Summer School: Satellite-Based Hydrological Data Assimilation
Registration is open for the Summer School of “SATELLITE-BASED HYDROLOGICAL DATA ASSIMILATION”, August 25-28, 2026, which will be hosted by the Geodesy Research Group of Aalborg University, Denmark.
The school is free of charge, but a registration process will be followed to select the most relevant audiences.
This Summer School offers early career researchers interested in large-scale hydrology research an opportunity to engage in dedicated lectures and practical sessions. The focus will be on advanced techniques for measuring and modeling the water cycle, as well as integrating Satellite Gravity, Satellite Altimetry, and Soil Remote Sensing into large-scale hydrological models. Participants will be introduced to ensemble-based sequential Data Assimilation (DA) techniques for merging satellite data with models. The school emphasizes hands-on learning, featuring practical exercises in Python, along with various interactive activities. The school emphasizes hands-on learning, featuring practical exercises in Python, along with various interactive activities.
Modellers, DA and satellite Earth observation experts will join as lecturers and instructors:
Maike Schumacher (AAU, Denmark), Cecile Kittel (DHI, Denmark), Henrik Madsen (DHI, Denmark), Radoslaw Guzinski (DHI, Denmark), Guillaume Ramillien (CNRS, France), Augusto Getirana (NASA; US), Zdenko Heyvaert (ECMWF, UK), Mohammad Shamsudduha (UCL, UK), Anke Fluhrer (DLR, Germany), Jürgen Kusche (University of Bonn, Germany)
AAU: Leire Retegui-Schiettekatte, Fan Yang, Shima Azimi, Çağatay Çakan, Supriya Tiwari, Manu K Soman, Ehsan Forootan
The school is supported by the Independent Research Fund Denmark through “DFF2 – DANSk-LSM, https://vbn.aau.dk/da/projects/developing-efficient-multi-sensor-data-assimilation-frameworks-fo/” and Villum Fonden through “A Novel Synergy of Physics-based and Data-driven Methods for Reliable Hydrological Predictions under Changing Climate, https://villumfonden.dk/en/projekt/novel-synergy-physics-based-and-data-driven-methods-reliable-hydrological-predictions-under“.
Author: Ehsan Forootan (GGOS Science Panel)
