| Monday 26 |
Tuesday 27 |
Wednesday 28 |
Thursday 29 |
Friday 30 |
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| 9.00 9.30 |
Registration and Opening | Summary of the day before lectures | Summary of the day before lectures | Summary of the day before lectures | 9.00 10.00 |
Paccagnella The TIGGE-LAM project in the context of the THORPEX Interactive Grand Global Ensemble (TIGGE). |
| 9.30 10.30 |
Kalnay Atmospheric predictability: from basic theory to forecasting practice. |
Hamill Visualization and verification of ensemble forecasts. Methods for forecasters to visualize the information. Common methods of verification. |
Talagrand Advantages and limitations of ensemble predictions. Sampling effects (size of forecast ensembles, size of validating sample). Impact of observational errors. |
Talagrand Data assimilation and targeting in relation to ensemble forecasting. Economic value of ensemble forecasting. |
10.00 11.00 |
Garcia-Moya Multimodel / Multinalysis Ensemble applied to the Mediterranean region. |
| 10.30 11.00 |
Coffee break | Coffee break | Coffee break | Coffee break | 11.00 12.00 |
Marrocu Skill comparison of different calibration methods for a multi-model multi-analysis limited area ensemble. |
| 11.00 12.00 |
Talagrand Why probabilistic weather forecasts: theoretical fundaments of ensemble forecasting. Reminder of basics of the theory of probability and statistics. |
Talagrand Theoretical aspects of objective evaluation of ensemble forecasting. Reliability and resolution. Objective scores for validation: reliability curve, Brier and Brier-like scores and their decomposition, ROC curve area, rank histograms, reduced centred random variable. |
Hamill Severe-weather and extreme-event forecasting: predictability issues. Model errors at the mesoscale and the microscale. Review of severe-weather ensemble forecast experiments at the NOAA Storm Prediction Center. |
Talagrand Intercomparison of different initialization methods. |
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| 12.00 13.30 |
Lunch | |||||
| 12.00 13.00 |
Kalnay Ensemble prediction and strategies for initialization: tangent linear and adjoint models, singular vectors, Lyapunov vectors. |
Kalnay Local Ensemble Transform Kalman Filtering. |
Kalnay Review of the ensemble prediction systems used at NCEP. |
Hamill Multi-model, and superensemble forecasts. Calibration techniques. Review of experiments from TIGGE multi-model ensemble data set. |
13.30 14.30 |
Thielen Application of EPS in flood forecasting. |
| 13.00 14.30 |
Lunch | Lunch | Lunch | Lunch | 14.30 15.00 |
Closing |
| 14.30 15.30 |
Kalnay Bred vectors: theory and applications in operational forecasting. |
Hamill Hydrologic ensemble prediction: sources of predictability. Requirements of ensemble weather forecast prediction systems for driving hydrologic models. Verification of hydrologic forecasts. |
Tutoring and summary preparation | Kalnay Comparison of 4D-Var and Ensemble Kalman Filter methods. |
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| 15.30 15.45 |
Break | Coffee break | Free Time | Break | ||
| 15.45 16.45 |
Talagrand Description of initialization methods for ensemble forecasting: singular modes, bred modes, ‘perturbed observations’, Ensemble Kalman Filter, Ensemble Transform Kalman Filter. |
Hamill Limited-area ensemble forecasting. Scale interactions and effects of boundary conditions. Perturbation methods for the mesoscale. Tradeoff of domain size vs. grid spacing vs. ensemble size. |
Hamill Use of reforecasts in probabilistic ensemble forecast calibration. |
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| 16.45 17.30 |
Tutoring and summary preparation | Tutoring and summary preparation | Tutoring | |||