A radar-based centroid tracking algorithm for severe weather surveillance: identifying split/merge processes in convective systems

Abstract Nowcasting tools using radar data are essential when researching severe weather phenomena. Identifying thunderstorms and characterising their properties are usually the main steps to follow in order to make a good short-term forecast. These analyses are normally used to feed early warning systems in many countries, helping to reduce the impact of severe weather. Over the last few decades, research in this meteorological field has increased significantly, defining different methodologies that have worked well for many severe events. Most of these methodologies are based on a prior 3D identification of the thunderstorms in question, by applying intensity and size thresholds and obtaining their characteristics, allowing their centroids to be tracked. In some cases, the thresholds for identification and the distance established to track the centroid are too restrictive, which results in the incorrect identification of individual cells in multicell systems, or even means that the algorithm is unable to distinguish when an anomalous movement takes place. This paper presents a new type of 3D cell identification and tracking, based on the algorithm developed by Rigo and Llasat (2004). This last algorithm is currently used in the Meteorological Service of Catalonia (SMC), and consists of a nowcasting methodology based on centroid tracking. In the new version, a new two-step methodology to construct 3D radar cells has been proposed. A double reflectivity thresholding method plus an overlapping technique have been applied for a better definition of the convective structures. This makes it possible to identify possible changing processes such as splitting or merging within the same thunderstorm. Furthermore, a dynamic distance threshold technique has been adopted to correctly track cells with anomalous movements. An in-depth study has been carried out for a severe weather case in which a multicell system presented a complex merging and splitting process that was correctly forecasted using the proposed algorithm.

[1]  Tomeu Rigo,et al.  Pilot project for intensive surveillance of hail events in Terres de Ponent (Lleida) , 2007 .

[2]  Patrick King,et al.  Investigating the Potential of Using Radar Echo Reflectivity to Nowcast Cloud-to-Ground Lightning Initiation over Southern Ontario , 2010 .

[3]  Anna del Moral,et al.  Identification of anomalous motion of thunderstorms using daily rainfall fields , 2016 .

[4]  M. C. Llasat,et al.  A methodology for the classification of convective structures using meteorological radar: Application to heavy rainfall events on the Mediterranean coast of the Iberian Peninsula , 2004 .

[5]  P. Marcacci,et al.  Thunderstorm nowcasting by means of lightning and radar data: algorithms and applications in northern Italy , 2008 .

[6]  Daniel Rosenfeld.  Objective Method for Analysis and Tracking of Convective Cells as Seen by Radar , 1987 .

[7]  A. Seed.  A Dynamic and Spatial Scaling Approach to Advection Forecasting , 2001 .

[8]  M. C. Llasat,et al.  Analysis of convective structures that produce heavy rainfall events in Catalonia (NE of Spain), using meteorological radar , 2002 .

[9]  Donald W. Burgess,et al.  Developing Tools for Nowcasting Storm Severity , 2006 .

[10]  Tomeu Rigo,et al.  Inferring the Severity of a Multicell Thunderstorm Evolving to Supercell, by Means of Radar and Total Lightning , 2016, E-Journal of Severe Storms Meteorology.

[11]  E. Lai,et al.  TREC Application in Tropical Cyclone Observation , 2000 .

[12]  Arthur Witt,et al.  The Storm Cell Identification and Tracking Algorithm: An Enhanced WSR-88D Algorithm , 1998 .

[13]  Tomeu Rigo,et al.  Forecasting hailfall using parameters for convective cells identified by radar , 2016 .

[14]  Robert Crane,et al.  Automatic Cell Detection and Tracking , 1979, IEEE Transactions on Geoscience Electronics.

[15]  Hartwig Deneke,et al.  Characterization of Initiation and Growth of Selected Severe Convective Storms over Central Europe with MSG-SEVIRI , 2015 .

[16]  Juanzhen Sun,et al.  Nowcasting Thunderstorms: A Status Report , 1998 .

[17]  José Manuel López,et al.  Two cases of severe weather in Catalonia (Spain): an observational study , 1997 .

[18]  Elizabeth E. Ebert,et al.  Sydney 2000 Forecast Demonstration Project: Convective Storm Nowcasting , 2004 .

[19]  R. Rinehart,et al.  Three-dimensional storm motion detection by conventional weather radar , 1978, Nature.

[20]  Lei Han,et al.  3D Convective Storm Identification, Tracking, and Forecasting—An Enhanced TITAN Algorithm , 2009 .

[21]  Chris G. Collier,et al.  GANDOLF: a system for generating automated nowcasts of convective precipitation , 2000 .

[22]  Tomeu Rigo,et al.  Analysis of warm season thunderstorms using an object-oriented tracking method based on radar and total lightning data , 2010 .

[23]  Tomeu Rigo,et al.  Lightning jump as a nowcast predictor: Application to severe weather events in Catalonia , 2017 .

[24]  G. Austin,et al.  An evaluation of extrapolation techniques for the short‐term prediction of rain amounts , 1981 .

[25]  Christopher J. Schultz,et al.  Preliminary Development and Evaluation of Lightning Jump Algorithms for the Real-Time Detection of Severe Weather , 2009 .

[26]  Tomeu Rigo,et al.  A study of the 21 March 2012 tornadic quasi linear convective system in Catalonia , 2015 .

[27]  W. Cotton,et al.  Storm and Cloud Dynamics , 1992 .

[28]  L. Mediero,et al.  Using Lightning Data to Better Understand and Predict Flash Floods in the Mediterranean , 2011 .

[29]  M. Dixon,et al.  TITAN: Thunderstorm Identification, Tracking, Analysis, and Nowcasting—A Radar-based Methodology , 1993 .

[30]  B. Golding.  Nimrod: a system for generating automated very short range forecasts , 1998 .

[31]  M. C. Llasat,et al.  Flash floods in Catalonia: a recurrent situation , 2009 .

[32]  Marco Turco,et al.  Towards a better understanding of the evolution of the flood risk in Mediterranean urban areas: the case of Barcelona , 2018, Natural Hazards.

[33]  M. Llasat,et al.  Predicting the potential for lightning activity in Mediterranean storms based on the Weather Research and Forecasting (WRF) model dynamic and microphysical fields , 2010 .

[34]  Nicolau Pineda,et al.  The weather radar network of the Catalan Meteorological Service: description and applications , 2004 .

[35]  Christopher D. Lloyd,et al.  Spatial Data Analysis: An Introduction for GIS users , 2010 .

[36]  Terri Betancourt,et al.  NCAR Auto-Nowcast System , 2003 .