Hydrometeorological Prediction Center

HPC Experimental PQPF:HPC Experimental PQPF:Method, Products, and Preliminary VerificationMethod, Products, and Preliminary Verification

1

David NovakHPC Science and Operations Officer

Based on work by: Keith Brill (Technique)

Chris Bailey (Product Generation)Mark Klein (Web Design)

Additional contributions from Ed Danaher, Robert Kelly, and Mike Eckert

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Learning ObjectivesLearning Objectives

At the end of this module, you will be able to:

•Explain the method used to generate the HPC PQPF

•List two experimental HPC PQPF products

•Identify at least one way in which the PQPF product can be used in your operations

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MotivationMotivation

Singled-value QPF is not the whole story

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MotivationMotivation

Recent high-profile flood events highlight the need for expressing and quantifying low probability, yet high impact events.

Atlanta: Sept. 21, 2009

Nashville: May 1, 2010 Providence: March 30, 2010

Seattle: Jan 7, 2009

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MethodMethod

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HPC PQPF MethodHPC PQPF Method

Based on Bi-Normal Method – Toth and Szentimrey (1990)

Modifies ensemble distribution such that HPC deterministic QPF is the mode, while allowing skew

Ensemble Spread(SREF+GEFS+NAM+GFS+ECMWF)

HPC “most likely” deterministic value

Pro

bab

ility

QPF

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HPC “most likely” deterministic value

Pro

bab

ility

HPC PQPF MethodHPC PQPF Method

Modifies ensemble distribution such that HPC deterministic QPF is the mode, while allowing skew

Based on Bi-Normal Method – Toth and Szentimrey (1990)

QPF

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HPC “most likely” deterministic value

Pro

bab

ility

HPC PQPF MethodHPC PQPF Method

HPC PQPF provides full distribution consistent with the HPC deterministic forecast

QPF

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ProductsProducts

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PQPF at HPCPQPF at HPC

PQPF available in 6 h increments out to 72 h

•Probability of Exceedance

•Percentile

Available in graphical (web) and gridded format (ftp)

Products updated synchronously with issuance of HPC deterministic QPF

5th 10th 90th95thP

rob

abili

ty

QPF

25th 75th

50th

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Web ProductsWeb ProductsProbability of ExceedanceProbability of Exceedance

http://www.hpc.ncep.noaa.gov/pqpf_6hr/conus_hpc_pqpf_6hr.php

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http://www.hpc.ncep.noaa.gov/pqpf_6hr/conus_hpc_pqpf_6hr.php

Web ProductsWeb ProductsPercentilePercentile

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Gridded ProductsGridded Products

Exceedance probabilities and percentile products available in grib2 format: ftp://ftp.hpc.ncep.noaa.gov/pqpf/conus/pqpf_6hr

Gridded percentile products for hydrologic applications

HPC Percentile

AWIPS

GFE

Hydrologic Model

24 h 48 h 60 hRFC

*

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ApplicationsApplications

Probabilistic and contingency hydrologic modeling

Graphics for use in decision support briefings

Situational awareness of reasonable worst case scenarios

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Tennessee ExampleTennessee Example12 UTC 1 May – 12 UTC 3 May

Observed HPC Deterministic(Issued 12 UTC 1 May)

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Tennessee ExampleTennessee Example12 UTC 1 May – 12 UTC 3 May

Observed 95th percentile

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Preliminary VerificationPreliminary Verification

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Preliminary VerificationPreliminary Verification

• Four Methods considered:- HPC PQPF

- SREF uncalibrated relative frequency

- MDL High-Res QPF MOS (Charba 2009)

- Tulsa Method applied to HPC QPF (Amburn and Frederick 2006)

• 6 h PQPF at F12 and F24 verified over CONUS using RFC Stage IV (MPE) analysis (remapped to 32 km)

• Skill quantified in terms of Brier Skill Score and Reliability (relative to sample climatology)

IMPORTANT CAVEATS• Short period: February 1 – May 15, 2010• Mainly Spring season• Over CONUS• Verification continuing

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Feb 1 - May 15, 2010

•HRMOS and Tulsa approaches best at lower thresholds while HPC best at higher thresholds

•HPC generally has higher score than ensemble

Preliminary VerificationPreliminary Verification

Day 1 Brier Skill Score

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No Skill

Perfe

ct

0.25” Reliability

Preliminary VerificationPreliminary Verification

0.50” Reliability

Feb 1 - May 15, 2010

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SummarySummary

•HPC issuing experimental Probabilistic QPF

•Modifies ensemble distribution such that HPC deterministic QPF is the mode

•Graphical and gridded probability of exceedance and percentile products available

•Preliminary verification shows that the product is at least as skillful as ensemble guidance

•Additional adjustments to method and product format may be made

•Interested in your feedback: Edwin.Danaher@noaa.gov

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ResourcesResources

•Webpage Description: http://www.hpc.ncep.noaa.gov/pqpf_6hr/navigating_6hr_pqpf.shtml

•Charba, 2009: Hi-res gridded MOS 6-h QPF guidance. 23rd Conf on Wea. Analysis and Forecasting/19th Conf on NWP, 17B.2, Omaha, NE, AMS

•Amburn, S., and J. Frederick, 2006: Probabilistic quantitative precipitation forecasting. P2.21, 18th Conf. on Probability and Statistics, Atlanta, GA, Amer. Meteor. Soc.

•Toth, Z., and T. Szentimrey, 1990: The binormal distribution: A distribution for representing asymmetrical but normal-like weather elements. J. Climate, 3, 128-136.