Agenda 1. Summary of progress and feed back from AMS meeting and LWG meeting (10min) (Michiko) 2. NASA portal status update (Harper and Michiko) 5min 3. Diagnostics study from T799 NR (Oreste) 25 min 4 Arctic boundary layer in T511 NR ( Nikki)25min 5. Troubles in precursor run (Yuanfu Trouble, Jack, Michiko, Daryl) 15min 6 Progress in simulation of observation (Input from Tong, and Ron Errico, Stoffellen ) 15 min 7. Schedule Next meeting (Avoid Spring break)

Good hurricanes and storms in T799 run even for meso scale OSSEs. Before producing regional NR, it is highly recommended to perform regional OSSEs (40-60km resolution) with T799 global NR. Mesoscale NR must be another Joint OSSE NR which will be shared within Joint OSSE Regional OSSEs are affordable to Universities. Simulation of observations may be difficult. Regional OSSE must present evaluation of effect of lateral boundary conditions. Integrations of meso/regional OSSE effort into Joint OSSEs Note: There are global meso-scale model (NICAM, GFDL, ESRL) and relatively low resolution regional OSSEs are considered.

Potential candidate for the next NR NICAM Nonhydrostatic icosahedral atmospheric model Global cloud resolving model km model integrations are done for one week (stop due to computing resource) 7 and14km model integrated for days 40 levels Forecast skill is yet to be proved Only seven day integration was performed

Requirement for the meso scale (can be global) Nature run - sample suggestions- ♦Could be either global or regional. ♦The NWP model must have good forecast skill Great visualization does not guarantee good forecast skill. ♦At least 3 month lower resolution run with same model is required to provide a period for spin up for bias correction. ♦Must have a good TC or a severe storm in the nature run period. ♦Sufficient number of vertical levels. Minimum 91 levels. ♦Some degree of coupling with ocean and land surface ♦If it is regional, the effect of the lateral boundary must be evaluated. ♦ A list of verification method must be produced by Joint OSSE. ♦ Need NR to be shared within Joint OSSE ♦ User friendly archive

NASA Portal Contact person is now Harper Pryor ( Maitemance of portal at NASA/GSFC potal was moved from SIVO to NCCS There are several of copies of NR at NASA Portal, Backup in original form Files Reorganized for GMAO users, Oreste’s file system at NCCS 8TB od disk space will be allocated. 7TB for nature run in grib code. There are some data with binary format. Better support software will be provided. Down load of multiple files will be available. The data will be reorganized for each time period. Any comments to be made how to organize data. What we need.

NASA portal maintenance was moved from SIVO to NCCS Data Portal NCCS = NASA Center for Computation Sciences The NCCS is managed by CISTO CISTO = Computational and Information Sciences and Technology Office Contact person Harper Pryor Harper Pryor is the Programs Development Manager for CISTO and the SMD User Advocate to the NCCS Alindo is working on reorganizing the data. Verification data was delivered to NRL/Monterey Verification data: 1x1 deg and 0.5x0.5 deg lat lon gridded data in pressure, potential temperature and surface data. Reorganized for each time period and grads control files are created. Links to make the ctl file work are also provided.

Zonal mean RMS Analysis Increment of U1000 Trouble in precursor run

Absolute value of Analysis Increment of U1000

It looks like there is a pretty bad drift in the temperatures over antarctica. I wonder if the drift is the result of a model problem, and that there is no data (i.e. satellite data) to control and correct the problem. Just look at the surface temperatures over this region from the 10th to the 20th, there is a pretty big drift downward. The regions where I see the negative moisture problem develop also correspond to bullseye's in really cold skin temperatures that develop (from the surface flux files). I'm starting to see a pattern develop, but I'm not sure how to fix it. We may need to talk to some of the modelers or Suru (or someone that has run the forecast model in cmip / climate mode). I'll try and dig some more tomorrow. daryl

I have a better suggestion than running with a new time step (or in addition to this). I'm noticing that in the extreme cold regions, that the older version of the lim-q constraint is behaving very poorly, and actually making things worse. There could be some positive feedback developing here. So, i'd suggest just turning off the moisture constraint as a sensitivity test. In the GSI namelist "SETUP", set the following parameters: factqmin=0.0,factqmax=0.0 If you need help setting this up, let me know. All this means is that the model may generate negative and supersaturated moisture points, but the analysis will no longer try to constrain them. daryl

