Operational Application of Optical Flow Techniques to Radar-Based Rainfall Nowcasting

Hong Kong Observatory has been operating an in-house developed rainfall nowcasting system called “Short-range Warning of Intense Rainstorms in Localized Systems (SWIRLS)” to support rainstorm warning and rainfall nowcasting services. A crucial step in rainfall nowcasting is the tracking of radar echoes to generate motion fields for extrapolation of rainfall areas in the following few hours. SWIRLS adopted a correlation-based method in its first operational version in 1999, which was subsequently replaced by optical flow algorithm in 2010 and further enhanced in 2013. The latest optical flow algorithm employs a transformation function to enhance a selected range of reflectivity for feature tracking. It also adopts variational optical flow computation that takes advantage of the Horn–Schunck approach and the Lucas–Kanade method. This paper details the three radar echo tracking algorithms, examines their performances in several significant rainstorm cases and summaries verification results of multi-year performances. The limitations of the current approach are discussed. Developments underway along with future research areas are also presented.

[1]  Harri Hohti,et al.  Optical flow in radar images , 2004 .

[2]  Neill E. Bowler,et al.  Development of a precipitation nowcasting algorithm based upon optical flow techniques , 2004 .

[3]  Rashmi Bhardwaj,et al.  Use of SWIRLS nowcasting system for quantitative precipitation forecast using Indian DWR data , 2021, MAUSAM.

[4]  G. Wahba,et al.  Some New Mathematical Methods for Variational Objective Analysis Using Splines and Cross Validation , 1980 .

[5]  Donald W. Burgess,et al.  The Sydney 2000 World Weather Research Programme Forecast Demonstration Project: Overview and Current Status , 2003 .

[6]  Timo Kohlberger,et al.  Real-Time Optic Flow Computation with Variational Methods , 2003, CAIP.

[7]  Y. C. Wang,et al.  Towards the Blending of NWP with Nowcast – Operation Experience in B 08 FDP * , 2009 .

[8]  Ping-chuen Chin,et al.  Rainfall in Hong Kong , 1971 .

[9]  Alan Seed,et al.  Application of Radar-Raingauge Co-Kriging to Improve QPE and Quality Control of Real-time Rainfall Data , 2011 .

[10]  Alamelu Kilambi,et al.  McGill algorithm for precipitation nowcasting by lagrangian extrapolation (MAPLE) applied to the South Korean radar network. Part I: Sensitivity studies of the Variational Echo Tracking (VET) technique , 2009 .

[11]  Clive Pierce,et al.  Forecast Demonstration Project Sydney 2000: Part 1: An overview of the project and the participating systems , 2001 .

[12]  Berthold K. P. Horn,et al.  Determining Optical Flow , 1981, Other Conferences.

[13]  Takeo Kanade,et al.  An Iterative Image Registration Technique with an Application to Stereo Vision , 1981, IJCAI.

[14]  Dit-Yan Yeung,et al.  Convolutional LSTM Network: A Machine Learning Approach for Precipitation Nowcasting , 2015, NIPS.

[15]  K. Shadan,et al.  Available online: , 2012 .

[16]  Edwin S. T. Lai,et al.  Thunderstorm Downburst and Radar-based Nowcasting of Squalls , 2008 .

[17]  Lei Han,et al.  A Machine Learning Nowcasting Method based on Real-time Reanalysis Data , 2016, ArXiv.

[18]  I. Zawadzki,et al.  Scale-Dependence of the Predictability of Precipitation from Continental Radar Images. Part I: Description of the Methodology , 2002 .

[19]  Linus H.Y. Yeung,et al.  Lightning Initiation and Intensity Nowcasting based on Isothermal Radar Reflectivity—A Conceptual Model , 2007 .

[20]  A. Seed,et al.  STEPS: A probabilistic precipitation forecasting scheme which merges an extrapolation nowcast with downscaled NWP , 2006 .

[21]  Liping Liu,et al.  Application of multi-scale tracking radar echoes scheme in quantitative precipitation nowcasting , 2013, Advances in Atmospheric Sciences.

[22]  Wai-Kin Wong,et al.  An overview of nowcasting development, applications, and services in the Hong Kong Observatory , 2014, Journal of Meteorological Research.

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

[24]  Edwin S. T. Lai,et al.  Applications of the Hong Kong Observatory Nowcasting System Swirls-2 in Support of the 2008 Beijing Olympic Games , 2009 .

[25]  Wang-chun Woo,et al.  An Algorithm to Enhance Nowcast of Rainfall Brought by Tropical Cyclones through Separation of Motions , 2014 .

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

[27]  Miguel A. Rico-Ramirez,et al.  Quantitative assessment of short‐term rainfall forecasts from radar nowcasts and MM5 forecasts , 2012 .

[28]  I. Zawadzki,et al.  Scale Dependence of the Predictability of Precipitation from Continental Radar Images. Part II: Probability Forecasts , 2004 .

[29]  Harold E. Brooks,et al.  Verification of Nowcasts from the WWRP Sydney 2000 Forecast Demonstration Project , 2004 .

[30]  Timo Kohlberger,et al.  Universität Des Saarlandes Fachrichtung 6.1 – Mathematik Variational Optic Flow Computation in Real-time Variational Optic Flow Computation in Real-time , 2022 .

[31]  M. C. Wong,et al.  Reprint 673 Application of Rainstorm Nowcast to Real-time Warning of Landslide Hazards in Hong Kong , 2006 .

[32]  Adrian J. Saul,et al.  Comparing quantitative precipitation forecast methods for prediction of sewer flows in a small urban area , 2014 .

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

[34]  P. Cheung,et al.  Reprint 1025 Application of optical-flow technique to significant convection nowcast for terminal areas in Hong Kong , 2012 .

[35]  C. Doswell,et al.  On Summary Measures of Skill in Rare Event Forecasting Based on Contingency Tables , 1990 .

[36]  T. Keenan The World Weather Research Programme (WWRP) Sydney 2000 Forecast Demonstration Project: Overview , 2001 .

[37]  G. P. Cressman AN OPERATIONAL OBJECTIVE ANALYSIS SYSTEM , 1959 .

[38]  Jungho Im,et al.  Detection of deterministic and probabilistic convection initiation using Himawari-8 Advanced Himawari Imager data , 2016 .