3rd THORPEX International Science Symposium 09/2009

Slide 1

Slide 1

Impact of increased satellite data density

in sensitive areas

Carla Cardinali, Peter Bauer, Roberto Buizza, Jean-Noël Thépaut

European Centre for Medium-Range Weather Forecastsin lovely Reading, Berkshire, UK

3rd THORPEX International Science Symposium 09/2009

Slide 2

Slide 2

Background• Thinning of data is applied to:

－ reduce data volume－ avoid the introduction of spatial observation error correlation

that is currently not accounted for in data assimilation algorithm • Thinning is performed statically on a fixed latitude/longitude grid.

Objective Evaluate impact of selective satellite observational data thinning on

medium-range NWP aiming at denser data in sensitive areas and less dense data in other areas trade-off between data impact and data volume.

Approach• Experiments with global data thinning:

－ Change global latitude/longitude thinning grid.• Experiments with data thinning in selected regions:

－ Increased density in sensitive areas and reduced density elsewhere using a Singular Vector based measure to identify areas from which forecast errors are growing fast (ECMWF 2007 QJ papers).

－ Sensitive areas are computed for Southern Hemisphere

Study contents

3rd THORPEX International Science Symposium 09/2009

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Slide 3

ExperimentsGlobal data thinning• Thinn_2.5 : global latitude/longitude thinning is 2.5o.• Thinn_1.25 : ~ is 1.25o current operational configuration• Thinn_0.625 : ~ is 0.625o.

Selective data thinning• Thinn_Cntrl : ~ is 1.25o proxy for Thinn_1.25• Thinn_SV : ~ is 1.25o and 0.625o in SV areas.• Thinn_RD : ~ is 1.25o and 0.625o in randomly distributed areas.• Thinn_CSV : ~ is 1.25o and 0.625o in Climatological SV areas.• Thinn_0.625

Additional information• All experiments are run at T511L91 (12-hour 4D-Var) for 01/12/2008-

28/02/2009.• All experiments are verified with T799L91 operational model analyses

(without first 7 days (spin-up) i.e. 83 cases).• All SV/RD/CSV areas occupy same fraction (15%) of the Southern

hemisphere.• The SV-based climatology derived from the mean 2007 SV-areas.

3rd THORPEX International Science Symposium 09/2009

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Slide 4

Global data thinning: Forecast impact Thin_2.5-Thin_1.2500hPa Normalized RMSE 95% confidence 55 cases

0 1 2 3 4 5 6 7 8 Forecast Day

North H

South H

3rd THORPEX International Science Symposium 09/2009

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Slide 5

Global data thinning: Forecast impact Thin_1.2-Thin_0.6500hPa Normalized RMSE 95% confidence 83 cases

North H

South H

0 1 2 3 4 5 6 7 8 Forecast Day

3rd THORPEX International Science Symposium 09/2009

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Slide 6

Data coverage: Single case01/01/2009 00 UTCdata density AMSU-A channel 9:

Singular Vectors:

Randomly distributed circular areas:

2007 Singular Vector climatology:

3rd THORPEX International Science Symposium 09/2009

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Slide 7

Data coverage: Average01-07/01/2009 00 and 12 UTC data density AMSU-A channel 9:

Singular Vectors:

Randomly distributed circular areas:

2007 Singular Vector climatology:

3rd THORPEX International Science Symposium 09/2009

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Slide 8

Selective data thinning: DFSDecrease of DFS relative to the Thin_0.625 experiment

0 10 20 30 40 50 60 70 80 90 100

Thin_0.6

SV

RD

C_sv

Thin_1.2

DFS (%)0 10 20 30 40 50 60 70 80 90 100

Thin_0.6

SV

RD

C_sv

Thin_1.2

DFS (%)

Global Southern Hemisphere

3rd THORPEX International Science Symposium 09/2009

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Slide 9

Selective data thinning: Forecast impact SV-CNTRLSouthern H. Normalized RMSE 95% confidence 83 cases

1000 hPa

500 hPa

200 hPa

0 1 2 3 4 5 6 7 8 Forecast Day

3rd THORPEX International Science Symposium 09/2009

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Slide 10

Selective data thinning: Forecast impact SV-RDSouthern H. Normalized RMSE 95% confidence 83 cases

1000 hPa

500 hPa

200 hPa

0 1 2 3 4 5 6 7 8 Forecast Day

3rd THORPEX International Science Symposium 09/2009

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Slide 11

Selective data thinning: Forecast impact SV - CSVSouthern H. Normalized RMSE 95% confidence 83 cases

1000 hPa

500 hPa

200 hPa

0 1 2 3 4 5 6 7 8 Forecast Day

3rd THORPEX International Science Symposium 09/2009

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Conclusions

Global data thinning•Current operational setting (1.25o) is too conservative and

satellite data density could be increased.•0.625 º thinning will be considered for operational

implementation.

Selective data thinning•Forecast scores are best for experiment with increased data

density in SV-based areas that are updated for each analysis.•40% loss of DFS by increasing the data density over SV areas

instead than globally.•0.42° thinning is thought to be used in SV areas.