1. WWRP Toward a Seamless Process for the Prediction of Weather and Climate: On the Advancement of Sub-seasonal to Seasonal Prediction TTISS, September 2009, Monterey Gilbert Brunet

2. WWRP Forecasting-system improvement at ECMWF %

3. WWRP Toward A Seamless Process for the Prediction of Weather and Climate  A collaborative effort between the WMO Programs World Weather Research Programme(WWRP)- THORPEX and World Climate Research Programme (WCRP) on the advancement of sub-seasonal to seasonal prediction;  A white paper was prepared by a joint WWRP- THORPEX/WCRP team comprised of: Gilbert Brunet, Melvyn Shapiro, Brian Hoskins, Mitch Moncrieff, Randal Dole, George Kiladis, Ben Kirtman, Andrew Lorenc, Rebecca Morss, Saroja Polavarapu, David Rogers, John Schaake and Jagadish Shukla.

4. WWRP Proposed Joint Research Objectives between WCRP and WWRP  Seamless weather/climate prediction with Multi-model Ensemble Prediction Systems (MEPSs)  The multi-scale organisation of tropical convection and its two-way interaction with the global circulation  Data assimilation for coupled models as a prediction and validation tool for weather and climate research  Utilization of sub-seasonal predictions for social and economic benefits

5. WWRP Seamless weather/climate prediction with Ensemble Prediction Systems(EPSs)  Terms of reference for collaboration between TIGGE and CHFP must be establish for experimentation and data sharing for sub-seasonal to seasonal historical forecasts ( weeks to season) including the required infrastructure.  Development and use of ensemble based modeling methods in order to improve probabilistic estimates of the likelihood of high-impact events.  The requirements for both ensemble prediction methods and greatly increased spatial resolution imply substantial future requirements for computational power and for data storage and delivery capacity.

6. WWRP Composites of Z500 and tropical PR in PHASEs 3 and 7 Z500 Wintertime, NCEP reanalysis, 1979-2003 PR Subseasonal prediction: tropical influence

7. WWRP Subseasonal prediction: the mid-latitude response to MJO  A simplified general circulation model (GCM)  Four hundreds monthly forecast with different initial conditions  Idealized MJO Phase 3 forcing anomaly  Aknowledgements to Hai Lin

8. WWRP Average response Composites based on NCEP reanalysis (GZ500) GZ500 mean anomaly response forecasted with the simplified GCM

9. WWRP GZ500 standard deviation of forecasted anomalies Day 11-15 standard deviation: two first EOFs explain 43%

10. WWRP Regression to wind at 250hP initial conditions shows that strength and latitudinal position of Pacific jetstream will significantly modulate the forecasted response to MJO Phase 3. The tropical interaction with the global mid-latitude circulation is an essential ingredient for successful subseasonal prediction.

11. WWRP The multi-scale organisation of tropical convection and its two- way interaction with the global circulation  Collaborative effort through YOTC and TPARC;  Capability acceleration of the High-Performance Computing (HPC) centers for high-resolution regional and global numerical weather, climate and environmental science activities;  Maintaining existing and implementing planned satellite missions that measure tropical cloud and precipitation systems in order to provide a long-term capability for process studies, data assimilation and prediction in collaboration with GCOS.

12. WWRP Forecasting-system improvement at ECMWF % % Historical trend Updated from Simmons & Hollingsworth (2002) Acknowledgements to A. Simmons Historical re-forecast project trend using re-analyses

13. WWRP North America Z500 RMSE for the control experiments and latest upgrades of the MSC global analysis-forecast system (January and February 2007) Acknowledgements to S. Laroche

14. WWRP Data assimilation for coupled models as a prediction and validation tool for weather and climate research  Promote research towards the development of a composite data assimilation system, applying different assimilation steps to different scales (weather to climate time-scales) and components (atmosphere, land, ocean, atmospheric composition) of the total Earth system model.  Promote the need to test climate models in a deterministic prediction mode, as started within the WCRP SPARC Programme. The seasonal prediction time frame provides a valuable opportunity to do this.  Promote the use of advanced data assimilation methodologies for parameter estimation, both in weather and climate models, through close collaboration with model developers to interpret assimilation results.  Promote interdisciplinary research on data assimilation methods appropriate for the next generation of re-analysis projects aimed at developing historical records for climate studies.

15. WWRP MJO connection to Canadian surface air temperature; high-impact weather? Lagged winter SAT anomaly in Canada Significant warm anomaly in central and eastern Canada 1-2 pentads after MJO phase 3

16. WWRP Utilization of Sub-Seasonal and Seasonal Predictions for Social and Economic Development  A need for closer ties between weather and climate research:  Understanding how information at the weather/climate interface, including uncertainty, connects with decision-making  There is also a great need for much easier access to forecast data by the user community. These need to be available in special user-oriented products. How to achieve this service?  The post-processing techniques that are needed by many users may require an archive of past forecasts (e.g. for water cycle applications). Some user applications require an archive of re-forecasts from fixed models for periods as long as 20 years or more.

17. WWRP Simplified set of public health- related decisions and supporting (e.g. Rift Valley Fever)