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Development of the deterministic forecast system (June 2006) Martin Miller (Head of Model Division) with input from many colleagues

1 Development of the deterministic forecast system (June 2006) Martin Miller (Head of Model Division) with input from many colleagues

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Page 1: 1 Development of the deterministic forecast system (June 2006) Martin Miller (Head of Model Division) with input from many colleagues

1

Development of the deterministic forecast system

(June 2006)

Martin Miller(Head of Model Division)

with input from many colleagues

Page 2: 1 Development of the deterministic forecast system (June 2006) Martin Miller (Head of Model Division) with input from many colleagues

2

Operational changes

from June 2004 up to

June 2005

(the last User Meeting)

• 29 June 2004 – Early Delivery System

• 28 September 2004 – IFS cycle 28r3

• 18 October 2004 – IFS cycle 28r4

• 5 April 2005 – IFS cycle 29r1

• 28 June 2005 – IFS cycle 29r2 (examples)

Day

Anomaly correlation of 500hPa forecasts for Europe

Mean from 1 Dec 2004 to 28 June 2005

Cycle 29r2Cycle 29r1

Page 3: 1 Development of the deterministic forecast system (June 2006) Martin Miller (Head of Model Division) with input from many colleagues

3

Assimilation of rain-affected microwave radiancesand improvement of humidity analysis

Rain Asm

Hurricane CharleyTrack forecasts from 12 UTC 11 Aug

2004

e-suite ops

Global 1.74 1.90N. Hemisphere 1.63 1.71Tropics 2.12 2.43S. Hemisphere 1.53 1.62N. Atlantic 1.63 1.69N. Pacific 1.57 1.69

St.dev(kg/m2)

Comparison of cycle 29r2e-suite and operations

with independent TCWV retrievals from Jasonmicrowave radiometer

Page 4: 1 Development of the deterministic forecast system (June 2006) Martin Miller (Head of Model Division) with input from many colleagues

4

Bias-correction of surface-pressure observations

Altamera, Brazil

December 2004 April 2005

Page 5: 1 Development of the deterministic forecast system (June 2006) Martin Miller (Head of Model Division) with input from many colleagues

5

Use of Baltic Sea Ice Analysis from SMHI

Mean sea-ice concentration 5 - 24 January 2004

NCEP analysis Local analysis

Page 6: 1 Development of the deterministic forecast system (June 2006) Martin Miller (Head of Model Division) with input from many colleagues

6

Also included :

• Refinements to use of ATOVS and AIRS

• Improved use of TEMP and SYNOP humidity observations

• Lower surface-pressure observation errors for automatic stations

• Use of Meteosat-8 (MSG) winds

• Statistics for Wavelet Jb from new ensemble data assimilation

• Small revisions to surface, convection and cloud schemes

• Better vertical diffusion in first minimization of 4D-Var

Page 7: 1 Development of the deterministic forecast system (June 2006) Martin Miller (Head of Model Division) with input from many colleagues

7

1 February 2006 – IFS cycle 30r1

• T799 horizontal resolution for deterministic forecast

• 4D-Var increments at T255 (30min time step)

- Use of grid-point humidity and ozone

- Revised ozone chemistry

• 91-level vertical resolution

• Changes to the wave model ‑ Grid spacing reduced from 0.5° to 0.36°

‑ Use of Jason altimeter wave height data and ENVISAT ASAR spectra in the wave model assimilation

• T399 L62 resolution for EPS

‑ Wave model grid unchanged at 1°, but number of frequencies increased from 25 to 30, and number of directions from 12 to 24

Page 8: 1 Development of the deterministic forecast system (June 2006) Martin Miller (Head of Model Division) with input from many colleagues

8

T799 orog

Page 9: 1 Development of the deterministic forecast system (June 2006) Martin Miller (Head of Model Division) with input from many colleagues

9

T799 grid

Globe has 843,490 points(348,528 for the T511 grid)

Resolution ~25km

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0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0 0 0 0

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0 0 0 0 0 0 0 0 0 0 0 00

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0 0

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0

0

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0 0 0 0 0 0

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0 0 0 0 0 0 0 0 0 0

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00 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0

