Hydrometeorological Prediction Center HPC Experimental PQPF: Method, Products, and Preliminary Verification 1 David Novak HPC Science and Operations Officer.

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Presentation transcript:

Hydrometeorological Prediction Center HPC Experimental PQPF: Method, Products, and Preliminary Verification 1 David Novak HPC 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

Hydrometeorological Prediction Center 2 Learning 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

Hydrometeorological Prediction Center 3 Motivation Singled-value QPF is not the whole story

Hydrometeorological Prediction Center 4 Motivation 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, 2010Providence: March 30, 2010 Seattle: Jan 7, 2009

Hydrometeorological Prediction Center 5 Method

6 HPC 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 Probability QPF

Hydrometeorological Prediction Center 7 HPC “most likely” deterministic value Probability HPC 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

Hydrometeorological Prediction Center 8 HPC “most likely” deterministic value Probability HPC PQPF Method HPC PQPF provides full distribution consistent with the HPC deterministic forecast QPF

Hydrometeorological Prediction Center 9 Products

10 PQPF 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 10th90th 95th Probability QPF 25th75th 50th

Hydrometeorological Prediction Center 11 Web Products Probability of Exceedance

Hydrometeorological Prediction Center 12 Web Products Percentile

Hydrometeorological Prediction Center 13 Gridded Products Exceedance probabilities and percentile products available in grib2 format: ftp://ftp.hpc.ncep.noaa.gov/pqpf/conus/pqpf_6hrftp://ftp.hpc.ncep.noaa.gov/pqpf/conus/pqpf_6hr Gridded percentile products for hydrologic applications HPC Percentile AWIPS GFE Hydrologic Model 24 h48 h 60 h RFC *

Hydrometeorological Prediction Center 14 Applications Probabilistic and contingency hydrologic modeling Graphics for use in decision support briefings Situational awareness of reasonable worst case scenarios

Hydrometeorological Prediction Center 15 Tennessee Example 12 UTC 1 May – 12 UTC 3 May ObservedHPC Deterministic (Issued 12 UTC 1 May)

Hydrometeorological Prediction Center 16 Tennessee Example 12 UTC 1 May – 12 UTC 3 May Observed95th percentile

Hydrometeorological Prediction Center 17 Preliminary Verification

Hydrometeorological Prediction Center 18 Preliminary 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

Hydrometeorological Prediction Center 19 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 Verification Day 1 Brier Skill Score

Hydrometeorological Prediction Center 20 No Skill Perfect 0.25” Reliability Preliminary Verification 0.50” Reliability Feb 1 - May 15, 2010

Hydrometeorological Prediction Center 21 Summary 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:

Hydrometeorological Prediction Center 22 Resources Webpage Description: Charba, 2009: Hi-res gridded MOS 6-h QPF guidance. 23 rd Conf on Wea. Analysis and Forecasting/19 th 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,