PQPF: THEORY AND OPERATIONAL USE

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PQPF THEORY AND OPERATIONAL USE

• Theresa Rossi
• NOAA/NWS Pittsburgh, PA

Presented at Hydromet 00-2 Monday, 28 February
2000
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OVERVIEW

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

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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)

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PROBABILISTIC HYDROMETEOROLOGICAL FORECASTING
SYSTEM
To improve the reliability and lead time of flood
warnings.
WFO
RFC
Probabilistic Quantitative Precipitation
Forecasting System PQPF
Probabilistic River Stage Forecasting
System PRSF
WFO
River Flood Warning System RFI
Probabilistic RSFs
USERS
Flood Watches Warnings
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THE PQPF SYSTEM
GUIDANCE
WFO
FORECAST METHODOLOGY
RFC
LOCAL CLIMATIC DATA
FORECAST VERIFICATION
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PQPF METHODOLOGY
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PQPFTOTAL AMOUNT

• Precipitation amount accumulated during a period
  W
• Probability of Precipitation PoPP(Wgt0)
• Conditional Exceedance Fractiles of Amount
• P(WgtX25Wgt0)0.25
• P(WgtX50Wgt0)0.50

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Conditional Probability
calculated
X75
X50
X25
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ASSESSMENT OF CONDITIONAL EXCEEDANCE FRACTILES
Judgments of equally likely events
HYPOTHESIS 0ltW
ACTUAL PRECIPITATION W
X50
HYPOTHESIS X50 ltW
ACTUAL PRECIPITATION W
X25
P(WgtX25 W gt0).25 P(WgtX50 Wgt0).50
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PQPFTemporal Disaggregation

• Precipitation amount during subperiod i Wi
• Expected subamounts miE(WiWgt0)
  i1,2,3,412,34
• Expected fractions ziE(Wi/WWgt0)
  i1,2,3,412,34

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INTERACTIVE SOFTWARE FOR PROBABILISTIC
QUANTITATIVE PRECIPITATION FORECASTING
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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

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PROBABILISTIC REASONING
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SCHEME FOR JUDGMENTAL PROCESSING OF
INFORMATION INTO PQPF
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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
WHAT IS PREDICTABILITY OF PATTERN?
YES
NO
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
-MIX GUIDANCE WITH LOCAL ADJUSTMENTS -LARGER
UNCERTAINTY
ADJUSTMENT
WORKING QPF
EXPERT KNOWLEDGE OF LOCAL HYDROMET INFLUENCES
INTEGRATION
LOCAL CLIMATOLOGICAL GUIDANCE
INTEGRATION
POSTERIOR QPF
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MAKING A PQPF
REVIEW
DEVELOPMENT
ADJUSTMENT
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THE REVIEW PHASEExamine Observations and Guidance

• Review Initial Conditions
• Diagnose past/current conditions, trends and how
  well models initialized.
• Compare Model Outputs
• If Agreeconfidence is increased.
• If Notuncertainty decreases confidence.

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THE DEVELOPMENT PHASEJudge Likelihood/Predictabil
ity of Precipitation

• Ask three questions
• Is precipitation probable?
• Is a significant amount probable?
• What is predictability of pattern?
• No significant amount predictability
• highmore confidence in guidance.
• lowless confidence/further analysis
• Significant amountfurther analysis.

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THE ADJUSTMENT PHASEAdjust Guidance/Ascertain
Uncertainty

• Nonsignificant Event
• Predictability highfollow guidance/uncertainty
  smaller.
• Predictability lowmay adjust guidance/
  uncertainty larger.
• Significant Event
• Predictability highlocal analysis should
  corroborate guidance/uncertainty smaller.
• Predictability lowextensive use of analysis, may
  significantly adjust guidance/uncertainty larger.
• Working PQPFincludes amounts uncertainties.

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THE INTEGRATION PHASEWorking PQPF Integrated
with LCG

• Integrate Information From
• Working PQPF
• Knowledge of local influences
• Local Climatic Guidance (LCG)
• Uncertainty smalltend toward Working PQPF
• Uncertainty largetend toward LCG

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PQPF CASE STUDYWell Organized Frontal
SystemMay18-19,1999
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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

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THE DEVELOPMENT PHASE Case 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
  

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THE ADJUSTMENT PHASE Case Study May 18-19, 1999

• Adjust guidance/Ascertain Uncertainty
• Significant Event
• Predictability highlocal analysis corroborated
  guidance/uncertainty smaller
• Working PQPFincludes amounts uncertainties

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THE INTEGRATION PHASE Case Study May 18-19, 1999

• Integrate Working PQPF, local influences LCG
• Uncertainty smalltend toward Working PQPF

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24hour POP
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X50
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X50
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X25
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X25
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X75
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X75
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T50
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T50
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Z1
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Z1
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Z2
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Z3
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Z4
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Summary of Case Study May 18-19, 1999Well
Organized Frontal System

• Precipitation probable significant.
• Predictability of pattern highmodels in
  agreement. Analysis corroborate guidance.
• Convective nature, spatially variable, localized
  higher amounts possible.
• Uncertainty reflected in wide credible interval.

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WFO Mosaic
Stage 3 Precip (actual)
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Summary of Case Study May 18-19,
1999Monongahela River Basin24-h period ending
1200 UTC 5/19/99
PoP 100
Expected Fractions
Exceedance Fractiles
(inches)
()
Z1 Z2 Z3 Z4
X75 X50 X25
PQPF .54 1.10 2.00
10 30 50 10
LCG
.34 0.47 0.74
28 20 21 31
ACTUAL
0.31
0 7 93 0
LCG estimates are conditioned on a minimum of
0.25 inches.
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RIVER FORECAST INTERFACE
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GRAPHICAL RIVER FORECAST INTERFACE

• Input - Probabilistic River Stage Forecasts
  (PRSF)
• Purpose
• Display PRSF
• Aid forecaster in deciding flood alarm
  (watch/warning)
• Communicate flood alarms to users
• Aid users in making decisions based on PRSF

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SUMMARY

• Provided overview of Probabilistic
  Hydrometeorological Forecasting System
• Focused on PQPF
• Methodology
• Interactive Software
• Probabilistic Reasoning
• Demonstrated concepts with May18-19, 1999 Case
  Study