0

00 0 0 0 0 0 0

0 0 0 0 0 0 0 0

0 0 0

000 0 0 0 0 0

0 0 0 0 0 0 0 0 0

0

0 0 00 0 0 0 0 0

0 0 0 0 0 0 0 0 00 0

0 0

0 0 0 00 0 0 0 0

0 0 0 0 0 0 0 0 0

0 00 0 0

0 0 00 0 0 0 0

0 0 0 0 0 0 0 0 0

0 00 0 0 0 0

0 00 0 0 0 0

0 0 0 0 0 0 0 0 0

0 0 0 0 0 0

00 0 0 0

0 0 0 0 0 0 0 0 0

0 0 0 0 0

0 0 0 0

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00 0 0 0 0 0

0 0 0 0

0 0 0 0 0 0 0 0 0 00 0 0 0 0 0

0 0 0 0

0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00

0 0 0 00

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00

0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0

0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00 0 0

0 0 0 0 0

00 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0

0 0 00 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0

0 0 0 00 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 00 0

0 0 0

0 0 0 0 0 00 0

0 0 0 0 0 0 0 0 0 0 0 0 0 00

0 0 0

0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0

0

0 0 0 0 0 00 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 00

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 00 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 00 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0 00 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0

0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0

0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 0

0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0

0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 00 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0

0 0 00

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 00

00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 00

0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0 00 0 0

0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 00 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 0

0 0 0 0 0 0 0 0 0 0 0 0

0 0 0 0 0 00 0

0 0 0 0

0 0 0 0 0 0

0 0

00

1

1 1 1 1 1

1 1 1 1 1 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 11

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 11 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1

1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 11 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 11 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1

1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1

1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 11

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 11 1 1 1 1 1 1 1 1 1 1

1 11 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 11 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 11 1 1 1 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 11 1 1 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 11

1 1 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 11 1 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 11 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 11 1 1 1 1 1 1

1 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 1 11 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 1 11 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 11 1 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

11 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 11 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 1 1 1 1 11 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 1 1 1 11 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 1 1 1 11 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 11 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 11 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 11 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 11 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 11 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 1 11 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 11 1 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 11 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 11 1 1 1 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 1 1 1 1 11 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 11 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 11

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 11 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 11 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 11 1 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1

1 1 1 1 1 1 1 1 1 1 1

1

60°N

70°N

20°E

20°E 40°E

40°E

ECMWF Analysis VT:Monday 1 January 1996 00UTC Surface: land/ sea mask

Page 10: 1 Development of the deterministic forecast system (June 2006) Martin Miller (Head of Model Division) with input from many colleagues

10

Vertical Resolution Increase

The number of vertical levels for analysis and deterministic model increased from 60 to 91. Largest resolution increase near the tropopause Model top raised from 0.1hPa (~65km) to 0.01hPa

(~80km).

Position of levels and pressure layer thickness of L60 (blue) and L91 (red)

L91L600.01

0.02

0.03

0.050.07

0.1

0.2

0.3

0.5

0.7

1

2

3

5

7

10

20

30

50

70

100

200

300

500

700

1000

Pre

ssu

re (h

Pa

)

60 levels 91 levels

1

2

3

4

5

6

7

8

9

10

12

14

16

18

20

25

30

35

40455055606570

91

Leve

l nu

mb

er

0.01hPa

0.1hPa

Page 11: 1 Development of the deterministic forecast system (June 2006) Martin Miller (Head of Model Division) with input from many colleagues

11

Fit to Aircraft data:

V-wind in NH extra-tropics

Page 12: 1 Development of the deterministic forecast system (June 2006) Martin Miller (Head of Model Division) with input from many colleagues

12

Fit to Radiosonde Data:U-Wind in the Tropics

used UTEMP-Uwind Tropicsexp:0028 , ref:oper 2005080100-2005083112(12)

nobsexp

10046 10079 12858 13821 11692 9576 7697 7757

10098 16468 14853 12940 8444 4997 4655 872

exp - ref

+69 -3

+18 +5 +4 +7 +3 +25

+111 +303 +138 +44 +11 +2 -20 -3

0 1.6 3.2 4.8 6.4 8

STD.DEV

1000 850 700 500 400 300 250 200 150 100 70 50 30 20 10 5

Pre

ssur

e (h

Pa)

-4 -3 -2 -1 0 1 2 3 4

BIAS

1000 850 700 500 400 300 250 200 150 100 70 50 30 20 10 5

background departure o-b(ref)background departure o-banalysis departure o-a(ref)

analysis departure o-a

Page 13: 1 Development of the deterministic forecast system (June 2006) Martin Miller (Head of Model Division) with input from many colleagues

13

Green numbers: T799L91 better than T511L60, red numbers: T799L91 is worse

Statistical significance (t-test) for Z 500hPa scores from 304 forecast

Day 1 Day 3 Day 5 Day 7

N HemAC:

