1 / 17

Teolo radar viewed from weather station

erek
Download Presentation

Teolo radar viewed from weather station

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Applications of the McGill Algorithm for Precipitation Nowcasing Using Semi-Lagrangian Extrapolation (MAPLE) within the ARPAV HydoMet Decision Support SystemBill Conway1, Dr Gabriele Formentini2, Chip Barrere1, Dr Luciano Lago21Weather Decision Technologies, Norman, Oklahoma, USA 2Environmental Protection and Prevention Agency Veneto Region, Centro Meteorological, Teolo, Italy WSN05, Toulouse, France

  2. Teolo radar viewed from weather station WSN05, Toulouse, France

  3. View of Teolo towards Venice from weather station WSN05, Toulouse, France

  4. Presentation Background • WDT has worked with ARPAV in Italy to provide a HydroMet Decision Support System (HDSS) • HDSS contains technologies developed by WDT, the National Severe Storms Laboratory, McGill University of Montreal, Canada, and the Oklahoma Climate Survey • HDSS integrates numerous data sources and contains algorithms that provide the following functionality: • Storm centroid tracking, analysis, and prediction • Storm area tracking and prediction (MAPLE) • Rainfall prediction using MAPLE • Hail detection and prediction • Circulation prediction and detection • Quantitative Precipitation Estimation Using Multiple Sensors • Web based display – WxScope • three dimensional workstation display – 3D Sigma • This paper concentrates on application of the MAPLE algorithm and its applications with the ARPAV HDSS to reflectivity forecasting and rainfall prediction WSN05, Toulouse, France

  5. HDSS Web Page Example WSN05, Toulouse, France

  6. MAPLE - Briefly • Developed at McGill University, Montreal, Canada by Zawadski and Germann over a period of several years • Provides forecasts of reflectivity out to 8 hours depending on scale predictablity • Uses prior image history to forecast reflectivity out to 8 hrs in advance using stream function analysis • Determines the changing scale of predictability using past images compared to current image though wavelet analysis • Filters non-predictable scales from the T=0 analysis • Deduces stream functions for predictable scales and uses those stream functions to forecast radar reflectivity location and intensity • Current research includes integration of numerical model data for applications towards storm growth and decay • WDT has developed software to run MAPLE in real-time for commercial applications and also to provide radar based QPF WSN05, Toulouse, France

  7. Example Vector Derivation WSN05, Toulouse, France

  8. C a n a d a >8h 5.5h 1.5h Gulf of Mexico Example of Scale Predicability Scale predictability determined by comparison of previous forecasts with current images. Scales are removed in the forecast after exceeding their derived “predictability” flag WSN05, Toulouse, France

  9. Example 4 hr Precip Type Forecast WSN05, Toulouse, France

  10. Hybrid Scanning Grey – data from 1st elevation Yellow – data from 2nd elevation Orange – data from 3rd elevation WSN05, Toulouse, France

  11. Hybrid Scan Example WSN05, Toulouse, France

  12. MAPLE Applications to QPF • Uses output from QPE-SUMS as “T0” input for MAPLE • Applies a Z-R or Z-S relationship to each 5 min MAPLE time step based on surface temperature and whether stratiform or convective • Will apply a bias correction at each time step based on QPESUMS radar to gauge correction* • Accumulates total rainfall forecasts at each grid point across the MAPLE domain WSN05, Toulouse, France

  13. Objective Analysis of Rain Gauge Data WSN05, Toulouse, France

  14. Example of variable Z-R/Z-S Relationships WSN05, Toulouse, France

  15. 1 Hr MAPLE Hybrid Forecast WSN05, Toulouse, France

  16. MAPLE 2 hr Accumulation WSN05, Toulouse, France

  17. Future Work • McGill continuing to work on model integration and storm growth/decay for MAPLE improvements • Correct Italian data for beam blockage • Integrate further radars from Italy network as they become available • Develop software for real-time statistical analysis of MAPLE performance • Optimize the Z-R and Z-S relationships used in the northern Italy region • Use basin delineation and flash flood guidance with MAPLE QPF results to provide a Flash Flood Prediction Algorithm Merci! Grazie! Thanks! Ciao! WSN05, Toulouse, France

More Related