1. Slide 1 3 rd THORPEX International Science Symposium 09/2009 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 Forecasts in lovely Reading, Berkshire, UK

2. Slide 2 3 rd THORPEX International Science Symposium 09/2009 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

3. Slide 3 3 rd THORPEX International Science Symposium 09/2009 Slide 3 Experiments Global data thinning Thinn_2.5: global latitude/longitude thinning is 2.5 o. Thinn_1.25: ~ is 1.25 o current operational configuration Thinn_0.625: ~ is 0.625 o. Selective data thinning Thinn_Cntrl: ~ is 1.25 o proxy for Thinn_1.25 Thinn_SV: ~ is 1.25 o and 0.625 o in SV areas. Thinn_RD: ~ is 1.25 o and 0.625 o in randomly distributed areas. Thinn_CSV: ~ is 1.25 o and 0.625 o 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.

4. Slide 4 3 rd THORPEX International Science Symposium 09/2009 Slide 4 Global data thinning: Forecast impact Thin_2.5-Thin_1.2 500hPa Normalized RMSE 95% confidence 55 cases 0 1 2 3 4 5 6 7 8 Forecast Day North H South H

5. Slide 5 3 rd THORPEX International Science Symposium 09/2009 Slide 5 Global data thinning: Forecast impact Thin_1.2-Thin_0.6 500hPa Normalized RMSE 95% confidence 83 cases North H South H 0 1 2 3 4 5 6 7 8 Forecast Day

6. Slide 6 3 rd THORPEX International Science Symposium 09/2009 Slide 6 Data coverage: Single case 01/01/2009 00 UTC data density AMSU-A channel 9: Singular Vectors: Randomly distributed circular areas: 2007 Singular Vector climatology:

7. Slide 7 3 rd THORPEX International Science Symposium 09/2009 Slide 7 Data coverage: Average 01-07/01/2009 00 and 12 UTC data density AMSU-A channel 9: Singular Vectors: Randomly distributed circular areas: 2007 Singular Vector climatology:

8. Slide 8 3 rd THORPEX International Science Symposium 09/2009 Slide 8 Selective data thinning: DFS Decrease of DFS relative to the Thin_0.625 experiment Global Southern Hemisphere

9. Slide 9 3 rd THORPEX International Science Symposium 09/2009 Slide 9 Selective data thinning: Forecast impact SV-CNTRL Southern H. Normalized RMSE 95% confidence 83 cases 1000 hPa 500 hPa 200 hPa 0 1 2 3 4 5 6 7 8 Forecast Day

10. Slide 10 3 rd THORPEX International Science Symposium 09/2009 Slide 10 Selective data thinning: Forecast impact SV-RD Southern H. Normalized RMSE 95% confidence 83 cases 1000 hPa 500 hPa 200 hPa 0 1 2 3 4 5 6 7 8 Forecast Day

11. Slide 11 3 rd THORPEX International Science Symposium 09/2009 Slide 11 Selective data thinning: Forecast impact SV - CSV Southern H. Normalized RMSE 95% confidence 83 cases 1000 hPa 500 hPa 200 hPa 0 1 2 3 4 5 6 7 8 Forecast Day

12. Slide 12 3 rd THORPEX International Science Symposium 09/2009 Slide 12 Conclusions Global data thinning Current operational setting (1.25 o ) 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.