Assessing the Skill of ECMWF Forecasts in Weeks 2-4
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Assessing the Skill of ECMWF Forecasts in Weeks 2-4 Jeff Whitaker NOAA/ESRL • How much skill is there? • Where does it come from? • Is there much room for improvement? • Focus on wintertime temp. forecast.
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Assessing the Skill of ECMWF Forecasts in Weeks 2-4. Jeff Whitaker NOAA/ESRL How much skill is there? Where does it come from? Is there much room for improvement? Focus on wintertime temp. forecast. Dataset (courtesy Frederic Vitart). ECMWF Monthly Forecast System (32-d forecasts) - PowerPoint PPT Presentation
Transcript of Assessing the Skill of ECMWF Forecasts in Weeks 2-4
Assessing the Skill of ECMWF Forecasts in Weeks 2-4
Jeff Whitaker NOAA/ESRL
• How much skill is there?
• Where does it come from?
• Is there much room for improvement?
• Focus on wintertime temp. forecast.
Dataset (courtesy Frederic Vitart)
ECMWF Monthly Forecast System (32-d forecasts)http://ecmwf.int/research/monthly_forecasting/mofc-des.html
• Atmosphere: IFS at T159L62 resolution.
Ocean: HOPE 1.4ox0.3o at equator, 29 levels.
• Retrospective: 5-members, once per week 94-05.
• Real-time: 51 members, once per week 2006.
• Coming in 2008: once-weekly VarEPS, ~18 years.
Z500 Skill
2-Meter Temp. Skill
Mean 0.52Expected RPSS 0.16
Mean 0.24Expected RPSS 0.03
Mean 0.1Expected RPSS 0.005
Week 3 vs LIM (upper-trop circulation)
LIM 250
theoretical actual
EC Z500
T2M ‘most predictable pattern’ week 2
T2M ‘most predictable pattern’ week 3
T2M ‘most predictable pattern’ week 4
Correlation of MJO indices with week 3 forecast error
Conclusions• Some modest skill in week 3 - T skill
comparable to week 2 P skill (or seasonal mean T skill for lead 0).
• Not much skill in week 4.• Week 3 predictable pattern same as week 2 -
but more strongly tied to tropical convection in week 3
• Improvements in tropical convection forecasts not likely to improve week 2 much, should help week 3 (but has to be more than MJO).
Week 3 most predictable pattern
Skill in predicting the MJO. Cycle 32R3
Prediction of the Madden Julian oscillation: anomaly correlation between the PC2 time series predicted by the monthly forecasting system at different time ranges from 45 cases one day apart and the time series computed from the analysis.
VAREPS MOFC MOFC + ML
0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30
Day
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Linear Correlation with observed PC2: Ensemble MeanCY32R2
30
25
20
15
10
5
0
30E 90E 150E 150W 90W 30W
LONGITUDE
30E 90E 150E 150W 90W 30W
Initital conditionsPersistence
30
25
20
15
10
5
0
DAYS
30E 90E 150E 150W 90W 30W
LONGITUDE
30E 90E 150E 150W 90W 30W
Ensemble meanexou
30
25
20
15
10
5
0
DAYS
30E 90E 150E 150W 90W 30W
LONGITUDE
30E 90E 150E 150W 90W 30W
Ensemble Meanewku
<-.9 -.9..-.8 -.8..-.6 -.6..-.4 -.4..0.4 0.4..0.6 0.6..0.8 0.8..0.9 > 0.9
