High-Resolution Gridded MOS (HRMOS) QPF Guidance: Part I – Description of Products

1. High-Resolution Gridded MOS (HRMOS) QPF Guidance: Part I – Description of Products Jess Charba Fred Samplatsky Meteorological Development Laboratory OST / NWS / NOAA

2. Motivation for HRMOS QPF Model Predictive skill of model- and human-produced QPFs lags skill of other atmospheric variables and weather elements Recent availability of fine grid radar-based precipitation data offers potential for improved MOS-based gridded QPF guidance Improved guidance should exhibit improved spatial and intensity resolution

3. HRMOS QPF Model Basics Produces GFS-based MOS QPF guidance on a 2.5-km grid (4 km presently) for CONUS New QPF products contain better spatial and intensity resolution than other numerical and statistical model QPF guidance New QPF products exhibit equal or higher skill than comparable products HRMOS model issues conventional and new QPF products

4. HRMOS QPF Products 6- & 12-h QPFs to 192 hours on 2.5 km grid over CONUS Produced (experimentally) twice per day by 0530 and 1730 Z QPF products - Probabilities for precip thresholds - Categorical precip amount - Continuous precip amount (web scores at http://www.weather.gov/mdl/hrqpf/verif.php) - Prob-weighted precip amount

5. Probability (Prob) QPF Probs for eight 6-h precip thresholds which range from ≥ 0.01” to ≥ 2.00” For 12-h period probs issued only for 0.01” (POP) Probs decrease with increasing threshold and projection Probs are basic …other three QPF products are derived from them http://www.weather.gov/mdl/hrqpf/gridded.phpand example prob maps

6. ≥ 0.01 in. ≥ 0.25 in. 84-h Prob (%) for 18-00 z 18 Apr 2009 (Note scale chgs in these maps) ≥ 1.00 in. ≥ 2.00 in.

7. Categorical Precip (Cat) QPF Derived from probs along with pre-determined threshold probs - Prob thresholds vary by precip threshold, geography, and projection - Where prob thresholds are met for multiple precip thresholds, precip category selection algorithm applied to obtain Cat QPF Cat QPF has bias of ~ 1.2 (perfect bias = 1.0) for all precip thresholds and projections http://www.weather.gov/mdl/hrqpf/gridded.php and example maps of Cat QPF and Probs

8. Spatial pattern uniqueness for Cat QPF due to localized prob thresholds Cat QPF (in.) Prob (%) ≥ 0.25 in. 84-h Cat & Prob QPFs for 18-00 z 18 Apr 2009 Prob (%) ≥ 1.00 in. Prob (%) ≥ 2.00 in.

9. Continuous (Cont) QPF Derived from Cat QPF by “interpolating” between (bounded) categories and “extrapolating” above top category - use multi-variate algebraic formulae - variables are probs, prob thresholds, categorical precip bounds, max prob and upper bound for ≥ 2.00 in. category Max Cont QPF for 6-h period is 4.75 in. (7.0 in. for 12-h period) http://www.weather.gov/mdl/hrqpf/gridded.php and example maps of Cont and Cat QPF

10. Note: - spatial pattern similarity of Cont QPF to Cat QPF - extrapolation above top category Cont QPF (in.) 84-h QPFs for 18-00 z 18 Apr 2009 Cat QPF (in.)

11. Prob Weighted (ProbWt’d) QPF Computed from probs for bounded precip intervals (computed) and conditional means for precip intervals (pre-determined) Contains non-zero values where precip (of any intensity) is a threat Has tendency to spread low values over broad areas High values are generally much lower than for Cont QPF http://www.weather.gov/mdl/hrqpf/gridded.php and example maps of ProbWt’d, Prob, & Cont QPF

12. Prob Wt’d QPF shows: - spatial pattern similarity to Prob QPF - spatial pattern and magnitude contrasts to Cont QPF - lower peak values than Cont QPF and Obs Prob Wt’d QPF (in.) Prob (%) ≥ 0.25 in. 84-h QPFs & Obs for 18-00 z 18 Apr 2009 Cont QPF (in.) Obs (in.)

13. HRMOS QPF Strengths High spatial resolution in locations with local precip forcing, based on - hi-res precip climatology - hi-res topography Example

14. Note precip amt scale chg Prob (%) ≥ 0.50 in. Prob Wt’d QPF (in.) Cont QPF (in.) Obs (in.) 84-h QPFs & Obs for 18-00 z 05 Jan 2008

15. HRMOS QPF Strengths (Cont) High precip intensity resolution (for extra-tropical and tropical systems) due to - high precip thresholds - geographical regionalization of model - “smart” extrapolation of Cat QPF above top threshold Example

16. Extra-tropical 18-h QPF & Obs for 00-06 z 19 Mar 2008 Cont QPF (in.) Obs (in.) Extra-tropical &Tropical 72-h QPF & Obs for 06-12 z 13 Sep 2008 HUR. IKE

17. HRMOS QPF Strengths (Cont) Prob and ProbWt’d QPFs show high consistency across forecast projections and cycles

18. HRMOS QPF Weaknesses Probs drop off rapidly with increasing precip thresholds Cat and Cont QPFs tend to - fluctuate excessively across consecutive projections for a given cycle - fluctuate excessively across consecutive cycles for a given valid period - example / fix for problem in progress All QPF products tend to over-forecast heavy precip events in the northern US and under-forecast in the southern US All QPF products tend to under-forecast development of intense convection along southern flank of cold fronts Examples of over/under-prediction

19. 84-h QPF for 18-00 z 18 Apr 2009 Over-fcst in KS, NE Under-fcst E TX Cont QPF (in.) Obs (in.) 42-h QPF for 12-18 z 28 Mar 2009 Over-fcst in E TN Under-fcst S AL, GA Cont QPF (in.) Obs (in.)

20. Targeted Users of HRMOS Guidance NCEP/HPC WFOs RFCs External customers/partners

21. Real-time HRMOS QPF Availability Downloadable Grib2 files at http://www.weather.gov/mdl/hrqpf/ Graphical charts (including comparative QPF products) at same website Operational ingest into AWIPS is work in progress

22. Implementation Plan Replace and supplement GMOS QPF guidance over CONUS Operational deployment FY 2010

23. User Feedback Feedback alternatives at http://www.weather.gov/mdl/hrqpf/ - “Comments and Suggestions” link - “Contact Us” link - “Join the Mailing List” link Your constructive comments are welcome and appreciated

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