F. Prates Data Assimilation Training Course April 2008 1

Error Tracking

F. Prates

F. Prates Data Assimilation Training Course April 2008 2

Monitoring of the forecasting system is carried out on daily basis by a meteorologist at ECMWF.

The main reason of this activity is to investigate bad or very inconsistent forecast by detecting deficiencies in the analysis and in the forecasting system.

Investigations are covering all aspects of the system, often dealing with initial conditions (data availability) and data assimilation problems.

INTRODUCTION

ERROR TRACKING BY MEANS OF SYNOPTIC-DIAGNOSIS

F. Prates Data Assimilation Training Course April 2008 3

Every day we summarize our findings in the MetOps Daily Report. The daily report is posted on our internal web site where can be accessed by people in RD and OD.

Every four months there is a special meeting (OD/RD meeting) in which OD present a summary of the daily reports of the previous months.*

Daily Report

F. Prates Data Assimilation Training Course April 2008 4

Investigations can be divided in the following main steps:

When did occur (Verification Scores)

Where did it happen (Error maps, EPS and Increment charts)

What caused the error (Departures from different obs syst)

TROUBLESHOOTING PROCEDURES

F. Prates Data Assimilation Training Course April 2008 5

WHEN?

Verification statistics should tell which forecast had a bad performance

F. Prates Data Assimilation Training Course April 2008 6

WHEN?

Verification statistics should tell which forecast had a bad performance

F. Prates Data Assimilation Training Course April 2008 8

WHEN ?

AN 30Jul 0Z

Fc+120Fc+144

Fc+168

F. Prates Data Assimilation Training Course April 2008 9

WHEN ? (comparison with other models)

546

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582

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30°N40°N

50°N

60°N

70°N

60°W

60°W

40°W

40°W

20°W

20°W

0°

0°

20°E

20°E 40°E

40°E

60°E

60°E

ECMWF Analysis VT:Monday 30 July 2007 00UTC 500hPa Geopotential

552

558

558

564564

570

570

576

576

582

582

588

588

588

59430°N

40°N

50°N

60°N

70°N

60°W

60°W

40°W

40°W

20°W

20°W

0°

0°

20°E

20°E 40°E

40°E

60°E

60°E

Wednesday 25 July 2007 00UTC Forecast t+120 VT: Monday 30 July 2007 00UTC 500hPa Geopotential

552552

558

558

564564

570

570

576

576

582

582

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594

30°N40°N

50°N

60°N

70°N

60°W

60°W

40°W

40°W

20°W

20°W

0°

0°

20°E

20°E 40°E

40°E

60°E

60°E

Wednesday 25 July 2007 00UTC BRAKL Forecast t+120 VT: Monday 30 July 2007 00UTC 500hPa Geopotential

546

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570

570

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582

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588

30°N40°N

50°N

60°N

70°N

60°W

60°W

40°W

40°W

20°W

20°W

0°

0°

20°E

20°E 40°E

40°E

60°E

60°E

Wednesday 25 July 2007 00UTC NCEP Forecast t+120 VT: Monday 30 July 2007 00UTC 500hPa Geopotential

NCEP D+5

MONTL D+5AN 30th 0Z

BRAKL D+5

Best forecast

F. Prates Data Assimilation Training Course April 2008 10

WHEN ? (Inconsistency between successive fcs)

FC 16th 12Z

FC 16th 0Z

a priori evaluation

F. Prates Data Assimilation Training Course April 2008 11

WHERE?

Different techniques are used to identify the origin of forecast error

1) Error maps:

A sequence of maps shows how initial errors will propagate downstream.

Focus on the evolution of the most amplified error wave train.

because …

Error patterns become more complex as the forecast range increases.

The energy associated to the wave train is transmitted by their group velocity which is different of phase speed of the individual perturbations.

F. Prates Data Assimilation Training Course April 2008 12

Winter track

Summer track

The most likely areas for errors (energy) to amplify rapidly (release) are baroclinic regions and developing cyclones

They provide the most efficient mechanism for the “spread of influence” in mid-latitude upper-tropospheric westerlies.

Theoretical and observational studies indicate that the energy associated to the wave packets travel at 30˚/day in midlatitudes.