RMS:

0.1%

0.1%

0.1%

0.1%

2%

0.2%

-

-

S HemAC:

RMS:

0.1%

0.1%

0.1%

0.1%

0.1%

0.1%

0.2%

0.1%

EuropeAC:

RMS:

0.1%

0.1%

0.1%

0.1%

5%

0.1%

-

10%

Page 14: 1 Development of the deterministic forecast system (June 2006) Martin Miller (Head of Model Division) with input from many colleagues

14

00UTC 12 December 2005: Pmsl and 10m windspeed

D+3

D+3

D+4

D+4

D+5

D+5

Analysis

Analysis Operations

T799L91

Page 15: 1 Development of the deterministic forecast system (June 2006) Martin Miller (Head of Model Division) with input from many colleagues

15

00UTC 9 January 2005: Pmsl and 10m windspeed

D+2

D+2

D+3

D+3

D+4

D+4

Analysis

AnalysisOperations

T799L91

Page 16: 1 Development of the deterministic forecast system (June 2006) Martin Miller (Head of Model Division) with input from many colleagues

16

Forecasts of Katrina for 12 UTC, Monday 29 August

OperationalT511 L60

72h forecast

36h forecast

OperationalT511 L60

TestT799 L91

TestT799 L91

+

++

+

Page 17: 1 Development of the deterministic forecast system (June 2006) Martin Miller (Head of Model Division) with input from many colleagues

17

105

1

959

980

980

990

990

990

1000

1000

10001000

1000

100030°N 30°N

90°W

90°W 20050826 00UTC t+72h VT: 20050829 00UTCT511

Hurricane Katrina - MSLP and 3h accum. precipitation

0.5

1

2

5

10

20

40

70

125

200

300

500

1000

198

1

921970

980

980

990

990

990

1000

1000

1000

1000

1000

1000

30°N 30°N

90°W

90°W 20050826 00UTC t+72h VT: 20050829 00UTCT799

Hurricane Katrina - MSLP and 3h accum. precipitation

0.5

1

2

5

10

20

40

70

125

200

300

500

1000

opsT511

e-suite T799

Hurricane Katrina in operations and e-suite: t+72h

Page 18: 1 Development of the deterministic forecast system (June 2006) Martin Miller (Head of Model Division) with input from many colleagues

18

26th 00UTC 3.5 days

26th 12UTC 27th 00UTC 2.5 days

Page 19: 1 Development of the deterministic forecast system (June 2006) Martin Miller (Head of Model Division) with input from many colleagues

19

This upgraded forecasting system provides:

more accurate analyses and forecasts leading to better medium-range forecast guidance from both the deterministic and ensemble prediction systems

improved input to limited area forecasting in the Member States

more skilful forecasts of most types of severe weather

a better (more accurate) system on which to base research and development to further the expectations of the ECMWF longer-term strategy

Remarks

Page 20: 1 Development of the deterministic forecast system (June 2006) Martin Miller (Head of Model Division) with input from many colleagues

20

7 February 2006 – New radiance bias correction

Applied statically, but derived from variational scheme to be implemented with cycle 31r1

pre

ssu

re (

hP

a)

Sonde-bg ControlSonde-bg New bias correctionSonde-an ControlSonde-an New bias correction

Temperature (K)

N Hem

RMS error of 300hPa tropical temperature forecasts

New bias correction

Control

Mean from 8-31 Jan 2006

Day

Page 21: 1 Development of the deterministic forecast system (June 2006) Martin Miller (Head of Model Division) with input from many colleagues

21

Coming next – IFS cycle 31r1 (Aug 2006)

• Variational radiance bias correction

• Thinning of low-level AMDAR data

• Revisions to the 1D and 4D-Var rain assimilation

• Improved treatment of ice sedimentation, auto-conversion to

snow in cloud scheme and super-saturation with respect to ice

• Implicit treatment of convective transports

Page 22: 1 Development of the deterministic forecast system (June 2006) Martin Miller (Head of Model Division) with input from many colleagues

22

IFS cycle 31r1 continued (Aug 2006)

• Introduction of turbulent orographic drag scheme

• Includes changes for EPS extension to day 15

‑ T255 perturbed forecasts from day 10 to day 15

‑ T399/255 control to day 10/15

‑ Also uniform T399 and T255 controls to day 15

• To be used in version 3 of Seasonal Forecasting System

• Also for the Interim reanalysis (1989 onwards)

Page 23: 1 Development of the deterministic forecast system (June 2006) Martin Miller (Head of Model Division) with input from many colleagues

24

Simple ECMWF scheme: comparison to Mozaic aircraft data

(from Gierens et al.)Region Lat:30./70., Lon:0./360.

