, R. Roskies, J. Scott, Nancy Wilkins-Diehr (2014)
XSEDE: Accelerating Scientific DiscoveryComputing in Science & Engineering, 16
Z. Janjic (1994)
The Step-Mountain Eta Coordinate Model: Further Developments of the Convection, Viscous Sublayer, and Turbulence Closure SchemesMonthly Weather Review, 122
George, H., Bryan, John, C., Wyngaard, J., Michael Fritsch (2003)
Resolution Requirements for the Simulation of Deep Moist ConvectionMonthly Weather Review, 131
T. Lane, R. Sharman, T. Clark, H. Hsu (2003)
An Investigation of Turbulence Generation Mechanisms above Deep ConvectionJournal of the Atmospheric Sciences, 60
(1991)
A comparison of several airborne measures of turbulence
J. Doyle, S. Gabersek, Q. Jiang, L. Bernardet, John Brown, A. Dörnbrack, Elmar Filaus, V. Grubišić, D. Kirshbaum, O. Knoth, S. Koch, J. Schmidli, I. Stiperski, S. Vosper, S. Zhong (2008)
An Intercomparison of T-REX Mountain-Wave Simulations and Implications for Mesoscale PredictabilityMonthly Weather Review, 139
J. Wolff, R. Sharman (2008)
Climatology of Upper-Level Turbulence over the Contiguous United StatesJournal of Applied Meteorology and Climatology, 47
R. Sharman, L. Cornman, G. Meymaris, J. Pearson, T. Farrar (2014)
Description and Derived Climatologies of Automated In Situ Eddy-Dissipation-Rate Reports of Atmospheric TurbulenceJournal of Applied Meteorology and Climatology, 53
Jung‐Hoon Kim, H. Chun, R. Sharman, S. Trier (2014)
The Role of Vertical Shear on Aviation Turbulence within Cirrus Bands of a Simulated Western Pacific CycloneMonthly Weather Review, 142
Michael Emanuel (2013)
In Situ Performance Standard for Eddy Dissipation Rate
(1980)
Probability forecasts of clear - air turbulence based on numerical output
(2012)
Estimation of eddy dissi
Jung‐Hoon Kim, H. Chun (2012)
A Numerical Simulation of Convectively Induced Turbulence above Deep ConvectionJournal of Applied Meteorology and Climatology, 51
N. Ahmad, F. Proctor (2012)
Estimation of Eddy Dissipation Rates from Mesoscale Model Simulations
John Williams (2011)
Measuring in-cloud turbulence: the NEXRAD Turbulence Detection Algorithm
John Williams (2012)
RECENT ADVANCES IN THE UNDERSTANDING OF NEAR-CLOUD TURBULENCE
(1973)
New indices to locate clear air turbulence
R. Sharman, C. Tebaldi, G. Wiener, J. Wolff (2006)
An Integrated Approach to Mid- and Upper-Level Turbulence ForecastingWeather and Forecasting, 21
Dragana Zovko-Rajak, T. Lane (2014)
The Generation of Near-Cloud Turbulence in Idealized SimulationsJournal of the Atmospheric Sciences, 71
M. Weisman, C. Davis, Wei Wang, Kevin Manning, J. Klemp (2008)
Experiences with 0–36-h Explicit Convective Forecasts with the WRF-ARW ModelWeather and Forecasting, 23
(2015)
Simulations of convectively-induced turbu
J. Sauer, D. Muñoz‐Esparza, J. Canfield, K. Costigan, R. Linn, Young‐joon Kim (2016)
A Large-Eddy Simulation Study of Atmospheric Boundary Layer Influence on Stratified Flows over TerrainJournal of the Atmospheric Sciences, 73
T. Lane, J. Doyle, R. Sharman, M. Shapiro, C. Watson (2009)
Statistics and Dynamics of Aircraft Encounters of Turbulence over GreenlandMonthly Weather Review, 137
P. Lester (1993)
Turbulence near thunderstorm tops
J. Pearson, R. Sharman (2017)
Prediction of Energy Dissipation Rates for Aviation Turbulence. Part II: Nowcasting Convective and Nonconvective TurbulenceJournal of Applied Meteorology and Climatology, 56
R. Sharman, J. Doyle, M. Shapiro (2012)
An Investigation of a Commercial Aircraft Encounter with Severe Clear-Air Turbulence over Western GreenlandJournal of Applied Meteorology and Climatology, 51
(2014)
Summer season squall-line
S. Trier, R. Sharman, R. Fovell, R. Frehlich (2010)
Numerical Simulation of Radial Cloud Bands within the Upper-Level Outflow of an Observed Mesoscale Convective SystemJournal of the Atmospheric Sciences, 67
R. Wakimoto, Hanne Murphey (2009)
Analysis of a Dryline during IHOP: Implications for Convection InitiationMonthly Weather Review, 137
Wayne Golding (2002)
Turbulence and Its Impact on Commercial Aviation, 11
L. Bernardet, L. Grasso, J. Nachamkin, C. Finley, W. Cotton (2000)
Simulating convective events using a high‐resolution mesoscale modelJournal of Geophysical Research, 105
U. Schumann (1991)
Subgrid length-scales for large-eddy simulation of stratified turbulenceTheoretical and Computational Fluid Dynamics, 2
G. Ellrod, J. Knox (2010)
Improvements to an Operational Clear-Air Turbulence Diagnostic Index by Addition of a Divergence Trend TermWeather and Forecasting, 25
(2017)
Aeronautical Information Manual: Official Guide to Basic Flight Information and ATC Procedures
(1980)
Probability forecasts of clear-air turbulence
L. Cornman, Corinne Morse, G. Cunning (1994)
Real-time estimation of atmospheric turbulence severity from in-situ aircraft measurementsJournal of Aircraft, 32
R. Mcnulty (1995)
Severe and Convective Weather: A Central Region Forecasting ChallengeWeather and Forecasting, 10
AbstractConvectively induced turbulence (CIT) poses both a serious threat to aviation operations and a challenge to forecasting applications. CIT generation and propagation processes occur on scales between 10 and 1000 m and therefore are best treated with high-resolution cloud-resolving models. However, high-resolution model simulations are computationally expensive, limiting their operational use. In this study, summertime convection in the North Dakota region is simulated over a 1-week period using a variety of model setups that are similar to those utilized in operational and research applications. Eddy dissipation rate and Ellrod index, both popular turbulence metrics, are evaluated across various model resolutions and compared with pilot reports from aircraft. The Ellrod index was found to be extremely sensitive to model resolution and overestimated turbulence intensity. The variability of turbulence values with respect to model resolution and distance away from convection is also examined. Turbulence probability was found to be the greatest when farther than 20 mi (32.2 km) away from convective cores. Model resolution was found to influence the intensity of predicted turbulence, and the model setup with the highest horizontal and vertical resolution predicted the highest turbulence values. However, the influence on turbulence intensity of vertical resolution and convective properties, such as storm depth, was found to be minimal for 3-km horizontal grid spacing.
Journal of Applied Meteorology and Climatology – American Meteorological Society
Published: Jan 21, 2018
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