ERROR PROPAGATION / DOWNSTREAM DEVELOPMENT *

(Anders Persson)

F. Prates Data Assimilation Training Course April 2008 13

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59230°N 30°N

40°N40°N

50°N 50°N

60°N60°N

70°N 70°N

80°N80°N

100°W

100°W 80°W

80°W 60°W

60°W 40°W

40°W 20°W

20°W 0°

0° 20°E

20°E 40°E

40°EWednesday 25 Jul 2007 T799: solid verifying analysis: dash difference: red/blue (dgpm)

ECMWF AN VT: 20070725 00UTC 500 Z/ ZECMWF AN VT: 20070725 00UTC 500 ** Z

F. Prates Data Assimilation Training Course April 2008 14

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592

3.3.2.

1.

1.0.

-4.

-2.

-2.

30°N 30°N

40°N40°N

50°N 50°N

60°N60°N

70°N 70°N

80°N80°N

100°W

100°W 80°W

80°W 60°W

60°W 40°W

40°W 20°W

20°W 0°

0° 20°E

20°E 40°E

40°EWednesday 25 Jul 2007 T799: solid verifying analysis: dash difference: red/blue (dgpm)

20070725 00UTC ECMWF FC t+24 VT: 20070726 00UTC 500 Z 20070725 00UTC ECMWF FC t+24 VT: 20070726 00UTC 500 ** Z

ECMWF AN VT: 20070726 00UTC 500 Z

F. Prates Data Assimilation Training Course April 2008 15

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576576

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544544

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9.

5.

3.3.

2.

-4.

-3.-3.

30°N 30°N

40°N40°N

50°N 50°N

60°N60°N

70°N 70°N

80°N80°N

100°W

100°W 80°W

80°W 60°W

60°W 40°W

40°W 20°W

20°W 0°

0° 20°E

20°E 40°E

40°EWednesday 25 Jul 2007 T799: solid verifying analysis: dash difference: red/blue (dgpm)

20070725 00UTC ECMWF FC t+48 VT: 20070727 00UTC 500 Z 20070725 00UTC ECMWF FC t+48 VT: 20070727 00UTC 500 ** Z

ECMWF AN VT: 20070727 00UTC 500 Z

F. Prates Data Assimilation Training Course April 2008 16

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59259

2

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560560

576576

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59259

2

10.

7.

3.

3.

2.

1. 0.

-9.

-6.

-3.

30°N 30°N

40°N40°N

50°N 50°N

60°N60°N

70°N 70°N

80°N80°N

100°W

100°W 80°W

80°W 60°W

60°W 40°W

40°W 20°W

20°W 0°

0° 20°E

20°E 40°E

40°EWednesday 25 Jul 2007 T799: solid verifying analysis: dash difference: red/blue (dgpm)

20070725 00UTC ECMWF FC t+72 VT: 20070728 00UTC 500 Z 20070725 00UTC ECMWF FC t+72 VT: 20070728 00UTC 500 ** Z

ECMWF AN VT: 20070728 00UTC 500 Z

F. Prates Data Assimilation Training Course April 2008 17

544544

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576576

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544544

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10.

10.

8.

5.

3.

2.

2.

-22.

-6.

30°N 30°N

40°N40°N

50°N 50°N

60°N60°N

70°N 70°N

80°N80°N

100°W

100°W 80°W

80°W 60°W

60°W 40°W

40°W 20°W

20°W 0°

0° 20°E

20°E 40°E

40°EWednesday 25 Jul 2007 T799: solid verifying analysis: dash difference: red/blue (dgpm)

20070725 00UTC ECMWF FC t+96 VT: 20070729 00UTC 500 Z 20070725 00UTC ECMWF FC t+96 VT: 20070729 00UTC 500 ** Z

ECMWF AN VT: 20070729 00UTC 500 Z

Wave train of errors

F. Prates Data Assimilation Training Course April 2008 18

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592592

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24.

16.

5.

3.

2.

1.

-20.

-10.

-6.-5.

