Coupled atmosphere-hydrological modeling for improved hydro-meteorological prediction
Co-organized as AS4.4/HS4.2.3
Convener: Harald Kunstmann | Co-conveners: Martin Drews, Stefan Kollet, Alfonso Senatore
| Thu, 11 Apr, 16:15–18:00
Room M2
| Attendance Thu, 11 Apr, 14:00–15:45
Hall X3

Prediction skill of hydro-meteorological forecasting systems has remarkably improved in recent decades. Advances in both weather and hydrology models, linked to the availability of more powerful and efficient computational resources, allowed the development of even more complex systems based on the combination of spatially distributed physically-based hydrologic- and hydraulic models with deterministic and/or ensemble meteorological forecasting systems. Coupled atmosphere-hydrological modeling aims at describing the full atmospheric-terrestrial regional water cycle, i.e. extending from the top of the atmosphere, through the boundary layer, via the land surface and subsurface till lateral flow in the groundwater and in the river beds. Fully two-way coupled model systems thereby give the possibility to study long range feedbacks between groundwater, soil moisture redistribution and precipitation. Via improved and completed process descriptions fully coupled modeling may also increase the performance of hydrometeorological predictions of various spatial and temporal scales.
The objective of the session is to create a valuable opportunity for the interdisciplinary exchange of ideas and experiences among atmospheric-hydrological modelers and members of both hydrology- and Earth System modeling communities. Contributions are invited dealing with the complex interactions between surface water, groundwater and regional climate, with a specific focus on those presenting work on the development or application of one-way (both deterministic and ensemble) or fully-coupled hydrometeorological prediction systems for floods/flash-floods, droughts and water resources. Presentations of inter-comparisons between one-way and fully-coupled hydrometeorological chains are encouraged, such as contributions on novel one-way and fully-coupled modeling systems that bridge spatial scales through dynamic regridding or upscaling/downscaling methodologies. Also, presentations addressing data assimilation in coupled model systems are welcome. Likewise abstracts are invited on field experiments and testbeds equipped with complex sensors and measurement systems allowing multi-variable validation of such complex modeling systems.