А workshop on «Predictability, dynamics and applications research using the TIGGE and S2S ensembles» , ECMWF, 2-5 April 2019

A workshop on «Predictability, dynamics and applications research using the TIGGE and S2S ensembles» will be held at ECMWF on 2-5 April 2019.

Workshop link:

TIGGE (The International Grand Global Ensemble) is a dataset, established by the World Weather Research Programme in 2006, comprised of operational global ensemble forecast data
from ten weather forecasting centres. TIGGE is designed to span the medium-range (out to day 15), but a similar multi-model ensemble, the S2S dataset, has been created with
contributions from 11 centres to extend across the sub-seasonal to seasonal range (up to day 60).

Both TIGGE and S2S data are archived at ECMWF and CMA providing a unique resource for predictability and dynamical processes research. TIGGE has already proved invaluable for the development of products for future operational forecasting. Examples include the forecasting of tropical cyclone tracks, heavy rainfall, strong winds, and flood prediction through coupling hydrological models to ensembles. TIGGE has added to our understanding of the dynamics of tropical cyclones, extra-tropical cyclones and storm tracks. The S2S database extends the time horizon and also the processes that are important to prediction out to a season, opening new avenues of research.

This workshop will provide an opportunity to review the main scientific advances in predictability, dynamical process studies and applications of ensemble forecasts across the medium and S2S forecast ranges. Examples of sectors rapidly developing in ensemble applications include energy, retail and agriculture, as well as disaster risk mitigation worldwide. The emphasis will be on the utilisation of the TIGGE and S2S databases in research and contributions on seamless prediction, multi-model prediction and ensemble post-processing are particularly welcome. One session will be dedicated to the technical development of ensembles, the TIGGE and S2S data bases and proposals for future development.