30°N 30°N

40°N40°N

50°N 50°N

60°N60°N

70°N 70°N

80°N80°N

100°W

100°W 80°W

80°W 60°W

60°W 40°W

40°W 20°W

20°W 0°

0° 20°E

20°E 40°E

40°EWednesday 25 Jul 2007 T799: solid verifying analysis: dash difference: red/blue (dgpm)

20070725 00UTC ECMWF FC t+120 VT: 20070730 00UTC 500 Z 20070725 00UTC ECMWF FC t+120 VT: 20070730 00UTC 500 ** Z

ECMWF AN VT: 20070730 00UTC 500 Z

Wave train of errors

?

F. Prates Data Assimilation Training Course April 2008 19

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32.

20.17. 12.

11.10.

9.

7.7.

6.

6.

4.4.

3.

3.

2.

2.

1.1.

1.

1.

0.0.

0.

0.

0.

-1.-1.

-3.

-3.

-35.

-27.

-18.

-17.

-14.

-14.-13.-13.

-7.-2.

9.

8°N

8°N

18°N

18°N18

°N

18°N

28°N

38°N

48°N

58°N

68°N

78°N

162.0°W142.0°W

122.0°W

102.0°W

82.0°W

62.0°W

42.0°W 22.0°W 2.0°W 18°E 38°E

58°E

78°E

98°E

118°E

138°E158°E178°EFriday 16 Feb 2007 T799: solid verifying analysis: dash difference: red/blue (dgpm) 20070216 12UTC ECMWF FC t+120 VT: 20070221 12UTC 500 Z

20070216 12UTC ECMWF FC t+120 VT: 20070221 12UTC 500 ** ZECMWF AN VT: 20070221 12UTC 500 Z

But most of the cases the error

map is quite confusing !

F. Prates Data Assimilation Training Course April 2008 20

500 hPa geopot. (556 gpdam) fcst 10 Sep. 12 UTC - 13 Sep. 00 UTC

Std. dev. 500 hPa geopot. of 51 ensemble members

Influence Area: Extropical Transition Typhoon Maemi (2003) [Doris Anwender et al]

F. Prates Data Assimilation Training Course April 2008 21

500 hPa geopot. (556 gpdam) fcst 10 Sep. 12 UTC - 14 Sep. 12 UTC

Std. dev. 500 hPa geopot. of 51 ensemble members

Influence Area: Extropical Transition Typhoon Maemi (2003) [Doris Anwender et al]

F. Prates Data Assimilation Training Course April 2008 22

Influence Area: Extropical Transition Typhoon Maemi (2003) [Doris Anwender et al]

500 hPa geopot. (556 gpdam) fcst 10 Sep. 12 UTC - 15 Sep. 12 UTC

Std. dev. 500 hPa geopot. of 51 ensemble members

F. Prates Data Assimilation Training Course April 2008 23

500 hPa geopot. (556 gpdam) fcst 10 Sep. 12 UTC - 20 Sep. 12 UTC

Std. dev. 500 hPa geopot. of 51 ensemble members

Influence Area: Extropical Transition Typhoon Maemi (2003) [Doris Anwender et al]

F. Prates Data Assimilation Training Course April 2008 24

WHERE?

2) EPS perturbations:

The perturbation fields computed by EPS can help to identify where the atmosphere is sensitive to possible errors growth.

These perturbations are generated using singular vectors of a linear version of ECMWF, which maximize the total energy norm (phase space) over a 48-hour time interval with a energy peaking at around 700 hPa in regions of strong barotropic and baroclinic energy conversion, at initial time. Thus we expected that small errors in initial conditions will amplify most rapidly affecting the forecast.

WHERE? SW & W regions of Hudson Bay can be sensitive to possible error growth

0.25

0.25

0.25 0.5

0.5

992994

999

1006

1009

1012

1013

1004

1008

1012

1016

1020

1020

1024

1000hPa **Geopotential - Ensemble member number 1 of 51Wednesday 25 July 2007 00UTC ECMWF EPS Perturbed Forecast t+0 VT: Wednesday 25 July 2007 00UTC

Surf ace: Mean sea lev el pressureWednesday 25 July 2007 00UTC ECMWF EPS Control Forecast t+0 VT: Wednesday 25 July 2007 00UTC

