Weather Prediction Center WPC Winter Weather Desk Operations

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Weather Prediction Center (WPC) Winter Weather Desk Operations Changes for 2017 - 2018 Season

Weather Prediction Center (WPC) Winter Weather Desk Operations Changes for 2017 - 2018 Season Dan Petersen Bruce Veenhuis Greg Carbin Mark Klein Mike Bodner February 23 -25, 2017

Weather Prediction Center (WPC) Winter Weather Desk Operations Outline • Describe changes in WPC

Weather Prediction Center (WPC) Winter Weather Desk Operations Outline • Describe changes in WPC snow & ice ensemble forecasts that go into Probabilistic Winter Precipitation Forecast generation (PWPF) • Explain why there was a decrease in the models used in the forecast • Explain changes in forecast generation and collaboration timelines • Describe use of WPC Watch Collaborator and new interface • Discuss 2016 -17 forecast verification for snow

Winter Weather Desk Overview (Internal Content) http: //www. wpc. ncep. noaa. gov/wwd/internal Deterministic 6

Winter Weather Desk Overview (Internal Content) http: //www. wpc. ncep. noaa. gov/wwd/internal Deterministic 6 -hour forecasts for snow/sleet & freezing rain Snow to liquid ratio grids & graphics Watch Collaborator maps and loops WPC/National Digital Forecast Database difference fields

Winter Weather Desk Overview (Public Content) http: //www. wpc. ncep. noaa. gov/ • 24

Winter Weather Desk Overview (Public Content) http: //www. wpc. ncep. noaa. gov/ • 24 -hr probabilities for snow/sleet & freezing rain computed from deterministic forecast and ensemble spread • Days 4 -7 probabilities for snow/sleet 0. 25” • Ensemble surface low tracks • Heavy snow/freezing rain discussion (QPFHSD)

2017 -18 Changes to Probabilistic Snow & Ice Forecasts http: //origin. wpc. ncep. noaa.

2017 -18 Changes to Probabilistic Snow & Ice Forecasts http: //origin. wpc. ncep. noaa. gov/wwd/winter_wx. shtml

Snow Verification Roebber Performance Diagram Frequency Bias = # of forecast events # of

Snow Verification Roebber Performance Diagram Frequency Bias = # of forecast events # of observed events s a i b h g i H b w o L s a i

Roebber Performance Diagram Threat Score = Hits + Misses + False Alarms

Roebber Performance Diagram Threat Score = Hits + Misses + False Alarms

 CONUS Snow Verification: Nov. 2016 - Jan 2017 Bias More Skill Based on

CONUS Snow Verification: Nov. 2016 - Jan 2017 Bias More Skill Based on Co. Ra. HS and Coop snow Obs Case Count = 639379 Event Count = ~ 1290 SREF ARW ECMWF Ensembles

Improved Resolution and Snow Level Calculations Old - 70 Members New - 46 Members

Improved Resolution and Snow Level Calculations Old - 70 Members New - 46 Members 90 th Percentile Forecasts Valid: 12 UTC Feb. 7, 2017 (Arrows show higher resolution and use of snow level for each member leading to improved depiction of snow in terrain. )

Changes in Ensemble Membership • The High Resolution Ensemble WRF-ARW member 2 - operational

Changes in Ensemble Membership • The High Resolution Ensemble WRF-ARW member 2 - operational November 1, 2017 • WRF ARW & NMMB arrive before the 00 z/12 z GFS arrives allowing 3 additional high resolution windows on day 1 forecast • WPC probabilities will incorporate the last 2 cycles (00 z and 12 z) • 3 members X 2 cycles = 6 members

Changes in Ensemble Membership (day shift example) Sept. 2016 -May 2017 26 SREF (all

