Model statistics in the COPS regionAssimilation of Raman Lidar dataDevelopment of a GPS operatorReal-time assimilation efforts for COPSModeling and assimilation efforts at IPM in preparation of COPS Hans-Stefan Bauer, Matthias Grzeschik, Florian Zus, Volker Wulfmeyer, Andreas Behrendt and Thomas SchwitallaInstitute of Physics and Meteorology (IPM)University of Hohenheim, Stuttgart, Germany

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.

Observation Locations

13-case average values as compared to observationsObservationsMM5 7 kmLM 7 kmMM5 1 km

Averaged 24h precipitation sum

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 UTCAssimilation of Raman lidar data

Comparison of RAMSES and model profiles

Impact on water vapor field still visible 6 hours after the assimilation window.

Future evaluations of impact required and ongoing.

Assimilation of GPS integrated water vaporGPS 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.

Operational Setup of the Real-Time System

Operational Setup - OverviewBlue arrows:Data transport Red: Computing (data processing, assimilation, forecast, ) Green: Idle time (time window for data retrieval) Blue: Observation Interval Black: Technical Problems

Data flow during COPS

COPS Operations Center (OC)

Operate webbased data management system as fast and user-fiendly interface to Visualize and discuss all forecasts and operational data available Select missions of the day Guide operations of the instruments Visualize and discuss COPS measurement data

NinJo

Fast and user-friendly interface forvisualizing DWD forecasts (and others) operational measurements

COPS Instruments

Guidance

MAP-FDP/D-PHASE

DWD

ETReC07

...

Real-time Quicklooks

EUMETSAT

GTS/AFD

Assimilation

COPS Real time

Quick-looks

UHOH

NetCDF

BUFR

Fall back: Use disk volume of Data Archive

Assimilation of Standard Observations

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

Expectations from the WorkshopDecisions 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

Unique opportunity for the AMF to address key science questions raised by the QPF and the ARM community simultaneously.- Post frontal situation in northern Germany- High pressure system in Italy- for our assimilation study, we picked out one of the "golden days" of LAUNCH-2005, which taked place on the 26th to 27th of october in 2005- in northern Germany there was a post frontal weather situation and in Italy there was a high pressure area.- the used Raman Lidar stations was Lindenberg, Leipzig and Ziegendorf, which provides water vapor measurements. The Raman Lidar in southern Italy, near Potenza, provides water vapor and temperature measurements.