HS4.3/AS1.3/NH1.3Ensemble hydro-meteorological forecasting (co-organized)
|Conveners: Sara Liguori , Maria-Helena Ramos | Co-Conveners: Florian Pappenberger , Schalk Jan van Andel , Giovanni Battista Chirico|
Expected benefits of ensemble hydrological predictions comprise higher forecasting skills, improved risk assessment and well-informed decision-making in operational water management. Ensemble hydro-meteorological forecast and warning systems have been developed to improve flood control and drought management, as well as to optimize water allocation and regulation for different uses. The value of such systems has been recognized across a wide range of sectors and users, including river basin authorities, public agencies, private entities and commercial industries.
The growing use of ensemble and probabilistic products has shown the importance of implementing integrated approaches across different scales (from local to climate scales) and also along the disaster cycle: from prevention (decadal predictions), over preparedness (seasonal, monthly, medium- and short-range forecasting), up to crisis management (nowcasting and operations during critical events). Seamless systems are expected to be able to appropriately bridge space-time scales, to handle different models and different sources of uncertainties, as well as to provide a suitable framework to develop training and communication pathways useful for several functionalities.
This session aims to bring together scientists and practitioners from the fields of hydrology, hydrosystems engineering, agriculture, meteorology and social sciences, as well as stakeholders and decision-makers, interested in exploring the use of ensemble forecast techniques in hydrological forecasting, reservoir operation, irrigation scheduling, crop modelling for agricultural management and other water management regulations.
Contributions will cover, but are not restricted to, the following topics:
- Data requirements and data assimilation techniques to improve the skill of hydro-meteorological ensemble forecasting systems;
- Methods to correct forecast biases (pre- and post-processing) and to assess or benchmark the performance of ensemble forecasts;
- Methods and products for probabilistic forecasting across scales and applications;
- Case studies dealing with different space-time scales, forecast ranges, hydrological and climatic regimes;
- Methods and products for improving human interpretation of forecasts (forecaster expertise);
- Approaches for efficient training and communication of forecasts.
Practical applications showing successful experiences, as well as problems and failures encountered in the use of uncertain forecasts in risk-based decisions are welcome.