Changes in Ensemble Membership (day shift example) Sept. 2016 -May 2017 26 SREF (all ARW/NMMB members) 25 ECMWF Ensemble 00 z (randomly chosen) 10 GFS Ensemble Members 06 z 1 CMC 00 z 1 ECMWF Ens Mean 00 z 1 00 Z ARW Hires Window (00 z GFS on Day 2) 1 00 Z NMMB Hires Window (06 z GFS on Day 2) 1 GFS 12 z 1 ECMWF Deterministic 00 z 1 NAM Nest 12 z (Day 1 -2), NAM 12 km Day 3 1 GEFS Ensemble Mean 06 z 69 Total Members 1 WPC Deterministic 70 total members for PWPF Nov. 2017 6 SREF ARW (09 z) 9 SREF NMMB (09 z) 10 ECMWF Ensemble (00 z) 10 GFS Ensemble Members (06 z) 4 ARW Hires Window (00 z/12 z) Day 1 or GFS (06 z)/SREF NMMB Day 2, 3 2 NMB Hires Window (00 z/12 z) Day 1 or GFS (00 z)/SREF NMMB Day 2, 3 1 GFS 12 z 1 ECMWF Deterministic (00 z) 1 NAM Nest (Days 1 -2) or NAM 12 km (Day 3) (12 z) 1 GEFS Ensemble Mean (06 z) 45 Total Members 1 WPC Deterministic 46 Total Members For PWPF

WPC Watch Collaborator Probability of Exceeding WFO Snow and Ice Watch Criteria NEW http:

WPC Watch Collaborator Probability of Exceeding WFO Snow and Ice Watch Criteria NEW http: //www. wpc. ncep. noaa. gov/wwd/internal/watchcollab/watch_collaborator. php

WPC Watch Collaborator Probability of Exceeding WFO Snow and Ice Watch Criteria Summary Graphic

WPC Watch Collaborator Probability of Exceeding WFO Snow and Ice Watch Criteria Summary Graphic 30 percent probability occurring at least 1 time period Freezing rain criteria met Snow criteria met

WPC Watch Collaborator Probability of Exceeding WFO Snow and Ice Watch Criteria Loop of

WPC Watch Collaborator Probability of Exceeding WFO Snow and Ice Watch Criteria Loop of 24 h freezing rain probabilities in 6 hr time steps. Jan. 15 -16, 2017

WPC Watch Collaborator Probability of Exceeding WFO Snow and Ice Watch Criteria Loop of

WPC Watch Collaborator Probability of Exceeding WFO Snow and Ice Watch Criteria Loop of 24 h snow probabilities in 6 -hr time steps. Mar 14 -16, 2017

WPC Forecast Operations 2017 -18 Display of Trends in Watch Collaborator Probabilities (date to

WPC Forecast Operations 2017 -18 Display of Trends in Watch Collaborator Probabilities (date to be announced) positive Increasing variance means less trust in trend. negative Left: How many of the last 3 cycles have probabilities >=30 percent of exceeding watch criteria? Center: What is the trend (increasing or decreasing) over last 2 cycles of watch collaborator probabilities? Right: How much variance has there been in watch probabilities (magnitude of change)?

WPC Forecast Operations 2017 -18 Ensemble Membership, November 2017 Day shift example 2045 z

WPC Forecast Operations 2017 -18 Ensemble Membership, November 2017 Day shift example 2045 z Post Collaboration* 6 SREF ARW (09 z) 02 z Update* 6 SREF ARW (21 z) 9 SREF NMMB (09 z) 10 GFS Ensemble Members (06 z) 10 ECMWF Ensemble (00 z) 1 GFS (12 z) 1 NAM Nest (Days 1 -2) or NAM (Day 3) (12 z) 4 ARW Hires Window (00 z/12 z) Day 1 or GFS (06 z)/SREF NMMB Day 2, 3 2 NMB Hires Window (00 z/12 z) Day 1 or GFS (00 z)/SREF NMMB Day 2, 3 1 ECMWF Deterministic (00 z) 1 GEFS Ensemble Mean (06 z) 45 Total Members 9 SREF NMMB (21 z) 10 GFS Ensemble Members (18 z) 10 ECMWF Ensemble (12 z) 1 GFS (18 z) 1 NAM Nest (Days 1 -2) or NAM (Day 3) (18 z) 4 ARW Hires Window (00 z/12 z) Day 1 or GFS (12 z)/SREF NMMB Day 2, 3 2 NMB Hires Window (00 z/12 z) Day 1 or GFS (06 z)/SREF NMMB Day 2, 3 1 ECMWF Deterministic (12 z) 1 GEFS Ensemble Mean (18 z) 45 Total Members 1 WPC Deterministic 46 Total Members For PWPF * Add 12 hours for 0845 z and 1400 z Post Collaboration and Update times.

