User experience with extended range forecasts -- climatic aspects of ECMWF products Christof Appenzeller Wolfgang Müller Heike Kunz Mark Liniger ERA-40.

User experience with extended range forecasts-- climatic aspects of ECMWF products

Christof AppenzellerWolfgang MüllerHeike KunzMark Liniger

ERA-40 compared to Swiss observations

Verification of seas. forecasts monthly forecasts in electricity

market seas. forecasts in media

2

ERA-40 T2 Upscaling

ZERA-40 - ZSchw.Stat. ~ 40m

3

ERA-40 T2 seasonal CycleT

emp

erat

ure

[°C

]

Temperature:

ERA-40, Swiss Stations

16

14

12

10

8

6

4

2

0

- 2

JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC

T[°

C]

Temperature difference:

ERA-40 – Swiss Stations

1.2

0.8

0.4

0.0

-0.4

-0.8

JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC

ERA-40 in Summer 0.8°C too high

ERA-40 in Winter 0.4°C too low

4

ERA-40 & GPS IWV: Correlation

Morland et al., submitted

5

IWV: Height dependent bias

Morland et al., submitted

6

System 2: Climate variability

ERA-401959 - 2001

System 2Nov. Fcsts.1987 - 2001

Müller et al. (2005), Clim. Dyn.

DJF North Atlantic Oscillation (NAO)EOF Z500

7

Predictability of NAO

Müller et al. (2005), Clim. Dyn.

regression of Z500 fields

8

Impact of climate variability

ERA-401959 - 2001

System 2Nov. Fcsts.1987 - 2001

Müller et al. (2005), Clim. Dyn.

DJF North Atlantic Oscillation (NAO)SVD Z500 & T2m

9

Predictability of NAO Impact

Müller et al. (2005), Clim. Dyn.

regression of T2m fields

10

Verification grid point

RPSSdT2m, 1987 – 2002, fc234, 3 cat.

Schwierz et al., subm.

against ERA-40

Perfect model approach

11

extended range forecast products at MeteoSwiss

seasonal forecasts T2m, Precip. Klimagramms probability maps

monthly forecasts T2m, Precip, Geopot. tercile maps

Klimagramm

12

Weather risk application

months

tem

pera

ture

ano

mal

y

Seasonal Forecast

Probabilistic Downscaling

local weather risk

13

Electricity Market

Electricity company in Southern Switzerland Monthly forecasts

14

Using monthly forecasts Contracts at EEX (European Energy Exchange) Lowermost tercile for S-Germany (spatial avg).

Forward Prices vs. Temperature

0

10

20

30

40

50

60

02.0

2.2

005

04.0

2.2

005

06.0

2.2

005

08.0

2.2

005

10.0

2.2

005

12.0

2.2

005

14.0

2.2

005

16.0

2.2

005

18.0

2.2

005

20.0

2.2

005

22.0

2.2

005

24.0

2.2

005

26.0

2.2

005

28.0

2.2

005

02.0

3.2

005

04.0

3.2

005

06.0

3.2

005

08.0

3.2

005

10.0

3.2

005

12.0

3.2

005

14.0

3.2

005

16.0

3.2

005

18.0

3.2

005

[€/M

Wh

]

0

10

20

30

40

50

60

70

80

90

100

[%]

Germany Peaks Wk12- 05

Temperature low er tercile

EE

X E

u/M

Wh

low

erm

ost t

erci

le %

Lead time

Contracts for peak load in week 12 (21.-27.3.2005)

T2 Zurich

• persistence?• other forecasts?• ?

15

Summer 2005 in Switzerland

ProbabilityT2m > norm

Klimagramm for Swiss-Temperature

16

MediaBasis MeteoSwiss does not intend to publish seasonal forecasts

for Switzerland. Public presentation of Swiss climate research programme.Interview Probability of Temperature in JJA > norm. Signal: 40-50%. Norm value: 17 oC. (JJA daily avg). Hit rate around 55 to 60%. Ocean information is important.Published Headline:

“MeteoSwiss: Summer will be cool” 40% used as signal. Hit rate compared to skill of 84% for next day forecast. Map of current buoys as basis for forecasts.

17

same and next days:

prime time news on national television (French and German).

several radio interviews. copied by several news paper (without feedback). scientific facts and context somewhat distorted and

wrongly quoted. main message: cool summer

18

19

Competing Sunday Press Journal Front page

“Summer 05: Weather-forecast destroys tourism!Tourism directors criticize meteorologists”

Headline“Weather forecasters drive away tourists”

Short street interviews → people would use seasonal forecasts for holiday planning.

Tourism industry: “Other countries would never have the idea to talk badly about their own products”

Forecasts are reason for low earnings in tourism industry ?! “Would the forecasts predict a nice summer, we would be happy”

20

Conclusions for handling press

JJA average of 17 oC is cool. Give clear numbers, no ranges/choices → extremes will be chosen Available actual forecasts will be published and used. A “scientific”

context or “experimental” label can get lost. Observations are preferred to models as technological basis for

forecasts. Should seasonal forecasts be published for the public? if yes, how?

Bulletin, press release, selected interviews, individually on request Tourism industry: stronger fluctuations due to weather and climate

forecasts? Tourists (would) use forecasts for booking, industry seems not to.