Improving Hydrologic Analysis and Applications in the U.S. and Canada Using Quality Controlled Radar Data and the Storm Precipitation Analysis System
Radar data far exceeds the spatial densities of rain gauge networks and has a finer temporal scale (as frequent as 5-minutes), providing precipitation estimation at all ungauged locations. While radar estimated precipitation provides a great improvement in temporal and spatial scales for hydrologic modeling, correction adjustments are required to account for issues such as under/over estimations, radar beam blockage, hail contamination and inaccurate radar-rain rate (Z-R) relationships.
This paper/presentation will demonstrate the effectiveness of combining quality controlled rain gauge data and radar data with the Storm Precipitation Analysis System (SPAS) in the U.S. and Canada, to generate accurate spatial and temporal precipitation, even throughout complex terrain.. SPAS applies innovative algorithms for spatial and temporal radar-aided precipitation analysis, including the hourly derivation and application of dynamic Z-R relationships algorithms. SPAS uses sophisticated techniques to account for biases and inadequate radar coverage through the use of background fields such as climatological data. The gridded precipitation output can aid in reservoir management, hydroelectric power optimization, emergency action plans, reservoir inflow monitoring and hydrologic modeling.