0.0904 0.25 0.5 0.75 1 1.25 1.455

0.4

0.4

0.4

0.8

0.81.2

991994

1001

1008 1014

1021

1004

1008

1012

1016

1016

1020

1020

1000hPa **Geopotential - Ensemble member number 1 of 51Wednesday 25 July 2007 00UTC ECMWF EPS Perturbed Forecast t+9 VT: Wednesday 25 July 2007 09UTC

Surf ace: Mean sea lev el pressureWednesday 25 July 2007 00UTC ECMWF EPS Control Forecast t+9 VT: Wednesday 25 July 2007 09UTC

0.1070 0.2 0.4 0.6 0.8 1 1.2 1.4 1.6 1.8 1.964

850hPa TemperatureWednesday 25 July 2007 00UTC ECMWF EPS Control Forecast t+0 VT: Wednesday 25 July 2007 00UTC

-1000 -18 -12 -6 0 6 12 18 1000

850hPa TemperatureWednesday 25 July 2007 00UTC ECMWF EPS Control Forecast t+9 VT: Wednesday 25 July 2007 09UTC

-1000 -18 -12 -6 0 6 12 18 1000

F. Prates Data Assimilation Training Course April 2008 26

ANALYSIS INCREMENTS : 20070725 0UTC 700-hPa

-5

-5

-5

-5

-5

-5

5

5

5

5

2880.

2880.

2920.

2920.

2920.

2920.

2960.

2960.

2960.

296 0.

2960.

3000.

3000.

3000.

3000

.

3040.

3040.

3040.

3080.

3080.

3080. 3120.

2900

.

2900.

2900.

2900.

2940.

2940.

2940

.

2940.

2980.

2980.

2980.

2980.

2980.

3020.

3020.

3020.

3060.

3060.

3060.

3100.

3100.

10.0m/sAN: stream=da time=0 date=20070725 -- FG: stream=dcda time=18 date=20070724 step=6

20070725 0utc exp=01 700hPa INCR (z:10m w:5m/s t:1K) AN (solid black) FG (dash black) OBS (+/-50hPa) used not flagged:navy flagged but used:ochre rejected:red

F. Prates Data Assimilation Training Course April 2008 27

ANALYSIS INCREMENTS : 20070724 18UTC 700-hPa

-10

-5

-5

-5

-5

-5

-5

-5

5

510

10

15

2880.

2880.

2880.

2880.

2920.

2920.

2920.

2920.

2960.

2960.

2960.

2960.

2960.

3000.

3000.

3000.

3040.

3040.

3040.

3080.

3080.

3080.3120.

2880.

2880.

2880.

2920.

2920.

2920.

2920.

2960.

2960.

2960.

2960.

3000.

3000.3000.

3040.

3040.

3040.

3080.

3080.

3080.

3120.

10.0m/s

60°N

70°N

120°W

120°W

100°W

100°W

80°W

80°W 60°W

60°W

AN: stream=dcda time=18 date=20070724 -- FG: stream=dcda time=6 date=20070724 step=1220070724 18utc exp=01 700hPa INCR (z:10m w:5m/s t:1K) AN (solid black) FG (dash black) OBS (+/-50hPa) used not flagged:navy flagged but used:ochre rejected:red

F. Prates Data Assimilation Training Course April 2008 28

WHAT DATA?

ECMWF data base provides records and statistics of available observations in the area (300 million obs values per day, 99% is from satellite)

The cause/effect relation between obs and increments is not always trivial

But we can…

Assess the impact of different obs data in the analysis comparing the obs departures from the first-guess and analysis.