0.8 1.0 1.2 1.4 1.6 1.8RH

0.001

0.010

0.100

1.000

10.000

Fre

q

defaultclipping to Koop

new parameterizationMoziac

New scheme

Aircraft data

Default

Page 24: 1 Development of the deterministic forecast system (June 2006) Martin Miller (Head of Model Division) with input from many colleagues

25

Impact on relative humidity (RH) climatology

31r1 – 30r1 annual mean difference

Largest changes in the tropical upper troposphere

Page 25: 1 Development of the deterministic forecast system (June 2006) Martin Miller (Head of Model Division) with input from many colleagues

27

CY31R1: New vegetation roughness + turbulent orographic form drag scheme (TOFD)

•Vegetation roughness from correspondence table linked to dominant land use type (Mahfouf et al. 1995)•Scales of interest are below 5 km • Use most recent 1 km orographic data • Wood and Mason (1993) parametrization for surface drag• Drag distribution over model levels rather than effective roughness length concept (Wood, Brown and Hewer, 2001)• Parametrize orographic scales from 5 km to the smallest scales as an integral over an empirical orographic spectrum (Beljaars et al. 2004

Examples of orographic spectra from 100m data over the USA

Measure spectral amplitude from 1 km data.

Extrapolate spectrum by making assumption about power law.

dkekcUkFkCz

o

m

k

czkmm

/23 )/()(2

Page 26: 1 Development of the deterministic forecast system (June 2006) Martin Miller (Head of Model Division) with input from many colleagues

28

Impact of TOFD + new roughness lengths

Smaller drag coefficients: diff stress/wind(level48)^2

Higher 10m wind

Page 27: 1 Development of the deterministic forecast system (June 2006) Martin Miller (Head of Model Division) with input from many colleagues

29

Revised numerics of gust parametrization only (CY31R1) Old New

Without

stochastic

physics

With stochastic

physics

Page 28: 1 Development of the deterministic forecast system (June 2006) Martin Miller (Head of Model Division) with input from many colleagues

30

Mean gust averaged over 14 days: gust from 24-36 hour forecasts verifying at 0-12 UTC

New (CY31R1)

Old (CY30R1)

New-Old

Page 29: 1 Development of the deterministic forecast system (June 2006) Martin Miller (Head of Model Division) with input from many colleagues

31

Observed gusts versus model gusts (12 to 24 hour forecasts)

New (CY31R1)

Old (CY30R1)

Page 30: 1 Development of the deterministic forecast system (June 2006) Martin Miller (Head of Model Division) with input from many colleagues

32

CY31R1: only non-blocked part of subgrid orography excites gravity waves (cutoff mountain)

Lott and Miller 1997

Only this height is used to excite gravity waves.

Page 31: 1 Development of the deterministic forecast system (June 2006) Martin Miller (Head of Model Division) with input from many colleagues

33

Impact of cutoff mountain in

subgrid orography parametrization

15°N 15°N

30°N30°N

45°N 45°N

75°E 90°E 105°Eeo19-eo19 an: T511 Jan2005 average T+96h vertical ly integrated zonal wind error (Pa s) (level 1 to 60)

-25000

-20000

-15000

-10000

-5000

-2500

2500

5000

10000

15000

20000

25000

15°N 15°N

30°N30°N

45°N 45°N

75°E 90°E 105°Eeppr-eo19: T511 Jan2005 average T+96h vertically integrated zonal wind error (Pa s) (level 1 to 60)

-25000

-20000

-15000

-10000

-5000

-2500

2500

5000

10000

15000

20000

25000

15°N 15°N

30°N30°N

45°N 45°N

75°E 90°E 105°Eeppr-eo19 an: T511 Jan2005 average T+96h vertical ly integrated zonal wind error (Pa s) (level 1 to 60)

-25000

-20000

-15000

-10000

-5000

-2500

2500

5000

10000

15000

20000

25000

T511 average vertically integrated zonal wind error from 96h CY29R1 forecasts from 12Z on each day of January 2005 using the new turbulent orographic drag scheme and cutoff mountain.

