Storm Identification, Tracking and Forecasting Using High-Resolution Images of Short-Range X-Band Radar

نویسندگان

  • Sajid Shah
  • Riccardo Notarpietro
  • Marco Branca
  • Guifu Zhang
چکیده

Rain nowcasting is an essential part of weather monitoring. It plays a vital role in human life, ranging from advanced warning systems to scheduling open air events and tourism. A nowcasting system can be divided into three fundamental steps, i.e., storm identification, tracking and nowcasting. The main contribution of this work is to propose procedures for each step of the rain nowcasting tool and to objectively evaluate the performances of every step, focusing on two-dimension data collected from short-range X-band radars installed in different parts of Italy. This work presents the solution of previously unsolved problems in storm identification: first, the selection of suitable thresholds for storm identification; second, the isolation of false merger (loosely-connected storms); and third, the identification of a high reflectivity sub-storm within a large storm. The storm tracking step of the existing tools, such as TITANand SCIT, use only up to two storm attributes, i.e., center of mass and area. It is possible to use more attributes for tracking. Furthermore, the contribution of each attribute in storm tracking is yet to be investigated. This paper presents a novel procedure called SALdEdA (structure, amplitude, location, eccentricity difference and areal difference) for storm tracking. This work also presents the contribution of each component of SALdEdA in storm tracking. The second order exponential smoothing strategy is used for storm nowcasting, where the growth and decay of each variable of interest is considered to be linear. We evaluated the major steps of our method. The adopted techniques for automatic threshold calculation are assessed with Atmosphere 2015, 6 580 a 97% goodness. False merger and sub-storms within a cluster of storms are successfully handled. Furthermore, the storm tracking procedure produced good results with an accuracy of 99.34% for convective events and 100% for stratiform events.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Tracking fuzzy storm centers in Doppler radar images

In this paper, we describe an automatic storm tracking system to help with the forecasting of severe storms. The concepts fuzzy point, fuzzy vector, fuzzy length of a fuzzy vector, and fuzzy angle between two non-zero fuzzy vectors are rst examined. We use a region splitting algorithm with dynamic thresholding to determine storm masses in Doppler radar intensity images. We represent the center ...

متن کامل

Tracking Fuzzy Storm Centers in Doppler Radar

In this paper, we describe an automatic storm tracking system to help with the forecasting of severe storms. The concepts fuzzy point, fuzzy vector, fuzzy length of a fuzzy vector, and fuzzy angle between two non-zero fuzzy vectors are rst examined. We use a region splitting algorithm with dynamic thresholding to determine storm masses in Doppler radar intensity images. We represent the center ...

متن کامل

Tracking severe weather storms in Doppler radar images

We describe an automatic storm-tracking system to help Doppler radar system to detect severe storms such as thunderwith the forecasting of severe storms. In this article, we present the storms and tornadoes. The Doppler radar generates intensity and concepts of fuzzy point, fuzzy vector, fuzzy length of a fuzzy vector, radial velocity images, examples of which are shown in Figures and fuzzy ang...

متن کامل

Quantitative Precipitation Nowcasting: A Lagrangian Pixel-Based Approach

Short-term high-resolution precipitation forecasting has important implications for navigation, flood forecasting, and other hydrological and meteorological concerns. This article introduces a pixel-based algorithm for Short-term Quantitative Precipitation Forecasting (SQPF) using radar-based rainfall data. The proposed algorithm called PixelBased Nowcasting (PBN) tracks severe storms with a hi...

متن کامل

Demonstration of advanced reconnaissance techniques with the airborne SAR/GMTI sensor PAMIR

PAMIR (Phased Array Multifunctional Imaging Radar) is an experimental airborne radar system that has been designed and built by the Research Institute for High Frequency Physics and Radar Techniques (FHR) of Forschungsgesellschaft für Angewandte Naturwissenschaften (FGAN). The goal is to meet the growing demands for future reconnaissance systems with respect to flexibility and multi-mode operat...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2015