lennart bengtsson essc, uni. reading thorpex conference december 2004 predictability and predictive...

Lennart BengtssonESSC, Uni. Reading

THORPEX Conference December 2004

Predictability and predictive skill of weather systems and atmospheric flow patterns

-25 years of progress--The legacy of FGGE-

Professor Lennart Bengtsson

ESSC, University of Reading, UK

MPI for Meteorology, Hamburg

Many thanks to colleagues at ESSC and ECMWF

and especially to Kevin Hodges, ESSC



Predictability and predictive skill of weather systems and atmospheric flow patterns

The improvements in NWP over the last 25 years

• The impact of observations on forecast skill

• The importance of data-assimilation

• How much better can the forecasts be?

• The need for a new initiative in weather forecasting



Improvements in NWP from Miyakoda (1972) to 2002. Courtesy ECMWF

How long to get to D+10 in winter?



What are the causes of the improvements?

• More accurate models

• Advanced data-assimilation

• Better observational coverage



The principle of error reduction in data assimilation



Same model and data- assimilation but different observations. Results from ERA40 Courtesy ECMWF



Note that the error growth is virtually unchanged between the time of a good forecast (r=0.90) and the time of a useful

forecast (r=0.60). This fall in skill takes ca. 3.5 days



Possible causes?

• When errors have reached a certain size the growth rate is determined by internal dynamics. If so the skill can only be increased by a more accurate initial state.

• Or, there are errors due to down-scale cascade, say from tropical forcing, which not yet is properly handled by models

• Or, perhaps errors, due to aliasing or to incorrect handling of the up-scale cascade of physical processes, such as convection, projecting the errors on synoptic scale modes leading to an overly rapid growth?



There are large variations in forecast skillECMWF 1000 hPa height anomaly correlation

Cumulative frequency distribution for Europe. Winter 1988 and 1998



0

10

20

30

40

50

60

70

80

90

100

1 2 3 4 5 6 7 8 9 10

Forecast days

Anomaly correlation

There are large variations in forecast skillECMWF 500 hPa height anomaly correlation, Europe. Winter 1998 and 2004. Courtesy H Böttger, ECMWF

95% 75%

50%

25%

5%

Jan-Mar 1998

Jan-Mar 2004



Improvements in predictive skill in atmospheric flow patterns since FGGE

• NH extra-tropics has improved by more than three days• SH extra-tropics is as good as the NH• Five day forecasts in the tropics are as good as a one day

forecast 25 years ago But There are large differences in skill from day to day The time it takes for a forecast at 90% correlation to reach

60% correlation in the extra-tropics is about 3.5 days. This has not changed. Forecast improvements is due to more accurate initial states.



The impact of observations on forecast skillExperiments with different observing systems

DJF 1990/91 using ERA40 observations

• The control system (using all observations)

• A terrestrial based system ( radio-sondes and aircraft obs.)

• A satellite based system ( satellites and surface pressure)

• A surface based system ( surface observations)



Global forecasts DJF 90/91

• 7- day forecasts, every 6hr.• Later ECMWF model T159/L60

• Extra-tropics 20-90N and 20-90S• 500 hPa Z, normalized SD for the period

• Tropics 20N-20S

• Wind vector field 850 and 250hPa



Observing systems and predictive skillNorthern Hemisphere extra-tropics

Bengtsson and Hodges, 2004



Observing systems and predictive skillSouthern Hemisphere extra-tropics




Observing systems and predictive skillTropics V 250 hPa




Observing systems and predictive skillNorthern Hemisphere Z 500 hPa

DJF 1990/91 (full line) and DJF 2000/01 (dashed))



Observing systems and predictive skillSouthern Hemisphere Z 500 hPa

DJF 1990/91 (full line) and DJF 2000/01 (dashed))



Forecast skill and observations

• The terrestrial system is the best at the NH extra-tropics

• The satellite system is crucial for the SH extra-tropics

• In the tropics the terrestrial system and the satellite system are equally useful and highly complementary

• Between 1990 and 2000 the satellite system has increased its information content and the terrestrial system has decreased it



The impact of observations on forecast skillExperiment with ERA40

The impact of observations of humidity on NWP

360 global forecasts DJF 1990/91



Impact of humidity observationsNH Z 500 hPa

Full observing systemNo humidity observations in data-assimilation



Impact of humidity observationsSH Z 500 hPa




Impact of humidity observationsTropics wind at 850 hPa




Impact of humidity observationsTropics wind at 850 hPa (mean error at day 5)


Control

No humidity



Humidity observationsin present data-assimilation

• Moisture observations have no detectable influence on the overall large scale predictive skill

• During the cause of the data-assimilation the large scale moisture field is mainly controlled by the model dynamics

• There is an urgent need to develop techniques for a better assimilation of humidity observations



Assessment of predictability

• Growth of small perturbations inserted in a model

• Comparing how consecutive forecasts separate from each

other ( Lorenz, 1982)



Estimation of predictability ( Lorenz, 1982)

The error between consecutive forecasts separated by a day ( or shorter) is a suitable expression for predictability. The initial error is then the difference between the analysis an day 1 and the forecast from the day before



Predictive skill ( Z 500 hPa) for the NHand predictability estimates ( for 6 ( red)

and 24 hr (blue) increments)



Predictive skill ( Z 500 hPa) for the SHand predictability estimates ( for 6 ( red)




Predictive skill ( V 850 hPa) for the Tropicsand predictability estimates ( for 6 ( red)




What are the predictive skill and predictability of storm-tracks?

• Storm- tracks as a proxy for predicting the transient weather

• Predictive skill of storm-tracks as a function of the observing system

• Estimation of predictability following Lorenz (1982)



NH, MSLP, Cyclones

Tracks Intensities



NCEP Ensemble Storm TracksCourtesy Z Todt, NCEP and L Froude, ESSC



Predictive skill and predictability of storm tracksfor different observing systems

NH

SH



Conclusions

• Major progress have been achieved following the FGGE in 1979 but significant improvements are still feasible

• Predictability estimates indicate a possible gain of several days compared to the present best forecasts

• The largest potential improvements are in the tropics

• The Thorpex program is a timely initiative and should be strongly supported



What is needed?

• Weather independent observations of wind and temperature profiles

• Research to better identify priorities of the observing system

• Higher resolution in model integrations to reduce numerical errors and representation problems and to simplify the parameterization of physical processes

• Continue dedicated process studies and associated field experiments



END

lennart bengtsson essc, uni. reading thorpex conference december 2004 predictability and predictive...

Documents

essc slide

reading thorpex conference

university of reading

days slide

forecast skill ecmwf

data assimilation slide

era40 courtesy ecmwf

weather forecasting