First results and future directions of the Global Microwave Data Collection Initiative (GMDI) to scale up the usage of commercial microwave link data for rainfall observation

Accurate quantitative precipitation estimation (QPE) remains a critical challenge in many data-scarce regions, particularly across low- and middle-income countries. Recent research in Sri Lanka, Burkina Faso, Zambia, Nigeria, Ghana and Cameroon has demonstrated that Commercial Microwave Links (CMLs) can bridge this gap, providing rainfall data with high temporal resolutions (1–15 minutes) that can outperform satellite products like IMERG in both accuracy and spatial detail, especially in densely populated urban areas where CML density is high.While the technical feasibility of CML-based rainfall observation is well-established, its widespread implementation is often hindered by legal, business, and organizational barriers. To address these issues, the SetGMDI project, a strategic outcome of the COST Action OpenSense, is working on setting up the Global Microwave Data Collection Initiative (GMDI). The SetGMDI consortium, comprising mobile network operators (MNOs), hardware vendors, national meteorological and hydrological services (NMHSs), and academia, is building a sustainable, scalable solution for global collection of CML data for rainfall monitoring. In this contribution, we present results from the first pilot studies utilizing a prototype of the technological core system of GMDI: The Data Collection, Archiving, and Processing (CAP) system. The CAP system enables real-time data flows and interactively explores large data archives of CML data combined with meteorological datasets. Furthermore, we discuss the legal and organizational framework necessary to formalize long-term data-sharing agreements with MNOs, balancing commercial sensitivity with the public good resulting from improved precipitation observations.The CAP system creates vital synergies by providing NMHSs with access to high-resolution data for hydrometeorological applications, while MNOs and vendors benefit from meteorological insights to optimize network management. By addressing both organizational and technical barriers, GMDI will significantly increase the global availability of CML data, improving rainfall observations in particular in the Global South. This will also pave the way for integrating satellite and CML rainfall estimates, ultimately strengthening flood early warning systems, water management, and climate adaptation strategies worldwide.