1. Institut für Physik der Atmosphäre WG4: Data Assimilation and Predictability George C. Craig DLR-Institut für Physik der Atmosphäre

2. Institut für Physik der Atmosphäre Folie 2 > Vortrag > Autor 1. What will be the relative improvement in forecasts resulting from better large-scale and local forecasts ?  This is likely to depend strongly on the meteorological situation and the nature of the different data sets. 2. How should high-resolution data assimilation be done ?  Important to involve a variety of models and assimilation methods to benefit from their different advantages. 3. How should limited computing power be allocated between resolution, complex parameterizations, data assimilation, ensemble size,... ?  Need to evaluate performance of the entire DA/NWP chain 4. What improvements can be transformed to operational practice ?  An important question but should not restrict the ideas involved in the project. Scientific Goals

3. Institut für Physik der Atmosphäre Folie 3 > Vortrag > Autor Goal: To quantify and extend the limits of predictability of convection through high-resolution ensemble forecasting and advanced data assimilation. Scientific Questions: DAP 1. What are the relative roles of upper and mid-tropospheric forcing versus local orographic and surface flux influences on the predictability of convective precipitation in a region of moderate orography? DAP 2. What is the impact of the assimilation of high-resolution remote sensing data on short-range forecasts of convective precipitation? Can assimilation help to improve process understanding and model parameterizations? DAP 3. What is the impact of model errors on forecast accuracy, in comparison to error in initial fields, and can a synergetic use of observations lead to a characterization and reduction of model error? DAP 4. Is there an obvious impact of COPS measurements on model forecasts? DAP 5. If reasons for lack of positive impact can be identified, can a better measurement strategy be devised? DAP 6. Which assimilation systems best handle the data and which may be practical for real-time use (nudging, 3DVAR, 4DVAR, ensemble-based)? DAP 7. Is such a system a valuable tool to support mission planning?

4. Institut für Physik der Atmosphäre Folie 4 > Vortrag > Autor Plans Real-time ETReC 2007 University of Hohenheim DLR - COSMO-LEPS Operational products from national meteorological services Near real-time Sensitivity studies Post-Campaign Studies

5. Institut für Physik der Atmosphäre Folie 5 > Vortrag > Autor Lokal Modell: all 10 clusters Meteosat 7 IR 16:00 UTC Episode I: 9 July 2002

6. Institut für Physik der Atmosphäre Folie 6 > Vortrag > Autor Image matching as pre-conditioner for DA 1. COSMO-LEPS ensemble forecast - highly non-Gaussian error stats. 2. Image matching selects best sub-ensemble - Gaussian error stats. 3. Conventional DA assimilates most recent data for short-range forecast

7. Institut für Physik der Atmosphäre Folie 7 > Vortrag > Autor Preconditioning for Latent Heat Nudging (Daniel Leuenberger, MeteoSchweiz)

8. Institut für Physik der Atmosphäre Folie 8 > Vortrag > Autor DLR Realtime Image matching FQM in real-time COSMO-LEPS Provision to operations center Near real-time impact studies – impact of observations – impact of preconditioning

9. Institut für Physik der Atmosphäre Folie 9 > Vortrag > Autor ETReC 2007 Goals 1. Predictability 2. Adaptive Observing System Timeline T+2-3 days: Calculation of sensitive regions for two target regions – COPS – MEDEX/HYMEX T+1-3 days: Targetted observations (T+24) – EURORISK-PREVIEW - radiosonde, AMDAR, ASAP – COPS - airborne lidar T+0.5-1 day: Improved forecasts – NMS with GTS data – COPS real-time/near real-time

10. Vortragstitel10 27 June 2006: 06 UTC – 12 UTC

11. Vortragstitel11 Méso-NH Simulation : Initial Time 27-06-06 06 UTC 3h accumulated precipitation (09-12 UTC) : ICE 3 / ARPEGE ICE 4 / ARPEGE ICE 3 / ECMWF

12. Vortragstitel12 Initial fields : Horizontal wind @ z =1 km ARPEGE ECMWF

13. Vortragstitel13 Verif. time: 27 june 12UTC Obs. time: 26 00UTC; 12UTC, 27 00UTC EPS: 25 June 12UTC (Courtesy of P. Arbogast) Targeted observations in sensitive areas T – 36 h T – 24 h T – 12 h

14. Institut für Physik der Atmosphäre Folie 14 > Vortrag > Autor Issues Data exchange and archive Data for real-time use – GTS – cutoff times Provision of products for operations centre Participation of national meterological services - – ETReC 2007 meeting Exeter 11 Oct. 2006

15. Vortragstitel15 Initial fields: Relative humidity @ Z=1km ARPEGE ECMWF