روشی برای پیش‌بینی رخداد توفان‌های تندری با طرح دو بررسی موردی

نویسندگان

1 سازمان هواشناسی کشور- دکتری

2 دانشگاه آزاد اسلامی ، واحد علوم و تحقیقات- دانشجوی دکتری

3 سازمان هواشناسی کشور- کارشناس ارشد

چکیده

در این تحقیق کوشش شده است تا شیوه پیش‌بینی وقوع توفان تندری با استفاده از درخت تصمیم‌گیری (decision tree) عرضه شود. این روش که می‌تواند راهنمای خوبی برای پیش‌بین‌های هواشناس باشد، به کمک خروجی‌های هر مدل منطقه‌ای قابل بررسی است. از این رو، در این مقاله ضمن بررسی الگوهای بزرگ‌مقیاس جوّ در بررسی‌های موردی، با تحلیل برخی از مهم‌ترین خروجی‌های مدل منطقه‌ای MM5 با درجه تفکیک 35 کیلومتر برای پیش‌بینی توفان تندری (همگرایی جریان در سطح زمین، سرعت قائم در لایه‌های زیرین جوّ، میزان رطوبت و فرونشست جریان در لایه‌های میانی و بالایی جوّ)، از آنها در درخت تصمیم‌گیری استفاده شده است. نتایج این تحقیق نشان می‌دهد که شاخص‌های بزرگ‌مقیاس وقوع توفان تندری مشابه غالب ناپایداری‌های جوّی است و پیش‌بینی این پدیده نیازمند اجرای مدل‌های منطقه‌ای میان‌مقیاس است. آستانه مقادیر عددی خروجی‌های رطوبت نسبی و فرونشست جریان در لایه‌های میانی جوّ در ایستگاه مهرآباد تهران با مقادیر آستانه‌ای موجود برای رخداد توفان هم‌خوانی دارد اما مقادیر عددی سرعت قائم در تراز 850 میلی باری در این مدل با آستانه‌های موجود هماهنگ نیست. همچنین مقادیر عددی برخی از مهم‌ترین شاخص‌های صعود ( LI ، KI ،SWEAT و CAPE) براساس نمودار skew-t در ایستگاه یادشده با آستانه‌های موجود در جدول‌های عرضه شده برای رخداد توفان تندری در دیگر تحقیقات همخوان است. از این رو می‌توان با اعمال مقادیر عددی پیش‌بینی شده پارامترهای موردنیاز برای تحلیل نقشه‌های skew-t به آستانه‌های یادشده اطمینان کرد.

کلیدواژه‌ها


عنوان مقاله [English]

Two case studies to introduce a method for thunderstorm forecasting

نویسندگان [English]

  • sahar Tajbakhsh 1
  • Parvin Ghaffarian 2
  • Ebrahim Mirzaei 3
1
2
3
چکیده [English]

Thunderstorm is one of the most dangerous phenomena in aviation because the greatest number weather hazards such as icing, turbulence, wind shear, lightning hail are combined in one single source, the thunderstorm. Spatial characteristics of thunderstorms which can be associated with irreparable outcomes are known by most of the forecasters. Tornadoes, microbursts, very strong winds and flash floods are some of the accompanying hazardous atmospheric conditions with thunderstorm. Therefore, its prediction is one of the elementary duties of forecasting centers to rectify aeronautical problems.
Typical horizontal and vertical extents of thunderstorm are in order of tens of kilometers and 30,000 feet (up to and pushing into the tropopause at times) respectively, and typical duration in time is in the order of 30 minutes. The life cycle of a thunderstorm is divided into three stages. In the first, the towering cumulus stage, warm moist unstable air feeds the cloud’s vertical growth and updraft increases in strength. The second stage is known as the mature stage where the cumulonimbus top glaciates and down drafts become significant. In the third, dissipating, Stage, the anvils are well developed and the down drafts diminish. Associated clouds include cumulus cloud (Cu), towering cumulus (TCu), cumulonimbus (Cb) thunderstorm cloud. Often low-level stratus (St) forms in the precipitation at the base of a thunderstorm, The morning appearance of altocumulus castellans, turrets of middle-level cloud, are the precursor to thunderstorm activity later in the day.
Several methods have been presented for thunderstorm forecasting since 1951. Most of them are applicable when an active atmospheric system on a large scale is dominant. But many strong storms cannot be monitored on the synoptic scale. Therefore, some other forecasting methods were introduced by Dvorak et al. (1975).These methods have been known as decision tree. Colquhoun was the first one who used decision tree for thunderstorm forecasting. He tried to solve some problems of thunderstorm forecasts using skew-t data and NWP outputs. Then, in 1998 Miles and Colquhoun (1998) modified the tree, so that all parameters could be computed automatically from numerical weather prediction outputs.
The method which is presented in this paper is the Colquhoun (1996) algorithm. It is a suitable guide for meteorologists for predicting thunderstorms using each numerical weather prediction output.
Two case studies are considered to survey the thunderstorm in the present research. Both of them occurred at 15 UTC at Mehr-Abad airport. One of them on 13th of May and another on 5th of June 2007 which are analyzed according to the decision tree. The surface and upper air synoptic patterns and satellite images are studied in events of storms. On the other hand some MM5 numerical weather prediction outputs are examined to determine the threshold values of vertical velocity in 850mb, relative humidity in 500-600mb and subsidence currents in 400-500 mb layers. It should be mentioned that the MM5 was run with 35km resolution in regional scale. To access better results, some of the most significant thermodynamic upward motion indices are calculated for Mehr-Abad airport such as LI, KI, SWEAT index, CAPE and BRN using the RAOB software.
Analysis of the MM5 outputs shows that the vertical velocity in 850 mb is not reliable because the observations confirm the passage of a cold front which is a reason for convergence in low level but the vertical velocity values do not correspond with them. The threshold values of relative humidity and sinking currents are the same as other studies in the world. Also, the LI, KI, SWEAT and CAPE values represented unstable conditions for thunderstorm occurrence.
Although most of decisions in the Colquhoun algorithm are designed for severe thunderstorms in tropical and subtropical regions, some boxes of the decision tree are denoted to ordinary storms which occur in mid latitudes of which 2 examples are shown in this research. So, it can be used in operational applications such as aeronautical meteorology in forecasting center of IRIMO. Large scale patterns are not suitable guides for the prediction of thunderstorms because there are no especial indexes for identifying the storms and they can show instability qualitatively. The thermodynamic indexes (LI, KI, SWEAT and CAPE) and their threshold values are appropriate signs to forecast storms in the Tehran area. MM5 vertical velocity at low level isn't reliable and needs to be modified but relative humidity and subsiding currents in mid levels give the acceptable results.

کلیدواژه‌ها [English]

  • Decision Tree
  • Numerical weather prediction
  • Thermodynamic Ascend index
  • Thunderstorm