Hydrometeorological Prediction Center

The Inaugural Hydrometeorological The Inaugural Hydrometeorological Testbed Testbed – HPC HPC

Winter Weather ExperimentWinter Weather Experiment

1

David Novak

Faye Barthold, Mike Bodner, Ed Danaher, Dan Petersen, Rich Bann, Mike Musher,

Chris Hedge

and

Many participants and contributors

Hydrometeorological Prediction Center

Hydrometeorological Testbed Hydrometeorological Testbed – HPC HPC

Goal: To accelerate R2O-O2R to enhance HPC services

Roles:• Identify and test new techniques

to improve HPC forecasts• Provide training in new techniques to

HPC forecasters• Host visiting forecasters and scientists

Principal Collaborators:• Other NOAA Testbeds (e.g. HWT, AWT)• Forecasters and academia

Description

2

A component of the NOAA HMT

Hydrometeorological Prediction Center

Internal deterministic 6-h snow /sleet /ZR / SLR grids & graphicshttp://www.hpc.ncep.noaa.gov/wwd/internal/

Heavy Snow and Ice Discussion (QPFHSD)

HPC Winter Weather DeskHPC Winter Weather DeskOverviewOverview

3

Public products: 24 & 48 h probabilities for:

-Snow/Sleet/ Freezing Rain-Probabilities computed from deterministic forecast and model spread

Track forecasts for surface lows associated w/ significant winter weather

Hydrometeorological Prediction Center

HMT-HPC Winter Weather ExperimentHMT-HPC Winter Weather Experiment

4

•14 participants (WFO, SPC, AWC, HPC, EMC, ESRL, and COMET)

Approach•Create snow and ice accumulation forecasts using experimental guidance

•Write “confidence discussion”

•Subjectively evaluate experimental guidance

Jan 10 – Feb 11, 2011

•Can high-resolution models improve Day 1 forecasts of precipitation type and amount?

•Can we better quantify and communicate winter weather uncertainty for Day 1-2 forecasts?

Goals

Participants

Hydrometeorological Prediction Center

A Great Time to Have an ExperimentA Great Time to Have an Experiment

5

•Several major winter weather events

•Period of unusually low hemispheric predictability from late January – early February

Jan 10 – Feb 11, 2011

Mean 500 hPa height Dec 24-28, 2010 Jan 9-13, 2011

Jan 26-27, 2011 Feb 1-3, 2011

Hydrometeorological Prediction Center

Experimental DataExperimental Data

6

•Can high-resolution models improve Day 1 forecasts of precipitation type and amount?

Ensemble

Goals

High ResolutionResolution Fields Day 1 Day 2

HRW-ARW 4 km Amounts, Ptype,Sim Reflect

x

HRW-NMM 4 km Amounts, Ptype,Sim Reflect

x

NMMB nest (new NAM) 4 km Amounts, Ptype,Sim Reflect

x x

Resolution Fields Day 1 Day 2

SREF 32 km MeansMax/Min amountsProbabilities

x x

HPC Superensemble 32 km Mean amounts x x

Hydrometeorological Prediction Center

Can high-resolution models improve Day 1 forecasts of precipitation type and amount?

HMT-HPC Winter Weather ExperimentHMT-HPC Winter Weather Experiment

7

HRW-NMM ObservedHRW-ARWExperimental NAM

Pros: •Improved orographic precipitation, lake effect

•Visualizing temporal evolutions

•Providing unique fields (simulated reflectivity)

•Explicit prediction of mesoscale bands

Cons:•Overall amounts not superior to operational

•Little additional confidence in band location

BandBandBand

Neutral

Useful

Not Useful

Hydrometeorological Prediction Center

Feb 2-4, 2011 SnowstormFeb 2-4, 2011 Snowstorm

*

8

Simulated Reflectivity experimental 4 km NMMB model (to become operational this fall)

03Z Tuesday Feb 01 to 12Z Wednesday Feb 02

Low Tracks

Snowfall

Obs

NAM

Exp NAM

Hydrometeorological Prediction Center9

Confidence: “above average confidence that an area near Chicago will receive up to 20" of snow.”

Storm track: “Fairly confident of storm track, though high resolution models seem to deepen low center more and pull it further north and west into the cold air.”

Snow Probs: >12": 80%>20": 20%

HMT-HPC Winter Weather ExperimentHMT-HPC Winter Weather Experiment•Can we better quantify and communicate winter weather

uncertainty for Day 1-2 forecasts?

Hydrometeorological Prediction Center10

Forecast team’s confidence was qualitatively correlated to snowfall errors

When forecast teams rated their snow forecast confidence as low (high), there were generally larger (smaller) errors

HMT-HPC Winter Weather ExperimentHMT-HPC Winter Weather Experiment•Can we better quantify and communicate winter weather

uncertainty for Day 1-2 forecasts?

Hydrometeorological Prediction Center

Operational ImpactsOperational ImpactsNWPNWP

11

Diagnosed “strange band” in HRW-NMM

Fixed before implementation

Identified NAM snow depth limitations

Hydrometeorological Prediction Center12

•Exposed forecasters to cutting-edge tools and techniques

•Increased confidence in using NMMB (upgraded NAM) for winter weather forecasting.

•Revealed substantial limitations of ice accumulation analysis used for verification. Exploring alternatives.

•Revising guidelines to include confidence information in HPC Heavy Snow and Icing Discussion.

Operational ImpactsOperational ImpactsHPC Winter Weather DeskHPC Winter Weather Desk

Hydrometeorological Prediction Center13

2012 Experiment Plans 2012 Experiment Plans

Assess, quantify, and communicate uncertainty• Explore how humans can add value to probabilistic products• Evaluate experimental ensemble systems from EMC, HMT and AFWA• Evaluation of ensemble clusters and QPF bias-correction

Evaluate societal impacts• Explore categorizing impacts of forecasts (low, moderate, high, historic)• Calculate impact by using joint probabilities

Expand participation• Goal of 3 forecasters per region, NCEP, NSSL, ESRL involvement

Jan 9 – Feb 10 2012

Hydrometeorological Prediction Center14

SummarySummary

Inaugural HMT-HPC Winter Weather Experiment conducted

Participants had a neutral-to-positive view of the operational utility of high resolution models for winter weather

Human forecast teams showed skill in anticipating errors in their forecasts (confidence – skill relationship)

2012 Experiment planned for Jan-Feb 2012

If interested, contact david.novak@noaa.gov

Full detailed report with recommendations at: http://www.hpc.ncep.noaa.gov/hmt/HMT_HPC_WWE_Summary_Final.pdf