1 / 34

Using Meteorological Model Ensembles to Generate Short Term Hydrologic Ensembles

A joint project of the 3 Eastern Region RFCs. Using Meteorological Model Ensembles to Generate Short Term Hydrologic Ensembles. Project Origins (NERFC). Contingency forecasts are time consuming to generate and rarely accurate

enan
Download Presentation

Using Meteorological Model Ensembles to Generate Short Term Hydrologic Ensembles

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 joint project of the 3 Eastern Region RFCs Using Meteorological Model Ensembles to Generate Short Term Hydrologic Ensembles

  2. Project Origins (NERFC) • Contingency forecasts are time consuming to generate and rarely accurate • Longer term ensembles (30-90 day AHPS plots) do not meet the needs of most users in the East • Assist in Flood Outlook Product production

  3. Question • Can we use atmospheric model ensembles to drive short-term (1-7) day probabilistic hydrologic forecasts?

  4. Original Proposal (NERFC) Use the Global Ensemble Forecast System (GEFS) precip and surface temperature individual members that are available on AWIPS as input traces for driving hydrologic model GEFS selected because: Individual members available on AWIPS, not just mean/spread Long enough time horizon available to provide enhanced information for FOP use

  5. Revised Proposal • MMEFS – Met Model-based Ensemble Forecast System • Add other met ensembles • SREF, Mesoscale (WRF, MM5)*, NCEP GEFS*, CMCE* • * - MARFC Initially • Generalize system • Portable, adaptable • Utilize local 64-bit processing (ER-provided) • AWIPS only and AWIPS/64-bit hybrid • Add’l Products • Objective FOP, text probabilities, combine results of multiple ensemble inputs where possible

  6. NWP Models AWIPS GEFS – 12 members (2x/day, avail. +6) SREF – 21 members (4x/day, Syn+3, avail +6) NCEP GEFS – 21 members (4x/day, avail +6) CMCE – 21 members (2x/day, avail +8?) WRF - ??? Members (1x/day, avail +14) Up to 12 for SUNY project (MARFC only)

  7. Procedure • De-grib individual member, time step, data type • Use GRASS to convert grid point values to MAP/MAT • Post MAP/MAT to database • Generate Datacard files • Run ESP, ESPADP, local applications • Note: Each met ensemble system analyzed separately*

  8. Products Baseline, ESPADP derived Traces, expected values, probability histograms New to project Tabular probability levels (NERFC) Objective FOP (NERFC/OHRFC) Combined system expected value plots (OHRFC)

  9. ESPADP derived (SREF)

  10. ESPADP derived (SREF)

  11. ESPADP derived (SREF)

  12. ESPADP derived (SREF)

  13. ESPADP derived (SREF)

  14. ESPADP derived (SREF)

  15. ESPADP derived (GEFSA)

  16. ESPADP derived (GEFSA)

  17. ESPADP derived (SUNY)

  18. ESPADP derived (SUNY)

  19. Well???

  20. Text Products (New) ... GFS Ensemble Run : 04 / 09 / 2008 00 Z ACTION MINOR MODERATE MAJOR Stg Pct Stg Pct Stg Pct Stg Pct COHN6 17.0 25% 20.0 <5% 21.0 <5% 22.0 <5% EAGN6 9.0 16% 11.0 <5% 12.0 <5% 16.0 <5% FLVC3 6.0 15% 7.0 <5% 10.0 <5% 15.0 <5% FTEN6 24.0 95% 26.0 95% 27.0 95% 29.0 74% GAYC3 7.0 15% 8.0 <5% 10.0 <5% 15.0 <5% HDYN6 9.0 95% 14.0 95% 17.0 81% 19.0 61% HOPN6 6.0 95% 7.0 95% 9.0 27% 10.0 <5% KASN6 5.0 95% 6.0 95% 7.0 77% 8.0 30% LTLN6 13.0 95% 15.0 58% 17.0 23% 18.0 14% MCKN6 10.0 95% 12.0 43% 13.0 23% 15.0 <5% MRNN6 18.0 <5% 20.0 <5% 22.0 <5% 24.0 <5% MTRN6 8.0 <5% 11.0 <5% 15.0 <5% 18.0 <5% NCKN6 8.0 95% 10.0 84% 11.0 64% 12.0 25% PTVN6 9.0 <5% 12.0 <5% 14.0 <5% 16.0 <5% ROSN6 14.0 <5% 18.0 <5% 21.0 <5% 23.0 <5% RVRN6 6.0 95% 7.0 95% 8.5 95% 9.0 95%

  21. FOP (New)

  22. Combined Plots (New)

  23. AWIPS GEFS Grid

  24. NCEP GEFS Grid

  25. SREF Grid

  26. WRF 12 km Grid

  27. Downscaling

  28. Downscaling (12 km)

  29. Downscaling (12 km)

  30. Sensitivity Analysis • SUNY, 12 km resolution, 48 hours • 1 pt ~800 secs • 1pt w/ -n ~1540 secs • 4pt ~2620 secs • 4pt w/ -n ~3250 secs • Max MAP diff for 48 hour duration among all methods: • .013” out of 1.3” MAP

  31. Status • NERFC • Original system • AWIPS GEFS only (2x/day, 1 hr process time) • HTML, graphics, tabular (no FOP) • Internal ER FTP access for WFOs • OHRFC • Original system • AWIPS GEFS only (1x/day, 4 hr process time) • HTML, graphics, tabular, FOP • Internal ER FTP access for WFOs

  32. Status • MARFC • New system, hybrid AWIPS/64-bit • AWIPS GEFS, 2x/day (< 30 mins. per) • SREF, 4x/day (~90 mins. per) • SUNY WRF, 1x/day (15-20 mins. per) • Internal ER FTP access - 8/11 • 15-19 MB/system/cycle • HTML & graphics

  33. Issues and Questions • Will the limited (12-21) members provide a valid statistical sample? • Will the use of the met. ensembles provide sufficient spread to the hydrologic ensembles? • Is the grid resolution adequate to provide sufficient resolution of the basin average precip? • Does numerical downscaling provide proper detail and distribution? • Does this input provide an unbiased data set relative to our calibrated hydrologic models?

  34. Issues and Questions (cont’d) Differences between operational GFS solutions and GEFS (NERFC) Current ESP mechanics Need for input data to work on 12Z-12Z periods Reservoir operations Operational definition and ESP validity Delivery to WFOs 15-19 MB/system/cycle Effective operational use XEFS

More Related