PQPF: THEORY AND OPERATIONAL USE

1. PQPF: THEORY AND OPERATIONAL USE Theresa Rossi NOAA/NWS Pittsburgh, PA Presented at Hydromet 00-2 Monday, 28 February 2000

2. OVERVIEW • Probabilistic Hydrometeorological System • PQPF Methodology • Interactive PQPF Software • Probabilistic Reasoning • PQPF Case Study • River Forecast Interface

3. NWS End-to-End Probabilistic Risk Reduction • Define AWIPS-compatible PQPF/PRSF methodologies, PQPF guidance, and public product formats. • Approach is grid-based and benefits from HPC, TDL and OH input. • 1998-2000. With funding, similar Risk Reductions in other Regions after 2001. • UVA/PBZ/RLX/OHRFC/TDL/HPC/OH/ OM • Users (County EMA & Barge Industry)

4. PROBABILISTIC HYDROMETEOROLOGICAL FORECASTING SYSTEM To improve the reliability and lead time of flood warnings. WFO RFC ProbabilisticQuantitative Precipitation Forecasting System PQPF Probabilistic River Stage Forecasting System PRSF WFO River Flood Warning System RFI Probabilistic RSFs USERS Flood Watches & Warnings

5. THE PQPF SYSTEM GUIDANCE WFO FORECAST METHODOLOGY RFC LOCAL CLIMATIC DATA FORECAST VERIFICATION

6. PQPF METHODOLOGY

7. PQPFTOTAL AMOUNT • Precipitation amount accumulated during a period: W • Probability of Precipitation: PoP=P(W>0) • Conditional Exceedance Fractiles of Amount: • P(W>X25|W>0)=0.25 • P(W>X50|W>0)=0.50

8. ConditionalProbability calculated X75 X50 X25

9. ASSESSMENT OF CONDITIONAL EXCEEDANCE FRACTILES Judgments of equally likely events HYPOTHESIS: 0<W ACTUAL PRECIPITATION W X50 • HYPOTHESIS: X50 <W ACTUAL PRECIPITATION W X25 P(W>X25 |W>0)=.25 P(W>X50 |W>0)=.50

10. PQPFTemporal Disaggregation • Precipitation amount during subperiod i: Wi • Expected subamounts: mi=E(Wi|W>0); i=1,2,3,4;12,34 • Expected fractions: zi=E(Wi/W|W>0); i=1,2,3,4;12,34

11. INTERACTIVE SOFTWARE FOR PROBABILISTIC QUANTITATIVE PRECIPITATION FORECASTING

12. Purpose • Aids field forecasters in preparing PQPFs. • Provides crucial input to Probabilistic River Stage Forecast System. • Prototype Testing • Weather Service Forecast Offices • Pittsburgh, PA • Charleston, WV

23. PROBABILISTIC REASONING

24. SCHEME FOR JUDGMENTAL PROCESSING OF INFORMATION INTO PQPF

25. OBSERVATIONS LOCAL SUBJECTIVE ANALYSIS TDL MODEL OUTPUT STATISTICS NMC MANUAL GUIDANCE NMC NUMERICAL MODELS REVIEW REVIEW -MODEL ASSESSMENT/COMPARISON -GUIDANCE REVIEW IS PRECIP PROBABLE? NO STOP YES IS SIGNIFICANT AMOUNT PROBABLE? HIGH FURTHUR ANALYSIS -MODEL OUTPUTS -LOCAL ANALYSIS YES NO WHAT IS PREDICTABILITY OF PATTERN? DEVELOPMENT LOW WHAT IS PREDICTABILITY OF PATTERN LIMITED FURTHER ANALYSIS HIGH LOW -FOLLOW GUIDANCE CLOSELY -SMALLER UNCERTAINTY -FOLLOW CLOSELY LOCAL ADJUSTMENTS TO GUIDANCE -LARGE UNCERTAINTY -FOLLOW CLOSELY GUIDANCE WITH MINOR LOCAL ADJUSTMENTS -SMALLER UNCERTAINTY ADJUSTMENT -MIX GUIDANCE WITH LOCAL ADJUSTMENTS -LARGER UNCERTAINTY WORKING QPF EXPERT KNOWLEDGE OF LOCAL HYDROMET INFLUENCES INTEGRATION LOCAL CLIMATOLOGICAL GUIDANCE INTEGRATION POSTERIOR QPF

26. INTEGRATION MAKING A PQPF REVIEW • DEVELOPMENT ADJUSTMENT

27. THE REVIEW PHASEExamine Observations and Guidance • Review Initial Conditions • Diagnose past/current conditions, trends andhow well models initialized. • Compare Model Outputs • If Agree…confidence is increased. • If Not…uncertainty decreases confidence.

28. THE DEVELOPMENT PHASEJudge Likelihood/Predictability of Precipitation • Ask three questions: • Is precipitation probable? • Is a significant amount probable? • What is predictability of pattern? • No significant amount & predictability: • high…more confidence in guidance. • low…less confidence/further analysis • Significant amount…further analysis.

29. THE ADJUSTMENT PHASEAdjust Guidance/Ascertain Uncertainty • Nonsignificant Event • Predictability high…follow guidance/uncertainty smaller. • Predictability low…may adjust guidance/ uncertainty larger. • Significant Event • Predictability high…local analysis should corroborate guidance/uncertainty smaller. • Predictability low…extensive use of analysis, may significantly adjust guidance/uncertainty larger. • “Working PQPF”…includes amounts & uncertainties.

30. THE INTEGRATION PHASE“Working PQPF” Integrated with LCG • Integrate Information From: • “Working PQPF” • Knowledge of local influences • Local Climatic Guidance (LCG) • Uncertainty small…tend toward “Working PQPF” • Uncertainty large…tend toward LCG

31. PQPF CASE STUDYWell Organized Frontal SystemMay18-19,1999

32. THE REVIEW PHASECase Study May 18-19, 1999 • Examine Observations and Guidance • 00Z 5/18/99 ETA Model • Models initialized well & in agreement • confidence increased

46. THE DEVELOPMENT PHASECase Study May 18-19, 1999 • Judge Likelihood/Predictability of Precipitation • A significant amount of precipitation probable • Predictability of pattern is high • Models in agreement on speed & movement of system • Precipitation of convective nature & spatially variable with localized higher amounts possible

47. THE ADJUSTMENT PHASECase Study May 18-19, 1999 • Adjust guidance/Ascertain Uncertainty • Significant Event • Predictability high…local analysis corroborated guidance/uncertainty smaller • “Working PQPF”…includes amounts & uncertainties

48. THE INTEGRATION PHASECase Study May 18-19, 1999 • Integrate “Working PQPF”, local influences & LCG • Uncertainty small…tend toward “Working PQPF”

49. 24hour POP

50. X50