EGU General Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Presentation of a high-resolution present-day joint atmosphere-land surface-hydrology simulation dataset for South Africa

Zhenyu Zhang1,2, Patrick Laux1,2, Joel Arnault1, Jussi Baade3, Marcel Urban4, Christiane Schmullius4, and Harald Kunstmann1,2
Zhenyu Zhang et al.
  • 1Institute of Geography, University of Augsburg, Augsburg, Germany (
  • 2Karlsruhe Institute of Technology, Institute of Meteorology and Climate Research (IMK-IFU), Garmisch-Partenkirchen, Germany
  • 3Department for Physical Geography, Friedrich-Schiller-University, Jena, Germany
  • 4Department for Earth Observation, Friedrich-Schiller-University, Jena, Germany

Due to the high variability of climate variables under climate change, the assessment of the climate impacts on water management, ecosystems restoration, as well as climate change adaptation requires very detailed climate information regionally and ideally at a local scale. State-of-the-art coupled land-atmosphere numerical models incorporate the water and energy exchange processes in the soil–vegetation–atmosphere continuum in a physically consistent way, thereby their simulations capture the complete evolution of state variables and provide the complex linkages across compartmental boundaries in the Earth system. As an effort to contribute to climate- and water-related research in South Africa, we present a high spatial and temporal resolution climatological atmosphere–land surface–hydrology analysis dataset covering the period 2000-2020. This analysis dataset is dynamically downscaled from ERA5 reanalysis using the Weather Research and Forecasting Model Hydrological modeling system (WRF-Hydro). This dataset covers the territory of South Africa with a grid resolution of 4 km and a time interval of 1 hour.

As a result, a comprehensive analysis dataset is provided, including the land surface and atmosphere state conditions, as well as the water flux components for the joint atmospheric-terrestrial water balance. The model performance is evaluated based on in-situ measurement records and remote sensing results. For instance, we evaluate the soil moisture and soil temperature using continuous in-situ measurement over six South Africa locations following a climate gradient, and the spatiotemporal trends of soil moisture are further evaluated using a newly developed radar-retrieved Surface Moisture Index (SurfMI). Biases of simulation results have been identified that should be taken into account in any application.

How to cite: Zhang, Z., Laux, P., Arnault, J., Baade, J., Urban, M., Schmullius, C., and Kunstmann, H.: Presentation of a high-resolution present-day joint atmosphere-land surface-hydrology simulation dataset for South Africa, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-10349,, 2022.