Jet and storm track shifts in the Northern
Hemisphere: Driving by tropical convection, sea
ice, interference, and implications for climate
models
Steven Feldstein
Collaborators: Sukyoung Lee, Michael Goss, Christian Franzke
The Pennsylvania State University
SPARC-Workshop on Storm Tracks, Grindelwald, Switzerland, August 25, 2015
Question:
1. What is the relationship between the jet latitude, storm
tracks, tropical convection, Arctic sea ice, and interference?
Stationary wave index (SWI): Defined as the
projection of the daily 300-hPa streamfunction
onto the 300-hPa climatological stationary eddies.
Methods:
Composites,
Self-Organizing
Idealized
Map (SOM)
Numerical
analysis,
Model
Data: ERA-Interim Reanalysis, NOAA OLR, NSICD sea ice
Evolution of outgoing longwave radiation
Enhanced
convection
Positive SWI days
Negative SWI days
Arctic Sea-Ice Concentration evolution
Positive SWI days
Reduced
Sea ice
Negative SWI days
Time evolution: OLR  SWI  sea ice  stratospheric
polar vortex  AO (for k=1,2)
Sea Ice
Tropical convection
Sea Ice
6.5-7.5 day timescale for patterns
SOM patterns, trend, and frequency of occurrence
Anomalous OLR associated with SOM Patterns
SOM1
SOM2
SOM3
SOM4
Zonal-mean zonal wind
SOM1
SOM3
SOM1 (preceded by positive sea ice anomaly) EP Fluxes
Zonal wave 3 and above
Zonal wave 1 and 2
Summary of impact of sea ice
(4) Strong polar vortex
a)
(3) Weaker ver cal
wave ac vity flux into
the stratosphere
(1) cooling
(2) Destruc ve
interference with
climatological high
(4) weaker polar vortex
(b)
(3) Stronger ver cal
wave ac vity flux into
the stratosphere
(1) warming
(2) Construc ve
interference with
climatological high
IMPLICATION FOR CLIMATE MODELS
Two Groups of CMIP5 (Historic Climate Model runs: All models
exhibit a high correlation (> 0.90) between the Surface Air Temperature
(SAT) and Downward Infrared Radiation (IR) trends
• Group 1 (more similar to obs):
Small correlation between surface heat flux and downward IR
trend
Large correlation between circulation and downward IR trend
• Group 2:
Large correlation between surface heat flux and downward IR
trend
Small correlation between circulation and downward IR trend
Groups 1 & 2 Convective Precipitation Trends
Groups 1 & 2 Circulation Trends
CONCLUSIONS
• Equatorward Jet & Storm Track Shift: Enhanced tropical convection 
Reduced sea ice  constructive interference  enhanced vertical wave
activity propagation into stratosphere  deceleration of stratospheric
polar vortex  excitation of negative AO (equatorward jet shift).
• Poleward Jet & Storm Track Shift: Enhanced convection  poleward jet
shift  positive feedback with synoptic-scale eddies (further poleward jet
shift)
• Large variation is convection precipitation and circulation trends in historic
CMIP5 model runs. There may be large sensitivity in the jet and storm
track latitude and strength in the CMIP5 models to the details of the
model’s representation of tropical convection
Implications
• For medium-range and climate models, if a single
tropical convection anomaly is wrong, the
extratropical response could be rather inaccurate.
Poleward Jet Shift in the Northern Hemisphere
Lagged-correlations between Arctic sea ice and SOM frequency
positive sea ice
anomaly leads
SOM1
negative sea ice
anomaly leads
SOM3
positive sea ice
anomaly leads
AO
Negative Interference
occurs in SOM1
-60 to -45 days
-30 to -10 days
-45 to -30 days
-10 to 0days
Positive Interference
occurs in SOM3
-60 to -45 days
-30 to -10 days
-45 to -30 days
-10 to 0days
Sea-ice concentration anomalies
Days -60 to -45 prior to SOM1
Anomalously high sea ice concentration
Days -10 to 0 prior to SOM3
Anomalously low sea ice concentration
Question: What is the relationship between
interference, tropical convection, and surface air
temperature, sea ice, the stratospheric polar vortex,
and the Arctic Oscillation?
Stationary wave index (SWI): Defined as the projection
of the daily 300-hPa streamfunction onto the 300-hPa
climatological stationary eddies.
Evolution of 300-hPa streamfunction
Positive SWI days
Negative SWI days
Correlation between sea-ice area (Barents and Kara
Seas) and SOM frequencies
Composites of AO index
Composite eddy-momentum flux convergence & zonal wind
SOM1
synoptic waves
planetary-scale waves
SOM2
synoptic waves
SOM3
synoptic waves
planetary-scale waves
planetary-scale waves
SOM4
synoptic waves
planetary-scale waves
CONCLUSIONS
•
Four distinct teleconnection (SOM) patterns in the Northern Hemisphere,
associated with GHG driving/ENSO and Arctic sea ice (time scale 6.5-7.5
days, driven by storm track eddies)
•
Poleward shift of subtropical jet associated with GHG driving and Arctic sea
ice decline
•
GHG driving contributes to poleward shift of eddy-driven jet and Arctic sea
ice decline to an equatorward eddy-driven jet shift (implications for AO trend)
•
Up-to 12 month predictability based upon Arctic sea ice
•
Our understanding of inter-decadal variability hinges in part on (1) the
dynamics of intraseasonal time scale processes (2) the mechanism by which
external forcing (GHG, sea ice) alter the frequency of intraseasonal time
scale teleconnection patterns.
•
Impact of SOMs manifested through change in tropical convection.