Lessons in predictability part 1: The Post Groundhog Day 2009 Storm

Neil A. Stuart1, Richard H. Grumm2, and Michael J. Bodner3

1National Weather Service Office Albany, NY2National Weather Service Office State College, PA

3National Centers for Environmental Prediction, Camp Springs, MD.

NROW 2009

Some “Big Snow Busts from the Past” that inspired this study

• 30 December 2000: – A well advertised big snowfall event for Virginia, Washington D.C. Philadelphia and

DELMARVA – Observed snow (12-24 inches) was confined to interior NJ and interior southern NY

• 25-26 January 2000– Significant snow storm (12-20 inches) impacted NC to MA– Storm was poorly forecasted with any significant lead time

• 4-6 March 2001: – I-95 corridor from Washington D.C. to Philadelphia, NYC and Boston missed by

advertised big snowstorm– 24”+ of snow upstate NY through interior central and northern New England

• 3-4 February 2009:– Potential storm given names such as “Groundhogzilla”, “Big Daddy”, “Megastorm”

and “Compared to Superstorm 1993”– A big miss– A small mesoscale band produced 3-6” of snow from southeastern PA through NJ,

New York City, Long Island, and coastal southern New England, with embedded isolated spots of 6-10”

Overview and definitions• The impact occurred on 3-4 February 2009• The terms “forecasters” and “forecast community”

will refer to forecast staff in all forecast services, including mass media

• Forecast services include – the NWS, private sector, broadcast media– internet-based services and blogs.

• There were 3 phases to the prediction and communication of the storm – Watch and wait – Sound the alarms before and louder then your competitors– Careful back pedaling

Phase 1 - Watch and wait • Long range forecasts prior to 12Z 29 January NWP Model

runs– T - 6 days: GFS/ECMWF and GFS Ensemble showed hints at a

coastal storm originating from the northern Gulf Coast states– Broad consensus in guidance that any potential storm would affect

much of the U.S. east coast with heavy precipitation– Significant spread in the track and movement of the upper energy

and surface low tracks in ensemble members– Most forecasters didn’t perceive 30% chance of watch or warning

level impact, so no mention in NWS HWOs– So, the forecast community chose a watch and wait philosophy

conveying the high level of uncertainty, if mentioned at all

Phase 2 – Sound the alarms• 1200 UTC 29 January: The forecasts heard down the coast

• T- 5 days: The first set of guidance/ensembles that showed a “consensus” on an interior eastern U.S. surface low track

– All modeling centers had a low somewhere in the eastern US all just inland

• Even with the “consensus”, there was considerable spread in the predicted track and movement of the upper and surface features

– Ensemble and Poorman’s Forecast Systems (EFS and PEFS)

• Probability of precipitation (POP) and quantitative precipitation forecasts (QPF) from guidance suggested heavy snow and rain

– Uncertainty in precipitation type and amount were clear in the EFS

• Forecasters looked to the relatively low spread in guidance as the trigger to begin alerting the public about a high impact storm

– Guidance was misinterpreted– The spread in the EFS and PEFS was high– There was a storm but the track, intensity and timing showed lots of uncertainty

• Important: Less consideration for run-to-run consistency and trends

Precipitation forecasts and trendsECMWF series

GFS series

Plumes from Albany, NY and 24 hour probabilities for 1 inch QPF

12Z 29 January MREF 12Z 30 January MREF 12Z 1 February MREF

MREF 500 hPa, 850 hPa and PWAT500 hPa series

850 hPa winds/anomalies series PWAT series

MSPL ensemble means and spreadsPoor Man’s Ensemble – Mean and spread of operational GFS,

ECMWF, UKMET and GGEM12Z 29 January GFS 12Z 29 January ECMWF

12Z 29 January GGEM 12Z 29 January Poor Man’s Ensemble

GFSEnsemble MSLP Series

Run-to-run trends in the operational GFS, ECMWF and GGEM

GFS ECMWF

GGEM

Revisiting the terms used in predicting the post Groundhog Day Storm 5 days prior to onset

• Some forecasters used these terms:– “Groundhogzilla”– “Big Daddy”– “Megastorm”– “Compared to Superstorm

1993”– “Monster Storm”– “Will cover “X” square

miles”– “Will produce…”

• Other forecasters used these terms:– “Significant precipitation

may occur”– “Significant snowfall might

occur”– “Uncertainty” in terms of

coastal flood potential– “Significant impact possible”– “Likely/Unlikely”– “Potential” flooding and/or

ice jams where heavy rain can occur

– “Depending on exact track”

So What happened?

Questions that need to be answered

• What threshold(s) should be used to alert users to various weather hazards?

• How many false alarms will cause a user to stop using a source of information?

• What language is emotionally charged and psychologically affects user perceptions?

• What language will prompt users to take “appropriate” action at various stages of a forecast?

• How do we best communicate uncertainty?

• How can the public, private and academic sectors best work together to improve the end-to-end-to-end forecast process?

This figure courtesy of Steve Tracton from the Capital Weather gang

Salient take away points• No two storms are exactly alike, so citing analogs 2 or

more days prior to an event is at the very least dangerous• Consult ensemble mean and spread guidance• Consult ensemble probabilities for various liquid

equivalent precipitation values, along with plumes – let numerical probabilities guide you to “chance”, “likely” and “definite”

• Look for run-to-run consistency in 00Z and 12Z guidance/ensembles, for at least 2 consecutive runs before increasing forecast confidence to “scenario likely”

• Run-to-run trends are EXTREMELY IMPORTANT, as are ensemble spreads (spaghetti plots), especially if spreads are large and if shifts in storm tracks are noted

• Communicate sources of uncertainty and ranges of possibilities, especially 2 or more days prior to the event

Salient take away points• Avoid specific snow/sleet/ice amounts ≥ 2 days prior to an event• Avoid emotionally charged language including but not limited to

“Blizzard”, “Crippling”, “Mega”, “Super” “Colossal”, “Historic”, or anything with the suffix “zilla”, especially ≥ 3 days prior to an event

• Routinely study past events, including rarely studied storms that do not occur

• Do broadcast meteorologists need to negotiate agreements with company/station management as to proper communication of uncertainties?

• Broadcast/internet media hype affects the ENTIRE forecasting community– Increased phone requests to all information sources– Inconsistencies between information sources– Ultimately the CREDIBILITY of the ENTIRE forecasting community can be

affected

Thank you for your attention! - Questions?Case study analyses of these events can be found at:

http://cstar.cestm.albany.edu/PostMortems/CSTARPostMortems/2009/march2/megastormcomp.htmand

http://nws.met.psu.edu/severe/2009/03Feb2009Mega.pdf