1. Bo Christiansen Downward propagation from the stratosphere:
Physical mechanism and potential for seasonal prediction
Bo Christiansen
Danish Meteorological Institute
What is it?
How can we explain it?
How can we use it?

2. Downward propagation of zonal mean zonal wind in ERA40.
Annual cycle and timescales faster than 30 days are removed.
Watch the movie at

3. Downward propagation is robust and ubiquitous
Minimal model
Holton Mass model
Perp. Jan. GCM
Full GCM
Observations
Zonal wind at 60 N

4. Quasi-Biennial Oscillation

5. Schematic overview of the statistical forecast model
P is the predictand
pi, i=0,..,n-1 are the n predictors
T is the lead time
Tau is the time over which the predictand is averaged
Delta is time interval between the predictors
The predictand will be the zonal mean wind at the surface or the near surface temperature in northern Europe
The predictors pi will be the zonal mean wind at different vertical levels
Only the winter season is considered

6. Only winter, DJF Forecast skill as function of lead time T
for different vertical levels of the predictor.
Forecast of daily values
70 hPa
10 hPa
surface
Purple curve shows forecast when
wind at surface and at 70 hPa are
used as predictors simultaneously
Forecast of 14 days means
70 hPa
10 hPa
surface
Only winter, DJF

7. The forecast skill as function of lead time and the vertical level of the predictor.
Daily values are predicted. Winter season.

8. The forecast skill as function of lead time and the time over which the predictand is averaged.
The level of the predictor is 70 hPa.
The forecast skill as function of lead time and the strength of the predictor.
14 days means are forecasted.

9. Probability distribution of two weeks mean of the normalized surface zonal mean zonal wind for quintile intervals of the predictor 7 days before.
70 hPa as predictor
Surface as predictor

10. The Ranked Probability (Brier) Skill Score as function of lead time
The Ranked Probability (Brier) Skill Score as function of lead time. The score measures the skill of the probabilistic forecast relative to climatology.
7 days means are forecasted.
70 hPa
surface

11. 51 events from the ECMWF ensemble seasonal prediction system.
Comparison with dynamical forecast.
51 events from the ECMWF ensemble seasonal prediction system.
Model
Model+70 hPa
70 hPa
70 hPa,
51 events
surface
Predictand is surface wind at 60 N, Daily values are forecasted.

12. Vertical component of EP-flux at 60 N
Vertical component of EP-flux at 100 hPa
Zonal mean wind at 60 N

13. Covariance between zonal mean wind
at 10 hPa, 60 N and components in the
balance equation for zonal monentum.
Lag (days)

14. height
Radiative
equilibrium
wind
The basic mechanism

15. A minimal model Coriolis term Zonal wind trend Wave coupling
1-dimensional:
Simple resistance:
Nonlinear coupling (Charney-Drazin):

16. Conclusions
Downward propagation is ubiquitous: found in observations and models of different complexity
Downward propagation driven by waves from the troposphere and the two-way interaction between mean flow and waves is important
Stratospheric information improves statistical surface forecasts on time-scales 5-60 days (with up to 100 %)
Best predictor found in lower stratosphere
The simple statistical forecast with stratospheric information is as good as a dynamical ensemble system
Model and stratosphere are orthogonal. Room for model improvement