1. Teleconnections & Extended-Range Prediction
Steven Feldstein
The Pennsylvania State University
March 3, 2016

2. Teleconnection Patterns
Definition: Teleconnection patterns are recurring and persistent spatial patterns that connect weather (wind, temperature, precipitation, pressure) over great distances across the globe.

3. The dominant Northern Hemisphere teleconnection patterns
Climate Prediction Center

4. Impact of teleconnections on the jet stream

5. Earliest NAO Observations
Norse (Viking) settlers arrived in Greenland in CE 985. The Norse, who appeared to be very interested observers of the weather, also seemed to be aware of teleconnection patterns in the North Atlantic basin.
There was an anonymous Norwegian book (approx. CE 1230), entitled the `King's Mirror'. This book, in the form of a discussion between father and son, wrote that severe weather in Greenland coincides with warmer weather at distant locations, and vice versa.

6. Wallace and Gutzler (1982) WP NAO PNA A modern study which
unified previous teleconnection
research and systematically
Identified the key patterns WP
NAO
PNA

7. Two types of teleconnections
Northern Annular Mode
Southern Annular Mode
Annular (dipole) Modes
(Thompson and
Wallace (2000))
Wave train
patterns
PNA
Pacific South American (PSA) pattern

8. What is the timescale of teleconnections?
Teleconnections last for about 2 weeks
For most of 20th century, scientists thought the teleconnections persisted for several months and were probably forced by SST anomalies
Using a climate model, Lau (1981) showed that teleconnections remain in model solution if the SST field is fixed
Feldstein (2000) showed with daily observational that all teleconnections except the Southern Oscillation have an e-folding time scale of about 10 days

9. How are the PNA and PSA excited(a modeling study)?
Wavetrain
Model’s tropical
convection
Horel and Wallace (1981)
PNA and PSA are excited by
tropical convection
Wallace and Gutzler (1981)

10. How are the NAO, NAM, and SAM excited
How are the NAO, NAM, and SAM excited? (The NAO is generated by Rossby wave breaking)
Black contours show two
different potential
temperature contours on
the tropopause. Wave
breaking is identified by
warm air being located
poleward of cold air.
Benedict et al. (2004)

11. The PNA is amplified by breaking Rossby waves (after tropical convection)
As with the NAO, the PNA is also associated with wave breaking. However,
wave breaking plays a smaller role for the PNA.

12. 8-14 day medium-range NOAA CPC forecasts

13. Gap in forecasting between 10 and 30 days
NWP forecasts from 1-10 days have been steadily improving. These forecasts are limited by chaos theory.
Probabilistic forecast (for lead times > 30 days) are now being performed. The physical basis for these forecasts is that anomalies in SST change slowly over many months.
Up until the past few years, because of this gap, forecasts have not been performed.
Using our knowledge of the properties of teleconnections, and the physical processes that drive them, we are optimistic that day probabilistic weather forecast will soon be taking place.

14. Edward Lorenz ( )
Pioneered chaos theory, which placed the 7-10 day limit on forecast predictability under a firm theoretical foundation (Lorenz 1963). Lorenz showed that two atmospheric states, with an imperceptible difference, can evolve into very different states. Since there are always errors in observational measures of the atmosphere, this implies that there is a limit to skillful weather forecasts. This is the so-called Butterfly Effect.

15. Why is SST linked to long-range forecasting?
SST anomalies slowly evolve over many months.

16. Why do SST anomalies last for several months?
Tropical SST anomalies are associated with ocean waves that
propagate very slowly and persist for many months.

17. Madden Julian Oscillation
A day tropical oscillation in convection and the wind
Eastward propagating
convection
The MJO is the most
prominent mode of
intraseasonal variability
in the tropics. There are
many theories that offer
explanations for the
occurrence of the MJO.

18. A link between the NAO and the MJO
The relationship between the MJO phase and the anomalous frequency of
occurrence as a function of lead time for 4 teleconnection patterns
The MJO has
a big influence
on both NAO
phases
Cassou (2008)
A physical explanation for the link between the NAO and MJO is unclear

19. PNA occurrence depends upon where tropical convection is
When Convection is over
Indonesia (Phase 4), +PNA occurs
more frequently days later
small pattern numbers
represent +PNA
large pattern numbers
represent -PNA
When Convection is over
Indonesia (Phase 4), --PNA occurs
less frequently days later
Johnson and Feldstein (2010)
Physical mechanism linking the MJO to the PNA is Rossby wave propagation

20. MJO convection excites Rossby waves that propagate from the tropics to midlatitudes

21. Development of a Probabilistic Extended-Range Forecast Model
To test if probabilistic 2-4 weeks forecast based upon the phase of the MJO, ENSO, and long term-trend are feasible
As we will see, our project was a success. The results also show the importance of using basic science to advance weather forecasting.

22. Wheeler and Hendon diagram
Source:
RMM1 and RMM2 define the phase and amplitude of the MJO

23. Extended-range prediction: MJO and ENSO
Extended-range (10-30 day) prediction is based on two key ideas:
MJO and ENSO tropical convection persists for more than days. The MJO has a period of days and remains in a single phase for about 5-6 days. The ENSO SST anomalies persist for many months.
It takes tropical convection about 7 days to excite midlatitude teleconnection patterns, and once established these patterns typically last for about 2 weeks.

24. The method for obtaining probabilistic forecasts.
Generate two probability density function: all days (left
panel), days for a specific MJO and ENSO phase (right
panel). Comparing the solid and dashed curves in the right
panel gives the probabilistic forecast.

25. Heidke Skill Score HSS = (H - E)/(T - E) X 100
H = number of days correctly forecasted
E = expected fraction of correct forecast by chance (E=1/3 total number of days)
T = number of forecasted days
Use leave-one-year-out forecast approach
HSS is used to evaluate the forecast skill.
HSS = 0 corresponds to a random forecast

26. Comparing HSS values for observational and GFSv2 model data
HSS value for all days
with observational data
(statistical model)
HSS values for those days
when the MJO and/or ENSO
are active (statistical model)
HSS values for GFSv2 numerical
model (state-of-the-art US model)
Statistical model better beyond 3 weeks

27. At many locations HSS values are high
Forecast lead time
The MJO and
ENSO influence
different
locations

28. HSS values by MJO phase: Some MJO phases yield better forecasts

29. Examples of a 2-week forecast
Teleconnection pattern
HSS
Forecast
Forecast
HSS

30. Examples of 3 and 4 week forecasts
HSS

32. Further improvement of forecasts
Our research suggests that accounting for the following features has the potential to further improve probablistic forecasts
The initial flow in midlatitudes
The state of the stratospheric polar vortex
Arctic sea ice
Interference between stationary and planetary waves in midlatitudes

33. Examining the initial flows that leads to a large/small amplitude extratropical response to the MJO
The 300-hPa geopotential height
field that is followed 7-10 days
later by a large (left column)
or a small (right column)
amplitude wave field in
midlatitudes.
Include a new parameter in the forecast based on the similarity between
the observed flow and the above patterns

34. The NAM in the stratosphere and troposphere
When the NAM is active in the stratosphere, the NAM and NAO in the
troposphere sometimes persist for up to two months. This has potential
Implications for extended and long range forecasting.
(Baldwin and Dunkerton (1999, 2001)

35. Summary of impact of sea ice
Lee and Feldstein (2014)

36. Interference in the upper troposphere
Constructive
Interference:
Positive SWI
Destructive
Interference:
Negative SWI
Constructive and destructive interference between the climatological
stationary eddies and transient eddies for all seasons (Goss et al. 2015)