subjective evaluation of different versions of aladin/hu
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Subjective evaluation of different versions of ALADIN/HU. Helga T óth , HMS. Contents. Motivation Method Results Comparison to objective scores Conclusions. Motivations. Complex view of the models behavior in different synoptic situation - PowerPoint PPT PresentationTRANSCRIPT
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ALADIN Workshop 2004, Innsbruck
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Subjective evaluation of different versions of ALADIN/HU
Helga Tóth, HMS
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Contents
• Motivation• Method• Results• Comparison to objective scores• Conclusions
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Motivations• Complex view of the models behavior in different synoptic situation• Grey zone problem is exist on 6.5 km resolution, or is not?• 3D-VAR vs. dynamical adaptation comparison not only objectively but also subjectively• To have more information about that variables which are not included in the objective verification system
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Methods• From 1. Febr. 2004.• Subjective verification of the previous
day :the Sunday fcst. on Monday the Thursday fcst. on Friday
• On the territory of Hungary:• Discussion and classification (1 bad 5 excellent) at 11:30 am
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Methods II• Comparison of different models Previous 00 runs by:
- ALADIN/HU dyn. ad. on 6.5 km res.- ALADIN/HU dyn. ad. on 12 km res.- ALADIN-3D-VAR on 12 km res.
12 UTC run two days before by:- ECMWF
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Methods III• Participants: Gabriella Csima, Edit
Hágel, István Ihász, Gabriella Szépszó, Helga Tóth, (Regina Szoták)
• Verified parameters:- 2m Temperature- Precipitation- Total cloudiness- 10m Wind
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Results• Total mean and standard deviation
Total average
3,9
3,95
4
4,05
4,1
4,15
AL6 AL12 3D-V ECM
Total standard deviation
0,55
0,6
0,65
0,7
0,75
AL6 AL12 3D-V ECM
3D-VAR got the worst marks, the dyn. ad.-s are better
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3,2
3,4
3,6
3,8
4
4,2
4,4
T2m Precip. Wind Cloud.
AL6
AL12
3D-V
ECM
-weak forecast: - cloudiness: for all ALADINs
- T2m: for 3D-VAR
-good and similar: Wind and the precipitation
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T2m AL-3DV1210%
31%
41%
18% rate of 1,1/2, 2, 2/3
rate of 3,3/4rate of 4
rate of 4/5,5
T2m AL-DYN6
21%
57%
17%5%
rate of 1,1/2, 2, 2/3 rate of 3,3/4rate of 4
rate of 4/5,5
T2m AL-DYN125%
22%
17%
56%
rate of 1,1/2, 2, 2/3 rate of 3,3/4rate of 4
rate of 4/5,5
T2m ECMWF6%
19%
17%
58%
rate of 1,1/2, 2, 2/3
rate of 3,3/4
rate of 4
rate of4/5, 5
3D-VAR produced 2 times more middle-class 2mT forecasts than the others
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Precip. AL-DYN6
22%
24%
49%
5%
rate of 1,1/2, 2, 2/3 rate of 3,3/4rate of 4
rate of 4/5,5
Precip. AL-3DV12
16%
26%
53%
5%rate of 1,1/2, 2, 2/3 rate of 3,3/4rate of 4
rate of 4/5,5
Precip. AL-DYN122%
22%
29%
47%
rate of 1,1/2, 2, 2/3 rate of 3,3/4rate of 4
rate of 4/5,5
Precip. ECMWF
21%
29%
50%
0% rate of 1,1/2, 2,2/3 rate of 3,3/4
rate of 4
rate of4/5, 5
3D-VAR got the most excellent marks and the least middle-class
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Cloud. AL-DYN62%
35%
46%
17% rate of 1,1/2, 2, 2/3rate of 3,3/4
rate of 4
rate of 4/5,5
Cloud. AL-DYN122%
35%
44%
19% rate of 1,1/2, 2, 2/3
rate of 3,3/4
rate of 4
rate of4/5, 5
Cloud. AL-3DV123%
39%
42%
16% rate of 1,1/2, 2, 2/3
rate of 3,3/4
rate of 4
rate of 4/5,5
Cloud. ECMWF
25%
36%
37%
2%rate of 1,1/2, 2, 2/3
rate of 3,3/4
rate of 4
rate of 4/5,5
Too many middle-class forecasts of ALADINs and Too few excellent
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Mean precipitation-mark on rainy days
3,53,553,6
3,653,7
3,753,8
3,853,9
AL6 AL12 3D-V ECM
- rainy day > 5mm (~23 days)
- Order is the same as the for the full period
- Not neglectable diff. AL6 and ECMWF
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Objective scores on the surface2mT-Opposite results
for some parameters than got by the subjective evaluation
- But the the scores are calculated on the whole domain
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Wind direction
Wind speed
Subjective and objective verif. gave similar results for wind
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rel.hum
Geopot.
ECMWF produced better scores for the 2Rh and geopot.
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Regular deficiency• Cloudiness DYN. 12
DYN. 6.5
3D-V
ECM
ALADIN models generally forecast to much total cloudiness, which is not informative in the oper. practice.
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• Temperature I
- Smaller max. temperature in ALADINs on the spring time
- 3D-VAR the coldest model
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• Temperature II
‘Bean-shape’ cold spot in the 2mT and Tsurf in 3D-VAR and the guess
after a time disappeared
? modification in 3D-VAR
? By accident
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Case study (2004. 02. 22)• Strong inversion sleet• Temperature structure at the initial time:
— Temp— AL6— AL12— 3D-V
- DYN. AD-s contain the inversion
- in 3D-VAR too weak (nothing in the guess)
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•Temperature structure after 12 h integration:
— Temp
— AL6
— AL12
— 3D-VNo inversion at all
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-Too warm 2mT, ECWMF is better (below 0 in the North few degree SE)
- Few degree wind-direction error which can be the reason of the misfcst.
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Conclusion• Small differences between the two kind of
dynamical adaptation (no grey zone?)• 3D-VAR has a positive impact on the
precipitation, but negative on the 2mT and cloud.
• Inconsistency between the subjective and objective evaluation maybe because of the domain differences Scores on Hungarian territory by the help of Slovenian colleague