H161-08
ULYSSES: a global multi-model high-resolution hydrological seasonal predictions system
Tuesday, 15 December 2020: 04:28
Virtual
Luis Samaniego1, Stephan Thober2, Matthias Kelbling2, Robert Schweppe3, Oldrich Rakovec2, Gwyn Rees4, Eleanor Blyth4, Katie A. Smith4, Matt Fry4, Alberto Martinez-de la Torre4, Marc FP Bierkens5, Niko Wanders6, Edwin Sutanudjaja7 and Ludovicus P Van Beek6, (1)Helmholtz Centre for Environmental Research UFZ Leipzig, Leipzig, Germany, (2)Helmholtz Centre for Environmental Research - UFZ, Computational Hydrosystems, Leipzig, Germany, (3)Helmholtz Centre for Environmental Research UFZ Leipzig, Computational Hydrosystems, Leipzig, Germany, (4)UK Centre for Ecology and Hydrology, Wallingford, United Kingdom, (5)Deltares, Unit Subsurface and Groundwater Systems, Utrecht, Netherlands, (6)Utrecht University, Department of Physical Geography, Utrecht, Netherlands, (7)Utrecht University, Physical Geography, Utrecht, Netherlands
Abstract:
The Copernicus Climate Change Service aims at facilitating the emergence of a downstream market of climate services with the ultimate goal of supporting the development of a climate-smart society. Central to this vision is the free and unrestricted distribution of high-quality climate data through the Climate Data Store [1], with seasonal meteorological predictions among them. Within this unique and challenging framework, ULYSSES [2] will provide the first "seamless" multi-model hydrological seasonal prediction system, with a global coverage at a spatial resolution of 0.1º. The ULYSSES modeling chain is based on the successfully tested EDgE proof of concept [3] using four state-of-the-art hydrological models (Jules, HTESSEL, mHM, PCR-GLOBWB). A unique feature of this production chain consists of using the same land surface datasets (e.g. DEM, soil properties) with identical spatio-temporal resolutions and forecast inputs for all HMs, and the same river routing scheme (i.e., the multi-scale routing model mRM).
The initial conditions of the production chain will be based on ERA5-Land dataset and the seasonal forecasts will be driven by a 51-member ensemble generated by the ECMWF-SEAS5 model. ULYSSES aims at generating six essential hydrological variables: snow-water equivalent, snowmelt, evapotranspiration, soil moisture, total runoff, and streamflow with a lead-time of up to six months. The seasonal forecast will be verified at 250+ gauges distributred in all continents during the hind-casting period from 1993 to 2019. The operational forecasting period −in testing phase− will start in November 2020 and be extended through to July 2021. The first operational ULYSSES forecast will be made available by the 10th of each month starting in Nov. 2020.
All input data sets (ERA5-Land), seasonal forecasts (SEAS5) and ULYSSES outputs will be made available in the Copernicus Climate Data Store [1] and will be open access. We aim to engage institutions and researchers around the world that are willing to evaluate the forecasts model performance, with the aim of improving the system in the future. In this talk, the modelling chain concept, model setup and verification of initial results will be presented.
- https://cds.climate.copernicus.eu
- https://www.ufz.de/ulysses
- https://doi.org/10.1175/BAMS-D-17-0274.1
