EGU24-11049, updated on 08 Mar 2024
EGU General Assembly 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

On the predictability of the seasonal droughts at global scale

Luis Samaniego1,2, Ehsan Modiri1, E.H. (Edwin) Sutanudjaja5, Pallav Shrestha1, Alberto Martinez-de la Torre3, Oldrich Rakovec1, Robert Schweppe1, Matthias Kelbling1, Katie Facer-Childs4, Amulya Chevuturi4, Maliko Tanguy4, Niko Wanders5, Rohini Kumar1, and Stephan Thober1
Luis Samaniego et al.
  • 1Helmholtz Centre - UFZ, Department Computational Hydrosystems, Leipzig, Germany (
  • 2Institute of Environmental Science and Geography, University of Potsdam, Potsdam, Germany
  • 3Meteorological Surveillance and Forecasting Group, DT Galicia, Agencia Estatal de Meteorología (AEMET), A Coruña, Spain
  • 4UK Centre for Ecology Hydrology, Wallingford
  • 5Department of Physical Geography, Faculty of Geosciences, Utrecht University, Utrecht, The Netherlands

Long-lasting droughts have become more common worldwide in recent decades, such as in Australia (2001-2009), California (2012-2014), Chile (2010-2023), and Europe (2018-2022). The combination of droughts and heatwaves has led to intense flash droughts, worsening soil moisture deficits. This has resulted in global shortages of essential food, serious public health issues, and prolonged forest fires that harm air quality in populated areas. Extended droughts also contribute to food insecurity, reduced energy production, increased health crises, and the destruction of natural landscapes, causing significant economic setbacks in various regions. International agencies, such as the WMO, and water authorities are actively promoting the advancement of seasonal soil moisture monitoring and forecasting systems. In this presentation, we'll give you an update on ULYSSES [2], the global multi-model hydrological seasonal predictions system supported by the Copernicus Climate Change Service. This fully operational system runs directly at the ECMWF's HPC and aims to be the first seamless multi-model hydrological seasonal prediction system with global coverage at a spatial resolution of 0.1 degrees.

The ULYSSES modeling chain builds on the successful EDgE proof of concept [3], employing four advanced hydrological models (Jules, HTESSEL, mHM, PCR-GLOBWB). Notably, this production chain features a distinctive aspect: the utilization of a standard set of physiographical datasets (e.g., DEM, soil properties) with consistent spatio-temporal resolutions and similar forecast inputs for all hydrological models, as well as the same multi-scale routing model (mRM). The seasonal forecasts are initialized using the ERA5-land product from ECMWF. The Equitable Thread Score (ETS) skill is employed to assess the ensemble forecasting abilities for drought events, specifically when soil moisture exceeds 80% of the time, across lead times ranging from one to three months.

In a recent assessment, the global ensemble Equitable Thread Score (ETS) for the system stands at 63%, 43%, and 34% for lead times ranging from 1 to 3 months. Notably, over Europe, the ensemble ETS is significantly higher, reaching 91%, 71%, and 61% for the corresponding lead times. Contrasting these findings with a prior study that employed the mHM initialized with E-OBS forcing and the NMME ensemble over Europe [4], our analysis suggests potential reasons for the diminished performance of the current system. These factors may include: 1) the meteorological forcings utilized for initializing the hydrological models, and/or 2) the skill level of the NWF model ensemble. In this study, we will present the sensitivity of ETS when one of the models (mHM) is initialized with different available forcings procucts available such as EM-EARTH, MSWEP, WE5E, and E-OBS. Finding of this study is key for the further improvement of the system.


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How to cite: Samaniego, L., Modiri, E., Sutanudjaja, E. H. (., Shrestha, P., Martinez-de la Torre, A., Rakovec, O., Schweppe, R., Kelbling, M., Facer-Childs, K., Chevuturi, A., Tanguy, M., Wanders, N., Kumar, R., and Thober, S.: On the predictability of the seasonal droughts at global scale, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11049,, 2024.