Agenda for OSSE meeting on Thursday September 13 1Paper accepter by GRL (Oreste) 2. Summary of progress in data distribution 2.a First disk of T799 NR (Michiko) 2.b NASA/SIVO portal (Joe and Gail) 2.c Data at NCAR (Michiko) 3. Simulation of radiance data 3.a Basic strategies (Ron Errico) 3.b Detail tasks and procedure (Michiko) 3.c Period for initial experiments (Tong Zhu) 4. Precursor assimilation (Yuanfu Jack, Yucheng ) 4.a Data to be included 4.b Experiments to be performed Do we need to run for real data? 5 Highlight from calibration experiments by T213 NR OSSE (Michiko) 6. Setting up sub group meeting on regional OSSEs (Lars Peter and Michiko)

Subject for the next OSSE meeting 1.Plan data impact in ensemble prediction and/or ETKF (Zoltan and Yucheng) 2. Simulation of RAOB Drift (Joe Terry and Jack) 3. Summary of subgroup meeting of regional OSSE

First half of T799 Oct05 NR arrived Complete Sfc data: reduced Gaussian N400 and 0.5x0.5 lat lon 13 variables are in 1degx1deg as well Pressure level Isentropic level 0.5x0.5 lat lon Model level: one time period per file (each file size has to be less than 2GB)

- Procedure of simulation of Radiance for existing instruments- Initially, we would produce files for HIRS, AMSU, AIRS, and GOES We will work on two streams, A and B, in parallel: A. Development of codes and scripts from NR grib code to BUFR formatted radiance data. 1)Retrieve the information about radiance data from the archive. (RADINFO) 2) Generate soundings as a necessary first step, separate from any cloud masking or error assignments. We would use the orbital data patterns from BUFR dump files. (DB91L). DB91L can be saved either 6 hourly or every 6 min depending on the amount of data. 3) DB91L using RTN simulated radiance data to produce BUFR files containing the simulate the clear sky radiances. (SIMRAD) First we will use ad hoc sampling strategies. If TCC is less than a certain amount (for example, 10%) simulate clear sky radiance.

B.Development of sampling strategies and study of error characteristics presented by Ron Errico. 1)How big are differences between radiances produced by different RT algorithms for identical input profiles. I have asked her to use 2 different RTMs that I think are options in the CRTM. This is to check whether we can in fact use a different RTM to simulate radiances fro the NR than used in the GSI-DAS. 2)What is the distribution of relevant cloud parameters in the NR that we hope to use to determine whether clouds are affecting radiances at observation locations. She is starting by looking at the distribution of cloud fractions for H,M and L clouds at a single time. What this distribution looks like will inform us of our options for proceeding.

[Proposed task for next few months] Simulation of radiance for existing instruments: Jack Woollen Jack offered to work on A1-A2. DB91L for task A is in BUFR format and contains only basic data. Haibing and Tong Zhu will work on task A3. Read DB91L and generate SIMRAD using adhoc sampling and error assignment. Haibing will work on AIRS AMSU and HIRS data and Tong Zhu will work on GOES data. Tong Zhu may continue to GOESR project by generating DB91L for GOESR himself Yuanfu and Michiko will provide help for Haibing. Runhua, Ron Errico, and Emily will work on task B. For task (B), Jack will generate DB91L for October 1, 2005 for T511NR containing all model and surface variables in binary format, not BUFR. GMAO work on one day data and select the list of variables. For the selected variables DB91L will be generated for the first two or three weeks of October 2005 from T511NR.

Strong demand from regional OSSE Tom Schlatter: In either case, this will require a tremendous amount of storage. Depending upon the focus of the regional OSSE, it may be necessary to generate special observations from the regional nature run within its geographical confines. In addition, the regional assimilating model (separate from the model used for the regional nature run model), must be nested in a global assimilating model, which supplies the lateral boundary conditions. The mix of observations used inside and outside the regional domain should be consistent for the control run, calibration runs, and the specific new observing system being simulated. In regional OSSEs, it can be hard to discern whether any forecast improvement came from observations supplied to the regional assimilation model or from the lateral boundary conditions supplied by the global model. The longer the forecast, the more serious this problem becomes. This is not to say that regional OSSEs are inherently bad, just that they pose many challenging problems that can be avoided with a global OSSE.

Michiko’s Comments 1.Is there any noise by nesting regional Nature run to global nature run which may be significant enough compared to data impact. 2.There are many option to produce high resolution NR and they are still under development. 3.Effort to produce regional Nature run will take up much of resources from global OSSE. 4.I doubt 1km resolution data will actually resolve 1km event in data assimilation. Many low quality high resolution data will produce one high quality information using method such as super-obbing. Therefore T799 NR will be still useful to test 1km density data which represented by low density higher quality data. 5, We should concentrate on the best use of T511 T799 nature run. Joint OSSE will clarify the requirement for high resolution model. Requirement should include format of out put. While we are working on OSSEs with T511 T799 NR, notify the requirement to people who works on high resolution model.

Work Plan: Joint OSSE Nature Runs Joint OSSE T511 Nature Run –Produced by ECMWF Equivalent approximately 25km grid point model 40 km resolution in physics 91 vertical layers –3 hourly output from May 2005 to June 2006 integration –Realistic extratropical storm frequency and statistics, hurricane and tropical waves –Improved cloud –Suitable for global OSSEs Joint OSSE T799 Nature Run –Produced by ECMWF Equivalent approximately 15km grid point model 25 km resolution in physics 91 vertical layers –Hourly outputs for two 35day periods –Better hurricane and severe storm seasons –Suitable for most mesoscale OSSEs and to test synoptic and mesoscale impacts of GOES-R Lifespan distribution of extratropical cyclones during February 2006 in Northern Hemisphere. Red bars are for NR. Green bars are for NCEP analysis

Need for higher resolution Nature Run Need for a Nature Run with higher resolution mesoscale OSSEs –Hurricanes, lake snow effects, severe storms –Less than 5km model (without cloud parameterization) –Frequency of output : 5min Candidates –Global cloud resolving model GFDL-ESRL (Planned delivery time 2012) NICAM (run 3.5 km 3month) –Local high resolution global model Using Fibonacci grid Some work by John McGrager Etc. –Nested regional model CSU RAMS (regional atmospheric modeling system) RUC WRF