With 4DVAR the increments no longer have a local interpretation

Other causes…

If one or several observations are wrong → quality control is applied

If the obs errors turn out to be systematic → blacklisting is produced

F. Prates Data Assimilation Training Course April 2008 29

ECMWF Analysis VT:Sunday 22 July 2007 00UTC Surface: 2 metre temperature

-0.5125 0 5 10 15 20 25 30 35 40

10

ECMWF Analysis VT:Monday 23 July 2007 00UTC Surface: 2 metre temperature

-5 0 5 10 15 20 25 30 35 40

ECMWF Analysis VT:Tuesday 24 July 2007 00UTC Surface: 2 metre temperature

-0.7207 0 5 10 15 20 25 30 35 40

ECMWF Analysis VT:Wednesday 25 July 2007 00UTC Surface: 2 metre temperature

-5 0 5 10 15 20 25 30 35 40

ECMWF Analysis VT:Thursday 26 July 2007 00UTC Surface: 2 metre temperature

-0.2365 0 5 10 15 20 25 30 35 40

ECMWF Analysis VT:Friday 27 July 2007 00UTC Surface: 2 metre temperature

-5 0 5 10 15 20 25 30 35 40

2M Temp ANAL VT: 22Jul to 27Jul 2007 0Z

30C< Orange < 35C 35C< Red < 40C

25Jul

24Jul23Jul22Jul

26Jul 27Jul

F. Prates Data Assimilation Training Course April 2008 30

Saturday 21 J u ly 2007 12U TC EC MW F Forec as t t+12 VT: Sunday 22 J uly 2007 00U TC Sur fac e: C onv ec tiv e av ailab le potentia l energy

1000 2000 3000 4000 5000 5041.6

Sunday 22 J uly 2007 12U TC EC MW F Forec as t t+12 VT: Monday 23 J u ly 2007 00U TC Surfac e: C onv ec tiv e av ailable potentia l energy

1000 2000 3000 3901.4

Monday 23 J uly 2007 12U TC EC MW F Forec as t t+12 VT: Tues day 24 J uly 2007 00U TC Surfac e: C onv ec tiv e av ailable potentia l energy

1000 2000 3000 4000 5000 6000 6323.5

Tuesday 24 July 2007 12UTC ECMWF Forecast t+12 VT: Wednesday 25 July 2007 00UTC Surface: Convective available potential energy

1000 2000 3000 4000 5000 6000 7000 7700

Wednesday 25 July 2007 12UTC ECMWF Forecast t+12 VT: Thursday 26 July 2007 00UTC Surface: Convective available potential energy

1000 2000 3000 4000 5000 5780.4

Thurs day 26 J uly 2007 12U TC EC MW F Forec as t t+12 VT: Fr iday 27 J uly 2007 00U TC Sur fac e: C onv ec tiv e av ailable potentia l energy

1000 2000 3000 4000 4406.8

CAPE VT: 22Jul to 27Jul 2007 0Z

Orange <> CAPE > 5000 J/kg

25Jul

24Jul23Jul22Jul

26Jul 27Jul

F. Prates Data Assimilation Training Course April 2008 31

NOAA Surface AN

AN 24 12Z

AN 25 12Z

F. Prates Data Assimilation Training Course April 2008 32

Anomalous warm conditions in NW USA and Canada during several days

… and very high convective potential instability reaching a peak on 24th & 25th across the region …

… preceded an advancing southward cold frontal system into the region

F. Prates Data Assimilation Training Course April 2008 33

0

6

6

6

6

6

12

12

12

12

18

18

18

18

24

24

30

850 hPa TemperatureWednesday 25 July 2007 0UTC

-1.364

0

3

6

9

12

15

18

21

24

27

30

33

36

36.55

F. Prates Data Assimilation Training Course April 2008 34

WHAT DATA?

-70 -60 -50 -40 -30 -20 -10 0 10 20 30

OBS TEMPERATURE (C)

-10

-9

-8

-7

-6

-5

-4

-3

-2

-1

0

1

2

3

4

5

6

7

8

9

10

OB

S -

FG

TEMPERATUREAREA: (50N ,120W) - (60N , 90W)

00 UTC 25 JUL 2007AIRCRAFT

NO. OF USED OBS: 927 ( 32 %)NO. OF OBS: 2876 BIAS: 0.4 STD: 1.6

-70 -60 -50 -40 -30 -20 -10 0 10 20 30

OBS TEMPERATURE (C)

-10

-9

-8

-7

-6

-5

-4

-3

-2

-1

0

1

2

3

4

5

6

7

8

9

10

OB

S -

AN

TEMPERATUREAREA: (50N ,120W) - (60N , 90W)

00 UTC 25 JUL 2007AIRCRAFT

NO. OF USED OBS: 927 ( 32 %)NO. OF OBS: 2876 BIAS: 0.7 STD: 1.5

F. Prates Data Assimilation Training Course April 2008 35

WHAT DATA?

