RainMerge: a two-stage framework for gauge-independent merging of multiple rainfall products

Gauge-independent, multi-source precipitation data merging is a well-established approach for improving precipitation estimation across regions and scales. However, existing merging techniques often assume precipitation follows a unique, state-independent statistical distribution, overlooking the inherently mixed nature of rain and no-rain occurrence states. This assumption leads to two major limitations: (i) uncertainty in rain/no-rain classification and (ii) biased merging weights, resulting in suboptimal precipitation magnitude estimates. Here we introduce RainMerge, a novel two-stage merging framework designed to address these limitations. In Stage 1 (Binary Merging), we employ the Categorical Triple Collocation Merging (CTC-M) to enhance rain/no-rain detection by optimally combining three input datasets. In Stage 2 (Conditional Merging), we use the binary-merged product to conditionally group samples in time, and merge rain-flagged groups with at least two positive detections using Signal-to-Noise Ratio Optimisation (SNR-opt) to refine precipitation magnitudes. Using gauge observations from diverse hydroclimatic settings, we show that RainMerge improves daily rain/no-rain classification by 25–60 % in False Alarm Ratio (FAR) and Heidke Skill Score (HSS) relative to the parent products (ERA5, SM2RAIN, and IMERG-final). In terms of overall magnitude error (RMSE), RainMerge reduces the parent-product RMSE by 2–6  mm/day and outperforms the state independent (termed One-stage) framework, by 1.5–2.5  mm/day. Additionally, RainMerge reduces underestimation bias by 2–8  mm/day for extreme precipitation events (75th–99th percentiles) compared to One-stage, demonstrating its superior performance in capturing heavy events. These results highlight the potential of RainMerge for hydrological and climate applications, offering a globally applicable approach to improve detection and magnitude accuracy in multi-source precipitation products.