1. 3 rd THORPEX DAOS Working Group meeting Objective * Review the issue of adaptive observations * Results from T-PARC (winter phase and TCS-08) * Update on other campaigns and activities * Review paper on the value of targeted data to be published in peer-review literature (BAMS) –Presentations available at * http://web.sca.uqam.ca/~wgne/DAOS/DAOS3_meeting/

2. DAOS-WG recommendations for Targeted Observing Field Programs 1.Impact of targeted observations from previous field programs (esp. WSRP, ATreC-2003TPARC) * Expensive observation campaigns should not be justified based only on previous methods of targeting * Rabier et al. (2008) 2.Carefully consider data assimilation issues (impacts of small vs. large sets of observations, frequency of special observations, etc. ) 3.Develop and test new adaptive strategies * Adaptive selection and assimilation of satellite observations (less than 10% of available data currently used)

3. Observability of a structure function (Lupu and Gauthier, 2010) Correlation between the innovations and a structure function v This defines the observability of a structure functions * Can the observations detect a given structure function?

4. Observability of different structure functions based on key analyses Structure functions Obs. type , correlation coefficient January 27, 2003 January 06, 2003 February 06, 2002 January 19, 2002 GLOBAL RAOB 0.010.020.03-0.01 AIREP 0.000.02-0.01 ATOVS 0.130.110.070.12 TOTAL 0.05 0.03 LOCAL RAOB -0.010 -0.02 AIREP -0.03-0.01-0.03 ATOVS 0.050.010.060.02 TOTAL 000-0.01 HEMISPHERIC RAOB 0.000.020.01 AIREP -0.050.02-0.02-0.03 ATOVS 0.080.07 0.04 TOTAL 0.030.04 0.02 PV-BAL RAOB 0.010 0 AIREP -0.030.01-0.030 ATOVS 0.090.08 0.05 TOTAL 0.03-0.010.060.02

5. The intercomparison experiment on the impact of observations  A goal of THORPEX is to improve our understanding of the ‘value’ of observations provided by the current global network  In 2007, DAOS-WG proposed a comparison of observation impacts in several forecast systems, facilitated by the emergence of new (adjoint-based) techniques  Experiments for a baseline observation set were designed by DAOS members from NRL, GMAO, EC, ECMWF, Météo-France …so far, results obtained for 3 systems: NRL, EC, GMAO optimize the use of current observations inform the design/deployment of new obs systems

6.  Comparison experiments for NRL, GMAO and EC systems completed (published) for baseline set of observations  Despite differences in DA algorithms, RTMs and data handling, overall quantitative results similar for all systems  Largest overall impact provided by AMSU-A, but also raobs, satwinds and aircraft  Details of impact differ between forecast systems: impacts per-ob, -channel, -region  Only a small majority of assimilated observations improve the forecast  Much improvement comes from a large number of observations with small individual impacts Summary of Current Results

7. Exeter May- Bauer et al: Singular vector-based thinning of satellite data 7 Singular vector-based thinning of satellite data Peter Bauer, Roberto Buizza, Carla Cardinali and Jean-Noël Thépaut European Centre for Medium-Range Weather Forecasts

8. Exeter May- Bauer et al: Singular vector-based thinning of satellite data 8 This plot shows the density of AMSU-A channel 9 data for the case of 2008/12/14@00UTC for the different experiments:  EXP-HI: global thinning to 0.625 o  EXP: global thinning to 1.25 o (i.e. ope)  EXP-SV: EXP but with SV thinning 0.625 o  EXP-CLI:EXP but with SVcli thinning 0.625 o  EXP-RND: EXP but with random thinning 0.625 o Target areas occupy same fraction (15%) of the Southern hemisphere. The SV-based climatology was derived from the mean 2007 SV-areas Experiments have been run for JAS08 and D08JF09 Forecasts from these experiments have been verified against EXP-HI analyses (~83 cases per season, i.e. without first 7 days to avoid spin-up) 3. Experiments list EXP-HI EXP EXP-SV EXP-CLI EXP-RND

9. Exeter May- Bauer et al: Singular vector-based thinning of satellite data 9  The ECMWF current operational setting (1.25  ) is too conservative and satellite data density could be increased.  0.625  thinning will be considered for operational implementation.  Volume increase can be kept to affordable levels if satellite data density is increased only in a selective way. This study has shown that over the SH, singular vector-based satellite data thinning is a strategy that can lead to better analyses and lower forecast errors. Results are seasonal dependent:  In JAS08 the impact of the extra data is small. DFS indicates that less information was extracted from the obs located in the SV-area than in other regions. Eady index statistics indicate that perturbation grow faster, and this could explain why other sources of forecast errors becomes as important as initial condition.  In D08JF09, all targeting experiments (EXP-SV/CLI/RND) perform better than EXP for a longer period. Of the three targeting experiments, EXP-SV gives the best results, very similar to EXP-HI after 72h. DFS of obs located in SV-areas is larger than the DFS of obs located in other regions. Perturbation growth is slower (Eady index) and initial condition errors are dominant for a longer time period. The day-2 average forecast error reduction of ~4% detected for Z500 over SH is equivalent to a predictability gain of ~1 hour. Conclusions

