1. Blending of Radar, Satellite and Gauge Rainfall data for Hydrological Applications.
- Author
-
Pudashine, Jayaram and Velasco-Forero, Carlos
- Subjects
RADAR ,RAINFALL ,HYDROLOGY ,FLOOD risk ,WATER supply - Abstract
The Bureau currently generates various rainfall products, reporting observed precipitation data at diverse spatial scales, accumulated over different time frames, and provided in several formats. These products are derived from various instruments, including rain gauges, radars, and satellites. Each instrument offers unique benefits and has specific limitations. Recognising this, there is a need to blend these data into a single product that caters to an array of hydrological applications. This presentation will focus on our innovative methodology for blending rainfall data. This approach amalgamates Rainfields data, which is a quality-controlled radar product collated from weather radar across Australia, with Himawari satellite data and observations from rain gauges. Our analysis draws upon components of the Short-Term Ensemble Prediction System (STEPS). This system employs a multiplicative cascade model of rainfall and merges multiple data sources at various cascade levels. The weights assigned in this blending process are determined based on the mutual correlation of the data at each cascade level. To address the inherent uncertainties of each data source, we have incorporated spatial error properties into our methodology. For the rain gauge data, we use Kriging covariance. In the case of radar data, we factor in an error field that takes into account both topography and distance from the radar location. For satellite data, we utilise the residual error from the bias-corrected satellite data to detect and accommodate error properties. At present, our blending methodology has been applied and tested in regions of 1024x1024 km around Brisbane, Sydney, and Melbourne. Looking forward, we plan to extend this methodology to a continental scale, enabling us to provide data updates at hourly intervals. This comprehensive and timely data will prove invaluable for a wide range of hydrological applications. [ABSTRACT FROM AUTHOR]
- Published
- 2023