hydrometeorological prediction center hpc experimental pqpf: method, products, and preliminary...
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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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Hydrometeorological Prediction Center2
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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Hydrometeorological Prediction Center3
MotivationMotivation
Singled-value QPF is not the whole story
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Hydrometeorological Prediction Center4
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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Hydrometeorological Prediction Center5
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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Hydrometeorological Prediction Center7
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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Hydrometeorological Prediction Center8
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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Hydrometeorological Prediction Center9
ProductsProducts
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Hydrometeorological Prediction Center10
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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Hydrometeorological Prediction Center11
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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Hydrometeorological Prediction Center13
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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Hydrometeorological Prediction Center14
ApplicationsApplications
Probabilistic and contingency hydrologic modeling
Graphics for use in decision support briefings
Situational awareness of reasonable worst case scenarios
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Hydrometeorological Prediction Center15
Tennessee ExampleTennessee Example12 UTC 1 May – 12 UTC 3 May
Observed HPC Deterministic(Issued 12 UTC 1 May)
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Hydrometeorological Prediction Center16
Tennessee ExampleTennessee Example12 UTC 1 May – 12 UTC 3 May
Observed 95th percentile
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Hydrometeorological Prediction Center17
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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Hydrometeorological Prediction Center20
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: [email protected]
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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.