1. 4 th COPS Workshop, Hohenheim, 25 – 26 September 2006 Modeling and assimilation efforts at IPM in preparation of COPS Hans-Stefan Bauer, Matthias Grzeschik, Florian Zus, Volker Wulfmeyer, Andreas Behrendt and Thomas Schwitalla Institute of Physics and Meteorology (IPM) University of Hohenheim, Stuttgart, Germany Model statistics in the COPS region Assimilation of Raman Lidar data Development of a GPS operator Real-time assimilation efforts for COPS

2. 4 th COPS Workshop, Hohenheim, 25 – 26 September 2006 Model statistics in the COPS region 13 different precipitation cases categorized into strongly-forced (4), weakly-forced (5), and non-forced (4) cases Creation of an average daily cycle from grid boxes containing observations Model configurations: 2-way nested 3, 1 km resolution, 36 level, sophisticated physics, 30 h forecasts initialized with ECMWF analysis, no data assimilation, 7 km directly initialized with ECMWF, param. conv.

3. 4 th COPS Workshop, Hohenheim, 25 – 26 September 2006 Observation Locations DWD SYNOP stations HVZ + Meteo France hourly precipitation

4. 4 th COPS Workshop, Hohenheim, 25 – 26 September 2006 13-case average values as compared to observations Observations MM5 7 km LM 7 km MM5 1 km

5. 4 th COPS Workshop, Hohenheim, 25 – 26 September 2006 Averaged 24h precipitation sum No observations

6. Example: First 4DVAR using Raman lidar data (Grzeschik et al. 3.11-P) during LAUNCH 2005 IOP7, Oct 26/27 (see Engelbart et al. 9.5-I) Additional observations: - 4 water vapor Raman lidars - 1 temperature Raman lidar (see Di Girolamo et al. 2.2-I, Klein et al. 8.2-O) MM5 set up: - 27 km horizontal resolution - 36 vertical layers - 3-h assimilation window from 23-02 UTC Assimilation of Raman lidar data

7. 4 th COPS Workshop, Hohenheim, 25 – 26 September 2006 Comparison of RAMSES and model profiles RAMSES observation MM5, 1 km, no assimilation MM5, 1 km, with assimilation

8. 4 th COPS Workshop, Hohenheim, 25 – 26 September 2006 Impact on water vapor field still visible 6 hours after the assimilation window. Future evaluations of impact required and ongoing.

9. 4 th COPS Workshop, Hohenheim, 25 – 26 September 2006 Assimilation of GPS integrated water vapor GPS provides data with a large spatial coverage and high temporal resolution under all- weather conditions. During GOP/COPS it is planned to densify the existing GPS network. Technical development of the forward operator is finished. Validation is possible. Implementation and testing ongoing.

10. 4 th COPS Workshop, Hohenheim, 25 – 26 September 2006 Operational Setup of the Real-Time System

11. 4 th COPS Workshop, Hohenheim, 25 – 26 September 2006 Operational Setup - Overview Blue arrows:Data transport Red: Computing (data processing, assimilation, forecast, …) Green: Idle time (time window for data retrieval) Blue: Observation Interval Black: Technical Problems

12. 4 th COPS Workshop, Hohenheim, 25 – 26 September 2006 Data flow during COPS

13. 4 th COPS Workshop, Hohenheim, 25 – 26 September 2006 Assimilation of Standard Observations

14. 4 th COPS Workshop, Hohenheim, 25 – 26 September 2006 Conclusions First results from model statistics were presented. At 7 km with parameterized convection both models show the well-known luv/lee effect. In the 1-km MM5 simulation this error is no longer present. However, things not always improve with just increasing the horizontal resolution. What is the best way to go? Increasing the resolution, improving the used parameterization schemes, or a combination of both ? Interestingly, even the small set of 13 cases from one summer season used here shows the main features and errors found in longer climatologies. The assimilation of data from only a few Raman lidar stations show an impact hours after the end of the assimilation window. Even better results can be expect when data from several sources are assimilated at the same time. During the preparation of our real-time assimilation efforts important questions evolve …

15. 4 th COPS Workshop, Hohenheim, 25 – 26 September 2006 Expectations from the Workshop Decisions about data handling and organization of data flow. Which kind of data will be available for the assimilation? What is the estimated time of arrival of the data after the end of the mission? Daily schedule for operational instruments as well as IOP missions? We need this information to set-up our operational cycle. How will the visualization of the model output of COPS/MAP D-PHASE be organized so that an easy comparison of the different models is guaranteed? More questions are expected to come up during the workshop