A set of Temp obs was not used during several days because of the very anomalous warm layer (temperature observations were considered suspicious by quality control check) at lower levels

… obs humidity was assumed suspicious by this quality check

-30 -25 -20 -15 -10 -5 0 5 10 15 20 25 30 35 40 45 50 55 60 65

-30

-20

-10

0

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140 150 160 170 180 190 200 210 220 230 240 250 260 270 280 290

10501000950900

850

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450

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250

200190180170160

150

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60

50

40

30

40

36

32

28

24

20

16

12

8

4

0

-4

-8

-12

-16

-20

0.4 1 1.5 2 3 5 7 9 12 16 20 28 36 48 66 80

OBSERVED

305.

289.

268.

257.

241.

231.

219.

210.

207.

213.

215.

221.

-30.0

-24.6

-54.6

-57.0

-65.9

-73.8

-76.5

-72.4

-73.2

-83.6

FG 4DVAR

305.

289.

268.

259.

242.

232.

220.

211.

208.

211.

217.

221.

-7.8

-28.2

-41.1

-48.9

-58.4

-75.7

-86.8

TEMP 72768 (87) 48.2N,106.6W 25 JUL 2007 0 UTC

PWCobs= 18.4 Kg/m2SHOWALTER= 3LIFTED INDEX= 3

DCAPEmax=2382.9 J/Kg at level 467.0 hPa CAPEmax=1410.5 J/Kg at level 924.0 hPa

OBSERVED

PWCmod= 5.2 Kg/m2SHOWALTER=****LIFTED INDEX= 1

DCAPEmax= 282.9 J/Kg at level 353.0 hPa CAPEmax= 0.0 J/Kg at level 542.0 hPa

FG 4DVAR

F. Prates Data Assimilation Training Course April 2008 36

Daily Rep. of 25th April: “on 19 April 06UTC (2007) winds from 7 dropsondes were used even though the location information (lat/lon) was completely incorrect. The lat/lon was probably not reported and for some reason and they ended up as dropsondes from 0N; 0E.”

“[..] although the wind departures were very large, they were not rejected by VarQC and therefore used by 4DVar.”

Decision: blacklist rule to reject all data with lat/lon=0/0

Other causes…:missing coordinates ►wrong observations

F. Prates Data Assimilation Training Course April 2008 37

Other causes…:missing coordinates ►wrong observations

-30 -25 -20 -15 -10 -5 0 5 10 15 20 25 30 35 40 45 50 55 60 65

-30

-20

-10

0

10

20

30

40

50

60

70

80

90

100

110

120

130

140 150 160 170 180 190 200 210 220 230 240 250 260 270 280 290

10501000950900850800

750

700

650

600

550

500

450

400

350

300

250

200190180170160150

140

130

120

110

100

90

80

70

60

50

40

30

40

36

32

28

24

20

16

12

8

4

0

-4

-8

-12

-16

-20

0.4 1 1.5 2 3 5 7 9 12 16 20 28 36 48 66 80

OBSERVED FG 4DVARTEMP (96) 0.0S, 0.0W 19 APR 2007 3 UTC

SHOWALTER= 9LIFTED INDEX=****

DCAPEmax= 811.8 J/Kg at level 555.0 hPa CAPEmax= 86.8 J/Kg at level 978.0 hPa

OBSERVED

SHOWALTER= 1LIFTED INDEX= 4

DCAPEmax= 623.1 J/Kg at level 574.0 hPa CAPEmax= 0.5 J/Kg at level 613.0 hPa

FG 4DVAR

F. Prates Data Assimilation Training Course April 2008 38

SUMMARY

Synoptic diagnosis of NWP forecast is a necessary complement to the usual statistical verifications.

Diagnostic tools allow to identify complex problems that often do not show up in objective scores.

Through this type of monitoring we have been able to identify several problems successively taken under consideration by the RD department.

F. Prates Data Assimilation Training Course April 2008 39

To find out more:

http://www.ecmwf.int/products/forecasts/guide/Monitoring_of_the_data_assimilation_system.html

Persson, A, 2000: Synoptic-dynamic diagnosis of medium range weather forecast systems, ECMWF

Seminar on diagnosis of models and data assimilation systems, 6-10 September 1999.pp.123-137 .