- 1Ghent University, Ghent, Belgium (oscar.baezvillanueva@ugent.be)
- 2Laboratory of Catchment Hydrology and Geomorphology, School of Architecture, Civil and Environmental Engineering, EPFL Valais Wallis, Sion, Switzerland
- 3Remote Sensing Centre for Earth System Research, Institute of Geophysics and Geology, Leipzig University, Leipzig, Germany
- 4Image and Signal Processing Group, Institute of Computer Science, Leipzig University, Leipzig, Germany
- 5Helmholtz Centre for Environmental Research (UFZ), Leipzig, Germany
Terrestrial evaporation (E) is a critical climate variable that links the water, carbon, and energy cycles. It plays a vital role in regulating precipitation, temperature, and extreme events such as droughts, floods, and heatwaves. In hydrology, E represents a net loss of water resources, while in agriculture, it determines irrigation demands. Despite its significance, global E estimates remain uncertain due to the scarcity of ground-based measurements, the complexity of physiological and atmospheric interactions, and challenges in capturing E through satellite observations. Addressing these limitations, the fourth generation of the Global Land Evaporation Amsterdam Model (GLEAM4¹) enhances the representation of E and its components by improving the representation of key processes such as interception loss, atmospheric water demand, soil moisture dynamics, and plant groundwater access. Using a hybrid framework that combines machine learning for evaporative stress estimation with physical principles, GLEAM4 balances interpretability with adaptability and validation against hundreds of eddy-covariance sites demonstrates its robustness and improved performance.
Building on GLEAM4, efforts are underway to develop a high-resolution (1 km) E dataset tailored to the needs of agriculture, water management, and climate adaptation. GLEAM-HR downscales precipitation from MSWEPv2.8 and radiative forcing data by optimally merging LSA SAF and MODIS. The innovations introduced in GLEAM-HR address fine-scale E dynamics, particularly in agricultural regions, while enabling the characterization of droughts, heatwaves, and water resource distribution in vulnerable areas. Preliminary results from GLEAM-HR over the Meteosat disk (covering Europe and Africa) highlight its potential to tackle water-related challenges, support sustainable water management practices, and contribute to evidence-based decision-making. In the future, the data products will be available publicly through an interactive 3D data cube application.
¹Miralles, D.G., Bonte, O., Koppa, A., Baez-Villanueva, O.M., Tronquo, E., Zhong, F., Beck, H., Hulsman, P., Dorigo, W., Verhoest, N.E. and Haghdoost, S. GLEAM4: global land evaporation dataset at 0.1° resolution from 1980 to near present, 20 November 2024, PREPRINT (Version 1) available at Research Square (https://doi.org/10.21203/rs.3.rs-5488631/v1)
How to cite: Baez-Villanueva, O. M., G. Miralles, D., Bonte, O., Koppa, A., Massant, J., Ruan, F., Söchting, M., and Mahecha, M.: Towards high resolution evaporation data integrating satellite observations and hybrid modelling over Europe and Africa, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16431, https://doi.org/10.5194/egusphere-egu25-16431, 2025.