1 / 22

A Meso-Gamma Simulation of an Extreme Precipitation Event

A Meso-Gamma Simulation of an Extreme Precipitation Event. Mark Žagar Environmental Agency of Slovenia. EWGLAM 2005. A Convective Event. 500 hPa. 10-Oct-2004, 00 UTC. EWGLAM 2005. EWGLAM 2005. Evaluation. Different ways Radar (subjective) Point measurements Integrated quantities

tanika
Download Presentation

A Meso-Gamma Simulation of an Extreme Precipitation Event

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. A Meso-Gamma Simulation of an Extreme Precipitation Event Mark Žagar Environmental Agency of Slovenia EWGLAM 2005

  2. A Convective Event 500 hPa 10-Oct-2004, 00 UTC EWGLAM 2005

  3. EWGLAM 2005

  4. Evaluation • Different ways • Radar (subjective) • Point measurements • Integrated quantities • Area precipitation totals vs. river discharge EWGLAM 2005

  5. 1. Model vs. RADAR • Computed reflectivity of simulated raindrops: • Compare hourly pictures of Zm • Difficult to assess quantitatively the degree of confidence unless: • Very frequent model output (at least 15 minutes) • Generaly good temporal agreement EWGLAM 2005

  6. The Model • COAMPSTM • NH • Cloud resolving • Forced by the ECMWF analyses • or ECMWF forecast • Davies LBC EWGLAM 2005

  7. 3km 1km 9-Oct-2004 22 UTC EWGLAM 2005

  8. 9-Oct-2004 23 UTC 3km 1km EWGLAM 2005

  9. 10-Oct-2004 00 UTC 3km 1km EWGLAM 2005

  10. 10-Oct-2004 01 UTC 3km 1km EWGLAM 2005

  11. 10-Oct-2004 02 UTC 3km 1km EWGLAM 2005

  12. 2. Model vs. point observations • Typically not considered the best approach, especially at small scales • Don´t even try to compute skill scores on less than 6hrs basis • Point observations can be carried out much more frequently • Smaller volume of data • Enabling intelligent evaluations EWGLAM 2005

  13. 2. Model vs. point observations EWGLAM 2005

  14. In-Depth Diagnostics • Based on very frequent observations • Very frequent model output • For showers, compare: • variability • number • duration • separation • total volume EWGLAM 2005

  15. In-Depth Diagnostics 7 7 12 hours: OBS: RR=5.64 mm/h, =8.47 mm/h Mod: RR=5.08 mm/h, =5.78 mm/h 7 hours: OBS: RR=9.46 mm/h, =9.27 mm/h Mod: RR=7.50 mm/h, =6.42 mm/h EWGLAM 2005

  16. In-Depth Diagnostics 7 9 12 hours: OBS: RR=5.64 mm/h, =8.47 mm/h Mod: RR=5.08 mm/h, =6.06 mm/h 7 hours: OBS: RR=9.46 mm/h, =9.27 mm/h Mod: RR=7.53 mm/h, =6.89 mm/h EWGLAM 2005

  17. 2. Model vs. point observations Sensitivity to horizontal resolution EWGLAM 2005

  18. Sensitivity to horizontal resolution Integrated quantities Area precipitation totals and river discharge EWGLAM 2005

  19. 2. Model vs. point observations Sensitivity to lateral forcing EWGLAM 2005

  20. Sensitivity to horizontal resolution Integrated quantities Area precipitation totals and river discharge EWGLAM 2005

  21. Conclusions • A model can • Character of the rainfall • Peaks • Quite correct in number • Quite correct in duration • Quite correct in separation • Normally do not fade to zero • More sensitive to the LBC than to the initial conditions • Large scale information can be sufficient even for such a local event EWGLAM 2005

  22. Outlook • Repeat using ALADIN (AROME) • Construct additional forecast parameters EWGLAM 2005

More Related