Gridded precipitation datasets are increasingly used as operational tools, with growing emphasis on cloud-native processing to handle multi-decadal archives through reproducible and auditable workflows. This paper presents an end-to-end pipeline that uses Google Earth Engine for the automated extraction of ERA5-Land precipitation, enabling on-the-fly analysis and targeted spatiotemporal data retrieval. The extracted outputs are subsequently evaluated through station-based comparisons using one linear and one non-linear biascorrection technique. The workflow emphasizes scalable data access, consistent station alignment, and distribution-aware diagnostics for extremes. It is designed to support rapid national screening and to provide a transferable blueprint for hydrometeorological applications.
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