Simulation of GOES-R ABI radiances for OSSE Tong Zhu et al. : 5GOESR P1.31 at AMS annual meeting Simulated from T511 NR. GOES data will be simulated to investigate its data impact

Black lines are total points mean Tb, red lines are the mean Tb over clear sky condition, and the blue lines are the mean Tb over cloudy condition. Clear sky condition is defined as where total cloud coverage (TCC) 0.1

GOES-12 Sounder Simulated Radiances Nature Run simulated GOSE-12 sounder 18 bands In nature Run, there is hurricane generated on September 27. At 1200 UTC October 1, it is located at about 43 W, 20N. The high moisture air mass associated with the hurricane is shown clearly.

Observed vs. simulated GOES-12 sounder for the mean Tb over North Atlantic Ocean region. Black lines are mean Tb from NR simulated, and the red lines are the mean Tb from observation.

Compare with the observed GOES-12 Sounder Observed GOES bands on 0230 UTC October 01, 2005 for North Atlantic Ocean section. Nature Run simulated GOSE-12 sounder 18 bands Observed GOES bands on 0230 UTC October 01, 2005 for North Atlantic Ocean section.

1. Our software development for our first attempt at a GSI DA with all currently used observations is nearly complete. We are still working on some final pieces for the IR radiances and expect it to be working for both AIRS and HIRS by the middle of March. The code has been developed with the hope of also applying it to AMSU with minimal changes, but since we as yet know little about that instrument, we can't say yet what special effort may be required. All the simulated observations have some random error added and the datasets are in bufr format. They are all produced directly from the sigma-level data on the reduced Gaussian grid. 2. The new version of the GMAO GSI adjoint is now working, so all our tuning of the observation simulations will be conducted using that tool, rather than running OSEs. If you want to learn about this tool, Ron gelaro will present a seminar describing its use and validation on Monday Feb 25th at 2:30 at GSFC. 3. In order to save processing time, we are producing radiances for only a thinned set of locations. The thinning is not as drastic as the GSI applies so it still allows the GSI to apply its own data selection algorithm, but to a reduced set. Also, we plan to produce AMSU results only over oceans, since the current version of GSI that we use does not use such obs over land. This makes our task much easier, with both fewer issues to consider and less data to process. Progress in simulation of Observation at GMAO

4. We hope to have tunned results for all observations by this summer, which allows us several iterations of 2-4 week assimilation experiments to conduct before then. These will be for a winter period. The tunning concerns parameters used to specify cloud effects and error statistics. Once we have the tunned results, we will make available the bufr datasets we have and the software we used to produce them. We will also then begin to complete the full year of simulated observations. 5. Runhua is currently busy with some other projects, but will return to the OSSE work shortly. I have other things I am supposed to be doing now, but have instead been working on the OSSE code development, augmenting what Runhua has done. Some components took us a long time to develop; if someone who understood some critical pieces that we had to get from elsewhere, we could have saved 6 weeks at least. None-the-less, I like what we have thus far. It seems easy to both use and modify, being in the form of modules independent of the massive GSI code. 6. After this first set of tunned simulated obs are produced (this summer) I will work on further improvement of the realism of the observations.

Ad Stoffelen 2/20/2008 There is no connection between the EE format discussed by Tan et al and the LIPAS BUFR. We are currently not in a position to provide you with Aeolus data as you will get them in NRT, but we will be able closer to the launch. In principle we could deliver:- L1B data and a L2B processor, standalone and portable source code- L2B data (LOS wind profiles, optically classified)The L2B processor needs NRT T meteo input with accuracy better than 10K.T sensitivities and references are delivered in the L2B data, so any Met centre may correct for his own best T, but there appears not much reason to do so (all are better than 10K). The T (and less p) sensitivity is important for the width of the molecular Rayleigh distribution, which is used in the processing.Both datasets may be delivered in ESA EE format and BUFR. The former is about ten times the size of BUFR. What would you require in terms of format and timeliness?Please ask for further clarification if need be. More details are available.Cheers,Ad

Expanding interest and collaboration Michiko start note on help record. Any small help provided to be recorded so help will be acknowledged appropriately. Michiko, Yuanfu, Yucheng and Tong will form a help line to answer basic questions and direct to right people, and build knowledge base for OSSE.