Three-dimensional analysis of the initial stage of convective precipitation using an operational X-band polarimetric radar network

Abstract In this study, we propose a new methodology for analysis of the initial stage of localized convective precipitation. The developed algorithm was used to create three-dimensional constant-altitude plan-position-indicator (3D CAPPI) data, which are high-spatiotemporal-resolution volumetric data, using two X-band polarimetric radars that are located in the Kanto region of Japan. Advection vectors are estimated by applying the normalized cross-correlation method to observed successive precipitation echoes on the polar coordinate system at each antenna tilt angle. The estimated advection vectors are expressed by a linear regression model that depends on time and tilt angle. In addition, 3D CAPPI data utilize the mosaic method to obtain further precipitation information from radar observations. The algorithm produces the detailed 3D structure of rapidly developing convective cells and provides quantitative information on convective precipitation, such as the echo top height, maximum reflectivity, and appearance time and height of each cell. The 3D CAPPI mosaic also clearly shows the back-building process at the initial stage of convective precipitation.

[1]  G. Cotton,et al.  Precipitation Results of Two Randomized Pyrotechnic Cumulus Seeding Experiments , 1971 .

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

[3]  Uwe D. Hanebeck,et al.  Template matching using fast normalized cross correlation , 2001, SPIE Defense + Commercial Sensing.

[4]  Roscoe R. Braham,et al.  The thunderstorm : report of the thunderstorm project , 1949 .

[5]  Yuh-Lang Lin,et al.  Orographic effects on localized heavy rainfall events over southwestern Taiwan on 27 and 28 June 2008 during the post-Mei-Yu period , 2011 .

[6]  Giovanni Emilio Perona,et al.  MicroRadarNet: A network of weather micro radars for the identification of local high resolution precipitation patterns , 2013 .

[7]  Alexander V. Ryzhkov,et al.  The Impact of Size Sorting on the Polarimetric Radar Variables , 2012 .

[8]  M. R. Rasmussen,et al.  A Numerical Method to Generate High Temporal Resolution Precipitation Time Series by Combining Weather Radar Measurements with a Nowcast Model , 2014 .

[9]  Jan Handwerker,et al.  Cell tracking with TRACE3D—a new algorithm , 2002 .

[10]  E. Zipser,et al.  The Vertical Profile of Radar Reflectivity of Convective Cells: A Strong Indicator of Storm Intensity and Lightning Probability? , 1994 .

[11]  F. Fujibe.  Relationship between Interannual Variations of Extreme Hourly Precipitation and Air/Sea-Surface Temperature in Japan , 2015 .

[12]  F. Martin Ralph,et al.  The Utility of X-Band Polarimetric Radar for Quantitative Estimates of Rainfall Parameters , 2005 .

[13]  Sergey Y. Matrosov,et al.  X-Band Polarimetric Radar Measurements of Rainfall , 2002 .

[14]  Francesco Marra,et al.  Autocorrelation structure of convective rainfall in semiarid-arid climate derived from high-resolution X-Band radar estimates , 2018 .

[15]  Arthur Witt,et al.  A Real-Time, Three-Dimensional, Rapidly Updating, Heterogeneous Radar Merger Technique for Reflectivity, Velocity, and Derived Products , 2006 .

[16]  The motion of simulated convective storms as a function of basic environmental parameters , 2004 .

[17]  Christopher E. Hann,et al.  Fast normalized cross correlation for motion tracking using basis functions , 2006, Comput. Methods Programs Biomed..

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

[19]  Lisako Konoshima,et al.  FUNDAMENTAL STUDY ON FUTURE CHANGE OF LOCALIZED HEAVY RAINFALL DURING BAIU DUE TO CLIMATE CHANGE USING A REGIONAL CLIMATE MODEL , 2012 .

[20]  K. Iwanami,et al.  Developing a composite rainfall map based on observations from an X-band polarimetric radar network and conventional C-band radar , 2012 .

[21]  Anna del Moral,et al.  A radar-based centroid tracking algorithm for severe weather surveillance: identifying split/merge processes in convective systems , 2018, Atmospheric Research.

[22]  Juan M. Stella,et al.  Coupling X-band dual-polarized mini-radars and hydro-meteorological forecast models: the HYDRORAD project , 2013 .

[23]  Henry G. Houghton,et al.  On Precipitation Mechanisms and their Artificial Modification , 1968 .

[24]  刘黎平,et al.  Study of Methods for Three-Dimensional Multiple-Radar Reflectivity Mosaics , 2008 .

[25]  Alan Shapiro,et al.  Retrieval of Model Initial Fields from Single-Doppler Observations of a Supercell Thunderstorm. Part I: Single-Doppler Velocity Retrieval , 2002 .

[26]  Jian Zhang,et al.  Constructing Three-Dimensional Multiple-Radar Reflectivity Mosaics: Examples of Convective Storms and Stratiform Rain Echoes , 2005 .

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

[28]  Emmanouil N. Anagnostou,et al.  X-band Polarimetric Radar Rainfall Measurements in Keys Area Microphysics Project , 2006 .

[29]  Olivier P. Prat,et al.  The Impact of Raindrop Collisional Processes on the Polarimetric Radar Variables , 2014 .

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

[31]  Giovanni Battista Chirico,et al.  Sampling errors in rainfall measurements by weather radar , 2005 .

[32]  A. Bellon,et al.  The Evaluation of Two Years of Real-Time Operation of a Short-Term Precipitation Forecasting Procedure (SHARP). , 1978 .

[33]  Sung-Hwa Jung,et al.  Development of Convective Cell Identification and Tracking Algorithm using 3-Dimensional Radar Reflectivity Fields , 2011 .

[34]  Petr Novák,et al.  The Czech Hydrometeorological Institute's severe storm nowcasting system , 2007 .

