کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4449715 1311647 2016 11 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Forecasting hailfall using parameters for convective cells identified by radar
ترجمه فارسی عنوان
افزایش پیش بینی با استفاده از پارامترهای سلول های کنتراست شناسایی شده توسط رادار
موضوعات مرتبط
مهندسی و علوم پایه علوم زمین و سیارات علم هواشناسی
چکیده انگلیسی


• Tracking the life cycle of thunderstorms helps hail diagnosis.
• The use of simple radar parameters (reflectivity, vertical integrated liquid, and echo tops) and their evolution along their life cycle means it is possible to determine the presence of hail on the surface.
• The quicker a reflectivity core exceeding 45 dBZ develops vertically in a thunderstorm, the higher the probability of hail on the surface.

The main goal of the present paper is to propose some new criteria that will improve the diagnosis for hail at the surface in real-time, so that they can be applied to surveillance tasks and for nowcasting purposes. The criteria are based on a better knowledge of convective cells that produce hail during their life cycle and better distinguishing between these cells and cells that do not produce hail on the surface. The work focused on a region in the northeast of the Iberian Peninsula, selecting hail events that occurred in the 2004–2012 period and using the information provided by the Meteorological Service of Catalonia's weather radar network. The methodology deals with the analysis of the level of reflectivity associated with the maximum values, which can be considered as the core of the convective vertical development. The chosen radar parameters are operative and they take into consideration the following: the reflectivity, the vertically integrated liquid, the highest altitude at which radar echoes have been observed over a determined reflectivity threshold, as well as the direction and the duration of the convective cells. This work aims to complement all the previous work carried out by different authors, in order to better identify hail in the chosen region.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Atmospheric Research - Volume 169, Part A, 1 March 2016, Pages 366–376
نویسندگان
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