10. Example of AMVs from MTSAT-2 Rapid Scan images Left: AMV (IR-only) field produced from routinely available hourly sequence of MTSAT-1 images during Typhoon Sinlaku Bottom Left: Same as above, but using a 15-min rapid scan sequence from MTSAT-2 (better AMV coverage and coherence) Bottom Right: Same as above, but using a 4-min rapid scan sequence (improved coverage/detail of typhoon flow fields)

11. 150 hPa Divergence analyzed from upper level R/S AMVs 150 hPa Vorticity analyzed from upper level R/S AMVs TC Diagnostic Studies using High-Res. Rapid- Scan AMVs Example: Typhoon Sinlaku during TPARC

12. 500 hPa analyses in the Mid-Lats during TC Sinlaku Hourly MTSAT AMVs have positive impact, particularly during the period of large NOGAPS track forecast errors (NOAMV exp.) for Sinlaku

13. Results from Winter Storms Reconnaissance Program (WSRP) Summary of main results (Y. Song) * Future plans on the reanalysis of the results obtained from WSRP Discussions as to how to quantify the forecast improvement. * The current system is based on comparisons with radio-sondes within a 1000km radius of the initial target area which changes from one case to another. This can pose problems if there are only few observations in the verification domain. Suggestions * larger fixed domains and using more relevant fields such as total energy norm and/or precipitation * impact of the observations be judged against the general rate of improvements due to advances in assimilation systems etc., increase of the volume of data

14. Review of the impact of targeted data Community paper being written * Lead author is Sharan Majumdar with contributions from the DAOS-WG and scientists involved in targeting campaigns (including Y. Song and Z. Toth) Reconcile seemingly opposing views on the impact of targeted data * Summary of results obtained so far * Identify issues that need to be addressed to improve the use of observations that impact weather forecasts (e.g., metrics, assimilation methods, sampling of precursors to dynamic instability)

15. Conclusion THORPEX data assimilation and observing systems working group has reached a mature stage * Focus on fundamental issues associated with data assimilation to improve forecasts * Links with CBS, satellite agencies and NWP Centres WMO does not have a specific working group on data assimilation * Important for model validation and reanalysis

16. Current status of WGNE Representatives from a number of other expert working groups (e.g, GLASS, GCISS, SPARC) on top of representatives from operational centres Numerous data assimilation issues emerge in different groups * Is there a need to provide a forum to discuss DA issues specifically? * The WMO Data Assimilation Symposium provides an occasion to discuss progress in data assimilation in different areas (oceanography, meteorology, atmospheric chemistry, land surface, analysis for climate, etc…) * Advice to Expert Team on the Global Observing system. Discussions at WGNE were about providing a voice on WGNE to summarize progress, issues and recommendations on DA and observations in support for modeling

17. Historical perspective from Andrew Lorenc WGNE was a pioneer in OSSE studies ( Andrew went to WGNE organised conferences in 1970s!). * The discussions transformed into reports as ET-EGOS CBS-OPAG/IOS Expert Team on the Evolution of global observing systems took over. WGNE was a pioneer in advocating re-analyses, and a major player in organising conferences. I believe that is now "owned" by GCOS. http://reanalyses.org/ WGNE was involved in organising the regular WMO DA Symposia * each seems to actually depend on an ad hoc selection of organizers * It would be good to have a group to "own" this series. WCRP Observations and Assimilation Panel is also interested in reanalysis. SPARC DA organises regular meetings. WGNE is interested in several THORPEX activities, including those of DAOS WWRP Mesoscale DA group

18. Issues to discuss Is there a need for a central structure to coordinate research related to observations and data assimilation? * The THORPEX-DAOS is seen to be the best candidate to take the lead * Representatives from other working groups to link with DAOS (GLASS, SPARC, Mesoscale Data assimilation, …) could attend our meetings * Mandate for the organization of the WMO Symposium on Data assimilation Link between DA and modeling must be preserved * DA is a lot about model validation and it may be more natural to have bodies that foster this linkage (e.g., SPARC-DA) * There may be an interest to have DA specific issues discussed with others (e.g., the DA problems are not always about improving a forecast)

19. Organisational aspects The THORPEX working groups * Discussions on moving them up to the WWRP level once the THORPEX programme is over (already happened with SERA) WGNE is a joint WCRP-WWRP working group and then needs to cover climate modeling and DA issues * Covering all aspects of DA exceeds by far the THORPEX objectives WGNE is considering to have data assimilation as its main theme for 2012 or 2013 * DA at higher resolutions * Reanalyses