China’s Cloud-Based Global Meteorological Early Warning System: Development and Applications

Addressing the critical global challenge of bridging the early warning capability gap, particularly for developing and least developed countries, this paper presents the Cloud-Based Global Meteorological Early Warning System (CEWS) developed by the China Meteorological Administration (CMA). Beyond a technical system, CEWS embodies a novel operational paradigm that overcomes persistent barriers to effective early warning operations in resource-constrained settings. Its lightweight, cloud-based architecture ensures universal accessibility by consolidating multi-source observations, global numerical weather prediction (NWP) models, and artificial intelligence (AI) forecasts into a unified web environment. This has reduced page response times in Africa and the Arab region from half a minute to just a few seconds. Unlike platforms offering single-model outputs or basic visualization, CEWS provides comprehensive multi-model diagnostic analysis that integrates both physics-based and AI-driven forecasts, and delivers objective early warning products. Verification against 2025 global data demonstrates that these products achieve threat score improvements of 44%, 50%, and 36% for heavy rainfall (24-h accumulated precipitation ≥ 50 mm) at 24, 48, and 72-h lead times, respectively, and a 44% reduction in the root-mean-square error for 24-h daily maximum temperature forecasts (24-h lead time), compared to the raw ECMWF_IFS baseline. Operational efficiency gains include a 136% increase in warning product volume since deployment. Furthermore, the platform’s collaborative co-development model enables partner countries to co-create tailored early warning solutions, balancing out-of-the-box usability with in-depth, application-specific customization. Since its deployment, CEWS has been used in more than 40 countries and contributed to WMO pilot projects and coordination mechanisms. This work demonstrates a scalable and scientifically robust pathway to broaden access to advanced forecasting capabilities, directly contributing to the United Nations’ “Early Warnings for All” (EW4All) initiative and strengthening global climate resilience.