When radar and hourly gauges are scarce: Sharpening gridded precipitation estimates using daily observations

Long-term hourly precipitation data are critical for many applications. However, in many regions, particularly during earlier historical periods, limited hourly observations have prevented the development of reliable hourly gridded products. In contrast, daily observations are often more readily available. In this study, we introduce and evaluate a framework for incorporating daily gauge observations for hourly precipitation estimates under data-limited conditions. The framework integrates four data sources: satellite data, radar data, hourly gauge data and hourly disaggregated gauge data. The satellite data provide the background field. The other three data sources provide source-specific local corrections to the background field at each target location. The last source, the hourly disaggregated gauge data, is derived from daily gauge observations using temporal patterns from a second satellite product. Error characteristics are quantified separately for each data source and used to determine their respective contributions. In particular, the hourly disaggregated gauge data are estimated to possess much larger errors than the direct hourly gauge observations and are therefore treated differently. The framework is evaluated under two national-scale scenarios: a recent high-coverage network (radar covering 72.1% of Australia along with 2390 hourly gauges) and an early-period low-coverage network (radar covering 11.2% of Australia along with 151 hly gauges). Results show improved hourly estimates, particularly in regions without radar coverage, where 70–80% and 85–95% of independently evaluated gauge locations show improvements at the hourly and daily scales, respectively. These results demonstrate that daily gauge observations can effectively sharpen high-resolution hourly gridded precipitation estimates in regions and historical periods with sparse radar and hourly gauge coverage.