Winter Weather Desk - Day Shift Forecast Product Timeline PWPF = Probabilistic Winter Precipitation

Winter Weather Desk - Day Shift Forecast Product Timeline PWPF = Probabilistic Winter Precipitation Forecast Prelim PWPF and watch Updated PWPF collaborator and watch collaborator Final PWPF and watch available Post Deadline for collaborator available Prelim collaborated deterministic snow/ice grids sent updates grids sent 1730 z 1800 z WPC/WFO collaboration (chats, calls) 2015 z 2045 z Additional collaboration (event driven) 0100 z 0200 z No further collaboration (no sn/zr updates)

 WPC Deterministic Snow Verification Day 1 Snow 2016 -17 Over the CONUS https:

WPC Deterministic Snow Verification Day 1 Snow 2016 -17 Over the CONUS https: //www. nohrsc. noaa. gov/ Threat score automated ensemble (green) vs. winter weather desk (red) Frequency bias automated ensemble (green) vs. winter weather desk (red) Automated Ensemble (WSE): NAM + GFS + ECMWF + SREF + GEFS + ECMWF* + WRF ARW + NMMB + Canadian Global * partial membership

 WPC Deterministic Snow Verification Day 2 Snow 2016 -17 Over the CONUS https:

WPC Deterministic Snow Verification Day 2 Snow 2016 -17 Over the CONUS https: //www. nohrsc. noaa. gov/ Threat score automated ensemble (green) vs. winter weather desk (red) Frequency bias automated ensemble (green) vs. winter weather desk (red) Automated Ensemble (WSE): NAM + GFS + ECMWF + SREF + GEFS + ECMWF* + WRF ARW + NMMB + Canadian Global * partial membership

 WPC Deterministic Snow Verification Day 3 Snow 2016 -17 Over the CONUS https:

WPC Deterministic Snow Verification Day 3 Snow 2016 -17 Over the CONUS https: //www. nohrsc. noaa. gov/ Threat score automated ensemble (green) vs. winter weather desk (red) Frequency bias automated ensemble (green) vs. winter weather desk (red) Automated Ensemble (WSE): NAM + GFS + ECMWF + SREF + GEFS + ECMWF* + WRF ARW + NMMB + Canadian Global * partial membership

Freezing Rain Case Verification 07 -08 Feb 2017 • Icing amounts higher than forecast

Freezing Rain Case Verification 07 -08 Feb 2017 • Icing amounts higher than forecast across interior eastern NY and MA

WPC Winter Weather Desk Operations Summary of Changes • Improvements in probabilistic products, with

WPC Winter Weather Desk Operations Summary of Changes • Improvements in probabilistic products, with snow level calculation added and members run at 5 km resolution • Reduced SREF ARW & ECMWF members for 2017 -18 due to bias and resolution issues, respectively • Number of high resolution window forecasts increases from 2 to 6 • Watch Collaborator probabilities now updated by 14 z/02 z • WPC deterministic forecasts now issued at 1730 z and 0530 z • New Watch Collaborator trend tools maps coming soon • Freezing rain accumulations verified using ASOS freezing rain sensor

Thank You! Questions or Comments? • Winter Weather Desk (301)683 -0784 • Dan. Petersen@noaa.

Thank You! Questions or Comments? • Winter Weather Desk (301)683 -0784 • Dan. Petersen@noaa. gov

Verification of Model/Ensemble Surface Low Forecasts

Verification of Model/Ensemble Surface Low Forecasts

WPC Probability Forecast Verification Winter 2016 -17 Snow Prob 4” Observed Frequency vs Predicted

WPC Probability Forecast Verification Winter 2016 -17 Snow Prob 4” Observed Frequency vs Predicted Probability Day 1 Day 2 Under forecast Over forecast