1 / 17

Sub-seasonal to Seasonal Prediction (1-90 days) - A Seamless Approach

Sub-seasonal to Seasonal Prediction (1-90 days) - A Seamless Approach. Gilbert Brunet WWRP/JSC Chair Environment Canada. Workshop “Sub-seasonal to Seasonal Prediction” UK Met Office, Exeter 1-3 December 2010. An Earth-System Prediction Initiative.

Download Presentation

Sub-seasonal to Seasonal Prediction (1-90 days) - A Seamless Approach

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Sub-seasonal to Seasonal Prediction (1-90 days) - A Seamless Approach Gilbert Brunet WWRP/JSC Chair Environment Canada Workshop “Sub-seasonal to Seasonal Prediction” UK Met Office, Exeter 1-3 December 2010

  2. An Earth-SystemPrediction Initiative • An Earth-System Prediction Initiative for the Twenty-First Century (Shapiro et al.) • Addressing the Complexity of the Earth System (Nobre et al.) • Toward a New Generation of World Climate Research and Computing Facilities (Shukla et al.) • Collaboration of the Weather and Climate Communities to Advance Subseasonal-to-Seasonal Prediction (G. Brunet, M. Shapiro, B. Hoskins, Mitch Moncrieff, Randal Dole, G. Kiladis, B. Kirtman, A. Lorenc, R. Morss, S. Polavarapu, D. Rogers, J. Schaake and J. Shukla

  3. Centres participating in the WMO Long Range Forecast Verification Systemhttp://www.bom.gov.au/wmo/lrfvs/index.html • WMO Commission for Basic System prediction time range definitions • MEDIUM-RANGE WEATHER FORECASTING: • BEYOND 72 HOURS AND UP TO 240 HOURS DESCRIPTION OF WEATHER PARAMETERS • EXTENDED-RANGE WEATHER FORECASTING: • BEYOND 10 DAYS AND UP TO 30 DAYS DESCRIPTION OF WEATHER PARAMETERS, USUALLY AVERAGED AND EXPRESSED AS A DEPARTURE FROM CLIMATE VALUES FOR THAT PERIOD. • LONG-RANGE FORECASTING: • FROM 30 DAYS UP TO TWO YEARS • CLIMATE FORECASTING: • BEYOND TWO YEARS

  4. A predictability and dynamical processes perspective of the low frequency variability • Time scale (e.g. natural frequency) of the Wave Activity Variability on the NH 315K isentropic surface - Cumulative principal component variance. - Discrete modes have finite contributions spanning the intraseasonal variability and the continuous modes project on the baroclinic wave activity, Brunet (1994, JAS) Continuous spectrum (80%) Discrete spectrum (dim. ~ 12, 20%) • The low frequency variability (AO, PNA, Atlantic blockings, …) controls significantly the distribution of high-impact weather (like the Atlantic storm track and equatorial westerly duct)

  5. Predicting the Low Frequency Variability Medium-range forecasting the 500hPa height with the ECMWF deterministic prediction system Extended-range forecasting of the NAO with the Canadian GEM Monthly ensemble prediction System

  6. Collaboration of the Weather and Climate Communities to Advance Subseasonal-to-Seasonal Prediction: Research Issues • The multi-scale organisation of tropical convection and its two-way interaction with the global circulation (Session 3 and 5) • Data assimilation for coupled models as a prediction and validation tool for weather and climate research (Session 4) • Seamless weather/climate prediction with Multi-model Ensemble Prediction Systems (MEPSs) (Session 4 and 5) • Utilization of sub-seasonal predictions for social and economic benefits (Session 1 and Session 6)

  7. The multi-scale organisation of tropical convection and its two-way interaction with the global circulation • Collaborative effort through YOTC; • 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.

  8. The multi-scale organisation of tropical convection and its two-way interaction with the global circulation: MJO and NAO (Session 3: H. Lin presented by F. Vitart) The NAO The MJO Lin, H., G. Brunet, and J. Derome, 2009: An observed connection between the North Atlantic Oscillation and the Madden-Julian Oscillation. J. Climate, 22, 364-380.

  9. Extended-range forecasting of the NAO with the Canadian GEM Monthly ensemble prediction System • Impact of the North Atlantic Oscillation on the forecast skill • of the Madden-Julian Oscillation(Hai Lin and Gilbert Brunet, submitted to GRL)

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

  11. 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

  12. 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 and WGNE Transpose-AMIP. 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.

  13. Seamless weather/climate prediction with Ensemble Prediction Systems(EPSs) • Terms of reference for collaboration between WCRP CLIVAR Climate-system Historical Forecast Project (CHFP) and the THORPEX Interactive Grand Global Ensemble (TIGGE) must be establish for experimentation and data sharing for sub-seasonal to seasonal historical forecasts ( weeks to season) including the required infrastructure. • 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. • Development and use of ensemble based modeling methods in order to improve probabilistic estimates of the likelihood of high-impact events.

  14. 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

  15. 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.

  16. A seamless approach to weather and seasonal prediction. • Need for a collaborative effort with physical and social science researchers, service providers and users. • The initiative should be focussed on: • Coupled global modelling • Coupled data assimilation • MJO and organised tropical convection • Polar processes • Surface-atmosphere interactions • Stratosphere-troposphere interactions • Ensemble prediction systems (EPS) • Data bases for research • Forecasting system design • Societal and economic benefits from improved sub-seasonal to seasonal prediction

More Related