Week 1- Overview: Climate and its variability in WAS, Scientific Fundation for Seasonal Forecasts, WASS2S Approaches.
Timeline
| Time | Monday | Tuesday | Wednesday | Thursday | Friday |
|---|---|---|---|---|---|
| 08:30 - 10:00 | Opening and Presentation of Participants | Overview of Data Structures in Python and the Libraries NumPy and Xarray (K. Arsène & al.) | Overview of Data Structures in Python and the Libraries NumPy and Xarray (K. Arsène & al.) | Access Dynamical Model data for Seasonal Forecasting (H. Mandela) | Observational Datasets and Their Improvements (H. Mandela & al.) |
| Break | |||||
| 10:30 - 12:30 | Climate and its Variability in West Africa and the Sahel (H. Mandela) | Overview of Data Structures in Python and the Libraries NumPy and Xarray (K. Arsène & al.) | Overview of Data Structures in Python and the Libraries NumPy and Xarray (K. Arsène & al.) | Access Dynamical Model data for Seasonal Forecasting (H. Mandela & al.) | Validation of Dynamical seasonal forecasts (H. Mandela) |
| Break | |||||
| 14:00 - 17:30 | Seasonal Forecasts: Scientific foundations, Approaches, … (H. Mandela) → Next Generation of Seasonal Forecasting in West Africa and The Sahel (H. Mandela) | Overview of Data Structures in Python and the Libraries NumPy and Xarray (K. Arsène & al.) | Debrief with Participants (K. Arsène & al.) | Observational Datasets and Their Improvements (H. Mandela) | Validation of Dynamical seasonal forecasts (H. Mandela & al.) |
The green highlight indicates time allocated for Participant Exercises.