pqpf: theory and operational use
DESCRIPTION
PQPF: THEORY AND OPERATIONAL USE. Theresa Rossi NOAA/NWS Pittsburgh, PA. Presented at Hydromet 00-2 Monday, 28 February 2000. OVERVIEW. Probabilistic Hydrometeorological System PQPF Methodology Interactive PQPF Software Probabilistic Reasoning PQPF Case Study - PowerPoint PPT PresentationTRANSCRIPT
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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
ProbabilisticProbabilistic QuantitativeQuantitative PrecipitationPrecipitation
Forecasting SystemForecasting SystemPQPFPQPF
WFO
To improve the reliability and lead time of flood warnings.To improve the reliability and lead time of flood warnings.
Probabilistic River StageProbabilistic River Stage Forecasting SystemForecasting System
PRSFPRSF
River FloodRiver FloodWarning SystemWarning System
RFIRFI
USERSUSERS
RFC
WFO
Probabilistic RSFs
Flood Watches & Warnings
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FORECASTFORECASTMETHODOLOGYMETHODOLOGY
LOCALLOCALCLIMATICCLIMATIC
DATADATA
FORECAST FORECAST VERIFICATIONVERIFICATION
THE PQPF SYSTEM
WFOWFO
RFCRFC
GUIDANCEGUIDANCE
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PQPF METHODOLOGY
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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
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CONDITIONAL EXCEEDANCE FUNCTIONW = 24-hour Basin Average Precipitation Amount
0
0.25
0.5
0.75
1
50% CREDIBLE INTERVAL
ww
(P W>w|W>0)(P W>w|W>0)
X75 - 75% FractileX50 - 50% FractileX25 - 25% Fractile
Conditional Probability
X75 X50 X25
calculated
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ASSESSMENT OF CONDITIONAL EXCEEDANCE FRACTILES
X50
Judgments of equally likely events
X25
ACTUAL PRECIPITATION W
HYPOTHESIS: X50 <WACTUAL PRECIPITATION W
P(W>X25 |W >0)=.25
P(W>X50 |W>0)=.50
HYPOTHESIS: 0<W
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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
13%
17%57%
13% z1z2Z3Z4
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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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NMC NUMERICAL
MODELS
TDL MODEL OUTPUT STATISTICSNMC MANUAL GUIDANCE
LOCALSUBJECTIVE ANALYSIS
REVIEW-MODEL ASSESSMENT/COMPARISON
-GUIDANCE REVIEW
ISPRECIP
PROBABLE?
STOP
ISSIGNIFICANT
AMOUNTPROBABLE?
FURTHUR ANALYSIS-MODEL OUTPUTS-LOCAL ANALYSIS
WHAT IS PREDICTABILITY OF
PATTERN?
WHAT ISPREDICTABILITY OF
PATTERN
LIMITEDFURTHER ANALYSIS
-FOLLOW CLOSELYLOCAL ADJUSTMENTS
TO GUIDANCE-LARGE UNCERTAINTY
-FOLLOW CLOSELYGUIDANCE WITH MINORLOCAL ADJUSTMENTS
-SMALLER UNCERTAINTY
-MIX GUIDANCE WITH LOCAL
ADJUSTMENTS-LARGER UNCERTAINTY
-FOLLOW GUIDANCECLOSELY
-SMALLERUNCERTAINTY
LOCAL CLIMATOLOGICALGUIDANCE
INTEGRATIONEXPERT KNOWLEDGE OF
LOCAL HYDROMETINFLUENCES
OBSERVATIONS
NO
YES
YES NO
LOW
HIGH
LOW HIGH
WORKING QPF
POSTERIOR QPF
RE
VIE
WD
EV
EL
OPM
EN
TA
DJU
ST
ME
NT
INT
EG
RA
TIO
N
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MAKING A PQPF
DEVELOPMENDEVELOPMENTT
REVIEWREVIEW
ADJUSTMENADJUSTMENTT
INTEGRATIONINTEGRATION
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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 Agree…confidence is increased.• If Not…uncertainty decreases confidence.
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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.
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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.
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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
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PQPF CASE STUDYWell Organized Frontal System
May18-19,1999
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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 high…local analysis corroborated
guidance/uncertainty smaller
• “Working PQPF”…includes amounts & uncertainties
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THE INTEGRATION PHASE Case Study May 18-19, 1999
• Integrate “Working PQPF”, local influences & LCG
• Uncertainty small…tend toward “Working PQPF”
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24hour POP24hour POP
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X50X50
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X50X50
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X25X25
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X25X25
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X75X75
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X75X75
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T50
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T50
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Z1Z1
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Z1Z1
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Z2Z2
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Z3Z3
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Z4Z4
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Summary of Case Study May 18-19, 1999Well Organized Frontal System
• Precipitation probable & significant.
• Predictability of pattern high…models in agreement. Analysis corroborate guidance.
• Convective nature, spatially variable, localized higher amounts possible.
• Uncertainty reflected in wide credible interval.
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WFOWFOMosaicMosaic
Stage 3Stage 3PrecipPrecip(actual)(actual)
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Summary of Case Study May 18-19, 1999Monongahela River Basin
24-h period ending 1200 UTC 5/19/99
Exceedance Fractiles Expected Fractions(inches) (%)
X75 X50 X25Z1 Z2 Z3 Z4
PQPF .54 1.10 2.00 10 30 50 10
LCG* .34 0.47 0.74 28 20 2131
*LCG estimates are conditioned on a minimum of 0.25 inches.
ACTUAL 0.31 0 7 93 0
PoP = 100%
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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