Aims and Requirements for Ensemble Forecasting By T.N.Palmer ECMWF.

Aims and Requirements for Ensemble Forecasting

By

T.N.Palmer

ECMWF

A Brief History of Ensemble Prediction for Weather/Climate

Monthly forecasting

Medium Range Seasonal-to-Interannual

Short range Climate Change

1980s

1990s

2000s

“Roots of ensemble forecasting” J.M Lewis. Mon Wea Rev, 133, 1865 (2005)

First operational probabilistic ensemble forecast?

Used in Met Office commercial operations.

Scientific Basis for Ensemble Prediction

In a nonlinear dynamical system, the finite-time growth of initial uncertainties is flow dependent.

Lorenz (1963): prototype model of

chaos

October 1987!

is a nonlinear system

Since is a nonlinear function of

( )

dXF X

dtd X dF

X J Xdt dXF X

J J X

In a nonlinear system, finite-time predictability is a function of initial state

EPS spread/Error

12UTCEurope Lat 35.0 to 75.0 Lon -12.5 to 42.5

500hPa GeopotentialTime series curves

MAR2005

APR MAY JUN0

20

40

60

80

100

120

ENSTD T+24 Mean forecast

ENSTD T+48 Mean forecast

ENSTD T+144 Mean forecast

ENSMN T+24 Root mean square error forecast

ENSMN T+48 Root mean square error forecast

ENSMN T+144 Root mean square error forecast

ECMWF Ensemble Forecasts of Katrina

26 Aug 0z26 Aug 12z

27 Aug 0z 27 Aug 12z

Who is coming? Pthreshold

Queen 1%

Mayor

Mother-in-law

Mates from the pub

10%

30%

70%

Decision: Rent marquee if P>20%

Queen Mayor Mother

-in-lawMates from pub

From ECMWF web site.

Weather Roulette• London-Heathrow, 2m temperature

• 2002: training data for dressing

• 2003: test data

• odds: set by dressed T511 forecast

• bets: placed by best member dressed EPS

• start capital: £1 (re-invest all money, unlimited stakes)

odds(bin) = 1 / prob_hr(bin)bets(bin) = prob_eps(bin) * capital(t-1)

Daily winnings:

win(t) = odds(bin_v) * bets(bin_v) – capital(t-1)

= (prob_eps(bin_v)/prob_hr(bin_v) – 1) * capital(t-1)

Collaboration with L.Smith, LSE

Weather Roulette

Days in 20030 50 100 150 200 250 300 3500

20

40

Win

nin

gs

[lo

g_1

0 £]

168h lead time

Collaboration with L.Smith, LSE

Weather Roulette

Lead time [days] 1 2 3 4 5 6 7 8 9 100

25

50

Win

nin

gs

[lo

g_1

0 £]

Bootstrapping Results

Collaboration with L.Smith, LSE

DEMETER-based PDFs of malaria incidence for Botswana (forecasts made 5 months in advance

of epidemic; Thomson et al 2005)

5 years with lowest observed malaria incidence

5 years with highest observed malaria incidence

Why No Ensembles on the TV Weather

Forecasts?

956

AN 19871016, 06GMT

979

EPS Cont FC +66 h

984

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989

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MLSP 66-hour forecasts, VT: 16-Oct-1987, 6 UTC

TL399 EPS with TL95, moist SVs

Probability of Beaufort force 12 winds 6-12am October 16th 1987

“Weather forecasts are inevitably uncertain, sometimes more so than others. We now run our forecast models many times with slightly different starting conditions to assess the uncertainty in the forecasts. Press the red button on your remote control to see an estimate of the expected accuracy of the forecast for some of the main cities in the UK.”

Aims of Ensemble Forecasting

•To enhance (substantially) the value of numerical weather and climate forecasts by quantifying the flow-dependent uncertainty in the forecast

•To enhance the credibility of weather and climate forecasts, thereby allowing our profession to gain the respect of the public

Requirements for Ensemble Forecasting

•A better theoretical understanding of the role of error made in truncating/parametrizing the underlying PDEs of climate, on both initial uncertainty and forecast model uncertainty

•Much much much bigger computers (resolution, ensemble size and model complexity are all important)

•A recognition amongst media forecasters that uncertainty is an intrinsic part of the science of weather and climate prediction..and that the public will respect us more if we are more open about uncertainty

•A recognition amongst BBC TV producers that use of ensemble forecast information on weather forecasts can inform, educate and entertain the viewing public and is something worth giving more effort to.

“He believed in the primacy of doubt; not as a blemish upon our ability to know, but as the essence of knowing”Gleick (1992) on Richard Feynman’s philosophy of science.