Mesoscale Convective Systems and Squall Lines, Formation

Mesoscale Convective Systems
and Squall Line Formation
Crystal K Williams
Department of Geography-Geology
Illinois State University
Mesoscale Convective Systems
Squall Lines
• Thunderstorms are an important part of the
hydrologic cycle
• >70% annual precipitation in central US falls
during 25% of days with totals >12.7 mm (0.5 in)
• 10% of the annual rain events are thunderstorms
• Creates challenges for:
hydrologic modeling
agricultural needs
Prediction of flood events
Dangerous winds, hail, lightning, tornadoes
Using a hydrologic viewpoint, what is the
current research on Mesoscale Convective
Systems and squall lines?
Background Information
• Four main types of thunderstorms:
– single cell
– multicell clusters
– multicell lines
– supercell storms
• Focus on multicell systems
• Mesoscale Convective Systems and squall lines
Thunderstorm Ingredients
• Moisture
– Water vapor
• Instability
– Wind shear
– ‘thermal wind’ in MSC
• Lifting mechanism
– Conduction, convection
Mesoscale Convective System (MCS)
• Commonly occur in the Plains and Midwest
• cloud system occurs in connection with a
group of thunderstorms --convective
• produces a large precipitation area,
round/linear - horizontal scale of 100 km or
more --meso
• Types: tropical cyclones, squall lines, and
Mesoscale Convective Complexes (chance for
MCS Animations
• Creation
• Example
Squall Line
• a type of MCS with a larger length to width ratio, continuous or with
• form on the leading edge of a cold front, but are separate from the front
Image Courtesy of
Squall line continued
• increase in wind speed > 18
mph, sustained speed of 25 mph
for over 1 minute
• tropical squall lines are
significantly weaker than the
midlatitude systems, why?
– areas with identical
temperatures, precipitable
water content, and convective
potential energy determine the
higher intensity
• squall lines can merge with
supercell systems (severe
thunderstorms that have the
potential to produce tornadoes)
• Chance of an increase in
intensity after the merge is 59%
Precipitation Detection
• Radar and satellites have added an extensive
quantity of data for weather observations
• Radio Detection and Ranging - electromagnetic
radiation to sense precipitation
• Satellite: visible, infrared, water vapor
• used to improve weather simulations and
– Conventional and Doppler (reflectivity and wind
• rain gauges have been the main method of ground
truthing, although stream level recorders can be used to
supplement the gages into gaining further insight into
spatial patterns of storm events
• Multiple mathematical models have been developed to
better predict and estimate precipitation spatially,
specifically thunderstorm events.
– Examining the patterns of these thunderstorms and the
hydrologic cycle can further the accuracy of these estimations.
Newest technology: Dual polarization radar
– better detect heavy rainfall in flooding events, detect
precipitation type (rain, hail, snow)
Case Study – Balling and Goodrich (2011)
• precipitation values and Atlantic Multidecadal
Oscillation (sea surface temperatures) were compared
and analyzed (1975–2009) to see if correlation exists
between the Earth’s warming temperature and higher
precipitation levels
• concluded that daily precipitation records from the
conterminous U.S. reveal that with recent Earth
warming, precipitation intensity appears to have
increased at a continental scale
• “making any direct link between anthropogenic
changes in atmospheric composition and increases in
precipitation intensity must be done with caution.”
• Mesoscale Convective Systems, including squall lines
vary in spatial movement and precipitation properties
– Potential convection, water vapor, wind shear
• Although many models and scientific prediction
methods utilizing radar, satellite, and case studies to
predict strength of storms along with intense
precipitation and wind
– The correlation between the Earth’s rising temperatures
and higher precipitation values shows the need to update
hydrological modeling.
– Also, more thunderstorm research, from a hydrologic
perspective, is needed for connect meteorological
modeling/simulation and effects on hydrologic modeling.
Balling Jr., R. C., & Goodrich, G. B. (2011). Spatial analysis of variations in precipitation intensity in the USA. Theoretical & Applied Climatology, 104(3/4), 415-421.
Chen, S. S., and W. M. Frank (1993). A numerical study of the genesis of extratropical convective mesovortices. Part I: Evolution and dynamics, Journal of
Atmospheric Science, 50, 2401–2426.
Chen, Shu-Hua, Zhan Zhao, Jennifer S. Haase, Aidong Chen, Francois Vandenberghe. (2008) A study of the characteristics and assimilation of retrieved modis total
precipitable water data in severe weather simulations. Monthly Weather Review, 136, 3608–3628.
doi: 10.1175/2008MWR2384.1
Efrat Morin, David C. Goodrich, Robert A. Maddox, Xiaogang Gao, Hoshin V. Gupta, Soroosh Sorooshian, (2006). Spatial patterns in thunderstorm rainfall events and
their coupling with watershed hydrological response, Advances in Water Resources, 29(6), 843-860, doi: 10.1016/j.advwatres.2005.07.014
French, A. J., & Parker, M. D. (2012). Observations of Mergers between Squall Lines and Isolated Supercell Thunderstorms. Weather & Forecasting, 27(2), 255-278.
Groisman, P. a., Knight, R. W., & Karl, T. R. (2012). Changes in Intense Precipitation over the Central United States. Journal Of Hydrometeorology, 13(1), 47-66.
Hocker, James E., (2008). A 10-year spatial climatology of squall line storms across Oklahoma. International Journal of Climatology, 28 (6), 765-775. doi:
Huang, C.-Y., Y.-H. Kuo, S.-H. Chen, and F. Vandenberghe (2005). Improvements in typhoon forecasts with assimilated GPS occultation refractivity. Weather
Forecasting, 20, 931–953
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thunderstorm precipitation and distinguishing rain from snow. Water Resources Research, 45(W00D25). doi: 10.1029/2008WR006995
Takemi, Tetsuya (2007). A sensitivity of squall-line intensity to environmental static stability under various shear and moisture conditions. Atmospheric Research,
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