The MASTER Super Model Ensemble System (MSMES)

Motivated by the SALLJEX Intercomparison Program in 2003 and the THORPEX goals to improve predictability through the proper combination of numerical weather forecasts produced by a large set of models, we have explored the potential predictability associated with the numerical products available in S. America. There are several models outputs currently available of regular basis in S. Approximately 40 models outputs are available on a daily basis. It is concludes that the simple procedure based on data assimilation principles was quite successful and the results are routinely available at public access homepages. Future implementations are based on the optimal choice of the averaging period for computing bias and MSE are based on Kalman Filters and Neural Networks. This experience has been quite successful not only in terms of providing a realistic statistical estimate of the optimal forecast up to 7 days but also in terms of the exchange of experience among participating groups. Addition of forecasts produced by other centres is also encouraged. Surface based variables at the highest resolution possible and frequent time intervals (at least 3hr) are required to improve the optimal statistical forecast. The system can be extended to other surface based measurements such as radiation.