The Climatology and Interannual Variability of North American Stormtracks in the GFS and

CFS Global Climate Models

Timothy Eichler and Wayne Higgins

Climate Prediction Center/NCEP

• T62 GFS run with AMIP II SST

• Run from 1950-2002

• SLP saved twice daily

GFS Simulation

CFS Simulation

• 2.5x2.5 fully coupled simulation

• Run from 2002-2033

• Free Run (i.e. climate mode)

• SLP saved twice daily

Storm Track Frequency Climatology (5x5 grid) for I: Obs II: GFS III: CFS from a: Winter through d: Fall

I IIIII

Storm Track Frequency Difference a: GFS-OBS b: CFS-OBS

a

b

Storm Track Frequency Difference CFS-GFS

SLP (hPa) of Storms I: Obs II: GFS III: CFS

a-d: (winter through fall)

I II III

SLP Diff I: GFS-Obs II: CFS-OBS

(a-d: winter through fall) I II

Standard Deviation Analysis for I: GFS and II: CFS

I II

a

Storm Tracks by El Nino Phase (OBS ) a: Strong El Nino b: Weak El Nino c: Neutral d: weak La Nina e: Strong La Nina.

a

b

c

d

e

Storm Tracks by El Nino Phase (GFS Model) a: Strong El Nino b: Weak El Nino c: Neutral d: weak La Nina e: Strong La Nina.

a

b

c

d

e

Storm Tracks by El Nino Phase (CFS Model) a: Strong El Nino b: Weak El Nino c: Neutral d: weak La Nina e: Strong La Nina.

a

b

c

d

e

Composite Stormtrack Frequency Anomaly for a: Strong El Nino-neutral and b: strong La Nina-neutral

a

b

Composite GFS Stormtrack Frequency Anomaly for a: Strong El Nino-Neutral and b: Strong La Nina-Neutral

a

b

Composite CFS Stormtrack Frequency Anomaly for a: Strong El Nino-Neutral and b: Strong La Nina-Neutral

a

b

Stormtrack difference (Strong El Nino – Strong La Nina) for a: Observations b: GFS Model c: CFS Model

a

b

c

Merdional Temp. Gradient ((degrees C/ km)*100) for a: obs b: GFS model c: GFS-obs

a

b

c

a

b

c

Merdional Temp. Gradient ((degrees C/ km)*100) for a: obs b: CFS model c: CFS-obs

H500 Gradient ((m/km)*100) for a: obs b: CFS model c: CFS-obs

a

b

c

H500 Gradient ((m/km)*100) for a: obs b: GFS model c: GFS-obs

a

b

c

Conclusions

• GFS Produces Stormtrack Climatology spatially reasonable though approximately 50% less frequent… CFS slightly better.

• Storm tracks less frequent and weaker especially in the North Pacific and North Atlantic in areas normally associated with strong baroclinicity.

• GFS and CFS models exhibit a seasonal cycle for stormtracks though weaker than obs.

• GFS and CFS stormtracks show a response to ENSO evident especially when comparing strong events

• Reduced storm frequency relative to observed implies weak model variability. Evidence suggests that the GFS and CFS models have less baroclincity than observed.

Future Work

• Explore GFS and CFS model physics to ascertain why models’

storm variability is less than observed (e.g. look at surface heat budget)

• Investigate Storm structure (e.g. fronts, precipitation, etc.) to see if

they are realistic

• Use stormtracks software on other data: rr data, ETA model… Program has potential as a prognostic tool…