1 / 17

BASIC UNDERSTANDING OF MESOSCALE DYNAMICS IN 0-6 HOUR TIMEFRAME Patrick Mukunguta

BASIC UNDERSTANDING OF MESOSCALE DYNAMICS IN 0-6 HOUR TIMEFRAME Patrick Mukunguta. Zimbabwe Meteorological Dept. Harare, Zimbabwe. • Thunderstorm Lifetime, Evolution and Characteristics • Boundary Influences on Thunderstorm Evolution • Stability Influences on Thunderstorm Evolution

Download Presentation

BASIC UNDERSTANDING OF MESOSCALE DYNAMICS IN 0-6 HOUR TIMEFRAME Patrick Mukunguta

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. BASIC UNDERSTANDING OF MESOSCALE DYNAMICS IN 0-6 HOUR TIMEFRAMEPatrick Mukunguta Zimbabwe Meteorological Dept. Harare, Zimbabwe

  2. •Thunderstorm Lifetime, Evolution and Characteristics • • Boundary Influences on Thunderstorm Evolution • • Stability Influences on Thunderstorm Evolution • • Forecast Parameters

  3. Thunderstorm Lifetime, Evolution and CharacteristicsThunderstorm Lifetime

  4. Example Evolution of a Single Cell and a Convective System

  5. Thunderstorm Characteristics: • Radar can provide time trends of thunderstorm movement, size, height, • intensity, height of the rain mass centroid, and vertically integrated • liquid water equivalent. Beyond ~ 15 min these parameters by themselves are of only limited forecast value. This is because physical processes that dictate • changes in storms are not necessarily observable in the past history of the storm but are often driven by boundary layer events such as convergence and stability. • The vast majorities of storms have short lifetimes and/or frequent rapid changes in storm intensity and size thus - forecasts by extrapolation alone are generally insufficient. Need to forecast initiation, growth and dissipation. Mature supercells and large squall lines are often exceptions. Extrapolation alone for these systems is often sufficient for periods up to at least 2 hr. • As can be seen in the figure below the accuracy of the forecasts decreases very rapidly during the first hour. Large-scale numerical models can not even make forecasts on this short time • scale. Forecasts with explicit storm numerical methods are in their infancy. The approach used here is an expert system, which is based on the heavy use of observations and theory.

  6. •Boundary Influences on Thunderstorm Evolution • Boundary layer convergence lines (boundaries) frequently influence the evolution of thunderstorms. These boundaries can often be observed in: • Satellite cloud imagery • Clear-air radar features.

  7. CONVERGING WINDS Thunderstorm initiation frequently occurs near boundary layer convergence lines. This region is referred to as the lifting zone. The lifting zone is the most likely region for storm initiation and storm growth. It is positioned about the boundary based on the boundary speed of movement. Lifting zone

  8. •Boundary Influences on Thunderstorm Evolution • •Colliding Boundaries Often Initiate Intense Storms • Colliding boundaries are frequently responsible for storm initiation and significant increase in the intensity and size of existing storms. • •Storm Initiation often follows a boundary intercepting • Cumulus clouds • When a gust front is intercepts a convective roll. The cumulus clouds along • the roll grow into thunderstorms once the gust front passes under them. • •Convergence Magnitude and Depth • Obviously strong low-level convergence and deep updrafts • have greater potential for developing intense thunderstorms. Thunderstorm Nowcasting requires close Monitoring of Boundaries, Storms and Clouds to Anticipate • when they will Intercept each other

  9. Static Stability is a Critical Parameter for ForecastingThunderstorms.Traditionally radiosondes are used to measure stability. Unfortunately they are widelyspaced and observations are infrequent, thus of limited use for thunderstorm nowcasting purposes. RADIOSONDE ( Harare Belvedere)

  10. Static Stability is a Critical Parameter for ForecastingThunderstorms. Soundings are of limited use for thunderstorm nowcasting because of small- scale variability in water vapor. In this example three simultaneous soundings show there are large variations in the convective available potential energy (orange area) over short distances in the vicinity of a convergence line. Soundings are of limited use for thunderstorm nowcasting because of small- scale variability in water vapor.

  11. Static Stability is a Critical Parameter for ForecastingThunderstorms

  12. Static Stability is a Critical Parameter for ForecastingThunderstorms • Satellite Cloud Imagery is used to monitor the stability. • The presence of cumulus clouds indicates instability although of unknown magnitude and depth. • The use of satellite visible and infrared imagery to monitor the location • and development of cumulus clouds serves as a useful proxy for • stability.

  13. Forecast ParametersFactors Associated With Storm Initiation: • • Presence of convergence line (Boundary) • • Lifted index < 0 in lifting zone • • Cu in lifting zone • • Rapid growth of Cu in lifting zone • • Colliding boundaries • • Low boundary relative cell speeds

  14. Forecast ParametersFactors Associated With Storm Growth: • • Boundary motion = storm motion • • Convergence strong and deep • • Erect updrafts • • Merging of storms • • Boundary intercepting cumulus and storms

  15. Forecast ParametersFactors Associated With Storm Dissipation: • • Boundary moving away from storms • • Boundary moving into a stable region • • Storm decreasing in size and intensity and no boundary present

  16. References Browning, K. A., C. G Collier, P.R. Larke, P. Menmuir, G. A. Monk, and R. G. Owens, 1982: On the forecasting of frontal rain using a weather radar network. Mon. Wea. Rev., 110, 534-552. Doswell,C.A., 1986: Short-range forecasting. Mesoscale Meteorology and Forecasting, P.Ray, Ed. Amer. Meteor. Soc., Boston, 793 pp Henry, S. G., 1993: Analysis of thunderstorm lifetime as a function of size and intensity. Preprints. 26th Conference on Radar Meteorology, Norman OK, Amer. Meteor. Soc., 138-140. Moncrieff, M.W., and M.J. Miller, 1976: The dynamics and simulation of tropical cumulonimbus and squall lines. Quart. J. Roy. Meteor. Soc., 102, 373-394. Weckwerth, T.M., J.W. Wilson, and R.M. Wakimoto, 1996: Thermodynamic variability within the convective boundary layer due to horizontal convective rolls. Mon. Wea. Rev., 124, 769-784. Weisman M.L., and J.B. Klemp, 1986: Characteristics of isolated convective storms, Chapter 15. Mesoscale Meteorology and Forecasting, P.S.Ray, Ed., Amer. Meteor. Soc., 763 pp. Wilson, J.W., G.B. Foote, J.C. Fankhauser, N.A. Crook, C.G. Wade, J.D. Tuttle, C.K. Mueller, S.K. Krueger, 1992: The role of boundary layer convergence zones and horizontal rolls in the initiation of thunderstorms: a case study. Mon. Wea. Rev., 120, 1758-1815. Wilson, J. W., and C. K. Mueller, 1993: Nowcasts of thunderstorm initiation and evolution. Wea. Forecasting., 8, 113-131. Wilson, J. W., and D. L. Megenhardt, 1997: Thunderstorm initiation, organization and lifetime associated with Florida boundary layer convergence lines. Mon. Wea. Rev., 125, 1507-1525

  17. THE END • Thanks and • Good Bye

More Related