[35]  R. L. Vaughan,et al.  An Economical Procedure for Cartesian Interpolation and Display of Reflectivity Factor Data in Three-Dimensional Space , 1979 .

[36]  Jerry M. Straka,et al.  An Adaptation of the Barnes Filter Applied to the Objective Analysis of Radar Data , 2000 .

[37]  Jian Zhang,et al.  Four-Dimensional Dynamic Radar Mosaic , 2004 .

[38]  Jerry M. Straka,et al.  Polarimetric Signatures above the Melting Layer in Winter Storms: An Observational and Modeling Study , 2013 .

[39]  K. Browning,et al.  On the Forecasting of Frontal Rain Using a Weather Radar Network , 1982 .

[40]  R. Houze,et al.  Microphysics of the Rapid Development of Heavy Convective Precipitation , 2001 .

[41]  Dusan S. Zrnic,et al.  Correlation Analysis of Doppler Radar Data and Retrieval of the Horizontal Wind , 1983 .

[42]  Howard B. Bluestein,et al.  Formation of Mesoscale Lines of Pirecipitation: Severe Squall Lines in Oklahoma during the Spring , 1985 .

[43]  Alexander V. Ryzhkov,et al.  The Impact of Evaporation on Polarimetric Characteristics of Rain: Theoretical Model and Practical Implications , 2009 .

[44]  Koyuru Iwanami,et al.  Semi‐operational rainfall observations with X‐band multi‐parameter radar , 2005 .

[45]  E. Luke,et al.  The Role of Cloud Microphysics Parameterization in the Simulation of Mesoscale Convective System Clouds and Precipitation in the Tropical Western Pacific , 2013 .

[46]  L. Sutherland-Stacey,et al.  The spatial and temporal sampling errors inherent in low resolution radar estimates of rainfall , 2011 .

[47]  U. Germann,et al.  Can Lagrangian Extrapolation of Radar Fields Be Used for Precipitation Nowcasting over Complex Alpine Orography , 2012 .

[48]  Carl G. Mohr,et al.  The Simple Rectification to Cartesian Space of Folded Radial Velocities from Doppler Radar Sampling , 1986 .

[49]  Yura Kim,et al.  Data that effectively demonstrate the benefits of a 3D CAPPI algorithm , 2019, Data in brief.

[50]  Emmanouil N. Anagnostou,et al.  Performance evaluation of high-resolution rainfall estimation by X-band dual-polarization radar for flash flood applications in mountainous basins , 2010 .

[51]  K. Tsuboki,et al.  Structure and evolution of deeply developed convective cells in a long- lived cumulonimbus cloud under a weak vertical wind-shear condition , 2005 .

[52]  A. Ryzhkov,et al.  Freezing of Raindrops in Deep Convective Updrafts: A Microphysical and Polarimetric Model , 2012 .

[53]  M. Maki,et al.  Localized Heavy Rainfall Near Zoshigaya, Tokyo, Japan on 5 August 2008 Observed by X-band Polarimetric Radar — Preliminary Analysis — , 2009 .

[54]  P. W. Li,et al.  Short-range quantitative precipitation forecasting in Hong Kong , 2004 .

[55]  Emmanouil N. Anagnostou,et al.  Correction for Rain Path Specific and Differential Attenuation of X-Band Dual-Polarization Observations , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[56]  G. Foote,et al.  Determination of the Boundary Layer Airflow from a Single Doppler Radar , 1990 .

[57]  Roscoe R. Braham,et al.  THE WATER AND ENERGY BUDGETS OF THE THUNDERSTORM AND THEIR RELATION TO THUNDERSTORM DEVELOPMENT , 1952 .

[58]  Jian Zhang,et al.  National mosaic and multi-sensor QPE (NMQ) system description, results, and future plans , 2011 .

[59]  Jidong Gao,et al.  Single-Doppler Velocity Retrieval with Rapid-Scan Radar Data , 2003 .

[60]  C. Simmer,et al.  Precipitation and microphysical processes observed by three polarimetric X-band radars and ground-based instrumentation during HOPE , 2016 .

[61]  Carl G. Mohr,et al.  Results of a Randomized Hail Suppression Experiment in Northeast Colorado. Part VI: Post Hoc Stratification by Storm Intensity and Type , 1979 .

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

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

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

[65]  Peter H. Hildebrand,et al.  Feasibility Test of an Airborne Pulse-Doppler Meteorological Radar. , 1983 .

[66]  Jingfeng Jiang,et al.  A fast hybrid algorithm combining regularized motion tracking and predictive search for reducing the occurrence of large displacement errors , 2011, IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control.

[67]  Matthias Steiner,et al.  Climatological Characterization of Three-Dimensional Storm Structure from Operational Radar and Rain Gauge Data , 1995 .

[68]  S. Mecklenburg,et al.  Improving the nowcasting of precipitation in an Alpine region with an enhanced radar echo tracking algorithm. , 2000 .

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

[70]  Frédéric Fabry,et al.  High resolution rainfall measurements by radar for very small basins: the sampling problem reexamined , 1994 .

[71]  C. Kottmeier,et al.  The convective and orographically-induced precipitation study: A research and development project of the world weather research program , 2008 .

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

[73]  Patrick Willems,et al.  Enhanced object-based tracking algorithm for convective rain storms and cells , 2018 .

[74]  L. Li,et al.  Nowcasting of Motion and Growth of Precipitation with Radar over a Complex Orography , 1995 .

[75]  Harold E. Brooks,et al.  Radar Reflectivity–Derived Thunderstorm Parameters Applied to Storm Longevity Forecasting , 1999 .

[76]  Daniel Sempere-Torres,et al.  An inverse method to retrieve 3D radar reflectivity composites , 2014 .