Error: FC-AN

Old

Error: FC-AN

New

Diff: FC_new-FC_old

Page 32: 1 Development of the deterministic forecast system (June 2006) Martin Miller (Head of Model Division) with input from many colleagues

34

1d+4d-Var Rain Assimilation Modifications proposed for CY31R1:

• Inclusion of 10m-wind speed in 1D-Var control vector: x = (t, q, u10, v10)• Revised q/c and replacement of ESSL routines for (B) Eigenvector calculations• DMSP satellite specific bias correction; more predictors (TCWV, SST, SWS, RWP)• Screening of areas with excessive frozen precipitation (mainly SH)

Rejected due to excessive frozen precip (260141)

-135 -90 -45 0 45 90 135

-90

-75

-60

-45

-30

-15

0

15

30

45

60

75

Successful 1D-Var (423457)

-135 -90 -45 0 45 90 135

-75

-60

-45

-30

-15

0

15

30

45

60

75

90

050

100

150

200

250

300

350

400

450

500

550

600

650

700

750

800

850

900

950

1000

1050

1100

1150

1200

12501300

Num

ber

of o

bser

vatio

ns p

er 5

by

5 de

gree

box

DMSP-F13

-135 -90 -45 0 45 90 135

-90

-75

-60

-45

-30

-15

0

15

30

45

60

75

90

DMSP-F14

-135 -90 -45 0 45 90 135

-90

-75

-60

-45

-30

-15

0

15

30

45

60

75

90

DMSP-F15

-135 -90 -45 0 45 90 135

-90

-75

-60

-45

-30

-15

0

15

30

45

60

75

90

August 2005 er6k 1D-Var mean TCWV increment

-0.5

-0.4

-0.3

-0.2

-0.1

0.0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1.0

1.1

1.2

1.3

1.4

1.5

kgm

-2

DMSP-F13

-135 -90 -45 0 45 90 135

-90

-75

-60

-45

-30

-15

0

15

30

45

60

75

90

DMSP-F14

-135 -90 -45 0 45 90 135

-90

-75

-60

-45

-30

-15

0

15

30

45

60

75

90

DMSP-F15

-135 -90 -45 0 45 90 135

-90

-75

-60

-45

-30

-15

0

15

30

45

60

75

90

1-21 Aug 2005 ers5 1D-Var mean TCWV increment, % of mean TCWV

-4.0

-3.6

-3.2

-2.8

-2.4

-2.0

-1.6

-1.2

-0.8

-0.4

0.0

0.4

0.8

1.2

1.6

2.0

2.4

2.8

3.2

3.6

4.0

%

1D-Var Performance Mean TCWV Increments Mean TCWV Increments

CY30R2 CY31R1

Page 33: 1 Development of the deterministic forecast system (June 2006) Martin Miller (Head of Model Division) with input from many colleagues

35

-90 -60 -30 0 30 60 90Latitude

1000

800

600

400

200

Pre

ssur

e, h

Pa

-1.0-0.9-0.8-0.7-0.6-0.5-0.4-0.3-0.2-0.10.00.10.20.30.40.50.60.70.80.91.0

RH

/%

-90 -60 -30 0 30 60 90Latitude

1000

800

600

400

200

Pre

ssur

e, h

Pa

-0.20-0.18-0.16-0.14-0.12-0.10-0.08-0.06-0.04-0.02-0.000.020.040.060.080.100.120.140.160.180.20

Tem

pera

ture

/K

48-hour Forecast RMSE Difference CY31R1-CY30R2

Relative humidity

Temperature

>0: CY30R2 better<0: CY31R1 better

(August 2005, T511L60)

Page 34: 1 Development of the deterministic forecast system (June 2006) Martin Miller (Head of Model Division) with input from many colleagues

36

Also planned for later in 2006:

• Use of surface albedo fields from MODIS

• Use of high-resolution NCEP SST fields

• Refinements to stratospheric analysis

• Recalibrated radiosonde temperature bias corrections

• Unified medium-range/monthly EPS

Page 35: 1 Development of the deterministic forecast system (June 2006) Martin Miller (Head of Model Division) with input from many colleagues

37

And possibly at the end of 2006:

• 4D-Var changes:‑ 3rd inner loop‑ revised trajectory interpolation‑ revised data usage, including modified Var QC‑ new cloud and convection schemes in minimization

• Upgrade fast radiative transfer to RTTOV-9

• Change model short-wave radiation scheme to RRTM-SW

• Upgrades to ocean wave advection and assimilation

And over course of the year:

• Monitoring and later assimilation of data from:‑ AMSR-E, CHAMP, COSMIC, FY-2C, METOP ATOVS + … ,

MET9, MTSAT, SSMIS, TMI