Forecast Challenges Associated with the Valentine’s Day, St. Patrick’s Day

and Tax Day Nor’easters of 2007

Neil A. Stuart

NWS Albany, NY

NROW 9

Valentine’s Day Storm

• Forecast guidance– Anomalies– Ensembles– Plumes– NCEP/HPC– Observational data

• Forecast process and considerations

• What happened

Anomalies and Plumes – 2 to 3 day lead time

} {

3-4 SD below normal 3+ days

in advance, increased to 4-5

SD closer to onset of storm

Clustering between 1.5”

and 2.4”

Ensemble probabilities for ≥1.00” liquid equivalent

Widespread region of ≥ 90% probability of ≥ 1.00” of liquid

equivalent

Unusual consistency in the spread

Other guidance and observations

HPC WWD forecasts temporal consistency with

axis of heaviest snow

Wind profile at boundary layer suggested warming

and period of mixed precipitation at Albany

Verified with 1800 UTC observed sounding

What Happened?

•Widespread 20-42” of snow Capital Region of NY and north and west

•NESIS Category 3 – ranked near Blizzard of ’78 in SE New England

•I-80 shut down in PA due to accidents in mixed precipitation

•Many planes stranded on runways for hours at JFK airport

•35 deaths

Surface low track across southeastern New

England, analog to some of the biggest snows in

upstate NY

Band of snow produced 4”-6” per hour

St. Patrick’s Day Storm

• Forecast guidance– Anomalies– Ensembles– Plumes– NCEP/HPC– Observational data

• What happened

Anomalies

3-4 SD below normal

Only 1-2 SD below normal in U direction,

but 3-5 SD above normal in V direction, with NE U.S. in RRQ

AnomaliesDeterministic operational GFS and NAM show 4-5 SD below normal – not

dampened by 15+ ensemble members

Deterministic and ensemble upper level wind

anomalies barely 2 SD below normal

Ensemble probabilities of 1.00” of liquid equivalent and plume guidance

Widespread region of ≥ 90% probability of ≥ 1.00” of liquid

equivalent, however, note western edge

Most clustering between 1.0”

and 2.5”

}{

Other guidance and observationsHPC WWD consistently kept the axis of heaviest snow in the Catskills and

northern New England

Extremely tight 850 hPa thermal gradient across southern NY and New England

Extremely tight boundary layer thermal gradient

contributed to very strong frontogenesis

What Happened?

•18-30” of snow in the Catskills with a foot or more over much of interior New England and New York

•NESIS Category 2

•10 deaths – all due to traffic accidents

Surface low tracked across southeastern

New England, similar to Valentine’s Day Storm

Primary heavy snow band in Catskills, note much

less reflectivity than Valentine’s Day Storm

Tax Day/Patriots Day Storm

• Forecast guidance– Anomalies– Ensembles– Plumes– Observational data

• What happened

Anomalies – Forecasted

U wind anomalies at 850 hPa forecasted to be

3-5 SD below normal

V wind anomalies at 850 hPa forecasted to be 3-4 SD above normal

U wind anomalies at 250 hPa 2-3 SD

below normal

MSLP anomalies of 4-5 SD below normal

Anomalies – Observed

U and V wind anomalies at 850 hPa U > 5 SD below normal

U wind anomalies at 250 hPa between 3 and 4 SD below normal

MSLP anomalies > 5 SD below normal

Ensemble probabilities of 2.00” of liquid equivalent and plume guidance

Ensemble probabilities of ≥ 2.00” of liquid equivalent were > 50%, with MREF the

highest and most widespread

SREF shows more spread, but both ensembles show virtually all members supporting ≥ 2.00”

of liquid equivalent

} {Clustering of plumes between 1.5” and 3.5”

of liquid equivalent

Other observations – What Happened

•Widespread flooding in southern NY and the mid-Atlantic states

•Severe coastal flooding and erosion from NJ through southern and eastern New England

•50 MPH wind gusts along the mid-Atlantic and New England coasts

•50 MPH or greater winds in the higher elevations of VT causing widespread tree and property damage

•IRS allowed 2 more days to file tax returns

•156 MPH gust at Mt. Washington

•Worst Weather in history of Boston Marathon

•$180 million damages in NJ, second only to Hurricane Floyd

Nearly isothermal at Albany, NY - Winds ≥ 50 KT

above the surface

Strong warm advection and deep winds ≥ 50 KT

Strong deep southeast winds ≥ 50 KT

Lessons from all three storms• Ensemble guidance and derived products are revolutionizing

forecasting

• New tools and products are allowing for unprecedented lead times for warning of high impact events

• POD ≥ 90%, FAR ≤ 20%, lead time for Watches ≥ 48 hours, Warnings ≥ 24 hours

• Anomalies showing departures from normal distinguishes high vs. low potential storm impact in extended ranges (2+ days prior to onset)

• Recognizing signals in ensemble means and spreads, and in anomaly displays helps quantify forecaster confidence

• Ensemble means and spreads help quantify uncertainty and temporal trends/consistency from run to run

• Probabilities for liquid equivalent rainfall amounts quantify confidence levels for corresponding snow amounts

Lessons from all three storms• Plume diagrams depict

– A range of liquid equivalent rainfall amounts– Precipitation types– Mean and maximum amounts of each precipitation type– Clustering near certain values and precipitation types helps quantify

confidence in those values• Despite advances in data analysis, assimilation and visualization,

some important user groups are not benefiting– PA interstate closed due to multiple accidents – Jets stranded on runways for 10+ hours in NYC– 67 deaths attributed to all three storms

• How can meteorologists help users to reduce the societal impacts of major winter storms like the 2007 storms?– Need to communicate forecast information in a manner understood by the

most user groups– Need to educate users on how to best use current forecast products and

services– Need to coordinate with users to best tailor current and future products

for their needs

Improving predictions and communication = Better preparation for weather-related hazards =

Reduced societal impacts!

Thank you for your attention!

• Real-time ensembles, anomalies, plumes and probabilities can be found at: http://eyewall.met.psu.edu

Questions?

http://www.sip.ucar.edu/wasis